Ann M Mc Cartney

Giulio Formenti

Alice Mouton

Diego De Panis

Luísa S Marins

Henrique G Leitão

Genevieve Diedericks

Joseph Kirangwa

Marco Morselli

Judit Salces-Ortiz

Nuria Escudero

Alessio Iannucci

Chiara Natali

Hannes Svardal

Rosa Fernández

Tim De Pooter

Geert Joris

Mojca Strazisar

Jo Wood

Katie E Herron

Ole Seehausen

Phillip C Watts

Felix Shaw

Robert P Davey

Alice Minotto

José M Fernández

Astrid Böhne

Carla Alegria

Tyler Alioto

Paulo C Alves

Isabel R Amorim

Jean-Marc Aury

Niclas Backstrom

Petr Baldrian

Laima Baltrunaite

Endre Barta

Bertrand Bed'hom

Caroline Belser

Johannes Bergsten

Laurie Bertrand

Helena Bilandžija

Mahesh Binzer-Panchal

Iliana Bista

Mark Blaxter

Guilherme Paulo Av Borges

Borges Dias

Mirte Bosse

Tom Brown

Rémy Bruggmann

Elena Buena-Atienza

Josephine Burgin

Elena Buzan

Nicolas Casadei

Matteo Chiara

Sergio Chozas

Fedor Čiampor

Angelica Crottini

Corinne Cruaud

Fernando Cruz

Love Dalen

Alessio De Biase

Javier Del Campo

Teo Delić

Martijn Alice B Dennis

F L Derks

Maria Angela Diroma

Mihajla Djan

Simone Duprat

Philine Klara Eleftheriadi

G D Feulner

Jean-François Flot

Giobbe Forni

Bruno Fosso

Pascal Fournier

Christine Fournier-Chambrillon

Toni Gabaldon

Shilpa Garg

Carmela Gissi

Luca Giupponi

Jèssica Gómez-Garrido

Josefa González

Miguel L Grilo

Bjoern Gruening

Thomas Guérin

Nadège Guiglielmoni

Marta Gut

Marcel P Haesler

Christoph Hahn

Balint Halpern

Peter Harrison

Julia Heintz

Maris Hindrikson

Jacob Höglund

Kerstin Howe

Graham Hughes

Benjamin Istace

Mark J Cock

Franc Jancekovic

Zophonías O Jónsson

Sagane Joye-Dind

Janne J Koskimaki

Boris Krystufek

Justyna Kubacka

Heiner Kuhl

Szilvia Kusza

Karine Labadie

Meri Lahteenaro

Henrik Lantz

Anton Lavrinienko

Lucas Leclère

Ricardo Jorge Lopes

Ole Madsen

Ghislaine Magdelenat

Giulia Magoga

Tereza Manousaki

Tapio Mappes

João P Marques

Martinez Redondo

Florian Maumus

Hendrik-Jan Megens

José Melo-Ferreira

Sofia L Mendes

Matteo Montagna

João Moreno

Mai-Britt Mosbech

Monica Moura

Zuzana Musilova

Eugene Myers

Will J Nash

Alexander Nater

Pamela Nicholson

Manuel Niell

Reindert Nijland

Benjamin Noel

Karin Norén

Pedro H Oliveira

Remi-Andre Olsen

Lino Ometto

Stephan Ossowski

Vaidas Palinauskas

Snaebjörn Pálsson

Jerome P Panibe

Joana Paupério

Martina Pavlek

Emilie Payen

Julia Pawłowska

Jaume Pellicer

Graziano Pesole

Joao Pimenta

Martin Pippel

Anna Maria Pirttilä

Nikos Poulakakis

Jeena Rajan

Ruben Mc Rego

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Philipp Resl

Ana Riesgo

Patrik Rödin-Mörch

E R André

Carlos Rodríguez Soares

Maria M Fernandes

Guilherme Romeiras

Lukas Roxo

María José Ruber

Urmas Ruiz-López

Luis P Saarma

Manuela Silva

Lucile Sim-Sim

Vitor C Soler

Carla Sousa Sousa

Alberto Santos

Milomir Spada

Viktor Stefanović

Josefin Steger

Matthias Stiller

Stöck

Hugo H Torsten

Hiranya Struck

Riikka Sudasinghe

Christian Tapanainen

Helena Tellgren-Roth

Yevhen Trindade

Ilenia Tukalenko

Benoit Urso

Steven M Vacherie

Kees Van Belleghem

Carlos Van Oers

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Noel Velickovic

Adriana Vella

Cristiano Vella

Sara Vernesi

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Mazzoni

The European Reference Genome Atlas: piloting a decentralised approach to equitable biodiversity genomics

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Reference genomes as a key biodiversity genomics tool

In the midst of the Earth's sixth mass extinction, species worldwide are declining at an unprecedented rate 1 directly impacting ecosystem functioning and services 2 , human health [START_REF] Urban | Real-time genomics for One Health[END_REF] and our resilience to climate disturbances [START_REF] Kumar | Changes in land use enhance the sensitivity of tropical ecosystems to fire-climate extremes[END_REF] . Biodiversity and ecosystem decline [START_REF]The IUCN Red List of Threatened Species Version 2022-2. The IUCN Red List of Threatened Species[END_REF][START_REF]Summary for policymakers of the global assessment report on biodiversity and ecosystem services[END_REF] , loss and degradation raise the prospect that many, if not most, of the Earth's biodiversity will be lost forever before they can be genomically explored -analogous to the 'dark extinctions' in the pre-taxonomic period [START_REF] Boehm | Dark extinction: the problem of unknown historical extinctions[END_REF] . Our ability to genomically characterise and investigate the species that span the tree of life, and their ecosystems, can help not only scientifically inform decision making processes to flatten the biodiversity extinction curve [START_REF] Supple | Conservation of biodiversity in the genomics era[END_REF] , but also can unlock diverse genetic-, species-and ecosystem-level [START_REF] Formenti | The era of reference genomes in conservation genomics[END_REF] discoveries that can be used for human health, bioeconomy stimulation, food sovereignty, biosecurity amongst many more.

As genomic sequencing has become increasingly cost effective and the platforms and computational algorithms become more technically efficient, many biodiversity genomics tools have become available to expedite the investigation of both known and unknown species e.g., DNA barcoding, genome skimming, reduced representation sequencing, transcriptome sequencing, and whole genome sequencing for reference genome production [START_REF] Theissinger | How genomics can help biodiversity conservation[END_REF] . Reference genomes (see glossary) are one such tool that offer an unparalleled, scalable, and increasingly cost-effective high resolution insight into species, and their accessibility has made the construction of a planetary-wide genomic database of all eukaryotic life a more realistic endeavor [START_REF] Lewin | Earth BioGenome Project: Sequencing life for the future of life[END_REF] .

To date, reference genomes do not exist for most of eukaryotic life. For instance, the largest genomics data repository, the International Nucleotide Sequence Database Collaboration (INSDC), has genome-wide DNA sequence information for just 6,480 eukaryotic species (about 0.43% of described species) of which over 63% (4,082) are short-read based (draft quality) [START_REF] Lewin | Earth BioGenome Project: Sequencing life for the future of life[END_REF] and most are variable in terms of sequence quality, data type, data volume, associated voucher samples, completeness of metadata and protocol reproducibility [START_REF] Crandall | Importance of timely metadata curation to the global surveillance of genetic diversity[END_REF][START_REF] Samuel | Understanding experiments and research practices for reproducibility: an exploratory study[END_REF][START_REF] Buckner | The critical importance of vouchers in genomics[END_REF] . Building from this, the biodiversity research community is pushing to expand beyond reference genome production alone and toward the production of a complete reference resource for each species. A complete reference resource includes a reference genome, an annotation, all metadata, and associated ex-situ samples (voucher(s) and cryopreserved specimen(s)). Complete reference resources are necessary to unlock the plurality of possible scientific enquiries beyond the scope of any singular research project [START_REF] Formenti | The era of reference genomes in conservation genomics[END_REF] . However, the scientific enquiries that can be actualised from reference resources [START_REF] Sabot | On the importance of metadata when sharing and opening data[END_REF] are limited in scope due in large to a current lack of standardisation across the multitude of actors involved throughout the production of complete reference resources.

