Stéphanie ; Manel
email: stephanie.manel@cefe.cnrs.fr

Charles Perrier

Marine Pratlong

Laurent Abi-Rached

Julien Paganini

Pierre Pontarotti

D Aurelle

Didier Aurelle

Pratlong M † ‡ Abi-Rached

Genomic resources and their influence on the detection of the signal of positive selection in genome scans

Keywords: Adaptation, Ecological Genetics, Genomics/Proteomics, Landscape Genetics Conservation biology, Local adaptation, Natural population, Population genomics, Landscape genetics, Landscape genomics

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Representation Sequencing are increasingly used in genome scans. Besides, genomes are also becoming more available, allowing better processing of short-read data, offering physical localisation of variants, and improving haplotype reconstruction and data imputation.

Ultimately, genomes are also becoming the raw material for selection inferences. Here, we discuss how the increasing availability of such genomic resources, notably genomes, influences the detection of signals of selection. Mainly, increasing data density and having the information of physical linkage data expand genome scans by i) improving the overall quality of the data; ii) helping the reconstruction of demographic history for the population studied to decrease false positive rates; iii) improving the statistical power of methods to detect the signal of selection. Of particular importance, the availability of a high quality reference genome can improve the detection of the signal of selection by i) allowing matching the potential candidate loci to linked coding regions under selection, ii) rapidly moving the investigation to the gene and function, and iii) ensuring that the highly variable regions in coding regions of the genomes are also investigated. For all those reasons, using reference genomes in analyses of genome scans is highly recommended. how these environmental factors lead to genetic adaptation is a longstanding question in evolutionary biology [START_REF] Kawecki | Conceptual issues in local adaptation[END_REF]. With the rapidly increasing availability of large genomic resources, this topical question can now be addressed by genome scans, i.e. the survey of genetic variability across whole genomes or across a large number of loci in a large number of individuals living in distinct environments [START_REF] Pritchard | How we are evolving[END_REF]. The main objective of genome scans is to identify signals of selection at the genome level in natural populations and thus uncover how natural selection affects genetic variation in response to environmental heterogeneity and changes [START_REF] Mitchell-Olds | Which evolutionary processes influence natural genetic variation for phenotypic traits?[END_REF][START_REF] Nosil | Divergent selection and heterogeneous genomic divergence[END_REF][START_REF] Schluter | Genetics and ecological speciation[END_REF].

The identification of these signatures of natural selection in genome scans has become an area of intense research, stimulated by the increasing ease with which a high number of genetic markers can be discovered and characterized in non-model species thanks to Next Generation Sequencing (NGS) [START_REF] Davey | Genome-wide genetic marker discovery and genotyping using next-generation sequencing[END_REF]. Loci identified as targets of natural selection are likely adaptively and / or functionally important [START_REF] Vitti | Detecting Natural Selection in Genomic Data[END_REF], and hence candidates for involvement in local adaptation 1 , disease susceptibility, resistance to pathogens, and other traits of interest to plant and animal breeders. Here, we illustrate our discussion mainly in the field of conservation and evolutionary biology [START_REF] Allendorf | Genomics and the future of conservation genetics[END_REF][START_REF] Segelbacher | Applications of landscape genetics in conservation biology: concepts and challenges[END_REF]. We focus on studies based on the analysis of the spatial sampling of geo-referenced individuals or populations in sites characterized by different environmental conditions. In some cases, the measure of the geo-referenced environmental variable is also available. Those studies aims to better understand local adaptation.

One application of genomes scans in conservation biology is the improvement of the definition of management units through integrating adaptive genetic variability (Funk et al. 2012). This is particularly important in the case of cryptic genetic lineages which are identified only when using a sufficient number of markers (e.g. [START_REF] Bourret | Landscape genomcis in Atlantique salmon (Salmo salar) : searching for gene-environment interactions driving local adaptation[END_REF][START_REF] Bradbury | Genomic islands of divergence and their consequences for the resolution of spatial structure in an exploited marine fish[END_REF][START_REF] Hemmer-Hansen | Conserving marine biodiversity: insights from life-history trait candidate genes in Atlantic cod (Gadus morhua)[END_REF][START_REF] Russello | Detection of outlier loci and their utility for fisheries management[END_REF]. For instance, positive selection but also on restrictions to gene flow, which can be used as a tool to identify management units (Gagnaire et al. 2015). Another important application of genome scans in conservation biology is the study of species ability to adapt in response to climate change [START_REF] Pauls | The impact of global climate change on genetic diversity within populations and species[END_REF]. The identification of current adaptive polymorphisms can help to identify and maintain adaptive genetic potential. For example Dixon et al. (2015) have identified genomic regions potentially involved in the response to selection for thermal tolerance in the coral Acropora millepora. This gives some clues on the possibility of adaptive evolution in future environments, which is essential for conservation [START_REF] Allendorf | Genomics and the future of conservation genetics[END_REF]. Then, detecting climatic variables and polymorphisms potentially involved in local adaptation can improve models of future species dynamics under climate change [START_REF] Manel | Broad-scale adaptive genetic variation in alpine plants is driven by temperature and precipitation[END_REF].

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Gaining information on the genetic basis of adaptation to different environments could also be used to improve assisted evolution of natural populations [START_REF] Van Oppen | Building coral reef resilience through assisted evolution[END_REF].

Here, we focus on genomic data and discuss only the use of NGS-derived markers. Single Nucleotide Polymorphism (SNP) data are the marker of choice to conduct genome scans.

The physical position of these SNPs on the genome can be known or not, with different degree of precision. SNPs of unknown genomic position are now widely used in non-model species since the recent development of various protocols of Reduced Representation Sequencing promoted by the decreasing cost of high throughput sequencing [START_REF] Davey | Special features of RAD Sequencing data: implications for genotyping[END_REF][START_REF] Davey | Genome-wide genetic marker discovery and genotyping using next-generation sequencing[END_REF]. Alternatively, the recent increase of availability of genomes for a wide variety of species opens the perspective to locate SNPs on the genome using reference genomes (Box 1). The main benefit of moving from thousands of anonymous unpositioned markers with no reference genome to the case of having a reference genome (or long -read sequences), independently of its quality, is to be able to locate and order markers (SNPs) along the genome [START_REF] Bragg | Genomic variation across landscapes: insights and applications[END_REF] (Figure 1). This is important since in most cases, candidate SNPs identified through genome scans are not the direct target of selection but are rather physically linked to these targets. Then, the knowledge of the physical linkage allows the identification of genomic regions, and not only SNPs, with exceptionally high population differentiation [START_REF] Tine | European sea bass genome and its variation provide insights into adaptation to euryhalinity and speciation[END_REF]. It also allows to explore the number and physical extent of such regions [START_REF] Nosil | Divergent selection and heterogeneous genomic divergence[END_REF]Roesti et al. 2012a), to derive robust demographic data [START_REF] Huber | Keeping It Local: Evidence for Positive Selection in Swedish Arabidopsis thaliana[END_REF] and to investigate subtle fine spatial structure [START_REF] Leslie | The fine-scale genetic structure of the British population[END_REF] that are necessary for the inference of selection.

In this review, we discuss the benefits of using additional genomic resources such as reference genomes on the ability of genome scans to detect selection in conservation and evolutionary

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biology (Figure 1). We will first discuss which inferences can be made without reference genomes which is still the rule for most species (Gagnaire et al. 2012), and then the perspectives that are open by the availability of a reference genome or other genomic resources (Box 1). We then discuss the main challenges remaining even when reference genome is available. First, when genome scans rely on reference genomes, only high quality assembly makes it possible to study the highly variable regions of the genomes in coding regions (Box 2). Second, genome scans only represent a screening tool to reveal potential differences among environments in the functions and histories of the candidate genes identified in these analyses. We therefore discuss more extended validations of the adaptive function of the candidate loci [START_REF] Pavey | What is needed for nextgeneration ecological and evolutionary genomics?[END_REF].

Genomic data used in genome scans

We describe here the diversity of genomic data used to conduct a genome scans in function of the availability of one or several related genomes. et al. 2013). Dedicated approaches are required to limit this biases such as a search of orthologous genes [START_REF] Li | OrthoMCL: Identification of ortholog groups for eukaryotic genomes[END_REF][START_REF] Pratlong | The red coral (Corallium rubrum) transcriptome: a new resource for population genetics and local adaptation studies[END_REF] which can be complemented by the filtering method of SNPs proposed by Gayral et al. (2013).

