Third-generation sequencing has revolutionised de novo genome assembly. Thanks to this technology, genome reference sequences have evolved from fragmented drafts to gapless, telomere-to-telomere genome assemblies. Long reads produced by Oxford Nanopore and PacBio technologies can span structural variants and resolve complex repetitive regions such as centromeres, unlocking previously inaccessible genomic information. Nowadays, many research groups can afford to sequence the genome of their working model using long reads. Nevertheless, genome assembly poses a significant computational challenge. Read length, quality, coverage and genomic features such as repeat content can affect assembly contiguity, accuracy, and completeness in almost unpredictable ways. Consequently, there is no best universal software or protocol for this task. Producing a high-quality assembly requires chaining several tools into pipelines and performing extensive comparisons between the assemblies obtained by different tool combinations to decide which one is the best. This task can be extremely challenging, as the number of tools available rises very rapidly, and thorough benchmarks cannot be updated and published at such a fast pace. 

In their paper, Orjuela and collaborators present CulebrONT [1], a universal pipeline that greatly contributes to overcoming these challenges and facilitates long-read genome assembly for all taxonomic groups. CulebrONT incorporates six commonly used assemblers and allows to perform assembly, circularization (if needed), polishing, and evaluation in a simple framework. One important aspect of CulebrONT is its modularity, which allows the activation or deactivation of specific tools, giving great flexibility to the user. Nevertheless, possibly the best feature of CulebrONT is the opportunity to benchmark the selected tool combinations based on the excellent report generated by the pipeline. This HTML report aggregates the output of several tools for quality evaluation of the assemblies (e.g. BUSCO [2] or QUAST [3]) generated by the different assemblers, in addition to the running time and configuration parameters. Such information is of great help to identify the best-suited pipeline, as exemplified by the authors using four datasets of different taxonomic origins. Finally, CulebrONT can handle multiple samples in parallel, which makes it a good solution for laboratories looking for multiple assemblies on a large scale. 

References

1. Orjuela J, Comte A, Ravel S, Charriat F, Vi T, Sabot F, Cunnac S (2022) CulebrONT: a streamlined long reads multi-assembler pipeline for prokaryotic and eukaryotic genomes. bioRxiv, 2021.07.19.452922, ver. 5 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2021.07.19.452922

2. Simão FA, Waterhouse RM, Ioannidis P, Kriventseva EV, Zdobnov EM (2015) BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics, 31, 3210–3212. https://doi.org/10.1093/bioinformatics/btv351

3. Gurevich A, Saveliev V, Vyahhi N, Tesler G (2013) QUAST: quality assessment tool for genome assemblies. Bioinformatics, 29, 1072–1075. https://doi.org/10.1093/bioinformatics/btt086

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

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

The genomics era has pushed forward our understanding of fungal biology. Much progress has been made in unraveling new gene functions and pathways, as well as the evolution or adaptation of fungi to their hosts or environments through population studies (Hartmann et al. 2019; Gladieux et al. 2018). Closing gaps more systematically in draft genomes using the most recent long-read technologies now seems the new standard, even with fungal species presenting complex genome structures (e.g. large and highly repetitive dikaryotic genomes; Duan et al. 2022). Understanding the genomic dynamics underlying host specialization in phytopathogenic fungi is of utmost importance as it may open new avenues to combat diseases. A strong host specialization is commonly observed for biotrophic and hemi-biotrophic fungal species or for necrotrophic fungi with a narrow host range, whereas necrotrophic fungi with broad host range are considered generalists (Liang and Rollins, 2018; Newman and Derbyshire, 2020). However, some degrees of specialization towards given hosts have been reported in generalist fungi and the underlying mechanisms remain to be determined.

