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

Oriowo et al. (2024) offer a thorough and meticulously conducted study that makes a substantial contribution to our understanding of the Eurasian minnow (Phoxinus phoxinus), particularly in terms of its genetic diversity, structural variations, and evolutionary adaptations. The authors have achieved an impressive feat by generating an annotated haplotype-phased, chromosome-level genome assembly (2n = 50). This was accomplished through the integration of high-fidelity long reads with chromosome conformation capture data (Hi-C), resulting in a highly complete and accurate genome assembly. The assembly is characterized by a haploid size of 940 Megabase pairs (Mbp) for haplome one and 929 Mbp for haplome two, with scaffold N50 values of 36.4 Mb and 36.6 Mb, respectively. These metrics, alongside BUSCO scores of 96.9% and 97.2%, highlight the high quality of the genome, making it a robust foundation for further genetic exploration and analyses.

The study’s findings are both novel and significant, providing deep insights into the genetic architecture of P. phoxinus. The authors report heterozygosity rate of 1.43% and a high repeat content of approximately 54%, primarily consisting of DNA transposons. These transposons play a crucial role in genome rearrangements and variations, contributing to the species' adaptability and evolution (Bourque et al. 2018). The research also identifies substantial structural variations within the genome, including insertions, deletions, inversions, and translocations (Oriowo et al. 2024). Beyond these findings, the genome annotation is exceptionally comprehensive, containing 30,980 mRNAs and 23,497 protein-coding genes. The study’s gene family evolution analysis, which compares the P. phoxinus proteome to that of ten other teleost species, reveals immune system gene families that favor histone-based disease prevention mechanisms over NLR-based immune responses. This provides new insight into the evolutionary strategies that have emerged in P. phoxinus, enabling its survival in its environment. Moreover, the demographic analysis conducted in the study reveals historical fluctuations in the effective population size of P. phoxinus, likely correlated with past climatic changes, offering insights into the species' evolutionary history.

This annotated and phased reference genome not only serves as a crucial resource for resolving taxonomic complexities within the genus Phoxinus but also highlights the importance of haplotype-phased assemblies in understanding genetic diversity, particularly in species characterized by high heterozygosity. The authors have delivered a study that is methodologically sound, richly detailed, and highly relevant to the field. The study represents a valuable and impactful contribution to the scientific community, offering resources and knowledge that will likely inform future research in the field.

References

Bourque G, Burns KH, Gehring M, Gorbunova V, Seluanov A, Hammell M, Imbeault M, Izsvák Z, Levin HL, Macfarlan TS, Mager DL, Feschotte C (2018) Ten things you should know about transposable elements. Genome Biology, 19, 199. https://doi.org/10.1186/s13059-018-1577-z

Oriowo TO, Chrysostomakis I, Martin S, Kukowka S, Brown T, Winkler S, Myers EW, Böhne A, Stange M (2024) A chromosome-level, haplotype-resolved genome assembly and annotation for the Eurasian minnow (Leuciscidae: Phoxinus phoxinus) provide evidence of haplotype diversity. bioRxiv, ver. 6 peer-reviewed and recommended by PCI Genomics https://doi.org/10.1101/2023.11.30.569369

Dating evolutionary trees is a critical task that allows us to connect biological history to ecological and geological events, helping us explore connections between environmental change and genetic innovations. The central idea behind these techniques is to link changes at the sequence level to divergence times, under the general assumption that substitutions accumulate steadily over time. So, sequences that diverged earlier are expected to be more different than sequences that diverged more recently. For a number of biological and statistical reasons, the relationship between sequence divergence and time is not linear, so it is not always the case that more divergent sequences have accumulated more substitutions than less divergent ones. In the case of organismal-level divergences, a natural approach to mitigate these challenges is to incorporate as many genes as possible into the analyses. However, this route is not available when we are focusing our interest on a single gene or a gene family. Thus, exploring how different features of single gene trees impact the accuracy and precision of divergence time estimates is of interest. In this study, Louvel and Roest Crollius (2024), select a well-studied group of mammals, primates, extract single copy genes from their genomes, and explore how different factors such as alignment size, evolutionary rate variation and discordance between the gene and species trees impact divergence time estimates. 

