Developing new sequencing and bioinformatic strategies for non-model species is of great interest in many applications, such as phylogenetic studies of diverse related species, but also for studies in population genomics, where a relatively large number of individuals is necessary. Different approaches have been developed and used in these last two decades, such as RAD-Seq (e.g., Miller et al. 2007), exome sequencing (e.g., Teer and Mullikin 2010) and other genome reduced representation methods that avoid the use of a good reference and well annotated genome (reviewed at Davey et al. 2011). However, population genomics studies require the analysis of numerous individuals, which makes the studies still expensive. Pooling samples was thought as an inexpensive strategy to obtain estimates of variability and other related to the frequency spectrum, thus allowing the study of variability at population level (e.g., Van Tassell et al. 2008), although the major drawback was the loss of information related to the linkage of the variants. In addition, population analysis using all these sequencing strategies require statistical and empirical validations that are not always fully performed. A number of studies aiming to obtain unbiased estimates of variability using reduced representation libraries and/or with pooled data have been performed (e.g., Futschik and Schlötterer 2010, Gautier et al. 2013, Ferretti et al. 2013, Lynch et al. 2014), as well as validation of new sequencing methods for population genetic analyses (e.g., Gautier et al. 2013, Nevado et al. 2014). Nevertheless, empirical validation using both pooled and individual experimental approaches combined with different bioinformatic methods has not been always performed.
Here, Deleury et al. (2020) proposed an efficient and elegant way of quantifying the single-nucleotide polymorphisms (SNPs) of exon-derived sequences in a non-model species (i.e. for which no reference genome sequence is available) at the population level scale. They also designed a new procedure to capture exon-derived sequences based on a reference transcriptome. In addition, they were able to make predictions of intron-exon boundaries for de novo transcripts based on the decay of read depth at the ends of the coding regions.
Based on theoretical predictions (Gautier et al. 2013), Deleury et al. (2020) designed a procedure to test the accuracy of variant allele frequencies (AFs) with pooled samples, in a reduced genome-sequence library made with transcriptome regions, and additionally testing the effects of new bioinformatic methods in contrast to standardized methods. They applied their strategy on the non-model species Asian ladybird (Harmonia axyridis), for which a draft genome is available, thereby allowing them to benchmark their method with regard to a traditional mapping-based approach. Based on species-specific de novo transcriptomes, they designed capture probes which are then used to call SNPx and then compared the resulting SNP AFs at the individual (multiplexed) versus population (pooled) levels. Interestingly, they showed that SNP AFs in the pool sequencing strategy nicely correlate with the individual ones but obviously in a cost-effective way. Studies of population genomics for non-model species have usually limited budgets. The number of individuals required for population genomics analysis multiply the costs of the project, making pooling samples an interesting option. Furthermore, the use of pool sequencing is not always a choice, as many organisms are too small and/or individuals are too sticked each other to be individually sequenced (e.g., Choquet et al. 2019, Kurland et al. 2019). In addition, the study of a reduced section of the genome is cheaper and often sufficient for a number of population genetic questions, such as the understanding of general demographic events, or the estimation of the effects of positive and/or negative selection at functional coding regions. Studies on population genomics of non-model species have many applications in related fields, such as conservation genetics, control of invasive species, etc. The work of Deleury et al. (2020) is an elegant contribution to the assessment and validation of new methodologies used for the analysis of genome variations at the intra-population variability level, highlighting straight bioinformatic and reliable sequencing methods for population genomics studies.