The state of reference genome production today

After two decades of uncoordinated and unstandardised biodiversity genomics sequencing data production (e.g. with little coordination among individual research laboratories or projects), the Earth BioGenome Project (EBP) [START_REF] Lewin | Earth BioGenome Project: Sequencing life for the future of life[END_REF] was established. The goal of the EBP is to create a global network of biodiversity genomics researchers that share a mission to produce a database of openly accessible, standardised, and complete reference resources that span the whole eukaryotic phylogenetic tree. The project has a three-phase approach and to date (Phase I) has produced ~1,213 reference genomes for species across ~1,010 genera [START_REF] Challis | Genomes on a Tree (GoaT): A versatile, scalable search engine for genomic and sequencing project metadata across the eukaryotic tree of life[END_REF] . However the rate of production is fast increasing, for instance in 2022 over 316 reference genomes were produced and in the coming years the rate is estimated to increase by at least 10 fold. It is important to acknowledge that during this initial phase, 910 reference genomes were produced by a single affiliated project, the Darwin Tree of Life [START_REF] Null | Sequence locally, think globally: The Darwin Tree of Life Project[END_REF] , and a further 120 by the Wellcome Sanger Tree of Life Programme (https://www.sanger.ac.uk/programme/tree-of-life/). As the EBP approaches Phase II where 150,000 reference resources for species are planned, the status quo centralised approach poses significant challenges for scaling up reference genome production. Additionally, it raises important concerns regarding inclusion, accessibility, equity, and fairness.

The goal of building a decentralised model embracing all of Europe and beyond

Given these limitations, the European node of the EBP, the European Reference Genome Atlas (ERGA) (Box 1) set out to develop and implement a pilot decentralised infrastructure that would act to test the effectiveness of the approach in creating and scaling reference genomic resources for Europe's eukaryotes.

A decentralised approach for the production of genomic reference resources for ERGA supports:

1) an expansion in the diversity of expertise, processes and innovative ideas that can act synergistically to accelerate scientific outcomes, 2) a platform for accessible, equitable, and standard production of, high quality, ethically and legally compliant reference genomic resources, 3) streamlined communication and opportunities for new collaborations to be fostered, 4) an expansion of funding opportunities, 5) mitigation of hierarchical power imbalances, 6) increased access to up-to-date and reproducible tools and workflows, and 7) increased downstream analyses applications.

The ambition of the pilot test was to identify the challenges in constructing and implementing a decentralised infrastructure, but also to understand and find solutions on how best to support the inclusion of ERGA members who face a multitude of different realities whilst participating e.g., resource availability, geographic, and political positioning. The lessons learned from this initial pilot can certainly be used by ERGA to inform future developments, but can also be used to inform the broader EBP strategy as to whether decentralised approaches are effective in the production of reference genomic resources that meet with EBP minimum standards. https://www.earthbiogenome.org/) [START_REF] Lewin | Earth BioGenome Project: Sequencing life for the future of life[END_REF] , the mission of the European Reference Genome Atlas is to coordinate the generation of high-quality reference genomes for all eukaryotic life across Europe [START_REF] Mazzoni | Biodiversity: an atlas of European reference genomes[END_REF] . At the core of this mission is ensuring the implementation of an inclusive, accessible, and distributed genomic infrastructure that supports the inclusion of all who wish to participate, advances scientific excellence and data sharing best practices, and increases taxonomic, geographic, and habitat representation of sequenced species in a balanced manner.

Embracing diversity in this way brings opportunities for ERGA to build a genomic infrastructure that can be used by the large network of biodiversity researchers and also foster new international and transdiscipline collaborations. 1]. In many cases, researchers completely, or partially, financed their participation in the pilot test. In other cases, partnering sequencing contributed their own grant funds to completely cover or offer heavy discounts for the cost of library preparation, sequence data production and/or assembly services whilst also covering the costs of the scientific personnel within their facilities to participate in the pilot test. In addition, collaborations were fostered with commercial sequencing companies to obtain in-kind contributions that could be used to support those researchers who wished to participate but deserved financial support. All in-kind contributions were shipped to three established ERGA Hubs, two ERGA Library Preparation Hubs (University of Antwerp, Belgium and the Metazoa Phylogenomics Lab at the Institute of Evolutionary Biology (CSIC-UPF) in Barcelona, Spain) and one ERGA Sequencing Hub (University of Florence, Italy).

Building a representative species list

Prior to developing and testing the decentralised infrastructure (Figure 1), we first needed to consider the species that would test it. For this, a nomination form was issued for completion by all ERGA members that were willing to contribute samples for a species. The form collected information on genome properties, vouchering, habitat and sampling, conservation status, permit prerequisites, sample properties, species identification, and sex(https://treeofsex.sanger.ac.uk/) [START_REF] Stöck | A brief review of vertebrate sex evolution with a pledge for integrative research: towards 'sexomics[END_REF] for each suggested species [START_REF] Böhne | Contextualising samples: Supporting reference genomes for European biodiversity through sample and associated metadata collection[END_REF] . To prioritise nominations, a scoring system was applied based on several feasibility criteria: small genome size (<1Gb), an ease of availability, possibility for being freshly collected and flash frozen, >1g of tissue, a well-established nucleic acid extraction protocol, a specimen voucher present, no species identification ambiguity, all necessary permits existing, and no restrictions on export [START_REF] Böhne | Contextualising samples: Supporting reference genomes for European biodiversity through sample and associated metadata collection[END_REF] . ERGA council representatives were given the prioritised species list and asked to select three species per predefined ERGA target category (pollinators, freshwater species and endangered/iconic) from the nominations from members within their country. After nomination form closure, many additional species were nominated by ERGA members. However, only nominations that fulfilled all of the selection criteria, had funding available, and/or were from a country not yet represented were accepted for inclusion into the test.

Overall, from the 33 countries (17 Widening countries (see glossary)) and regions, 98 species were included in the pilot test (Figure 2a). However despite efforts made during the prioritisation process, the dispersion of species selected was not equal across countries predominantly due to the acceptance of additional species after nomination closure (Figure 2b).

Developing a decentralised infrastructure

Nine iterative steps were developed to support the production of a complete reference genomics resource for each of the species included into the pilot project (Figure 1). Step 1: Genome team establishment After a successful nomination, including a species into the ERGA infrastructure was reliant on the creation of a 'genome team'. A genome team is a transdisciplinary group of researchers that have a shared interest in a particular species and assume the shared responsibility of shepherding this species through each of the infrastructure's steps. Each team member has an assigned role (Figure 1, Supplementary Table 2). Further, all teams were strongly encouraged to include both national and international members and all teams were overseen by the "Principle Investigator" and a "Sample Ambassador" who was ideally from the country of origin of the focal species. The role of the sample ambassador was to coordinate the species project, and to ensure the continuous communication across the team members. In total, 98 genome teams were established and each had at least one international team member, 23% having three members, and 26% having >five members (n=93) (Figure 2b). A total of 76 genome team sample ambassadors were comfortable sharing their self-declared sex, (only "male" and "female" were proposed as choices) from this subset, 63 (16%) self-identified as male and 36 (84%) as female (Figure 2b). To ensure compliance with GDPR regulations, no other data was collected to assess representation by other critically important dimensions of diversity e.g., race, ethnicity, religion, sexual orientation or their intersections. Hence, ERGA does not currently have any means to evaluate its inclusiveness beyond sex and it is likely that it suffers the same lack of racial representation and inclusion that characterises European science at large [START_REF] Boytchev | Diversity in German science: researchers push for missing ethnicity data[END_REF] .

Step 2: Pre-sampling requirements Supporting genome team compliance with all relevant ethical and legal customary, local, regional, national, and international obligations was a priority during the infrastructure development process. was mandatory as it codifies the official ERGA standards for how to ethically and legally collect samples, as well as how to responsibly engage all interested parties (see glossary). In addition, educational webinars were used as a researcher capacity-building tool, providing more general information on pertinent topics such as the Nagoya Protocol on Access and Benefit Sharing, and Digital Sequence Information (https://www.youtube.com/@erga-consortium1001).

Step

3: Sampling and metadata acquisition

During sample collection important metadata concerning the species collection event were expected to be documented by the sample collector. To standardise this process a robust metadata schema was developed, using the DToL metadata schema as a foundation [START_REF] Lawniczak | Specimen and sample metadata standards for biodiversity genomics: a proposal from the Darwin Tree of Life project[END_REF] . The tailored ERGA schema, including unique ERGA specimen identifiers as well as ToLID (https://id.tol.sanger.ac.uk/), was codified into a .csv formatted 'manifest' and made publicly available (https://github.com/ERGA-consortium/ERGA-sample-manifest). In tandem, a standard operating procedure document [START_REF] Leonard | ERGA Sample Manifest Standard of Practice[END_REF] was developed to provide details on how to complete all of the 81 validatable manifest fields. Unique to ERGA, fields were developed to mandate important information disclosure e.g., permanent unique identifiers (PUID) associated with ex-situ specimens, permits, and Indigenous rights and interests (TK and BC Labels and Notices) [START_REF] Mc Cartney | Guidelines on the implementation of the Traditional Knowledge and Biocultural Labels and Notices in the European Reference Genome Atlas for biodiversity researchers[END_REF][START_REF] Liggins | Creating space for Indigenous perspectives on access and benefit-sharing: Encouraging researcher use of the Local Contexts Notices[END_REF][START_REF] Mc Cartney | Indigenous peoples and local communities as partners in the sequencing of global eukaryotic biodiversity[END_REF][START_REF] Mc Cartney | Balancing openness with Indigenous data sovereignty: An opportunity to leave no one behind in the journey to sequence all of life[END_REF] .