Botrytis cinerea is a polyphagous necrotrophic phytopathogen with a particularly wide host range and it is notably responsible for grey mould disease on many fruits, such as tomato and grapevine. Because of its importance as a plant pathogen, its relatively small genome size and its taxonomical position, it has been targeted for early genome sequencing and a first reference genome was provided in 2011 (Amselem et al. 2011). Other genomes were subsequently sequenced for other strains, and most importantly a gapless assembled version of the initial reference genome B05.10 was provided to the community (van Kan et al. 2017). This genomic resource has supported advances in various aspects of the biology of B. cinerea such as the production of specialized metabolites, which plays an important role in host-plant colonization, or more recently in the production of small RNAs which interfere with the host immune system, representing a new class of non-proteinaceous virulence effectors (Dalmais et al. 2011; Weiberg et al. 2013).

In the present study, Simon et al. (2022) use PacBio long-read sequencing for Sl3 and Vv3 strains, which represent genetic clusters in B. cinerea populations found on tomato and grapevine. The authors combined these complete and high-quality genome assemblies with the B05.10 reference genome and population sequencing data to perform a comparative genomic analysis of specialization towards the two host plants. Transposable elements generate genomic diversity due to their mobile and repetitive nature and they are of utmost importance in the evolution of fungi as they deeply reshape the genomic landscape (Lorrain et al. 2021). Accessory chromosomes are also known drivers of adaptation in fungi (Möller and Stukenbrock, 2017). Here, the authors identify several genomic features such as the presence of different sets of accessory chromosomes, the presence of differentiated repertoires of transposable elements, as well as related small RNAs in the tomato and grapevine populations, all of which may be involved in host specialization. Whereas core chromosomes are highly syntenic between strains, an accessory chromosome validated by pulse-field electrophoresis is specific of the strains isolated from grapevine. Particularly, they show that two particular retrotransposons are discriminant between the strains and that they allow the production of small RNAs that may act as effectors. The discriminant accessory chromosome of the Vv3 strain harbors one of the unraveled retrotransposons as well as new genes of yet unidentified function.

I recommend this article because it perfectly illustrates how efforts put into generating reference genomic sequences of higher quality can lead to new discoveries and allow to build strong hypotheses about biology and evolution in fungi. Also, the study combines an up-to-date genomics approach with a classical methodology such as pulse-field electrophoresis to validate the presence of accessory chromosomes. A major input of this investigation of the genomic determinants of B. cinerea is that it provides solid hints for further analysis of host-specialization at the population level in a broad-scale phytopathogenic fungus.

References

Amselem J, Cuomo CA, Kan JAL van, Viaud M, Benito EP, Couloux A, Coutinho PM, Vries RP de, Dyer PS, Fillinger S, Fournier E, Gout L, Hahn M, Kohn L, Lapalu N, Plummer KM, Pradier J-M, Quévillon E, Sharon A, Simon A, Have A ten, Tudzynski B, Tudzynski P, Wincker P, Andrew M, Anthouard V, Beever RE, Beffa R, Benoit I, Bouzid O, Brault B, Chen Z, Choquer M, Collémare J, Cotton P, Danchin EG, Silva CD, Gautier A, Giraud C, Giraud T, Gonzalez C, Grossetete S, Güldener U, Henrissat B, Howlett BJ, Kodira C, Kretschmer M, Lappartient A, Leroch M, Levis C, Mauceli E, Neuvéglise C, Oeser B, Pearson M, Poulain J, Poussereau N, Quesneville H, Rascle C, Schumacher J, Ségurens B, Sexton A, Silva E, Sirven C, Soanes DM, Talbot NJ, Templeton M, Yandava C, Yarden O, Zeng Q, Rollins JA, Lebrun M-H, Dickman M (2011) Genomic Analysis of the Necrotrophic Fungal Pathogens Sclerotinia sclerotiorum and Botrytis cinerea. PLOS Genetics, 7, e1002230. https://doi.org/10.1371/journal.pgen.1002230

Dalmais B, Schumacher J, Moraga J, Le Pêcheur P, Tudzynski B, Collado IG, Viaud M (2011) The Botrytis cinerea phytotoxin botcinic acid requires two polyketide synthases for production and has a redundant role in virulence with botrydial. Molecular Plant Pathology, 12, 564–579. https://doi.org/10.1111/j.1364-3703.2010.00692.x