On the other hand, the availability of reference genomes opens different possibilities for generating more powerful individual data to be used in genome scans. First, it is possible to use reference genomes to improve RRS data. The alignment of short-reads produced by RRS methods on a reference genome can notably improve the overall quality of the SNP calling since erroneous reads would be pruned out during the alignment. Physically indexing loci also benefits to data filtering, allowing computing linkage disequilibrium (LD) among physically close loci. Loci in high LD can then be filtered out to allow the use of the dataset in software requiring unlinked loci. Instead of pruning linked loci, the LD data obtained can also be used as a complementary input to limit biases associated with the used of linked loci.

Physically locating loci also increases the strength of the datasets since it allows applying a wide variety of selection detection tools, taking advantage of both allele frequencies and loci physical positions (eg F ST sliding windows). Lastly, the distance and LD among loci can also be used during the statistical reconstruction of haplotypes [START_REF] Browning | Haplotype phasing: existing methods and new developments[END_REF][START_REF] Stephens | Accounting for decay of linkage disequilibrium in haplotype inference and missing-data imputation[END_REF]. Moreover, as discussed by [START_REF] Buerkle | The n=1 constraint in population genomics[END_REF], analyses of multi-allelic DNA sequences (as haplotypes) rather than bi-allelic markers should help to solve the "n=1 constraint" related to the use of SNP. Besides, haplotypes can be used to improve the imputation of missing data [START_REF] Browning | Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering[END_REF]. Indeed, if some alleles are inherited more frequently together (haplotypes), and that this information is known, it is crucial to impute data considering these associations rather than only the population frequencies of the alleles being imputed. However, haplotype phasing will be increasingly difficult with increasing recombination rate and decreasing SNP density, which would be an important limitation in studies implementing RRS using relatively rare cutters and single-end short sequencing since sequenced SNP may often fall too far apart.

Genome sequences are also increasingly considered as raw material for genome scans, allowing increasing the number of SNPs detected, to construct haplotypes and at larger divergence scale to perform comparative genomics. Indeed, De novo sequencing can be used to generate a high number of SNPs for multiple individuals. While sequencing parts of the genome using RRS (described above) can bring informative results on adaptive diversity, the number of loci identified through these approaches is also much lower than with genome sequencing (up to tens of thousands compared to millions of SNPs respectively; [START_REF] Rellstab | A practical guide to environmental association analysis in landscape genomics[END_REF]. De novo assembled genome by deep-sequencing (Chaisson et al. 2015a) is one of the most informative approaches for selection detection. However, such data cannot be derived yet for a high number of individuals in conservation projects because it is still too expensive.

Nevertheless, a two-step strategy can be used with first de novo assembly of a reference genome by deep-sequencing one individual and followed by the resequencing of additional The cost effectiveness of pooled genome sequencing (Pool-Seq) comes from the cost of the preparation of libraries and on the sequencing of more individuals which can increase the estimates of allele frequencies [START_REF] Schloetterer | Sequencing pools of individuals-mining genome-wide polymorphism data without big funding[END_REF]. In their analysis of the pros and cons of Pool-Seq, Schlöterrer et al. (2014), indicate their interest to study genetic differentiation, heterozygosity, or selective sweep [START_REF] Boitard | Detecting Selective Sweeps from Pooled Next-Generation Sequencing Samples[END_REF]. For instance, [START_REF] Turner | Population resequencing reveals local adaptation of Arabidopsis lyrata to serpentine soils[END_REF] have sequenced Arabidopsis lyrata from four populations (two from serpentine soils and two from granitic soils), with 25 individuals pooled per population, with a 39-fold genome coverage. On the basis of allele frequency differences and F ST , they identified candidate SNPs for the adaptation to soil types. However, Pool-Seq can be limiting for example if one is interested in linkage disequilibrium [START_REF] Schloetterer | Sequencing pools of individuals-mining genome-wide polymorphism data without big funding[END_REF]. In summary, the above data can be directly used as raw material in the statistical analysis of genomes scans: SNPs (from a small to a high number) or haplotypes.

Detecting the signal of selection without and with a reference genome

Here we discuss how additional genomic resources improve the inferences of the signal of selection in genome scan analyses. We introduce briefly the main principle of the statistical methods, but we do not enter into the details of the available methods and software since multiple reviews have already been published on the subject [START_REF] Manel | Perspectives on the use of landscape genetics to detect genetic adaptive variation in the field[END_REF][START_REF] Rellstab | A practical guide to environmental association analysis in landscape genomics[END_REF][START_REF] Schoville | Adaptive genetic variation on the Landscape: methods and cases[END_REF].

Without any reference genome, SNPs sampled in multiple populations are analyzed as independent variables with methods derived from the test of neutrality of [START_REF] Lewontin | Distribution of gene frequency as a test of theory of selective neutrality of polymorphisms[END_REF] and looking for outlier loci (i.e. loci with higher or lower levels of divergence than expected under neutrality). Loci with high values of F ST , a measure of genetic differentiation among sampled populations, correspond to loci potentially under divergent local selection while loci with low F ST values correspond to loci under balancing selection [START_REF] Beaumont | Identifying adaptive genetic divergence among populations from genome scans[END_REF].

When We describe below how the reference genome may improve the power of genome scans and help to decrease the number of false positives either through the use of reference genomes to improve previous analysis, or in a direct analysis of raw data.

Mapping SNPs (e.g. identified through RRS loci) to reference genomes can give insights into the potential genes involved in adaptation (see next section) and on the distribution of population genetic statistics along the genome since additional inferences as genetic differentiation and genetic diversity on chromosomal regions become possible with a dense, ordered set of genome-wide markers (Figure 1). In practice, a sliding window sweeps across the genome, to look for regions showing significant deviation of the statistics inferred. Sliding windows are implemented to average locally those statistics and to compare them toward a random set of windows that can be taken from a larger genomic region (eg. the considered chromosome or the whole genome). This sliding-based windows method reinforces the statistical power of the detection of selection since it can highlight regions that may potentially not be spotted using non genomic outlier SNP approaches. It also allows inferring the physical extent of the signal of selection. The size of the window on which the average is calculated and the size of the step are usually defined around 150kb and 50kb, respectively, the step-size being equal or smaller than the windows-size. These windows and step sizes are crucial parameters that can largely influence the detection power of such analyses and should be defined according to the SNP density and sampling variance [START_REF] Hohenlohe | Population Genomics of Parallel Adaptation in Threespine Stickleback using Sequenced RAD Tags[END_REF]). It should be noted that SNP densities obtained in RRS using rare cutters would probably be too small to allow applying with robustness sliding windows along the entire genome. The information of physical linkage among SNPs also opens the possibility to detect reduced genetic diversity in the neighborhood of a selected (directional selection) site along a chromosome, which can be the consequence of selective sweep [START_REF] Nielsen | Molecular signatures of natural selection[END_REF]. The extent of the area displaying reduced diversity will depend on the intensity of selection, on recombination rate, on the breeding system and on the age of the selective event. The elimination of slightly deleterious mutations (background selection) can be difficult to separate from selective sweeps [START_REF] Nielsen | Molecular signatures of natural selection[END_REF]. Specific statistical methods have been developed to detect selective sweeps at the population level [START_REF] Nielsen | Molecular signatures of natural selection[END_REF][START_REF] Sabeti | Positive natural selection in the human lineage[END_REF]. They differ in the type of the genomic signature of selection detected [START_REF] Oleksyk | Genome-wide scans for footprints of natural selection[END_REF]): local reduction in genetic variation at the proximity of the loci under selection [START_REF] Oleksyk | Identifying Selected Regions from Heterozygosity and Divergence Using a Light-Coverage Genomic Dataset from Two Human Populations[END_REF], changes in the shape of the frequency distribution of genetic variation, i.e. site frequency spectrum [START_REF] Tajima | Statisticial method for testing the neutral mutation hypothesis by DNA polymorphisms[END_REF], extended linkage disequilibrium segments [START_REF] Sabeti | Detecting recent positive selection in the human genome from haplotype structure[END_REF][START_REF] Vatsiou | Detection of selective sweeps in structured populations: a comparison of recent methods[END_REF], or elevated admixture contribution from one Lastly, the fact that adaptation may rely on polygenic traits with small changes in allele frequencies has been discussed (de Villemereuil et al. 2014). One interesting development here is to test outliers not on a single marker basis but on set of genes linked in biological pathways [START_REF] Daub | Evidence for Polygenic Adaptation to Pathogens in the Human Genome[END_REF]. This is possible only for species with good genomic knowledge, as it requires to assign SNPs to genes on the basis of their physical location and to use functional relationships between genes. Finally, to improve our understanding of the genomic architecture of adaptation (and speciation) and the nature of the genes involved in these processes, genome scans can be combined with QTL mapping, genome wide association studies (GWAS) and/or sequence and functional analysis (Gagnaire et al. 2013;[START_REF] Strasburg | What can patterns of differentiation across plant genomes tell us about adaptation and speciation?[END_REF]. In cases of divergent selection, the challenge is to document how functional polymorphisms at individual genes translate into different phenotypes, including quantitative traits values, which in turn translate into fitness differences [START_REF] Storz | Integrating evolutionary and functional approaches to infer adaptation at specific loci[END_REF]. In such investigations, the statistical tests used to detect the signatures of natural selection, as well as all the steps before the functional validation, provide the basis for functional inferences: association studies for example link polymorphism at one locus to a phenotypic difference, as was done for the shell color polymorphism in the snail Cepaea nemoralis [START_REF] Richards | RAD-Seq derived markers flank the shell colour and banding loci of the Cepaea nemoralis supergene[END_REF]). An important argument to confirm the adaptive function of a particular allele is the design of appropriate experiments to study the resulting effects on protein function or protein expression [START_REF] Storz | Integrating evolutionary and functional approaches to infer adaptation at specific loci[END_REF].