References

[1] Choquet et al. (2019). Towards population genomics in non-model species with large genomes: a case study of the marine zooplankton Calanus finmarchicus. Royal Society open science, 6(2), 180608. doi: https://doi.org/10.1098/rsos.180608
[2] Davey, J. W., Hohenlohe, P. A., Etter, P. D., Boone, J. Q., Catchen, J. M. and Blaxter, M. L. (2011). Genome-wide genetic marker discovery and genotyping using next-generation sequencing. Nature Reviews Genetics, 12(7), 499-510. doi: https://doi.org/10.1038/nrg3012
[3] Deleury, E., Guillemaud, T., Blin, A. and Lombaert, E. (2020) An evaluation of pool-sequencing transcriptome-based exon capture for population genomics in non-model species. bioRxiv, 10.1101/583534, ver. 7 peer-reviewed and recommended by PCI Genomics. https://doi.org/10.1101/583534
[4] Ferretti, L., Ramos‐Onsins, S. E. and Pérez‐Enciso, M. (2013). Population genomics from pool sequencing. Molecular ecology, 22(22), 5561-5576. doi: https://doi.org/10.1111/mec.12522
[5] Futschik, A. and Schlötterer, C. (2010). Massively parallel sequencing of pooled DNA samples—the next generation of molecular markers. Genetics, 186 (1), 207-218. doi: https://doi.org/10.1534/genetics.110.114397
[6] Gautier et al. (2013). Estimation of population allele frequencies from next‐generation sequencing data: pool‐versus individual‐based genotyping. Molecular Ecology, 22(14), 3766-3779. doi: https://doi.org/10.1111/mec.12360
[7] Kurland et al. (2019). Exploring a Pool‐seq‐only approach for gaining population genomic insights in nonmodel species. Ecology and evolution, 9(19), 11448-11463. doi: https://doi.org/10.1002/ece3.5646
[8] Lynch, M., Bost, D., Wilson, S., Maruki, T. and Harrison, S. (2014). Population-genetic inference from pooled-sequencing data. Genome biology and evolution, 6(5), 1210-1218. doi: https://doi.org/10.1093/gbe/evu085
[9] Miller, M. R., Dunham, J. P., Amores, A., Cresko, W. A. and Johnson, E. A. (2007). Rapid and cost-effective polymorphism identification and genotyping using restriction site associated DNA (RAD) markers. Genome research, 17(2), 240-248. doi: https://doi.org/10.1101%2Fgr.5681207
[10] Nevado, B., Ramos‐Onsins, S. E. and Perez‐Enciso, M. (2014). Resequencing studies of nonmodel organisms using closely related reference genomes: optimal experimental designs and bioinformatics approaches for population genomics. Molecular ecology, 23(7), 1764-1779. doi: https://doi.org/10.1111/mec.12693
[11] Teer, J. K. and Mullikin, J. C. (2010). Exome sequencing: the sweet spot before whole genomes. Human molecular genetics, 19(R2), R145-R151. doi: https://doi.org/10.1093/hmg/ddq333
[12] Van Tassell et al. (2008). SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries. Nature methods, 5(3), 247-252. doi: https://doi.org/10.1038/nmeth.1185

Transposable elements (TEs) are important components of genomes. Indeed, they are now recognized as having a major role in gene and genome evolution (Biémont 2010). In particular, several examples have shown that the presence of TEs near genes may influence their functioning, either by recruiting particular epigenetic modifications (Guio et al. 2018) or by directly providing new regulatory sequences allowing new expression patterns (Chung et al. 2007; Sundaram et al. 2014). Therefore, the study of the interaction between TEs and their host genome requires tools to easily cross-annotate both types of entities. In particular, one needs to be able to identify all TEs located in the close vicinity of genes or inside them. Such task may not always be obvious for many biologists, as it requires informatics knowledge to develop their own script codes.

In their work, Meguerdichian et al. (2021) propose a command-line pipeline that takes as input the annotations of both genes and TEs for a given genome, then detects and reports the positional relationships between each TE insertion and their closest genes. The results are processed into an R script to provide tables displaying some statistics and graphs to visualize these relationships. 

This tool has the potential to be very useful for performing preliminary analyses before studying the impact of TEs on gene functioning, especially for biologists. Indeed, it makes it possible to identify genes close to TE insertions. These identified genes could then be specifically considered in order to study in more detail the link between the presence of TEs and their functioning. For example, the identification of TEs close to genes may allow to determine their potential role on gene expression.