Duan H, Jones AW, Hewitt T, Mackenzie A, Hu Y, Sharp A, Lewis D, Mago R, Upadhyaya NM, Rathjen JP, Stone EA, Schwessinger B, Figueroa M, Dodds PN, Periyannan S, Sperschneider J (2022) Physical separation of haplotypes in dikaryons allows benchmarking of phasing accuracy in Nanopore and HiFi assemblies with Hi-C data. Genome Biology, 23, 84. https://doi.org/10.1186/s13059-022-02658-2

Gladieux P, Condon B, Ravel S, Soanes D, Maciel JLN, Nhani A, Chen L, Terauchi R, Lebrun M-H, Tharreau D, Mitchell T, Pedley KF, Valent B, Talbot NJ, Farman M, Fournier E (2018) Gene Flow between Divergent Cereal- and Grass-Specific Lineages of the Rice Blast Fungus Magnaporthe oryzae. mBio, 9, e01219-17. https://doi.org/10.1128/mBio.01219-17

Hartmann FE, Rodríguez de la Vega RC, Carpentier F, Gladieux P, Cornille A, Hood ME, Giraud T (2019) Understanding Adaptation, Coevolution, Host Specialization, and Mating System in Castrating Anther-Smut Fungi by Combining Population and Comparative Genomics. Annual Review of Phytopathology, 57, 431–457. https://doi.org/10.1146/annurev-phyto-082718-095947

Liang X, Rollins JA (2018) Mechanisms of Broad Host Range Necrotrophic Pathogenesis in Sclerotinia sclerotiorum. Phytopathology®, 108, 1128–1140. https://doi.org/10.1094/PHYTO-06-18-0197-RVW

Lorrain C, Oggenfuss U, Croll D, Duplessis S, Stukenbrock E (2021) Transposable Elements in Fungi: Coevolution With the Host Genome Shapes, Genome Architecture, Plasticity and Adaptation. In: Encyclopedia of Mycology (eds Zaragoza Ó, Casadevall A), pp. 142–155. Elsevier, Oxford. https://doi.org/10.1016/B978-0-12-819990-9.00042-1

Möller M, Stukenbrock EH (2017) Evolution and genome architecture in fungal plant pathogens. Nature Reviews Microbiology, 15, 756–771. https://doi.org/10.1038/nrmicro.2017.76

Newman TE, Derbyshire MC (2020) The Evolutionary and Molecular Features of Broad Host-Range Necrotrophy in Plant Pathogenic Fungi. Frontiers in Plant Science, 11. https://doi.org/10.3389/fpls.2020.591733

Simon A, Mercier A, Gladieux P, Poinssot B, Walker A-S, Viaud M (2022) Botrytis cinerea strains infecting grapevine and tomato display contrasted repertoires of accessory chromosomes, transposons and small RNAs. bioRxiv, 2022.03.07.483234, ver. 4 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2022.03.07.483234

Van Kan JAL, Stassen JHM, Mosbach A, Van Der Lee TAJ, Faino L, Farmer AD, Papasotiriou DG, Zhou S, Seidl MF, Cottam E, Edel D, Hahn M, Schwartz DC, Dietrich RA, Widdison S, Scalliet G (2017) A gapless genome sequence of the fungus Botrytis cinerea. Molecular Plant Pathology, 18, 75–89. https://doi.org/10.1111/mpp.12384

Weiberg A, Wang M, Lin F-M, Zhao H, Zhang Z, Kaloshian I, Huang H-D, Jin H (2013) Fungal Small RNAs Suppress Plant Immunity by Hijacking Host RNA Interference Pathways. Science, 342, 118–123. https://doi.org/10.1126/science.1239705

In the last two decades, microbial research in its different fields has been increasingly focusing on microbiome studies. These are defined as studies of complete assemblages of microorganisms in given environments and have been benefiting from increases in sequencing length, quality, and yield, coupled with ever-dropping prices per sequenced nucleotide. Alongside localized microbiome studies, several global collaborative efforts have emerged, including the Human Microbiome Project [1], the Earth Microbiome Project [2], the Extreme Microbiome Project, and MetaSUB [3].