From prioritization of candidate loci to validation

This can be done through functional genetic approaches: in the Darwin finches for example, a genomic region with high differentiation levels corresponded to genes previously identified as involved in beak morphology [START_REF] Lamichhaney | Evolution of Darwin's finches and their beaks revealed by genome sequencing[END_REF]. For polygenic traits, QTL approaches or GWAS are useful. RAD sequencing was also used to identify QTL associated with ecologically important traits and to gene expression differences in the lake whitefish Finally as adaptation points to differences in fitness, an experimental validation by comparing different genotypes seems to be the most informative validation step. Experimental tests of local adaptation can be done for example with common garden or reciprocal transplant experiments with different genotypes for candidate loci [START_REF] Kawecki | Conceptual issues in local adaptation[END_REF]). This should be easier for traits that not relying on too many loci.

Conclusion

In summary, the availability of a reference genome can incontestably improve the detection of the signal of selection at all steps of the genome scans: production of genomic data, statistical detection of the signal of selection, and prioritization of candidate genes. Main improvements can be summarized as follows: i) improving the overall quality of the data; ii) helping to reconstruct an accurate demographic history for the population studied and hence decrease confounding effects [START_REF] Huber | Keeping It Local: Evidence for Positive Selection in Swedish Arabidopsis thaliana[END_REF] Haplotype : set of genetic variants or alleles physically linked on a chromosome and statistically associated. They are inherited together until disrupted by recombination.

Hitchhiking (to fixation): when a genetic variant that is physically linked to a selectively advantageous mutation goes to fixation because of the selection on that advantageous mutation.

Linkage disequilibrium (LD): the non-random association of alleles at different loci. LD can strongly increase around selected sites when selection is strong.

Local adaptation: the result of fitness differences between alleles [START_REF] Wollstein | Inferring positive selection in humans from genomic data[END_REF]. A fitness value can be assigned to each possible genotype.

Management unit: Genetically differentiated population to be managed separately because of its demographic independence

Negative selection (or purifying selection): any type of selection where new mutations are selected against [START_REF] Nielsen | Molecular signatures of natural selection[END_REF]. In this case, the derived allele is detrimental to the organisms.

Physical linkage describes the tendency of alleles near each other on a chromosome to be inherited together

Positive selection as introduced by Darwin and Wallace (1858) ), "is the principle that beneficial traits -those that make it more likely that their carriers will survive and reproducetend to become more frequent in populations over time" [START_REF] Sabeti | Positive natural selection in the human lineage[END_REF]. Then, it is any type of selection where coefficient of selection has a positive value. It occurs when the derived allele has a higher fitness than the ancestral allele. It comprises both directional selection and balancing selection as overdominance. Positive selection is the mechanism that can lead to local adaptation [START_REF] Nosil | Divergent selection and heterogeneous genomic divergence[END_REF][START_REF] Pritchard | How we are evolving[END_REF].

Reduced Representation Sequencing (RRS): a technique based on the use of restriction

enzyme digestion to reduce the complexity of the genome.

Selective sweeps: reduction or elimination of genetic variation in a genomic region as the result of natural selection having favored one particular variant in this region.

Boxes Box 1-A reference genome

A reference genome is an assembly of a genome that is representative of a species and can be used to align sequence reads for population-genomic studies. In genome scan analyses, a reference genome can either be the genome of the targeted species or that of a closely related species. Similarly, this reference can be based on a single individual or on a collection of individuals; in the former situation however, the reference genomes do not capture the full extent of nucleotide or structural variation segregating within a species. With the dramatic decrease in the cost of DNA sequencing of the past few years, an ever increasing number of genome are characterized, yet the quality of these genomes can be highly dependent upon the quality of the assembly [START_REF] Simpson | Exploring genome characteristics and sequence quality without a reference[END_REF]. As further developed below, reference genomes can thus be of two types: they can be represented by a single sequence ('golden path' reference genomes) or they can be representative of the genetic diversity of the species ('high quality' reference genomes). For these 'high quality' reference genomes, genetic variation does not just refer to single nucleotide polymorphisms (SNPs) but also to structural variation that represents a large source of genomic diversity [START_REF] Church | Modernizing Reference Genome Assemblies[END_REF].

High quality genome (like human, mouse or A. thaliana).

A 'high quality' reference genome is defined here as a reference sequence that is both complete in terms of coverage and representative of the genetic diversity of the species investigated. Because current sequencing technologies can only target the euchromatic portion of the genome (hence excluding the heterochromatin that includes the centromere and telomere regions), 'complete' refers here to the euchromatic genome. 'Finished' quality genome projects typically cover >95% of the euchromatin sequence, a target that can however be difficult to achieve depending on the genome size and complexity of the targeted species.

Here genetic variation does not just refer to single nucleotide polymorphisms (SNPs) but also to structural variation that represents a large source of genomic diversity [START_REF] Church | Modernizing Reference Genome Assemblies[END_REF].

With the notable exception of the human genome however, most genome sequences only satisfy the first criterion ('complete' sequence) and thus represent what was defined as a 'golden path' during the course of the sequencing of the human genome: a non-redundant haploid representation of the genome [START_REF] Kent | Assembly of the working draft of the human genome with GigAssembler[END_REF].

A 'golden path' reference genome

A 'golden path' reference genome thus represents the first level of reference sequence that could be used for genome scans. With sufficient coverage (>30X), this approach should lead to a reference genome covering >95% of the euchromatin sequences. Those values are however highly dependent on the size of the genome and on factors such as the frequency of repeated regions in the genome. Such complete sequences are rarely obtained in conservation biology at the moment however, as illustrated by the de novo sequencing of the genome of Arabis alpina, which resolved less than 50% of the genome (172 Mb out of 370 Mb) [START_REF] Lobreaux | Development of an Arabis alpina genomic contig sequence data set and application to single nucleotide polymorphisms discovery[END_REF]. Similarly, complex regions with recently duplicated segments for example or plastic regions in diploid genomes may not be well resolved by this approach [START_REF] Alkan | Applications of next-generation sequencing. Genome structural variation discovery and genotyping[END_REF]. Over the past couple of years, ways to improve initial genome assemblies have emerged. In particular, technology from Pacific Biosciences (PacBio) for long-read single molecule, realtime (SMRT) sequencing can upgrade genomes to a higher quality finished state [START_REF] Huddleston | Reconstructing complex regions of genomes using long-read sequencing technology[END_REF]. SMRT sequencing is however still costly and can thus only be applied to small genomes or to targeted resequencing of specific regions. To avoid the problems associated with sequencing plastic regions in diploid genomes, an interesting alternative is also to work with haploid cell lines generated from the same organism such as specific tissues Chaisson et al. 2015b) or specific life stages [START_REF] Rensing | The Physcomitrella genome reveals evolutionary insights into the conquest of land by plants[END_REF]). Although such cell lines will likely not be available for most organisms, single cell genomics are rapidly progressing so that single gametes could become an adequate resource to establish reference genome [START_REF] Macaulay | Single Cell Genomics: Advances and Future Perspectives[END_REF]. The sequencing of the genome of the European Sea Bass was based on the use of a meiogynogenetic individual [START_REF] Tine | European sea bass genome and its variation provide insights into adaptation to euryhalinity and speciation[END_REF]. Finally, in addition to the experimental improvements, the quality of the reference genomes also increases with the development of better assemblers, i.e. the software used to assemble genomes. Indeed, software now exists to help de novo assembly from whole -genome shotgun short reads [START_REF] Kajitani | Efficient de novo assembly of highly heterozygous genomes from whole-genome shotgun short reads[END_REF] and efforts are being made to evaluate the performance of these methods [START_REF] Bradnam | Assemblathon 2: evaluating de novo methods of genome assembly in three vertebrate species[END_REF]. While progress is being made to generate 'golden path' reference genomes, this will at best lead to the complete sequencing of one haploid genome in a given species. Such a sequence will be sufficient for the analysis of genome scans for the vast majority of genes and genomic regions but will be problematic to investigate the more plastic regions of the genome. Indeed, even for the highest quality mammalian genome, the human genome, it was found that some genomic regions were missing in the reference sequence [START_REF] Kidd | Characterization of missing human genome sequences and copy-number polymorphic insertions[END_REF]. These specific regions display structural differences between the genomes of the individuals investigated and the reference genome, either because of specific deletions or because of underrepresented multi-copy genes in the reference genome [START_REF] Sudmant | Diversity of Human Copy Number Variation and Multicopy Genes[END_REF].