Overall, samples were collected for 98 species spanning 92 genera, 81 families, 61 orders, 26 classes, and 13 phyla (https://goat.genomehubs.org/projects/ERGA-PIL, Figure 2a). The geographic distribution of samples collected was relatively even, although some countries contributed more species than others (Figure 2b). Altogether 89% of genome teams (n=93) reported >90% confidence level in that they had obtained all permits required with ten Nagoya permits and three CITES [Supplementary Case-study 1] permits being obtained.

Step 4: Sample manifest submission, validation, ex-situ storage Submission and Validation: An accessible and streamlined metadata manifest submission system was implemented to ensure that all ERGA's sample metadata was accurately validated and promptly submitted into the public archive. To achieve this, a user-friendly and highly customised data and metadata brokering system called Collaborative OPen Omics (COPO) (https://wellcomeopenresearch.org/articles/7-279/v1) was used [START_REF] Shaw | COPO: a metadata platform for brokering FAIR data in the life sciences[END_REF] . The COPO submission system validated each manifest submitted against an ERGA provided checklist to standardise and automate entry into the BioSamples public archive. By automating this process it ensured that all species samples collected had a permanent unique identifier (PUID) from BioSamples that can be automatically linked to the associated genomic sequencing data submitted to the European Nucleotide Archive (ENA; https://www.ebi.ac.uk/ena). Additionally, the submission system had the capability to upload permit documentation and supported its immediate transfer to a private and secure location on an internal ERGA data repository (that was built for the purposes of the pilot test) to avoid privacy concerns and data leakages. All documents were subsequently deleted from COPO's internal servers. The internal data repository itself was constructed in partnership with the Barcelona Supercomputing Centre (BSC; https://www.bsc.es/), and was a Nextcloud instance containing a group folder with a tiered storage system, or HSM (see glossary). All ERGA members could request access to the ERGA data repository and upon approval, members were assigned appropriate access privileges depending on their needs (read-, write-, or full file control access). To support repository utilisation, guidelines were developed detailing protocols for data upload/download as well as directory structure, to ensure standardisation, reusability, and interoperability [START_REF] Formenti | Data download from the ERGA Pilot repository[END_REF] .

Ex-situ Storage: We highly recommended that both voucher specimen(s) and cryopreserved specimen(s) be associated with all genomic resources produced during the pilot test. To support this we issued supporting guidance for biobanking and vouchering [START_REF] Cartney | ERGA Pilot Project Official Guidelines[END_REF] . The vouchering best practices developed recommended the deposition of both a physical and digital e-voucher(s)

(high-quality, informative photographs). Through ERGA's SSP Committee, we also supported genome teams in seek of a permanent collection for voucher deposition and a partnership with the LIB Biobank at Museum Koenig (Bonn) (https://bonn.leibniz-lib.de/en/biobank) was established to support the deposition of cryopreserved samples for those without access to a local biobank. Samples biobanked in LIB were made publicly visible via the international biodiversity biobanking portal (GGBN.org). Although not a mandatory requirement, voucher specimens were provided for 67% of the species (19% digital, 40% physical, and 40% had both physical and digital) and deposited in museum collections across 23 countries (Figure 2c). Of the specimens, 45% had an associated cryopreserved sample that were stored in 34 biobanks in 22 countries (Figure 2c). All 98 of genome teams successfully completed, validated and uploaded their metadata publicly to BioSamples through the COPO system and manifest submissions are publicly available through the ERGA Data Portal (https://portal.erga-biodiversity.eu/) that provides intuitive search and direct links to all of the data held in the public archives (See Step

Communication and Coordination Section).

6: Sequencing Strategy

A key component and strength of the decentralised infrastructure was the intentional distribution of sequence data production across partnering European sequencing facilities. To initialise these partnerships, a sequencing platform landscape assessment was conducted across all of the countries that ERGA had council representation. This effort assessed the quantity, distribution, and diversity of the sequencing platforms available across Europe and specifically examined their capability to produce long read (PacBio HiFi reads/ONT reads /IsoSeq reads), and short read (Hi-C/Omni-C/RNA-Seq/PCR-free Illumina) sequencing data. This mapping indicated an uneven distribution of sequencing platforms across Europe, and so we decided that any sequencing facility with a platform to produce long read sequencing data could be an ERGA partner. We took this long read data-type agnostic approach to maximise geographic breadth and increase accessibility but also to reduce shipping costs and the likelihood of customs issues. and additional data was generated by Novogene for four species from the Netherlands and Hungary. 27 species were sequenced using a ONT platform, 75 using the PacBio Sequel II platform, and four by both platforms. For scaffolding and curation purposes, proximity ligation sequencing was highly recommended. A total of 76 species had some form of proximity ligation sequencing conducted, 47 species with Arima-Hi-C (Arima Genomics), 24 species with Dovetail Omni-C® (Dovetail Genomics), and five with Proximo (Phase Genomics) [Figure 3a].

Regardless of the partnering sequencing facility utilised or species being sequenced, the facilities were expected to produce sufficient data to reach at minimum EBP recommendations [START_REF] Lawniczak | Standards recommendations for the Earth BioGenome Project[END_REF] . An ERGA Sequencing Hub was also established at the University of Florence (Italy) Genomics Core to support the sequencing of the 99 libraries prepared by the ERGA Library Preparation Hubs (Supplementary Table 3,4). Upon sequencing data generation, both genomic and transcriptomic data were shared with the genome teams through the internal ERGA data repository.

Step

7: Genome Assembly and Annotation

Assembly: A requirement for becoming an ERGA reference genome was that the genome assembly reached, at minimum, the EBP standard for assembly quality [START_REF] Lawniczak | Standards recommendations for the Earth BioGenome Project[END_REF] . To ensure the infrastructure supported the production of genomic references to this standard, we developed assembly guidelines with workflows tailored for both ONT and HiFi based genome assemblies [START_REF] Mc Cartney | ERGA Pilot Project assembly recommendations[END_REF] .

The use of these workflows was not mandatory, and any assembly workflow would be accepted if the resulting assembly met the appropriate assembly quality [START_REF] Lawniczak | Standards recommendations for the Earth BioGenome Project[END_REF] . To streamline the assessment and validate all ERGA genomic references, we established a stepwise procedure of 1) QC metrics assessment, 2) internal peer-review, and 3) manual curation. On completion of a draft assembly, each genome team reported a set of standard QC metrics [START_REF] Mc Cartney | ERGA Pilot Project post assembly quality control standards[END_REF] that include a contaminant assessment, K-mer metrics, Hi-C map and graph production, gene prediction analyses, and a set of summary statistics. After this, the assembly and the associated metrics underwent an internal round of peer-review from assembly experts (ERGA Sequencing and Assembly Committee).

After feedback integration, each genome team uploaded the pre-curation assembly to the internal ERGA data repository along with details of the assembly construction (https://gitlab.com/wtsi-grit/documentation/-/blob/main/yaml_format.md) and each team was provided with the opportunity to submit their reference genome to an internal panel of expert curators who conducted a final manual curation [START_REF] Howe | Significantly improving the quality of genome assemblies through curation[END_REF] .

Due to the decentralised nature of the infrastructure, all 98 species progressed through the steps at different rates, depending on the number and complexity of permits From the 30 reference genome assemblies with a 'Curated' or 'Pre-curation' status, we found 14 cases where the assemblies do not meet the quality standard 6.C.Q40 EBP standard criteria (See glossary and Supplementary Table 6, Figure 4a). For instance, Argentina silus (fArgSil1) and Knipowitschia panizzae (fKniPan1) have scaffold N50 values that meet the minimum requirement, indicating successful Hi-C scaffolding, however both fall short in terms of contig contiguity (N50 < 1 Mbp). In addition, those two pre-curation assemblies contained many small scaffolds, which increased the total number and translated to higher values of Scaffold L95.

