The brown hare, or European hare, Lupus europaeus, is a widespread mammal whose natural range spans western Eurasia. At the northern limit of its range, it hybridises with the mountain hare (L. timidis), and humans have introduced it into other continents. It represents a particularly interesting mammal to study for its population genetics, extensive hybridisation zones, and as an invasive species.

This study (Michell et al. 2024) has generated a high-quality assembly of a genome from a brown hare from Finland using long PacBio HiFi sequencing reads and Hi-C scaffolding. The contig N50 of this new genome is 43 Mb, and completeness, assessed using BUSCO, is 96.1%. The assembly comprises 23 autosomes, and an X chromosome and Y chromosome, with many chromosomes including telomeric repeats, indicating the high level of completeness of this assembly.

While the genome of the mountain hare has previously been assembled, its assembly was based on a short-read shotgun assembly, with the rabbit as a reference genome. The new high-quality brown hare genome assembly allows a direct comparison with the rabbit genome assembly. For example, the assembly addresses the karyotype difference between the hare (n=24) and the rabbit (n=22). Chromosomes 12 and 17 of the hare are equivalent to chromosome 1 of the rabbit, and chromosomes 13 and 16 of the hare are equivalent to chromosome 2 of the rabbit. The new assembly also provides a hare Y-chromosome, as the previous mountain hare genome was from a female.

This new genome assembly provides an important foundation for population genetics and evolutionary studies of lagomorphs.

References

Michell, C., Collins, J., Laine, P. K., Fekete, Z., Tapanainen, R., Wood, J. M. D., Goffart, S., Pohjoismäki, J. L. O. (2024). High quality genome assembly of the brown hare (Lepus europaeus) with chromosome-level scaffolding. bioRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2023.08.29.555262

 Comparative genomics is a general approach for understanding how genomes differ, which can be considered from many angles. For instance, this approach can delineate how gene content varies across organisms, which can lead to novel hypotheses regarding what those organisms do. It also enables investigations into the sequence-level divergence of orthologous DNA, which can provide insight into how evolutionary forces differentially shape genome content and structure across lineages. 
 
Such comparisons are often restricted to protein-coding genes, as these are sensible units for assessing putative function and for identifying homologous matches in divergent genomes. Although information is lost by focusing only on the protein-coding portion of genomes, this simplifies analyses and has led to crucial findings in recent years. Perhaps most dramatically, analyses based on hundreds of orthologous proteins across microbial eukaryotes are fundamentally changing our understanding of the eukaryotic tree of life (Burki et al. 2020).
 
These and other topics are highlighted in a new pre-print from Dr. Daniel Richter and colleagues, which describes EukProt (Richter et al. 2022): a database containing protein sets from 993 eukaryotic species. The authors provide a BLAST portal for matching custom sequences against this database (https://evocellbio.com/eukprot/) and the entire database is available for download (https://doi.org/10.6084/m9.figshare.12417881.v3). They also provide a subset of their overall dataset, ‘The Comparative Set’, which contains only high-quality proteomes and is meant to maximize phylogenetic diversity.
 
There are two major advantages of EukProt:
 
   1. It will enable researchers to quickly compare proteomes and perform phylogenomic analyses, without needing the skills or the time commitment to aggregate and process these data. The authors make it clear that acquiring the raw protein sets was non-trivial, as they were distributed across a wide variety of online repositories (some of which are no longer accessible!).
 
    2. Analyses based on this database will be more reproducible and easily compared across studies than those based on custom-made databases for individual studies. This is because the EukProt authors followed FAIR principles (Wilkinson et al. 2016) when building their database, which is a set of guidelines for enhancing data reusability. So, for instance, each proteome has a unique identifier in EukProt, and all species are annotated in a unified taxonomic framework, which will aid in standardizing comparisons across studies.
 
The authors make it clear that there is still work to be done. For example, there is an uneven representation of proteomes across different eukaryotic lineages, which can only be addressed by further characterization of poorly studied lineages. In addition, the authors note that it would ultimately be best for the EukProt database to be integrated into an existing large-scale repository, like NCBI, which would help ensure that important eukaryotic diversity was not ignored. Nonetheless, EukProt represents an excellent example of how reproducible bioinformatics resources should be designed and should prove to be an extremely useful resource for the field.
 