Improving quality of assembly

Status on genome sequencing

In The human reference genome was thus organized to include multiple sequences for these regions [START_REF] Church | Modernizing Reference Genome Assemblies[END_REF]. Thus 'high quality' reference genomes that include multiple sequences for the plastic regions are necessary to produce unbiased results in genome scans.

Such a reference sequence requires two additional steps once a first complete sequence of the genome is known: the identification of these regions and the characterization of the variation at these regions. Finally, data from these regions might need to be adapted to run some of the Population genomic studies can be useful both for the management of wild and domestic hatchery populations and for a better understanding of the evolution of species, which is useful for conservation purposes. The study on the European sea bass (Dicentrarchus labrax)

provides a good illustration of the multiple interests and applications of genomic data. This species is heavily harvested. Its distribution range, from the Atlantic Ocean to the Black Sea, encompasses an important barrier to gene flow at the Almeria-Oran front which separate two genetic lineages [START_REF] Lemaire | Maintenance of genetic differentiation across a transition zone in the sea: discordance between nuclear and cytoplasmic markers[END_REF]. The European sea bass can be present in different levels of salinity which raises the question of its adaptation to different environments (e.g [START_REF] Lemaire | Do discrepancies between microsatellite and allozyme variation reveal differential selection between sea and lagoon in the sea bass (Dicentrarchus labrax)?[END_REF]). Getting genomic information on this species would be useful to better understand its evolutionary history and would be useful for aquaculture purposes. Tine et al.

(2014) published the first draft genome of D. labrax. The sequencing of the genome was based on a meiogynogenetic male, with an average coverage depth of 30X and used a combination of whole-genome shotgun, mate pair and BAC end sequencing. The length of the assembled genome reached 650 Mbp and 86% of the contigs were assigned to the 24 chromosomes of this species. The genome annotation led to the identification of 26,719 genes and an important collinearity was observed with other teleosts genomes. This genome corresponds to the 'golden path' genome as described in Box 1. RAD-sequencing was then used to study the polymorphism at the genome scale for 100 individuals (and three from anoutgroup, D. punctatus). The authors obtained around 178,000 RAD loci which, after mapping on the genome, allowed them to analyze one locus every 7.5 kb and to reach a 2.5% genome coverage. The combination of the reference genome and RAD loci allowed for a better understanding of the evolutionary and adaptive history of the species. For example, the identification of signatures of positive selection in duplicates of genes involved in osmoregulation (e.g. PRL-L2) opened the way to a better understanding of euryhalinity in this species and in other teleosts as well. Here important information comes from the combination of a good annotation, the discovery of multiple gene copies of the same family and from statistical test of molecular evolution. The genomic analysis of differentiation between Atlantic and Mediterranean lineages led to a mean F ST of 0.28 but with highly heterogeneous repartition: genomic islands of differentiation were observed with lengths varying from several hundred kb to more than one Mb. These islands were negatively correlated with local recombination rate and diversity levels (with a few exceptions). Mapping SNPs obtained

  powerful approaches to investigate the action of natural selection on the genetic variation of natural populations and to better understand local adaptation. This is very useful for example in the field of conservation biology and evolutionary biology. Thanks to Next Generation Sequencing, genomic resources are growing exponentially, improving genome scan analyses in non-model species. Thousands of SNPs called using Reduced

  a wide variety of heterogeneous and changing environments, where the environment designs large range of abiotic factors (e.g. temperature, oxygen) and biotic factors (pathogens, symbionts, sexual partners) potentially causing selection. Understanding

1

  Words in bold are defined in the glossary

  individuals at lower coverage[START_REF] Soria-Carrasco | Stick Insect Genomes Reveal Natural Selection's Role in Parallel Speciation[END_REF]. In their study of speciation and adaptation to different host plants in the stick insect Timema cristinae,[START_REF] Soria-Carrasco | Stick Insect Genomes Reveal Natural Selection's Role in Parallel Speciation[END_REF] first sequenced the genome on the basis of libraries of lengths varying from 170 to The total genome size was estimated around 1.3 Gb and the assembled genome was estimated to cover around 80% of the genome. Then,[START_REF] Soria-Carrasco | Stick Insect Genomes Reveal Natural Selection's Role in Parallel Speciation[END_REF] resequenced at lower coverage the genomes of 160 individuals on eight lanes of Illumina Hi-Seq 2000. The reads were mapped to the reference genome. They thus obtained more than 12.10 6 SNPs with a mean coverage of 5 per SNP and per individual. Such sequencing of several individuals then allowed to produce 4,391,556 SNPs that mapped to one of the 13 linkage group and were used in phylogenetic analysis and to characterize the distribution of genomic variation across the 160 wild-caught T. cristinae. However, this approach is still relatively expensive for conservation projects needing numerous individuals. As the power of genome scan approaches can be increased by the number of locations sampled and the number of individuals sampled per location[START_REF] Lotterhos | The relative power of genome scans to detect local adaptation depends on sampling design and statistical method[END_REF], other approaches can be useful to reduce sequencing costs. Whole genome sequencing of pooled individuals is a promising and cost effective alternative to individual sequencing[START_REF] Schloetterer | Sequencing pools of individuals-mining genome-wide polymorphism data without big funding[END_REF].

  high quality genomes will allow studying of highly variable regions located in coding regions(Chaisson et al. 2015a) (Box 2). In humans, such plastic regions of the genome are known to contain important immune gene families such as the Major Histocompatibility Complex (MHC) class I and class II genes and the Killer-cell Ig-like Receptor (KIR) genes that are both critical for the resistance to pathogens and hence for the adaptation to different environments[START_REF] Sommer | The importance of immune gene variability (MHC) in evolutionary ecology and conservation[END_REF][START_REF] Vilches | KIR: Diverse, rapidly evolving receptors of innate and adaptive immunity[END_REF].

  et al. 2007). Suh methods relay on the analysis of haplotype. They open perspectives to capture the signal of selection left by both hard and soft sweep. If adaptation has been shaped by new mutations rapidly driven to high frequency in a new environment, those alleles will be detected on haplotypes with low genetic diversity and not observed in ancestral populations or environment[START_REF] Stapley | Adaptation genomics: the next generation[END_REF] . In this current issue,[START_REF] Vatsiou | Detection of selective sweeps in structured populations: a comparison of recent methods[END_REF] compared seven methods that either focus on patterns of long range haplotype homozygosity[START_REF] Sabeti | Detecting recent positive selection in the human genome from haplotype structure[END_REF] or on the effect of linkage on multilocus genetic differentiation[START_REF] Chen | Inferring Selection Intensity and Allele Age from Multilocus Haplotype Structure[END_REF]. Those methods open perspectives to capture the signal of selection left by both hard and soft sweep.As previously mentioned above, neutral processes can confound the signal of selection. Sophisticated methods using physically indexed SNPs, haplotype or sequence data have been recently developed to improve the inference of demographic processes by helping to reconstruct an accurate demographic history, potentially implicating heterogeneous gene flow along the genome, for the population studied and hence decrease confounding effects(Excoffier et al. 2013; Gutenkunst et al. 2009;[START_REF] Liu | Exploring population size changes using SNP frequency spectra[END_REF].

