|Id||Title▲||Authors||Abstract||Picture||Thematic fields||Recommender||Reviewers||Submission date|
06 May 2022
A deep dive into genome assemblies of non-vertebrate animalsNadège Guiglielmoni, Ramón Rivera-Vicéns, Romain Koszul, Jean-François Flot https://doi.org/10.20944/preprints202111.0170.v3
Diving, and even digging, into the wild jungle of annotation pathways for non-vertebrate animalsRecommended by Francois Sabot based on reviews by Yann Bourgeois, Cécile Monat, Valentina Peona and Benjamin Istace
In their paper, Guiglielmoni et al. propose we pick up our snorkels and palms and take "A deep dive into genome assemblies of non-vertebrate animals" (1). Indeed, while numerous assembly-related tools were developed and tested for human genomes (or at least vertebrates such as mice), very few were tested on non-vertebrate animals so far. Moreover, most of the benchmarks are aimed at raw assembly tools, and very few offer a guide from raw reads to an almost finished assembly, including quality control and phasing.
This huge and exhaustive review starts with an overview of the current sequencing technologies, followed by the theory of the different approaches for assembly and their implementation. For each approach, the authors present some of the most representative tools, as well as the limits of the approach.
The authors additionally present all the steps required to obtain an almost complete assembly at a chromosome-scale, with all the different technologies currently available for scaffolding, QC, and phasing, and the way these tools can be applied to non-vertebrates animals. Finally, they propose some useful advice on the choice of the different approaches (but not always tools, see below), and advocate for a robust genome database with all information on the way the assembly was obtained.
This review is a very complete one for now and is a very good starting point for any student or scientist interested to start working on genome assembly, from either model or non-model organisms. However, the authors do not provide a list of tools or a benchmark of them as a recommendation. Why? Because such a proposal may be obsolete in less than a year.... Indeed, with the explosion of the 3rd generation of sequencing technology, assembly tools (from different steps) are constantly evolving, and their relative performance increases on a monthly basis. In addition, some tools are really efficient at the time of a review or of an article, but are not further developed later on, and thus will not evolve with the technology. We have all seen it with wonderful tools such as Chiron (2) or TopHat (3), which were very promising ones, but cannot be developed further due to the stop of the project, the end of the contract of the post-doc in charge of the development, or the decision of the developer to switch to another paradigm. Such advice would, therefore, need to be constantly updated.
Thus, the manuscript from Guiglielmoni et al will be an almost intemporal one (up to the next sequencing revolution at last), and as they advocated for a more informed genome database, I think we should consider a rolling benchmarking system (tools, genome and sequence dataset) allowing to keep the performance of the tools up-to-date, and to propose the best set of assembly tools for a given type of genome.
1. Guiglielmoni N, Rivera-Vicéns R, Koszul R, Flot J-F (2022) A Deep Dive into Genome Assemblies of Non-vertebrate Animals. Preprints, 2021110170, ver. 3 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.20944/preprints202111.0170
2. Teng H, Cao MD, Hall MB, Duarte T, