Ricaut François-Xavier

Letellier Thierry

Pradiptajati Kusuma

Murray P Cox

Denis Pierron

Harilanto Razafindrazaka

Nicolas Brucato

Laure Tonasso

Helena Loa Suryadi

Thierry Letellier

Herawati Sudoyo

François-Xavier Ricaut

François-Xavier Ricaut

Alexander Adelaar

François- Xavier Ricaut

Abdul Manan

Chandra Nuraini

Philippe Grangé

François-Xavier Ricaut

AUTEUR : KUSUMA Pradiptajati TITRE : In search of Asian Malagasy ancestors in Indonesia DIRECTEUR DE THESE

Keywords: Indonesia, Madagascar, Migration, mtDNA, Y-chromosome, genome-wide SNP Western Eurasia, India, Arabia, Indonesia, mitochondrial DNA, Y chromosome

RESUME en français strong support for a new scenario of the Austronesian settlement of Madagascar by reconciling genetic, historical and linguistic data, in which the Banjar -who carry Malay-Ma'anyan genomic ancestry -were participants in Malay-led voyages. This group is the most probable Asian source for the founding Asian population of the Malagasy gene pool among all the analysed Island Southeast Asian populations. However, the exact maritime route(s) of migration from Borneo to Madagascar still remain an open question.

Introduction

L'Indonésie présente une grande diversité linguistique, ethnique et génétique, avec plus de 600 groupes autochtones et 700 différentes langues réparties sur plus de 17 000 îles. Au carrefour de deux océans et deux masses continentales, l'archipel indonésien a été l'objet de migrations humaines successives de la fin du Pléistocène à aujourd'hui. Le dernier évènement d'importance a été la dispersion Austronésienne qui a débuté il y a environ 5 000 ans, probablement depuis Taiwan, pour ensuite se propager à travers les Philippines et l'Indonésie, puis toucher une aire géographique allant de l'Océanie lointaine à l'est, à Madagascar et la côte est Africaine à l'ouest. Malgré de nombreuses recherches en génétique sur la dispersion Austronésienne vers l'est, il y a très peu de données sur la dispersion vers l'ouest, laissant sans réponse de nombreuses questions, liées notamment au peuplement de Madagascar. Reposant sur l'analyse des données culturelles et biologiques, les populations d'Indonésie semblent avoir joué un rôle majeur dans la colonisation de Madagascar, au milieu du premier millénaire de notre ère. Cependant, le peu de populations Indonésiennes étudiées à ce jour n'a pas permis jusqu'à présent d'identifier la/les population(s) indonésienne(s) source(s) ou de proposer un modèle de peuplement. Dans ce présent travail mené en collaboration avec plusieurs équipes internationales, j'ai réalisé des études en génétique des populations de 12 nouvelles populations Indonésiennes, qui à priori devraient éclairer l'histoire des migrations austronésiennes dans l'Océan Indien. Parmi elles sont inclus l'ethnie des Ma'anyan du sud-est de Bornéo qui sont les plus proches linguistiquement des Malgaches. En utilisant différents marqueurs génétiques (chromosome Y, ADN mitochondrial et marqueurs autosomaux), ma recherche a amélioré nos connaissances de la diversité génétique Indonésienne, et du lien génétique entre l'Indonésie et Madagascar.

Résultats

L'analyse des marqueurs uniparentaux (chromosome Y et ADNmt) à l'aide d'approches phylo-géographiques et d'analyses des distances génétiques, suggère que les Malgaches proviennent de plusieurs régions d'Indonésie, avec un lien privilégié avec le sud-est de Bornéo, le sud de Sulawesi et les îles de la Sonde. Etonnamment, les Ma'anyan partagent un nombre limité de lignées paternelles et maternelles avec les Malgaches, malgré leur proximité linguistique. Par ailleurs, en combinant l'analyse de fréquences des SNPs et des analyses haplotypique à partir des données autosomales, il a été confirmé que la diversité génétique des Ma'anyan ne correspond pas à l'ancestralité asiatique des Malgaches. Cependant, en centrant l'analyse sur les populations du sud-est de Bornéo, l'origine de l'ancestralité asiatique des Malgaches est ancrée dans la population Banjar, un mélange de population Ma'anyan et Malaise, résultat des activités commerciales de l'empire Malais dans le sud-est de Bornéo, qui se sont poursuivies à travers l'océan Indien. Par ailleurs nos résultats ont aussi permis d'accroitre notre compréhension de la diversité génétique de l'Indonésie en identifiant (1) une i nouvelle composante génétique austronésienne présente chez les Ma'anyan, et retrouvée à faible fréquence à travers l'Asie du Sud-Est, suggérant une plus grande complexité du modèle d'expansion austronésien dans la région et (2) le rôle joué par les nomades de la mer dans la structuration de la diversité génétique et les échanges entre populations dans l'Indonésie Centrale, soulignant l'histoire génétique complexe de populations suivant un mode de vie nomade.

Conclusions

L'histoire génétique des îles d'Asie du Sud-Est est plus complexe qu'envisagé précédemment, et de nouveaux événements de l'histoire des populations sont révélés par le présent travail, comme une nouvelle composante Austronésienne et une plus grande compréhension du rôle joué par les derniers nomades de la mer Indonésiens. Par ailleurs, malgré une affinité linguistique, les Ma'anyans ne sont pas la source première des populations Malgaches. Ce désaccord entre données linguistiques et génétiques reflète la complexité de l'histoire génétique des populations du sud de Bornéo. La présente étude propose un nouveau scénario de l'origine asiatique du peuplement de Madagascar qui réconcilie les données génétiques, historiques et linguistiques, scénario dans lequel les Banjar -un métissage génétique entre Malais et Ma'anyan-ont participé aux voyages maritimes menés par les Malais. Ce groupe (Banjar) est, parmi les populations des Iles d'Asie du Sud-Est analysées, la source asiatique la plus probable de la composante asiatique du génome Malgache. Cependant, les routes maritimes exactes de migration de Bornéo à Madagascar restent encore à élucider.

Mots-clés: Indonésie, Madagascar, Migration, ADNmt, Chromosome Y, SNP de l'ADN autosomal

RESUME en anglais

Background

Indonesia hosts a wide range of linguistic, ethnic and genetic diversity, comprising of more than 600 ethnic groups and 700 living languages across a total of ~17,000 islands. Acting as a crossroad between two oceans and two landmasses, the Indonesian archipelago has facilitated multi-layered human migrations from the Late Pleistocene to the modern day. The last substantial wave of human migration was the Austronesian dispersal ~5,000 years ago, which is thought to have originated in Taiwan. Its influence spread through the Philippines and Indonesia, ultimately impacting a wide geographical area ranging from Remote Oceania in the east, to Madagascar and the eastern coast of Africa in the west. Despite considerable genetic research on the eastward Austronesian expansion, there is little equivalent research on the western edge, leaving major issues unresolved regarding the settlement of Madagascar. Based on cultural and biological studies, it has been suggested that Indonesian peoples played a major role in the colonization of Madagascar from around the middle of the first millennium CE (Current Era). However, poor geographical coverage of Indonesian populations has prevented the Indonesian source populations from being identified and no clear settlement or migration patterns have been proposed. Here, in collaboration with an international team of colleagues, I performed human population genetic studies on 12 new Indonesian populations, which were a priori expected to shed light on the westward migration of Austronesians across the Indian Ocean. This includes the Ma'anyan ethnic group from Southeast Borneo, who are the closest linguistic siblings to modern Malagasy. Using different genetic markers (Y-chromosome SNPs, mitochondrial DNA and genome-wide SNPs), my research has improved the description of Indonesian genetic diversity, and investigated the genetic links between Indonesia and Madagascar.

ii

Results

Based on uniparental markers (Y-chromosome and mtDNA), a combination of phylogeographic and genetic distance analyses suggest that Malagasy derive from multiple regional sources in Indonesia, with a focus on southeastern Borneo, southern Sulawesi and the Lesser Sunda Islands. Interestingly, the Ma'anyan share limited paternal and maternal lineages with the Malagasy, despite their linguistic connection. Furthermore, combining SNP frequency and haplotype-based analyses from autosomal genome-wide data, it was confirmed that the genetic diversity of the Ma'anyan does not match the Asian ancestry of the Malagasy. However, by focusing on Southeast Borneo populations, strong support was found for an origin of the Asian ancestry of Malagasy among the people of Banjar, an admixed population of Ma'anyan and Malay, likely resulting from trading activities by the Malay Empire in Southeast Borneo, and later continuing across the Indian Ocean arena. These results increase our understanding of the genetic diversity across Indonesia by: 1) identifying the unique and undiscovered Austronesian genetic component carried by the Ma'anyan, which occurs at low levels across Island Southeast Asia and suggests a more complex model for the Austronesian expansion in this region, and 2) describing the role played by sea-nomads in structuring genetic diversity and population exchanges in central Indonesia, thus revealing the complex genetic history of populations living this rare nomadic lifestyle.

Conclusions

The genetic history of Island Southeast Asia is more complex than previously thought, and new layers of population history are revealed by the work presented here, including a new Austronesian component and greater understanding of the role played by the last Indonesian sea-nomads. Moreover, despite close linguistic affinity, the Ma'anyan are shown not to be the primary source population of the Malagasy. This discrepancy between linguistic and genetic evidence reflects the complex history of South Borneo populations. These studies provide Throughout human history, the Indian Ocean region has been an important route for human migration, dispersal and contact. In the late Pleistocene, southern India was situated in the southern dispersal corridor that facilitated the migration of modern humans across the world [START_REF] Field | The southern dispersal hypothesis and the South Asian archaeological record: Examination of dispersal routes through GIS analysis[END_REF][START_REF] Mellars | Genetic and archaeological perspectives on the initial modern human colonization of southern Asia[END_REF]. Millennia later, during the mid-Holocene, the development of long-distance seafaring technologies placed this region, and particularly its island components, at the centre of new maritime corridors (Beaujard, 2012a(Beaujard, , 2012b;;[START_REF] Macphee | Dating of modified femora of extinct dwarf Hippopotamus from Southern Madagascar: Implications for constraining human colonization and vertebrate extinction events[END_REF]. The settlement history and population interactions within this vast region are still not well-understood, and to date no significant human genetic study has been undertaken that focuses on the role played by Island Southeast Asia (ISEA) populations on the westward Austronesian migration from Indonesia to Madagascar.

Table of contents

Indonesia has been a busy intersection for human migrations since the early arrival of modern humans from 'Out-of-Africa' into Papua and Australia about 60,000 -50,000 years ago [START_REF] Allen | Both half right: Updating the evidence for dating first human arrivals in Sahul[END_REF][START_REF] Aubert | Pleistocene cave art from Sulawesi, Indonesia[END_REF][START_REF] Barker | Rainforest Foraging and Farming in Island Southeast Asia: the Archaeology of the Niah Caves, Sarawak[END_REF][START_REF] Grenet | New insights on the late Pleistocene-Holocene lithic industry in East Kalimantan (Borneo): The contribution of three rock shelter sites in the karstic area of the Mangkalihat peninsula[END_REF]. The country also was impacted by the dispersal of Austronesian language speakers from south China and Taiwan into the Pacific and Madagascar that started around 4,000 -3,000 years ago. This latter migration is strongly associated to specific cultural items (Bellwood, 2007;Bulbeck, 2008;[START_REF] Gray | Language trees support the express-train sequence of Austronesian expansion[END_REF]Spriggs, 2007), and is supported by many genetic studies (Jinam et al., 2012;Karafet et al., 2010;[START_REF] Soares | Resolving the ancestry of Austronesian-speaking populations[END_REF][START_REF] Wollstein | Demographic history of Oceania inferred from genome-wide data[END_REF]. It created the important cultural and biological population diversity that can be seen today in Indonesia; 700 languages are spoken by ~500 ethnic groups (Lewis et al., 2017). Many researchers have investigated the eastward Austronesian migration into the Pacific (Bellwood, 2007;Duggan and Stoneking, 2014;Kayser et al., 2008;Skoglund et al., 2016;[START_REF] Soares | Resolving the ancestry of Austronesian-speaking populations[END_REF][START_REF] Spriggs | The lapita culture and Austronesian prehistory in Oceania[END_REF], while the westward migration to Madagascar has remained understudied. Archaeological and paleoenvironmental evidence, such as changes in the biota (tropical rainforest turning into savanna, extinction of native fauna), suggests that people settled on the island of Madagascar, in the western part of the Indian Ocean, only recently (Burney et al., 2004;[START_REF] Gommery | Les plus anciennes traces d'activités anthropiques de Madagascar sur des ossements d'hippopotames subfossiles d'Anjohibe (Province de Mahajanga)[END_REF]. There may have been sporadic early arrivals from Africa around 2,400 years before present (BP) (these populations have unknown connections to the present-day Malagasy, current human populations in Madagascar), but a burst of continuous settlement events is clearly evident around the middle of the first millennium CE (Dewar and Wright, 1993;MacPhee and Burney, 1991). The Malagasy are believed to be the result of admixture between East African Bantu and Southeast Asian Austronesian, according to biological, cultural, and linguistic data (Adelaar, 2009;[START_REF] Ferrand | L'Origine Africaine des Malgaches[END_REF]Hurles et al., 2005;Serva et al., 2012).

The Malagasy speak the language Malagasy, which is a member of the Western-Malayo-Polynesian group of the Austronesian language family. About 90% of its lexicon comes from the Maa'nyan Dayak language, a language spoken by an ethnic group living in the Southeast Barito region in East Kalimantan and South Kalimantan, on Borneo Island (Dahl, 1951). In Malagasy there are loanwords from Javanese, Bugis, Malay, Sulawesi (all from Indonesia), Bantu (African), Arabic, and Sanskrit (India), which all together compose ~10% of Malagasy word diversity (Adelaar, 2005(Adelaar, , 2006)). Linguistic data (number of words from Javanese, Malay and Sanskrit transmitted through Malay/Javanese) suggest a close relationship between the Malagasy and Austronesians, due to human population movements, possibly as subordinates (ship crew or slaves) in Malay-led voyages (Adelaar, 2006;[START_REF] Blench | New palaeozoogeographical evidence for the settlement of Madagascar[END_REF] from Indonesia to Madagascar during the reign of the Srivijaya empire (western Indonesia, 6 th -13 th century CE), as depicted in a relief in an Borobudur temple in central Java (Figure 1.1). This hypothesis is consistent with material culture found in Madagascar originating from Southeast Asia (iron-work techniques, outrigger boats, musical instruments such as the stick-zither and xylophone, and the cultivation of 'tropical food kits', such as rice, bananas, yams and taro [START_REF] Blench | Using diverse sources of evidence for reconstructing the past history of musical exchanges in the Indian Ocean[END_REF][START_REF] Crowther | Ancient crops provide first archaeological signature of the westward Austronesian expansion[END_REF].

Several genetic studies have attempted to investigate the relationship between the Malagasy and the people from ISEA. Many researchers have concluded that Indonesia was the Malagasy's Asian ancestor, in correspondence with linguistic and cultural evidence (Hurles et al., 2005(Hurles et al., , 2005;;Razafindrazaka et al., 2010;Tofanelli et al., 2009). A recent study has supported the hypothesis that Asian Malagasy ancestral populations originated from central Indonesia (Java-Kalimantan-Borneo region) (Pierron et al., 2014). Another study, using mitochondrial DNA data, modeled the estimated number of Indonesian female settlers that arrived in Madagascar to be around 30 women (Cox et al., 2012). Despite these studies, there is still missing information that is needed to propose a detailed historical and demographic scenario of the connection between Indonesian and Malagasy populations. None of these previous studies have determined the level of involvement of the Malagasy's linguistic sister group, the Ma'anyan Dayak from Borneo, or have clarified whether linguistic and historical evidence are correlated with genetic data. Here, in collaboration with an international research network, I performed a human population genetic study on new Indonesian population samples, including the Ma'anyan ethnic group from Southeast Borneo, the closest linguistic sibling to the modern Malagasy. This overall goal of this study was to generate new information on the westward migration of Austronesians across the Indian Ocean.

Aims and questions

This thesis uses genetic analyses to investigate the demographic history of Austronesianspeaking people and their dispersal in Indonesia, across the Indian Ocean and into Madagascar. The thesis has two main aims: 1. To determine the origin of human genetic diversity in Indonesia.

2. To assess how this diversity impacts the gene pool of populations in the Indian Ocean region.

Genetic diversity in ISEA, especially in Indonesia, is very high (Lipson et al., 2014;Tumongor et al., 2014;Karafet et al., 2010;HUGO Pan Asian SNP, 2009). There are still regions, however, that have not been explored, and thus, potentially more populations that play key roles in the genetic diversity of Indonesia. In this thesis I focus on Bornean populations, because this island has not been investigated thoroughly by researchers studying areas of human history in ISEA, such as archaeology, anthropology, ethnography and population genetics. Moreover, this island exhibits unique anthropological and linguistic connections with other populations in Madagascar, and the exact ancestral population(s) of the Malagasy in Indonesia has not been found. To address the aims of this thesis I have published five articles in peer-reviewed scientific international journals, which are appended in section III (Published articles) of this thesis. The articles address specific questions and use two different genetic tools: uniparental markers (mtDNA and Y-chromosome) and autosomal genotype data, within a large interpretative framework (linguistic, historical, anthropological, and biological). This interdisciplinary study was only feasible through discussions with collaborators to define the research questions, select sample populations, design sampling campaigns, and for data generation and interpretation.

The articles focus on the following specific questions: Question 1: Do Bornean populations give additional genetic diversity to the diversity of Indonesia? Question 2: How has the historical influence of western Eurasia shaped Indonesian genetic diversity? Question 3: Is Malagasy's linguistic sister, the Ma'anyan from Borneo, their direct ancestor?

If not, which other population(s) can potentially be the ancestor(s) of the Malagasy? Question 4: Did Indonesian sea-nomads contribute to Austronesian migration to Madagascar? 1.3. Literature review

History of the people of Island Southeast Asia

ISEA, which encompasses Indonesia, East Malaysia (Borneo) and the Philippines, was first inhabited by modern humans about 70,000 to 60,000 years ago [START_REF] Allen | Both half right: Updating the evidence for dating first human arrivals in Sahul[END_REF][START_REF] Détroit | Upper pleistocene Homo sapiens from the Tabon cave (Palawan, The Philippines): Description and dating of new discoveries[END_REF] (Figure 1.2). Evidence of upper Pleistocene human occupation was discovered in the Philippines in the Tabon cave (human remains dated to 47,000 years ago [START_REF] Détroit | Upper pleistocene Homo sapiens from the Tabon cave (Palawan, The Philippines): Description and dating of new discoveries[END_REF], in the Callao cave (67,000 years ago) [START_REF] Mijares | New evidence for a 67,000-year-old human presence at Callao Cave, Luzon, Philippines[END_REF], and in the Wallacea region (Sulawesi island where Talepu rock art was uncovered and dated at 40,000 years ago) [START_REF] Aubert | Pleistocene cave art from Sulawesi, Indonesia[END_REF]. More than 100 archaeological sites in ISEA, however, are from the Holocene era (Neolithic, Bronze age, and later periods) (Spriggs, 2007). Borneo Island remains a terra incognita, although there have been rare archaeological excavations in the area, near the iconic site of the Niah Cave (Sarawak, Malaysian Borneo), which had a modern human presence around 46,000 years ago up to late Holocene [START_REF] Barker | The "human revolution" in lowland tropical Southeast Asia: the antiquity and behavior of anatomically modern humans at Niah Cave (Sarawak, Borneo)[END_REF][START_REF] Harrison | The Great Cave of Niah: A preliminary report on Borneo prehistory[END_REF]. Recent archaeological studies have found a number of well-dated sites, dated to under 10,000 years ago [START_REF] Grenet | New insights on the late Pleistocene-Holocene lithic industry in East Kalimantan (Borneo): The contribution of three rock shelter sites in the karstic area of the Mangkalihat peninsula[END_REF]Plutniak et al., 2014). The first modern humans likely settled and crossed ISEA no later than 70,000 years ago. At that time the Southeast Asian archipelago was divided into three main regions: Sundaland (i.e. Sumatra, Java, Borneo, the Malay Peninsula), Wallacea islands and Sahuland (i.e. Australia, New Guinea, Tasmania) [START_REF] Voris | Maps of Pleistocene sea levels in Southeast Asia: shorelines, river systems and time durations[END_REF] (Figure 1.3). Sea level rose 18,000 to 8,000 years ago, shifting coastlines and forming the ISEA topography observed today [START_REF] Wurster | Stable isotope composition of cave guano from eastern Borneo reveals tropical environments over the past 15,000 cal yr BP[END_REF]. The first wave of modern humans arriving in ISEA from Africa in the Upper Pleistocene were called "Australo-Melanesians". Traces of these early settlers, their specific morphological features and genetic profiles, can be seen today in some rare and remote populations, including the Mamanwa and Batak from the Philippines, the New Guineans/Papuans and Aboriginal Australians [START_REF] Bulbeck | Craniodental affinities of Southeast Asia's "Negritos" and the concordance with their genetic affinities[END_REF][START_REF] Malaspinas | A genomic history of Aboriginal Australia[END_REF][START_REF] Migliano | Evolution of the Pygmy phenotype: Evidence of positive selection from genomewide scans in African, Asian, and Melanesian pygmies[END_REF]. A recent hypothesis suggests that these early settlers survived through admixture with new settlers during the Neolithic, or by withdrawing into isolated refugia and evolving into socalled 'negrito' populations [START_REF] Higham | Hunter-gatherers in Southeast Asia: From prehistory to the present[END_REF]. Nevertheless, their genetic traces and distribution in ISEA is today very scarce. They were hunter-gatherers with a subsistence strategy based on foraging, and were well-adapted to the wide range of environmental conditions they encountered. They occupied three types of sites: rock shelters in the highland regions, river floodplains and coastal sites [START_REF] Higham | Hunter-gatherers in Southeast Asia: From prehistory to the present[END_REF]. This subsistence strategy and lifestyle lasted in ISEA for more than 40,000 years, but underwent a major shift starting around 5,000 years ago, driven by the invention and development of crop cultivation and farming. The post-glacial climatic changes led to environmental changes, which made food production in some specific regions of East Asia viable (i.e. 8,000 -7,000 years ago, Yangtze River valley, south China) [START_REF] Crawford | The origins of rice agriculture: recent progress in East Asia[END_REF][START_REF] Deng | From early domesticated rice of the middle Yangtze Basin to millet, rice and wheat agriculture: Archaeobotanical macro-remains from Baligang, Nanyang Basin, Central China (6700-500 BC)[END_REF][START_REF] Fuller | Pathways to Asian civilizations: Tracing the origins and spread of rice and rice cultures[END_REF]. This may have led to a sedentary way of life, and an increase in population density leading to population expansion [START_REF] Bellwood | First Migrants: Ancient Migration in Global Perspective[END_REF].

Later, Neolithic human migration occurred during the late Holocene from south China and Taiwan to ISEA. There were two waves of human migration from south China. The first wave was through Thailand and Vietnam, and then through Malaysia to Sumatra and Borneo, suggested by the distribution of archaeological artifacts (basket or cord-marked ceramics) [START_REF] Anderson | Crossing the Luzon Strait: archaeological chronology in the Batanes Islands, Philippines and the regional sequence of Neolithic dispersal[END_REF]. This has been associated with the early expansion of the Austroasiatic language to the Indonesian archipelago [START_REF] Higham | Early mainland Southeast Asia: From first humans to Angkor[END_REF][START_REF] Higham | A new chronology for the Bronze Age of Northeastern Thailand and its implications for Southeast Asian prehistory[END_REF]. The second wave was from south China through Taiwan and the Philippines to Sulawesi and Borneo, later reaching Malaysia, as suggested by the distribution of red-slipped pottery (Bellwood et al., 1995;[START_REF] Paz | Island Southeast Asia: spread or friction zone?[END_REF]. This was later associated with the Austronesian expansion "Out-of-Taiwan". These latter events, together with the population substrate from the first settlement wave, are supported by genetic studies showing that present-day ISEA populations have five main genetic layers (Jinam et al., 2012;Karafet et al., 2010;Lipson et al., 2014) (Figure 1.4).

These populations were the main ancestors of Indonesian and ISEA populations in general, together with the former group, the Australo-Melanesian group. The Neolithic migration southward from Taiwan to the Indonesian archipelago, was encouraged by the development of farming in Taiwan and south China, during the late Pleistocene to early Holocene. The Yangtze River basin has been suggested as the region where people first domesticated rice around 8,000 -5,000 years ago [START_REF] Crawford | The origins of rice agriculture: recent progress in East Asia[END_REF][START_REF] Deng | From early domesticated rice of the middle Yangtze Basin to millet, rice and wheat agriculture: Archaeobotanical macro-remains from Baligang, Nanyang Basin, Central China (6700-500 BC)[END_REF][START_REF] Fuller | Pathways to Asian civilizations: Tracing the origins and spread of rice and rice cultures[END_REF]. This preceded the significant movement of agricultural populations originating in south China, south to Southeast Asia, and finally into the Pacific Islands, over a time span of about 5,000 years (Bellwood et al., 1995;Bellwood, 2007[START_REF] Bellwood | First Migrants: Ancient Migration in Global Perspective[END_REF]. This southward expansion may have only been possible due to maritime foraging and trade, as shown by archaeological data (Bulbeck, 2008). It is widely accepted that this expansion led to almost the entire population residing in the western part of ISEA speaking Malayo-Polynesian languages, a branch of the Austronesian language, which is also spoken by the Malagasy population in Madagascar (Adelaar, 1995a(Adelaar, , 2005)). In contrast, populations from the eastern part of ISEA speak other branches of Austronesian (i.e. Central-Eastern Malayo-Polynesian) and Papuan languages (Bellwood et al., 1995;[START_REF] Greenhill | TransNewGuinea.org: An online database of New Guinea languages[END_REF]Lewis et al., 2016). There are nine other branches of the Austronesian language family that are only spoken by the indigenous people of Taiwan, the Formosan (Bellwood et al., 1995).

Therefore, it was concluded that the Austronesian language developed in Taiwan, then spread to other regions during the Holocene [START_REF] Diamond | Farmers and their languages: The first expansions[END_REF] (Figure 1.5). There were subsequent migrations from south and southwestern Eurasia, mainly from India and the Middle East through trading activities. Indianisation and Islamisation in Indonesia led to the development of Hindu, and later Islamic, kingdoms between the 5 th and 16 th centuries CE. These kingdoms reinforced interactions and influence from western Eurasia to all the regions in western and central Indonesia spanned by these kingdoms (Beaujard, 2012a;[START_REF] Beaujard | L'océan Indien avant le XVIe siècle : une charnière économique de l'ancien monde[END_REF]Gonda, 1975;Kanchan, 1990;Karafet et al., 2010). These interactions brought not only new ideas and trade goods into the Indonesian archipelago, but they also encouraged, to some degree, gene flow, in a number of Indonesian populations. This is one aspect that I will investigate in this study.

Austronesian language

Austronesian is the largest language family in the world and the most geographically widespread of all languages. The dispersal of Austronesian languages over their current geographic range (from the coast of East Africa to the eastern Pacific) is a relatively recent event that started about 4,000 years ago, triggered by Neolithisation in south China and Taiwan (Bellwood, 2007). Currently, Austronesian languages are spoken by native populations inhabiting the territories of Indonesia, Malaysia, the Philippines, Madagascar, Taiwan, Vietnam, southern Cambodia and south China (Adelaar, 2005;Bellwood et al., 1995). In the eastern regions, the language is also spoken by people in the coastal areas of West Papua, Papua New Guinea and the Melanesian Islands (New Ireland, New Britain, Solomon islands, Fiji, and Vanuatu), until Polynesia [START_REF] Pawley | The prehistory of the oceanic languages: a current view[END_REF]. More than 1,200 languages are affiliated to Austronesian language family, which is currently spoken by approximately 300 million individuals.

The Austronesian linguistic family is divided into ten primary groups, of which nine belong to the Formosan language subgroup, found only in Taiwan (Adelaar, 2005)

(Figure 1.6). All
Austronesian languages outside Taiwan belong to the Malayo-Polynesian subgroup of the Austronesian language. The great diversity of the Formosan language has been interpreted as a product of longer in situ divergence [START_REF] Blust | The Austronesian languages[END_REF]. Therefore, the Austronesian language family tree strongly favours Taiwan as the origin of the language.

In Indonesia there are three branches of the Proto-Austronesian language: 1) West-Malayo-Polynesian (WMP) spoken by populations in the western region of Indonesia and also in Madagascar; 2) Central-Malayo-Polynesian (CMP) spoken by populations in the central region of Indonesia; and 3) South Halmahera-West New Guinea (SHWNG) spoken by the majority of inhabitants in Maluku, and Papuans in coastal/lowland areas (Adelaar, 2005;[START_REF] Blust | Eastern Malayo-Polynesian: a subgrouping argument[END_REF]. Within each of these branches, each region may have different languages. In Indonesia there are in total ~700 different languages. Population dispersal over 17,000 islands (emphasised when sea-level rose in the early Holocene) led to some degree of isolation and linguistic differentiation, thus producing the vast diversity of Austronesian languages seen today [START_REF] Tryon | Proto-Austronesian and the major Austronesian subgroups[END_REF].

Borneo: an overview

Among the ~17,000 islands in the Indonesian archipelago, Borneo, the third largest island in the world, has contributed greatly to the cultural diversity of Indonesia. Borneo hosts some of the first evidence for Late Pleistocene modern human settlement in Sundaland, now ISEA [START_REF] Barker | Rainforest Foraging and Farming in Island Southeast Asia: the Archaeology of the Niah Caves, Sarawak[END_REF][START_REF] Détroit | Upper pleistocene Homo sapiens from the Tabon cave (Palawan, The Philippines): Description and dating of new discoveries[END_REF][START_REF] Krigbaum | The West Mouth burial series from Niah Cave: past and present[END_REF]. The deep skull of Niah cave in Sarawak (Malaysian Borneo), is one of the key specimens that has shed light on human migration into ISEA [START_REF] Barker | Rainforest Foraging and Farming in Island Southeast Asia: the Archaeology of the Niah Caves, Sarawak[END_REF][START_REF] Harrison | The Great Cave of Niah: A preliminary report on Borneo prehistory[END_REF]. Rather than resembling Australomelanesian skull morphology, the deep skull has unique features that are similar to autochthonous people living in Borneo today, the "Dayak" people, who probably originated from an early migration from mainland East Asia to Borneo around 30,000 years ago [START_REF] Curnoe | Deep skull from Niah Cave and the Pleistocene peopling of Southeast Asia[END_REF]. This finding may provide evidence for a degree of population continuity in this region of Borneo over the last 40,000 years. When sea-level rose and separated Sundaland into component islands, Borneo was separated from peninsular Malaysia about 12,000 years ago, and from Java and Sumatra around 10,000 years ago [START_REF] Bird | Palaeoenvironments of insular Southeast Asia during the Last Glacial Period: A savanna corridor in Sundaland?[END_REF]. Changes in geographical conditions with this newly formed coastline stimulated populations to adapt to their new environment (Bulbeck, 2008). Moreover, progressive ponding of the rivers and

(incl. Western Indonesian and Malagasy)

saline contamination of coastal ground waters and rivers, was likely to significantly affect the ecology of the area, hence encouraging population movement away from water edges [START_REF] Barton | Late Pleistocene foragers[END_REF]. This factor might have further influenced language and genetic diversity in Borneo.

People in Kalimantan, and the rest of Borneo Island, as well as other major western Indonesian populations, speak the Austronesian language family subgroup called the Western-Malayo-Polynesian group (Adelaar, 1995a;Lewis et al., 2016). There are 74 languages (~11% of total Indonesian language diversity) spoken in Kalimantan (Figure 1.7), clustered into 10 different subgroups: 7 endo-Bornean groups (Land Dayak, Rejang-Baram, Kenyah-Kayan, Apo Duat, West Barito, Barito-Mahakam and East Barito) and 3 exo-Bornean groups (Malayic Dayak, Tamanic and Sabahan) (Adelaar, 1995a(Adelaar, , 2005;;[START_REF] Blust | The Greater North Borneo hypothesis[END_REF].

Furthermore, there are also Sama-Bajau languages spoken by the Bajo sea-nomad people, who live in eastern coastal areas of Kalimantan (Lewis et al., 2016;Nuraini, 2016). Although all languages spoken in Borneo are classified as Austronesian, there is a significant influence from the Austroasiatic language substrate (Blench, 2011). Austronesian and Austroasiatic languages are generally recognised as coherent and internally consistent language phyla. However, it has been acknowledged, since Schmidt (1906), that they share some common vocabulary, which has led to proposals merging them in a single phylum. Consequently, similarities between lexical items would be due to inheritance from a common ancestor.

However, Borneo and Southeast Asia were part of the same land mass until 12,000 years ago, suggesting that there was late Holocene contact between mainland Asia, hence Austroasiatic speakers, and Borneo. These two hypotheses of an Austronesian-Austroasitic link, a common ancestor and recent interactions can be concomitant. There are three lines of evidence for language contact between Austronesians and Austroasiatics in Borneo: 1) resemblance between mainland Southeast Asia branches of Austroasiatic and Borneo Austronesian; 2) similarities between Asian languages and Borneo Austronesian; and 3) between Austronesian and Austroasiatic due to trade-driven expansion of the Malay (Blench, 2011). This evident connection was observed mainly in populations living in western/northwestern Borneo, such as the Land Dayak speaking group (Adelaar, 1995a), where some cultural and agricultural evidence was observed (taro cultivation, mouth organ musical instrument). Apart Austroasiatic, another influence from mainland Southeast Asia is also observed with the absorbency of Malay words; this is mainly found in the Malayic Dayak speaking group, and also in the non-indigenous Banjar group that speak the Malay language in South Kalimantan. Malay language and culture in South Kalimantan was most probably brought by the invasion of the Malay Srivijaya Empire in the region between the 6 th to 8 th centuries. Historical information on south Borneo is very scarce, but there is one valuable piece of information written in the 'Hikajat Banjar' ('Tale of Banjar'), which describes the history of Banjarmasin city (Ras, 1968). The story explains that there was an old Malay settlement in south Borneo in a region called "Tanjung". Tanjung is now located further up north from the coastal area.

However, a record states that during that time south Borneo was divided by a 200 km gulf (Van Bemmelen, 1949). This enabled the Malay Empire to reach the Tanjung area and establish an outpost, which later moved southward to the current city of Banjarmasin (Ras, 1968). The Malay invasion triggered two human dispersal events from south Borneo: the dispersal of proto-Bajo speakers (Blust, 2007) and the oceanic migration into Madagascar (Adelaar, 1989(Adelaar, , 2017)). The strong influence of the Malay empire in Indonesia brought about the Indianisation of almost the entire archipelago (Beaujard, 2012b;Kanchan, 1990). In parallel to cultural and trading influences, it is also highly probable that the movement of people from South and Southwest Asia to Indonesia occurred.

One unique Bornean language group spoken by people living around the Barito River is the Southeast Barito language. Intriguingly, it is also spoken by the Malagasy people of Madagascar. Around the Barito River, this language is now spoken mainly by the Ma'anyan people, and other smaller groups such as the Samihim, Paku, Dusun Witu and Dusun Deyah (Adelaar, 1995b(Adelaar, , 2005;;Hudson, 1972). However, there are cultural dissimilarities between the Ma'anyan people and the Malagasy. Some of the Malagasy are wet rice cultivators, while Dayaks are, as a rule, dry rice cultivators. Some Malagasy use outrigger canoes, whereas Southeast Barito Dayaks never do. The Malagasy migration to East Africa presupposes navigational skills, common to some Indonesian populations, but which can hardly be attributed to the Dayaks, who are forest dwellers today. These factors can be accounted for if we adopt the hypothesis that the Southeast Barito migrants did not cross the Indian Ocean themselves in order to colonise Madagascar, but that they were brought there as subordinates (slaves, ship crew, laborers) by the Malays (Adelaar, 1995a(Adelaar, , 2005)). It is important to resolve this issue; this issue it is investigated and discussed in this thesis with genetic evidence.