  Genome scans characterize loci potentially involved in the adaptation to particular environments but because these methods can generate false positives, a prioritization of candidate loci help to focus on the most reliable candidates. Mapping loci on a reference genome can allow the identification of coding candidates or to loci in physically proximity to coding regions (in this case, a transcriptome can be enough to identify expressed loci). If these genes are annotated in the studied species or a closely related one, it can highlight candidate genes functionally consistent with the studied selective context. For example, using exome sequencing, Yi et al (2010) studied the adaptation of human to high altitudes and found that the candidate gene with the strongest signal of selection was a transcription factor involved in response to hypoxia. In this case, the consistence between the function and the environmental context of the study provided a strong support for this candidate. For the non-model organisms for which the reference genome sequence lacks functional annotations, Gene Ontology (GO) could be a useful tool to find pertinent functions in the studied context among the candidate genes(Gu et al. 2009). The identification of loci repeatedly involved in the same biological or ecological function in different taxonomic groups exposed to comparable pressures can also be a good argument for the choice of candidate loci[START_REF] Pratlong | The red coral (Corallium rubrum) transcriptome: a new resource for population genetics and local adaptation studies[END_REF].For example,[START_REF] Rellstab | Validation of SNP Allele Frequencies Determined by Pooled Next-Generation Sequencing in Natural Populations of a Non-Model Plant Species[END_REF] studied the local adaptation of Arabidopsis halleri to local climatic conditions by the use of SNPs obtained from Pool Seq. First they detected outlier SNPs on the basis of F ST and differentiation tests. Then they tested the association between these outliers and environmental conditions while controlling for population structure. A GO enrichment was applied to the outlier loci as well and led to the discovery of the implication of functions linked with the response to biotic factors (such as "defence response to bacterium"). Conversely they considered genes with GO potentially involved in the adaptation to climate conditions: among these candidate genes, four were indeed associated with the corresponding environmental factor. This study then underlines how multiple identify the factors involved in local adaptation.

(

  Coregonus clupeaformis)(Gagnaire et al. 2013). The opportunity of whole genome sequencing allows nowadays to move toward GWAS, mostly in the identification of sequence variants associated with risks of complex traits in human genetics, where genomes are available at population scales(Hawley et al. 2014). In this field, GWAS was used in the identification of loci linked with the specialized diet of greenlandic Inuit, and associated with phenotypes(Fumagalli et al. 2015). Nevertheless, the last and probably the most difficult step will be to link phenotypic or genetic differences with fitness differences. Here the analysis of the fitness of all possible point mutants in different controlled environmental conditions open perspectives to make such link. For example,Heiptas et al. (2011) analyzed the effect on fitness (growth rate during binary competition in this case) of all possible point mutations for a nine-amino acid region of Hsp90 in yeast. They observed a large proportion of mutation with strong deleterious effect eliminated via purifying selection and few mutation with neutral effect which is consistent with the neutral model of molecular evolution. Linking genotype to fitness open new perspectives such as the possibility to study the population of origin (central population vs margin population) of the mutation in the species range(Rolland et al. in press).

Figure 1 .

 1 Figure 1. Schematic representation of the benefits of using additional genomic resources (mainly reference genomes) in the different steps of genome scans. GBS: Genotyping by sequencing.

  It is now possible to rapidly generate such a reference sequence thanks to modern sequencing technologies that have led to a rapid decrease in the cost of sequencing: for example in 2014-15, typical cost for re-sequencing of a human-size genome (3,000Mb) with paired-ends reads at 30X coverage on an Illumina HiSeq platform is $4,211. This cost includes labor, administration, management, utilities, reagents, and consumables; sequencing instruments and other large equipment (amortized over three years); informatics activities directly related to sequence production; submission of data to a public database and indirect costs (source: National Human Genome Research Institute (NHGRI); http://www.genome.gov/sequencingcosts/).

  human such plastic regions of the genome are known to contain important immune gene families such as the Major Histocompatibility Complex (MHC) class I and class II genes and the Killer-cell Ig-like Receptor (KIR) genes that are critical for the resistance to pathogens and hence for the adaptation to different environments (Sommer 2005; Vilches & Parham 2002). Indeed recent genome scans approaches on human populations underlined the critical roles of pathogens in local adaptation (Fumagalli et al. 2011).Both gene families display a high level of polymorphism but also gene-content variation (see Figure for the KIR locus) so that a single reference sequence will not represent correctly the gene content in all individuals and could lead to problematic analyses for genome scans. Indeed, not including multiple references for such regions produces misalignments of the reads and spurious variant calls.

  Methods based on the use of restriction enzyme digestion of target genomes to reduce the complexity of the target: example of RAD-seq RAD-Seq is based on the sequencing of short sequences flanking restriction sites[START_REF] Baird | Rapid SNP Discovery and Genetic Mapping Using Sequenced RAD Markers[END_REF]. It requires choosing the restriction enzyme(s) in combination with the sequencing depth and the number of individuals multiplexed in order to modulate the number of expected markers. This choice is done on the basis of genome knowledge (size and GC-content) for the target species or on phylogenetically related species as proposed by[START_REF] Herrera | Genome-wide predictability of restriction sites across the eukaryotic tree of life[END_REF]. The analysis of RAD-Seq data can be done thanks to different software packages such for example as Stacks[START_REF] Catchen | Stacks: an analysis tool set for population genomics[END_REF], PyRAD (Eaton 2014), RADtools[START_REF] Baxter | Linkage Mapping and Comparative Genomics Using Next-Generation RAD Sequencing of a Non-Model Organism[END_REF]), GATK (DePristo et al. 2010), or dDozent[START_REF] Puritz | dDocent: a RADseq, variant-calling pipeline designed for population genomics of non-model organisms[END_REF].As an illustration,[START_REF] Pavey | RAD Sequencing Highlights Polygenic Discrimination of Habitat Ecotypes in the Panmictic American Eel[END_REF] used RAD-Seq to study the genetic basis of the differentiation between ecotypes of the American eel (Anguilla rostrata). They used the EcoRI restriction enzyme and analyzed 379 individuals with around 24 individuals per lane of an Illumina HiSeq 2000. After cleaning and filtering the data they retained 42 424 SNPs which corresponded to 1 SNP every 40 kb. This density allowed them to identify 331 SNPs associated with the ecotypes, with 99 SNPs corresponding to annotated protein-coding genes.

  Figure 1

  round after outlier detection methods or directly for detecting outlier loci. The first application of GEA in the context of genome scan tests the correlation between allele frequencies and environmental variables[START_REF] Joost | A spatial analysis method (SAM) to detect candidate loci for selection: towards a landscape genomics approach to adaptation[END_REF][START_REF] Schoville | Adaptive genetic variation on the Landscape: methods and cases[END_REF]; then other regression based approaches have been used[START_REF] Rellstab | A practical guide to environmental association analysis in landscape genomics[END_REF].However the signature of adaptive processes are not always distinguishable from the neutral genomic background as assumed to have uniform effects across the entire genome, generating a high number of false positive outliers[START_REF] Schoville | Adaptive genetic variation on the Landscape: methods and cases[END_REF]. Population structure causes

	F o F o
	r r
	R e v i e w R e v i e w
	O n O n
	l y l y
	caveats being that the loci identified as potential targets of selection are usually only
	statistically linked with close targets of adaptive significance.

environmental variables are available, it is possible to use genetic environment associations

(GEA tests, Hedrick et al. 1976;[START_REF] Lotterhos | The relative power of genome scans to detect local adaptation depends on sampling design and statistical method[END_REF]

either in a second correlated allele frequencies and increases the number of false positives generated by genome scans for selective sweeps

(Excoffier et al. 2009)

. Demographic history can create patterns resembling selection, as in cases of severe bottlenecks, allele surfing during population expansion, secondary contact, and isolation by distance

[START_REF] Novembre | Spatial patterns of variation due to natural selection in humans[END_REF]

.

Genetic incompatibilities or background selection on gene-coding regions can also confound the signal of selection

[START_REF] Bierne | Pervasive selection or is it? why are FST outliers sometimes so frequent?[END_REF]

. Although, refinements have been introduced to account for those confounding effects

[START_REF] Lotterhos | The relative power of genome scans to detect local adaptation depends on sampling design and statistical method[END_REF]

, false positives remain.

