Prokaryotic antiviral systems, such as CRISPR-Cas and restriction-modification systems, provide defense against viruses through diverse mechanisms including intracellular signaling, chemical defense, and nucleotide depletion. However, bioinformatic tools and resources for identifying and cataloging these systems are still in development. The work by Tesson and colleagues (2024) presents a significant advancement in understanding the defense systems of prokaryotes. The authors have provided an update of their previously developed online service DefenseFinder, which helps to detect known antiviral systems in prokaryotes genomes (Tesson et al. 2022), plus three new databases: one serving as a wiki for defense systems, one housing experimentally determined and AlphaFold2-predicted structures, and a third one consisting of precomputed results from DefenseFinder. Users can analyze their own data through the user-friendly interface. This initiative will help promote a community-driven approach to sharing knowledge on antiphage systems, which is very useful given their complexity and diversity. The authors' commitment to maintaining an up-to-date platform and encouraging community contributions makes this resource accessible to both newcomers and experienced researchers in the rapidly growing field of defense system research. Experienced researchers will find that there are ways to contribute to the future expansion of these databases, while new users can easily access and use the platform. Overall, the updated DefenseFinder, as well as the other databases introduced in the manuscript, are well-suited  for researchers (both dry- and wet-lab ones) interested in antiphage defense. I am hopeful that the efforts by the authors will collectively create valuable online resources for researchers in this field and will foster an environment of open science and accessible bioinformatics tools.

References

Tesson F, Hervé A, Mordret E, Touchon M, d’Humières C, Cury J, Bernheim A (2022) Systematic and quantitative view of the antiviral arsenal of prokaryotes. Nature Communications, 13, 2561. https://doi.org/10.1038/s41467-022-30269-9

Tesson F, Planel R, Egorov A, Georjon H, Vaysset H, Brancotte B, Néron B, Mordret E, Atkinson G, Bernheim A, Cury J (2024) A comprehensive resource for exploring antiphage defense: DefenseFinder webservice, wiki and databases. bioRxiv, ver. 4 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2024.01.25.577194

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​

Any multicellular organism is a molecular mosaic with some somatic mutations accumulated between cell lineages. Big long-lived trees have nourished this imaginary of a somatic mosaic tree, from the observation of spectacular phenotypic mosaics and also because somatic mutations are expected to potentially be passed on to gametes in plants (review in Schoen and Schultz 2019). The lower cost of genome sequencing now offers the opportunity to tackle the issue and identify somatic mutations in trees.

However, when it comes to characterizing this somatic mosaic from genome sequences, things become much more difficult than one would think in the first place. What separates cell lineages ontogenetically, in cell division number, or in time? How to sample clonal cell populations? How do somatic mutations distribute in a population of cells in an organ or an organ sample? Should they be fixed heterozygotes in the sample of cells sequenced or be polymorphic? Do we indeed expect somatic mutations to be fixed? How should we identify and count somatic mutations?

To date, the detection of somatic mutations has mostly been done with a single variant caller in a given study, and we have little perspective on how different callers provide similar or different results. Some studies have used standard SNP callers that assumed a somatic mutation is fixed at the heterozygous state in the sample of cells, with an expected allele coverage ratio of 0.5, and less have used cancer callers, designed to detect mutations in a fraction of the cells in the sample. However, standard SNP callers detect mutations that deviate from a balanced allelic coverage, and different cancer callers can have different characteristics that should affect their outcomes.

In order to tackle these issues, Schmitt et al. (2022) conducted an extensive simulation analysis to compare different variant callers. Then, they reanalyzed two large published datasets on pedunculate oak, Quercus robur.  The analysis of in silico somatic mutations allowed the authors to evaluate the performance of different variant callers as a function of the allelic fraction of somatic mutations and the sequencing depth. They found one of the seven callers to provide better and more robust calls for a broad set of allelic fractions and sequencing depths. The reanalysis of published datasets in oaks with the most effective cancer caller of the in silico analysis allowed them to identify numerous low-frequency mutations that were missed in the original studies.

I recommend the study of Schmitt et al. (2022) first because it shows the benefit of using cancer callers in the study of somatic mutations, whatever the allelic fraction you are interested in at the end. You can select fixed heterozygotes if this is your ultimate target, but cancer callers allow you to have in addition a valuable overview of the allelic fractions of somatic mutations in your sample, and most do as well as SNP callers for fixed heterozygous mutations. In addition, Schmitt et al. (2022) provide the pipelines that allow investigating in silico data that should correspond to a given study design, encouraging to compare different variant callers rather than arbitrarily going with only one. We can anticipate that the study of somatic mutations in non-model species will increasingly attract attention now that multiple tissues of the same individual can be sequenced at low cost, and the study of Schmitt et al. (2022) paves the way for questioning and choosing the best variant caller for the question one wants to address.

References

Schoen DJ, Schultz ST (2019) Somatic Mutation and Evolution in Plants. Annual Review of Ecology, Evolution, and Systematics, 50, 49–73. https://doi.org/10.1146/annurev-ecolsys-110218-024955

Schmitt S, Leroy T, Heuertz M, Tysklind N (2022) Somatic mutation detection: a critical evaluation through simulations and reanalyses in oaks. bioRxiv, 2021.10.11.462798. ver. 4 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2021.10.11.462798

About twenty-five years after the sequencing of the first fungal genome and a dozen years after the first plant pathogenic fungi genomes were sequenced, unprecedented international efforts have led to an impressive collection of genomes available for the community of mycologists in international databases (Goffeau et al. 1996, Dean et al. 2005; Spatafora et al. 2017). For instance, to date, the Joint Genome Institute Mycocosm database has collected more than 2,100 fungal genomes over the fungal tree of life (https://mycocosm.jgi.doe.gov). Such resources are paving the way for comparative genomics, population genomics and phylogenomics to address a large panel of questions regarding the biology and the ecology of fungal species. Early on, population genomics applied to pathogenic fungi revealed a great diversity of genome content and organization and a wide variety of variants and rearrangements (Raffaele and Kamoun 2012, Hartmann 2022). Such plasticity raises questions about how to choose a representative genome to serve as an ideal reference to address pertinent biological questions.