Notably, Phaeosaccion multiseriatum (uoPhaMult1) meets the contig N50 but does not meet the scaffold N50 metric (N50 > 10 Mbp). In the cases of Spongipellis delectans (gfSpoDele1) and Phakellia ventilabrum (odPhaVent1), they reached a chromosomal scale N50 scaffolding (6.C.Q40), but not the N50 threshold used as a proxy in Figure 4a (6.7.Q40), a minimum criteria set for vertebrates but that cannot be applied to taxa with chromosome length N50 less than 10

Mbp.

We found differences between HiFi-and ONT-based assemblies in the K-mer-based analyses, for example the average quality value (QV) for HiFi-based assemblies was 61, while for ONT-based it was 38. From these ONT assemblies, five species showed values below the recommended 40, which corresponds to an error rate > 0.01% (Figure 4b). It should be noted that in the case of ONT-based assemblies K-mers were derived from orthogonal Illumina reads from the same individual, whereas in the case of Hifi assemblies the K-mers were derived from the same data used to generate the genome assembly, likely inflating QV estimation due to data-interdependence. Further research is warranted on how to mitigate this issue. Recent unpublished results from within ERGA suggest that assembly of newer ONT data (Kit14, Q20+) consistently generates assemblies with QV>40, perhaps side-stepping this issue. Eleven species showed K-mer completeness below 90%, with four being below 80% and one also lower than 70%. Out of these, six belonged to ONT-based assemblies while eight had curated status (Figure 4b). A caveat to K-mer completeness is that pseudohaploid assemblies (the typical output of ONT-based assemblies) of heterozygous genomes tend to have lower K-mer completeness. This highlights the need for continued development of diploid assembly strategies to ensure high K-mer completeness.

Five genomes exceeded the recommended metric Gaps/Gbp [START_REF] Lawniczak | Specimen and sample metadata standards for biodiversity genomics: a proposal from the Darwin Tree of Life project[END_REF] as they all had >1,000 remaining (Argentina silus (fArgSil1), Knipowitschia panizzae (fKniPan1), Ammodytes marinus (fAmmMar1), Salvelinus alpinus (fSalAlp1) and Vipera ursinii rakosiensis (rVipUrs1)). Despite this, for all the completed assemblies, Ns accounted for less than 0.05% of the genome, with the exception of Mustela lutreola (mMusLut1). For this genome assembly, which has yet to undergo final curation (the only large ONT-based assembly evaluated >2 Gbp), 0.55% of its sequence was composed of Ns (Figure 4b).

Besides EBP metrics, when estimating completeness using single-copy orthologs, Phakellia ventilabrum (odPhaVent1) and Gordionus montsenyensis (tfGorSpeb1) assemblies had lower values than recommended. tfGorSpeb1 is one of the first of its phylum to be sequenced [START_REF] Cunha | Rampant loss of universal metazoan genes revealed by a chromosome-level genome assembly of the parasitic Nematomorpha[END_REF] , and so is therefore underrepresented in the BUSCO database (Figure 4c) [START_REF] Eleftheriadi | The genome sequence of the Montseny horsehair worm, Gordionus montsenyensis sp. nov., a key resource to investigate Ecdysozoa evolution[END_REF] . Two species, Trifolium dubium (drTriDubi1) and the Salvelinus alpinus (fSalAlp1), both have higher ploidy levels (tetraploid and partial tetraploid, respectively) and had much higher BUSCO duplicate values than the recommended 5% (Supplementary Table 1).

Genome annotation: For the pilot test, the sample collection process for the included species was ideally conducted to facilitate simultaneous genomic and transcriptomic data production.

After data deposition to the ERGA data repository, we designed the infrastructure to have the flexibility necessary for each genome team to decide whether the annotation will be conducted i) by the genome team or sequencing facility, ii) with supporting expertise from the internal ERGA community, iii) or wait until the assembly and annotation data is uploaded to ENA where a gold standard annotation will be generated by Ensembl 38 . Although annotation was not mandatory, we produced sequencing data to support annotation data for 81 species (66 with RNA-Seq data, and 15 IsoSeq data). For those species with IsoSeq data generated, 13 also obtained RNA-Seq data.

For the 30 genome teams spanning 16 countries that lacked the resources necessary to generate annotation data, we ensured that samples were shipped to a dedicated ERGA Library Preparation Hub. Here, 76 libraries were prepared and shipped to the ERGA Sequencing Hub for data production. In some groups annotation is still underway, but seven genome teams reported that they have a finalised annotation.

Step 8: Data Analysis

Reference genomes can support many downstream analyses, including population genomics, phylogenomics, functional genomics and comparative genomics [START_REF] Formenti | The era of reference genomes in conservation genomics[END_REF] . Following the assembly and annotation of the newly-built reference genomes, we offered assistance through the ERGA Data

Analysis Committee to genome teams by suggesting and supporting avenues of downstream data analyses that could be followed to answer their biological questions of interest. In addition, we connected genome teams with relevant ERGA members that may be able to assist or mentor downstream biological exploration, sparking new collaboration and working groups. As many of the 98 species participating had not yet reached the point of data analysis, we conducted a brief survey to better understand what downstream analysis was planned across the genome teams participating (Extended Data Figure 5). For 59.8% of genome teams, the downstream analyses planned would not have been possible without the reference genome, and 70.7% reported that their planned analyses will be significantly improved by the availability of the reference genome, reinforcing that the biodiversity genomics community is in great need of genomic resources of this kind and quality. Results across the genome teams indicate that the most common type of downstream genomic analyses planned was population genomic based analyses (37.7%) for assessments of population history, structure and status of endangered and endemic species (e.g. demography, inbreeding, hybridization, and association with morphological or environmental factors). Comparative genomics was also a common analysis type across genome teams (27%) who seek to examine relevant evolutionary processes across species (e.g. trait-associated gene family evolution analysis, repeat content evolution, synteny, inversions, tRNA evolution).

Overall, the results of this survey show that the availability of reference genomes are considered a key tool for downstream applications.

Step

9: Upload to Public Archives

To follow the principles of Open Access to Scientific Publications and Research Data Guidelines of the European Research Council under Horizon 2020, ERGA adopted the data policy of "as open as possible but as closed as necessary". To support this policy, we developed an ERGA Pilot Project Data Sharing and Management Policy 39 specifically seeking to balance data openness with respecting the needs of diverse ERGA genome teams. The policy itself codified that all reference genome, annotation and raw sequence data was expected to be uploaded upon generation to the internal ERGA data repository, ensuring its immediate accessibility to the ERGA community. The policy also grants each genome team the ability to place an embargo on public upload of ERGA data into the public archives until the first publication but no longer than two years after data release. Laid clear in the policy is the provisions for fair and rightful attribution in all associated publications.

Communication and Coordination

The nature of the infrastructure constructed required streamlined communication between ERGA genome teams and partnering sequencing facilities spanning large geographic distances.

Training and Knowledge Transfer

Investing in building competency is important if ERGA is to provide scientists across disciplines, experience levels, demographic sectors of society, and geographies with equitable opportunities to leverage and benefit from the use of the enormous volume of data expected to be generated through ERGA, but also other large biodiversity genomics initiatives including and especially those in parts of the world where economic opportunities are much more limited. However, a significant gap remains in expertise between countries due to the diverse nature of resource availability, genomic research capacity and capability, and access to state-of-the-art training [Box 2]. To increase the accessibility and stimulate the use of existing infrastructure within ERGA across all the infrastructure steps, efforts were made to share expertise through conference participation, webinar organisation and through organising hands-on training workshop opportunities. For instance, many ERGA members participated in a BioHackathon to integrate new genome assembly methods into an openly accessible Galaxy pipeline and worked on the development of robust user guidance [START_REF] Larivière | Scalable, accessible, and reproducible reference genome assembly and evaluation in Galaxy[END_REF] . In addition, we organised a virtual workshop entitled "Building high-quality reference genome assemblies of eukaryotes" as part of the European Conference in Computational Biology 2022 [START_REF] Capella-Gutierrez | the 21st European Conference on Computational Biology[END_REF] and now freely available online to further educate researchers in best practices for genome assembly. We also organised a webinar on 'Access and Benefit-Sharing' with the National Focal Points across Europe to help genome team sample ambassadors to understand their Nagoya permitting obligations during the sample collection stage of the project and organised an online workshop on structural genome annotation with BRAKER & TSEBRA.

An online workshop was also organised to train pilot genome teams to identify the external actors (international, national, and local levels) involved in their reference genome project.