References

Burki F, Roger AJ, Brown MW, Simpson AGB (2020) The New Tree of Eukaryotes. Trends in Ecology & Evolution, 35, 43–55. https://doi.org/10.1016/j.tree.2019.08.008

Richter DJ, Berney C, Strassert JFH, Poh Y-P, Herman EK, Muñoz-Gómez SA, Wideman JG, Burki F, Vargas C de (2022) EukProt: A database of genome-scale predicted proteins across the diversity of eukaryotes. bioRxiv, 2020.06.30.180687, ver. 5 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2020.06.30.180687

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

Parasitoid wasps lay their eggs inside another arthropod, whose body is physically consumed by the parasitoid larvae. Phylogenetic inference suggests that Parasitoida are monophyletic, and that this clade underwent a strong radiation shortly after branching off from the Apocrita stem, some 236 million years ago (Peters et al. 2017). The increase in taxonomic diversity during evolutionary radiations is usually concurrent with an increase in genetic/genomic diversity, and is often associated with an increase in phenotypic diversity. Gene (or genome) duplication provides the evolutionary potential for such increase of genomic diversity by neo/subfunctionalisation of one of the gene paralogs, and is often proposed to be related to evolutionary radiations (Ohno 1970; Francino 2005).

In their recent preprint, Dominique Colinet and coworkers have explored the genetic and functional diversity of a Rho GTPase activating protein (RhoGAP) multigene family in two very divergent wasp clades within Parasitoida, namely Leptopilina (Figitidae) and Venturia (Ichneumonidae) (Colinet et al. 2024). Some members of the RhoGAP family are present in the venom of the parasitoid wasp Leptopilina boulardi as well as in other Leptopilina species, and are probably involved in the parasitic lifestyle by binding and inactivating host’s Rho GTPases, thereby interfering with the host’s immune response (Colinet et al. 2007).

Venom protein composition is highly variable, even between very closely related species, and is subject to rapid evolutionary changes. Although gene duplication and subsequent neo/subfunctionalisation have been frequently proposed as the main mechanism underlying this evolutionary diversification, observations are often compatible with alternative explanations, such as horizontal gene transfer, gene co-option or multifunctionalisation (Martinson et al. 2017; Alvarado et al. 2020; Huang et al. 2021; Undheim and Jenner 2021). Furthermore, high mutation rates in venom protein-encoding genes hinder phylogenetic hypothesis testing, and venom proteomics can be needed to verify transcriptomic predictions (Smith and Undheim 2018; von Reumont et al. 2022).

Colinet and coworkers (2024) have applied a combined transcriptomic, proteomic and functional approach to i) identify potential transcripts of the RhoGAP family in Leptopilina species using experimental and bioinformatic approaches; ii) experimentally identify proteins of the RhoGAP family in the venom of three Leptopilina species; iii) identify transcripts and proteins of the RhoGAP family in the ovarian calyx of Venturia canescens; and iv) perform phylogenetic and selection analyses on the extant sequences of these RhoGAP family genes to propose an evolutionary scenario for their origin and diversification. The most striking results are first the large diversity of RhoGAP sequences retrieved in the transcriptomes and proteomes of Leptopilina and of V. canescens, and second the high number of branches and positions identified to have evolved under positive selection. All the retrieved hits share a RhoGAP domain, either alone or in tandem, preceded in the case of Leptopilina RhoGAPs by a signal peptide that may be responsible for protein vehiculation for venom secretion. Further, for some of the protein positions identified to have evolved under positive selection, the authors have experimentally verified the functional impact of the changes by reverse genetic engineering.

The authors propose an evolutionary scenario to interpret the phylogenetic relationships among extant RhoGAP diversity in the clades under study. They posit that two independent, incomplete duplication events from the respectively ancestral RacGAP gene, followed by subsequent, lineage- and paralog-specific duplication events, lie at the origin of the wealth of diversity of in the Leptopilina venom RhoGAPs and of V. canescens ovarian calyx RhoGAPs. Notwithstanding, the global relationships presented in the work are not systematically consistent with this interpretation, e.g. regarding the absence of monophyly for Leptopilina RhoGAPs and Leptopilina RacGAP, and the same holds true for the respective V. canescens sequences. It may very well be that the high evolutionary rate of these genes has eroded the phylogenetic signal and prevented proper reconstruction, as the large differences between codon-based and amino acid-based phylogenies and the low support suggest. Explicit hypothesis testing, together with additional data from other taxa, may shed light onto the evolution of this gene family.