The huge linguistic diversity in Borneo is also enriched by the different lifestyles of its populations. Today, the majority of autochthonous populations make a living through agriculture, but a few Dayak sub-ethnic groups, like the Punan Dayak, have retained their original lifestyles as hunter-gatherers [START_REF] Sellato | Nomads of the Borneo Rainforest: The Economics, Politics, and Ideology of Settling Down[END_REF]. The later migration waves of Malay and Sulawesi people to Kalimantan added to the diversity of languages and cultures of the Kalimantan people (Adelaar, 1995a). Apart from geographical distance, different languages and cultures would have been barriers between populations. This resulted in a unique genetic background for each population, and consequently the vast human genetic diversity of Kalimantan today. For example, the Bidayuh, living in northwestern Kalimantan, have a significant genetic influence from mainland Southeast Asia, which corresponds to their linguistic characteristics (Jinam et al., 2012). On the other hand, Murut and Dusun groups, living in northeastern Kalimantan are genetically related to the Formosan (Austronesian speaking) in Taiwan and the Igorot people in the Philippines, as they live in geographic proximity to the Philippines (Mörseburg et al., 2016). The Tamanic people, living in centralnorthern Kalimantan, speak a language close to Buginese and other Sulawesi languages (Adelaar, 1995a), and may also have Sulawesi genetic influences in their understudied genome. Despite these recent studies, there remain many understudied populations in Kalimantan and its human genomic diversity is largely unknown. To date, there are extensive genetic studies at the regional level (Karafet et al., 2010;Lipson et al., 2014;Tumonggor et al., 2013), but Kalimantan populations were not included in these studies. In order to fill these gaps in knowledge of the region, this thesis aims to investigate human genetic diversity in Kalimantan and its influence on other populations.

Arrival of Austronesians in Madagascar

The populations on the island of Madagascar have strong cultural, linguistic and genetic connections to both Africa and ISEA (Adelaar, 1995a(Adelaar, , 2005(Adelaar, , 2009;;Beaujard, 2012b;Hurles et al., 2005;Soodyall et al., 1995). It is well-documented that the main phase of settlement took place around 2,000 -1,000 years ago (Burney et al., 2004;Hurles et al., 2005;Pierron et al., 2014), but there is also evidence for earlier (4,000 -3,000 years ago) sporadic human presence on the island, with unknown relationships to the present-day Malagasy and huntergatherers, most likely, from Africa (Burney et al., 2004;Dewar and Wright, 1993). Cut marks were found on hippopotamus bones in northwestern Madagascar, supporting a human presence around 2,400 years ago (MacPhee and Burney, 1991), as well as environmental changes (deforestation) (Burney et al., 2004), dated from around 2,000 years ago. Furthermore, there are reports stating the presence of anthropic artifacts around 4,000 years ago [START_REF] Gommery | Les plus anciennes traces d'activités anthropiques de Madagascar sur des ossements d'hippopotames subfossiles d'Anjohibe (Province de Mahajanga)[END_REF]. Decades of archaeological surveys and excavations have not found an ISEA presence in Madagascar. However, the latest archaeobotanic study showed an early Asian presence in the eastern Africa region, particularly in the Comoros Islands and northern Madagascar, at around the early 7 th and 11 th century CE respectively (Crowther et al., 2016) (Figure 1.8). Researchers found fossil Asian crops (rice and cotton) in those regions. This finding rises many further questions and drove research on how, when, and which Asian people brought these ancient crops to the East of the Indian Ocean, and ultimately participated in the settlement of Madagascar.

The presence of Asian people in Madagascar is strongly supported by linguistic research. The Malagasy are subdivided into 18 different ethnic groups, and this roughly corresponds to the division of dialects [START_REF] Rasoloson | Malagasy[END_REF]. Central dialects and southwestern dialects form two clearly separate groups, while the other dialects are more difficult to cluster (Adelaar, 2005). The most important groups, in order of their numbers, are the Merina (northern central mountains), the Betsimisaraka (along the east coast), the Betsileo (southern central mountains), the Tsimihety (northern mountains), the Sakalava (western savannas) and the Antandroy (southern dry lands). All ethnic groups speak Malagasy, but with different dialects. The differences between the Malagasy dialects are small enough to support the arrival of linguistically similar migrant groups (Adelaar, 2005;[START_REF] Rasoloson | Malagasy[END_REF]. The Malagasy language is part of the Western-Malayo-Polynesian (WMP) language of Austronesian. Most of the Malagasy language lexicon comes from Maa'nyan Dayak languages, languages spoken by tribes inhabiting the region of the Barito River in East Kalimantan and South Kalimantan (Dahl, 1951). The Ma'anyan language has striking phonetic, grammatical and lexical similarities with Malagasy, and is the most closely related language to Malagasy. Words are mostly found in terms associated with the domain of navigation and parts of the body. Loanwords from Javanese, Bugis, Bantu (African), Arabic and Sanskrit are found in lower frequency in the Malagasy language (Adelaar, 2006), however Malagasy has many borrow-words from Malay, which appear to be from two different dialects: Sumatra (Srivijaya?) Malay and Banjar Malay. For example, Sumatran Malay has the following words: sәmbah 'gesture of worship or honour'; lәmah 'weak'; cecak 'lizard'; and kәmbar 'twins'. Banjar Malay, which does not have the vowel ә and uses a instead, has the corresponding forms sambah, lamah, cacak and kambar (all with same meanings). These words were borrowed into Malagasy as samba 'expression of gratitude to God, lama 'weak', tsatsaka 'lizard' and (sakalava) hamba 'twins' (Adelaar, 2006). Sanskrit words in Malagasy were probably also brought via Malay/Asian people. Some linguists suggest that the close relationship between Malagasy and Austronesian, especially in Indonesia, is strong evidence for an Austronesian-speaking people migration from Indonesia to Madagascar, as ship workers or slaves [START_REF] Blench | New palaeozoogeographical evidence for the settlement of Madagascar[END_REF], possibly during the reign of the Srivijaya Malay empire in the 6 th -8 th centuries (Beaujard, 2012a(Beaujard, , 2012b)). The Malay influence on the Malagasy language would have lasted until after the introduction of Islam in Southeast Asia, as evidenced by the term 'sombily' which has a Malay origin to designate the ritual oxen slaughter (Adelaar, 1995a).

Apart from linguistic evidence, there are also cultural, material, and food plant transmission documentation from Indonesia to Madagascar, and eastern Africa in general [START_REF] Blench | The ethnographic evidence for long-distance contacts between Oceania and East Africa[END_REF].

Food plants, such as taro and banana species that are specifically of Southeast Asian origin, are widely present in Madagascar and in off-coast small islands, indicating anthropogenic translocations [START_REF] Boivin | East Africa and Madagascar in the Indian Ocean world[END_REF]. Furthermore, the existence of outrigger-canoes in eastern Africa that are widely practiced by sea-faring Vezo people in Madagascar, signifies the distinct introduction of Indonesian maritime technology (Adelaar, 1995a;[START_REF] Blench | The ethnographic evidence for long-distance contacts between Oceania and East Africa[END_REF][START_REF] Lambek | People of the sea: Identity and descent among the Vezo of Madagascar[END_REF]. Indonesian ethnomusicological evidence in Madagascar is also evident. The stick-zither is a characteristic instrument of Indonesia, especially in South Sulawesi and Sumba [START_REF] Blench | The ethnographic evidence for long-distance contacts between Oceania and East Africa[END_REF] (Figure 1.9). In Madagascar, the stick-zither's one or two strings are made from several twisted raffia fibers, although more recently, steel strings are also used.

Zithers are played only by men and not everyone is allowed to play them. Knowledge is passed down from father to son [START_REF] Mcleod | Musical instruments and history in Madagascar[END_REF]. In contrast to the extensive studies focusing on the linguistic and cultural relationships between Malagasy and Austronesian populations, there have only been a few studies investigating their genetic relationship, although there is strong support for a genetic influence of Austronesian populations from ISEA in Madagascar. In addition to a major African (Bantu) genetic input, there is at least a 30% Asian (Austronesian) input into the Malagasy gene pool (Pierron et al., 2014;Tofanelli et al., 2009), which has an affinity to populations located in the present-day Borneo-Java-Sumatra region in Indonesia (Hurles et al., 2005;Pierron et al., 2014). The Malagasy even exhibit a unique Asian genetic signature, the B4a1a1b mitochondrial haplogroup called the Malagasy motif (Razafindrazaka et al., 2010). This haplogroup is a subgroup of the Polynesian motif, a haplogroup marker of Polynesian, Oceanian and eastern Indonesian populations that evolved along the way of the south-and eastward Austronesian migration (Duggan et al., 2014;Duggan and Stoneking, 2014;Soares et al., 2011). Interestingly, however, the Malagasy motif haplogroup is only found in Madagascar (Cox et al., 2012;Razafindrazaka et al., 2010), and it is within this context that this thesis aims to further investigate the 'missing' genetic link between Indonesia and Madagascar.

Indonesia and Madagascar are separated by ~6,000 km of sea; historically, humans could have only made this long-distance oceanic voyage with the help of nature. Oceanic southequatorial currents connect Indonesia and northern Madagascar and Mozambique, and the north-equatorial current enables sea travel between Indonesia and the Horn of Africa.

Seafaring simulations using a computer simulated approach suggest that the 6,000 km (3,200 nautical miles) between Indonesia and Madagascar were not a significant boundary [START_REF] Fitzpatrick | Seafaring simulations and the origin of prehistoric settlers to Madagascar[END_REF] (Figure 1.10a). Instead, simulation models support several direct migration routes from Sunda/Sumatra to Madagascar, or an indirect migration route through south India/Sri Lanka, and suggest the Maldives as a possible en route stopping location between ISEA and Madagascar [START_REF] Fitzpatrick | Seafaring simulations and the origin of prehistoric settlers to Madagascar[END_REF] (Figure 1.10b). Thus, long-distance oceanic voyage was feasible, as supported by oceanic currents and advanced sea-faring technologies. 1.3.4. Genetic markers as tools to study human history 1.3.4.1. Mitochondrial DNA Mitochondrion (plural: mitochondria) is an organelle that has important roles in the life of a cell, including cellular respiration, signaling, cell cycle and apoptosis control. Mitochondria have their own genome, distinct from the cell's nucleus. Every eukaryotic cell has hundreds to thousands of mitochondrial genome copies. Mitochondrial DNA (mtDNA) is inherited maternally. Males cannot transmit their mitochondria because during conception sperms' mitochondria, which are located on the neck, do not penetrate the ovum with the sperms' head [START_REF] Gilbert | Developmental Biology, Eighth Edition[END_REF]. This prevents recombination event in the mitochondrial genetic material, although there are some rare cases of these events [START_REF] Kraytsberg | Recombination of human mitochondrial DNA[END_REF]. These special characteristics of mitochondria are used in anthropological genetic studies to trace the history of maternal lineages. Mutations that occur in the mitochondrial genome can cause diseases [START_REF] Mcfarland | A neurological perspective on mitochondrial disease[END_REF][START_REF] Sudoyo | Mitochondrial genome and susceptibility to diabetes mellitus[END_REF][START_REF] Wallace | Mitochondrial DNA sequence variation in human evolution and disease[END_REF], however, other specific mutations can be used as female-specific population markers for investigating human migration history [START_REF] Kivisild | Maternal ancestry and population history from whole mitochondrial genomes[END_REF][START_REF] Pierron | New evidence of a mitochondrial genetic background paradox: Impact of the J haplogroup on the A3243G mutation[END_REF][START_REF] Stoneking | Human origins[END_REF].

MtDNA is a circular double-stranded molecule. It has 16,569 base pairs (bp), which is only 0.0006% of nuclear DNA in length. MtDNA codes for 37 genes: 2 ribosomal RNAs (rRNAs), 13 subunits of the oxidative phosphorylation (OXPHOS) system, and 22 transfer RNAs (tRNAs) [START_REF] Anderson | Sequence and organization of the human mitochondrial genome[END_REF]. Within the genome there are ~1,100 bp of nucleotides that are not translated and have regulating functions. This region is called the control region. This region has been exploited widely for applications in population genetic studies. The control region contains three hypervariable segments (HVS), called HVS-I, HVS-II, and HVS-III, and also includes a short structure called the displacement loop (D-Loop) [START_REF] Clayton | Mitochondrial DNA Replication: What We Know[END_REF]. The control region has a very high nucleotide mutation rate, reaching 0.165x10 -6 substitutions/site/ year, while in the coding region the rate is only 0.017x10 -6 substitutions/site/year [START_REF] Pakendorf | Mitochondrial DNA and human evolution[END_REF]. This high sequence variability creates specific polymorphism patterns in individuals within a population that are often different from individuals in other populations. This feature makes mtDNA a prominent marker in population genetic studies and allows robust phylogenetic and phylogeographic studies.

Variation in mtDNA sequences is correlated with population geographical distributions and their histories [START_REF] Cann | Mitochondrial DNA and human evolution[END_REF]. Polymorphisms in mtDNA nucleotides produce haplotypes that can characterise a population or group of populations, forming a haplotype group called a haplogroup (which includes mtDNA sequences sharing a common mtDNA ancestor).

Currently 5,400 haplogroups have been identified worldwide (http://phylotree.org). The study of the geographic distribution of these haplogroups is called phylogeography. The history of haplogroup divergence and its evolution through time (based on the mutation rate we can obtain 'time to the most recent ancestor' (TMRCA)) is called phylogeny. MtDNA gives information about maternal lineages, providing a complementary picture to the scenarios that are built from the analysis of Y-or autosomal chromosome data (Kayser et al., 2008;[START_REF] Tobler | Aboriginal mitogenomes reveal 50,000 years of regionalism in Australia[END_REF].

The nomenclature of mtDNA haplogroups is firstly based on letters, and secondly on numbers to represent different and/or deeper groups. A comparison of mtDNA variation in global populations showed that modern humans originated in Africa; this region has the highest mtDNA diversity, confirming the 'Out-of-Africa' scenario [START_REF] Macaulay | Single, rapid coastal settlement of Asia revealed by analysis of complete mitochondrial genomes[END_REF]Pagani et al., 2015;[START_REF] Rasmussen | An Aboriginal Australian genome reveals separate human dispersals into Asia[END_REF]. The African signature haplogroup is classified as the L haplogroup, and has the highest degree of variation observed in Africa lineages. This haplogroup is divided into the sub-haplogroups L0, L1, L2, and L3. Outside Africa, specific Eurasian macrohaplogroups are classified as the M and N haplogroups, which evolved from the L3 haplogroup. European populations are classified as I, J, K, H, T, U, V, W, and X haplogroups. In ISEA we found lineages (E, B, F, M and N) originating in Sundaland (previous landmass located west of the Wallace Line) and other haplogroups (S, O, P, M, and Q) from the Sahul (Australia, Papua New Guinea, Melanesia islands) which both evolved in isolation from each other over the last 50,000 years. Currently, the mtDNA nomenclature has a robust branch structure, which has been constructed through the rigorous and detailed analyses of whole mtDNA genomes from more than 30,000 individuals (van Oven and Kayser, 2009). A number of haplogroups are found in the ethnic populations scattered throughout the Indonesian archipelago, the majority of which are thought to be related to small-scale late-Holocene migrations, notably the Neolithic Austronesian dispersal out-of-Taiwan (i.e., haplogroup B4*, M7b*, M7c*, and F1a4*) and earlier Neolithic dispersals from mainland Southeast Asia (B5a*, B5b*, F1a1*) (Bellwood, 2007;[START_REF] Brandão | Quantifying the legacy of the Chinese Neolithic on the maternal genetic heritage of Taiwan and Island Southeast Asia[END_REF][START_REF] Soares | Resolving the ancestry of Austronesian-speaking populations[END_REF]. These two events were preceded by ISEA population dispersals triggered by rises in sea-level after the Last Glacial Maximum 14-8 kya (E and F3* haplogroup) [START_REF] Brandão | Quantifying the legacy of the Chinese Neolithic on the maternal genetic heritage of Taiwan and Island Southeast Asia[END_REF][START_REF] Hill | A mitochondrial stratigraphy for island Southeast Asia[END_REF]Oppenheimer and Richards, 2001) (Figure 1.11). In eastern Indonesia, populations carry haplogroups affiliated to Papuan populations (i.e. haplogroup P and Q).

These haplogroups are also found in Austronesian and Papuan speaking populations, suggesting complex interactions driven by social behavior, language shifts, and admixture between Austronesian and Papuan speaking populations [START_REF] Brandão | Quantifying the legacy of the Chinese Neolithic on the maternal genetic heritage of Taiwan and Island Southeast Asia[END_REF][START_REF] Hill | A mitochondrial stratigraphy for island Southeast Asia[END_REF]Kayser et al., 2003Kayser et al., , 2008;;Tumonggor et al., 2013;[START_REF] Wilder | Genetic continuity across a deeply divergent linguistic contact zone in North Maluku, Indonesia[END_REF]. Meanwhile in Madagascar, Asian mtDNA haplogroups (such as B4a1a1, B4a1a1b, F1a1a, and M7c1) are found more frequently than African mtDNA haplogroups (L*), at a roughly 2:1 ratio [START_REF] Capredon | Histoire biologique d'une population du sud-est malgache : les Antemoro[END_REF]Razafindrazaka, 2010;Tofanelli et al., 2009). Interestingly, a unique ISEA haplogroup has been identified in Malagasy populations but not in other populations -a haplogroup classified as B4a1a1b (Malagasy motif), a sub-branch of the Polynesian motif (Cox et al., 2012;Razafindrazaka et al., 2010).

In conclusion, in the era of whole nuclear genome sequencing, mitochondrial genomes continue to be highly informative and are a widely used tool in human evolutionary and population genetic studies. MtDNA has offered many opportunities to explore genealogical relationships among individuals, and to study the frequency differences of matrilineal lineages among human populations at continental and regional scales, thus, assessing the femalespecific aspects of human demographic history [START_REF] Kivisild | Maternal ancestry and population history from whole mitochondrial genomes[END_REF].

Y chromosomes

The Y-chromosome is a male-unique chromosome; it has specific roles as a sex-determining chromosome and in male fertility. Compared to other chromosomes, it is the smallest in size and has the least number of genes [START_REF] Jobling | Fathers and sons: the Y chromosome and human evolution[END_REF]. The Y-chromosome is believed to have been a degenerated chromosome during its evolution [START_REF] Charlesworth | The evolution of chromosomal sex determination and dosage compensation[END_REF]; there are nine genes located on the short arm, and the remaining genes are located on the long arm [START_REF] Skaletsky | The male-specific region of the human Y chromosome is a mosaic of discrete sequence classes[END_REF]. The human Y-chromosome is normally unable to recombine with the X chromosome, except for small pieces of pseudoautosomal regions at the telomeres. The bulk of the Y-chromosome is called the non-recombining region of the Y-chromosome (NRY), and it has little functional genetic content. The recombination suppression mechanism in the Y-chromosome promotes its gradual degeneration, which is a common feature of non-recombining sex chromosomes [START_REF] Charlesworth | The degeneration of Y chromosomes[END_REF][START_REF] Steinemann | Enigma of Y chromosome degeneration: Neo-Y and Neo-X chromosomes of Drosophila miranda a model for sex chromosome evolution[END_REF]. The Y-chromosome is an important tool in population genetics and forensic research.

In human population genetics research, three types of polymorphisms are observed in the Ychromosome: insertions-deletions, SNPs and microsatellites [START_REF] Hammer | Out of Africa and back again: nested cladistic analysis of human Y chromosome variation[END_REF][START_REF] Jobling | Fathers and sons: the Y chromosome and human evolution[END_REF][START_REF] Karmin | A Recent Bottleneck of Y Chromosome Diversity Coincides with a Global Change in Culture[END_REF][START_REF] Underhill | The phylogeography of Y chromosome binary haplotypes and the origins of modern human populations[END_REF]. These polymorphisms have been widely used to investigate male phylogeography and global migration. Insertions and deletions are normally found at specific locations along chromosomes, known as Alu insertions [START_REF] Hammer | Out of Africa and back again: nested cladistic analysis of human Y chromosome variation[END_REF]. SNPs are also present along the NRY. Microsatellites, also called short-tandem repeats (STR), are short sequences of nucleotides that are repeated several times in tandem. Due to the Y-chromosome's non-recombining nature, these three polymorphisms are often found physically linked to each other, and researchers use this feature to define a Y-chromosome's haplotype. Determining Y-chromosome haplotype diversity in different populations is essential in reconstructing the history of global human settlement from a male perspective [START_REF] Jobling | The human Y chromosome: an evolutionary marker comes of age[END_REF][START_REF] Kivisild | The study of human Y chromosome variation through ancient DNA[END_REF][START_REF] Underhill | The phylogeography of Y chromosome binary haplotypes and the origins of modern human populations[END_REF][START_REF] Underhill | Use of Y cromosome and mitochondrial DNA population structure in tracing human migrations[END_REF].

A comprehensive description of Y-chromosome genetic diversity, using high-coverage nextgeneration sequencing (NGS), has been proposed for many Y-chromosome phylogenies worldwide [START_REF] Hallast | The Y-chromosome tree bursts into leaf: 13,000 high-confidence SNPs covering the majority of known clades[END_REF][START_REF] Karmin | A Recent Bottleneck of Y Chromosome Diversity Coincides with a Global Change in Culture[END_REF][START_REF] Poznik | Sequencing Y Chromosomes resolves discrepancy in time to common ancestor of males versus females[END_REF][START_REF] Trombetta | Regional differences in the accumulation of SNPs on the male-specific portion of the human Y chromosome replicate autosomal patterns: Implications for genetic dating[END_REF], and more specifically in the African continent [START_REF] Cruciani | A revised root for the human Y chromosomal phylogenetic tree: The origin of patrilineal diversity in Africa[END_REF][START_REF] Scozzari | An unbiased resource of novel SNP markers provides a new chronology for the human Y chromosome and reveals a deep phylogenetic structure in Africa[END_REF]. Like mtDNA haplogroups, Y-chromosome haplogroups are also represented by alphanumerical codes. Around 800 haplogroups have been identified in the minimum Yhaplogroup tree (http://phylotree.org/Y/), but there are thousands of Y-haplogroups in total (https://isogg.org/tree/ISOGG_YDNATreeTrunk.html). The major haplogroups A, B, and E, are found across all the continents, being associated with ancient African populations and later with specific Bantu dispersals. In European populations, the sub-haplogroup R1 is highly represented, while in Native American populations the sub-haplogroup Q is highly represented [START_REF] Battaglia | The first peopling of South America: New evidence from Ychromosome haplogroup Q[END_REF]. Sub-haplogroups K and O are found in East Asia (Karafet et al., 2010).

A specific scenario of male migration to Indonesia has been proposed (Karafet et al., 2010) In Madagascar, in contrast to the distribution of mtDNA haplogroups, African Y-chromosome haplogroups (B2*, E2*, and E3*) are more frequent than Asian haplogroups (O1a* and O2a*) at a 2:1 ratio, with a minor input from the Middle East with the presence of haplogroup T* and J* [START_REF] Capredon | Histoire biologique d'une population du sud-est malgache : les Antemoro[END_REF]Razafindrazaka, 2010;Tofanelli et al., 2009). This indicates sex-bias origins of Asian and African lineages in Madagascar. By the further study and comparative analysis of mtDNA and Y-chromosome uniparental markers, complementary scenarios of the parental ancestries of the studied populations will be generated in this thesis. 1.3.4.3. Autosomal SNPs Technological and scientific developments over the last decades have made large-scale, genome-wide investigations feasible and cost-effective. Today, Next Generation Sequencing (NGS) and genome-wide SNP screening is readily accessible to population genetics and clinical genomic research worldwide [START_REF] Goodwin | Coming of age: ten years of next-generation sequencing technologies[END_REF]. Diverse platforms (such as Illumina and Affymetrix) are available to survey a wide spectrum of genetic markers, to investigate human origins and population settlement histories.

Genome-wide data from SNP arrays/sequencing produce large public databases, which are analysed with specific bioinformatic tools to detect demographic/migratory events in population histories (at continental, regional and local scales) and selection signals. For instance, HapMap (International HapMap Consortium, 2010) and HGDP (Li et al., 2008) studies have mapped population diversity in four different continents (Africa, South and East Asia, Europe, and South America). Data from the 1000 Genomes Project was another milestone; the project performed whole-genome sequencing on 2,500 individuals from populations across the world (The 1000 Genomes Project Consortium, 2015). By screening a wide diversity of human population genomes, the results of these large projects help the interpretation of more focused studies. Currently large endeavors are being made to characterise population substructure and history, notably within Africa [START_REF] Busby | Admixture into and within sub-Saharan Africa[END_REF][START_REF] Henn | Hunter-gatherer genomic diversity suggests a southern African origin for modern humans[END_REF], Europe [START_REF] Novembre | Genes mirror geography within Europe[END_REF], the Near East [START_REF] Broushaki | Early Neolithic genomes from the eastern Fertile Crescent[END_REF]; India/South Asia (Moorjani et al., 2013;Reich et al., 2009), East Asia including Indonesia (Aghakhanian et al., 2015;L. Deng et al., 2015;HUGO Pan-Asian SNP Consortium et al., 2009;Lipson et al., 2014;Mörseburg et al., 2016), South America [START_REF] Skoglund | Genetic evidence for two founding populations of the Americas[END_REF], and Oceania (Duggan and Stoneking, 2014;Skoglund et al., 2016;[START_REF] Wollstein | Demographic history of Oceania inferred from genome-wide data[END_REF].

Population genetic studies focusing on Indonesia and Madagascar, using a SNP array technology approach, are still relatively limited (Cox et al., 2016;Pierron et al., 2014;[START_REF] Xu | Genetic dating indicates that the Asian-Papuan admixture through Eastern Indonesia corresponds to the Austronesian expansion[END_REF].

Such genetic studies depend crucially on the accurate and unbiased inference of ancestry, at the genome-wide level and at each locus in the genome, for a bi-fold analysis approach [START_REF] Pasaniuc | Analysis of Latino populations from GALA and MEC studies reveals genomic loci with biased local ancestry estimation[END_REF]. Determining the ancestry of a population has applications ranging from the inference of population history to the estimation of population structure [START_REF] Novembre | Genes mirror geography within Europe[END_REF][START_REF] Rosenberg | Informativeness of genetic markers for inference of ancestry[END_REF], population stratification and admixture history (Patterson et al., 2012), such that most current global populations can trace their ancestry to more than one distinct ancestral group. Populations that result from the admixture of different populations are referred to as admixed populations. For example, African-Americans have 80% African ancestry and 20% European ancestry (International HapMap Consortium, 2010).

In Indonesia, using sets of Ancestry Informative Markers (AIM) SNPs, Indonesian populations can be divided into Papuan and Austronesian/Asian components, forming east-towest gradient (Cox et al., 2010). This study was later confirmed by one that used a larger number of SNPs [START_REF] Xu | Genetic dating indicates that the Asian-Papuan admixture through Eastern Indonesia corresponds to the Austronesian expansion[END_REF]. In Madagascar, the Malagasy uniformly have around 70%

African ancestry and 30% Asian ancestry (Pierron et al., 2014) (Figure 1.13). Many methods have been developed to analyse admixed populations, to estimate the proportion of ancestry derived from each ancestral group, and to infer the time of the admixture event(s). Methods are mostly divided into two types of analyses: descriptive estimation and inference estimation methods (global and local ancestry). Descriptive analysis involves estimating the proportion of ancestry contributed by different populations averaged across the entire genome. Clustering methods such as Principal Component Analysis (PCA) (Patterson et al., 2006), STRUCTURE [START_REF] Pritchard | Inference of population structure using multilocus genotype data[END_REF] and ADMIXTURE (Alexander et al., 2009) have become indispensable tools for investigating population structure in genome-wide data. STRUCTURE and ADMIXTURE have been applied to determine regional levels of clustering and ancestries. The power of PCA analysis can recreate a geographical map of a continent by studying genetic variation within that region [START_REF] Novembre | Genes mirror geography within Europe[END_REF]. These methods are useful to determine population substructure, yet they do not provide any formal tests, such that the Isolation-by-Distance effect can generate similar results to long-distance historical migrations.

There are two types of inference methods: global and local ancestry inference analyses.

Global ancestry usually involves demographic models and phylogenetic. This method infers change in population size, time of admixture and split, and other parameters that can be included in the analysis. This method is run by the Approximate Bayesian Clustering (ABC) computation [START_REF] Beaumont | Approximate Bayesian Computation in population genetics[END_REF][START_REF] Csilléry | abc: an R package for approximate Bayesian computation (ABC)[END_REF]. Local ancestry, such as LAMP [START_REF] Sankararaman | Estimating local ancestry in admixed populations[END_REF], HAPMIX [START_REF] Price | Sensitive detection of chromosomal segments of distinct ancestry in admixed populations[END_REF], PCAdmix (Brisbin et al., 2012), fineSTRUCTURE (Lawson et al., 2012) and GLOBETROTTER (Hellenthal et al., 2014), determine ancestry at each locus in the genome, and provide individual-level information about ancestry, admixture mapping and time of admixture. This method relies on accurate population data given by the exact mixing populations and its sources. The absence of accurate mixing populations can disrupt the precision of the results. This method, however, can provide very useful information on recent admixture events (~5-150 generations ago), but it has a reduced capacity to detect older events (Hellenthal et al., 2014). Hence, the combination of both descriptive and inference methods, an approach used in this study, gives a broader insight into the admixture history of a population.

Disease related markers

During their vast migrations, human groups have encountered a wide spectrum of microorganisms and viruses that have affected their biology. In parallel to the epidemiological interest of these interactions, the study of hijacked genomes and their imprint on human biology is a powerful tool to further explore human history [START_REF] Cassar | Divergent KSHV/HHV-8 subtype D strains in New Caledonia and Solomon Islands, Melanesia[END_REF][START_REF] Cassar | Human T-Cell lymphotropic virus type 1 subtype C molecular variants among indigenous Australians: New insights into the molecular epidemiology of HTLV-1 in Australo-Melanesia[END_REF][START_REF] Moodley | The Peopling of the Pacific from a bacterial perspective[END_REF]Thedja et al., 2011) (Figure 1.14). The geographic distribution of pathogen diversity and host resistance genes are powerful population markers, as humans and pathogens would have co-evolved along the migratory route. One example is the geographic distribution of the Hepatitis B virus overlapping the dispersal route of human mtDNA in Indonesia. Hepatitis B virus (HBV) infection is a major cause of hepatitis. HBV genetic variants have important roles in the development of chronic hepatitis B, and so different prognoses and treatments are made according to the HBV genetic profile present [START_REF] Kao | Hepatitis B virus genotypes and spontaneous hepatitis B e antigen seroconversion in Taiwanese hepatitis B carriers[END_REF][START_REF] Zhang | Genetic variation of hepatitis B virus and its significance for pathogenesis[END_REF]. Until now, researchers have identified eight HBV genotypes: genotypes A to H. Genotype B and C are common in the region of Southeast Asia [START_REF] Lusida | Novel subgenotypes of Hepatitis B Virus genotypes C and D in Papua, Indonesia[END_REF]. A total of eight sub-genotypes HBV/B are present in different regions: B2 in China, B3 in Indonesia, B4 in Vietnam, B5 in the Philippines, and B7 and B8 in Nusa Tenggara. Similarly, the sub-genotype HBV/C is present in different regions: C1, C5 and C6 in Southeast Asia, C2 in East Asia, C3 in the Pacific islands, and C4 in Aboriginal Australian populations. Recent study has shown that the distribution pattern of the HBV genotype in Indonesia has a positive correlation the virus sub-genotype and the ethnic background of the population. For example, HBV sub-genotype B3 is common in ethnic populations in the western part of Indonesia, while HBV sub-genotype B7 is mainly found in ethnic populations in eastern Indonesia [START_REF] Thedja | Ethnogeographical structure of hepatitis B virus genotype distribution in Indonesia and discovery of a new subgenotype, B9[END_REF]. Another example comes from recent studies on the distribution patterns of the Human T-Lymphotropic Virus type 1 (HTLV1) and the Human Herpes Virus 8 (HHV8); both have been used successfully as markers of human migration into Australo-Melanesian regions [START_REF] Cassar | Divergent KSHV/HHV-8 subtype D strains in New Caledonia and Solomon Islands, Melanesia[END_REF][START_REF] Cassar | Human T-Cell lymphotropic virus type 1 subtype C molecular variants among indigenous Australians: New insights into the molecular epidemiology of HTLV-1 in Australo-Melanesia[END_REF][START_REF] Cassar | A novel human T-lymphotropic virus type 1c molecular variant in an indigenous individual from New Caledonia, Melanesia[END_REF]), but they have not yet been used for investigating migrations within ISEA. Both viruses have the ability to integrate their DNA into the human genome, and they have unique characteristics which make them relevant population markers for infected groups: low mutation rate, relative molecular stability and mother-to child mode of transmission. The HTLV1 genotypes are determined from the non-coding Long Terminal Repeat (LTR) region, and the phylogeographical tree is highly discriminative [START_REF] Cassar | Human T-Cell lymphotropic virus type 1 subtype C molecular variants among indigenous Australians: New insights into the molecular epidemiology of HTLV-1 in Australo-Melanesia[END_REF]. There are seven main subtypes of HTLV based on the LTR genomic proviral region: subtype A has a global distribution, subtypes B, D, E, F and G are found in Africa, and the Australo/Melanesian subtype C is found only in Oceania. On the other hand, molecular epidemiology studies on HHV-8 have focused mainly on the variable K1 region (ORF-K1).

This has led to the identification of five main viral subtypes (A, B, C, D, E) that exhibit geographical clustering. Subgroup A1-4 and subtype C are predominant among populations of European descendant in some regions of Asia. Subgroup B1-4 and clade A5 are predominant in Sub-Saharan Africa [START_REF] Betsem | Epidemiology and genetic variability of HHV-8/KSHV in Pygmy and Bantu populations in Cameroon[END_REF]. Subgroups E are found in Native American population, while subgroups D are found in Southeast Asia, Melanesia -Oceania region and Taiwan. Melanesia and Oceania regions have the highest diversity of HHV-8 (Cassar et al., 2007) (Figure 1.15).

In addition to viral diseases, Indonesia, as a tropical country, has many endemic parasitic diseases, including malaria which is caused by the Plasmodium parasite. Parasites and humans have a long history of interaction, and this has been implicit in the evolution of genetically determined disease resistance in humans. In malaria-endemic environments, different biological mechanisms have been selected for in human groups, for example, genetic diseases such as sickle-cell disease in Africa and the Southeast Asian Ovalocytosis (SAO) in Asia. SAO is characterised by the deformation of a patient's erythrocyte membranes into an oval shape [START_REF] O'donnell | Red cell morphology and malaria anaemia in children with Southeast-Asian ovalocytosis band 3 in Papua New Guinea[END_REF]. SAO has autosomal dominant inheritance, and all SAO carriers are heterozygous, because the dominant form of the SAO allele is lethal. In some cases, SAO is not characterised as a disease as it is asymptomatic, causing no health problems to the carrier [START_REF] Allen | Prevention of cerebral malaria in children in Papua New Guinea by southeast Asian ovalocytosis band 3[END_REF][START_REF] Liu | The homozygous state for the band 3 protein mutation in Southeast Asian Ovalocytosis may be lethal[END_REF]. The cause of SAO is a 27-bp deletion in the Solute Carrier Family 4 (AE1) member 1 (SLC4A1) gene [START_REF] Mohandas | Rigid membranes of Malayan ovalocytes: a likely genetic barrier against malaria[END_REF]. This causes a loss of nine amino acids in the protein erythrocyte band 3, which prevents Plasmodium parasites binding with erythrocytes and causing malaria.