During this training, we conducted a stakeholder and rightsholder, herein interested parties, mapping exercise, and examined sample ambassador perceptions of how to interact with interested parties across high and low GBARD (government budget allocations for R&D) countries. The results indicated that researchers did not categorise their project's interested parties differently (X 2 (3, (153-130)) = 5.66, p = 0.12) [Extended Data Figure 6] depending on whether they were situated in a low or high GBARD country. However, there does appear to be a tendency in the 'Consult' category (df = 1, p = 0.08), suggesting that researchers located in low GBARD countries may place a higher value on the involvement and collaboration of interested parties as opposed to those located in high GBARD countries [Extended Data Figure 6]. Microorganisms are excellent objects for genome sequencing and bioinformatics teaching due to their small genome size (making it possible to try many workflows and sets of parameters).

The genus Debaryomyces comprises species of extremophilic yeasts, some of which support plant health by modulating pathogen invasion [START_REF] Boekhout | Trends in yeast diversity discovery[END_REF][START_REF] Medina-Córdova | Biocontrol activity of the marine yeast Debaryomyces hansenii against phytopathogenic fungi and its ability to inhibit mycotoxins production in maize grain (Zea mays L.)[END_REF] . A high-quality reference genome will help study the impacts of radiation on this genome and elucidate the adaptive potential of host-microbe interactions. The yeast was isolated from a silver birch tree in the Red Forest, one of the most radioactive areas in the Chernobyl Exclusion Zone (CEZ) in Ukraine [START_REF] Mousseau | The Biology of Chernobyl[END_REF] .

Anthropogenic stresses caused by radionuclide contamination can adversely affect organism health through genotoxicity [START_REF] Lourenço | Radioactively contaminated areas: Bioindicator species and biomarkers of effect in an early warning scheme for a preliminary risk assessment[END_REF][START_REF] Kesäniemi | Exposure to environmental radionuclides associates with tissue-specific impacts on telomerase expression and telomere length[END_REF] . Although symbiotic interactions with endophytic microorganisms can facilitate a host's capacity to adapt and persist under such environmental stress [START_REF] Hardoim | The Hidden World within Plants: Ecological and Evolutionary Considerations for Defining Functioning of Microbial Endophytes[END_REF] , little is known about radiation exposure's impact on these endophytic interactions.

ONT genomic and cDNA sequencing was performed during the course, then the data were assembled with Flye [START_REF] Kolmogorov | Assembly of long, error-prone reads using repeat graphs[END_REF] and annotated with BRAKER [START_REF] Hoff | Whole-Genome Annotation with BRAKER[END_REF] by the course participants. The pedagogy of the EMBO course effectively combined hands-on research training with the necessary theoretical framing to support active learning of participants. Feedback by course participants was extremely positive, and as a result a second EMBO-funded Practical Course will be organised by the same team in 2024 (this time in Valencia, Spain). In addition to providing participants with a realistic insight into the research process, the training also created a suite of high-quality publicly available genomic resources for the yeast species sequence that will be directly useful to the sample provider's ongoing research, but also to potentially many more researchers. This successful teaching-through-research model will inform future ERGA training and capacity-building activities at locations across Europe and beyond.

Decentralisation Challenges

From the outset of the pilot test, we realised that the decentralised infrastructure built would have huge implications on who was included, had access to, and benefited from the production of genomic resources into the future. Collecting, identifying, storing, and cold-chain shipping of specimens as well as producing, analysing, and storing sequencing data is expensive, requiring ex-situ long term storage facilities, sequencing equipment, laboratory access, a skilled workforce, and significant computational resources. The resources to create genomic resources are neither evenly distributed across the globe, nor across Europe. A key goal of the pilot test was to identify how the existing inequitable structures and systems would manifest whilst building a distributed genomic infrastructure. Intertwining and embedding justice, equity, diversity and inclusion into the scientific mission was considered essential if a decentralised, accessible, and scalable infrastructure was to be achieved that truly supported the production of complete reference genomics resources for all species, and was accessible to all researchers.

Overall, the main objectives we set out for the decentralised infrastructure were achieved as it: i) supported the ethical and legal production of high quality genomic resources; ii) created a network of the researchers and institutions engaged in the field of biodiversity genomics; iii) leveraged the network's existing institutional capacities and capabilities; and iv) harnessed the diverse expertise of the ERGA memberbase and streamlined, as much as possible, equitable participation. However, the decentralised approach also revealed a number of challenges that need to be addressed by ERGA moving forward.

1) Phylogenetic representativeness and sampling bias

Bias was found in the representation of countries (Figure 2), distribution of species sampled per country (even when population size is considered [Extended Data Figure 7]) and species distribution across the phylogenetic tree. Generally, non-Widening countries were more strongly represented than Widening countries and certain branches of the tree of life were overrepresented (Mammalia, Aves, Actinopterygii and Magnoliopsida), whilst others (Insecta, Amphibia Mollusca, Annelida, Fungi and most protist groups) were underrepresented. Feasibility was another obstacle. First, the production of long-read and -range sequencing on a species sample requires a significant amount of HMW DNA per 1 Gb of genome size and so small-sized species or species with very large genomes remain an unsolved challenge [Supplementary Case-study 2]. Second, for some taxa and species, co-purification of secondary compounds resulted in sequencing chemistry interferences. Finally, ideal tissue preservation was not always possible due to sampling at remote destinations or from scientific collections where samples were preserved a long time ago [Supplementary Case-study 6].

Moving forward, a more robust species prioritisation process could ensure that all species are assessed using clearly specified criteria with a scoring system that is responsive to the needs of both equity deserving countries (see glossary) and underrepresented taxa. For example, species from higher taxonomic groups without reference genomes could be prioritised over those more resource abundant groups or Widening countries could be prioritised over non-Widening countries. A more robust species prioritisation process could also facilitate knowledge transfer and serve as a seed for national investments in biodiversity genomics. Tackling these challenges will require a greater investment in research and development as well as highly-skilled personnel, additionally researchers may need incentives to prioritise the interest of species or taxa that remain underrepresented in public databases.

2) Engagement

Effective engagement for the pilot test was a challenge for many reasons such as engagement being a constraint rather than an opportunity due to resource and time limitations, and a lack of training and awareness. Although a virtual workshop was provided during the pilot test to train researchers on 1) the significance of interested party engagement and 2) the skills to identify, map, and comprehend the needs of potential interested parties, it remained a challenge to transition researcher focus from reference genomes to the practical applications of genomics more broadly. Additionally, although the infrastructure was designed to recognise and include the rights and interests of Indigenous Peoples and Local Communities (TK and BC Labels and Notices, supporting guidelines for researcher implementation, and an "Open to Collaborate'' Notice on the ERGA website), researchers require more training on why and how to proactively engage and establish sustainable partnerships with Indigenous Peoples and Local Communities.

Overall, more training is needed for interested party identification, mapping, tailored engagement (varying interests and cultural perspectives), and communication. To address this, a comprehensive framework that encompasses targeted communication strategies, tailored dissemination channels, and proactive exploitation of research findings would be useful. This plan, if developed, could ensure that all interested parties receive timely and relevant information, fostering broader awareness, understanding, and utilisation of the results generated by biodiversity genomics research. Supporting ERGA members in this way could empower researchers to get more involved at the interface between biodiversity genomics research and biodiversity policy [Supplementary Case-study 4].

3) Decentralising reference production and reproducibility

During the pilot test the reference genomics resources were produced across diverse and transdisciplinary research groups, institutes and countries. This diversity resulted in variances in accessibility, capacity and capability in sequencing technologies, computation, and software but also across different taxa. The overrepresentation of pilot sequencing facility partners located in Western Europe compared to Eastern Europe demonstrates such disparity. Furthermore, the data agnostic approach taken led to challenges in standardising assembly, annotation and curation protocols, workflows and procedures across the project. For instance, a blanket adoption of the VGP pipeline for diploid genomes based on PacBio HiFi and Hi-C sequencing (https://gxy.io/GTN:T00039; https://workflowhub.eu/workflows/325?version=1) was not appropriate as this approach would not cater for polyploid genomes nor those assemblies produced that were ONT-based. A further challenge was the provision of a centralised system for the storage and transfer of raw and final genomic and transcriptomic data. This was particularly challenging in cases where data production spanned two or more locations (e.g., PacBio sequenced at one site, Hi-C at a second, and RNA at a third) and was subsequently assembled at another site. While the Nextcloud instance created by BSC was an elegant solution for transferring vast quantities of data between parties, it required a vast amount of personnel hours to manage, in addition to its baseline system-wide maintenance requirements.

Moving forward, a key goal for ERGA is the production of standardised and reusable pipelines that are: responsive to all sequencing "recipes" (PacBio, ONT, or other future technologies);

written for Galaxy, Snakemake, and/or Nextflow workflow managers; made publicly available (https://github.com/ERGA-consortium/pipelines); and are actively maintained by the ERGA community with regular scheduled and versioned updates. It would also be beneficial to diversify the availability of sequencing instruments to allow for more instances where sequencing and assembly can be produced concurrently at the same location, reducing the need for transferring files that can reach up to 1Tb in size.