The work by Colinet and coworkers communicates sound, novel transcriptomic, proteomic and functional data from complex gene targets, consolidated from an important amount of experimental and bioinformatic work, and related to evolutionarily intriguing and complex phenotypes. These results, and the evolutionary hypothesis proposed to account for them, will be instrumental for our understanding of the evolution and diversity of vesicle-associated RhoGAPs in divergent parasitoid wasps.

References

Alvarado, G., Holland, S., R., DePerez-Rasmussen, J., Jarvis, B., A., Telander, T., Wagner, N., Waring, A., L., Anast, A., Davis, B., Frank, A., et al. (2020). Bioinformatic analysis suggests potential mechanisms underlying parasitoid venom evolution and function. Genomics 112(2), 1096–1104. https://doi.org/10.1016/j.ygeno.2019.06.022

Colinet, D., Cavigliasso, F., Leobold, M., Pichon, A., Urbach, S., Cazes, D., Poullet, M., Belghazi, M., Volkoff, A-N., Drezen, J-M., Gatti, J-L., and Poirié, M. (2024). Convergent origin and accelerated evolution of vesicle-associated RhoGAP proteins in two unrelated parasitoid wasps. bioRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2023.06.05.543686

Colinet, D., Schmitz, A., Depoix, D., Crochard, D., and Poirié, M. (2007). Convergent Use of RhoGAP Toxins by eukaryotic parasites and bacterial pathogens. PLoS Pathogens 3(12), e203. https://doi.org/10.1371/journal.ppat.0030203

Francino, M.P. (2005). An adaptive radiation model for the origin of new gene functions. Nature Genetics 37, 573–577. https://doi.org/10.1038/ng1579

Huang, J., Chen, J., Fang, G., Pang, L., Zhou, S., Zhou, Y., Pan, Z., Zhang, Q., Sheng, Y., Lu, Y., et al. (2021). Two novel venom proteins underlie divergent parasitic strategies between a generalist and a specialist parasite. Nature Communications 12, 234. https://doi.org/10.1038/s41467-020-20332-8

Martinson, E., O., Mrinalini, Kelkar, Y. D., Chang, C-H., and Werren, J., H. 2017. The evolution of venom by co-option of single-copy genes. Current Biololgy 27(13), 2007-2013.e8. https://doi.org/10.1016/j.cub.2017.05.032

Ohno, S. (1970). Evolution by gene duplication. New-York: Springer-Verlag.

Peters, R., S., Krogmann, L., Mayer, C., Donath, A., Gunkel, S., Meusemann, K., Kozlov, A., Podsiadlowski, L., Petersen, M., Lanfear, R., et al. (2017). Evolutionary history of the Hymenoptera. Current Biology 27(7), 1013–1018. https://doi.org/10.1016/j.cub.2017.01.027

von Reumont, B., M., Anderluh, G., Antunes, A., Ayvazyan, N., Beis, D., Caliskan, F., Crnković, A., Damm, M., Dutertre, S., Ellgaard, L., et al. (2022). Modern venomics—Current insights, novel methods, and future perspectives in biological and applied animal venom research. GigaScience 11, giac048. https://doi.org/10.1093/gigascience/giac048

Smith, J., J., and Undheim, E., A., B. (2018). True lies: using proteomics to assess the accuracy of transcriptome-based venomics in centipedes uncovers false positives and reveals startling intraspecific variation in Scolopendra subspinipes. Toxins 10(3), 96. https://doi.org/10.3390/toxins10030096

Undheim, E., A., B., and Jenner, R., A. (2021). Phylogenetic analyses suggest centipede venom arsenals were repeatedly stocked by horizontal gene transfer. Nature Communications 12, 818. https://doi.org/10.1038/s41467-021-21093-8