Without additional genomic resources, those analyses produce a list of loci that are potentially under selection or linked to alleles under selection, and when available the relevant environmental variables acting as pressures of selection. They generally detect single loci with important effects on adaptation. However some questions may remain, the most evident

  Dicentrarchus labrax using a window size of 150 kb[START_REF] Tine | European sea bass genome and its variation provide insights into adaptation to euryhalinity and speciation[END_REF] (Box 4). This technique can also be used on whole genome resequencing data, as illustrated in[START_REF] Kardos | Whole genome resequencing uncovers molecular signatures of natural and sexual selection in wild bighorn sheep[END_REF] in which they implemented windows of 100 kb, with step size of 50 kb, and found elevated F ST in regions spanning growth hormone receptor gene. To go even further, Roesti et al.(Roesti et al. 2012b) suggested correcting SNP F ST by local recombination rates. In fact, they showed patterns of within-chromosome large-scale variations in recombination and hitchhiking and thus in F ST that were probably largely influenced by chromosomes structure.They propose to correct for this potential bias by applying sliding window tests on corrected F ST rather than raw F ST , to avoid potential false positive and false negative outliers. Another way of considering this potential bias is to estimate locally averaged recombination rate, nucleotide diversity, and genetic differentiation and to interpret these indices in an integrated manner as illustrated in the European sea bass Dicentrarchus labrax[START_REF] Tine | European sea bass genome and its variation provide insights into adaptation to euryhalinity and speciation[END_REF].

	F o
	r
	R e v i e w
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Comparing the classical local averaged F ST among populations to windows-based F ST would reveal the presence of putative targets of positive selection. For example, this strategy has been used to study the variation of F ST in different lineages of the European sea bass

  from a single individual are also sufficient to make demographic inference[START_REF] Miller | Polar and brown bear genomes reveal ancient admixture and demographic footprints of past climate change[END_REF][START_REF] Oleksyk | A locally funded Puerto Rican parrot (Amazona vittata) genome sequencing project increases avian data and advances young researcher education[END_REF]; iii) improving the statistical power of methods to detect the signal of selection. Finally, if the available genome is of high quality, i) it allows matching the potential candidate loci to linked coding regions under selection , ii) it rapidly moves the investigation to the gene and function[START_REF] Lamichhaney | Evolution of Darwin's finches and their beaks revealed by genome sequencing[END_REF], iii) it ensures that the highly variable regions of the genomes in coding regions are also investigated. This last point is important when region under selection are located in such variable regions (Box 2). Foundation and to the Labex OT-Med (no. ANR-11-LABX-0061) funded by the French Government 'Investissements d'Avenir' program of the French National Research Agency (ANR) through the A*MIDEX project (no. ANR-11-IDEX-0001-02). This project has been funded by the ADACNI program of the French National Research Agency (ANR) (project no. Yi X, Liang Y, Huerta-Sanchez E, et al. (2010) Sequencing of 50 Human Exomes Reveals Adaptation to High Altitude. Science 329, 75-78.

	de Villemereuil P, Frichot E, Bazin E, Francois O, Gaggiotti OE (2014) Genome scan Glossary
	methods against more complex models: when and how much should we trust them? De novo assembled genome: sequence of a genome from overlapping DNA sequences
	Molecular Ecology 23, 2006-2019. without having a reference genome.
	De Wit P, Palumbi SR (2013) Transcriptome-wide polymorphisms of red abalone (Haliotis
	ANR-12-ADAP-0016; http://adacni.imbe.fr) and rufescens) reveal patterns of gene flow and local adaptation. Molecular Ecology 22,
	2884-2897.
	Dixon GB, Davies SW, Aglyamova GA, et al. (2015) Genomic determinants of coral heat
	F o F o F o F o F o tolerance across latitudes. Science 348, 1460-1462. Eaton DAR (2014) PyRAD: assembly of de novo RADseq loci for phylogenetic analyses. F o F o F o F o F o F o F o F o F o F o
	r r r r r Bioinformatics 30, 1844-1849. r r r r r r r r r r
	R e v i e w R e v i e w R e v i e w R e v i e w R e v i e w R e v i e w R e v i e w R e v i e w R e v i e w R e v i e w R e v i e w R e v i e w R e v i e w R e v i e w R e v i e w
	O n l y O n l y O n l y O n l y O n l y O n O n O n O n O n O n O n O n O n O n Foll M, Gaggiotti O (2008) A genome scan method to identify selected loci appropriate for both dominant and codominant markers: a Bayesian perspective. Genetics 180, 977-l y l y l y l y l y l y l y l y l y l y
	993.
	Fumagalli M, Moltke I, Grarup N, et al. (2015) Greenlandic Inuit show genetic signatures of
	diet and climate adaptation. Science 349, 1343-1347.
	Fumagalli M, Sironi M, Pozzoli U, et al. (2011) Signatures of Environmental Genetic
	Adaptation Pinpoint Pathogens as the Main Selective Pressure through Human
	Evolution. Plos Genetics 7.

; with deep coverage, genome sequence data We state that having reference genomes represent a critical step to fully address the question of local adaptation. The community of researchers working in ecology on non-model species will thus gain to collaborate with the community of researchers working on species for which large genomic resources have long been available (human and other model species), as the latter have a long tradition of sequence analysis to detect signatures of natural selection. Combining evolution, ecology, genomics and comparative genomics will help to better address the question of local adaptation, which is topical in a context of global change. Finally we should keep in mind that adaptation sensu lato does not only rely on genetic diversity. Indeed the question of non-genetic effects, including epigenetic mechanisms, is of great interest in evolutionary biology (Danchin 2013); yet, here again the use of genomic information should be useful to study the diversity in epigenetic modifications. Excoffier L, Dupanloup I, Huerta-Sanchez E, Sousa VC, Foll M (2013) Robust Demographic Inference from Genomic and SNP Data. Plos Genetics 9. Excoffier L, Hofer T, Foll M (2009) Detecting loci under selection in a hierarchically structured population. Heredity 103, 285-298. Fischer MC, Rellstab C, Tedder A, et al. (2013) Population genomic footprints of selection and associations with climate in natural populations of Arabidopsis halleri from the Alps. Molecular Ecology 22, 5594-5607.

Challenges of highly variable regions

	Box 2-
	F o
	r
	Progress http://www.ncbi.nlm.nih.gov/genome/browse/# on genome information R e v i e w	can	be	found	here:
	O n
			l y

  Figure. Example of a highly-variable region of the genomes of primates: the Killer-cell Iglike Receptor (KIR) locus. This drawing compares the organization and gene-content variability of the human and chimpanzee KIR loci. The branching pathways illustrate how different gene-content motifs can combine to produce different KIR haplotypes. Genes that are typically found on all haplotypes of both species (framework genes) are colored grey; chimpanzee-specific KIR are colored green. Humans have two broad groups of haplotypes called A and B haplotypes that differ in gene content and level of allelic variability (Parham et al. 2012): genes characteristic of human A haplotypes are colored red while genes characteristic of human B haplotypes are colored blue (2DP1 and 2DL1 in humans are colored grey to indicate their presence both on A and B haplotypes). Adapted from Abi-Rached et al. (Abi-Rached et al. 2010).

	F o
	r
	R e v i e w
	O n
	l y
	usual tests of local adaptation such as F ST outliers: for example by encoding presence/absence
	of genes (KIR locus) as SNPs or by considering complete alleles rather than individual SNP
	(MHC genes). Because these highly variable gene families have a strong impact on immune
	adaptation, they are often investigated by targeted analyses, outside of genome scans
	(candidate gene approaches)

Acknowledgement

We thank the foundation ECCOREV that financed the meetings for this paper. We thank 2 anonymous reviewers for very helpful comments. We thank Amanda Xuereb for reading the manuscript. This work is a contribution to the project SEACONNECT funded by the Total

Funk WC, McKay JK, Hohenlohe PA, Allendorf FW (2012) Harnessing genomics for delineating conservation units. Trends In Ecology & Evolution 27, 489-496. Gagnaire P-A, Broquet T, Aurelle D, et al. (2015) Using neutral, selected, and hitchhiker loci to assess connectivity of marine populations in the genomic era. Evolutionary Applications 8, 769-786. Gagnaire P-A, Normandeau E, Cote C, Hansen MM, Bernatchez L (2012) The Genetic Consequences of Spatially Varying Selection in the Panmictic American Eel (Anguilla rostrata). Genetics 190, 725-U703. Gagnaire PA, Pavey SA, Normandeau E, Bernatchez L (2013) The genetic architecture of reproductive isolation during speciation-with-gene-flow in lake whitefish species pairs assessed by rad sequencing Evolution 67, 2483-2497. Gayral P, Melo-Ferreira J, Glemin S, et al. (2013) Reference-Free Population Genomics from Next-Generation Transcriptome Data and the Vertebrate-Invertebrate Gap. Plos Genetics 9. Gu J, Orr N, Park SD, et al. (2009) A Genome Scan for Positive Selection in Thoroughbred Horses. Plos One 4. Gutenkunst RN, Hernandez RD, Williamson SH, Bustamante CD (2009) Inferring the Joint Demographic History of Multiple Populations from Multidimensional SNP Frequency Data. Plos Genetics 5. Hawley NL, Minster RL, Weeks DE, et al. (2014) Prevalence of Adiposity and Associated Cardiometabolic Risk Factors in the Samoan Genome-Wide Association Study. American Journal of Human Biology 26, 491-501. Hedrick PW, Ginevan ME, Ewing EP (1976) Genetic polymorphism in heterogeneous environements Annual Review of Ecology And Systematics 7, 1-32.