References

Biémont C (2010). A brief history of the status of transposable elements: from junk DNA to major players in evolution. Genetics, 186, 1085–1093. https://doi.org/10.1534/genetics.110.124180

Chung H, Bogwitz MR, McCart C, Andrianopoulos A, ffrench-Constant RH, Batterham P, Daborn PJ (2007). Cis-regulatory elements in the Accord retrotransposon result in tissue-specific expression of the Drosophila melanogaster insecticide resistance gene Cyp6g1. Genetics, 175, 1071–1077. https://doi.org/10.1534/genetics.106.066597

Guio L, Vieira C, González J (2018). Stress affects the epigenetic marks added by natural transposable element insertions in Drosophila melanogaster. Scientific Reports, 8, 12197. https://doi.org/10.1038/s41598-018-30491-w

Meguerditchian C, Ergun A, Decroocq V, Lefebvre M, Bui Q-T (2021). A pipeline to detect the relationship between transposable elements and adjacent genes in host genomes. bioRxiv, 2021.02.25.432867, ver. 4 peer-reviewed and recommended by Peer Community In Genomics. https://doi.org/10.1101/2021.02.25.432867

Sundaram V, Cheng Y, Ma Z, Li D, Xing X, Edge P, Snyder MP, Wang T (2014). Widespread contribution of transposable elements to the innovation of gene regulatory networks. Genome Research, 24, 1963–1976. https://doi.org/10.1101/gr.168872.113

Böhne et al. (2024) do not present a classical scientific paper per se but a report on how the European Reference Genome Atlas (ERGA) aims to deal with sampling and sample information, i.e. metadata.

As the goal of ERGA is to provide an almost fully representative set of reference genomes representative of European biodiversity to serve many research areas in biology, they have to be really exhaustive. In this regard, in addition to providing sample metadata recording guidelines, they also discuss the biases existing in sampling and sequencing projects.

The first task for such a project is to be sure that the data they generate will be usable and available in the future (“[in] perpetuity", Böhne et al. 2024). The authors deployed a very efficient pipeline for conserving information on sampling: location, physical information, copies of tissues and of DNA, shipping, legal/ethical aspects regarding the Nagoya Protocol, etc., alongside a best-practice manual. This effort is linked to practical guides for the DNA extraction of specific taxa. More generally, these details enable “Findable, Accessible, Interoperable, and Reusable” (FAIR) principles (Wilkinson et al. 2016) to be followed.

An important aspect of this paper, in addition to practical points, is the reflection upon the different biases inherent to the choice of sequenced samples. Acknowledging their own biases with regards to DNA extraction protocol efficiency, small genome size choice, as well as the availability of material (Nagoya Protocol aspects) and material transfer efficiency, the authors recommend in the future to not survey biodiversity by selecting one’s favorite samples or species, but also considering "orphan" taxa. Some of these "orphan" taxonomic groups belong to non-arthropod invertebrates but internal disparities are also prominent within other taxa. Finally, the implementation of the "Collective benefit, Authority to control, Responsibility, and Ethics" (CARE) principles (Carroll et al. 2021) will allow Indigenous rights to be considered when prioritizing samples, and to enable their "knowledge systems to permeate throughout the process of reference genome production and beyond" (Böhne et al. 2024).

Last, but not least, as ERGA, including its Sampling and Sample Processing committee, is a large collective effort, it is very refreshing to read a paper starting with the acknowledgements and the roles of each member.

References

Böhne A, Fernández R, Leonard JA, McCartney AM, McTaggart S, Melo-Ferreira J, Monteiro R, Oomen RA, Pettersson OV, Struck TH (2024) Contextualising samples: Supporting reference genomes of European biodiversity through sample and associated metadata collection. bioRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2023.06.28.546652

Carroll SR, Herczog E, Hudson M, Russell K, Stall S (2021) Operationalizing the CARE and FAIR Principles for Indigenous data futures. Scientific Data, 8, 108. https://doi.org/10.1038/s41597-021-00892-0