SAO has a worldwide distribution in Malaysia, Melanesia, Papua New Guinea, the Philippines, Indonesia and Madagascar [START_REF] Paquette | The evolutionary origins of Southeast Asian Ovalocytosis[END_REF], a distribution which is hypothesised to be related to the Austronesian dispersal towards Indonesia, the Pacific and Madagascar [START_REF] Rabe | South-East Asian ovalocytosis among the population of the Highlands of Madagascar: a vestigé of the island's settlement[END_REF][START_REF] Wilder | Molecular population genetics of SLC4A1 and Southeast Asian Ovalocytosis[END_REF] [START_REF] Rabe | South-East Asian ovalocytosis among the population of the Highlands of Madagascar: a vestigé of the island's settlement[END_REF][START_REF] Wilder | Molecular population genetics of SLC4A1 and Southeast Asian Ovalocytosis[END_REF]. A study conducted on Papua New Guinean populations concluded that the distribution pattern of SAO is positively associated to populations with distinctive Austronesian markers [START_REF] Tsukahara | Austronesian origin of the 27-bp deletion of the erythrocyte band 3 gene in East Sepik, Papua New Guinea inferred from mtDNA analysis[END_REF]. The age of SAO has been estimated, by sequencing the region in the SLC4A1 gene, to around 10,000 years, predating the spread of agricultural practices and the dispersal of the Austronesian language [START_REF] Paquette | The evolutionary origins of Southeast Asian Ovalocytosis[END_REF]. This evidence indicates that SAO was brought by Austronesian people to Papua New Guinea about 3,500 years ago, in agreement with the origin of the Lapita cultural complex in the Bismarck Archipelago (Papua New Guinea). Using diseases as migratory markers can enhance our understanding of global human migration through history, especially in the Indo-Pacific region (Madagascar and the Indonesian archipelago), where studies on viruses and host resistance are scarce.

II. Samples and technical works

Collaborative framework

My thesis is a collaborative study between the Laboratory of Molecular Anthropology and Synthesis Imaging (AMIS) UMR-5288, University of Toulouse (France), and the Eijkman Institute for Molecular Biology (Jakarta, Indonesia). My host laboratory, AMIS, undertakes fundamental research focusing on humans and human diversity, from the first hominids to modern human groups inhabiting different environments across the world. The Eijkman Institute for Molecular Biology is a research institute that undertakes a wide range of studies related to the molecular analysis of the Indonesian populations, from forensic analyses to population genetic histories and disease-related molecular studies. Understanding human genetic structure has fundamental implications for understanding the evolution and impact of human diseases. The study on the genetic structure of Indonesian populations by researchers from the Eijkman Institute has focused on its connection to disease-related molecular epidemiology. This collaboration enriches the exploration of Indonesian population history and global migrations through multidisciplinary studies.

Study populations

Data collection and data privacy

The historical and medical advantages of studying Indonesian population structure is the approach that we used to explain the significance of our study to the people in the villages where we collected samples. Sample collection followed protocols for the protection of 1)). With the assistance of the Indonesian Public Health clinic and Eijkman Institute staff, we also provided medical care and medicines to the participants in each sampling location. The study overview was presented to all the participants, they then filled out a questionnaire that asked for information on their ethnicity, languages spoken and geographic location, for at least the last two to three generations.

Informed consent was signed by each participant, who could withdraw from the study at any time without giving reason. A statement guaranteed the confidentiality of the research participants, indicating that the participants had understood all the information in the consent form and were willing to volunteer/participate in the research. We collected biological samples in the form of blood and saliva samples for genetic analyses (using Oragene (DNA Genotek, Inc.) and/or Norgen (Norgen Biotek Corp.) sampling kit). I collected around ~500 samples during four different fieldwork campaigns, which I organised and conducted. The documentation of sampling activities are displayed in Annex A. I performed the DNA extractions from both blood and saliva samples in the Eijkman Institute laboratory, with the assistance of the Eijkman Institute staff. The detailed methods of the DNA extraction is described in the appended manuscripts. (Karafet et al., 2010;Gunnarsdottir et al., 2011;Tumonggor et al., 2013) and Malagasy populations [START_REF] Capredon | Histoire biologique d'une population du sud-est malgache : les Antemoro[END_REF]Razafindrazaka, 2010;Tofanelli et al., 2009). Each article published in this doctoral study used a different comparative population dataset, and all the data can be found in each article's appended annexes and supporting materials (section VI).

Laboratory and technical works

After the sampling campaigns, I performed DNA extractions from saliva samples using the manufacturer's standard protocols. All DNA extracts were quantified using Nanodrop 2000 (Thermo Scientific). For Y-chromosome haplogroup analysis, I sent the DNA extract to a designated service company (Integragen) in Paris to conduct SNP survies on the Ychromosome. Haplogroups were then estimated from all male samples from surveyed SNPs following international nomenclature (van Oven et al., 2014) (http://www.phylotree.org/Y/).

For mtDNA haplogroup analysis, I worked from the hyper-variable region (HVR) in laboratories in Jakarta and Toulouse. I performed the standard PCR protocol, the mtDNA hypervariable region I was sequenced using primers F15989 (5'CCCAAAGCTAAGATTCT AAT-3') and R389 (5'-CTGGTTAGGCTGGTGTTAGG-3'), the PCR product was purified, Cycle Sequencing PCR using Big Dye Terminator Kit (ThermoFisher Scientific) was undertaken, along with purification using the Ethanol precipitation and EXOSAP procedure.

The purified cycle-PCR products were then sent to sequencing services in both institutions (Genopole Toulouse Midi-Pyrénées, France, and Sequencing Laboratory of the Eijkman Institute for Molecular Biology, Jakarta), to conduct the Sanger sequencing. Mitochondrial haplogroups from all samples were estimated using polymorphisms of HVR sequences of all samples according to Phylotree v. 16 (van Oven and Kayser, 2009).

To complement the above work, I performed whole mitochondrial genome sequencing using

Next-Generation Sequencing, to confirm haplogroup assignment from HVR sequencing, focusing on the Indonesian maternal lineages connected with Madagascar (the B4a* haplogroups). Due to the late time-frame of data generation, analyses of these mitogenomes are not included in this thesis, but they will be investigated further in the near future. I used the capture-based and direct long-range PCR method. For the capture method, I prepared libraries from whole DNA samples using Kit NEBNext E7370S (New England Biolabs)

following the method of [START_REF] Meyer | Illumina sequencing library preparation for highly multiplexed target capture and sequencing[END_REF]. I then conducted the capture protocol from the Centre of GeoGenetics in Copenhagen in collaboration with Dr. Hannes Schroeder, following the method of [START_REF] Maricic | Multiplexed DNA Sequence capture of mitochondrial genomes using PCR products[END_REF]. For the direct long-range PCR method, I prepared libraries from the long-range mtDNA PCR products using a similar library preparation method as above. The libraries were sent to a sequencing service institution in Toulouse (Genopole Toulouse Midi-Pyrénées) to generate the sequencing reads. I built a bioinformatic pipeline to generate sequences from the raw sequencing reads (fastq format).

The haplogroups were estimated using Haplogrep (http://haplogrep.uibk. suggests that the Malagasy language branches from the Southeast Barito language family of southern Borneo, Indonesia, with the closest language spoken today by the Ma'anyan. To test for a genetic link between Malagasy and these linguistically related Indonesian populations, we studied the Ma'anyan and other Indonesian ethnic groups (including the sea nomad Bajo) that, from their historical and linguistic contexts, may be modern descendants of the populations that helped enact the settlement of Madagascar.

Result

A combination of phylogeographic analysis of genetic distances, haplotype comparisons and inference of parental populations by linear optimization, using both maternal and paternal DNA lineages, suggests that Malagasy derive from multiple regional sources in Indonesia, with a focus on eastern Borneo, southern Sulawesi and the Lesser Sunda islands.

Conclusion

Settlement may have been mediated by ancient sea nomad movements because the linguistically closest population, Ma'anyan, has only subtle genetic connections to Malagasy, whereas genetic links with other sea nomads are more strongly supported. Our data hint at a more complex scenario for the Indonesian settlement of Madagascar than has previously been recognized.

Keywords: Ma'anyan, Indonesia, Madagascar, sea nomad, mitochondrial DNA, Y chromosome 3.1.1.2. Introduction Prior to the European colonial period, Austronesian-speaking populations were the most widespread of any language family (Bellwood et al., 1995;[START_REF] Blust | Austronesian: A sleeping giant? Lang[END_REF]. While most groups speaking Austronesian languages moved eastward, settling the Pacific Ocean, others moved westward through the Indian Ocean, reaching eastern Africa and Madagascar. Dispersing halfway around the world within the past two millennia, the Austronesian expansion is often considered the last substantial wave of migration in human prehistory (Blench, 2006;Burney et al., 2004;[START_REF] Kumar | The single most astonishing fact of human geography": Indonesia's far west colony[END_REF].

Despite considerable research on the eastward Austronesian expansion, there is little equivalent research on the western edge, leaving major issues unresolved regarding the settlement of Madagascar. Although the exact nature and route of this movement is largely unknown, linguistic and anthropological evidence indicates strong Indonesian influences, as recorded in the vocabulary and socio-cultural life of Malagasy, the modern people of Madagascar (Adelaar, 2005;[START_REF] Blench | Evidence for the Austronesian voyages in the Indian Ocean[END_REF]Dewar and Wright, 1993;Serva et al., 2012).

Linguistic research suggests that the Malagasy language is derived from Southeast Barito (SEB), a subgroup of Austronesian languages, and is most closely related to the language spoken by the land-locked forest-dweller Ma'anyan in central and southeastern Kalimantan (Borneo) (Adelaar, 2005, 1995a, Dahl, 1991, 1977, 1951), one indigenous language among 73 others spoken in Borneo (Lewis et al., 2016). However, there is evidence of word borrowings from a small number of Austronesian languages spoken on other Indonesian islands as well (Adelaar, 2009(Adelaar, , 2006)). This probably reflects multiple Austronesian arrivals to Madagascar from about 700 AD onward (although earlier dates cannot be completely excluded). One hypothesis is that earlier movements were perhaps linked to Southeast Barito speakers, with later arrivals during the 12th-15th centuries connected instead to the Srivijaya and Majapahit kingdoms of Southeast Asia (Beaujard, 2012a[START_REF] Beaujard | Les arrivées austronésiennes à Madagascar: vagues ou continuum?[END_REF].

These linguistic findings are broadly supported by genetic studies, which emphasize the shared Indonesian and African genetic heritage of Malagasy. A recent study of genome-wide SNP data suggests that the western and central regions of Indonesia (Java/Borneo/Sulawesi) have the closest genetic connections with Malagasy (Pierron et al., 2014). This is in agreement with previous studies of uniparental markers (mtDNA and the Y chromosome), which found genetic affinity between Malagasy and western Indonesian populations (Hurles et al., 2005;Tofanelli et al., 2009). A key lineage linking Indonesia and Madagascar is the Polynesian motif (a mitochondrial DNA haplogroup, B4a1a1, characterized by the polymorphisms A14022G, T16217C, A16247G and C16261T) (Soodyall et al., 1995). More recently, it has been recognized that Malagasy carry specific point mutation variants (mtDNA nucleotides 1473 and 3423), which together have been termed the Malagasy motif (Razafindrazaka et al., 2010). This Malagasy version of the Polynesian motif is distributed throughout Madagascar with frequencies in specific ethnic groups ranging from 11-50% (Capredon et al., 2013;Razafindrazaka et al., 2010;Tofanelli et al., 2009). While still debated, this relatively homogenous distribution has been interpreted as supporting the first arrival of the Polynesian motif during an early phase of Madagascar's settlement (Cox et al., 2012). To date, the Malagasy motif has not been found in Indonesia, or anywhere else outside

Madagascar. However, this may simply reflect the paucity of Indonesian populations available for study.

The westward Austronesian expansion was likely associated with trading activities of the Srivijaya empire, as suggested by the many Malay loanwords present in Malagasy (Adelaar, 2009(Adelaar, , 2005(Adelaar, , 1989)), and this trade has been hypothesized to involve some sea nomad groups (i.e., the Orang Laut, Bajo and Bugis) [START_REF] Beaujard | The first migrants to Madagascar and their introduction of plants: linguistic and ethnological evidence[END_REF](Beaujard, , 2012a;;Pelras, 1997). This trading network was dominated by men, thus hinting at a potential male bias in the Indonesian contribution to Malagasy, in concordance with the standard matrilineal/matrilocal bias of traditional Austronesian society [START_REF] Jordan | Matrilocal residence is ancestral in Austronesian societies[END_REF][START_REF] Lansing | An ongoing Austronesian expansion in Island Southeast Asia[END_REF][START_REF] Marck | Proto Oceanic society was matrilineal[END_REF][START_REF] Peng | Tracing the Austronesian footprint in Mainland Southeast Asia: A perspective from mitochondrial DNA[END_REF]. Contact between the Srivijaya empire and southeast Borneo may have stimulated the dispersal of Southeast Barito speakers to Madagascar -possibly at the same time as the dispersal of Sama-Bajaw speakers from the same area, but a different subgroup of Barito languages (Blust, 2007). In this context, the Bajo are one sea nomad population of particular interest. Today, the Bajo live in several coastal communities around East Borneo, Sulawesi, the Lesser Sunda islands and the Maluku islands (Nuraini, 2008;Stacey, 2007). Because the Austronesian migration to Madagascar and the Sama-Bajaw dispersal may be interrelated, we compare genetic data from recent seafaring populations, such as the Bajo, with the more settled Malagasy.

Similarly, whether Barito populations such as the Ma'anyan, the closest linguistic siblings to modern Malagasy, share close genetic lineages with the Malagasy also remains unanswered.

For the first time, we report genetic data for the Ma'anyan and the Lebbo' (a population from Borneo with no presumed role in the settlement of Madagascar) to determine whether the Ma'anyan have an especially close genetic connection with Malagasy. We also include Bajo sea nomads from Sulawesi to determine whether there is a common genetic link based on their shared involvement in long distance maritime trading networks. A large data set of published and unpublished Indonesian populations is included for comparative analysis (Karafet et al., 2010;Tumonggor et al., 2013) [38, 39]. To investigate sex-specific genetic connections between Indonesia and Madagascar, we analyze both maternal (mtDNA) and paternal (Y chromosome) variation. We propose that the genetic connections of Malagasy to Indonesia are not restricted to Borneo, but instead include maternal and paternal lineages from a wide range of source populations from southern Sulawesi and the Lesser Sunda islands. We therefore propose that the settlement of Madagascar may have been mediated, at least in part, by sea nomad groups.

Methods

Population Samples

All samples analyzed in this study were collected with informed consent from unrelated individuals. Subjects were surveyed for language affiliation, current residence, familial birthplaces, and a short genealogy of four generations to establish regional ancestry We also included data for additional Indonesian populations from published (Gunnarsdóttir et al., 2011;Karafet et al., 2010;Tumonggor et al., 2013) and unpublished sources (Gayo, North Maluku, and a mixed assemblage of other Dayak ethnic groups from the southern part of South Kalimantan province ("SK Dayak") from the Eijkman Institute's archived samples)

(Annex C: Table S1). We also included published Malagasy data: seven Malagasy populations located in the southwest, southeast, and central highlands of Madagascar. The Malagasy were pooled for most analyses as these groups are genetically highly similar (between group FST < 0.05 and 95% of FST values non-significant (P > 0.05) for both mtDNA and the Y chromosome) (Capredon et al., 2013;Razafindrazaka, 2010;Tofanelli et al., 2009).

In total, the mtDNA dataset comprises 529 Malagasy and 2,841 Indonesians, and the Y chromosome dataset comprises 371 Malagasy and 2,095 Indonesians.

DNA Extraction and Genotyping

We collected blood samples for the Ma'anyan, except the Lebbo' and Bajo, for which saliva samples were collected using the Oragene DNA Collection kit (http://dnagenotek.com). DNA was extracted from blood using a standard salting-out procedure, and from saliva using the manufacturer's standard protocol. For paternal lineage analysis, 96 binary markers on the non-recombining region of the Y chromosome were analyzed. We used a nanofluidic dynamic array (Fluidigm, USA) high-throughput genotyping system. This system is developed for SNP genotyping assays and able to perform 9,216 real-time polymerase chain reactions (PCRs) ( 96primers × 96 samples) on a single chip. The results were analyzed using the BioMark™ HD system (Fluidigm, USA) which integrated the Real-Time PCR Analysis software. Each haplogroup was assigned based on the updated ISOGG's Y-DNA haplogroup tree [START_REF] Sudoyo | Mitochondrial genome and susceptibility to diabetes mellitus[END_REF] and the Y-Phylotree [65]. The full list of markers is shown in Annex C: Table S2. The mtDNA hypervariable region I was sequenced using primers F15989 (5'-CCCAAAGCTAAGATTCT AAT-3') and R389 (5'-CTGGTTAGGCTGGTGTTAGG-3'). Sequences (GenBank accession numbers: KM590988-KM591192) were then analyzed and aligned against the revised Cambridge Reference Sequence (rCRS) (Andrews et al., 1999) using the MAFFT aligner v.7 (Katoh and Standley, 2013). Mitochondrial haplogroups were determined with the Haplogrep program (http://haplogrep.uibk.ac.at) based on Phylotree v. 16 (van Oven and Kayser, 2009).

The Malagasy motif, defined by mitochondrial coding region polymorphisms at nucleotides 1,473 and 3,423, were typed on all individuals carrying haplogroup B4a* using the method previously described (Razafindrazaka et al., 2010).

Statistical Analysis

Pairwise FST distances between Indonesian and Malagasy populations were computed from haplogroup frequency data using Arlequin v. S3 and Table S4) was performed to visualize inter-population relations. The nonparametric Mann-Whitney U-test was applied to analyze the statistical significance of genetic affinity between Malagasy and Western/Eastern Indonesian groups. This phylogeographical division was defined by Wallace's line, in agreement with previous human genetic population studies (Cox et al., 2010;Tumonggor et al., 2013;[START_REF] Xu | Genetic dating indicates that the Asian-Papuan admixture through Eastern Indonesia corresponds to the Austronesian expansion[END_REF]. FST values obtained for the pairwise comparison of maternal and paternal lineages between Malagasy and Indonesian populations were plotted geographically with Surfer v.12.0 using the Kriging method. To determine which linear combination of Indonesian populations produces the closest genetic profile to that observed in Malagasy, we employed a statistical analysis of least squares with equalities and inequalities (lsei) algorithm in the R package, limSolve (Van den [START_REF] Van Den Meersche | A Bayesian Compositional Estimator for microbial taxonomy based on biomarkers[END_REF]. To capture sampling variance and drift dynamics, the genetic data were resampled 5,000 times and the linear optimization results visualized with box plots using the R package, ggplot. This analysis used mitochondrial DNA and Y chromosome haplogroup frequency distributions for both Malagasy and Indonesian populations (Annex C: Table S3 and Table S4). An African reference group was used to represent the non-Asian contribution to Malagasy. This reference comprised African samples from populations in North-, East-, Central-and South Africa [START_REF] Cruciani | Phylogeographic analysis of haplogroup E3b (E-M215) Y chromosomes reveals multiple migratory events within and out of Africa[END_REF][START_REF] Harich | The trans-Saharan slave trade -clues from interpolation analyses and high-resolution characterization of mitochondrial DNA lineages[END_REF][START_REF] Rosa | Population data on 11 Y-chromosome STRs from Guiné-Bissau[END_REF][START_REF] Salas | The African diaspora: Mitochondrial DNA and the Atlantic slave trade[END_REF][START_REF] Salas | The making of the African mtDNA landscape[END_REF][START_REF] Tishkoff | History of click-speaking populations of Africa inferred from mtDNA and Y Chromosome genetic variation[END_REF]Wood et al., 2005). Sharing of mitochondrial haplotypes was ascertained using Arlequin v.3.5. For this analysis, sequences from Tofanelli et al. (2009) were excluded due to their short length (360 bp compared to 520 bp for the present study).

Y chromosome and mitochondrial DNA classification

Based on analysis of 96 Y chromosome binary markers (Annex C: Table S2), the majority of men in the Ma'anyan, Lebbo' and Bajo carry haplogroups previously found in Southeast Asia, particularly C*, K*, and O* (Table 1). Only a few individuals carry Y chromosomes belonging to Western Eurasian haplogroups: R* (M207) [START_REF] Hammer | The human Y chromosome haplogroup tree: Nomenclature and phylogeography of its major divisions[END_REF][START_REF] Karafet | New binary polymorphisms reshape and increase resolution of the human Y chromosomal haplogroup tree[END_REF] was found in four Bajo individuals, R1a (M17) [START_REF] Pamjav | Brief communication: New Y-chromosome binary markers improve phylogenetic resolution within haplogroup R1a1[END_REF]Underhill et al., 2010) was found in one Ma'anyan individual, while the western Eurasian haplogroups L1a (M76) and T1a (M70) [START_REF] Mendez | Increased resolution of Y chromosome haplogroup T defines relationships among populations of the Near East, Europe, and Africa[END_REF] were found in one and two Bajo individuals, respectively. Indian haplogroup R*, which includes R1a, has previously been identified in Bali, Java, Borneo, and Mandar (Annex C: Table S3), and thus could conceivably have transited through Indonesia (as opposed to a direct connection), but T1a and L1a have not been identified to date in any Indonesian population.

On the mitochondrial DNA (Table 2), the frequency distributions of haplogroups found in the Ma'anyan, Lebbo' and Bajo are broadly similar, and consistent with, patterns of maternal lineages in Indonesia. Indeed, four main geographical/historical affiliations can be observed:

mainland Asia, the Austronesian expansion, western Eurasia/India, and New Guinea. In brief, mainland Asian mtDNA haplogroups (such as B4c2, M73, M74, M12) are carried by a majority of individuals (64%), followed by haplogroups that have been putatively linked with an Austronesian expansion out of Taiwan (such as B4a1a1, M7c1a4, F1*, E*; 32%). The remaining lineages likely derive from India and west Eurasia, and were only observed among the Ma'anyan (M2, M5a4, and M35a, ranging in frequency from 0.6-1.9%). The presence of Indian and other western Eurasian genetic traces has been observed previously in Borneo, as well as Sumatra, Java and Bali (Gunnarsdóttir et al., 2011;Karafet et al., 2005) (Annex C: Table S4). Indian haplogroups are restricted to western Indonesia, particularly in regions historically involved in the ancient trading networks of the Hindu kingdoms (such as Srivijaya and Majapahit). Among the Bajo, we also observed the M1a Y haplogroup and Q1 mitochondrial haplogroup, which likely traces its ancestry to New Guinea or eastern Indonesia [START_REF] Friedlaender | Melanesian mtDNA complexity[END_REF]Kayser et al., 2003;[START_REF] Mona | Genetic admixture history of eastern Indonesia as revealed by Ychromosome and mitochondrial DNA analysis[END_REF]Tumonggor et al., 2013). These haplogroups represent a trace of Papuan genetic input. This is perhaps due to the extensive trading network of the Bajo eastward to New Guinea (Stacey, 2007) and/or earlier westward expansions of Papuan speakers from New Guinea to eastern Indonesia [START_REF] Donohue | Farming and language in Island Southeast Asia: Reframing Austronesian history[END_REF].

Paternal lineage proximity to Malagasy

Shared lineages

Among the haplogroups shared between Malagasy and Indonesians (Annex C: Table S5), four originated in Island Southeast Asia (C, O1a, O1a2, O2a1*), while six have western Eurasian origins (J1, J2, J2b, T*, L* and R1a). The Ma'anyan and five other Indonesian groups, all located around the Sulawesi sea (east Kalimantan Dayak, Java, Bali, Mandar and Sumba), share four of these Island Southeast Asian haplogroups. Importantly, Malagasy uniquely share just one subhaplogroup (O2a1a1-M88) with Ma'anyan, and this lineage has not been discovered in other regions of Indonesia. O2a1a1 may therefore be a marker of male genetic contributions from southern Borneo to Madagascar. Shared Y chromosome haplogroups with a west Eurasian origin (J, T, L and R1a) (Annex C:

Table S5) are also present in Indonesian populations, but only in the south and west of the Sulawesi sea. They occur at low frequency (<0.1%) in Java, Bali, Mandar and Bajo, but R1a

is the only west Eurasian haplogroup identified in southern Borneo (Ma'anyan and east Kalimantan Dayak). However, west Eurasian lineages in Indonesia and Madagascar may result from independent dispersal events. Indeed, Indian and Arab traders have been active on both side of the Indian Ocean within the last three and one thousand years, respectively (Ardika and Bellwood, 1991;Ardika et al., 1997;Calo, 2014;[START_REF] Donkin | Between east and west: The Moluccas and the traffic in spices up to the arrival of Europeans[END_REF][START_REF] Ferrand | Les musulmans à Madagascar et aux iles Comores[END_REF]Karafet et al., 2005). Therefore, west Eurasian haplogroups shared between Malagasy and Indonesians may have originated from Indonesia, or alternatively, they may have been obtained directly from southwestern Eurasia (the Middle East or India).

Population cross-comparisons

FST values based on Y chromosome haplogroup frequencies (Annex C: Table S6) were visualized on a multidimensional scaling (MDS) plot (Figure 1). Due to their statistically supported genetic homogeneity, Malagasy groups were pooled. The MDS plot (Figure 1)

shows that Malagasy Y chromosome lineages are an outlier to Indonesian populations, in a similar way to certain Indonesian population outliers (Mentawai, Nias, Besemah, Semende).

Y chromosome FST values between Malagasy and Indonesians are relatively high (FST > 0.2;

Annex C: Table S6), mostly driven by the substantial African component of Malagasy (~65% of the paternal gene pool, but only ~30% of mtDNA (Capredon et al., 2013;Razafindrazaka et al., 2010)). No significant differences were observed to suggest specific genetic connections between Malagasy and eastern versus western Indonesians (Mann-Whitney Utest: P = 0.06). The Ma'anyan and other populations from Borneo cluster together with western Indonesian groups, including several population outliers (Mentawai, Nias, Besemah, Semende). The Bajo cluster with eastern Indonesian groups, consistent with the welldocumented genetic division between western and eastern Indonesia broadly along the Wallace line.

When FST values are visualized with Surfer (Figure 2), the Indonesian populations with closest affinity to Malagasy (FST in the lower quartile of the range) are from regions near Wallace's line in the west and south of the Sulawesi sea (southern Sulawesi, eastern Borneo and the Lesser Sunda islands). Populations with highest affinity to Malagasy are Mandar (Sulawesi), Flores (Lesser Sunda), Bajo (Sulawesi), and east Kalimantan Dayak and Lebbo' (Borneo)

(Annex C: Table S6). These results are supported by a linear optimization method, which aims to find the combination of Indonesian populations that most closely resembles the observed haplogroup diversity in Malagasy. This algorithm highlights two populations from the west and south of the Sulawesi sea, the Mandar (Sulawesi) and Lebbo' (Borneo), as populations that produce a Y chromosome genetic profile most closely resembling the observed pattern, which still accounting for the predominantly African genetic background found in Malagasy (Annex C: Figure S1).

These geographical regions comprised part of the trading sphere of the Srivijaya empire, including several Javanese kingdoms that played a crucial role in the region: Heluodan (5 th century), Tarumanagara (5 th century), Walaing (Chinese Heling, 7 th -8 th centuries), Kahuripan/Kediri (11 th century), Singasari (13 th century) and Majapahit (13 th -15 th centuries) (Beaujard, 2012b). This region also hosted several houseboat nomad groups (such as the Bajo), which had ample opportunities to incorporate men from a wider regional watershed.

The

Maternal lineage proximity to Malagasy

Shared lineages

Malagasy and Indonesians share mitochondrial haplogroups B4a1a, B4a1a1 (Polynesian motif), E1a1a, F3b, M7c1a4a, M32c and Q1 (Annex C: Table S7). Of these, B4a1a1, E1a1a and Q1 are found exclusively in eastern Indonesia. Conversely, F3b, B4a1a and M7c1a4a occur ubiquitously across both eastern and western Indonesia, and M32c has been observed in only one Javanese individual.

The Polynesian motif (B4a1a1) is considered strong evidence of Indonesian gene flow into Madagascar, where a variant is found at moderate frequency (11-50%). With the exception of Bali (Annex C: Table S4), B4a1a1 only occurs in eastern Indonesia. For the three new populations studied here, only the Bajo carry this Polynesian motif (just one of 27 individuals), and importantly, it was not found in any of our populations from Borneo.

Furthermore, the specific Malagasy motif has not been found in Indonesia at all, including the new populations screened here. Considering the restricted geographic distribution of the Polynesian motif, it is most likely that this lineage from Madagascar traces back to eastern rather than western Indonesia.

Population cross-comparisons

The MDS plot (Figure 4, Malagasy groups again pooled), which is based on FST values from mtDNA haplogroup frequencies (Annex C: Table S4), shows that Malagasy maternal lineages differ markedly from those of Indonesians, while paternal lineages appear relatively closer (Figure 1). Unlike the Y chromosome data, which favors both eastern and western Indonesian sources, Malagasy are closer to the mtDNA diversity of eastern rather than western Indonesians (Mann-Whitney U test: P < 0.01). FST values (Annex C: Table S9) visualized in Surfer (Figure 5) show that the regions with closest affinity occur to the south and east of Sulawesi, and support an eastern Indonesian connection. Populations with higher affinity to Malagasy (FST in the lower quartile of the range) include Sumba and Flores, the Maluku islands and the Bugis of south Sulawesi. As seen on the Y chromosome, the Bajo cluster with eastern Indonesian groups, while the Ma'anyan and other populations from Borneo cluster with western Indonesian groups. Linear optimization results broadly agree with the FST results: Malagasy are most likely derived from a combination of eastern Indonesian groups, such as North Maluku, Bugis and Bajo (Annex C: Figure S2). Indonesia (Oppenheimer and Richards, 2001;Soares et al., 2011). It is worth noting that eastern Indonesian influences occur in Madagascar: for cultivated plants (i.e., myths of origins, rituals for yams, the ancient importance of taro) (Beaujard, 2012a[START_REF] Beaujard | The first migrants to Madagascar and their introduction of plants: linguistic and ethnological evidence[END_REF], and through 56 the influence of the Orang Laut language on some Malagasy dialects (particularly the Vezo) (Dahl, 1991). Eastern Indonesia had no recorded sea-faring cultures involved in long-distance trading, except for the Bugis and Bajo. However, maritime foraging and trade were likely more common in earlier millennia as networks of long-distance sea-based interactions have been in place since at least the early Holocene (Bulbeck, 2008).

Discussion

The Southeast Barito language subgroup includes two languages spoken by populations separated by the 7,500 km expanse of the Indian Ocean: the Malagasy of Madagascar, off the east coast of Africa, and the Ma'anyan of Borneo, an island in western Indonesia. Knowing this linguistic connection, we investigated genetic linkages between these two populations.

Our results suggest that few genetic connections exist, either on the paternal Y chromosome or the maternal mtDNA. These results suggest that 1) the Ma'anyan groups sampled here are not directly related to the individuals who settled Madagascar, 2) subsequent demographic events have erased any genetic affinity between them, or 3) the Ma'anyan were just one population of many that contributed to the settlement of Madagascar (a possibility suggested by the exclusive sharing of Y chromosome haplogroup O2a1a). The first hypothesis might suggest that other Southeast Barito groups from southern Borneo (such as the Samihim or the Dusun Witu (Adelaar, 1995b)) were involved instead.

These conclusions are drawn from a suite of complementary analyses, including phylogeography, haplotype sharing and linear optimization approaches. In combination, they paint a picture of the genetic dynamics between Indonesia and Madagascar. Although the geographic distribution of Indonesian populations that most closely reflect Malagasy genetic diversity are remarkably convergent for both male and female lineages, it is noticeable that the regions suggested by these two systems do not overlap perfectly. Our analyses suggest that populations from the south and west of the Sulawesi Sea (east Borneo, south Sulawesi and the Lesser Sunda islands) best explain Y chromosome diversity, while populations from the south and east of Sulawesi (south Sulawesi, the Lesser Sunda islands and the Maluku islands), all in eastern Indonesia, best explain mtDNA diversity. We emphasize that parts of these two regions overlap, thus potentially explaining both paternal and maternal affinity.

For instance, the distribution of shared lineages favors different source populations for maternal and paternal loci. Y chromosome haplogroup O2a1a is found only in Ma'anyan, while mtDNA haplogroups B4a1a1 and Q1 are found exclusively in eastern Indonesia.

(Suggesting yet more connections, M32c has only been found in Java). FST and linear optimization results also highlight different source regions for the Y chromosome and mtDNA. Together, these patterns suggest that multiple regions may have contributed to the settlement of Madagascar, perhaps via one or a few admixed groups.

Sea nomads have been active traders along the eastern coast of Borneo, southern Sulawesi, the Lesser Sunda islands and the Maluku islands for at least the last few hundred years (Sather, 1997;Verheijen, 1986). These mobile populations linked western and eastern Indonesia, and absorbed individuals from different regions. Sea nomads traveled with their families, even on long distance journeys (Nuraini, 2008;Stacey, 2007). Moreover, languages of the Sama-Bajaw group, as spoken by the sea nomad Bajo, form a subgroup of the Barito languages of southeast Kalimantan (Blust, 2007), although not the closest language subgroup to Malagasy. Their patterns of genetic diversity and lifestyle make them possible contenders for the Indonesian populations who helped enact the settlement of Madagascar, although a definite assignment remains elusive.

Conclusion

We propose that the settlement of Madagascar had an Indonesian source location around southern Sulawesi, the Lesser Sunda islands and eastern Borneo. The populations involved may be related to modern sea nomad groups and the ancient Malay Srivijaya trading network.

The Indonesian ancestors of Malagasy certainly carried maternal lineages with greater putative contributions from eastern Indonesia, and paternal lineages from both eastern and western Indonesia. The absence of any clear genetic connection between Malagasy and at least some populations speaking their most closely related language, Ma'anyan, raises important questions about the link between genes and language in the Indonesian dispersal across the Indian Ocean. Studying other Southeast Barito and sea nomad groups (such as the Orang Laut, who played a crucial role in the Srivijaya expansion) and the application of genome-wide genotyping technologies to provide additional genetic resolution promises to bring new insight to bear on these questions. (Ardika and Bellwood, 1991;Ardika et al., 1997;Calo, 2014;Lawler, 2014). Indianization and Islamization in Indonesia led to the development of Hindu, and later Islamic, kingdoms between the 5th and 15th centuries, which reinforced interactions and influence from Western Eurasia to all the regions in western and central Indonesia spanned by these kingdoms (Beaujard, 2012a(Beaujard, , 2012b;;Gonda, 1975;Kanchan, 1990). These interactions brought not only new ideas and trade goods into the Indonesian archipelago, but were also accompanied to some degree by gene flow, which contributed to a number of modern Indonesian populations.