Yulong Fan

Xavier Le Roux

Anatole Lupu

André De Lustrac
email: andre.de-lustrac@c2n.upsaclay.fr

Ultra-compact on-chip metaline based 1.3/1.6 µm wavelength demultiplexer

In this article, we report an experimental demonstration of enabling technology exploiting resonant properties of plasmonic nanoparticles, for the realization of wavelength sensitive ultra-minituarized (4×4 µm) optical metadevices. To this end the example of a 1.3/1.6 µm wavelength demultiplexer is considered. Its technological implementation is based on the integration of gold cut wire based metalines on the top of a silicon on insulator waveguide. The plasmonic metalines modify locally the effective index of the Si waveguide and thus allow for the implementation of wavelength dependent optical pathways. The 1.3/1.6µm wavelength separation with extinction ratio between two demultiplexer's channels reaching up to 20dB is experimentally demonstrated. The considered approach, which can be readily adapted to other planar lightwave circuits platforms and nanoresonators of different types of materials, is suited for the implementation of a generic family of wavelength sensitive guided wave optical metadevices.

INTRODUCTION

The continuous improvement of fabrication technologies was the main driving vector enabling miniaturization of electronic circuits components to a nanometers scale. Similar trends hold also for optical circuits, with many efforts devoted to bridge the gap between photonics and electronics. Because of their massless nature, photons are orders of magnitude less confined than electrons. Even in the case of high index materials, such as silicon, implementation of optical functions exploiting interference between co-or contra-propagating waves in nanostructured dielectric materials like photonic crystals [START_REF] Yablonovitch | Inhibited spontaneous emission in solid-state physics and electronics[END_REF][START_REF] Yablonovitch | Photonic band-gap structures[END_REF] or similar [START_REF] Halir | Waveguide sub-wavelength structures: a review of principles and applications[END_REF] requires an interaction length of at least several wavelengths.

The change of paradigm brought by the advent of metasurfaces made possible to control the phase and amplitude of reflected or transmitted wave on a "skin depth" propagation length of the order of  /10 [START_REF] Yu | Light propagation with phase discontinuities: generalized laws of reflection and refraction[END_REF][START_REF] Ni | Broadband light bending with plasmonic nanoantennas[END_REF][START_REF] Huang | Dispersionless phase discontinuities for controlling light propagation[END_REF][START_REF] Pfeiffer | Metamaterial Huygens' surfaces: tailoring wave fronts with reflectionless sheets[END_REF][START_REF] Yu | Flat optics with designer metasurfaces[END_REF]. Based on this approach, numbers of functionalities targeting flat optics applications, have been demonstrated [START_REF] Yu | Light propagation with phase discontinuities: generalized laws of reflection and refraction[END_REF][START_REF] Ni | Broadband light bending with plasmonic nanoantennas[END_REF][START_REF] Huang | Dispersionless phase discontinuities for controlling light propagation[END_REF][START_REF] Pfeiffer | Metamaterial Huygens' surfaces: tailoring wave fronts with reflectionless sheets[END_REF][START_REF] Yu | Flat optics with designer metasurfaces[END_REF][START_REF] Shitrit | Spin-optical metamaterial route to spin-controlled photonics[END_REF][START_REF] Yang | Dielectric meta-reflect array for broadband linear polarization conversion and optical vortex generation[END_REF][START_REF] Chen | Dual-polarity plasmonic metalens for visible light[END_REF][START_REF] Larouche | Infrared metamaterial phase holograms[END_REF][START_REF] Ni | Metasurface holograms for visible light[END_REF][START_REF] Zheng | Metasurface holograms reaching 80% efficiency[END_REF][START_REF] Ni | An ultrathin invisibility skin cloak for visible light[END_REF]. Meanwhile another possibility for the manipulation of the optical flow by means of metasurfaces is to use them in a guided wave configuration [START_REF] Koenderink | Nanophotonics: Shrinking lightbased technology[END_REF][START_REF] Arango | Plasmonic antennas hybridized with dielectric waveguides[END_REF][START_REF] Zhou | Lasing action in strongly coupled plasmonic nanocavity arrays[END_REF][START_REF] Guo | Plasmonic Fano nanoantennas for on-chip separation of wavelengthencoded optical signals[END_REF][START_REF] Li | Controlling propagation and coupling of waveguide modes using phase-gradient metasurfaces[END_REF][START_REF] Peyskens | Bright and dark plasmon resonances of nanoplasmonic antennas evanescently coupled with a silicon nitride waveguide[END_REF][START_REF] Lupu | Metaldielectric metamaterials for guided wave silicon photonics[END_REF]. The demonstration of a gradient effective index metalens based on this concept was recently reported [START_REF] Fan | Integrated 2Dgraded index plasmonic lens on a silicon waveguide for operation in the near infrared domain[END_REF]. The technological implementation is performed by means of a metasurface made of 2D array of gold cut wires (CWs) integrated on the top of the Si waveguide. The aim of the present work is to provide a further impetus to this direction by introducing the concept of the wavelength dependent optical pathways, distinctly different from the wavelength dependent angular beam steering effects in photonic crystals [START_REF] Kosaka | Photonic crystals for micro lightwave circuits using wavelength-dependent angular beam steering[END_REF][START_REF] Lupu | Discontinuous wavelength super-refraction in photonic crystal superprism[END_REF] or bi-directional coupling using plasmonic Fano nanoantennas [START_REF] Guo | Plasmonic fano nanoantennas for on-chip separation of wavelengthencoded optical signals[END_REF]. To prove the feasibility of the considered approach we report the design, fabrication, and experimental demonstration of an ultra-compact (4 × 4 µm) demultiplexer (DMUX) operating in the wavelength range 1.3/1.6 µm.

METALINES BASED WAVELENGTH DMUX OPERATION PRINCIPLE, DESIGN AND MODELING

The operation principle of the reported wavelength DMUX is based on the wavelength dependent local variation of the hybrid metal-dielectric waveguide effective index (neff) induced by the plasmonic nanoresonators. Here we use metalines made of 1D arrays of gold cut wires (CWs) instead of 2D metasurfaces to modify locally the index of a Si waveguide, creating thus the equivalent of color sensitive optical fibers into the Si layer. They can serve as building blocks for numbers of guided wave optical metadevices based on the local variation of the effective index.

The schematic of the hybrid metal-dielectric DMUX operating in a guided wave configuration is shown in Fig. 1(a). Its technological implementation is performed by means of integration of 1D arrays of plasmonic nanoresonators on the top of the 220nm thick silicon on insulator (SOI) slab. The dimensions of gold CWs plasmonic nanoresonators are adapted to the transmitted wavelengths, around 1.3µm in one arm and 1.6µm in the other one. DMUX operation is performed in the fundamental TE polarization mode of SOI waveguide, i.e. when the direction of the electric field is parallel to the long axis of CWs in order to induce the excitation of localized surface plasmons. The resonant frequency of the localized surface plasmons is the primary parameter for the engineering of such hybrid waveguides local effective index. The effective permittivity  eff of the hybrid metal/dielectric slab waveguide can be approximated as the sum of the effective permittivity of the dielectric slab waveguide and Lorentzian type dispersion formula accounting for the resonant features of plasmonic cut wires [START_REF] Lupu | Metaldielectric metamaterials for guided wave silicon photonics[END_REF][START_REF] Fan | Integrated 2Dgraded index plasmonic lens on a silicon waveguide for operation in the near infrared domain[END_REF]. As shown in Fig. 1(b) the effective refractive index is higher than that of the dielectric slab below the resonant frequency and lower above it. The local value of neff can thus be on demand engineered through an appropriate design of resonant elements' geometry and their spatial positioning on the surface of slab waveguide. Since the resonant frequency of localized surface plasmons is strongly dependent of their dielectric environment, the use of 5nm thick interfacial native silicon dioxide layer greatly contributes for increasing CWs' resonant frequency and facilitates thus the technological fabrication process [START_REF] Lupu | Metaldielectric metamaterials for guided wave silicon photonics[END_REF]. However around the resonance frequency of the gold cut wire occurs a peak of losses. To avoid the detrimental effects of losses inherent to the resonant absorption of metal CWs, it is preferable to detune the operation frequency from the resonance and find an optimal trade-off between index variation and loss.