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

Repetitive extragenic palindromic sequences (REPs) are common repetitive elements in bacterial genomes (Gilson et al., 1984; Stern et al., 1984). In 2011, Bertels and Rainey identified that REPs are overrepresented in pairs of inverted repeats, which likely form hairpin structures, that they referred to as “REP doublets forming hairpins” (REPINs). Based on bioinformatics analyses, they argued that REPINs are likely selfish elements that evolved from REPs flanking particular transposes (Bertels and Rainey, 2011). These transposases, so-called REP-associated tyrosine transposases (RAYTs), were known to be highly associated with the REP content in a genome and to have characteristic upstream and downstream flanking REPs (Nunvar et al., 2010). The flanking REPs likely enable RAYT transposition, and their horizontal replication is physically linked to this process. In contrast, Bertels and Rainey hypothesized that REPINs are selfish elements that are highly replicated due to the similarity in arrangement to these RAYT-flanking REPs, but independent of RAYT transposition and generally with no impact on bacterial fitness (Bertels and Rainey, 2011).

This last point was especially contentious, as REPINs are highly conserved within species (Bertels and Rainey, 2023), which is unusual for non-beneficial bacterial DNA (Mira et al., 2001). Bertels and Rainey have since refined their argument to be that REPINs must provide benefits to host cells, but that there are nonetheless signatures of intragenomic conflict in genomes associated with these elements (Bertels and Rainey, 2023). These signatures reflect the divergent levels of selections driving REPIN distribution: selection at the level of each DNA element and selection on each individual bacterium. I found this observation particularly interesting as I and my colleague recently argued that these divergent levels of selection, and the interaction between them, is key to understanding bacterial pangenome diversity (Douglas and Shapiro, 2021). REPINs could be an excellent system for investigating these levels of selection across bacteria more generally.

The problem is that REPINs have not been widely characterized in bacterial genomes, partially because no bioinformatic workflow has been available for this purpose. To address this problem, Fortmann-Grote et al. (2023) developed RAREFAN, which is a web server for identifying RAYTs and associated REPINs in a set of input genomes. The authors showcase their tool by applying it to 49 Stenotrophomonas maltophilia genomes and providing examples of how to identify and assess RAYT-REPIN hits. The workflow requires several manual steps, but nonetheless represents a straightforward and standardized approach. Overall, this workflow should enable RAYTs and REPINs to be identified across diverse bacterial species, which will facilitate further investigation into the mechanisms driving their maintenance and spread.

References

Bertels F, Rainey PB (2023) Ancient Darwinian replicators nested within eubacterial genomes. BioEssays, 45, 2200085. https://doi.org/10.1002/bies.202200085

Bertels F, Rainey PB (2011) Within-Genome Evolution of REPINs: a New Family of Miniature Mobile DNA in Bacteria. PLOS Genetics, 7, e1002132. https://doi.org/10.1371/journal.pgen.1002132

Douglas GM, Shapiro BJ (2021) Genic Selection Within Prokaryotic Pangenomes. Genome Biology and Evolution, 13, evab234. https://doi.org/10.1093/gbe/evab234

Fortmann-Grote C, Irmer J von, Bertels F (2023) RAREFAN: A webservice to identify REPINs and RAYTs in bacterial genomes. bioRxiv, 2022.05.22.493013, ver. 4 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2022.05.22.493013

Gilson E, Clément J m., Brutlag D, Hofnung M (1984) A family of dispersed repetitive extragenic palindromic DNA sequences in E. coli. The EMBO Journal, 3, 1417–1421. https://doi.org/10.1002/j.1460-2075.1984.tb01986.x

Mira A, Ochman H, Moran NA (2001) Deletional bias and the evolution of bacterial genomes. Trends in Genetics, 17, 589–596. https://doi.org/10.1016/S0168-9525(01)02447-7

Nunvar J, Huckova T, Licha I (2010) Identification and characterization of repetitive extragenic palindromes (REP)-associated tyrosine transposases: implications for REP evolution and dynamics in bacterial genomes. BMC Genomics, 11, 44. https://doi.org/10.1186/1471-2164-11-44

Stern MJ, Ames GF-L, Smith NH, Clare Robinson E, Higgins CF (1984) Repetitive extragenic palindromic sequences: A major component of the bacterial genome. Cell, 37, 1015–1026. https://doi.org/10.1016/0092-8674(84)90436-7