4) Genome annotation

The first hurdle in annotation is the availability of sufficient evidence (transcriptomic and protein sequence data) from focal species, databases and predictive models of repeats. Secondly, even with appropriate data, the most accurate genome annotation pipelines require advanced skills to both install and run which reduces their accessibility and ultimately their utility. Finally, robust annotation quality assessment tools are lacking particularly for species with underrepresented genomic resources, for instance gene content assessment tools such as BUSCO [START_REF] Manni | BUSCO Update: Novel and Streamlined Workflows along with Broader and Deeper Phylogenetic Coverage for Scoring of Eukaryotic, Prokaryotic, and Viral Genomes[END_REF] remain unable to account for species within taxonomic groups that have incomplete gene sets available leading to unreliable quality assessments.

Obtaining, and equitably distributing, financial resources will be required to equip researchers, labs, and regions for annotation in a manner that responds to their varying resource realities.

Additionally, the development of more easily installable and reproducible pipelines are needed, and thankfully some new tools are now emerging with this in mind [START_REF] Gabriel | BRAKER3: Fully Automated Genome Annotation Using RNA-Seq and Protein Evidence with GeneMark-ETP, AUGUSTUS and TSEBRA[END_REF] . Standardised and streamlined annotation pipelines are needed for consistency which is crucial for many analyses such as comparative genomics as it can facilitate more confident comparisons. Finally, sequencing more underrepresented genomes will help improve quality assessment tools. Filling in phylogenetic gaps will provide more opportunities for comparisons among taxa but also to develop better models for gene predictions. Despite these challenges, it is important that genomes are annotated. Many downstream analyses are based solely on the predicted genes from the annotation, and incomplete or incorrect results will negatively impact studies of both short-term and broad evolutionary processes.

5) Ethical and legal compliance

ERGA is an international initiative and so safeguarding production of only ethical and legal reference genomes was a complex endeavour. Decentralisation of the infrastructure resulted in many species samples being transported across national and regional jurisdictions as well as in and out of the European Union, creating an ethical and legal compliance tribulation.

Additionally, depending on the species in question, the legal landscape may differ drastically e.g., CBD [START_REF]Convention on Biological Diversity[END_REF] , CITES [START_REF] Cites | Text of the Convention on International Trade in Endangered Species of Wild Fauna and Flora: Signed March 3, 1973[END_REF] , ITPGRFA 55 , UNCLOS [START_REF] Bassiouni | Convention on the Law of the Sea[END_REF] etc. Understanding legislation can be complex and difficult especially for researchers who do not have formal legal training, usually lack legal support within their institution, and often do not have the time or resources to acquire either. This created uncertainty amongst many researchers, especially those navigating this for the first time

[Supplementary Case-Study 1].

To add to this uncertainty, the pilot test coincided with international discussions on the fair and equitable sharing of benefits from the access and use of digital sequence information (i.e., genomic sequences) under the Nagoya Protocol adding increased uncertainty surrounding the legal compliance landscape [START_REF] Scholz | Multilateral benefit-sharing from digital sequence information will support both science and biodiversity conservation[END_REF] . Additionally, although researchers were supplied with documentation and infrastructural support to aid ethical and legal compliance, the pilot test had no means to monitor compliance.

Moving forward addressing the ethical, legal and social implications of ERGA will require professionalisation through a dedicated funding stream. Funded positions will attract trained personnel with the necessary experience needed to navigate complex permitting issues and compliance monitoring. Additionally, a greater effort needs to be made on training ERGA members on the importance of ELSI in biodiversity genomics research.

6) Training and knowledge transfer

Financial resources are not equally distributed among countries, institutions or researchers, leading to limited access to crucial state-of-the-art training, resulting in significant disparities in terms of the expertise required to access and utilise these resources. Given the economic privilege that even the least wealthy EU countries have when compared to countries in the Global South, it clear that access to funding for mobility is a huge barrier globally. Throughout the pilot test, several trainings were held and guidelines developed to enhance the user-friendliness of the infrastructure as well as to streamline its use; however there was no clear long-term strategy for training and knowledge transfer.

To develop a genomics curriculum that is responsive to the needs of researchers and trainees, and promote the long-term building of capacity within these countries, an investment into a long-term strategy will be required. For instance, a publicly available knowledge transfer platform could be created to provide ERGA members with resources and trainings relating to each step of reference genome production, but could also provide links to complementary initiative resources e.g., EBP, Elixir (https://elixir-europe.org/), Galaxy (https://usegalaxy.org/), DSI Network (https://www.dsiscientificnetwork.org/), gBIKE (https://g-bikegenetics.eu/en), CETAF (https://cetaf.org/) etc. Such a platform could also provide a space for the sharing of relevant biodiversity genomics educational materials that could further aid collaborations between researchers who are shaping the future of biodiversity genomics curricula development globally.

7) Building a more inclusive, diverse and equitable infrastructure

Building a truly inclusive, diverse and equitable infrastructure for biodiversity genomics faces structural constraints. They are mainly twofold: first, lack of equity for and inclusion of minorities in science within the countries of Europe As ERGA progresses, the consortium should prioritise the collection of applicable demographic data. Moreover, outreach activities should be conducted to explicitly recruit researchers from sectors of the population that are underrepresented in science. To really address the biodiversity crisis in a meaningful way, it will be important for ERGA to expand its reach globally. Afterall, most biodiversity by far resides not in Europe but in the Global South. Much commitment and ingenuity will be required to overcome the effects on biodiversity genomics of the equity gap that separates Europe as a block from many countries in the Global South. It will be a challenge to overcome the boundaries and constraints often dictated by scientific funding, but it is a challenge that must be overcome on the road towards a sustainable future. Through harnessing the power of its positioning in the EBP, ERGA should make efforts to become more integrated with other ongoing and related initiatives in neighbouring regions, e.g., Africa BioGenome Project [START_REF] Ebenezer | Africa: sequence 100,000 species to safeguard biodiversity[END_REF] .

Future Directions

The decentralised approach taken by ERGA through the pilot test illustrates the huge potential of the consortium to become a model for equitable and inclusive biodiversity genomics in the future. The power of such an approach was evident through the momentum it built across its participants. Not only did the pilot test successfully unite an international community of biodiversity researchers, but it also stimulated communities of researchers within the same country to combine and consolidate efforts under the ERGA umbrella e.g., DeERGA and Portugal BioGenome [START_REF] Marques | Building a Portuguese Coalition for Biodiversity Genomics[END_REF] . Additionally, it allowed participating researchers to apply the lessons learned from the test to build localised infrastructures that would remain interoperable with partners across Europe, e.g., ATLASea.

A key aim for testing the approach was making visible the challenges and issues that would manifest whilst working at an international level, and at scale and working to improve and build upon these learnings as the consortium moves forward.

Glossary

Biodiversity genomics -The application of genomic methods to research biodiversity.

BUSCO -A bioinformatic method (Benchmarking Universal Single-Copy Orthologues) used to estimate the completeness of the coding fraction of an organism's genome based on the proportion of (lineage specific) single copy orthologous genes that are found in a genome assembly [START_REF] Manni | BUSCO Update: Novel and Streamlined Workflows along with Broader and Deeper Phylogenetic Coverage for Scoring of Eukaryotic, Prokaryotic, and Viral Genomes[END_REF] .

INSDC -International Nucleotide Sequence Database Collaboration (https://www.insdc.org/) is an initiative between the DDBJ, EMBL-EBI and NCBI that together act as a global repository of sequence data and associated metadata, and provide tools and services that allow access to genomic resources.

Reference genome -An accepted standard representation of an organism's DNA sequence. High-quality reference genomes typically have high completeness (chromosome-level with few gaps in sequence), few errors, and are annotated and accessible. A reference genome serves as a tool for alignment-based analyses, such as variant calling or RNAseq, and has many other applications, for example, phylogenetics and evolutionary relationships, identification of genes and variants, functional analysis and comparative genomics. Reference genomes referred to as "drafts" are those that are under active construction and refinement, and not yet finalised through manual curation.

Genomic resource -A genomic resource, for the purpose of this manuscript, refers to a reference genome, genome annotation, voucher specimen, cryopreserved sample and comprehensive metadata.

FAIR Principles -A set of principles to guide appropriate management and curation of scientific data (https://www.go-fair.org/fair-principles/) that emphasise data accessibility and use by ensuring that data are Findable, Accessible, Interoperable, and Reusable. Due to the increasing amount of scientific data being reposited, FAIR guidelines promote a data format that is amenable to automated computational access of data by stakeholders [START_REF] Wilkinson | The FAIR Guiding Principles for scientific data management and stewardship[END_REF] .