Wilkinson MD, Dumontier M, Aalbersberg IjJ, Appleton G, Axton M, Baak A, Blomberg N, Boiten J-W, da Silva Santos LB, Bourne PE, Bouwman J, Brookes AJ, Clark T, Crosas M, Dillo I, Dumon O, Edmunds S, Evelo CT, Finkers R, Gonzalez-Beltran A, Gray AJG, Groth P, Goble C, Grethe JS, Heringa J, ’t Hoen PAC, Hooft R, Kuhn T, Kok R, Kok J, Lusher SJ, Martone ME, Mons A, Packer AL, Persson B, Rocca-Serra P, Roos M, van Schaik R, Sansone S-A, Schultes E, Sengstag T, Slater T, Strawn G, Swertz MA, Thompson M, van der Lei J, van Mulligen E, Velterop J, Waagmeester A, Wittenburg P, Wolstencroft K, Zhao J, Mons B (2016) The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3, 160018. https://doi.org/10.1038/sdata.2016.18

When discussing the Earth BioGenome Project with scientists and potential funding agencies, one common question is: why sequence everything? Whether sequencing a subset would be more optimal is not an unreasonable question given what we know about the mathematics of importance and Pareto’s 80:20 principle, that 80% of the benefits can come from 20% of the effort. However, one must remember that this principle is an observation made in hindsight and selecting the most effective 20% of experiments is difficult. As an example, few saw great applied value in comparative genomic analysis of the archaea Haloferax mediterranei, but this enabled the discovery of CRISPR/Cas9 technology (1). When discussing whether or not to sequence all life on our planet, smaller countries such as the Faroe Islands are seldom mentioned. 
 
Mikalsen and co-authors (2) provide strong arguments to appreciate, investigate and steward genetic diversity, from a Faroese viewpoint, a fishery viewpoint, and a global viewpoint. As readers, we learn to cherish the Faroe Islands, the Faroese, and perhaps by extension all of nature and the people of the world. The manuscript describes the proposed Faroese participation in the European Reference Genome Atlas (ERGA) consortium through Gen@FarE – the Genome Atlas of Faroese Ecology. Gen@FarE aims to: i) generate high-quality reference genomes for all eukaryotes on the islands and in its waters; ii) establish population genetics of all species of commercial or ecological interest; and iii) establish a “databank” for all Faroese species with citizen science tools for participation.

In the background section of the manuscript, the authors argue that as caretakers of the earth (and responsible for the current rapid decrease in biodiversity), humanity must be aware of the biodiversity and existing genetic diversity, to protect these for future generations. Thus, it is necessary to have reference genomes for as many species as possible, enabling estimation of population sizes and gene flow between ecosystem locations. Without this the authors note that “…it is impossible to make relevant management plans for a species, an ecosystem or a geographical area…”. Gen@FarE is important. The Faroe nation has a sizable economic zone in the North Atlantic and large fisheries. In terms of biodiversity and conservation, the authors list some species endemic to other Faroe islands, especially sea birds. The article discusses ongoing marine environmental-DNA-based monitoring programs that started in 2018, and how new reference genome databases will help these efforts to track and preserve marine biodiversity. They point to the lack of use of population genomics information for Red List decisions on which species are endangered, and the need for these techniques to inform sustainable harvesting of fisheries, given collapses in critical food species such as Northwest Atlantic cod and herring. In one example, they highlight how the herring chromosome 12 inversion contains a “supergene” collection of tightly linked genes associated with ecological adaptation. Genetic tools may also help enable the identification and nurturing of feeding grounds for young individuals. Critically, the Faroe Islands have a significant role to play in protecting the millions of tons of seafood caught annually upon which humanity relies. As the authors note, population genomics based on high-quality reference sequences is “likely the best tool” to monitor and protect commercial fisheries. There is an important section discussing the role of interactions between visible and “invisible" species in the marine ecosystem on which we all depend. Examples of “invisible” species include a wide range of morphologically similar planktonic algae, and invasive species transported by ballast water or ship hulls.​ As biologists, I believe we forget that our population studies of life on the earth have so far been mostly in the dark. Gen@FarE is but one light that can be switched on. 