Coupled with the development of sequencing technologies and the ever-increasing amount of data output, multiple standalone or online bioinformatic tools have been designed to analyze these data. Often these tools have been focusing on either of two main tasks: 1) Community analysis, providing information on the organisms present in the microbiome, or 2) Functionality, in the case of shotgun metagenomic data, providing information on the metabolic potential of the microbiome. Bridging between the two types of data, often extracted from the same dataset, is typically a daunting task that has been addressed by a handful of tools only.

The extent of tools and approaches to analyze microbiome data is great and may be overwhelming to researchers new to microbiome or bioinformatic studies. In their paper “A primer and discussion on DNA-based microbiome data and related bioinformatics analyses”, Douglas and Langille [4] guide us through the different sequencing approaches useful for microbiome studies. alongside their advantages and caveats and a selection of tools to analyze these data, coupled with examples from their own field of research.

Standing out in their primer-style review is the emphasis on the coupling between taxonomic/phylogenetic identification of the organisms and their functionality. This type of analysis, though highly important to understand the role of different microorganisms in an environment as well as to identify potential functional redundancy, is often not conducted. For this, the authors identify two approaches. The first, using shotgun metagenomics, has higher chances of attributing a function to the correct taxon. The second, using amplicon sequencing of marker genes, allows for a deeper coverage of the microbiome at a lower cost, and extrapolates the amplicon data to close relatives with a sequenced genome. As clearly stated, this approach makes the leap between taxonomy and functionality and has been shown to be erroneous in cases where the core genome of the bacterial genus or family does not encompass the functional diversity of the different included species. This practice was already common before the genomic era, but its accuracy is improving thanks to the increasing availability of sequenced reference genomes from cultures, environmentally picked single cells or metagenome-assembled genome.

In addition to their description of standalone tools useful for linking taxonomy and functionality, one should mention the existence of online tools that may appeal to researchers who do not have access to adequate bioinformatics infrastructure. Among these are the Integrated Microbial Genomes and Microbiomes (IMG) from the Joint Genome Institute [5], KBase [6] and MG-RAST [7].

A second important point arising from this review is the need for standardization in microbiome data analyses and the complexity of achieving this. As Douglas and Langille [4] state, this has been previously addressed, highlighting the variability in results obtained with different tools. It is often the case that papers describing new bioinformatic tools display their superiority relative to existing alternatives, potentially misleading newcomers to the field that the newest tool is the best and only one to be used. This is often not the case, and while benchmarking against well-defined datasets serves as a powerful testing tool, “real-life” samples are often not comparable. Thus, as done here, future primer-like reviews should highlight possible cross-field caveats, encouraging researchers to employ and test several approaches and validate their results whenever possible.

In summary, Douglas and Langille [4] offer both the novice and experienced researcher a detailed guide along the paths of microbiome data analysis, accompanied by informative background information, suggested tools with which analyses can be started, and an insightful view on where the field should be heading.

References

[1]  Turnbaugh PJ, Ley RE, Hamady M, Fraser-Liggett CM, Knight R, Gordon JI (2007) The Human Microbiome Project. Nature, 449, 804–810. https://doi.org/10.1038/nature06244

[2]  Gilbert JA, Jansson JK, Knight R (2014) The Earth Microbiome project: successes and aspirations. BMC Biology, 12, 69. https://doi.org/10.1186/s12915-014-0069-1

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[4]  Douglas GM, Langille MGI (2021) A primer and discussion on DNA-based microbiome data and related bioinformatics analyses. OSF Preprints, ver. 4 peer-reviewed and recommended by Peer Community In Genomics. https://doi.org/10.31219/osf.io/3dybg

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