In the present design the dimensions of CWs used for 1.3µm and 1.6µm output arms are 140 50 50 nm [arm 1 in the Fig. 1(a)] and 1905050 nm [arm 2 in the Fig. 1(a)], respectively. The longitudinal separation distance s between the cut wires in the direction of wave propagation is 50nm for the input area metaline and the output arms 1 and 2. While concerning the transverse separation distance d, it was fixed to 100nm. For a given CWs dimensions the effective index of the hybrid metal-dielectric waveguides, displayed in Fig. 1(b), was determined by means of numerical modeling with subsequent retrieval procedure [START_REF] Fan | Integrated 2Dgraded index plasmonic lens on a silicon waveguide for operation in the near infrared domain[END_REF][START_REF] Andryieuski | Wave propagation retrieval method for metamaterials: Unambiguous restoration of effective parameters[END_REF]. Here for 140 and 190 nm CWs length the resonance frequencies are 295 THz and 225 THz, respectively.

The role of the additionally implemented 2205050 nm size CWs, with a resonant frequency around 195THz, is to enhance the mode confinement of hybrid plasmonic-photonic waveguide at high frequencies. Indeed, as evident from Fig. 1(b), at the operating frequency of 230THz that corresponds to 1.3µm wavelength, the effective index of confinement areas (nconf=2.8) is lower than that of Si slab (nSi slab=2.92), and than that of the arm 1 (narm 1=3.1). In addition, the frequency of 230THz falls in the higly lossy frequency band of the arm 2. This is why the propagation of waves around this frequency in arm 2 is precluded by the resonance of the 190nm long CWs. This insures that the light is well confined under the arm 1. In contrast, at the operating frequency of 188THz (1.6 µm wavelength), the effective index of hybrid waveguide with 140 and 190 nm long CWs is 2.87 and 3.08, respectively. The light is then redirected into the arm 2.

The validity of the effective medium approach results was further verified by the full 3D optical simulations of the device. To this end we performed full 3D HFSS [28] simulations with usual parameters of SOI slab waveguide (2µm thick buried SiO2 underclad, 220nm thick Si core, 5nm thick SiO2 overclad corresponding to the native oxide). The parameters of Au, Si and SiO2 used in HFSS numerical simulations were taken from Palik [START_REF] Palik | Handbook of Optical Constants of Solids[END_REF].

The calculated distributions of light intensity at different wavelengths propagating across the hybrid plasmonic-photonic DMUX are shown in Figs 2(a) and 2(b). A clear spatial separation effect is observed for 1.3µm (230THz) and 1.62µm (185THz) wavelength. HFSS numerical simulations show also that the light is correctly guided at each frequency along the corresponding CWs metaline.

FABRICATION AND EXPERIMENTAL RESULTS

Figure 3 shows the scanning electron microscope (SEM) view of the experimentally fabricated on chip DMUX based on the discussed above design: the DMUX is located at the end of a 600nm wide single mode waveguide (SMW), and a 500nm SMW is created at the end of each optical arm to collect the transmitted optical signals. The experimental prototype was fabricated by using a technological process involving two levels of e-beam lithography. The first lithography is dedicated to the definition of metallic elements pattern, i.e. nano CWs and second mask level alignment marks. This step is performed by means of NB4 electron-beam lithography setup using PMMA positive resist to define the nanostructurs patterns on the surface of undoped SOI wafer from SOITEC with 220nm thick top Si layer and 2µm BOX. It is followed by resist development and a double step e-beam evaporation to deposit a 2nm film of chromium as an adhesion layer, then a 50nm film of gold.

The second e-beam lithography is dedicated to Si waveguides pattern definition using ZEP 520A positive resist. The residual resist is used after development as a soft mask for Si etching. Particular attention should be paid to the high precision alignment between the nano CWs and the Si waveguides patterns. This is achieved by utilizing the metal alignment mark implemented during the metallization step. The optical setup employed for the characterization of fabricated wavelengthDMUX is illustrated in Fig. 4. Three tunable diode lasers of the T100S series from Yenista Optics used as a light source cover a spectral range from 1.25µm to 1.68µm. The linearly polarized light is coupled into a polarization maintaining lensed fiber that serves for light injection into the waveguide. The light propagating through the DMUX is collected from the silicon chip output side facet by a 32  objective with 0.6 numerical aperture and then measured with a high sensitivity 1D CCD array IR camera used for registering the wavelength dependent spatial distribution of thetransmitted intensity. The distribution of light intensity in output waveguides as a function of wavelength is shown in Fig. 5(a). The obtained experimental results bring clear evidence of efficient wavelength separation performed by the DMUX. For wavelengths comprised between 1.25µm and 1.4µm the light propagates in the arm 1 with a very weak level of light intensity in the arm 2. In contrast, for the wavelengths between 1.6µm and 1.68µm, the light propagates mainly in the arm 2, while the residual light intensity in the arm 1 is very low. To illustrate the efficiency of the DMUX wavelength separation Fig. 5(b) shows superposition of snapshots of IR CCD obtained at 1.355µm and 1.655µm wavelength. The extinction ratio between the channels is very high reaching up to two orders of magnitude (20dB).

SUMMARY AND CONCLUSION

In conclusion, the demonstration of the wavelength separation produced by hybrid plasmonic-photonic DMUX unambiguously proves the ability for implementation of on demand light roads. In contrast to photonic crystals, the resonant nature of plasmonic nanoresonators inclusions allows a much higher degree of freedom for the wavelength dependent nanoscale engineering of the local effective index of the hybrid waveguide. Through an appropriate design of the resonant element, an effective index either higher or lower as that of the host slab waveguide can be obtained for a given wavelength. The extent of the effective index variation is essentially limited by the quality factor of gold plasmonic nanoresonator, which is relatively low in the NIR domain. By consequence, further improvement of the performances, that could be translated in a higher wavelength density of DMUX channels and even more smaller footprint, can be achieved by either considering applications in the MIR and THz domain, where metal related losses are negligible, or by extending the considered approach to all-dielectric metasurfaces and metalines [START_REF] Jahani | All-dielectric metamaterials[END_REF].

The reported enabling technology is quite generic and can be readily adapted to different types of planar lightwave circuits platforms: Silicon, GaN/AlN, InGaAsP/InP, doped silica glass etc. It paves the way for a new class of wavelength sensitive guided wave optical metadevices suited for color routing applications.

Fig. 1 .

 1 Fig. 1. (a) Schematic of integrated hybrid plasmonic-photonic wavelength DMUX. The difference in CWs' functional role evidenced by color. (b) Frequency dependence of effective refractive index of the hybrid plasmonic-photonic waveguide for different values of CWs length: 140, 190 and 220 nm considered here.

Fig. 2 .

 2 Fig. 2. HFSS modeling results for 1.3/1.6µm hybrid plasmonicphotonic DMUX. Distribution of propagating light intensity at different wavelengths: (a) f=185THz (=1.62µm); (b) f=230THz (=1.3µm).

Fig. 3 .

 3 Fig. 3. SEM image view of a fabricated DMUX.

Fig. 4 .

 4 Fig. 4. Schematic of the end-fire optical bench setup.

Fig. 5 .

 5 Fig. 5. Experimental results: (a) Colormap of light intensity distribution as a function of wavelength for a hybrid plasmonic-photonic DMUX; (b) Distribution of light intensity in the output arms at 1355nm and 1655nm wavelength.

Acknowledgment. The authors thank the C2N Orsay Cleanroom staff for their technological support in the device fabrication. This work was supported by theFrench RENATECH network.