Considering the historical events of the last two millennia, it has been variously postulated that WE genetic influx into Indonesia could have originated from India [START_REF] Lansing | The "Indianization" of Bali[END_REF][START_REF] Lukas | Theories of Indianization exemplified by selected case studies from Indonesia (Insular Southeast Asia), in: Sanskrit in Southeast Asia: The harmonizing factor of cultures[END_REF][START_REF] Mabbett | The "Indianization" of Southeast Asia: Reflections on the Historical Sources[END_REF], the Near East (Jacobsen, 2009) or Europe (Dutch colonialism) [START_REF] Taylor | The social world of Batavia: Europeans and Eurasians in colonial Indonesia[END_REF]. The genetic evidence so far suggests that the primary contribution came from the Indian subcontinent (HUGO Pan-Asian SNP Consortium et al., 2009;Karafet et al., 2005Karafet et al., , 2010)), but there is still debate regarding the importance of Indian gene flow, and its geographic diffusion into and impact on the Indonesian archipelago, with some scholars proposing colonization by Indian exiles [START_REF] Majumdar | Ancient Indian colonization in South-east Asia[END_REF], large scale migration establishing Indian colonies in South East Asia [START_REF] Mabbett | The "Indianization" of Southeast Asia: Reflections on the Historical Sources[END_REF], or more punctuated contact by Indian traders [START_REF] Lansing | The "Indianization" of Bali[END_REF][START_REF] Sandhu | Indian communities in Southeast Asia[END_REF]. Historical evidence mentions the "constant flux of people from Gujarat and neighboring regions" (in the Indian sub-continent) to Java (Beaujard, 2012b(Beaujard, , 2012a)). Indeed, genetic traces of paternal Indian ancestry have been detected at low frequency in Indonesia (<10%) (Karafet et al., 2005(Karafet et al., , 2010) ) across several islands (Sumatra, Java, Borneo and Bali), but in comparison, no Indian maternal lineages have been detected (Tumonggor et al., 2013). The influx of Indian ancestry has also been observed from genome-wide analysis using a limited number of nuclear SNPs (HUGO Pan-Asian SNP Consortium et al., 2009) in just a few populations from western Indonesia (Sumatra).

However, Indian markers in autosomal data were not detected in large-scale genotyping of eleven populations across Island Southeast Asia [START_REF] Pugach | Genome-wide data substantiate Holocene gene flow from India to Australia[END_REF].

Our study is based on the largest dataset of maternal (mtDNA) and paternal (Y chromosome) lineages assembled for the Indonesian archipelago to date, and aims to map West Eurasian genetic influences in this region. We propose that genetic contributions from West Eurasia (such as India) are mostly restricted to the areas where Indianized kingdoms were most powerful. We also show that genetic contact with both Indian men and women was involved.

3.1.2.3. Material and methods

DNA samples and data sources

Indonesian samples used in this study have been described previously (Gunnarsdóttir et al., 2011;Karafet et al., 2010;Kusuma et al., 2015;Tumonggor et al., 2013). In brief, the mtDNA dataset includes 2,841 individuals, and the Y chromosome dataset includes 2,095 individuals, from 7 major Indonesian islands and representing 22 and 17 different ethnic groups, respectively (Table 1). These two datasets represent the largest Indonesian genetic assemblage studied to date.

Haplogroup assignment

Mitochondrial DNA hypervariable region I sequences were compiled from published sources (Table 1) and aligned against the revised Cambridge Reference Sequence (rCRS) (Andrews et al., 1999) using the MAFFT aligner v.7 (Katoh and Standley, 2013)

Statistical analysis

Mitochondrial DNA and Y chromosome West Eurasian haplogroup frequencies in Indonesian populations were plotted geographically with Surfer v.12.0 using the Kriging method.

Mitochondrial DNA and Y chromosome haplogroup diversity was calculated using Nei's method [START_REF] Nei | Molecular evolutionary genetics[END_REF] S3). This is in agreement with the putative geographical origins of the WE haplogroups found in Indonesia. Indeed the source locations of WE mtDNA and Y haplogroups found in Indonesian populations do not overlap perfectly (Annex D: Table S1 and S2). The 13 WE mtDNA haplogroups are primarily derived from South Asia (mainly the Indian sub-continent). Conversely, the 15 WE Y chromosome haplogroups in Indonesia exhibit more diverse origins, yet South Asia remains the most frequent point of origin. The most common Y chromosome haplogroup is R1a1a (M17), which was observed in 5 of the 7

Indonesian populations that carry WE haplogroups, followed by R2a in 4 populations.

Outside Indonesia, R1a1a and R2a (M124) have similar distributions with relatively high frequencies in South Asia [START_REF] Sengupta | Polarity and temporality of high-resolution Y-Chromosome distributions in India identify both indigenous and exogenous expansions and reveal minor genetic influence of Central Asian pastoralists[END_REF]Underhill et al., 2010). For mtDNA, M5 is the most frequent haplogroup found in Indonesia, observed in 4 of 9 populations that carry WE haplogroups. Outside Indonesia, M5 is mainly found in India [START_REF] Sahoo | Phylogeography of mitochondrial DNA and Y-Chromosome haplogroups reveal asymmetric gene flow in populations of Eastern India[END_REF][START_REF] Sun | The dazzling array of basal branches in the mtDNA macrohaplogroup M from India as inferred from complete genomes[END_REF][START_REF] Thangaraj | In situ origin of deep rooting lineages of mitochondrial Macrohaplogroup "M" in India[END_REF]. A PCA plot of the distribution of Western Eurasian versus Asian lineages among Indonesia populations (grouped by island) also supports these results (Figure 2). The strongest West

Eurasian influence on the paternal gene pool can be seen in populations from Java, Bali, and Sulawesi. The strongest WE influences on the maternal gene pool are found in Java, Sumatra, and the Lesser Sunda islands. Java is the only population that received a strong WE contribution for both paternal and maternal lineages (14.8% and 7.84%, respectively). 3.1.2.5. Discussion

New archaeological evidence shows that a network of interactions moved goods and ideas across the Indian Ocean at least 2,000 years B.C.E (Lawler, 2014). Island South East Asia, and particularly the Indonesian archipelago, joined this network later in the 1st century B.C.E., with connections initially mostly with India (Ardika and Bellwood, 1991;Ardika et al., 1997;Calo, 2014). This promoted West Eurasian influences in Indonesia, and Indianized cultures became widespread in Indonesia shortly afterwards. Typical influences included old writings in Sanskrit, shadow puppets (wayang) and dances, sculptures, vast Hindu temples in Java and Bali, and modified socio-cultural structures (such as the caste system in Bali) [START_REF] Coedes | The Indianized states of Southeast Asia[END_REF][START_REF] Covarrubias | Island of Bali[END_REF][START_REF] Dumarcay | The temples of Java[END_REF][START_REF] Guy | Lost Kingdoms: Hindu-Buddhist sculpture of early Southeast Asia[END_REF]Kanchan, 1990;[START_REF] Mellema | Wayang puppets. carving, colouring and symbolism[END_REF][START_REF] Pigeaud | Java in the 14th century: a study in cultural history : the Nāgara-Kĕrtāgama by Rakawi Prapañca of Majapahit, 1365 A.D[END_REF][START_REF] Sumarsam | Gamelan: Cultural interaction and musical development in Central Java[END_REF]. Indian influences were accepted and frequently assimilated by Indonesians, and spread through many Hindu and Islamic kingdoms in Indonesia, such as Heluodan (5 th century), Tarumanagara (5 th century), Walaing (7 th -8 th centuries), Kahuripan/Kediri (11 th century), Singhasari (13 th century), and Majapahit (13 th -15 th centuries) (Beaujard, 2012a(Beaujard, , 2012b)). In parallel to cultural and trading influences, movements of people from South and Southwest Asia to Indonesia also likely occurred, but their impact on the gene pool of modern Indonesia has been debated and required further investigation.

Our study shows that a West Eurasian genetic contribution exists at non-negligible levels.

Frequency distributions of West Eurasian maternal and paternal lineages in Indonesian populations suggest that 1) about the same number of Indonesian populations (~40%) carry WE paternal and/or maternal haplogroups, 2) populations with the highest WE contributions are found in central Indonesia, to the south of the Celebes sea, 3) WE input is more frequent in the paternal (4.49%) than maternal (1.55%) Indonesian gene pool, and 4) the geographical origin of WE maternal and paternal haplogroups suggest a preponderance of haplogroup sources in South Asia (the Indian sub-continent).

WE paternal lineages are more frequent than maternal lineages (4.49% versus 1.55%), but also seem to be sourced from across a broader geographical area (South West and South Asia)

(Annex D: Table A1 andA2) than maternal lineages, which are mainly derived from the Indian sub-continent. This may be due to a male bias in trading activities, which are presumed to have been dominated by men, and also fits the hypothesis that Indian influence was not restricted only to trading/cultural activities, but involved a substantial movement of men, and importantly women, from the Indian sub-continent into Island South East Asia (Beaujard, 2012a(Beaujard, , 2012b;;[START_REF] Mabbett | The "Indianization" of Southeast Asia: Reflections on the Historical Sources[END_REF].

Interestingly, traces of Western Eurasian genetic lineages are mostly observed in regions where ancient Hindu and Islamic kingdoms were located. These kingdoms governed their regions in separate, but often overlapping, time frames from the 7 th to 16 th centuries. For example, Srivijaya was based in Sumatra; Majapahit, Singasari and Kahuripan/Kediri in Java;

Kutai in Kalimantan and Sulawesi; and Buleleng in Bali and neighboring islands in the Lesser Sunda chain (Beaujard, 2012a(Beaujard, , 2012b;;Kanchan, 1990;[START_REF] Pigeaud | Java in the 14th century: a study in cultural history : the Nāgara-Kĕrtāgama by Rakawi Prapañca of Majapahit, 1365 A.D[END_REF][START_REF] Wolters | Early Indonesian commerce: A study of the origins of Srivijaya[END_REF]. Later, Islamic kingdoms arose in northern Sumatra around the 14th century, influenced culturally by Arab (Near East) or Gujarat traders (India) [START_REF] Ali | Islam in Indonesia[END_REF][START_REF] Ricklefs | A History of modern Indonesia since C. 1300[END_REF]. In this study, WE traces are found in East Kalimantan, Sulawesi, Java, Bali, and northern Sumatra for both paternal and maternal lineages, and in the Lesser Sunda islands for maternal lineages. This indicates that the influence of Indianized/Islamic kingdoms in Indonesia was not restricted simply to cultural assimilation, trading and economical or political power, but was also associated to some degree with gene flow into Indonesia from cultural and/or trading centers in South and South West Asia.

Conclusion

West Eurasian influences into Island South East Asia helped shape the genetic background of modern Indonesian populations. Despite their relatively small genetic impact, aside from its huge cultural impact, Western Eurasian lineages are found in both the paternal and maternal Indonesian gene pools suggesting that contact extended beyond cultural and trading activities to at least some small-scale population movements coupled with long-term settlement. The exact small-scale geographical sources of these West Eurasian contributions still need to be clarified, but genetic evidence indicates slightly different origins for paternal and maternal Western Eurasian lineages, while emphasizing the major role played by the Indian subcontinent. Further genetic studies will need to be performed using larger sample sizes and a broader array of genetic markers (including genome-wide genotyping) in order to provide additional information on the exact sources, timing, and modality of the West Eurasian contribution into Indonesia.

Introduction

The Austronesian expansion was a major human migration in Southeast Asia, triggered by the spread of agricultural populations approximately 5,000 years ago (Bellwood et al., 1995;Bellwood, 2007;Oppenheimer and Richards, 2001).Thought to have originated in Taiwan, its influence spread through Philippines and Indonesian archipelago, ultimately impacting a wide geographical area ranging from Remote Oceania in the east, to Madagascar and the eastern coast of Africa in the west (Bellwood, 2007;Blench, 2006;Soares et al., 2011). This expansion had outsized cultural and genetic impact on these territories, but the populations caught up in the dispersal were regionally different and diverse across the Indo-Pacific. This created a diverse modern range of Austronesian populations with their own cultural traits and genetic heritage, among which Madagascar is a unique case.

Despite clear evidence, based on biological (Hurles et al., 2005;Kusuma et al., 2015;Pierron et al., 2014;Soodyall et al., 1995;Tofanelli et al., 2009) and linguistic data (Adelaar, 2009;Serva et al., 2012) of Malagasy's mixed ancestry with both African and Southeast Asian groups, identifying the parental populations of Malagasy and clarifying the process of settling Madagascar around the middle of the first millennium AD [START_REF] Burney | Late Holocene vegetational change in central Madagascar[END_REF]Burney et al., 2004; MacPhee and Burney, 1991) has remained complex. Language studies have identified many linguistic characters that relate Malagasy to languages spoken in Borneo, notably in the Southeast Barito region. This includes much vocabulary and structural linguistic agreement shared between Malagasy and Southeast Barito languages, which form a subgroup of West Malayo-Polynesian languages in the Austronesian language family (Adelaar, 1989, 2005, 2006, 2009, Dahl, 1951, 1977, 1991). Among the communities speaking Southeast Barito languages, the Ma'anyan show linguistic characteristics that place them as the closest known Asian parental population to Malagasy (Adelaar, 1995;Dahl, 1951Dahl, , 1977Dahl, , 1991;;Lewis et al., 2016). Curiously, the Ma'anyan are an indigenous ethnic group representing approximately 70,000 individuals, who live in remote inland areas of central and southeastern Kalimantan (the Indonesian part of the island of Borneo). Today, the Ma'anyan are largely agricultural, cultivating dry rice on shifting fields, but also gathering forest products [START_REF] Hudson | The Padju Epat Ma'anjan Dajak in historical perspective[END_REF]. They do not exhibit any particular mastery of seafaring technologies or navigational knowledge (Adelaar, 1995), raising questions about how a closely related language travelled across the vast Indian Ocean and came to be spoken in Madagascar. However, in historical times, the south Borneo coastline was split by a gulf that may have extended 200 kilometres into the interior (Adelaar, 2017;Van Bemmelen, 1949), thus potentially placing Ma'anyan communities that are firmly inland today in what was then a formerly coastal environment.

Several genetic studies have sought to detect Indonesian genetic connections in the Malagasy genome (including mitochondrial DNA, Y chromosome and autosomal markers) (Hurles et al., 2005;Kusuma et al., 2015;Pierron et al., 2014;Soodyall et al., 1995;Tofanelli et al., 2009), but no clear parental groups in Southeast Asia have yet been identified. The limited geographical coverage of Indonesian populations in these studies (including the absence of key populations such as the Ma'anyan) has often prevented precise conclusions. The possibility that the Ma'anyan are the Asian parental source of Malagasy was first explored genetically using uniparental markers (mitochondrial DNA and the Y chromosome) only in 2015 (Kusuma et al., 2015). This preliminary study, which covered a range of Southeast Asian groups, linked the origins of the Asian genetic components in Malagasy to modern populations located between Sulawesi (eastern Indonesia) and eastern Borneo (western Indonesia), thus confirming the general results of earlier studies (Tofanelli et al., 2009).

However, surprisingly, the Ma'anyan shared few mtDNA or Y chromosome lineages with Malagasy. Given this apparent contradiction between linguistic evidence and genetic analyses of uniparental markers, and to overcome the potential bias of this lineage-based approach (which is more sensitive to genetic drift), a genome-wide analysis of Southeast Borneo individuals was deemed necessary to better explore the link between Madagascar and Borneo.

Here, we perform that genome-wide analysis in the Ma'anyan and other groups from southern Borneo to determine the genetic background and potential Asian sources of the Malagasy.

Using Illumina HumanOmniExpress Bead Chips, we genotyped over 700,000 genomic markers in 169 Ma'anyan individuals, together with a further 42 individuals from Dayak ethnic groups across southern Borneo. The aims of this study were dual: i) to examine the genetic diversity of populations in southeastern Borneo (focusing on the Ma'anyan and other indigenous Dayak groups), and thereby determine their place in the wider genetic diversity of Island Southeast Asia; and ii) to identify whether the clear linguistic relationship between the Ma'anyan and Malagasy is also reflected in a shared genetic inheritance.

Methods

Sample collection and ethics

A total of 211 DNA samples were analysed from two groups in Borneo: The Ma'anyan ethnic group (169 individuals), and the South Kalimantan Dayak, which comprises a mixed assemblage of diverse Dayak ethnic groups (42 individuals) (Figure 1 and Annex E: Table S1). The samples used in this study have been described previously (Kusuma et al., 2015).

Briefly, blood samples were collected from healthy adult donors, all of whom provided written informed consent. DNA was extracted using a standard salting-out procedure. All participants were surveyed for language affiliation, current residence, familial birthplaces, and a genealogy of four generations to establish ancestry. This study was approved by the Research Ethics Commission of the Eijkman Institute for Molecular Biology (Jakarta, Indonesia), and the methods were carried out in accordance with the approved guidelines.

Genome-wide SNP genotypes for the two groups were generated using the Illumina Human Omni Express-24 v1.0 Bead Chip (Illumina Inc., San Diego, CA), which surveys 730,525 single nucleotide markers regularly spaced across the genome. Genotyping data are available upon request.

Dataset integration

Two datasets were compiled from previous published data to fulfill key analytical criteria: i) the low density dataset has wide geographical coverage, but includes relatively few SNPs;

while ii) the high density dataset has greatly increased SNP density, but includes fewer populations. This approach, which is necessitated by the wide range of DNA genotyping chip technologies used by the scientific community (Supplementary Table S5), allows us to address the widest range of questions.

Filtering and quality controls were performed using PLINK v1.9 (Chang et al., 2015): i) to avoid close relatives, relatedness was measured between all pairs of individuals within each population using an Identity-by-Descent (IBD) estimation with upper threshold of 0.25 (second degree relatives); ii) SNPs that failed the Hardy-Weinberg exact (HWE) test (P < 10 - data quality. This low density dataset includes East and Southeast Asian populations (Mörseburg et al., 2016), Indonesian populations including the Lebbo' and Bajo (Pierron et al., 2014), and groups from Sumba (Cox et al., 2016), together with CEPH-HGDP data (Li et al., 2008), HUGO Pan-Asian SNP data (HUGO Pan-Asian SNP Consortium et al., 2009) and data for three Malagasy populations (Mikea, Vezo and Temoro) (Pierron et al., 2014) (Annex E: Table S1). The final high density dataset comprises a subset of the populations in the low density dataset, specifically covering 311,871 SNPs in 820 individuals from 28 populations.

Population structure analysis

The low density dataset was analysed using the following approaches. Genetic diversity was described using pairwise FST distance calculations and Principal Components Analysis using the 'smartpca' algorithm of EIGENSOFT v6.0.1 (Patterson et al., 2006). The Runs of Homozygosity (ROH) analysis was performed in PLINK v1.9 from the linkagedisequilibrium-pruned dataset. ADMIXTURE v1.23 (Alexander et al., 2009) was used to estimate the profile of individual genomic ancestries using maximum likelihood for components K = 2 to K = 20. Ten replicates were run at each value of K with different random seeds, then merged and assessed for clustering quality using CLUMPP (Jakobsson and Rosenberg, 2007), and the cross-validation value was calculated to determine the optimal number of genomic components (here, K = 14). ADMIXTURE and PCA plots were generated with Genesis and the results were confirmed using the high density dataset, to avoid any misinterpretation due to a potential bias driven by the density of SNPs. Gene flow between populations was investigated using two different approaches: i) SNP frequencies using TreeMix v1.12 (Pickrell and Pritchard, 2012)

The unique Austronesian origin of the Ma'anyan

Following quality control, we obtained genotypes for 701,211 SNPs in a new set of 202 individuals from Borneo: 162 Ma'anyan and 40 South Kalimantan Dayak (SK-Dayak). To characterize the Ma'anyan and SK-Dayak gene pool within an Asian context, we focused our analyses on Island Southeast Asian, East Asian and Mainland Southeast Asian populations (Fig. 1). In a Principal Component Analysis (PCA) using a subset of the SNPs that intersect with published data from an extensive range of regional populations (the low density dataset)

(Annex E: Figure S1), the first principal component (explaining 19.3% of the variance)

separates Island Southeast Asian populations from East Asian and Mainland Southeast Asian groups, while the second principal component (explaining 17.5% of the variance) splits the Igorot on the positive axis and the Ma'anyan on the negative axis, with other Austronesianspeaking populations falling in between, such as Taiwanese aborigines, Filipinos, Borneo populations (Murut, Dusun, Lebbo' and South Kalimantan Dayak) and Sumatran populations (Sumatran Malay and Karo). Other Austronesian-speaking groups, like the Bidayuh, Javanese and Malaysians cluster towards mainland Southeast Asia, likely due to the historical influence of that region on these groups. Interestingly, the Ma'anyan form their own pole on the plot and do not cluster closely with other populations from Borneo, although the genetically closest population is still the South Kalimantan Dayak group, which is also geographically the nearest neighbour to the Ma'anyan. A similar population clustering pattern is observed with both the low-and high density SNP datasets (Annex E: Figure S2). This observation also agrees with FST values calculated on the low density dataset (Annex E: Table S2).

This unique genetic placement of the Ma'anyan is supported by admixture estimates, also performed on the low density dataset (Figure 2), especially at K=14 where it achieves its lowest cross-validation value (Annex E: Figure S3). The main ancestral components observed in Southeast Asian populations are: i) an Austronesian Igorot and indigenous Taiwanese component (C3; light green), ii) a Mainland Southeast Asian (MSEA) component (C11; light brown); and iii) a Papuan component (C2; light blue). However, our analysis reveals a major new component in Island Southeast Asia, representing 80% to 95% of the ancestry in Ma'anyan individuals (C8; dark blue). This Ma'anyan component is also found using an ADMIXTURE analysis on our high density SNP dataset (Annex E: Figure S4a andS4b). The remaining ancestry components in the Ma'anyan also occur in most of the other Indonesian populations, and may result from shared history and/or limited gene flow between the Ma'anyan and neighbouring populations. In return, the new C8 component identified in the Ma'anyan is also found at much lower frequencies in many other Indonesian groups, reaching its highest frequency in surrounding populations of Ma'anyan in Borneo (~40%), but also appearing in some mainland Southeast Asian populations. To determine whether this distinct and homogenous genetic component in the Ma'anyan results from genetic drift (due to geographic isolation and/or endogamy), we inferred the extent of 'Runs of Homozygosity' (ROH) in the full high density dataset. Homozygosity in the Ma'anyan is similar to that of other Borneo populations (Annex E: Figure S5), even though these show much higher levels of admixture (Figure 2). However, homozygosity in the Ma'anyan is lower than in the Igorot, an isolated, indigenous Austronesian-speaking population living in the Philippine highlands. This suggests that the unusual homogeneity and unique ancestry component found in the Ma'anyan reflects the population's migration history, rather than simply resulting from high levels of genetic drift. Genetic drift has also potentially occurred in the Igorot, and other isolated ethnic populations that exhibit low genetic diversity and have small population size (such as the Mlabri) [START_REF] Oota | Recent origin and cultural reversion of a Hunter-Gatherer group[END_REF][START_REF] Xu | Genetic evidence supports linguistic affinity of Mlabri -a hunter-gatherer group in Thailand[END_REF], or that show a high level of consanguinity (such as the Malay Negritos) (Aghakhanian et al., 2015).

An f3-statistics analysis reveals more clearly that the Ma'anyan is not an admixed population

(Annex E: Table S3). Defining the Ma'anyan as the daughter group, all possible combinations of populations in the low density dataset returned positive f3 statistics with Z-scores > -2, indicating no significant gene flow. In addition, a TreeMix analysis supported eight migration events, none of which involved gene flow to or from the Ma'anyan (Annex E: Figure S6). In contrast, a migration event was supported from the basal cluster of MSEA Austroasiaticspeaking H'tin and Mlabri to the Bidayuh, a population in northwest Borneo. This suggests that MSEA gene flows reached the west of Borneo, but not the east.

To test whether the Ma'anyan gene pool has drifted from its original Austronesian or MSEA ancestry, we performed an f3-outgroup statistics analysis (Figure 3a). All Island Southeast Asian populations, except the Bidayuh, Javanese and Sundanese, were pulled to the Austronesian side (as defined by the Taiwanese aborigines). Conversely, mainland Southeast Asian groups were pulled to the MSEA side (as defined by the H'tin). The Ma'anyan fall in the upper left diagonal of the plot, indicative of genetic similarity with Austronesian rather than MSEA groups. To determine the closest population to the Ma'anyan, the configuration f3(Yoruba; Ma'anyan, x) was explored, where x represents all populations in turn in the low density dataset. The highest value was obtained when x was the Igorot from the Philippines or non-Ma'anyan Borneo populations (Figure 3b), a result that is also obtained when using the high density dataset. These results place the genetic diversity of the Ma'anyan within the broader Austronesian gene pool.

The Island Southeast Asian ancestries of the Malagasy

We performed PCA using the low density dataset, finding that the first two components described 54.6% of the observed variance (Annex E: Figure S8). The first component (PC1; reflecting their mixture of African and Asian ancestries (Pierron et al., 2014). Overall, Malagasy appear to contain more African ancestry than Asian.

Explicit admixture analysis on the low density dataset confirms this assessment, showing that the three Malagasy populations have ~70% African ancestry (red) versus ~30% Asian ancestry (mixed colours; Figure 2). These two main components appear consistently, in similar proportions, in plots from K = 2 to K =14 (Annex E: Figure S9). The Asian ancestry of Malagasy individuals is diverse, with no component (or set of components) pointing to a specific Asian population as the source of Malagasy. The Asian components found in Malagasy instead occur across Island Southeast Asia, including the South Kalimantan Dayak, Dusun, Murut, Javanese and the Ma'anyan. However, as described in the previous section, the Ma'anyan carry a particular component (C8) at very high frequency (50 to 95%), but this is much less frequent in other Western Indonesian populations (<50% in the South Kalimantan ancestry and Borneo groups, an FST analysis using the same dataset highlights that the South Kalimantan Dayak still have the lowest genetic distance to the three Malagasy groups (average FST = 0.022) (Annex E: Table S4), thus suggesting that this is a likely Asian source population.

Together, these analyses confirm that Malagasy are a mixture of African and Island Southeast Asian populations, as suggested by much previous research (Capredon et al., 2013;Hurles et al., 2005;Pierron et al., 2014;Razafindrazaka et al., 2010;Soodyall et al., 1995;Tofanelli et al., 2009). However, this study provides the new information that the Island Southeast Asian populations with closest genetic affinity to the Malagasy are located along the coasts of Borneo, although exact source populations still cannot be clearly identified. Surprisingly, the Ma'anyan, despite speaking the closest sister language to Malagasy, do not share any particularly strong genetic links with Malagasy (Figure 2 and Figure 5). This lack of convergence between the genetic and linguistic evidence suggests that a more complex model is needed for the settlement of Madagascar. On the other hand, the uniqueness of the genetic diversity observed in the Ma'anyan opens an unexpected window for studying the complex history of the Austronesian expansion in Island Southeast Asia.

Discussion

A more complex picture of Austronesian genetic diversity

A genome-wide analysis of 211 individuals from Borneo reveals the unique genetic diversity of the Ma'anyan, opening an unexpected viewpoint into Southeast Asian prehistory. Our data reveal that the Ma'anyan are characterized by a specific genomic component that differentiates them from other Island Southeast Asian groups (Figure 2 and Annex E: Figure S1). This does not simply result from strong genetic drift (Annex E: Figure S5), but instead represents a homogenous genetic component that is largely uninfluenced by external gene flow. Although currently living in an isolated location, the Ma'anyan only settled there recently (see details below) [START_REF] Hudson | The Padju Epat Ma'anjan Dajak in historical perspective[END_REF](Hudson, , 1972)). This recent migration to isolated inland territories appears to have favoured the preservation of a unique genetic component, which is only rarely found in other Southeast Asian populations.

Recent studies have identified at least three broad genomic classes that dominate the gene pool of Southeast Asian individuals: Papuan ancestry, Mainland Southeast Asian ancestry, and Austronesian ancestry (Deng et al., 2015;Lipson et al., 2014). To relate these components to major episodes of human migration inferred from previous anthropological and archaeological studies, the Papuan ancestry likely tracks back to the initial settlement period (60-45 kya) (Karafet et al., 2010;Lipson et al., 2014;Tumonggor et al., 2013), the Mainland Southeast Asian ancestry probably to the very late Pleistocene (30-10 kya) (Blench, 2011;Deng et al., 2015;Jinam et al., 2012;Lipson et al., 2014), and the Austronesian ancestry to the mid-Holocene (5 kya) (Deng et al., 2015;Karafet et al., 2010;Lipson et al., 2014;Tumonggor et al., 2013). The discovery of a new ancestry component in the Ma'anyan is novel, although we show that it does occur at low levels in many populations across Island Southeast Asia (Figure 2). The presence of this component in these groups does not appear to be linked to any recent admixture events (Annex E: Figure S6 and Table S2), and therefore might instead be the signal of ancient shared ancestry. Nevertheless, this Ma'anyan component retains links to Austronesian diversity (Figure 3a and Figure 3b), with the Ma'anyan showing a particularly close genetic connection to the Igorot in the Philippines (Figure 3b and Figure 4). The Igorot, who also have strong Austronesian connections, live in remote areas of the Philippine highlands, which likely favoured the retention of their specific genetic signature. Shared connections between the Igorot and the Ma'anyan highlight a more complex picture of Austronesian genetic ancestry than has previously been presumed. We postulate that the ancestral diversity behind the Ma'anyan and Igorot genomic components emerged from some common unidentified source around East Asia or Taiwan, perhaps due to isolation-by-distance effects. The diffusion, and subsequent differentiation, of these two genetic components may find some support in the diffusion from Taiwan of two different cultural groups identified, respectively, by cord-marked and red-slipped pottery materials (Plutniak et al., 2014;Spriggs, 2007). However, the modality and timing of the spread of this ancestral Ma'anyan population and its relationship to the Austronesian expansion needs to be investigated further.

The Ma'anyan are not the primary biological ancestors of Malagasy

Despite strong linguistic affinities (Adelaar, 2005, 2009, Dahl, 1951, 1977), the Ma'anyan were not obviously the primary source population of the Malagasy. This confirms results obtained from uniparental markers, which show little sharing of genetic lineages between these two populations (Kusuma et al., 2015). As hinted previously (Pierron et al., 2014), the Asian ancestry of the Malagasy is instead diverse, and appears to relate to a range of Southeast Asian populations, albeit with especially close connections to groups in southern Borneo. It seems likely that the Asian individuals who settled Madagascar were already highly mixed, rather than coming from a wide range of Asian populations with later mixing in Madagascar, in agreement with the most likely scenario whereby only a small number of migrants were involved in the initial settlement of Madagascar (Cox et al., 2012). Looking across the Indonesian genetic landscape, the Ma'anyan carry a distinctive autosomal gene pool (dominated by the C8 component), which is not found in Malagasy (Figure 2 and Figure 5). This marked genomic difference between the Ma'anyan and the Asian component of Malagasy contradicts the hypothesis of a common origin inferred from the languages spoken by these two groups (Adelaar, 2005, 2009, Dahl, 1951, 1977). Hence, despite the strong affinity of Ma'anyan with the Malagasy language, the Ma'anyan people apparently did not contribute significantly to the Malagasy gene pool.

Other anthropological data may shed new light on the complex history of the Ma'anyan, perhaps reconciling this discrepancy between the linguistic and genetic data. Prior to their migration to Madagascar around 1,500 years ago, proto-Malagasy people had probably already developed a derived language that differed from Ma'anyan (Adelaar, 2017). This cultural process was likely driven by the growing influence of Malay and Javanese populations, which were trading intensively with groups in southeast Borneo (Adelaar, 2005(Adelaar, , 2009)). The only pre-colonial record from the region, the Hikayat Banjar (the 'Tale of Banjar') describes an old Malay settlement in southern Borneo, further inland than today's south Borneo coastline, that acted as a trading outpost of Malay Kingdom -such as the important Hindu kingdom of Srivijaya, which was dominant from the 7-13 th centuries AD (Ras, 1968).

This outpost was established because the coastline might have extended over 100 kilometres, and perhaps as much as 200 kilometres, further inland that at present (Adelaar, 2017;Van Bemmelen, 1949),and possibly lay near Tanjung-Amuntai region, where the Ma'anyan consider their original homeland [START_REF] Hudson | The Padju Epat Ma'anjan Dajak in historical perspective[END_REF](Hudson, , 1972)). It is conceivable that this settlement might then have provided sea contact to what are now land-bound Ma'anyan. As the coastline move southward, the trading post were also moved south and later formed the city of Banjarmasin: the dominant city, commercial state, and centre of activity in the trading network of this region. The inhabitants of Banjarmasin, the Banjar people, might then have constituted a mix of individuals from south Borneo under the cultural influence of the Malay Srivijaya kingdom. Based on this historical source, together with linguistic work on the ancestral states of the Malagasy language showing a substantial number of Malay loanwords (Adelaar, 2017(Adelaar, , 2009)), we postulate that the Asian source population of the Malagasy constituted admixed Ma'anyan individuals (best represented in our dataset by the South Kalimantan Dayak), who lived in the Srivijaya area of influence, integrating Malay and Javanese cultural traits and favouring a large degree of gene flow, before migrating to Madagascar. Although the cause of their migration remains elusive, our data tend to favour an origin for the Malagasy in southern Borneo. Curiously, the group with the closest genetic affinity to Malagasy in our dataset is the South Kalimantan Dayak, a composite population of several ethnic groups located in southeast Borneo today (Annex E: Table S4). This suggests that an in-depth analysis of these ethnic groups, including the Banjar people and other southeast Borneo ethnic communities, might be a promising direction to better identify the (possibly mixed) genetic sources of the Malagasy and to determine the ultimate causes of the Malagasy expansion.

Our study shows that the Ma'anyan have genetic diversity that is unique in Southeast Asia, complicating existing scenarios of dispersal during the Austronesian expansion. Surprisingly, this component clearly shows that the Ma'anyan are not the primary source population of the Malagasy, as has long been supposed based on their common linguistic origin. The Asian parental population of the Malagasy instead appears to lie among the ethnic groups of the South East region of Borneo, potentially represented by the Banjar, or more generally, by the South Kalimantan Dayak people. This discrepancy between linguistic and genetic evidence may reflect the complex history of the south Borneo region, and more focused study of its peoples is needed to explore this hypothesis further.

3.2.1.5. Miscellaneous

Introduction

Rapid advances in sea faring technologies in Island Southeast Asia (ISEA) around 5,000 years ago created an intricate network of maritime interactions, the leading example being the wellknown expansion of Austronesian peoples (Bellwood, 2007;Bulbeck, 2008;[START_REF] Solheim | Archaeology and culture in Southeast Asia: Unraveling the Nusantao[END_REF]. Triggering inter-continental maritime connections linking ISEA with East Africa and Remote Oceania (Beaujard, 2012a(Beaujard, , 2012b;;Bellwood, 2007;Kayser et al., 2008;Oppenheimer and Richards, 2001;Skoglund et al., 2016), these contacts drove exchanges of goods, ideas, cultures and people around the Indo-Pacific region [START_REF] Chaudhuri | Trade and civilisation in the Indian Ocean: An economic history from the rise of Islam to 1750[END_REF]Lawler, 2014). Seaorientated populations, including sea nomads, emerged from this milieu, dominating trade within ISEA for centuries and helping to structure population interactions across Indonesia and beyond. Today, the Indonesian archipelago hosts ~600 ethnic groups (Lewis et al., 2016), of which only a handful are known for their sea-based lifestyles. Some, like the Bugis and Makassar of Southern Sulawesi (Pelras, 1997), are maritime inter-regional traders that arose within the framework of regional empires, such as Malay/Hindu Śrīvijaya and Majapahit.