CARE Principles -

The CARE principles for Indigenous data governance (https://www.gida-global.org/care) provide a governance framework that supports the recognition of rights and interests Indigenous Peoples' to their physical and digital data as well as their Indigenous Knowledges [START_REF] Carroll | The CARE principles for indigenous data governance[END_REF] .

Metadata -A collection of data that provides contextual information about multiple characteristics of other, corresponding data.

Voucher -A voucher specimen is a permanently preserved object (either whole or in part, and/or physical or digital) of an identified organism (verified by a recognised expert) and which is deposited in an accessible facility or database. A voucher provides physical evidence about any specimen's taxonomic identity [START_REF] Buckner | The critical importance of vouchers in genomics[END_REF] . Voucher deposition is a best practice for conducting biodiversity genomics research.

(Genome) annotation -The process of identifying the functions of different pieces of a genome. This includes genes that code for proteins and non coding features (e.g. intron-exon structure of protein coding genes, promotors, transposable elements). Typically performed using computational methods, followed by manual curation.

(Genome) completeness -An estimate of how well a reference genome represents the complete sequence of the target organism. A complete genome should equal the haploid genome size of the target, but may be defined when 'all chromosomes are gapless and have no runs of 10 or more ambiguous bases, there are no unplaced or unlocalized scaffolds, and all expected chromosomes are present.' (https://www.ncbi.nlm.nih.gov/assembly/). There are different approaches to estimate the completeness, like BUSCO, analysing K-mers, etc.

Library -DNA, cDNA, or RNA that has been prepared for NGS within (usually) a specific size range and containing adapters, which are designed to be appropriate for (a) specific sequencing platform(s).

(Genome) assembly -A genome assembly is a representation of an organism's genome that is made using computer programs to turn (assemble) raw sequence data into longer, continuous sequences.

PUID -A permanent unique identifier is a unique label for an object that does not change, such as the Digital Object Identifier (DOI) attached with a scientific publication.

ENA -

The European Nucleotide Archive (https://www.ebi.ac.uk/ena) is a global repository for sequence data and provides resources that support management and access to sequence data.

Horizon Europe regulation the Widening countries are: Bulgaria, Croatia, Cyprus, Czech republic, Estonia, Greece, Hungary, Latvia, Lithuania, Malta, Poland, Portugal, Romania, Slovakia, Slovenia and all associated countries with equivalent characteristics in terms of R&I performance and the Outermost Regions.

Figure 1 :

 1 Figure 1: Establishing an inclusive, accessible, distributed and pan-European genomic infrastructure that could support the streamlined and scalable production of genomic resources for all European species.

Figure 2 :

 2 Figure 2: Sample, country and partnering institution distribution across Europe. a) Taxonomic

Figure 3 :

 3 Figure 3: Pilot test data production per species progression. a) total data production progress across all 98 species included, noting that data not planned/required for 12 species for proximity ligation, and 15 species for annotation data. b) species distribution of species with genome assemblies available, both draft and curated assemblies are shown here. The data-type distribution for these species is also supplied. See Extended Data Figure 3 for complete species tree.

Figure 4 :

 4 Figure 4: Quality control and status of the 38 genome assemblies evaluated. a) Genome assemblies are represented according to their Scaffold N50 (y-axis, log 10 ) and number of the longest scaffolds that comprise at least 95% of the assembly (x-axis, log 2 ). Bubble size is

Box 2 :

 2 Opportunities for Training & Knowledge TransferDuring an EMBO Practical Course 'Hands-on course in genome sequencing, assembly and downstream analyses' held at the Université libre de Bruxelles (ULB), Belgium (https://meetings.embo.org/event/22-gen-seq-analysis), the organisers chose to use the endophytic yeast Debaromyces sp. RF-E1 (13 Mb) for sequencing during the course.

Box 1: The European Reference Genome Atlas

	As	the	European	node	of	the	Earth	BioGenome	Project	(EBP;

  The organisational structure of ERGA currently comprises the governing body of the Council of Country/Regional Representatives, with actions developed and implemented by the Executive Board and nine expert Committees, with participation from the large network of members (https://www.erga-biodiversity.eu/). With over 750 members spanning 38 countries, one regional ERGA affiliated project, and 234 institutions, ERGA is currently the largest initiative of its kind in the world. ERGA membership is open to all who wish to engage in the sequencing of European eukaryotes, foster new collaborations in and beyond Europe, and learn about the most up to date technologies for generating reference genomes for species (individuals interested in becoming a member can register through the ERGA website).

The first step towards decentralisation was to create a pan-European network of existing sequencing centres, biobanks, and museum collections that were willing to participate and provide diverse support options for sample storage, wet-lab preparation, sequencing, and data handling and storage. The second step was to obtain adequate funding to support the development and implementation of the infrastructure. Here, no central source of funding was available and so the majority of funds were acquired through the grassroots efforts of individual ERGA members contributing to the pilot test as well as a plethora of partnering institutions

[Supplementary Table

[Supplementary Case-study 1], difficulty of sample collection [Supplementary Case-study 2], need

for sample specific protocol development [Supplementary Case-study 3], partnering sequencing facility capacity, and assembly complexity.

Figure 3a highlights the current status of each species that has an assembly generated and shows that 13 complete and curated reference genomes have been generated (11 of which can be found in the INSDC), a further 17 are complete but require curation, and 8 are in non-final draft stage.

  [START_REF] Boytchev | Diversity in German science: researchers push for missing ethnicity data[END_REF][START_REF] Tseng | Strategies and support for Black, Indigenous, and people of colour in ecology and evolutionary biology[END_REF] ; second, extreme economic and political inequity between Europe and countries in the Global South[START_REF] Hickel | Imperialist appropriation in the world economy: Drain from the global South through unequal exchange, 1990-2015[END_REF] . For the pilot test, no data was collected on race, ethnicity, religion, sexual orientation, disability, career-level or the intersections of these with gender and with each other. This data deficiency made it impossible to critically evaluate the consortium in terms of inclusiveness. Some preliminary data generated in regards to sex suggested that by allowing genome teams to organically form it resulted in sex imbalances. Hence, there is a high likelihood that this also resulted in an underrepresentation of many other minoritised groups[START_REF] Boytchev | Diversity in German science: researchers push for missing ethnicity data[END_REF] , a known trend across European science[START_REF] Boytchev | Diversity in German science: researchers push for missing ethnicity data[END_REF] . The second constraint arises from a pressure to confine a biodiversity genomics consortium to the political boundary of Europe and the nation states within. Europe, and the nations within it, are not naturally occuring units of biodiversity. In fact Europe is part of a much wider biogeographical realm (the Palearctic) that includes large parts of Africa and Asia[START_REF] Holt | An update of Wallace's zoogeographic regions of the world[END_REF]

	( https://www.britannica.com/science/biogeographic-region) .

Knowledge and Biocultural Label and Notice development:

  funded by FCT and AKDN through the project CVAgrobiodiversity/333111699 and (LEAF/ISA) UID/AGR/04129/2020; Akira Peters (Bezhin Rosko, Santec, France) isolated from nature and donated the strain of Phaeosaccion multiseriatum; We would finally like to thank Loriano Ballarin and Fabio Gasparini, Università di Padova, Dipartimento di Biologia, for contributing to the design of the Pilot project of two Botryllus species. The implementation of the Labels and Notices and the development of the supporting guidance documentation was funded through the European Open Science Cloud (RDA_OSF_EOSC-228) in partnership with the Global Indigenous Data Alliance, RDA and Local Contexts.Nanotechnol. 4, 265-270 (2009). 66. Loman, N. J., Quick, J. & Simpson, J. T. A complete bacterial genome assembled de novo using only nanopore sequencing data. Nat. Methods 12, 733-735 (2015). 67. Wenger, A. M. et al. Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome. Nat. Biotechnol. 37, 1155-1162 (2019). 68. Wang, Z., Gerstein, M. & Snyder, M. RNA-Seq: a revolutionary tool for transcriptomics. Nat. Rev. Genet. 10, 57-63 (2009).

	Traditional	Some key challenges highlighted by the
	pilot test concerned: species selection processes (criteria, prioritisation) and sampling procedures
	(permitting, collection, preservation, metadata); modes of engagement across interested parties
	(citizen scientists, policymakers, Indigenous Peoples, Local Communities etc); the diversity and
	inclusion of the researchers participating; defining the scope of ERGA and how that aligns with
	global efforts particularly those containing the majority of the planets remaining biodiversity;

disparities in resources and capacity (personnel, financial, and infrastructural); balancing decentralisation and innovation with standardisation, reproducibility and consistency; a need for more long-term and consistent training opportunities and disproportionate interest; and protocols, research and investment in species that are underrepresented in public data repositories.