There are many strengths of this study. The central ones are the number of factors considered and the transparent discussion of the limitations. In this regard, the study is an elegant combination of empirical and simulated data. Some of the results match intuitive expectations. For example, the authors find that longer alignments are more informative than shorter ones, that differences in evolutionary rate among branches lead to loss in precision, and that slow-evolving genes perform worse. Intriguingly, they also find differences in performance among genes with different ontologies. The empirical data used in this study is limited to a single group, and generally considers genes that have apparently remained as single copies. Accordingly, the conclusions that can be drawn are somewhat limited, calling for future studies building on and expanding the concepts of the study by Louvel and colleagues. For example, including genes that have been lost or duplicated would be of interest because changes in gene complement are a prevalent source of variation at the genome level in mammals in general (Demuth et al. 2006), and particularly in primates (Hahn et al. 2007).

References

Demuth JP, De Bie T, Stajich JE, Cristianini N, Hahn MW (2006) The evolution of mammalian gene families. PLoS One, e85. https://doi.org/10.1371/journal.pone.0000085

Hahn MW, Demuth JP, Han SG (2007) Accelerated rate of gene gain and loss in primates. Genetics, 177,1941-1949. https://doi.org/10.1534/genetics.107.080077

Louvel, G and Roest Crollius, H (2024) Factors influencing the accuracy and precision in dating single gene trees. bioRxiv, ver. 6 peer-reviewed and recommended by PCI Genomics. https://doi.org/10.1101/2020.08.24.264671

Whole genome sequences are revolutionizing our understanding across various biological fields. They not only shed light on the evolution of genetic material but also uncover the genetic basis of phenotypic diversity. The sequencing of underrepresented lineages, such as the one presented in this study, is of critical importance. It is crucial in filling significant gaps in our understanding of Metazoa evolution. Despite the wealth of genome sequences in public databases, it is crucial to acknowledge that some lineages across the Tree of Life are underrepresented or absent. This research represents a significant step towards addressing this imbalance, contributing to the collective knowledge of the global scientific community.

In this genome note, as part of the European Reference Genome Atlas pilot effort to generate reference genomes for European biodiversity (Mc Cartney et al. 2023), Klara Eleftheriadi and colleagues (Eleftheriadi et al. 2023) make a significant effort to add a genome sequence of an unrepresented group in the animal Tree of Life. More specifically, they present a taxonomic description and chromosome-level genome assembly of a newly described species of horsehair worm (Gordionus montsenyensis). Their sequence methodology gave rise to an assembly of 396 scaffolds totaling 288 Mb, with an N50 value of 64.4 Mb, where 97% of this assembly is grouped into five pseudochromosomes. The nuclear genome annotation predicted 10,320 protein-coding genes, and they also assembled the circular mitochondrial genome into a 15-kilobase sequence.

The selection of a species representing the phylum Nematomorpha, a group of parasitic organisms belonging to the Ecdysozoa lineage, is good, since today, there is only one publicly available genome for this animal phylum (Cunha et al. 2023). Interestingly, this article shows, among other things, that the species analyzed has lost ∼30% of the universal Metazoan genes. Efforts, like the one performed by Eleftheriadi and colleagues, are necessary to gain more insights, for example, on the evolution of this massive gene lost in this group of animals.