However, these groups still have homeland territories on land. Far more extreme are ethnic groups that subsist entirely detached from the land, living their whole lives aboard small boats, and as recently as 40 years ago, living as nomadic seafarers [START_REF] Hogan | Urak Lawoi': Basic structures and a dictionary[END_REF][START_REF] Larish | The position of Moken and Moklen within the Austronesian language family[END_REF][START_REF] Sopher | The Sea Nomads: A study of the maritime boat people of Southeast Asia[END_REF].

The biggest group, the Bajo (also Bajaw, Bajau or Sama-Bajau (Sather, 1997;Stacey, 2007)), number approximately one million people, who today live in numerous scattered hamlets and villages recently created by the Indonesian government along the coasts of the Indonesian archipelago, as well as Sabah in Malaysia, and the Sulu archipelago and South-Western Mindanao in the Southern Philippines (Nuraini, 2016;[START_REF] Pallesen | Culture contact and language convergence[END_REF][START_REF] Sopher | The Sea Nomads: A study of the maritime boat people of Southeast Asia[END_REF]Verheijen, 1986). The geographical distribution of Bajo communities overlaps large parts of the coral triangle, which contains one of the highest rates of marine biodiversity in the world, thus underpinning the Bajo economy based on exploiting marine resources including fish, tortoise shell and sea cucumber. Within Indonesia, the Bajo presence extends over a wide geographical area (Figure 1). Historically, Bajo were frequently associated with Sulawesi Bugis traders and ship owners (Pelras, 1997;Stacey, 2007) and were well known for traveling with their families, even for long distance journeys reaching as far as New Guinea and Australia [START_REF] Macknight | The voyage to Marege': Macassan trepangers in Northern Australia[END_REF]. The Bajo may have mediated westward dispersals into the Indian Ocean, perhaps even playing a role in the Indonesian settlement of Madagascar (Kusuma et al., 2015). Although some Bajo communities live far apart today, they still have similar social and cultural features, including shared shipbuilding and fishing culture, traditions and myths [START_REF] Nagatsu | Persisting maritime frontiers and multi-layered networks in Wallacea[END_REF]Nuraini, 2008;Stacey, 2007). Their languages belong to a single sub-family, the Sama-Bajau sub-group on the West Malayo-Polynesian branch of the Austronesian language family (Blust, 2007;[START_REF] Noorduyn | A critical survey of studies on the languages of Sulawesi[END_REF]. This sub-group includes at least nine languages (Lewis et al., 2016;[START_REF] Pallesen | Culture contact and language convergence[END_REF], with its highest diversity in Sabah (North Borneo) and the Southern Philippines [START_REF] Pallesen | Culture contact and language convergence[END_REF]. However, the Sama-Bajau languages of Indonesia are poorly documented, and an ongoing survey has identified at least three unrecognized languages (Grangé, forthcoming). Some of these languages are mutually unintelligible, suggesting that the Bajo diaspora started centuries ago, fitting with oral tradition. Numerous loanwords indicate that the languages spoken by the Bajo were influenced by neighboring ethnic groups with whom the Bajo interacted and socialized, in a process called 'maritime creolization' [START_REF] Nagatsu | Persisting maritime frontiers and multi-layered networks in Wallacea[END_REF]. However, the extent of these social interactions on the genetic composition of Bajo communities remains unknown.

The Bajo have no written history, instead relying on oral tradition, especially epic songs, which say little about their early history. Hypotheses about their origins have been drawn from this folklore, as well as linguistic studies and rare records from European sailors from the 16 th century onward (Sather, 1997). The Bajo diaspora may have originated in Johor, 100

Malaysia [START_REF] Sopher | The Sea Nomads: A study of the maritime boat people of Southeast Asia[END_REF], or even Arabia (Nuraini, 2008), according to oral tradition. Brunei and Southern Sulawesi have also been proposed based on other Bajo stories [START_REF] Jubilado | The Sama-Bajaus of Sulu-Sulawesi seas: Perspectives from linguistics and culture[END_REF][START_REF] Liebner | Four oral versions of a story about the origin of the Bajo people of Southern Selayar[END_REF]Nuraini, 2008). Linguistic surveys point towards the Sulu archipelago of the Philippines,18 and at an earlier stage, to Southeast Borneo (Blust, 2007). None of these hypotheses have been tested with genetic data.

Here, we undertake a genomic survey to help clarify the history of Bajo sea nomad populations. We present genome wide analyses from three Bajo communities (n = 73; Annex F: Table S1), representing different Sama-Bajaw dialects, together with comparative data from neighboring populations potentially connected historically with the Bajo. Using this large comparative dataset, we investigate the genetic origins and history of the Bajo, and characterize the genetic impact of their near-unique lifestyle as some of the world's last remaining sea nomads.

Materials and methods

Ethics

Samples, dataset integration and quality control

Subjects were surveyed for language affiliation, current residence, familial birthplaces, and a short genealogy of four generations to establish regional ancestry. A total of 47 saliva samples were collected using the Oragene saliva sampling kit (DNA Genotek Inc., ON, Canada) from two Bajo communities: Derawan (n = 18) in coastal Northeastern Borneo, Indonesia and Kotabaru (n = 23) in coastal Southeastern Borneo, Indonesia (Figure 1). DNA was extracted using the standard kit protocol. We also added DNA samples from the Samihim in Eastern Borneo (n = 25), the Bugis of Southern Sulawesi (n = 25), the Mandar of Southern Sulawesi (n = 23) and North Maluku individuals from various linguistic groups (n = 14) as comparative populations. This sampling strategy is relevant for the statistical tests that are described below, both on population structure and admixture. Genome wide SNP genotypes were generated using the Illumina Human Omni5 Bead Chip (Illumina Inc., CA, USA), which surveys 4,284,426 single nucleotide markers semi-regularly spaced across the genome.

Genotype data from previously published Bajo individuals from the Kendari community of Southern Sulawesi were also included (n = 32) (Pierron et al., 2014). New genotyping data have been deposited at the European Genome-phenome Archive (EGA), which is hosted by the EBI and CRG, under accession number EGAS00001002246.

A comparative dataset was built from 110 worldwide populations comprising an additional 2,256 individuals (Annex F: Table S1). Data quality controls were performed using PLINK v1.9 (Chang et al., 2015): i) to avoid close relatives, relatedness was measured between all pairs of individuals within each population using an Identity-by-Descent (IBD) estimation with upper threshold of 0.25 (second degree relatives); ii) SNPs that failed the Hardy-Weinberg exact (HWE) test (P<10 -6 ) were excluded; iii) samples with an overall call rate <0.99 and individual SNPs with missing rates >0.05 across all samples in each population were excluded. The final dataset contains 230,833 SNPs. Genotypes were then phased with SHAPEIT v2 (Delaneau et al., 2012) using the 1000 Genomes Project phased data (Delaneau and Marchini, 2014) as a reference panel and the HapMap phase II genetic map. For specific analyses mentioned below, variants in high linkage disequilibrium (LD) (r 2 > 0.5; 50 SNP sliding windows) were also pruned, leaving a final dataset of 168,368 SNPs.

Population structure

Population structure was evaluated using a suite of different programs, each relying on specific algorithms and types of data, to obtain the most relevant and robust interpretations. A fineSTRUCTURE v2.07 (Lawson et al., 2012) analysis was performed using 2x10 6 Markov Chain Monte Carlo (MCMC) iterations, discarding the first 10 6 iterations as 'burn in', and sampling from the posterior distribution every 10 4 iterations following the burn in. This analysis detects shared IBD fragments between each pair of individuals, without self-copying, as calculated with Chromopainter v2.0 (Lawson et al., 2012) to perform a model-based Bayesian clustering of genotypes. From the results, a co-ancestry heat map and dendrogram were built to visualize the number of statistically defined clusters that best describe the data.

Principal Components Analysis was performed using the 'smartpca' algorithm of EIGENSOFT v6.0.1 (Patterson et al., 2006). The Runs of Homozygosity (ROH) and

Inbreeding Coefficient (FIS) analyses were performed in PLINK v1.9. FST distance calculations were calculated with EIGENSOFT v6.0.1. To ascertain the significance of each pairwise FST value, 10,000 bootstraps were conducted using StAMPP [START_REF] Pembleton | StAMPP: an R package for calculation of genetic differentiation and structure of mixed ploidy level populations[END_REF], from which probability values were determined.

Population admixture

Admixture scenarios are determined from statistically complex models that rely a priori on the algorithms, and their assumptions, implemented in each program. To compensate for the potential biases of individual methods, we based our interpretations on the convergence of results from multiple different programs and different types of data. ADMIXTURE v1.30 [START_REF] Shringarpure | Efficient analysis of large datasets and sex bias with ADMIXTURE[END_REF] was used to estimate the genomic ancestry profile of individuals using maximum likelihood for components (K) from K = 2 to K = 20. Ten replicates were run at each value of K with different random seeds, then merged and assessed for clustering quality using CLUMPP (Jakobsson and Rosenberg, 2007), and the cross-validation value was calculated to determine the optimal number of genomic components. To determine the sex bias of admixture for all Bajo communities, unsupervised ADMIXTURE analysis were run on K = 2 using both autosomal and X-chromosome SNPs using Igorot and PNG highlanders as proxies for East Asian and Papuan ancestry, respectively. Significance tests of the proportion of the Papuan component between the autosomes and X chromosome for all Bajo communities were conducted using the one-tailed Wilcoxon test. Gene flow between populations was first investigated using TreeMix v1.12 (Pickrell and Pritchard, 2012), with blocks of 200 SNPs to account for linkage disequilibrium, and migration edges added sequentially until the model explained 99% of the variance. The three-population (f3) test was performed as implemented in ADMIXTOOLS v1.3 [START_REF] Shringarpure | Efficient analysis of large datasets and sex bias with ADMIXTURE[END_REF]. Haplotype sharing using the Refined IBD algorithm of Beagle v.4.0 (Browning and Browning, 2007) was computed to estimate the total number of shared genetic fragments (logarithm of odds ratio > 3) between each pair of individuals. Finally, we used Chromopainter v2 (Lawson et al., 2012) and GLOBETROTTER v1 (Hellenthal et al., 2014) to estimate the ratios and dates of potential admixture events. For all results presented here, we standardized each co-ancestry curve by a 'NULL' individual designed to eliminate any spurious linkage disequilibrium patterns not attributable to that expected under a genuine admixture event (Hellenthal et al., 2014), and consistency between each estimated parameter was checked, though we note that results were similar when not performing this standardization. The 'best-guess' scenario given by GLOBETROTTER was considered for each target population. Using the parental populations given by GLOBETROTTER, we ran 100 bootstrap iterations to estimate admixture dates, assuming a generation interval of 28 years for all analyses [START_REF] Fenner | Cross-cultural estimation of the human generation interval for use in genetics-based population divergence studies[END_REF].

between the Derawan and Kendari Bajo, again suggesting that genetic similar does not simply match current geographical location. As also shown by FST distances, high shared IBD between Bajo groups does not exclude sharing with non-Bajo neighbors. Nevertheless, IBD sharing between the Kendari Bajo and Bugis, two sea based communities currently settled in Sulawesi, is lower than IBD sharing between the Kendari Bajo and other Bajo groups.

Like other analyses, a TreeMix analysis situates the three Bajo communities with eastern Indonesian and Philippine populations (Annex F: Figure S9). The tree supports 16 migration nodes, many showing migration into the Bajo from Papuan clusters. Interestingly, there is Papuan migration into the two Bajo groups on Borneo, as well as the Kendari Bajo, where Papuan contributions were noted by Admixture. The most parsimonious hypothesis is multilayer admixture -from Papuan or Eastern Indonesian groups into the Kendari Bajo, and from there into the other Bajo groups. However, the data cannot exclude a more complex scenario with direct contact between Bajo groups in Borneo and Papuans.

We also inferred admixture scenarios for the three Bajo populations using GLOBETROTTER. This suggests that the Kendari Bajo mixed with surrogates of Sulawesi Bugis and Papuans multiple times. The oldest admixture event occurred around 62 generations ago (1,736 years ago, assuming a 28 year generation interval) with 90% and 10% contributions from Sulawesi Bugis and Papuans, respectively, and more recent admixture 6 generations ago (175 years ago), with admixture just from the Bugis (Figure 4, Annex F: Table S4). In contrast, the Kotabaru Bajo show one admixture event between Indian (5%), Sulawesi Bugis (70%) and Bornean Banjar (25%) sources around 33 generations ago (925 years ago), suggesting that Sulawesi played a major role in shaping the genomes of Kotabaru Bajo individuals. Local populations also contribute to the genomic make up, highlighting the neighboring Banjar of Borneo as another contributing group. The Derawan Bajo have genomic components from Indian (5%), Filipino (70%), and Malay (25%) sources, dating to around 24 generations ago (675 years ago).

These results were obtained with significant fit values by excluding other Bajo communities as potential surrogate populations for any given Bajo community. When we allowed all Bajo groups to act as potential surrogate populations, lower fit values were obtained, reflecting uncertain inference of admixture scenarios (Annex F: Table S4). Nonetheless, these runs confirm the earlier GLOBETROTTER results for the Kendari and Kotabaru Bajo, but in a new finding, the Bugis appears to be a surrogate population for the Derawan Bajo, in addition to Malay, Filipinos and Indians. Given the potential role of the Bugis on the genetic make-up of the Bajo, we therefore tested their admixture profile using GLOBETROTTER. The Bugis experienced a multiway admixture event around 57 generations ago (1,600 years ago) between Papuans (14%), Filipinos (41%) and Malay (45%), at around the same time as the admixture event with the Kendari Bajo. These admixture events were confirmed using MALDER (Annex F: Table S5). Even among the extraordinary diversity of human lifeways, the entirely sea-based lives of the Bajo -being born, growing up, marrying and dying on the sea -is special. This way of living is unique to Southeast Asia, with the Bajo, Urak Lawoi and Moken being well known examples [START_REF] Ivanoff | Rings of coral: Moken folktales, 1st edition[END_REF][START_REF] Sopher | The Sea Nomads: A study of the maritime boat people of Southeast Asia[END_REF]. However, very little is understood about the genetic structure of these communities. Using genome-wide SNP data, we can reconstruct the genetic background and diversity of the Bajo across three communities with different dialects spanning their geographic range, thus helping to clarify where the Bajo originated and how their society interacted with other groups. Each Bajo community constitutes a homogenous genetic group, with surprisingly little overlap. A common theme is that genetic sharing is greater with neighboring populations than other Bajo groups, although there is a clear shared component of Bajo ancestry. Nevertheless, genetic contributions from these local populations were far from trivial, matching the maritime creolization process observed in their languages.

This admixture seems to have started early. Bajo were never the major ethnic group in the regions where they first lived, but instead seem to have attracted and assimilated people from nearby communities [START_REF] Nagatsu | Persisting maritime frontiers and multi-layered networks in Wallacea[END_REF]. For example, in Kangean, a small archipelago in the Java Sea between Eastern Java and Southern Borneo, where the Bajo language and culture predominates today, ethnicities were historically more numerous [START_REF] Nagatsu | Persisting maritime frontiers and multi-layered networks in Wallacea[END_REF]Nuraini, 2008). Before Bajo migrants arrived, the main island was inhabited by indigenous Madura (East Javanese people), then several waves of migrants spread from Southern Sulawesi (including the Bajo, but also Bugis, Makasar and Mandar). However, the number of Bajo speakers then increased dramatically, quickly reaching one third of the total island population.

Over time, non-Bajo speakers adopted Bajo languages and intermarried with the original Bajo. This also occurred elsewhere, with mixing between Bajo and neighboring 'land owners' being commonplace (Nuraini, 2016).

Consequently, all Bajo individuals share at least some common genetic background, suggesting that gene flow between these groups occurred until recently, and indeed, may still be ongoing today. Bajo communities maintained contact through sharing of goods, trading, fishing and marriage. Until recently, Bajo trading routes spanned Singapore in the west to New Guinea in the east, and Northeastern Borneo in the north to the Lesser Sunda Islands in the south [START_REF] Nagatsu | Persisting maritime frontiers and multi-layered networks in Wallacea[END_REF]. Records note peaceful contact of Bugis and Bajo with Australian Aborigines along the Northern coast of Australia, where the Bajo harvested trepang (sea cucumber) in shallow near-shore waters [START_REF] Macknight | The voyage to Marege': Macassan trepangers in Northern Australia[END_REF]Pelras, 1997;Stacey, 2007), but no genetic contact is known. Strikingly, an established and stable Bajo sea trading route connected Southeastern Sulawesi with Southeastern Borneo (including Kotabaru Island), and from there, Kotabaru Island with Northeastern Borneo as far as Brunei, albeit with less intense activity [START_REF] Nagatsu | Persisting maritime frontiers and multi-layered networks in Wallacea[END_REF]. This may explain the very recent admixture seen in the Bajo genomes, best illustrated by long shared IBD regions (Figure 4D).

Despite a complex genetic history involving creolization and multiple admixture events, the genomic data are suggestive of a single population origin for the Bajo, converging on Southern Sulawesi. The oldest estimated admixture event dates to the 4 th century CE (Figure 4A, Annex F: Table S4) between ancestral Bugis (90%) and a Papuan group (10%). The two Bajo communities on Borneo appear to have emerged later, around the 12 th century for the Kotabaru Bajo and the 14 th century for Derawan Bajo, perhaps suggesting that Bajo communities lived in Southern Sulawesi for nearly eight hundred years before spreading west to Borneo. In contrast, the most recent linguistic studies support an origin of the Bajo language in the Southeast Borneo region, followed by a dispersal up the east coast of Borneo during the 11 th century, only later spreading to the Southern Philippines and Northeast Borneo in the 13 th -14 th centuries (Blust, 2007). The linguistic and genetic evidence are therefore in broad agreement regarding the timing of the Bajo dispersal along the east coast of Borneo, but point to quite different locations for its origin: Southern Sulawesi for the gene pool and Southeast Borneo for the languages.

This apparent contradiction may be reconciled by aspects of recent history, as the expanding influence of the Malay kingdom of Śrīvijaya from the 7 th century onward (7-13 th centuries) (Beaujard, 2012a;Ras, 1968) heavily modified population structure and interactions in Southeast Borneo, triggering large population movements, such as the likely migration of the Banjar to Madagascar (Brucato et al., 2016;Kusuma et al., 2015). We postulate that similar causes may have also stimulated the dispersal of Bajo speakers from Southeast Borneo, again around the 11 th century. The spread of the Bajo culture from Southeast Borneo possibly impacted pre-Bajo groups in Southern Sulawesi, leading to the emergence of the Kendari Bajo (Figure 4B). This Southern Sulawesi community with an incipient Bajo culture then unified the Bajo language and genome by settling other areas, creating communities such as the Kotabaru and Derawan Bajo (11 th -14 th centuries), likely with sex biased admixture between men from mainland Asia and women from the Bajo ancestral population (Annex F: Figure S5). This sex bias pattern is also observed in other sea-nomad populations along coastal Mainland Southeast Asia, such as the Moken sea-nomads, who exhibit lower female gene flow from mainland Asian populations [START_REF] Dancause | Origins of the Moken Sea Gypsies inferred from mitochondrial hypervariable region and whole genome sequences[END_REF]. Later, admixture with local groups occurred (Figure 4C), as well as ongoing contact between Bajo communities (Figure 4D). A similar process likely impacted other regions where the Bajo culture is common now, such as the Sulu archipelago in the Southern Philippines. Furthermore, Southern Sulawesi was long a center of trading activity during and after the Śrīvijaya Empire (Pelras, 1997), reaching its peak during the 16 th century [START_REF] Villiers | Makassar: the rise and fall of an east Indonesian maritime trading state, 1512-1669[END_REF]. The main actors with significant role as traders are the Bugis, Makasar and Bajo, all with Southern Sulawesi connections [START_REF] Sopher | The Sea Nomads: A study of the maritime boat people of Southeast Asia[END_REF]. Therefore, the presence of a Southern Sulawesi genetic background in all Bajo communities may also result from contact directly between these three sea trading groups.

Outside Indonesia, similar admixture behaviors, notably shared long-distance contact with local genetic contributions, has also been observed in other recent diasporas, such as the Romani and the Jewish in Europe. The Romani, who originated in Northwest India, later admixed with local European populations where they settled, yet with relatively modest genetic contributions [START_REF] Mendizabal | Reconstructing the population history of European Romani from genome-wide data[END_REF]. Likewise, the Jewish diaspora has been traced back to the Levant, but local genetic admixture has been identified in each respective community [START_REF] Behar | The genome-wide structure of the Jewish people[END_REF]. In both examples, all communities shared a common culture and genetic heritage, but like the Bajo, experienced gene flow from populations surrounding them.

The complexity of the Bajo genomic profile provides a striking reflection of their history, mediated by both migratory and local admixture events, and emphasizing their unique lifestyle played out across multiple geographical scales. Despite speaking Sama-Bajau languages, the Bajo prove to be diverse, encompassing rich genetic inputs from many groups, each distributed differently in the major Bajo communities, but homogenous for individuals within each community. It appears that contact between Bajo groups was a major feature of this history, but countered by strong regional contacts: Papuan influence in the Kendari Bajo;

Banjar in the Kotabaru Bajo; and Filipino and Malay in the Derawan Bajo -all with an outsized influence from their Southern Sulawesi origin, possibly obtained by proxy from the Bugis. This genetic structure is in part due to a process of maritime creolization, exhibiting The Malagasy are the descendants of a unique prehistoric admixture event between African and Asian individuals, the outcome of one of the earliest proto-globalization processes that began approximately 4,000 years before present (BP) (Beaujard, 2012b(Beaujard, , 2012a;;[START_REF] Fuller | Across the Indian Ocean: the prehistoric movement of plants and animals[END_REF]Lawler, 2014). Today, this island population in the western Indian Ocean shows strong biological [START_REF] Fourquet | Hémoglobine S et origines du peuplement de Madagascar : Nouvelle hypothèse sur son introduction en Afrique[END_REF]Pierron et al., 2014) and linguistic (Adelaar, 2009;Serva et al., 2012) connections to east coast African and Island Southeast Asian groups. Although this remarkable admixture event has long been studied [START_REF] Fourquet | Hémoglobine S et origines du peuplement de Madagascar : Nouvelle hypothèse sur son introduction en Afrique[END_REF][START_REF] Hewitt | Beta-globin haplotype analysis suggests that a major source of Malagasy ancestry is derived from Bantu-speaking Negroids[END_REF]Hurles et al., 2005;Kusuma et al., 2015;Pierron et al., 2014;Soodyall et al., 1995;Tofanelli et al., 2009), the settlement process -specifically the geographic origin of the populations involved, dates of settlement and the nature of the population admixture event -are still routinely debated (Adelaar, 2009(Adelaar, , 2017;;Beaujard, 2012b;Kusuma et al., 2015;Pierron et al., 2014). Both linguistic and genetic studies suggest that the western and central regions of Indonesia (particularly Java, Borneo and Sulawesi) have the closest Asian genetic connections with modern Malagasy (Adelaar, 2017;Kusuma et al., 2015Kusuma et al., , 2016)), and the island was probably settled by a small founding population (Cox et al., 2012). More specifically, recent anthropological research points to the Southeast region of Borneo as a potential source location for Malagasy (Adelaar, 2017;Kusuma et al., 2016). However, the Indonesian parental population of the Malagasy has so far not been clearly identified (Kusuma et al., 2015(Kusuma et al., , 2016)). To better reconstruct the settlement history of Madagascar and identify the Asian source populations, we conducted widespread sampling and genome-wide analysis of human groups across the Indian Ocean region. In particular, we present here new genome-wide data for two southeast Borneo populations, the Banjar (n=16) and the Ngaju (n=25) (Annex G:

Figure S1), which have previously been noted as potential parental groups to the Malagasy (Adelaar, 2017). The newly generated data were analysed in the context of previously published data for a wide range of populations from the Indian Ocean rim (Annex G: Table S1).

The Malagasy Asian ancestry derives from Southeast Borneo.

To identify the most probable Asian parental groups of the Malagasy, we adopted a two-stage approach: first, we identified the most likely proxy populations using a dataset with wide geographical coverage but relatively low density of SNP, then followed by a higher density SNP dataset that gives increased statistical power. This allows us to reconstruct the admixture processes that led to the emergence of modern Malagasy. The admixture profile of our dataset (2,183 individuals from 61 populations genotyped for 40,272 SNPs; Annex G: Figures S2 and Figure S3), based on ADMIXTURE analyses (Alexander et al., 2009), shows that the Malagasy genetic diversity is best described as a mixture of 68% African genomic components and 32% Asian components, corresponding well with the results of previous studie (Capredon et al., 2013;Pierron et al., 2014). While the African ancestry component in Malagasy appears to be broadly similar to that still present today in South African Bantu, the Asian ancestry presents a more complex pattern. This complexity is the key reason why previous studies have been unable to point firmly to a unique Asian source, making any subsequent anthropological inferences debatable (Pierron et al., 2014). This problem arose with a study of the Ma'anyan population of Borneo, whose language has long been identified

as the closest to the Malagasy language (Dahl, 1951), but who surprisingly exhibit no clear genetic connection to Malagasy (Kusuma et al., 2016). Instead, the higher genetic complexity of the Asian ancestry component in Malagasy likely reflects the fact that more than a single source population was involved in its formation. G: Table S5). The admixture event was dated to 675 years BP (95% CI: 625-725 years BP, Annex G: Table S5), which is similar to the dates of admixture estimated by ALDER (550-750 years BP) using Banjar population in combination with the South African Bantu (Annex G: Table S6) (Loh et al., 2013). When each Malagasy ethnic group is analysed separately, similar parental populations, admixture proportions and dates are obtained with the noticeable older estimated dates towards the east coast of Madagascar (Annex G: Table S5). Crucially, these dates of genetic admixture, in agreement with a previous study (Pierron et al., 2014), reflect the midpoint or end of noticeable admixture between groups of Asian and African ancestry in Madagascar, rather than the start of this contact. Therefore they could correspond to the end of the period of the main Austronesian presence in Madagascar that started around the first millennium CE (Adelaar, 1995(Adelaar, , 2017;;Cox et al., 2012;Dahl, 1951Dahl, , 1991;;Dewar and Wright, 1993). On the other hand, around 1,100-700 years BP, climatic changes in the South of Africa forced Bantu populations to move to more hospitable places [START_REF] Huffman | Mapungubwe and the origins of the Zimbabwe culture[END_REF]. This South Bantu migration has previously been suggested as an explanation for the higher density of populations observed in the South of Madagascar (Beaujard, 2012b). As all of our sampled groups live in the South of Madagascar, and considering that the estimated dates of admixture are more recent on the west coast ( Annex G: Table S5 andTable S6), it is tempting to interpret our admixture date as marking the last significant Bantu migration to Madagascar, perhaps initiated by climatic changes in Africa.

The Proto-Malagasy people were a Malay-Ma'anyan admixed group.

These analyses clearly identify an Austronesian-speaking population, the Banjar in the southeast region of Borneo, as the closest Asian sources for modern Malagasy. Linguistic reconstruction of the Proto-Malagasy language indicated that it appears to be derived mainly from the Southeast Barito language spoken today by the Ma'anyan (Dahl, 1951), a Southeast Borneo group. However, we have previously shown (Kusuma et al., 2016), and reconfirm here, that in genetic analyses, the Ma'anyan are only distantly related to the Malagasy in terms of genetics. In contrast, the Banjar currently speak a Malay language. Interestingly the linguistic studies indicated a noticeable proportion of Malay words in present-day Malagasy languages (Adelaar, 1989(Adelaar, , 2009)). We estimated the best fit scenario for the admixture process by modeling the current Banjar diversity with GLOBETROTTER (Hellenthal et al., 2014).

The genetic diversity of the Banjar best fits a model of a unique admixture event (r 2 =0.62; P < 0.01) between two major ancestries that can be traced back to Malay (77%) and Ma'anyan (23%) (Figure 2 and Annex G: Table S5). We estimate the date of the last noticeable admixture approximately 425 years BP (95% CI: 275-500 years BP). Since the Banjar originated from a Ma'anyan-Malay admixture, at a time preceding the supposed date of migration to Madagascar (i.e. 1,000 years BP), the ancestors of the Banjar were presumably speaking a language close to that reconstructed for Proto-Malagasy (Adelaar, 2017). Although we cannot fully exclude that the Malay-Ma'anyan admixture occurred in Malagasy, prior to the Bantu gene flow, the observed haplotypic structure is so similar to the ones observed in the Banjar that it is more parsimonious to interpret this admixture to have happened first in Borneo. This analysis reconciles both the linguistic and genetic data, strengthening our scenario placing the Banjar as the main Asian parental populations of the Malagasy. Their current genetic diversity appears to be the reflection of the historical relationship between Madagascar, Southeast Borneo and the Malay. The maritime routes linking Madagascar to Borneo were particularly exploited during the rapid expansion of trading networks led by the Hindu Malay Kingdoms, such as Srivijaya (6 th -13 th centuries) (Beaujard, 2012b;Ras, 1968).

Established on the islands of Sumatra and Java, the Malay traded with far-distant regions, notably across East Asia and reaching as far as East Africa (Beaujard, 2012b). Their influence increased across all the Southeast Asian islands, notably in Borneo where they established several trading posts, such as one in the city of Banjarmasin in S#outheast Borneo (Beaujard, 2012b;Ras, 1968). As related in the only Banjarese historical records available, the Hikayat Banjar ('Tale of Banjar') (Ras, 1968), the main city of the Banjar population was a major trading post in the former Malay Empires. This probably favoured interactions with inland groups in Borneo, such as the Ma'anyan, but also with other populations such as the Bajo sea nomads (Annex G: Figure S6 and Table S5) (Adelaar, 2009;Beaujard, 2012b;Kusuma et al., 2015). The Malay domination of trading networks collapsed during the 15 th -16 th centuries, with the emergence of several sultanates and the arrival of Europeans, which could correspond to the end of noticeable Malay gene flow into the Banjar population, as indicated by our estimated date of admixture between Malay and Ma'anyan around 425 years BP.

Our study provides strong support for a new scenario for the Austronesian settlement of Madagascar, reconciling cultural, linguistic and genetic data, in which the Banjar population played key roles in establishing the Asian founder population of the Malagasy. The Malay trading networks during the first millennium CE triggered one of the earliest protoglobalization processes, bringing Southeast Asian populations to East Africa (Beaujard, 2012b). The Banjar, currently living in Southeast Borneo, show the highest affinity to the main genetic ancestry component in Malagasy and can therefore be suggested to be likely to have been the ethnic group that accompanied the Malay in their maritime voyages to Madagascar. This population with composite ethnic ancestry emerged from the long-standing presence of Malay in Borneo, creating an admixed community with local Austronesianspeaking groups, such as the Ma'anyan. Before the probable date of migration (around 1,000 years BP), the ancestors of the current Banjar would have contained both Malay and Ma'anyan genetic diversity, and probably linguistic inheritances from both (Adelaar, 2017).

Although the exact maritime route(s) of migration from Borneo to Madagascar are still an open question, our study identifies the flow of Malay-Ma'anyan genomic ancestries as carried by Banjar ancestors as the source to Malagasy. ISEA, such as the routes, timing of dispersals, and also the nature of possible admixture events. I also performed analyses on the genetic history of the Bajo sea nomads; their way of life has been instrument in shaping Indonesian genetic diversity and they were potentially involved in the settlement to Madagascar. Dispersed along coastal areas on different islands in Indonesia, the Bajo still speak a single language; the scientific debate on the origin of this language is in progress. In this study, I proposed a scenario for the origin and dispersal of the Bajo, including sex bias admixture during migrations. Their sea-orientated way of life, their prime role in the maritime trading networks and their location at the maritime frontier, placed the Bajo in contact with various populations (including South Asians and Papuans), whose genomes left traces in their communities. By studying the Bajo, we will be able to investigate biological/genetic interactions in such maritime interaction network, which has been the main way for populations to interact in ISEA since the mid-Holocene.

Concerning the origins of the Malagasy, the results of genome-wide SNP analyses confirmed that the Ma'anyan are not the primary ancestor of the Malagasy. After subsequent analyses it East. As a consequence, not only goods and commodities were exchanged, but also genes.

Gene flow from India and the Middle East to several Indonesian populations has probably been constant since their first contact and potentially intensified during the period of the Hindu/Malay Kingdoms in Indonesia (6 th to 16 th century CE). Even minor Indian genetic traces that have been found in Madagascar are thought to have been brought from Indonesia, and not directly from India. This indicates that the influence of Indianised Kingdoms in Indonesia was not restricted simply to cultural assimilation, trading and economic power, but was also associated to some degree of gene flow into Indonesia and then to Madagascar.

In the context of the results generated, summary conclusions can be made for each of the four questions of my doctoral study (see p13):

1. Borneo populations enrich the overall diversity of Indonesian populations, and a previously undetermined, unique Austronesian component was identified in Ma'anyan speaking populations.

2. Western Eurasian populations have left genetic traces in some Indonesian populations, mainly in Java, Bali and Sumatra, however, the proportion of the autosomal component is low. This influence was probably brought into Indonesia during the reign of the Malay Kingdoms, which started in the 6 th century CE. In conclusion, this thesis provides valuable insights into the connection between Indonesian and Malagasy populations, helping to address important questions related to the history and ancestry of these groups.

Limitations

In this study, the precision of dating generated by software is not absolute, as it is approached by generation interval in time of year. I calculated the date estimation in years by multiplying the date estimate in generations with the average number of years per generation. The date of admixture cannot be equated to the date of migration, but to the date of the last admixture event. The date of migration could be addressed using historical and archaeological evidence, but this evidence is limited, hence should be interpreted with caution.

Perspectives

Sample coverage

A key area for future work should be to identify the exact (or the closest) population as the source of admixture, as this can provide important insights on the evolutionary history of populations in general. To date, most studies only cover the major global populations in Europe and Africa, and the inclusion of native indigenous regional populations is lacking.

Studies would benefit greatly from improving their global coverage of samples, particularly in Therefore, the aim is to determine whether the Malagasy's genetic motif is detected outside Madagascar, to investigate the nature of its apparition and diffusion.

Sequence data

Technological advances have made whole genome sequencing from considerable number of individuals cost-effective, providing favorable circumstances to analyse data without ascertainment-bias by sampling all the variation in the genome. Inferences of demographic parameters can be estimated without modeling or correcting any ascertainment biases. Rare alleles will be observed, thus provide information about recent population structuring. In haplotype level, shared segments that contain rare alleles can give insight on ancestry signatures in admixed populations, and also to know the source of admixture. Full and more dense data on haplotype length distribution can give thorough information while modeling the demographic events such as population admixtures and its divergences, as well as its timing.

Not only covering demographic questions, whole genome sequence data will also provide robust information on genetic adaptation to selective pressures and environmental changes.

The international collaborative genomic projects in which I am involved, will, for the first time, explore these areas in indigenous and native populations.

Mitogenome sequences from various populations in Indonesia and eastern Africa (~800 mitogenome sequences), that were generated during the final year of my doctoral study, will be analysed further to model the settlement of populations in Indonesia. For example, the demographic history of the Ma'anyan, who has a unique genetic background, but doesn't exhibit any admixture events, can be modeled using mitogenome sequence data in the context of the maternal lineage. In addition, mitogenome data on Malagasy populations, once available in the scientific community, will be useful to model the divergence, split, and migrations from respective Asian and African ancestral populations, to complement the results from the genome-wide SNP data presented in this dissertation.