As ERGA progresses, now with a dedicated funding stream through Biodiversity Genomics Europe, it can now build upon, learn and make the intentional investments needed to address at least some of these challenges. Although a centralised source of funding to support these endeavours is overall a positive it will also provide many challenges concerning diversity and equity, however efforts are underway to safeguard at least some level of the decentralised process e.g., community sampling and hotspot sequencing. was

Acknowledgements

ERGA Infrastructure: We acknowledge access to the storage resources at Barcelona Supercomputing Center, which are partially funded from European Union H2020-INFRAEOSC-2018-2020 programme through the DICE project (Grant Agreement no. 101017207), RES (Spanish Supercomputing Network), INB (Spanish National Bioinformatics Institute). We would like to thank Alisha Ahamed, Josephine Burgin, Joana Paupério, Jeena Rajan and Guy Cochrane from the European Nucleotide Archive (ENA) for their support PhD fellowship 1156622N), S.P is supported by the Icelandic Research Council, grant nr. 173908-05; S.V is supported by the Department of Agricultural and Environmental Sciences (DiSAA), University of Milan, both with her PhD scholarship and with the project "SPEED: Species distribution modelling and population genomics to calculate extinction risk in a changing climate", Piano di Sostegno alla Ricerca 2019 (PSR2019_DIP_014SPIER), awarded to the team member Simon Pierce; J.H is supported by VR, Formas and BGE;S.G is supported by the Novo Nordisk Foundation (NNF20CC0035580 and NNF210C0069089); G.M.H is supported by University College Dublin Ad Astra grant; The Royal Swedish Academy of Sciences provided funding for the reference genome of Stylops ater to Johannes Bergsten (Grant BS2022-0020); Portuguese National Funds through FCT (Fundação para a Ciência e a Tecnologia) support the research contract to AC [2020.00823.CEECIND/CP1601/CT0003]; this study was partly supported by the Slovenian Research Agency through research core funding No. P1-0403 for F.J.; IRA funded by Portuguese funds through FCT -Fundação para a Ciência e a Tecnologia, I.P., under the Norma Transitória -DL57/2016/CP1375/CT0003; A Böhne received support from the German Research Foundation DFG (grant numbers DFG 497674620 and DFG 492407022) and the Leibniz Association, A Böhne and R.Fernandez were funded by Horizon Europe under the Biodiversity, Circular Economy and Environment (REA.B.3); co-funded by the Swiss State Secretariat for Education, Research and Innovation (SERI) under contract number 22.00173; and by the UK Research and Innovation (UKRI) under the Department for Business, Energy and Industrial Strategy's Horizon Europe Guarantee Scheme; Z.O.J is supported by University of Iceland research fund; P.C.W is supported by the Academy of Finland (324602); C.V would like to thanks COST Action CA 18134 G-BiKE; Sampling and shipping for H.B was funded under HUNVIPHAB LIFE-project (LIFE18NAT/HU/000799); J. Höglund would like to thank the Faculty of Sciences of Uppsala University (Sweden) for its generous contribution, which guaranteed the inclusion of all the Swedish species in the ERGA pilot project ; RJL was supported by the Fundação para a Ciência e Tecnologia (FCT) through a Transitory Norm contract [DL57/2016/CP1440/CT0006]; The tissue sample for the European mink has been taken from a male mink in Dordogne (France) in 2006 by Pascal Fournier and Christine Fournier-Chambrillon (GREGE, sample collectors), in the framework of the first National Action Plan for the conservation of the European mink, and sent to a collection of cryopreserved cells (managed by Vitaly Volobouev) at MNHN (National Museum of Natural History). This

://canadacouncil.ca/glossary/equity-seeking-groups) equity deserving groups are those individual researchers, communities, Peoples, regions or countries that have identified barriers to equal access, opportunities, and resources due to disadvantage and/or discrimination and that are actively seeking, and deserving of social justice and reparation. The discrimination experienced could be caused by attitudinal, historic, social, and environmental barriers that could be based on a plethora of characteristics that are including (but not limited to) sex, age, ethnicity, disability, economic status, gender, gender expression, nationality, race, sexual orientation, and creed.

COPO -

The Collaborative OPen Omics (COPO) platform is for researchers to publish their research assets, providing metadata annotation and deposition capability. It allows researchers to describe their datasets according to community standards and broker the submission of such data to appropriate repositories whilst tracking the resulting accessions/identifiers [START_REF] Shaw | COPO: a metadata platform for brokering FAIR data in the life sciences[END_REF] .

Open data -Open data are freely accessible and unrestricted data that can be accessed, used, reused and shared with third parties for any purpose.

HSM -Hierarchical Storage

Management is both a data management and data storage technique which transparently manages the movement of data between the different layers of a tiered storage based on file size thresholds, usage and I/O pressure. Usually, a tiered storage is composed of one or more layers of disk arrays, ordered by capacity, latency, redundancy and storage cost. A slow but economically effective archival layer is at the bottom, composed of magnetic tape libraries and automated tape robots, with the highest capacity and latency. The movement between layers is automatically triggered.

ONT -Oxford Nanopore Technologies (ONT; https://nanoporetech.com/) is a next generation sequencing technology whereby sequence data are generated from the changes in current that occur as single-stranded DNA or RNA molecules pass through nanoscale protein pores (nanopores). ONT provides long read data (up to several megabases) that facilitate genome assembly [START_REF] Clarke | Continuous base identification for single-molecule nanopore DNA sequencing[END_REF]66 .

PacBio -Pacific Biosciences (PacBio; https://www.pacb.com/) is a single-molecule, real time (SMRT) next generation sequencing technology in which sequence data are generated by fluorescent light emission that occurs when a DNA polymerase adds nucleotides. PacBio produces long read data (tens of kilobases) that facilitate genome assembly.

HiFi reads -HiFi (High Fidelity) PacBio reads are produced by taking multiple sequences of the same molecule to provide a consensus sequence that is usually 12-20kbp long and has a low error rate (>99.9 % consensus accuracy) 67 .

Hi-C -Sequencing-based method used to study three-dimensional interactions among chromatin regions by measuring the frequency of contact between pairs of loci. Since contact frequency is related to the distance between a pair of loci, Hi-C linking information is used to help with scaffolding stages during a genome assembly process.

Hi-C map / graph production -The occurrence and frequency of Hi-C contacts are analysed and used in assembly scaffolding. They are typically visualised in Hi-C 2D heatmaps with the full genome sequence on the X and Y axis and a markup for each observed contact.

Omni-C -Modified version of Hi-C that uses a sequence-independent endonuclease during its protocol to produce more even sequence coverage increasing overall resolution.

RNA-Seq -RNA-Seq is a technique that determines the complete or partial RNA sequence using NGS. The RNA expression profiles vary in different tissues of the same organism and can be influenced by physiopathological circumstances. RNA-Seq data facilitate genome assembly by providing empirical evidence for annotation of transcribed regions 68 .

IsoSeq -This is a sequencing protocol developed by PacBio that aims to sequence full-length transcripts using the accurate, long read capabilities of PacBio HiFi technology. IsoSeq data facilitate analysis of transcriptomes and genome annotation by identifying full-length isoforms of transcripts.

Haplotype -A haplotype refers to the collection of genetic material within an organism that is inherited together. Haplotype may be used to describe a few loci or any number of chromosomes (a chromosome-scale haplotype). K-mer -A K-mer is a DNA sequence of length k; for example, the sequence AGCT contains the 3-mers (K-mers of length 3) AGC and GCT.

Transcriptome -A transcriptome is a set of aligned RNAseq reads representing RNA collected from a sample or collection of samples. This includes both protein-coding and non-coding transcripts. For the ERGA Pilot Project, poly-A+ transcripts were profiled.

Interested Parties -This term, for the purposes of this manuscript refers to the range of external stakeholders (e.g., commercial companies, policymakers etc) and rights holders (e.g., Indigenous Peoples) that have an interest in biodiversity genomics research.

EBP Genome assembly quality standard 6..Q40 -Minimum reference standard of 6.C.Q40, i.e. megabase N50 contig continuity and chromosomal scale N50 scaffolding, with less than 1/10,000 error rate. For species with chromosome N50 smaller than a megabase this will be C.C.Q40. Additional recommendations include K-mer completeness >90%, BUSCO complete single-copy single >90%, BUSCO complete single duplicate < 5%, and Gaps/Gbp <1000.

Widening Country -Widening countries are countries with low participation rates in FP7 and H2020 projects (low level of investment into research and innovation (R&I)). According to the