The authors conclude by discussing Gen@FarE plans for citizen science and education, perhaps the most important part of this project if humanity is to learn to cherish and care for the earth. Where initiatives such as the Human Genome Project did not need the collaborative efforts of the world for sample access, the Earth BioGenome Project most certainly does. In the same way, at a smaller scale, Gen@FarE requires the support and determination of the Faroese. 
 

References    

1          Mojica, F. J., Díez-Villaseñor, C. S., García-Martínez, J. & Soria, E. Intervening sequences of regularly spaced prokaryotic repeats derive from foreign genetic elements. J Mol Evol 60, 174-182 (2005).

2          Mikalsen, S-O., Hjøllum, J. í., Salter, I., Djurhuus, A. & Kongsstovu, S. í. The need of decoding life for taking care of biodiversity and the sustainable use of nature in the Anthropocene – a Faroese perspective. EcoEvoRxiv (2024), ver. 3 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.32942/X21S4C

Green algae of the genus Coccomyxa (family Trebouxiophyceae) are extremely diverse in their morphology, habitat (i.e., in marine, freshwater, and terrestrial environments) and lifestyle, including free-living and mutualistic forms. Coccomyxa viridis (strain SAG 216–4) is a photobiont in the lichen Peltigera aphthosa, which was isolated in Switzerland more than 70 years ago (cf. SAG, the Culture Collection of Algae at the University of Göttingen, Germany). Despite the high diversity and plasticity in Coccomyxa, integrative taxonomic analyses led Darienko et al. (2015) to propose clear species boundaries. These authors also showed that symbiotic strains that form lichens evolved multiple times independently in Coccomyxa.

Using state-of-the-art sequencing data and bioinformatic methods, including Pac-Bio HiFi and ONT long reads, as well as Hi-C chromatin conformation information, Kraege et al. (2024) generated a high-quality genome assembly for the Coccomyxa viridis strain SAG 216–4. They reconstructed 19 complete nuclear chromosomes, flanked by telomeric regions, totaling 50.9 Mb, plus the plastid and mitochondrial genomes. The performed quality controls leave no doubt of the high quality of the genome assemblies and structural annotations. An interesting observation is the lack of conserved synteny with the close relative Coccomyxa subellipsoidea, but further comparative studies with additional Coccomyxa strains will be required to grasp the genomic evolution in this genus of green algae. This project is framed within the ERGA pilot project, which aims to establish a pan-European genomics infrastructure and contribute to cataloging genomic biodiversity and producing resources that can inform conservation strategies (Formenti et al. 2022). This complete reference genome represents an important step towards this goal, in addition to contributing to future genomic analyses of Coccomyxa more generally.

References

Darienko T, Gustavs L, Eggert A, Wolf W, Pröschold T (2015) Evaluating the species boundaries of green microalgae (Coccomyxa, Trebouxiophyceae, Chlorophyta) using integrative taxonomy and DNA barcoding with further implications for the species identification in environmental samples. PLOS ONE, 10, e0127838. https://doi.org/10.1371/journal.pone.0127838

Formenti G, Theissinger K, Fernandes C, Bista I, Bombarely A, Bleidorn C, Ciofi C, Crottini A, Godoy JA, Höglund J, Malukiewicz J, Mouton A, Oomen RA, Paez S, Palsbøll PJ, Pampoulie C, Ruiz-López MJ, Svardal H, Theofanopoulou C, de Vries J, Waldvogel A-M, Zhang G, Mazzoni CJ, Jarvis ED, Bálint M, European Reference Genome Atlas Consortium (2022) The era of reference genomes in conservation genomics. Trends in Ecology & Evolution, 37, 197–202. https://doi.org/10.1016/j.tree.2021.11.008

Kraege A, Chavarro-Carrero EA, Guiglielmoni N, Schnell E, Kirangwa J, Heilmann-Heimbach S, Becker K, Köhrer K, WGGC Team, DeRGA Community, Schiffer P, Thomma BPHJ, Rovenich H (2024) High quality genome assembly and annotation (v1) of the eukaryotic terrestrial microalga Coccomyxa viridis SAG 216-4. bioRxiv, ver. 2 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2023.07.11.548521