Study of human disease and migration

The migration of large numbers of people creates opportunities for the spread and establishment of common or novel infectious diseases. There are significant inter-regional differences in geographical and climatic conditions, and indigenous people have adapted to the specific conditions and endemic diseases in their respective homelands. The role of environmental change is important in the dissemination of infectious diseases, and when people migrate they also bring pathogens from their specific regions. Studying various diseases as population history and migration markers can be a complement to general population genetics / molecular anthropology studies, to gain a holistic view on where populations originated, where people migrate, and how people have adapted to their old and new environments. Traces of infectious disease parasites and their vectors can bring an understanding, not only of adaptation mechanisms against diseases, but also on the routes taken by humans during their global migrations.

Studies of adaptation to malaria have shown that populations have unique regional-level genetic profiles to counter malaria 210

Table S1.

  Résumé.........................................................................................................................................i Acknowledgements.....................................................................................................................v Table of contents.........................................................................................................................1 I. Introduction..............................................................................................................................4

Figure 1 . 1 .

 11 Figure 1.1. A relief in Borobudur temple illustrating the oceanic voyage from Indonesia to eastern Africa during the Srivijaya era in 6 th century using triggered-boat.

Figure 1 . 2 .

 12 Figure 1.2. An outline of the modern human migration route out of Africa until East Asia and Indonesia, taken fromOppenheimer (2008)

Figure 1 . 3 .

 13 Figure 1.3. A map showing the Island Southeast Asia region in (a) Pleistocene era consisted of three main areas: the Sundaland, Sahuland, and Wallacea regions, and in (b) recent time when sea level rose and created thousands of islands in the Indonesian archipelago and other regions across ISEA , taken from Voris (2000).

Figure 1 . 4 .

 14 Figure 1.4. Genetic reconstruction of human settlement and migration waves in Island Southeast Asia, taken from Lipson et al. (2014).

Figure 1 . 5 .

 15 Figure 1.5. Dispersal of Austronesian-speaking people, taken from Gray et al. (2009).

Figure 1 . 6 .

 16 Figure 1.6. Tentative tree diagram of Austronesian language, taken and modified from Adelaar (2013).

Figure 1 . 7 .

 17 Figure 1.7. Maps of language diversity in Kalimantan, taken from http://ethnologue.com. Red circle indicates where the Ma'anyan (Southeast Barito) speakers live.

Figure 1 . 8 .

 18 Figure 1.8. A map of eastern Africa with archaeobotanical findings showing Asian traces in eastern Africa as early as mid 7 th century, taken from Crowther et al (2016).

Figure 1 . 9 .

 19 Figure 1.9. The stick-zither musical instrument found in Sumba, Indonesia (left) and in Madagascar (right), photo courtesy of Roger Blench (http://www.rogerblench.info/Images/Artefacts/SEAsi/Indonesia/)

Figure 1 . 10 .

 110 Figure 1.10. Possible direct (a) and downwind (b) sailing from Indonesia to Madagascar and eastern Africa in March and January respectively from computational simulation, taken from Fitzpatrick & Callaghan (2008).

Figure 1 . 11 .

 111 Figure 1.11. Maps of East Asian mtDNA lineages distributions and their migration scenarios through the Indonesian archipelago, taken from Brandao et al. (2016).

  : four migration phases within different time-frames, marked by the presence of specific Y-chromosome haplogroups or lineages. The haplogroups C-M38, S-M230 and M-P256 represented the first male arrivals into Indonesia (50,000 -45,000 years ago); these haplogroups are now commonly found in Papua and eastern Indonesian. The influx of various O haplogroups into Indonesia from mainland Asia (O-P203, O-M95, O-M122, O-P201, O-M119) occurred in the late Pleistocene (35,000 -8,000 years ago), and later from Taiwan with Austronesian haplogroups (O-P203, O-M110, P-P201) (6,000 -4,000 years ago). Subsequent migrations from the Indian subcontinent and the Middle East into Indonesia were marked with the presence of H-M69, R* and L-M20 haplogroups during the historical era (Figure 1.12).

Figure 1 . 12 .

 112 Figure 1.12. Maps illustrating the phases of human settlement in the Indonesian archipelago over 50,000 years taken from Karafet et al. (2010).

Figure 1 . 13 .

 113 Figure 1.13. A diagram of admixture in Madagascar populations (Mike, Vezo, Temoro) showing a mixture between African (red) and Asian ancestry (blue and green), taken from Pierron et al. (2014).

Figure 1 . 14 .

 114 Figure 1.14. The distribution of Helicobacter pylorii genotype mimics the Austronesian-speaking dispersal route from South China and Taiwan into the Pacific, taken from Moodley et al. (2009).

Figure 1 . 15 .

 115 Figure 1.15. Phylogenetic tree of HHV8 subtypes clustered according to their regional geographical distribution, taken from Cassar et al. (2012).

  human subjects established by both the Eijkman Institute and by the French scientific institution. The study was approved by the Eijkman Research Ethic Commission under Research Ethic clearance number 90 for the study of Indonesia Human Genome Diversity and Diseases, and by the Cellule Bioéthique of the Secretariat d'état à l'enseignement supérieur et à la recherche (n°IE-2015-837(

Figure 2 . 1 .

 21 Figure 2.1. The geographical distribution of the new and archived samples included in this study. Numbers on the map correspond to the population ID number inTable 2.1 and Table 2.2. The Indonesian map is taken from

( 4 .

 4 ac.at) according to Phylotree v.16 To generate data using SNP arrays, I used different types of SNP chips. Firstly, I used Illumina Omni Express (700K SNPs surveyed) conducted by Gene by Gene (Houston, Texas, USA), then Illumina Omni 2.5 (2M SNPs surveyed) in collaboration with Dr. Denis Pierron, conducted in the Centre National de Génotypage (CNG -Paris), and also Illumina Omni 5 5M SNPs surveyed) conducted in CNG. The data were retrieved in PLINK ped/bed format, then followed by quality control checks for SNP calling quality in each locus and individual. Detailed parameters were specified in each published article in section III. Samples to which each SNP array were applied are mentioned in the respective annex of each published article (Section III and VI). All different analyses performed on each population (mtDNA, Ychromosome, Illumina Omni Express SNP array, Illumina Omni 2.5 SNP array, Illumina Omni 5 SNP array) are listed in Annex B. III. Indonesian genetic diversity and their genetic impact in Madagascar 3.1. Uniparental marker analyses In this sub-chapter, I present my research on the two main aims of this thesis -the origin of Indonesian genetic diversity and its relationship to the genetic background of the Malagasy population -by using uniparental markers (mtDNA and Y-chromosome). I published two articles on these topics, using data from newly sampled Indonesian populations and previously published data. The first article was published in the journal BMC Genomics, entitled "Mitochondrial DNA and the Y-chromosome suggest the settlement of Madagascar by Indonesian sea nomad populations", and the second was published in Quaternary International journal, entitled "West Eurasian genetic influences in the Indonesian archipelago". The first article focuses on question 1, 3 and 4 (see p13), and explains the position of the Indonesian populations within the current genetic diversity of Indonesia and ISEA, making a clear distinction between western and eastern Indonesia. Furthermore, I also observed some links between Indonesian and Malagasy populations from uniparental markers, suggesting a complex scenario in the role that Indonesian populations have played in the settlement of Madagascar. Based on the same dataset, the second article focused on question 2 (see p13). The study revealed western Eurasian (South West and/or South Asia) genetic traces in various Indonesian populations related to the last 2,000 years of historical interactions, and a different geographic origin in western Eurasia and geographic distribution in Indonesia of the western Eurasian maternal and paternal lineages.3.1.1.1. Abstract Background Linguistic, cultural and genetic characteristics of the Malagasy suggest that both Africans and Island Southeast Asians were involved in the colonization of Madagascar. Populations from the Indonesian archipelago played an especially important role because linguistic evidence

3 . 5 (

 35 Excoffier and Lischer, 2010) with 5,040 permutations. Multidimensional scaling (MDS) from FST values based on Y chromosome and mitochondrial DNA haplogroup frequencies (Annex C: Table

Figure 1 .

 1 Figure 1. MDS plot showing FST values between Indonesian and Malagasy populations based on Y chromosome haplogroup frequencies (Kruskal stress: 0.149). Red: western Indonesians; blue: eastern Indonesians.

  Ma'anyan from southern Borneo do not show any privileged link with Malagasy (indeed, they have a relatively high FST value showing genetic differentiation), despite being the only Indonesian population that shares Y haplogroup O2a1a with Malagasy. This may indicate that the genetic contribution of Ma'anyan was limited, either due to the recent arrival of this lineage in Ma'anyan, or perhaps O2a1a has since been lost or is still undetected in other Indonesian populations.

Figure 2 .

 2 Figure 2. Map of Y chromosome FST values obtained by pairwise comparison between Malagasy and Indonesian populations. Dark red shading corresponds to lower pairwise FST values between Malagasy and Indonesian populations (represented by black squares), and dark blue to higher FST values. Note: 2. Batak Toba, 3.Besemah, 4. Semende, 5. Nias, 6. Mentawai, 7. Lebbo', 8. Ma'anyan, 10. EK Dayak, 11. Java, 12. Bali, 13. Mandar, 17. Bajo, 18. Sumba, 19. Flores, 20. Lembata, 22. Alor, 24. Maluku

Figure 3 .

 3 Figure 3. Asian mtDNA haplotypes shared between Malagasy and Indonesian populations.

Figure 4 .

 4 Figure 4. MDS plot showing FST values between Indonesian and Malagasy populations based on mtDNA haplogroup frequencies (Kruskal stress: 0.143). Red: western Indonesians; blue: eastern Indonesians.

Figure 5 .

 5 Figure 5. Map of mitochondrial DNA FST values obtained by pairwise comparison between Malagasy and Indonesian populations. Dark red shading corresponds to lower pairwise FST values between Malagasy and Indonesian populations (represented by black squares), and dark blue to higher FST values. Note: 1. Gayo, 2.Batak Toba,3. Besemah, 4. Semende, 5. Nias, 6. Mentawai, 7. Lebbo', 8. Ma'anyan, 9. SK Dayak, 11. Java, 12. Bali, 13. Mandar, 14. Kajang, 15. Toraja, 16. Bugis, 17. Bajo, 18. Sumba, 19. Flores, 20. Lembata, 21. Pantar, 22. Alor, 23. North Maluku

Figure 1 .

 1 Figure 1. Frequency of West Eurasian A) Y chromosome and B) mtDNA haplogroups among Indonesian populations (indicated by red dots). Dark shaded areas have higher frequencies. Data and populations details are provided in Tables1 and A1 and A2. Note: 1. Gayo, 2. Batak Toba,3. Besemah, 4. Semende, 5. Nias, 6. Mentawai, 7. Lebbo', 8. Ma'anyan, 9. SK Dayak, 10. EK Dayak, 11. Java, 12. Bali, 13. Mandar, 14. Kajang, 15. Toraja, 16. Bugis, 17. Bajo, 18. Sumba, 19. Flores, 20. Lembata, 21. Pantar, 22. Alor, 23. North Maluku, 24. Maluku

Figure 2 .

 2 Figure 2. PCA plot showing the 1st and 2nd principal components computed from West Eurasian mtDNA and Y chromosome haplogroup frequencies in Indonesia (grouped by island).

  sub-chapter, the analyses of uniparental markers generated robust results regarding the two main aims of this thesis -the origin of Indonesian genetic diversity and its relationship to the genetic background of the Malagasy population. However, it was not possible to accurately determine the Asian group(s) that settled Madagascar, or undertake a deep investigation of Indonesian genetic diversity. Thus, in this sub-chapter, I present my research on the analyses of autosomal genome-wide SNP data from new Indonesian populations, and bring key new elements to the aims. I published three articles on this topic.The first was published in the journal Scientific Reports, entitled "Contrasting linguistic and genetic influences during the Austronesian settlement of Madagascar", the second is in press. in the journal European Journal of Human Genetics, entitled "The last sea nomads of the Indonesian archipelago: Genomic origins and dispersal", and the third was published in the journal Molecular Biology and Evolution, entitled "Malagasy genetic ancestry comes from an historical Malay trading post in Southeast Borneo". The first article focuses on questions 1 and 3 (see p13), and explores the autosomal genetic background of the Ma'anyan, the linguistic-sister population of the Malagasy; it assesses whether the Ma'anyan have a close genetic affinity to the Malagasy. The second article investigates the genetic history of the Indonesian Bajo sea-nomads, and how their way of life shapes the genetic diversity of central Indonesia populations. Later, I also tested their affinity with the Malagasy to determine if the sea nomads contributed directly to the westward migration into Madagascar. This article gives additional insight into questions 1, 3, and 4 (see p13). The third article examines the genetic affinities of other Indonesian populations living in the vicinity of the Ma'anyan in South Borneo, especially Banjar and Ngaju populations, to the Malagasy, and finally manages to identify the Asian ancestor of the Malagasy, hence reconciling linguistic, historical and genetic evidence. This article gives strong answers to the general question addressed throughout this thesis on the genetic connection between Indonesia and Madagascar.

  , with blocks of 200 SNPs to account for linkage disequilibrium and migration edges added sequentially until the model explained 99% of the variance (the TreeMix outputs in Newick format were visualized with MEGA6(Tamura et al., 2013)); and three-population (f3) statistics(Patterson et al., 2012), defining the African Yoruba population as an outgroup for the low density dataset; and ii) haplotype sharing using the Refined IBD algorithm of Beagle v.4.0(Browning and Browning, 2007) visualized with Cytoscape v.3.2.1 (Shannon et al., 2003) using the high density dataset to estimate the total number of shared genetic fragments (logarithm of odds ratio>3) between each pair of individuals.To characterize the Island Southeast Asian ancestry in Malagasy individuals, we discarded estimated African components using PCAdmix(Brisbin et al., 2012). First, genome-wide SNP data from Malagasy, Yoruba and Asian samples (represented by the Ma'anyan, the Igorot and the Bajo to cover a range of Asian diversity) of the high density dataset were phased using Beagle v4.0. The Yoruba and Asian samples comprised 100 randomly selected individuals, and were defined as 'parental' populations compared to the Malagasy 'daughter' population for the purposes of the PCAdmix software. The ancestry of each defined linkage disequilibrium window was estimated by the Viterbi algorithm for each individual and used to mask all potential African SNPs. The masked Malagasy dataset was merged with the high density dataset, trimmed to 17,043 overlapping SNPs, and used to find the closest Indonesian populations that match the Malagasy Asian component using FST distances, an ancestryspecific PCA in EIGENSOFT v6.0.1 and a TreeMix analysis.

Figure 1 .

 1 Figure 1. Map showing the location of each population group studied in this work. The map is generated using Global Mapper v.15 software (http://www.bluemarblegeo.com/ products/global-mapper.php)

Figure 2 .

 2 Figure 2. ADMIXTURE plot using the low density database with K = 14 (the optimum determined by crossvalidation). Each component is identified by a specific color and a C label which corresponds to its order of appearance from K = 2 to K = 14.

Figure 3 .

 3 Figure 3. (a) An f3 outgroup statistics analysis showing shared genetic history with Austronesian groups (represented by indigenous Taiwanese) compared to Mainland Southeast Asian groups (represented by the H'tin). (b) Genetic similarity between Ma'anyan and other Asian populations measured using f3 outgroup statistics. Error bars show the standard error of the f3 statistics. Red dots represent East Asian groups; blue dots represent Island Southeast Asian groups; green dots represent Mainland Southeast Asian groups.

Figure 4 .

 4 Figure 4. Shared Identity-By-Descent fragments between pairs of individuals in Southeast Asia, filtering for shared IBD >20 cM, 40 cM and 60 cM. Each individual is represented as a blue dot. Each individual is represented as a blue dot. Populations are represented by a circle of dots. Shared IBD fragments are represented by a black line. The maps were generated using Global Mapper v.15 software (http://www.bluemarblegeo.com/ products/global-mapper.php). The networks lines were generated using Cytoscape v.3.2.152 software.

  explaining 39.1% of the variance) largely separated the continental groups of Africa, Europe, South Asia, and East and Southeast Asia. The second component (PC2; explaining 15.5% of the variance) differentiated the Malagasy, and separated the East and Southeast Asians into a broad north-to-south gradient. The Ma'anyan and South Kalimantan Dayak populations fall within the Asian cluster. The three previously published Malagasy groups (Temoro, Vezo and Mikea) are located at an intermediate position between the African and Asian clusters,

Figure 1 .

 1 Figure 1. Map showing the distribution of Bajo communities across Island Southeast Asia (yellow), together with the location of sampled Bajo villages (red dots) and sampled historically related communities (blue dots).

  Biological sampling was conducted by the Eijkman Institute for Molecular Biology, with the assistance of Indonesian Public Health clinic staff, following protocols for the protection of human subjects established by the Eijkman Institute. All samples were collected with informed consent from unrelated individuals. Collection and use of these samples was approved by the Research Ethics Commission at the Eijkman Institute for Molecular Biology, Indonesia.

Figure 4 .

 4 Figure 4. Admixture history of the three Bajo communities inferred with GLOBETROTTER. (a) Admixture of Bugis (South Sulawesi) with multiple populations, including Malay, Filipinos and Papuans, up to 1,600 years ago (ya), followed by subsequent admixture of pre-Bajo Kendari by Bugis and Papuans around 1,750 ya. (b) The expansion of the Śrīvijaya empire to Southeast Borneo triggered the dispersal of Bajo language, culture and people in many directions, including South Sulawesi and the Kendari, who assimilated them into its society. (c) South Sulawesi populations subsequently migrated westward to Southeast Borneo, forming the Kotabaru community by admixing with local Banjar populations, in addition to Indian influences through the reigning Malay empire around 925 ya. Northward migrations formed the Derawan community, which also admixed with local Malay and Filipino groups around 675 ya. The influence of South Sulawesi populations (dashed arrows) is observed in both the Kotabaru and Derawan Bajo. (d) Recent interactions between the three Bajo communities were maintained with different intensities (dashed lines).

Figure 1 .

 1 Figure 1. Localization of the Asian ancestry of Malagasy by (A) a TreeMix dendrogram, (B) FST distances and f3 statistics, all based on the Asian-SNP dataset, and (C) a shared IBD analysis based on haplotypes inferred from the high density of SNP dataset.(A) The TreeMix dendrogram was inferred imposing no a priori assumptions of migration, displaying only the tree topology. (B) Values of the f3(Asian-SNP Vezo, X; Yoruba) statistics are represented by dots with standard error bars. The color of each dot corresponds to the FST distances between the Asian ancestry of the Vezo and each Asian population using a grey-yellow-red color scale from the highest (0.196) to the lowest values (0.02). (C) The cumulative shared IBD (Mb) between pairs of Malagasy:Asian individuals were averaged to obtain one value of IBD sharing per Asian population. The obtained values are represented by a grey-yellow-red color scale. The numbers 1 to 15 correspond to the populations presented on the TreeMix dendrogram with the addition of 16 which stands for Brahmin Indian.

Figure 2 .

 2 Figure 2. Scenario for the Asian genetic ancestry in Malagasy based on the best fit models inferred by GLOBETROTTER. The brown circle represents the Malagasy (bottom left), while the green circle represents the Banjar (right). Red semicircles show the African ancestry (South African Bantu), while the other semicircles represent Asian ancestry from Malay (blue), Banjar (green) and Ma'anyan (yellow). Black dots highlight other populations included in the high density genomic dataset. The arrows show migration events, with indicative routes, inferred in our analyses with dates of admixture in italic estimated by GLOBETROTTER. Dates in bold correspond to dates of migration estimated from archaeological and historical data(Beaujard, 2012b).

1 .

 1 Conclusions and contributionsMy thesis had two main aims: 1) To determine the origin of human genetic diversity in Indonesia; and 2) To assess how this diversity impacts the gene pool of populations in the Indian Ocean region. To achieve these aims I sampled new Indonesian populations in Borneo, and used a broad range of molecular and bioinformatic approaches for sample and data analyses, designed to answer questions regarding human demographic history and migration. Discussions of the results have been made in an interdisciplinary context, drawing on inferences from other disciplines, such as linguistics, history, archeology, and anthropology. I have published the results of my doctoral study as 1 st author in five articles in peer-reviewed scientific journals. In the first part of this study (uniparental markers analyses, section 3.1), I used uniparental markers to determine the genetic background of the Bornean populations within the complex genetic diversity of Indonesia. Genetically, there is clear segregation between western and eastern Indonesian populations, and the genetic profiles of the new Bornean populations are related to those of western Indonesian populations. They have mitochondrial and Ychromosome haplogroups from East Asia/mainland Southeast Asia, and a limited number of western Eurasian haplogroups. In relation to this, results of which are published in the second article, I detected the genetic influence of western Eurasians on present-day Indonesian populations. I found that populations from Java and Bali have the most significant influence from western Eurasian mtDNA and Y-chromosome haplogroups, and in contrast populations from Borneo, Maluku, Nias, and Mentawai have the least genetic influence. Concerning the relationship between Indonesian and Malagasy populations, I performed standard genetic distance and haplotype-sharing analyses to observe which Indonesian populations are the closest genetically to the Malagasy. The study showed that populations from eastern Indonesia exhibit the closest link with the Malagasy, specifically Sulawesi and Lesser Sunda island populations. This is most probably driven by the strong presence of the Polynesian motif mitochondrial (macro)haplogroup (B4a1a1*) in eastern Indonesia and Madagascar. Interestingly, no plausible connection with the Malagasy's linguistic sister population, the Ma'anyan was found. Moreover, according to my preliminary results on whole mitogenome sequences in the populations sampled (see

  was determined that the most plausible Asian ancestor of the Malagasy is the Banjar people, a population who lived in Banjarmasin, southeast Borneo, an admixed population between the Ma'anyans and Malay immigrants. I tested data from the Bajo and the Bornean populations with the Illumina Omni 5 Indonesian data altogether (Annex I), using GLOBETROTTER analysis. The results, however, did not change, and the Banjar remained the most plausible Asian ancestral population to the Malagasy. This conclusion is supported by historical and linguistic evidence; Indonesians were carried on the Srivijaya ship by the Malay Kingdom during their trading activities to eastern Africa (1 st millennium CE), during a period of significant proto-globalization along the Indian Ocean rim.The key factor that links all of these results together is the presence of the Malay Kingdom in southern Borneo; this Kingdom played a very important role in triggering population admixture and demographic fluctuations in the region, and in Indonesia in general. A Srivijaya Kingdom outpost was established in southern Borneo because of its strategic location. The long coastline might have extended northward as far as 200 kilometers, and further inland than at present, and this outpost was possibly located near the Tanjung region, the auto-identified original homeland of the Ma'anyans. It forced the Ma'anyan people to move further towards the forests in the current East Barito district, where they are still present today. As the coastline moved southward, the trading post was also moved south and it later formed the city of Banjarmasin, which is the main city, commercial state and activity centre of the trading network of this region. During their establishment, the Malay Kingdom introduced Malay cultures and words to the indigenous populations in the region. Moreover, gene flow has been detected from populations with the Malay genetic background to indigenous populations living in the Malay Kingdom, mainly in southern and southeastern Borneo, but not in central or eastern Borneo. This event might have prompted the migration of proto-Malagasy groups from southern Borneo into Madagascar in a Malay-led oceanic voyage, although the cause of their migration remains elusive (potentially related to trading or slavery). This event might also have triggered the outbound dispersal of proto-Bajo groups from southern Borneo, which initiated the life history of the Bajo sea nomads in the Indonesian archipelago. On the other hand, the reign of the Hindu/Malay Kingdom(s) in the archipelago accommodated trading activities by merchants from South Asia and the Middle

3 .

 3 Despite a close linguistic affinity with the Malagasy, the Ma'anyan are not their direct ancestors. The most probable ancestor of the Malagasy is the Banjar, an admixed population composed of Ma'anyan and Malay individuals, whose genetic influence was present during the trading activities of the Malay Kingdom on the eastern coast of Africa from the mid 7 th century CE. 4. Bajo sea nomads have a unique genetic background, which can be explained by their nomadic lifestyle. They are, however, not linked directly to the migration process from southern Borneo to Madagascar, although their dispersal started at the same time as people from southern Borneo departed to Madagascar.

  Indonesia and in other populations from ISEA. Concerning ISEA, a comprehensive coverage of samples in this area would help to identify the source of local Asian ancestry in each of the unsampled populations. Borneo is understudied in Indonesian population genetic research.Almost all major local populations in Sumatra, Java, Bali, Sulawesi, Lesser Sunda Islands and Maluku have been sampled, however, Borneo has not been sampled thoroughly. In collaboration with international research institutions, I am co-leading a genomic research project in Borneo, together with Prof. Herawati Sudoyo from the Eijkman Institute for Molecular Biology, Jakarta, funded by the Indonesian Science Fund (DIPI). Starting this year, I am planning other sampling activities to cover all major ethnic and linguistic groups in Borneo. This data will generate important information on the history of human settlement in Borneo and the population structure of the indigenous Dayak people in Kalimantan: how their genetic diversity reflects that of present-day Indonesians, to reveal how people have adapted to different environments and evolved different lifestyles, continuing the works that have been done during my doctoral study (Publication list, Annex J) Concerning the history of human settlement in Madagascar, the ancestor of the Malagasy has been pinpointed in this study. However, I only used three southern Malagasy populations as representatives of the Malagasy population, and therefore, more individuals in other Malagasy populations should be included in future studies to confirm this finding. In addition, the exact maritime routes taken during the migration events remain unknown. The inclusion of sample populations across the Indian Ocean rim, may provide information on a possible indirect route from Indonesia to eastern Africa. In this context, the inclusion of various populations on the eastern coast of Africa, such as the Swahili and Comoros, can give further insight on the Indonesian influence in the western corner of the Indian Ocean, and also on the African ancestor of the Malagasy, so concluding the scenario of human settlement in Madagascar. My current involvement in the international research projects led by Dr. François-Xavier Ricaut at the University of Toulouse (genomic and archaeological projects in Papua New Guinea and genomic project on the Swahili corridor in East Africa), will allow us to screen populations in East Africa and in the regions of eastern Indonesia and Melanesia where the Polynesian motif possibly arose.

Figure S2 .

 S2 Figure S2. Population proportion based on mitochondrial DNA haplogroups estimated with the lsei algorithm.

Figure S2 .

 S2 Figure S2. Cross-validation plot generated from the ADMIXTURE analysis.

Figure S3 .

 S3 Figure S3. Runs of Homozygosity results showing that the Ma'anyan have comparable homozygosity relative to other Borneo populations.

Figure S4 .

 S4 Figure S4. TreeMix analysis on the low density dataset with eight migration nodes showing no gene flow to or from the Ma'anyan.

Figure S5 .

 S5 Figure S5. Shared Identity-By-Descent fragments between pairs of individuals in Southeast Asia, using nine filtering thresholds (from 10cM to 90cM). The maps were generated using Global Mapper v.15 software (http://www.bluemarblegeo.com/ products/global-mapper.php).The networks lines were generated using Cytoscape v.3.2.152 software.

Figure S6 .

 S6 Figure S6. Principal Component Analysis on all populations in the low density dataset. Ma'anyan and South Kalimantan Dayak individuals are clustered together with other Island Southeast Asian individuals.

Figure S7 . 14 Figure S8 .

 S714S8 Figure S7. ADMIXTURE plots on the low density dataset from K = 2-14

Figure S1 .

 S1 Figure S1. Principal component analysis of the three Bajo communities (red symbols) within East Asia genetic diversity.

Figure S2 .

 S2 Figure S2. Clustering analysis using fineSTRUCTURE showing Bajo individuals clustered within each community (blue boxes) and no overlap between communities.

Figure S3 .

 S3 Figure S3. Admixture plot from K=11 -K=20 for all populations in the studied dataset. The lowest CV value is at K=17. The three Bajo groups are marked by asterisks.

Figure S4 .

 S4 Figure S4. Cross validation analysis of ADMIXTURE runs from K=11 to K=25 with 10 iterations showing K=17 as the most representative plot.

Figure S5 .

 S5 Figure S5. Comparisons of estimated autosomal and X ancestry on the basis of unsupervised clustering using ADMIXTURE. There is no significant difference between autosomal and X-chromosome of East Asian/Papuan ancestry in Kendari Bajo and Bugis (one-tailed Wilcoxon test P > 0.05), but there is significance difference, leading to potential Bajo ancestral female-bias admixture, in Derawan and Kotabaru Bajo (one tailed Wilcoxon test P < 0.01), traced by the Papuan component brought by Bajo ancestral women from Sulawesi to Borneo.

Figure S6 .

 S6 Figure S6. Runs of Homozygosity analyses on Island Southeast Asian populations compared to other representative populations from Africa, Europe, South Asia and East Asia.

Figure S7 .

 S7 Figure S7. Inbreeding coefficient analyses on Island Southeast Asian populations compared to other representative populations from Africa, Europe, South Asia and East Asia.

Figure

  Figure S8. Shared IBD results from refinedIBD showing long chunk IBD sharing between Bajo communities with (a) Derawan Bajo (b) Kotabaru Bajo (c) Kendari Bajo as target populations.

Figure S9 .

 S9 Figure S9. TreeMix analysis on 13 migration nodes showing migrations from Papuan cluster to the three Bajo communities.

Figure S3 .

 S3 Figure S3. Cross-validation plot generated from the ADMIXTURE analysis from K=2 to K=18 on the low density SNP dataset from 10 iterations. It shows that K=16 has the lowest median CV value thereby representing the strongly supported ADMIXTURE plot on the analysis.

Figure S5 .

 S5 Figure S5. Ancestry-specific Principal Component Analysis based on masked SNPs from individuals of the high density dataset obtained after PCAdmix analysis and plot with EIGENSOFT v6.0.1.

Figure S6 .

 S6 Figure S6. Shared Identity-By-Descent fragments between pairs of individuals in the high density dataset, filtering for different thresholds of shared IBD fragments (from IBD > 10cM to IBD >90cM), calculated with RefinedIBD. Populations are represented by a blue circle which diameter is proportional to the number of individuals (from n=4 to n=31). Shared IBD fragments between each pair of individuals are represented by a black line with Cytoscape.

Figure S7 .

 S7 Figure S7. Coancestry heat map (A) and pairwise coincidence matrix (B) of the individuals of the high SNP density dataset generated by fineSTRUCTURE ##(Lawson, et al. 2012)##. The color scale in (A) indicates the chunk counts between each pair of individuals calculated by Chromopainter. The color scale in (B) indicates the pairwise coincidence between each pair of individuals. Nodes are collapsed below 60% probability. For convenience, close labels are merged (e.g., Kenya-Luhya 1/2 refers to population sub-structure in two groups of the Kenya-Luhya).

Table 2 . 1 .

 21 List of the populations sampled

	No.	Ethnic group	Language	Region	Latitude Longitude n
	1	Ma'anyan	Ma'anyan	East Barito, Central Kalimantan	-2.108057 115.163496 167
	2	SK Dayak	Various southern Dayak languages	Banjarmasin, South Kalimantan	-3.319621 114.589684 38
	3	Ngaju	Ngaju	Banjarmasin, South Kalimantan	-3.319621 114.589684 28
	4	Banjar	Banjar/Malay	Banjarmasin, South Kalimantan	-3.319621 114.589684 100
	5	Samihim	Samihim (a subgroup of Ma'anyan)	Kotabaru, South Kalimantan	-2.485020 115.944103 71
	6	Bajo Kotabaru	Bajo	Kotabaru, South Kalimantan	-3.224478 116.267831 60
	7	Bajo Derawan	Bajo	Berau, East Kalimantan	2.284365 118.243355 42

2.2.2. Fieldwork

Sampling campaigns were performed in the Indonesian part of Borneo Island (Kalimantan) during different phases of my doctoral study. The first sampling campaign was undertaken in 2013, a few months prior to the starting the doctoral program. The subsequent sampling campaigns were performed in late 2014 and twice in 2015. Each campaign required 2 weeks of paperwork (clearance and permits from local authorities), and on average 2 weeks for sampling individuals in each ethnic group with a team of 5 to 6 people (scientists, technicians and medics). Sampling activities were conducted in different areas of Borneo Island to include 6 distinct ethnicities and 1 Dayak group of various ethnicities. All samples collected in the fieldwork campaigns are summarised in Table

2

.1.

Table 2 . 2 .

 22 List of archived samples of populations involved in this study.

	No. Ethnic group	Language	Region	Latitude Longitude n
	8	Lebbo'	Lebbo'	Malinau, North Kalimantan	1.785167 114.829353
	9	Bajo Kendari	Bajo	Kendari, Southeast Sulawesi	-4.001891 122.509459
	10	Bugis	Bugis	Luwu, South Sulawesi	-3.311117 120.347988
	11	Mandar	Mandar	Majene, West Sulawesi	-3.264819 118.880867
	12 North Maluku	Various local Austronesian and Papuan languages	Ternate, North Maluku	0.786298 127.374594

Table 2

 2 All archived samples are stored in each institution, and those included in my study are listed in Table 2.2. The geographical locations of all new and archived samples are depicted in Figure 2.1.

.1 and Table 2.2. The Indonesian map is taken from http://freevectormaps.com 2.2.3. Archived samples I incorporated samples in my data analyses from previous independent sampling campaigns in Indonesia conducted by Dr. François-Xavier Ricaut (AMIS laboratory, University of Toulouse) through the MAFBO (Mission Archéologique Francaise à Borneo) research project, and also through a project led by the Human Genome Diversity and Diseases Laboratory of Eijkman Institute for Molecular Biology. 2.2.4. Comparative dataset I included SNP data from public databases, such as the 1000 Genomes (The 1000 Genomes Project Consortium, 2015) (http://www.internationalgenome.org), HGDP (Li et al., 2008) (http://www.cephb.fr/en/hgdp_panel.php), HUGO Pan Asian SNP (HUGO Pan-Asian SNP Consortium et al., 2009) (http://www4a.biotec.or.th/PASNP/front-page), and other published data from several publications. For mtDNA and Y-chromosome haplogroup comparative datasets, I incorporated published data on studies of Indonesian populations

Table 1 .

 1 Y chromosome haplogroup frequencies in the Ma'anyan, Lebbo' and Bajo.

	Haplogroups	Lebbo'	Ma'anyan	Bajo	Geographic origin
	C*	C-RPS4Y* 0.1333	0.5222	0.0370	SEA
	K*	K-M9*	0.0667	--	--	SEA
	KxLT	K-M526* 0.1333	0.0222	0.2222	SEA
	O1a	O-M119*	--	0.0222	0.0370	SEA
	O1a1	O-P203	--	0.1000	--	SEA
	O2a1	O-M95*	0.3333	0.0778	--	SEA
	O3	O-M122*	--	0.0111	0.0370	SEA
	C1c	C-M38*	--	--	0.2222	SEA
	O1a2	O-M110	0.2667	0.0222	--	SEA
	O2a1a	O-M88	--	0.0111	--	SEA
	O3a2	O-P201*	0.0667	0.1778	0.0741	SEA
	O3a2b	O-M7	--	--	0.0370	SEA
	M1a	M-186	--	--	0.0741	SEA
	P*	P-M45*	--	0.0222	--	SEA
	R*	M-207*	--	--	0.1481	WE
	R1a	R-M17	--	0.0111	--	WE
	T1a	T-M70	--	--	0.0741	WE
	L1a	L-M76	--	--	0.0370	WE
	Note.
	SEA: Southeast Asian origin; WE: Western Eurasian origin

Table 2 .