Cryphonectria parasitica is a fungal pathogen that is infamous for the devastation of chestnut forests in North America after its accidental introduction more than a century ago (Anagnostakis 1987). Since then, it has been a quarantine species under surveillance in various parts of the world. As for other fungi causing diseases on forest trees, the study of adaptation to its host in the forest ecosystem and of its reproduction and dissemination modes is more complex than for crop-targeting pathogens. A first reference genome was published in 2020 for the chestnut blight fungus C. parasitica strain EP155 in the frame of an international project with the DOE JGI (Crouch et al. 2020). Another genome was then sequenced from the French isolate YVO003, which showed a few differences in the assembly suggesting possible rearrangements (Demené et al. 2019). Here the sequencing of a third isolate ESM015 from the native area of C. parasitica in Japan allows to draw broader comparative analysis and particularly to compare between native and introduced isolates (Demené et al. 2022).

Demené and collaborators report on a new genome sequence using up-to-date long-read sequencing technologies and they provide an improved genome assembly. Comparison with previously published C. parasitica genomes did not reveal dramatic changes in the overall chromosomal landscapes, but large rearrangements could be spotted. Despite these rearrangements, the genome content and organization – i.e. genes and repeats – remain stable, with a limited number of genes gains and losses. As in any fungal plant pathogen genome, the repertoire of candidate effectors predicted among secreted proteins was more particularly scrutinized. Such effector genes have previously been reported in other pathogens in repeat-enriched plastic genomic regions with accelerated evolutionary rates under the pressure of the host immune system (Raffaele and Kamoun 2012). Demené and collaborators established a list of priority candidate effectors in the C. parasitica gene catalog likely involved in the interaction with the host plant which will require more attention in future functional studies. Six major inter-chromosomal translocations were detected and are likely associated with double break strands repairs. The authors speculate on the possible effects that these translocations may have on gene organization and expression regulation leading to dramatic phenotypic changes in relation to introduction and invasion in new continents and the impact regarding sexual reproduction in this fungus (Demené et al. 2022).

I recommend this article not only because it is providing an improved assembly of a reference genome for C. parasitica, but also because it adds diversity in terms of genome references availability, with a third high-quality assembly. Such an effort in the tree pathology community for a pathogen under surveillance is of particular importance for future progress in post-genomic analysis, e.g. in further genomic population studies (Hartmann 2022). 

References

Anagnostakis SL (1987) Chestnut Blight: The Classical Problem of an Introduced Pathogen. Mycologia, 79, 23–37. https://doi.org/10.2307/3807741

Crouch JA, Dawe A, Aerts A, Barry K, Churchill ACL, Grimwood J, Hillman BI, Milgroom MG, Pangilinan J, Smith M, Salamov A, Schmutz J, Yadav JS, Grigoriev IV, Nuss DL (2020) Genome Sequence of the Chestnut Blight Fungus Cryphonectria parasitica EP155: A Fundamental Resource for an Archetypical Invasive Plant Pathogen. Phytopathology®, 110, 1180–1188. https://doi.org/10.1094/PHYTO-12-19-0478-A

Dean RA, Talbot NJ, Ebbole DJ, Farman ML, Mitchell TK, Orbach MJ, Thon M, Kulkarni R, Xu J-R, Pan H, Read ND, Lee Y-H, Carbone I, Brown D, Oh YY, Donofrio N, Jeong JS, Soanes DM, Djonovic S, Kolomiets E, Rehmeyer C, Li W, Harding M, Kim S, Lebrun M-H, Bohnert H, Coughlan S, Butler J, Calvo S, Ma L-J, Nicol R, Purcell S, Nusbaum C, Galagan JE, Birren BW (2005) The genome sequence of the rice blast fungus Magnaporthe grisea. Nature, 434, 980–986. https://doi.org/10.1038/nature03449

Demené A., Laurent B., Cros-Arteil S., Boury C. and Dutech C. 2022. Chromosomal rearrangements with stable repertoires of genes and transposable elements in an invasive forest-pathogenic fungus. bioRxiv, 2021.03.09.434572, ver.6 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2021.03.09.434572

Goffeau A, Barrell BG, Bussey H, Davis RW, Dujon B, Feldmann H, Galibert F, Hoheisel JD, Jacq C, Johnston M, Louis EJ, Mewes HW, Murakami Y, Philippsen P, Tettelin H, Oliver SG (1996) Life with 6000 Genes. Science, 274, 546–567. https://doi.org/10.1126/science.274.5287.546

Hartmann FE (2022) Using structural variants to understand the ecological and evolutionary dynamics of fungal plant pathogens. New Phytologist, 234, 43–49. https://doi.org/10.1111/nph.17907

Raffaele S, Kamoun S (2012) Genome evolution in filamentous plant pathogens: why bigger can be better. Nature Reviews Microbiology, 10, 417–430. https://doi.org/10.1038/nrmicro2790

Spatafora JW, Aime MC, Grigoriev IV, Martin F, Stajich JE, Blackwell M (2017) The Fungal Tree of Life: from Molecular Systematics to Genome-Scale Phylogenies. Microbiology Spectrum, 5, 5.5.03. https://doi.org/10.1128/microbiolspec.FUNK-0053-2016