References

Cunha, T. J., de Medeiros, B. A. S, Lord, A., Sørensen, M. V., and Giribet, G. (2023). Rampant Loss of Universal Metazoan Genes Revealed by a Chromosome-Level Genome Assembly of the Parasitic Nematomorpha. Current Biology, 33 (16): 3514–21.e4. https://doi.org/10.1016/j.cub.2023.07.003

Eleftheriadi, K., Guiglielmoni, N., Salces-Ortiz, J., Vargas-Chavez, C., Martínez-Redondo, G. I., Gut, M., Flot, J.-F., Schmidt-Rhaesa, A., and Fernández, R. (2023). The Genome Sequence of the Montseny Horsehair worm, Gordionus montsenyensis sp. Nov., a Key Resource to Investigate Ecdysozoa Evolution. bioRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2023.06.26.546503

Mc Cartney, A. M., Formenti, G., Mouton, A., De Panis, D., Marins, L. S., Leitão, H. G., Diedericks, G., et al. (2023). The European Reference Genome Atlas: Piloting a Decentralised Approach to Equitable Biodiversity Genomics. bioRxiv. https://doi.org/10.1101/2023.09.25.559365

Contamination, the presence of foreign DNA sequences in a sample of interest, is currently a major problem in genomics. Because contamination is often unavoidable at the experimental stage, it is increasingly recognized that the processing of high-throughput sequencing data must include a decontamination step. This is usually performed after the many sequence reads have been assembled into a relatively small number of contigs. Dubious contigs are then discarded based on their composition (e.g. GC-content) or because they are highly similar to a known piece of DNA from a foreign species.

Here [1], Mathieu Gautier explores a novel strategy consisting in decontaminating reads, not contigs. Why is this promising? Assembly programs and algorithms are complex, and it is not easy to predict, or monitor, how they handle contaminant reads. Ideally, contaminant reads will be assembled into obvious contaminant contigs. However, there might be more complex situations, such as chimeric contigs with alternating genuine and contaminant segments. Decontaminating at the read level, if possible, should eliminate such unfavorable situations where sequence information from contaminant and target samples are intimately intertwined by an assembler.

To achieve this aim, Gautier proposes to use methods initially designed for the analysis of metagenomic data. This is pertinent since the decontamination process involves considering a sample as a mixture of different sources of DNA. The programs used here, CLARK and CLARK-L, are based on so-called k-mer analysis, meaning that the similarity between a read to annotate and a reference sequence is measured by how many sub-sequences (of length 31 base pairs for CLARK and 27 base pairs for CLARK-L) they share. This is notoriously more efficient than traditional sequence alignment algorithms when it comes to comparing a very large number of (most often unrelated) sequences. This is, therefore, a reference-based approach, in which the reads from a sample are assigned to previously sequenced genomes based on k-mer content.

This original approach is here specifically applied to the case of Drosophila suzukii, an invasive pest damaging fruit production in Europe and America. Fortunately, Drosophila is a genus of insects with abundant genomic resources, including high-quality reference genomes in dozens of species. Having calibrated and validated his pipeline using data sets of known origins, Gautier quantifies in each of 258 presumed D. suzukii samples the proportion of reads that likely belong to other species of fruit flies, or to fruit fly-associated microbes. This proportion is close to one in 16 samples, which clearly correspond to mis-labelled individuals. It is non-negligible in another ~10 samples, which really correspond to D. suzukii individuals. Most of these reads of unexpected origin are contaminants and should be filtered out. Interestingly, one D. suzukii sample contains a substantial proportion of reads from the closely related D. subpulchera, which might instead reflect a recent episode of gene flow between these two species. The approach, therefore, not only serves as a crucial technical step, but also has the potential to reveal biological processes.

Gautier's thorough, well-documented work will clearly benefit the ongoing and future research on D. suzuki, and Drosophila genomics in general. The author and reviewers rightfully note that, like any reference-based approach, this method is heavily dependent on the availability and quality of reference genomes - Drosophila being a favorable case. Building the reference database is a key step, and the interpretation of the output can only be made in the light of its content and gaps, as illustrated by Gautier's careful and detailed discussion of his numerous results. 

This pioneering study is a striking demonstration of the potential of metagenomic methods for the decontamination of high-throughput sequence data at the read level. The pipeline requires remarkably few computing resources, ensuring low carbon emission. I am looking forward to seeing it applied to a wide range of taxa and samples.

Reference

[1] Gautier Mathieu. Efficient k-mer based curation of raw sequence data: application in Drosophila suzukii. bioRxiv, 2023.04.18.537389​, ver. 2, peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2023.04.18.537389​