 2 Mitochondrial haplogroup frequencies in the Ma'anyan, Lebbo' and Bajo.

	Haplogroups	Lebbo'	Ma'anyan	Bajo	Geographic origin
	B4a	0.2105	0.0943	0.0741	MA
	B4c1b	--	0.0252	0.0741	MA
	B4c2	--	0.1887	--	MA
	B5a	0.1579	0.0377	0.0370	MA
	B4a2a	--	0.0440	--	MA
	B4a4	--	--	0.0741	MA
	B4b1	--	0.0818	--	MA
	F3b1a	--	0.0189	--	MA
	M12	--	0.0377	--	MA
	M20	0.1579	0.0440	--	MA
	M71a2	0.1579	--	--	MA
	M73	--	0.0566	0.0370	MA
	M74b1	--	0.1069	--	MA
	N22	--	0.0189	--	MA
	N9a6a	--	0.0252	--	MA
	R22	--	--	0.0370	MA
	R9b1a1a	0.1053	--	--	MA
	X	--	--	0.0370	MA
	Q1	--	--	0.0741	NG
	B4a1a1	--	--	0.0370	Taiw
	D4s	--	0.0629	--	Taiw
	E1a	0.2105	--	0.0741	Taiw
	F1a	--	0.0377	0.0370	Taiw
	F1a1a	--	0.0377	--	Taiw
	F1a3	--	--	0.0741	Taiw
	F1a4	--	0.0252	--	Taiw
	M7b1a1i	--	--	0.1481	Taiw
	M7b1a2	--	0.0126	0.0741	Taiw
	M7c1a4a	--	0.0126	0.1111	Taiw
	M2	--	0.0063	--	WE
	M35a	--	0.0189	--	WE
	M5a4	--	0.0063	--	WE
	Note.

MA: Mainland Asian origin; NG: New Guinea origin; Taiw: Out of Taiwan origin; WE: Western Eurasian origin

  Wood, E.T.,Stover, D.A., Ehret, C., Destro-Bisol, G., Spedini, G., McLeod, H., Louie, L., Bamshad, M., Strassmann, B.I., Soodyall, H., Hammer, M.F., 2005. Contrasting patterns of Y chromosome and mtDNA variation in Africa: evidence for sex-biased demographic processes. Eur. J. Hum. Genet. 13, 867-876. doi:10.1038/sj.ejhg.5201408 Xu, S., Pugach, I., Stoneking, M., Kayser, M., Jin, L., 2012. Genetic dating indicates that the Asian-Papuan admixture through Eastern Indonesia corresponds to the Austronesian expansion. Proc. Natl. Acad. Sci. 109, 4574-4579. doi:10.1073/pnas.1118892109 3.1.2.2. Introduction Western Eurasia (WE), notably the Near East and South Asia, had established very close contact with Southeast Asia since 4th B.C.E (Bellina & Glover, 2004), and spread to Island South East Asia (particularly Indonesia) through cultural and trading networks in Maritime Silk Route as early as the 1st century B.C.E.

	3.1.1.7. Miscellaneous
	Abbreviations

  . Mitochondrial haplogroups were determined with the Haplogrep program (http://haplogrep.uibk.ac.at) based on Phylotree v.16 (van Oven and Kayser, 2009). Y chromosome haplogroups were assigned from SNPs data based on the updated ISOGG Y-DNA haplogroup tree (International Society of Genetic Genealogy, 2014) and the Y-Phylotree (van Oven et al., 2014).

  closer genetic connections with neighboring populations than distant Bajo groups. The sea oriented way of life of the Bajo and their prime role in the maritime trading network placed them in contact with surprisingly diverse populations, including South Asians and Papuans, whose contact left secondary traces in the genomes of the Bajo today. Studies of other Bajo communities, of which there are hundreds scattered across 1,300 km of Island Southeast Asia Malagasy genetic diversity results from an exceptional proto-globalisation process that took place over a thousand years ago across the Indian Ocean. Previous efforts to locate the Asian origin of Malagasy highlighted Borneo broadly as a potential source, but so far no firm source populations were identified. Here, we have generated genome-wide data from two Southeast Borneo populations, the Banjar and the Ngaju, together with published data from populations across the Indian Ocean region. We find strong support for an origin of the Asian ancestry of Malagasy among the Banjar. This group emerged from the long-standing presence of a Malay Empire trading post in Southeast Borneo, which favoured admixture between the Malay and an autochthonous Borneo group, the Ma'anyan. Reconciling genetic, historical and linguistic data, we show that the Banjar, in Malay-led voyages, were the most probable Asian source among the analysed groups in the founding of the Malagasy gene pool.

	3.2.3.1. Abstract 3.2.3.2. Main manuscript
	from east to west and 2,000 km from north to south, are likely to reveal more nuanced
	patterns of contact, as well as differential associations with means of subsistence, language,
	traditions and origin myths. In addition, this may well provide greater insight into the likely
	genetic histories of other nomadic populations that speak closely related languages, but span
	wide geographical areas.
	3.2.2.6. Miscellaneous

  3.2.3.3. Methods All experimental and analytical procedures are described in the Supplementary Method file (Supplementary Material online). This study was approved by the Research Ethics Commission of the Eijkman Institute for Molecular Biology (Jakarta, Indonesia).

Table 2

 2 .1 and 2.2), there are no Malagasy motif haplogroups (B4a1a1b) observed (Annex H). This motif has been tested in research byCox et al. (2012) on ~3,000 individuals from populations across the Indonesian archipelago, but no positive results have yet emerged. It still remains unclear whether this haplogroup emerged in situ, during migration, or in unsampled Indonesian populations.In the second part of this study (autosomal DNA analyses, section 3.2), I explored the autosomal genetic diversity, using genome-wide SNPs, of the Bornean populations and their connection with the Malagasy. The Ma'anyan have a unique genetic component that has never been observed at such a high frequency in one population. Explored further, this component is strongly related to the Austronesian genetic profile, which is carried by Aboriginal Taiwanese and the Igorot (Kankanaey) of the Philippines, and not to mainland Southeast Asians who are often affiliated to Austroasiatic speakers. A new ancestral component in the Ma'anyan is an important discovery, and its presence does not appear to be linked to any recent admixture events based on the formal admixture tests conducted. This result may give important information on the scenario of Austronesian dispersal throughout

  infection, such as sickle cell anemia and Duffy negativity in western Africa, Hemoglobin E (HbE) and Southeast Asian Ovalocytosis (SAO) in Southeast Asia, and alpha and beta Thalassaemia and G6PD deficiency which have different genotypes in different populations across the world. Research by Rabe et al. (2002) on several villages in the highlands of central Madagascar have shown a small percentage of SAO presence. Further surveys of SAO presence throughout Madagascar, and determining the presence of the SLC4A1 gene haplotype around the SAO-deletion region, can give additional supporting evidence of an Indonesian influence in Madagascar. Studies detecting SAOpresence in Indonesian and eastern African populations is currently in progress. In addition, other unique Indonesian genotypes for molecular adaptation against malaria, as mentioned, will also be investigated in the future.I have started a collaboration with the Pasteur Institute in Paris, to study the distribution of HTLV-1 and HHV-8 viruses in Indonesia. These viruses have wide distributions in Oceania and East Asia, but no studies have been conducted in Indonesia in the context of it being a focal crossroad in human migration from East Asia into Oceania. Traces of these viruses must be present in Indonesia. This study will bring new understanding on HTLV-1 and HHV-8 genotype diversity, and will also complement the scenario of Austronesian eastward dispersal into the Pacific. List of analyses performed on each population brought in this study.

	Annex B. No Ethnic group	mtDNA HVR	Whole mtDNA	Y-chromoso me SNPs	Array Omni Express (700K SNPs)	Array Omni 2.5 (2.5M SNPs)	Array Omni 5 (4.5M SNPs)
	1	Ma'anyan	v	*	v	v
	2	SK Dayak	v	*	v	v
	3	Ngaju	v	*	v	v
	4	Banjar		*	*	v
	5	Samihim		*	*			v
	6 Bajo Kotabaru		*	*			v
	7 Bajo Derawan		*	*			v
	8	Lebbo'	v	*	v	v
	9 Bajo Kendari	v	*	v	v
	10	Bugis		*	*			v
	11	Mandar		*	*		v
	12 North Maluku	v	*	v			v
	* Data have been generated but not analysed in this thesis due to different data production
	time-frame.

Table S1 .

 S1 List of populations used in this study.

Table S2 .

 S2 List of Y chromosome SNP markers screened.

Table S1 .

 S1 Frequency of Western Eurasian origin Y-haplogroups in Indonesia

Table S1 (continued).

 S1 Frequency of Western Eurasian origin Y-haplogroups in Indonesia

Table S2 .

 S2 FST genetic distances between Ma'anyan and other populations in the low density dataset.

	Populations	Ma'anyan	Populations Ma'anyan
	SK-Dayak	0.006	Bidayuh	0.026
	Sundanese	0.012	Manobo	0.027
	Javanese	0.012	Manggarai	0.029
	Dayak	0.012	Taiwan	0.029
	Cambodian	0.014	Karen	0.03
	Sumatran-Malay	0.014	Hmong-CN	0.034
	Malaysia-Malay	0.015	Lawa	0.034
	Filipino	0.015	Lebbo'	0.034
	Tai-Yuan	0.016	Mentawai	0.036
	Vietnamese	0.017	Lamaholot	0.038
	Toraja	0.017	Hmong-TH	0.041
	Dai	0.018	Lembata	0.042
	Tai-Yong	0.018	Igorot	0.042
	Toba	0.018	Paluang	0.043
	Tai-Khuen	0.019	H'tin	0.043
	Bajo	0.019	Jehai	0.056
	Karo	0.02	Ati	0.056
	Murut	0.021	Agta	0.057
	Burmese	0.022	Alor	0.063
	Tai-Lue	0.022	Kensiu	0.073
	Mon	0.022	IN-Brahmin	0.075
	Plang	0.022	Vezo	0.08
	Dusun	0.022	Temoro	0.081
	E-Sumba	0.023	Mikea	0.085
	Han	0.024	Iraya	0.087
	Wa	0.024	Mamanwa	0.091
	Kambera	0.024	Aeta	0.094
	Yao	0.025	French	0.108
	C-Sumba	0.025	Mlabri	0.154
	W-Sumba	0.025	Yoruba	0.164
	Temuan	0.026

Table S3 .

 S3 Results of f3-statistics, showing the lowest 50 Z-score combinations, on all populations in the low density dataset to test for Ma'anyan admixture. An f3-statistic is expected to be positive significant with a Z score >-2 if no admixture has taken place.

	Ma'anyan	Iraya	Bidayuh	0,00209877 0,000258412	8,1218
	Ma'anyan	H'tin	Agta	0,00258133 0,000316796 8,14823
	Ma'anyan	Jehai	Mentawai	0,00198762 0,000243679	8,1567
	Ma'anyan	Kensiu	Taiwan	0,00151931 0,000184827 8,22014
	Ma'anyan	Banjar	Mlabri	0,00253314 0,000308105 8,22168
	Target population Ma'anyan Ma'anyan Ma'anyan Ma'anyan Ma'anyan Ma'anyan Ma'anyan Ma'anyan Ma'anyan	Population 1* Jehai Iraya Alor Mlabri Mlabri Jehai Hmong-TH Mlabri H'tin	Population 2* Taiwan Mlabri Mlabri Igorot Toba Igorot Yoruba Taiwan Dayak	f3 value 0,00131213 0,000159384 8,23251 SE Z-score 0,0012494 0,000643656 0,00314537 0,000380185 8,27324 1,9411 0,00246328 0,000295879 8,32529 0,000964953 0,000388148 2,48604 0,000531593 0,00021105 0,00404823 0,000485567 8,33712 2,51879 0,000980097 0,000315858 3,10296 0,0021435 0,000257094 8,3374
	Ma'anyan	Kensiu	Igorot	0,00100631 0,000251586 3,99986
	Ma'anyan * This table shows the 50 lowest Z-score combinations of populations from all combinations produced in the f3-Mlabri Agta 0,00216078 0,000539446 4,00555
	Ma'anyan statistics analysis	Manobo	Mlabri	0,00146867 0,000360337 4,07582
	Ma'anyan	H'tin	Igorot	0,000966092 0,000236618 4,08291
	Ma'anyan	Aeta	Mlabri	0,00309591 0,000719123 4,30511
	Ma'anyan	Sumatran-Malay	Mlabri	0,00241122 0,000508989 4,73727
	Ma'anyan	Yoruba	Igorot	0,00206575 0,000392053 5,26905
	Ma'anyan	Ati	Mlabri	0,00227472 0,000409701 5,55215
	Ma'anyan	Filipino	Mlabri	0,00159951 0,000285164 5,60909
	Ma'anyan	Mamanwa	Mlabri	0,00186683 0,000306453 6,09173
	Ma'anyan	Iraya	Jehai	0,00209051 0,000343169	6,0918
	Ma'anyan	Dayak	Mlabri	0,00207119 0,000331207 6,25346
	Ma'anyan	Mikea	Igorot	0,00222687 0,000353957 6,29137
	Ma'anyan	Iraya	Kensiu	0,00263222 0,000415146 6,34046
	Ma'anyan	Mentawai	Mlabri	0,00214312 0,000337205 6,35555
	Ma'anyan	Yoruba	Mentawai	0,00242817 0,000378587 6,41376
	Ma'anyan	Temuan	Igorot	0,00127519 0,000198279 6,43128
	Ma'anyan	Yoruba	Murut	0,00219002 0,000336151	6,515
	Ma'anyan	Mentawai	H'tin	0,00184931 0,000281734 6,56402
	Ma'anyan	Iraya	H'tin	0,00217233 0,000324486 6,69467
	Ma'anyan	Mlabri	E-Sumba	0,00266682 0,000382994 6,96309
	Ma'anyan	Hmong-TH	Mlabri	0,00314585 0,000443036 7,10068
	Ma'anyan	Dusun	Mlabri	0,00233471 0,000323972 7,20654
	Ma'anyan	H'tin	Taiwan	0,00154934 0,000214634 7,21854
	Ma'anyan	Vezo	Igorot	0,00229219 0,000316639 7,23912
	Ma'anyan	Yoruba	Lebbo'	0,00283852 0,000388072 7,31441
	Ma'anyan	Temoro	Igorot	0,00223352 0,000293669 7,60558
	Ma'anyan	C-Sumba	Mlabri	0,00269372 0,000352449 7,64286
	Ma'anyan	Yoruba	Mlabri	0,0036162	0,000471247 7,67367
	Ma'anyan	Mlabri	Toraja	0,00196584 0,000254647 7,71987
	Ma'anyan	Sumatran-Malay	Yoruba	0,00334507 0,000430849 7,76391
	Ma'anyan	French	Mlabri	0,00425063 0,000535803 7,93319
	Ma'anyan	H'tin	Toraja	0,00188538 0,000236766 7,96307
	Ma'anyan	Mlabri	Tai-Lue	0,00356898 0,000443113 8,05434
	Ma'anyan	Mlabri	Murut	0,00249194	0,00030931	8,05645
	Ma'anyan	French	Igorot	0,00228156 0,000282665 8,07162

Table S4 .

 S4 Pairwise FST values from the dataset of Asian SNPs

		Mikea Temoro	Vezo	Malagasy (average)
	Mikea	0	0,018	0,014
	Temoro	0,018	0	0,013
	Vezo	0,014	0,013	0
	Han	0,04	0,029	0,033	0,034
	Dai	0,035	0,025	0,027	0,029
	Cambodian	0,033	0,024	0,025	0,027
	Burmese	0,035	0,025	0,029	0,030
	Vietnamese	0,035	0,024	0,026	0,028
	Dusun	0,04	0,031	0,031	0,034
	Murut	0,039	0,029	0,03	0,033
	Ma'anyan	0,032	0,024	0,025	0,027
	SK-Dayak	0,027	0,018	0,02	0,022
	Lebbo'	0,048	0,04	0,043	0,044
	Bajo	0,033	0,023	0,026	0,027
	C-Sumba	0,035	0,026	0,028	0,030
	E-Sumba	0,041	0,029	0,033	0,034
	W-Sumba	0,038	0,027	0,031	0,032
	Filipino	0,03	0,02	0,023	0,024
	Igorot	0,057	0,051	0,051	0,053

Table S2 .

 S2 Table of the populations included in both the low and high density SNP datasetsused in the study. Note: LDD: Low Density of SNP Dataset (40,272 SNPs); HDD: High Density of SNP Dataset (374,189 SNPs). *: Sumbanese of the LDD were sub-grouped in 3 locations of sampling for some analyses: West (W-Sumba), Central (C-Sumba), East (E-Sumba).; **: For some analyses Filipino individuals from Reich et al. (2011) and Mörseburg et al. (2016) were pooled. Results of f3-statistics showing the Z-score <-2 obtained for each combination on populations in the high density dataset to test for admixture. Only the 15 lowest Z-scores are shown for each tested group.

	Luzon	Onge	CHB	Igorot	Andaman -0,00059 0,00006	10 -9,63134	Sumbanese	-	Luhya S-	Igorot (Reich, et al. 2011) -0,00065 0,00011	-5,87579
	Dravidian Luzon Vietnamese Gyan CEU	Igorot Burmese	India -0,00046 0,00006 -0,00234 0,00008	12 -7,76522 -30,74300	Sumbanese Sumbanese	-	African_Bantu Yoruba	Igorot (Reich et al. 2011) -0,00065 0,00011 Igorot -0,00065 0,00011	-5,85895 -5,84816
	Besemah Gyan Malay-SG Semende Gyan CEU Gyan Ngaju	Indonesia (Sumatra) CEU -0,00235 0,00008 Indonesia (Sumatra) Sumbanese -0,00240 0,00009 CEU -0,00242 0,00009	8 -28,72070 9 -28,18800 -27,79990	Sumbanese Sumbanese Sumbanese	--	Eth-Somalian Somalian Gyan	Igorot (Reich et al. 2011) -0,00047 0,00010 Igorot -0,00045 0,00010 (Reich et al. 2011) Igorot -0,00021 0,00009	-4,53064 -4,34370 -2,35079
	Population Bidayuh Gyan SK-Dayak Yoruba Mende Gambian European Han Luhya Beninese Afar Tygray Amhara Wolayta Oromo Ari-Cutivator Ari-Blacksmith Gumuz Anuak Sudanese Somalian Bantu Mikea Temoro Vezo Lebbo Bajo Indian Nusa Tenggara Gyan Banjar Moluccas PNG Highlander Filipino** Philippines Negrito Taiwanese Aborigines Fiji Polynesian Sumbanese* Brahmin Burmese Vietnamese Igorot Filipino** Dusun Murut Ma'anyan SK.Dayak Ngaju Banjar Tested group Parental Pop A Gyan Vietnamese Bajo Luhya Gyan Dusun Bajo Gyan CEU Gyan CEU Gyan CEU Gyan CEU Gyan CEU Gyan CEU Gyan CEU Luhya Eth-Somalian Luhya Yoruba Luhya Yoruba Luhya S-African_Bantu Luhya Gyan Luhya S-African_Bantu Luhya Yoruba Luhya Malay-SG Luhya Yoruba Luhya Dusun Luhya SK-Dayak Luhya Ngaju Luhya Yoruba Luhya Yoruba Luhya Vietnamese Malay-SG Gyan Malay-SG Gyan lMalay-SG SK-Dayak S-Burmese Vietnamese Malay-SG Gyan Malay-SG CEU Burmese Gyan Malay-SG SK-Dayak Burmese CHB Malay-SG CEU S-Malay-SG Dusun Burmese African_Bantu Malay-SG Ngaju	Country Malaysia (Borneo) CEU -0,00242 0,00009 Nigeria Senegal Gambia USA China Kenya Benin Ethiopia Ethiopia Ethiopia Ethiopia Ethiopia Ethiopia Ethiopia Ethiopia Ethiopia Sudan Somalia South Africa Malagasy Malagasy Malagasy Indonesia (Borneo) Indonesia (Sulawesi) Singapore Indonesia CEU -0,00235 0,00009 Indonesia Papua New Guinea Philippines Philippines Taiwan Fiji Polynesia Indonesia (Sumba) India Myanmar Vietnam Philippines Philippines Malaysia (Borneo) Malaysia (Borneo) Indonesia (Borneo) Indonesia (Borneo) Indonesia (Borneo) Indonesia (Borneo) Parental Pop B f3 SD CEU -0,00238 0,00009 Igorot -0,00074 0,00015 CEU -0,00248 0,00009 Maanyan -0,00238 0,00009 Murut -0,00241 0,00009 Lebbo -0,00240 0,00009 Luzon -0,00224 0,00009 CHB -0,00225 0,00009 Bajo -0,00235 0,00010 Igorot -0,00231 0,00010 Yoruba -0,00072 0,00005 Somalian -0,00071 0,00005 CEU -0,00101 0,00007 Somalian -0,00062 0,00004 Yoruba -0,00087 0,00006 Eth-Somalian -0,00059 0,00005 Burmese -0,00068 0,00007 Yoruba -0,00068 0,00007 Sumbanese -0,00067 0,00007 Yoruba -0,00070 0,00007 Yoruba -0,00068 0,00007 Yoruba -0,00068 0,00007 CHB -0,00068 0,00007 Luzon -0,00067 0,00007 Yoruba -0,00068 0,00007 Maanyan -0,00165 0,00006 Murut -0,00190 0,00007 Gyan -0,00144 0,00005 Igorot -0,00202 0,00008 Eth-Somalian -0,00260 0,00007 Maanyan -0,00168 0,00007 Igorot -0,00290 0,00008 CEU -0,00151 0,00007 Luhya -0,00257 0,00007 Murut -0,00196 0,00008 Gyan -0,00159 0,00007 CHB -0,00261 0,00007 Gyan -0,00121 0,00006	N (LDD) 10 -27,08320 206 85 115 99 103 97 24 10 20 24 6 21 21 14 15 22 21 23 94 18 24 24 15 31 83 10 -26,65450 10 24 16 11 12 25 19 180 47 20 20 21 16 17 17 162 40 25 16 Z-score -26,49640 -4,83578 -26,47620 -26,35860 -25,80560 -25,68800 -25,41830 -24,96840 -24,66920 -23,36910 -15,55730 -15,36080 -14,90660 -13,93520 -13,82580 -12,47290 -10,42080 -10,24830 -10,19040 -10,17090 -10,16430 -10,06140 -10,01850 -9,95678 -9,92264 -26,43780 -26,38870 -26,33230 -24,03160 -36,71400 -23,49810 -36,48650 -23,18220 Vietnamese N (HDD) -Sumbanese 25 --25 25 25 -----------23 25 18 24 24 15 31 --Temoro African_Bantu CEU S-(International HapMap, et al. 2010) Igorot -0,00012 0,00011 -1,08230 (Reich et al. 2011) Reference (International HapMap et al. 2010) (International HapMap et al. 2010) (International HapMap et al. 2010) (International HapMap et al. 2010) (International HapMap et al. 2010) Fortes-Lima, personal communication (Pagani, et al. 2012) (Pagani et al. 2012) (Pagani et al. 2012) (Pagani et al. 2012) (Pagani et al. 2012) (Pagani et al. 2012) (Pagani et al. 2012) (Pagani et al. 2012) (Pagani et al. 2012) (Pagani et al. 2012) (Pagani et al. 2012) (May, et al. 2013) (Pierron, et al. 2014) (Pierron et al. 2014) (Pierron et al. 2014) (Pierron et al. 2014) (Pierron et al. 2014) Ngaju -0,01130 0,00009 -124,99600 (Reich et al. 2011) -(Reich et al. 2011) -(Reich et al. 2011) -(Reich et al. 2011) -(Reich et al. 2011) -(Reich et al. 2011) -(Reich et al. 2011) -(Reich et al. 2011) 25 (Cox, et al. forthcoming) 25 (Mörseburg, et al. forthcoming) 20 (Mörseburg et al. forthcoming) 20 (Mörseburg et al. forthcoming) 21 (Mörseburg et al. forthcoming) 16 (Mörseburg et al. forthcoming) 17 (Mörseburg et al. forthcoming) 17 (Mörseburg et al. forthcoming) 25 (Kusuma, et al. 2016) 25 (Kusuma et al. 2016) 25 this study 16 this study S-Tested group Parental Pop A Parental Pop B f3 SD Temoro African_Bantu SK-Dayak -0,01141 0,00009 -124,52900 Z-score Mikea SK-Dayak Yoruba -0,00995 0,00010 Temoro SK-Dayak Yoruba -0,01133 0,00009 -123,75300 -100,59000 Temoro Ngaju Yoruba -0,01122 0,00009 -123,16300 Temoro S-African_Bantu Maanyan -0,01147 0,00009 -122,94300 Temoro S-African_Bantu Banjar -0,01118 0,00009 -122,91200 Temoro S-African_Bantu Malay-SG -0,01083 0,00009 -122,90400 Temoro Banjar Yoruba -0,01112 0,00009 -121,74100 Temoro Yoruba Maanyan -0,01137 0,00009 -121,48900 Temoro Malay-SG Yoruba -0,01073 0,00009 -121,35500 Temoro Yoruba Murut -0,01149 0,00009 -121,07700 Temoro S-African_Bantu Murut -0,01157 0,00010 -120,65900 Temoro Vietnamese S-African_Bantu -0,01114 0,00009 -120,07700 Temoro S-African_Bantu Luzon -0,01108 0,00009 -119,93300 Temoro Yoruba Luzon -0,01099 0,00009 -118,51300 Vezo S-African_Bantu Ngaju -0,01131 0,00009 -126,64300 Vezo S-African_Bantu SK-Dayak -0,01140 0,00009 -125,42300 Vezo S-African_Bantu Maanyan -0,01147 0,00009 -124,43700 Vezo S-African_Bantu Malay-SG -0,01079 0,00009 -123,28900 Vezo S-African_Bantu Banjar -0,01118 0,00009 -122,99600 Vezo SK-Dayak Yoruba -0,01132 0,00009 -122,00400 Vezo Ngaju Yoruba -0,01123 0,00009 -121,63800 Vezo S-African_Bantu Murut -0,01161 0,00010 -121,03500 Vezo S-African_Bantu Luzon -0,01109 0,00009 -120,72900 Vezo Yoruba Maanyan -0,01138 0,00009 -120,61700 Vezo S-African_Bantu Dusun -0,01146 0,00010 -120,42300 Vezo Vietnamese S-African_Bantu -0,01113 0,00009 -120,37100 Vezo Malay-SG Yoruba -0,01070 0,00009 -119,67100 Vezo Banjar Yoruba -0,01112 0,00009 -119,60800 SK-Dayak Malay-SG Maanyan -0,00023 0,00003 Vezo Yoruba Murut -0,01153 0,00010 -118,59900 -7,08378 SK-Dayak Maanyan Bajo -0,00035 0,00005 Ngaju CHB -0,00062 0,00004 -16,10290 -7,02357 -35,51950 SK-Dayak CEU Maanyan -0,00041 0,00007 -23,08730 Vietnamese SK-Dayak CHB -0,00054 0,00004 -14,28810 -6,08851 -22,56590 Vietnamese Banjar CHB -0,00053 0,00004 -12,78690 (Teo, et al. 2009) -35,41820 SK-Dayak Maanyan CHB -0,00024 0,00004 -5,80104 -21,92340 Vietnamese Maanyan CHB -0,00052 0,00004 -12,52290
	Malay Burmese Yoruba Malay-SG SK-Dayak Burmese SK-Dayak Malay-SG Eth-Somalian	Singapore -0,00257 0,00007 Somalian CHB -0,00130 0,00006 Gyan -0,00220 0,00006 Murut -0,00172 0,00008	89 -34,33380 -21,53510 Vietnamese 25 SK-Dayak -34,22450 SK-Dayak -21,37210 Vietnamese	Gyan Malay-SG Temoro CHB	Igorot CHB (Teo et al. 2009) -0,00049 0,00008 -0,00043 0,00004 Maanyan -0,00028 0,00005 Murut -0,00042 0,00005	-5,79169 -11,57120 -5,32602 -9,27405
	Burmese Luzon Malay-SG Luzon Malay-SG Luzon Malay-SG Luzon Malay-SG Luzon Mikea Luzon Luzon Mikea Luzon Mikea	Gyan Gyan SK-Dayak Somalian Somalian CEU Eth-Somalian Eth-Somalian Maanyan S-Luhya African_Bantu Yoruba S-S-African_Bantu African_Bantu S-Vezo African_Bantu S-	Maanyan Eth-Igorot Somalian Igorot Murut Igorot Maanyan Igorot Somalian Igorot SK-Dayak Igorot Igorot Ngaju Igorot Maanyan	-0,00233 0,00007 -0,00226 0,00008 -0,00129 0,00006 -0,00228 0,00009 -0,00169 0,00008 -0,00233 0,00010 -0,00138 0,00007 -0,00227 0,00010 -0,00137 0,00007 -0,00229 0,00010 -0,01002 0,00010 -103,48400 Vietnamese -33,86420 SK-Dayak -26,73450 SK-Dayak -21,28580 Vietnamese -24,00030 SK-Dayak -21,09710 Vietnamese -23,76760 SK-Dayak -20,51370 Vietnamese -23,51470 SK-Dayak -20,33400 Vietnamese -22,86680 Somalian -0,00229 0,00010 -22,43360 Somalian -0,00227 0,00010 -22,24460 Somalian -0,00991 0,00010 -102,49300 Vietnamese -0,00161 0,00008 -20,85780 Somalian -0,01012 0,00010 -102,06900 Vietnamese		Vezo Maanyan CHB Maanyan Dusun Luhya Burmese CHB S-African_Bantu Yoruba CHB CEU Gyan S-African_Bantu Gyan CEU	Maanyan Murut Lebbo Luhya CHB Igorot Igorot Bajo Maanyan CEU Sumbanese Luhya Igorot CEU Luhya Igorot	-0,00027 0,00005 -0,00021 0,00004 -0,00047 0,00005 -0,00034 0,00007 -0,00033 0,00005 -0,00049 0,00010 -0,00036 0,00005 -0,00025 0,00005 -0,00034 0,00007 -0,00478 0,00010 -0,00013 0,00004 -0,00448 0,00009 -0,00020 0,00009 -0,00443 0,00010 -0,00221 0,00009 -0,00012 0,00010	-5,20714 -9,09139 -5,04424 -7,09284 -4,91390 -6,54163 -4,90414 -4,59526 -4,84829 -2,85187 -47,79240 -47,43610 -2,18635 -44,19020 -1,17054 -25,10260
	Luzon Mikea		Mikea African_Bantu	Igorot Murut		-0,00166 0,00008 -0,01023 0,00010 -100,83700 -20,39340	Somalian		Gyan	Yoruba	-0,00237 0,00009	-24,97390
											S-
	Luzon			Temoro	Igorot		-0,00160 0,00008	-20,18860	Somalian		African_Bantu	Gyan	-0,00205 0,00009	-21,81550
	Luzon		Burmese	Igorot		-0,00112 0,00006	-18,23300	Somalian		Burmese	Luhya	-0,00036 0,00010	-3,47382
	Luzon			Igorot	Sumbanese	-0,00073 0,00006	-12,37340	Somalian		Yoruba	Burmese	-0,00034 0,00011	-2,98567
	Luzon		Malay-SG	Igorot		-0,00069 0,00006	-12,16120	Somalian		CHB	Luhya	-0,00013 0,00011	-1,19885

Table S3 .

 S3 f3-statistics table obtained for the tree configuration (Malagasy population; Asian population; Yoruba) using the Asian-SNP dataset.

	Kintaq	Mikea	Yoruba	0.108	0.006	18.301
	Mah-Meri	Mikea	Yoruba	0.113	0.005	20.671
	CheWong	Mikea	Yoruba	0.115	0.006	19.484
	Source 1 Jakun	Source 2 Mikea	Target Yoruba	f3 0.118	SE 0.006	Z-score 20.018	SNPs
	Han Temuan	Temoro Mikea	Yoruba Yoruba	0.114 0.115	0.005 0.005	21.092 21.211
	Burmese Seletar	Temoro Mikea	Yoruba Yoruba	0.108 0.109	0.005 0.006	21.899 19.324
	Vietnamese Malay	Temoro Mikea	Yoruba Yoruba	0.119 0.115	0.006 0.005	20.305 22.626
	Jehai Besemah	Temoro Mikea	Yoruba Yoruba	0.109 0.122	0.006 0.006	18.594 21.96
	Bateq Semende	Temoro Mikea	Yoruba Yoruba	0.106 0.12	0.006 0.006	16.485 20.337
	Mendriq Bidayuh	Temoro Mikea	Yoruba Yoruba	0.11 0.121	0.006 0.006	17.136 21.17
	Kintaq Banjar	Temoro Mikea	Yoruba Yoruba	0.108 0.122	0.006 0.005	18.793 22.223
	Mah-Meri Ngaju	Temoro Mikea	Yoruba Yoruba	0.111 0.119	0.006 0.006	19.042 21.055
	CheWong SK-Dayak	Temoro Mikea	Yoruba Yoruba	0.114 0.123	0.006 0.005	17.852 23.21
	Jakun Ma'anyan	Temoro Mikea	Yoruba Yoruba	0.117 0.123	0.006 0.006	19.377 21.426
	Temuan Lebbo	Temoro Mikea	Yoruba Yoruba	0.115 0.121	0.005 0.006	21.534 21.713
	Seletar Murut	Temoro Mikea	Yoruba Yoruba	0.115 0.118	0.007 0.005	17.066 21.946
	Malay Dusun	Temoro Mikea	Yoruba Yoruba	0.115 0.124	0.005 0.006	22.628 20.771
	Besemah Bajo	Temoro Mikea	Yoruba Yoruba	0.119 0.116	0.006 0.005	21.528 21.556
	Semende C-Sumbanese	Temoro Mikea	Yoruba Yoruba	0.123 0.116	0.006 0.006	21.331 19.959
	Bidayuh E-Sumbanese	Temoro Mikea	Yoruba Yoruba	0.118 0.113	0.006 0.006	21.085 19.793
	Banjar W-Sumbanese	Temoro Mikea	Yoruba Yoruba	0.121 0.115	0.006 0.005	21.923 21.267
	Ngaju Nusa_Tenga	Temoro Mikea	Yoruba Yoruba	0.12 0.114	0.005 0.006	22.258 18.352
	SK-Dayak Moluccas	Temoro Mikea	Yoruba Yoruba	0.121 0.116	0.005 0.006	23.247 17.925
	Ma'anyan PNG highlander	Temoro Mikea	Yoruba Yoruba	0.122 0.089	0.006 0.008	21.937 10.992
	Lebbo Philippine Negrito	Temoro Mikea	Yoruba Yoruba	0.117 0.109	0.005 0.006	21.457 17.881
	Murut Filipino	Temoro Mikea	Yoruba Yoruba	0.119 0.121	0.005 0.006	22.637 21.286
	Dusun Igorot	Temoro Mikea	Yoruba Yoruba	0.119 0.126	0.006 0.006	20.81 20.052
	Bajo Taiwan Aboriginese	Temoro Mikea	Yoruba Yoruba	0.116 0.12	0.005 0.006	21.905 20.126
	C-Sumbanese Fiji	Temoro Mikea	Yoruba Yoruba	0.117 0.107	0.005 0.006	21.529 18.074
	E-Sumbanese Polynesia	Temoro Mikea	Yoruba Yoruba	0.113 0.12	0.005 0.006	20.879 18.604
	W-Sumbanese	Temoro	Yoruba	0.114	0.005	21.931
	Nusa_Tenga	Temoro	Yoruba	0.107	0.006	18.523
	Moluccas	Temoro	Yoruba	0.111	0.006	19.981
	PNG highlander	Temoro	Yoruba	0.086	0.008	11.34
	Philippine Negrito	Temoro	Yoruba	0.109	0.006	19.665
	Filipino	Temoro	Yoruba	0.12	0.006	20.97
	Igorot	Temoro	Yoruba	0.127	0.006	22.68
	Taiwan Aboriginese	Temoro	Yoruba	0.119	0.006	20.335
	Fiji	Temoro	Yoruba	0.103	0.005	19.196
	Polynesia	Temoro	Yoruba	0.116	0.006	20.188
	Han	Vezo	Yoruba	0.12	0.005	25.6

Table S4 .

 S4 FST genetic distances (lower diagonal) between 'Asian-SNP' Malagasy and data from the Asian populations of the high density dataset, and the corresponding standard deviation (upper diagonal).

				Temo		Burme	Vietnam	Malay-		Ma'any		SK-				Sumb	Filipi
	FST \ S.D.	Vezo Mikea	ro	CHB	se	ese	SG	Banjar	an	Ngaju	Dayak Lebbo	Murut Dusun Bajo	anese	no	Igorot
	Vezo	0 0.005 0.006 0.004	0.004	0.003	0.004	0.003	0.004 0.003	0.003	0.004	0.004 0.004 0.003 0.003 0.003	0.003
	Mikea	0.01	0 0.006 0.005	0.004	0.005	0.004	0.005	0.004 0.004	0.004	0.005	0.005 0.005 0.004 0.004 0.005	0.005
	Temoro	0.007 0.016	0 0.004	0.004	0.004	0.004	0.004	0.004 0.004	0.004	0.005	0.004 0.005 0.004 0.004 0.004	0.005
	CHB	0.035 0.041 0.031	0	0.001	0.001	0.001	0.001	0.001 0.001	0.001	0.002	0.002 0.002 0.001 0.001 0.001	0.002
	Burmese	0.032 0.034 0.024 0.009	0	0.001	0.001	0.001	0.001 0.001	0.001	0.002	0.001 0.001 0.001 0.001 0.001	0.002
	Vietnamese	0.026 0.032 0.021 0.007	0.009	0	0.001	0.001	0.001 0.001	0.001	0.002	0.001 0.002 0.001 0.001 0.001	0.002
	Malay-SG	0.019 0.028 0.015 0.015	0.009	0.007	0	0.001	0.001 0.001	0.001	0.002	0.002 0.002 0.001 0.001 0.001	0.002
	Banjar	0.021 0.029 0.016	0.02	0.015	0.009	0.004	0	0.001 0.001	0.001	0.002	0.002 0.001 0.001 0.002 0.001	0.002
	Ma'anyan	0.026 0.036 0.021 0.028	0.024	0.017	0.009	0.008	0 0.001	0.001	0.002	0.001 0.001 0.001 0.001 0.001	0.002
	Ngaju	0.021 0.028 0.016 0.021	0.015	0.011	0.003	0.004	0.008	0	0.001	0.002	0.001 0.002 0.001 0.001 0.001	0.002
	SK-Dayak	0.018 0.025 0.015 0.019	0.014	0.01	0.002	0.002	0.005 0.001	0	0.002	0.001 0.001 0.001 0.001 0.001	0.002
	Lebbo	0.043 0.046 0.036 0.042	0.036	0.034	0.024	0.027	0.034 0.027	0.025	0	0.002 0.002 0.002 0.002 0.002	0.003
	Murut	0.033 0.041 0.027 0.028	0.028	0.021	0.016	0.018	0.024 0.016	0.015	0.035	0 0.002 0.001 0.002 0.001	0.002
	Dusun	0.033 0.041 0.026 0.028	0.026	0.02	0.017	0.016	0.022 0.019	0.015	0.036	0.023	0 0.001 0.002 0.001	0.002
	Bajo	0.028 0.032 0.018	0.02	0.016	0.014	0.008	0.011	0.019 0.011	0.009	0.028	0.02 0.019	0 0.001 0.001	0.002
	Sumbanese	0.031 0.037 0.019 0.025	0.02	0.019	0.011	0.015	0.021 0.014	0.012	0.032	0.025 0.024 0.008	0 0.001	0.002
	Filipino	0.023 0.028 0.017 0.013	0.015	0.008	0.006	0.008	0.013 0.009	0.006	0.028	0.013 0.012 0.007 0.012	0	0.002
	Igorot	0.051 0.056 0.043 0.047	0.05	0.039	0.037	0.038	0.042 0.038	0.037	0.057	0.04 0.041 0.038 0.044 0.026	0

) were excluded; iii) samples with an overall call rate <0.99 and individual SNPs with missing rates >0.05 across all samples in each population were excluded; and iv) variants in high linkage disequilibrium (r 2 > 0.5; 50 SNP sliding windows) were also removed for the low density dataset.The final low density dataset contained 9,743 SNPs in 1,817 individuals from

populations, after excluding 7 Ma'anyan and 2 South Kalimantan Dayak individuals for reasons of low

Acknowledgements

I have had a wonderful three and a half years with the Evolutionary Medicine research group (AMIS Laboratory), not forgetting days full of discussions, debates (typically French, neverending) and productive scientific work at the Evolutionary Medicine research group, AMIS Laboratory. This work, entitled "In search of Asian Malagasy ancestor in Indonesia", together with the 5 scientific publications in international peer-reviewed journals, would not have been accomplished without significant contributions from the parties mentioned below. I thank Dr. Francois-Xavier Ricaut, my supervisor, for his tutoring, dedication, and encouragement. I have really enjoyed working with him professionally. I also thank him for the lunch invitations every time we published a paper. Those were the only days where I could taste proper European dishes and improve my nutritional intake quality, as a foreign student living far away from his homeland. I thank Dr. Thierry Letellier, my supervisor, for his critical thinking and in depth scientific discussions. Through him I have learnt valuable lessons on the different viewpoints of how to undertake science and research. He is a biochemist, but also excels in population genetics problems, and he has reminded me to focus and understand the core issues of my research that I will do in the future. I thank Prof. Herawati Sudoyo, director of the Eijkman Institute for Molecular Biology, Jakarta, a woman in science who has pioneered population genetics research in Indonesia. I thank her for her encouragement, trust, and the opportunity she has given me to pursue my studies in France. I thank Dr. Nicolas Brucato, a cool post-doctoral researcher in our group. I consider him as my third supervisor and he has improved my knowledge to work on technical details. I also thank him for his updates on published population genetics tools and the discussions we have shared together. I thank Prof. Murray Cox, a computational biology scientist at Massey University, New Zealand, for his support and help on the technical discussions in every article that we have published together. The red ink, comments and suggestions he made on all my manuscript drafts were priceless. I thank Prof. Alexander Adelaar and Dr. Philippe Grange, linguists from the University of Sydney, Australia, and from Universite de La Rochelle, France, for their support and critical discussions on the linguistic and anthropological aspects of the genetics study I v performed. One day, I would really like to go to the field together, to see how these great linguists work and collect data, so I could learn from them. I thank Dr. Hannes Schroeder, a researcher at the Centre of GeoGenetics, Copenhagen, Denmark, for the opportunity to practice and learn the Capture Method. It was a great pleasure to meet him and the other members of Prof. Thomas Gilbert's team. I thank Prof. Antoine Gessain and Dr. Olivier Cassar, microbiology/genetics researchers at the Pasteur Institute, Paris, for the time and opportunity they gave me to learn methods on the detection and genetic analysis of HTLV-1 and HHV-8 viruses. I hope that this collaboration between Paris and Jakarta will continue, so that this study on viruses can be replicated in Indonesia. I thank Laure Tonasso and Stephanie Schiavinato, the laboratory technicians at the AMIS Laboratory, for their laboratory tutorials and all their help on the laboratory work performed in the AMIS Laboratory, Toulouse. I thank Dr. Safarina G. Malik, Dr. Helena Suryadi, Gludhug Purnomo, Chelzie Crenna, and Isabella Apriyana for their assistance during the sampling campaigns in Indonesia. Also to other colleagues in the Genome Diversity Laboratory, Eijkman Institute for Molecular Biology, Jakarta, for their love and moral support. I thank Dr. Rebecca Coles for the great assistance during the redactional phase of my thesis writing. I thank all the members of the AMIS laboratory who have shared these past three years with me and for their support: Dr. Denis Pierron, Dr. Margit Heiske, Dr. Morgane Gibert, Dr. Patricia Balaresque, Dr. Harilanto Razafindrazaka, Dr. Xavier Mata, and my 'companion Acknowledgments We thank Stephanie Schiavinato and Julie Bosc for technical assistance, and to Alexander Adelaar for helpful discussion. We also thank the Eijkman Institute for Molecular Biology (Jakarta, Indonesia) for accommodating the sampling program; Phillipe Grangé, Charles Illouz, and Chandra Nuraini (Université de La Rochelle) for facilitating access to the Bajo population; Budi Amuranto (Dinas Kebudayaan dan Pariwisata, East Kutai Sangata, Indonesia) for facilitating access to the Lebbo' population; Bambang Sugiyanto (Balai Arkeologi Banjarmasin, Indonesia); Adhi Agus Oktaviana (National Research Center for Archaeology, Indonesia); Antonio Guerreiro (CNRS UMR-6571, Université Aix-Marseille); and especially, all our Indonesian participants. This research was supported by the French ANR grant number ANR-14-CE31-0013-01 (grant OceoAdapto to F-X.R), the French ANR-12-PDOC-0037-01 (grant GENOMIX to D.P), the Region Aquitane of France (grant MAGE to D.P), the French Ministry of Foreign and European Affairs (French Archaeological Mission in Borneo (MAFBO) to F-X.R), the European Research Council (ERC 295918 MesAndLin(g)k to N.B.), and the French Embassy in Indonesia through its Cultural and Cooperation Services (Institut Français en Indonésie). 3.1.1.8. References Adelaar, K.A., 2009. Loanwords in Malagasy, in: Haspelmath, M., Tadmor, U. (Eds.), Loanwords in the World's Languages: A Comparative Handbook. De Gruyter Mouton, Berlin, Germany, pp. 717-746. Adelaar, K.A., 2006. The Indonesian migrations to Madagascar: making sense of the multidisciplinary evidence, in: Austronesian Diaspora and the Ethnogenesis of People in Indonesian Archipelago: Proceedings of the International Symposium. Presented at the Austronesian diaspora and the ethnogenesis of people in Indonesian archipelago, LIPI Press, Jakarta, Indonesia, pp. 205-232. Adelaar, K.A., 2005. The Austronesian languages of Asia and Madagascar: a historical perspective, in: The Austronesian Languages of Asia and Madagascar. Routledge, New York, USA, pp. 1-42. Adelaar, K.A., 1995a. Borneo as a cross-roads for comparative Austronesian linguistics, in: The Austronesians: Historical and Comparative Perspectives. ANU E Press, Canberra, Australia, pp. 81-102. Acknowledgements 72 This research was supported by the French ANR grant number ANR-14-CE31-0013-01 (grant Acknowledgements We wish to acknowledge support from the GenoToul bioinformatics facility of the Genopole Toulouse Midi Pyrénées, France. This research was supported by the French ANR via grant ANR-14-CE31-0013-01 (OCEOADAPTO to F.-X.R.), grant ANR-12-PDOC-0037-01 (GENOMIX to D.P.), as well as the Region Aquitaine of France (MAGE to D.P.), the French Ministry of Foreign and European Affairs (French Archaeological Mission in Borneo (MAFBO) to F.-X.R.), a Rutherford Fellowship from the Royal Society of New Zealand (RDF-10-MAU-001 to M.P.C.) and the French Embassy in Indonesia through its Cultural and Cooperation Services (Institut Français en Indonésie).

Acknowledgements

The authors thank Gludhug A. Purnomo, Isabella Apriyana, and Chelzie C. Darusalam from Eijkman Institute for Molecular Biology, Jakarta, Indonesia, for biological sampling, and Laure Tonasso and Stéphanie Schiavinato (University of Toulouse) for laboratory assistance.

We acknowledge support from the GenoToul bioinformatics facility of the Genopole Toulouse Midi Pyrénées, France. This research was supported by the French ANR via grant ANR-14-CE31-0013-01 (OCEOADAPTO) to F.-X.R., the French Ministry of Foreign and European Affairs (French Archaeological Mission in Borneo; MAFBO) to F.-X.R., a Rutherford Fellowship from the Royal Society of New Zealand (RDF-10-MAU-001) to M.P.C., the French Embassy in Indonesia through its Cultural and Cooperation Services (Institut Français en Indonésie) to F.-X. R. and the Ministry of Education and Culture of Indonesia to P.K. 3.2.2.7. References Beaujard, P., 2012a. Les mondes de l'océan Indien. Vol. 1 : De la formation de l'État au premier système-monde afro-eurasien (4e millénaire av. J.-C.-6e siècle apr. J.-C.). Armand Collin, Paris, France. Beaujard, P., 2012b. Les mondes de l'ocean indien. Vol. 2 : L'océan Indien, au coeur des globalisations de l'Ancien Monde (7e-15e siècles). Armand Collin, Paris, France. Behar, D.M., Yunusbayev, B., Metspalu, M., Metspalu, E., Rosset, S., Parik, J., Rootsi, S., Chaubey, G., Kutuev, I., Yudkovsky, G., Khusnutdinova, E.K., Balanovsky, O., Semino, O., Pereira, L., Comas, D., Gurwitz, D., Bonne-Tamir, B., Parfitt, T., Hammer, M.F., Skorecki, K., Villems, R., 2010. The genome-wide structure of the Jewish people. Nature 466, 238-242. doi:10.1038/nature09103 Acknowledgements We thank the Eijkman Institute for Molecular Biology (Jakarta, Indonesia), especially Alida Harahap and Deni Feriandika, and the Department of Health, Banjarmasin city in the province of South Kalimantan, for accommodating the sampling program. We wish to acknowledge support from the GenoToul bioinformatics facility of the Genopole Toulouse Midi Pyrénées, France. We thank Harilanto Razafindrazaka for her useful comments on the manuscript. This research was supported by French ANR grant number ANR-14-CE31-0013-01 (grant OceoAdapto to F-X.R), the French Ministry of Foreign and European Affairs (French Archaeological Mission in Borneo (MAFBO) to F-X.R), and the French Embassy in Indonesia through its Cultural and Cooperation Services (Institut Français en Indonésie). Genetic data has been deposited at the European Genome-phenome Archive (EGA, https://ega-archive.org), jointly managed by the EBI and CRG, under accession number African_Bantu Igorot -0,00075 0,00016 -4,79533 Mikea S-African_Bantu Malay-SG -0,00946 0,00009 -99,94540 Bajo Yoruba Igorot -0,00073 0,00015 -4,70864 Mikea Ngaju Yoruba -0,00985 0,00010 -99,50600 Bajo Eth-Somalian Igorot -0,00064 0,00015 -4,20585 Mikea Yoruba Maanyan -0,01003 0,00010 -99,44410 Bajo Somalian Igorot -0,00063 0,00015 -4,19374 Mikea Yoruba Murut -0,01017 0,00010 -99,15970 Bajo Gyan Igorot -0,00042 0,00014 -2,91720 Mikea S-African_Bantu Dusun -0,01009 0,00010 -99,13510 Bajo CEU Igorot -0,00038 0,00016 -2,34123 Mikea Vietnamese S-African_Bantu -0,00973 0,00010 -98,79300 Banjar Gyan Igorot -0,00117 0,00009 -12,53420 Mikea S-African_Bantu Luzon -0,00971 0,00010 -98,31260 Banjar Gyan Maanyan -0,00086 0,00007 -11,70650 Mikea S-African_Bantu Banjar -0,00979 0,00010 -98,24890 Banjar Somalian Igorot -0,00112 0,00010 -11,08290 Mikea Malay-SG Yoruba -0,00939 0,00010 -97,83200 Banjar Eth-Somalian Igorot -0,00113 0,00010 -10,98400 Mikea Dusun Yoruba -0,01003 0,00010 -97,10260 Banjar CEU Maanyan -0,00089 0,00008 -10,75080 Ngaju Gyan Maanyan -0,00033 0,00006 -5,42691 Banjar CEU Igorot -0,00113 0,00010 -10,74080 Ngaju CEU Maanyan -0,00030 0,00007 -4,34292 Banjar Luhya Igorot -0,00110 0,00011 -10,40430 Ngaju Gyan Igorot -0,00037 0,00009 -4,23838 Banjar S-African_Bantu Igorot -0,00110 0,00011 -10,30480 Ngaju Eth-Somalian Maanyan -0,00021 0,00006 -3,27339 Banjar Yoruba Igorot -0,00110 0,00011 -10,24280 Ngaju Eth-Somalian Igorot -0,00030 0,00010 -3,01367 Banjar Eth-Somalian Maanyan -0,00077 0,00008 -9,87042 Ngaju Maanyan Somalian -0,00019 0,00006 -2,98514 Banjar Maanyan Somalian -0,00076 0,00008 -9,71601 Ngaju Luhya Igorot -0,00030 0,00010 -2,95500 Banjar Gyan Murut -0,00074 0,00008 -9,13794 Ngaju Somalian Igorot -0,00028 0,00010 -2,92635 Banjar S-African_Bantu Maanyan -0,00073 0,00008 -8,92003 Ngaju Yoruba Igorot -0,00029 0,00010 -2,85123 Banjar Maanyan Luhya -0,00069 0,00008 -8,65876 Ngaju S-African_Bantu Igorot -0,00028 0,00010 -2,68118 Banjar CEU Murut -0,00081 0,00009 -8,63599 Ngaju CEU Igorot -0,00026 0,00010 -2,60884 Burmese Gyan CHB -0,00325 0,00006 -56,17750 Ngaju S-African_Bantu Maanyan -0,00017 0,00007 -2,50506 Burmese Vietnamese Gyan -0,00306 0,00006 -51,65090 Ngaju Maanyan Luhya -0,00017 0,00007 -2,43966 Burmese CEU CHB -0,00316 0,00007 -43,60350 Ngaju Yoruba Maanyan -0,00016 0,00007 -2,32433 Burmese Vietnamese CEU -0,00311 0,00007 -42,84930 Ngaju Gyan Murut -0,00011 0,00007 -1,43415 Burmese CHB Somalian -0,00280 0,00007 -41,56630 SK-Dayak Maanyan Burmese -0,00031 0,00004 -7,90256 Burmese Eth-Somalian CHB -0,00283 0,00007 -40,63090 SK-Dayak Gyan Maanyan -0,00044 0,00006 -7,43457 Burmese Vietnamese Somalian -0,00260 0,00007 -37,29110 SK-Dayak Maanyan Sumbanese -0,00030 0,00004 -7,41106 Burmese Gyan Murut -0,00267 0,00007 -36,73700 SK-Dayak Vietnamese Maanyan -0,00027 0,00004 -7,27878

Authors' contributions P.K, M.P.C, and F-X.R designed the research, analyzed the data, and wrote the manuscript; P.K, H.L.S, H.S, and F-X.R collected the samples, P.K and L.T carried out the molecular labwork, D.P, H.R, N.B, and T.L helped draft the manuscript. All authors gave final approval for publication. Dayak) and in the Malagasy (2-15%), which instead exhibit a balanced range of other Asian components. The PCA and ADMIXTURE analyses confirm potential connections between Malagasy and western and central Indonesian populations (particularly Java, Borneo and Sulawesi), but do not pinpoint a primary source. These results are also consistent with the general nature of Island Southeast Asian gene flow into Malagasy, as determined by TreeMix (Annex E: Figure S10). Since the African ancestry in Malagasy may hinder the precise identification of Asian parental sources, we performed a PCAdmix analysis on the full high density dataset to mask African variants in the Malagasy data. An Asian ancestry-specific PCA, run on the filtered set of 17,043 SNPs, explained 46.8% of the observed variance in the dataset (Figure 5). The first principal component separated eastern Indonesians from western Indonesians and mainland East Asians. The second principal component separated the mainland Asian groups from those in Island Southeast Asia. As observed previously (Annex E: Figure S1), the Ma'anyan are positioned away from the other Island Southeast Asian groups and form their own pole on the graph. In this more refined analysis, the Asian markers found in the three Malagasy populations overlap closely with those from coastal Borneo (South Kalimantan Dayak, Murut and Dusun), although they do not obviously show any specific affinity with the Ma'anyan.

Additionally, some Malagasy individuals are closely clustered with Bajo individuals, which may indicate that sea-nomads are relevant factors in the migrations to Madagascar, as suggested earlier (Kusuma et al., 2015). Despite this general link between Malagasy Asian

Author contributions

With the parental populations given by GLOBETROTTER, dates of admixture were also estimated using MALDER v1.3 (Loh et al., 2013;[START_REF] Pickrell | Ancient west Eurasian ancestry in southern and eastern Africa[END_REF].

Results

We studied genetic variation in three Bajo communities spread across large parts of their geographical range: the Derawan of coastal Northeastern Borneo (n = 18, B-DRW), the Kotabaru of coastal Southeastern Borneo (n = 23, B-KTBR), and the Kendari of coastal Sulawesi (n = 32, B-KDR). To determine the population structure of these three Bajo communities, a principal component analysis (PCA) was performed using 645,385 overlapping SNPs in just the Bajo (Figure 2). Individuals from the three groups form distinguishable clusters. PC1 (16.2% variance explained) separates the Kotabaru Bajo from the two other groups, while PC2 (12.9% variance explained) differentiates the Kendari Bajo from the Derawan Bajo. Interestingly, there is no overlap between the groups presently living in Borneo.

The regional connections of the Bajo were determined from 230,833 overlapping SNPs in 116 surrounding populations. A clear division appears between East Asia/Mainland Southeast Asia and Island Southeast Asia, notably separating Papuan/Eastern Indonesian populations (PC1) from Western Indonesian populations (PC 2). All Bajo individuals fall within the Island Southeast Asia cluster, specifically with other Indonesian groups (Annex F: Figure S1). As before, all three Bajo communities still form their own clusters with limited overlap. Most Bajo individuals lie close to populations from Sulawesi, such as the Bugis and Mandar. The Derawan Bajo cluster close to Philippine populations; the Kotabaru Bajo cluster close to Borneo populations; while the Kendari Bajo have connections with eastern Indonesia, such as Sumba and North Maluku, and with Papuans.

The PCA results are consistent with fineSTRUCTURE clustering on phased genotype data (Annex F: Figure S2), which shows that all three Bajo communities form a single group, but trend towards their close geographic neighbors. Conversely, pairwise FST values (P < 1 x 10 -4 for all FST pairs) suggest that all three Bajo communities have closer genetic ties to their surrounding populations than between themselves (Annex F: Table S2), thus hinting that genetic connections within the Bajo are correspondingly weaker. For instance, the Kendari Bajo have closest genetic distances with Sulawesi Bugis and Mandar; the Kotabaru Bajo with Borneo Banjar and Malay; and the Derawan Bajo with Philippine populations and Borneo Lebbo. Geography, and interactions with local groups, are therefore dominant features in the development of Bajo genetic diversity.

However, all Bajo individuals do share common patterns of genetic ancestry, as revealed by ADMIXTURE analysis (Figure 3, Annex F: Figure S3, Figure S4). The three Bajo communities have an admixed profile with two major Asian components and a Papuan component, but in varying proportions. The Kendari Bajo have more of the Papuan component (red) than the two Borneo Bajo groups (~20%), in keeping with their location further east. The Asian genetic ancestry is formed by similar components as for other Indonesian groups, with three main contributions: one East Asian (orange), two Austronesian components (pink and yellow), and an indigenous peninsular Malaysia component (cyan), cumulatively summing to 80-90%. The three Bajo communities only differ by relatively minor proportions of genomic ancestry that can be linked to their specific locations: minor Negrito Philippine (Aeta and Batak) components, with white and grey colors respectively, are observed in the Derawan Bajo (~1-2%); and an Indian component (green) is detected in both the Derawan Bajo and Kotabaru Bajo (~6%). Interestingly, this Indian component was not clearly detected in the Kendari Bajo, contra Mörseburg et al. (2016), probably because of its very low proportion. We detect sex biased admixture in Kotabaru Bajo and Derawan Bajo (one-tailed Wilcoxon test; P < 0.01), but not in Kendari Bajo nor in the Bugis (one-tailed Wilcoxon test; P > 0.05). A higher proportion of Papuan X chromosomes relative to the autosomal contribution is also observed (Annex F: Figure S5). The f3 statistics suggest that the Derawan and Kendari Bajo are admixed (Annex F: Table S3). However, defining the Kotabaru Bajo as a daughter population, all possible surrogate population combinations return positive f3 statistics with Z-scores > -2, indicating no significant gene flow, or recent bottlenecks, or founder effects (Patterson et al., 2012), as also suggested by the Admixture plot at K = 20 (Annex F: Figure S3). This is consistent with the Runs of Homozygosity (ROH) and Inbreeding Coefficient (FIS) analyses, which show higher values compared to the other two Bajo groups (Annex F: Figure S6, Figure S7). Identity-by-Descent (IBD) was used to measure haplotype sharing across the genome. All Bajo communities share longer fragments with each other than with other regional populations (Annex F: Figure S8), suggesting that the Bajo communities did intermarry until their recent land-based resettlement. The highest IBD sharing was observed between the Kendari and Kotabaru Bajo, then between the Kotabaru and Derawan Bajo, with much less

Conflict of interest

The authors declare no conflict of interest.

Affinities to the Malagasy Asian components are found at high frequency across several Island Southeast Asian groups, but notably in Malay, a dominant group of ancient seafaring traders (first millennium CE), and admixed groups from Borneo (i.e. Banjar, Ngaju, South Kalimantan Dayak, Lebbo, Murut, Dusun and Bidayuh; Annex G: Figure S2). The connection between Malagasy, and the Borneo and Malay populations, is supported by f3-statistics (Zscores < -2; Annex G: Table S2) (Patterson et al., 2012) and TreeMix analyses (35% of Malay/Borneo gene flow to Malagasy; Annex G: Figure S4) (Pickrell and Pritchard, 2012).

However, to more specifically identify the Asian ancestry of the Malagasy genome, we performed a Local Ancestry analysis with PCAdmix (Brisbin et al., 2012) using two proxy parental meta-populations comprising 100 individuals with African ancestry (randomly selected from Yoruba, South African Bantu, Kenyan Luhya and Somali groups) and Asian ancestry (randomly selected from Chinese, Philippine Igorot, Bornean Ma'anyan and Malay groups). Masking the haplotypes inferred to derive from Africa, we performed an Ancestry-Specific PCA (Patterson et al., 2006) and TreeMix analysis (Pickrell and Pritchard, 2012).

Both show that the Asian genomic components of Malagasy cluster tightly with Southeast Borneo groups (Banjar, South Kalimantan Dayak, Ngaju and Ma'anyan) (1,664 SNPs; Figure 1A and Annex G: Figure S5). This connection is supported by the highest f3-statistics and the lowest FST genetic distances also being observed between Asian ancestry of the Malagasy and these same Southeast Borneo groups (f3 > 0.12; FST < 0.02; Figure 1B; Annex G: Table S3 and Table S4).

To explore this connection in more detail, we turned to the high density SNP dataset (551 individuals from 24 populations genotyped for 374,189 SNPs; Supplementary table S1, Supplementary Material online). This allows more statistically powerful analyses based on haplotypes. We confirmed the earlier result that Malagasy have the highest values of cumulative shared Identity-By-Descent fragments (IBD) with Southeast Borneo populations (Figure 1C; Supplementary figure S6, Supplementary Material online). To expand on this, however, we inferred the population sources of the Malagasy, their relative ratios and the dates of potential admixture events with GLOBETROTTER (Hellenthal et al., 2014), defining each population in our dataset as a donor/surrogate group and the Malagasy as the recipient, using the haplotype 'painting' data obtained with Chromopainter (Lawson et al., 2012). The best fit outcome for the Malagasy was obtained under a model of a single admixture event between two sources: the Banjar representing 37% of modern Malagasy and the South African Bantu population representing the other 63% (r 2 =0.99, P<0.01; Figure 2 Annex C. Supplementary informations from article entitled "Mitochondrial DNA and the Y chromosome suggest the settlement of Madagascar by Indonesian sea nomad populations" (Published in BMC Genomics, 16:191, March 17 th 2015. doi: 10.1186/s12864-015-1394-7) Pradiptajati Kusuma 1,4 Razafindrazaka 1 , Alexander Adelaar 4 , Herawati Sudoyo 2,5 , Thierry Letellier 1 , andFrançois Table S5. MALDER analysis for each Bajo community using the parental populations inferred from GLOBETROTTER. For each estimated admixture date (t0 and t1), the amplitude of the weighted LD curve (Amp) and the time in generation (Gen) are given with their respective standard errors and Z-scores. Table S5. GLOBETROTTER inferred dates (in both generations from present and years, bootstrap 95% CIs given in parenthesis; YBP = years before present), admixing sources, and percentage (%) of admixture for each population of interest. We assume a generation time of 25 years. R2 corresponds to the goodness-of-fit of the tested model. FQ1 and FQ2 correspond respectively to the fit of a single admixture event and the fit of the first two principal components capturing the admixture events. M corresponds to the additional R2 explained by adding a second date versus assuming only a single date of admixture (M>0.35 to infer multiple dates event). The admixture models presented in the table correspond to the best fit models considering the 'best guess'. P: p-value of evidence of any detectable admixture event obtained after 100 bootstrap resamplings of the NULL procedure. Date confidence intervals are based on 100 bootstrap replicates of the date inference.

Supplementary Methods

Sample collection and ethics

A total of 41 DNA samples were analyzed from two groups in Southeast Borneo: the Banjar (n=16) and the Ngaju (n=25) that were collected in Banjarmasin city (Annex E: Figure S1).

Blood samples were collected from healthy adult donors, all of whom provided written informed consent. DNA was extracted using a standard salting-out procedure. All participants were surveyed for language affiliation, current residence, familial birthplaces, and a genealogy of four generations to establish ancestry. This study was approved by the Research Ethics Commission of the Eijkman Institute for Molecular Biology (Jakarta, Indonesia).

Genome-wide SNP genotyping for individuals from the two groups were performed using the Illumina Human Omni Express Bead Chip-24 v1.0 (Illumina Inc., San Diego, CA), which characterizes 730,525 single nucleotide markers regularly spaced across the genome. The accession number for the Southeast Borneo samples genotyped for this study is EGA:

EGAS00001001841.

Dataset

We gathered data from previously published studies on populations from Madagascar, Southeast Asia, South Asia, East Asia, East Africa, South Africa, and Europe (Annex E: Table S1). Two datasets were compiled respective to their analytical use: a low SNP density dataset of populations covering a large geographical area; and a high SNP density dataset of populations composed by a subset of populations of the latter dataset. To avoid any statistical bias that could be induced by a size effect due to populations over-represented in the high SNP density dataset, we randomly selected a maximum of 31 individuals in each group, such as each population has a number of individuals between 15 and 31. Quality controls were applied using Plink v1.9 (Chang et al., 2015) to filter for i) close relatives, using an Identityby-Descent (IBD) estimation with upper threshold of 0.25 (second degree relatives); ii) SNPs that failed the Hardy-Weinberg exact (HWE) test (P < 10 -6 ) were excluded; iii) samples with a call rate <0.99 and displayed missing rates >0.05 across all samples in each population were excluded; and iv) variants in high linkage disequilibrium (r 2 > 0.5) were also removed for the low density dataset. After filtering, the low SNP density dataset included 2,183 individuals from 61 populations genotyped for 40,272; and the SNPs high SNP density dataset was composed of 551 individuals from 24 populations genotyped for 374,189 SNPs. All genotypes of the high SNP density dataset were then phased together with SHAPEIT v2.r790 (Delaneau et al., 2012) using the 1000 Genomes phased data (Delaneau et al., 2014) as reference panel and the HapMap phase 2 genetic map [START_REF] Hapmap | Integrating common and rare genetic variation in diverse human populations[END_REF].

Statistical Analyses

The low density dataset was described by the following analyses. Principal Components Analysis was computed with EIGENSOFT v6.0.1 (Patterson et al., 2006). ADMIXTURE v1.23 (Alexander et al., 2009) was used to estimate the profile of individual genomic ancestries using maximum likelihood for components K = 2 to K = 18. Ten replicates were run at each value of K with different random seeds, then merged and assessed for clustering quality using CLUMPP (Jakobsson & Rosenberg, 2007), and the cross-validation value was calculated to determine the optimal number of genomic components (here, K = 16).

ADMIXTURE and PCA plots were generated with Genesis [START_REF] Buchmann | Genesis Manual[END_REF].

Three-population (f3) statistics (Patterson et al., 2012) were computed for each trios of populations of the low SNP density dataset to identify groups showing potential recent admixture event. TreeMix v1.12 analysis (Pickrell & Pritchard, 2012) was performed with all Asian populations and three representative of African groups (Yoruba, Luhya, South African Bantu), to estimate gene flows from Asian groups and their relative intensity, with blocks of 200 SNPs to account for linkage disequilibrium and migration edges added sequentially until the model explained 99% of the variance (the TreeMix outputs in Newick format were visualized with MEGA v7.0 (Tamura et al., 2013)).

Population structure of the phased high density dataset was evaluated using the fineSTRUCTURE v2.07 package (Lawson et al., 2012). It uses the detection of shared IBD fragments between each pair of individuals, without self-copying, calculated with Chromopainter v2.0 (Lawson et al., 2012) to perform a model-based Bayesian clustering of genotypes. From the results, a coancestry heat map and a dendrogram were inferred to visualize the number of clusters statistically defined that would describe relevantly the data.

FineSTRUCTURE v2 identified 37 groups of individuals that can be statistically defined as natural populations (Lawson et al., 2012), according to their shared Identity-By-Descent (IBD) (bootstrapped nodes > 60%; Annex E: Figure S7). Most of these correspond to anthropologically defined populations, such as the Banjar or the Ngaju, with few exceptions (e.g., the sub-structuration of the Kenyan Luhya group). Although each Malagasy individual has its closest connections with other Malagasy, regardless of their ethnicity, these ethnic groups were treated separately for anthropological interest. Haplotype sharing between pairs of individuals was estimated from the phased high SNP density dataset by the Refined IBD algorithm of Beagle v4.0 (Browning & Browning, 2007;[START_REF] Browning | Improving the accuracy and efficiency of identity-by-descent detection in population data[END_REF], filtering for detected fragments with a logarithm of odds ratio (LOD)>3. Ten iterations were performed, randomizing the seed number for each run, and the overlapping shared fragments were merged to favour the detection of long shared IBD. Detected fragments between the same pairs of individuals were summed up and visualized with Cytoscape v3.2.1 (Shannon et al., 2003). IBD sharing data with Malagasy individuals was also averaged per Asian population to geographically plot a gradient map with Surfer v12.0 using the Kriging method. Viterbi algorithm was then used to mask all haplotypes according to one or the other ancestry in the Malagasy individuals. Ancestry-specific PCAs and FST calculations were realized with EIGENSOFT v6.0.1 (Patterson et al., 2006). Three-population (f3) statistics (Patterson et al., 2012) and TreeMix v1.12 analysis (Pickrell & Pritchard, 2012) were also performed on this masked dataset (1,664 SNPs for 18 populations). Haplotype 'painting' with Chromopainter v2 (Lawson et al., 2012) was realized on the high density of SNP dataset, defining each cluster of populations as target or donor/surrogate according to the anthropological question addressed.

Mutational rates and Ne parameters were first estimated with an Estimation-Maximization (EM) algorithm running Chromopainter v2 on all 22 autosomes for the entire dataset with 10 iterations (Lawson et al., 2012). The weighted average of these parameters, according to the SNP coverage of each used chromosomes and the number of individuals, were then used to compute the chromosomal painting. Each cluster of populations has been successively identified as target and the others as surrogates (at the exclusion of the Malagasy cluster which has not been used as surrogate). The obtained painted chromosomes for each cluster were used in GLOBETROTTER v1.0 (Hellenthal et al., 2014)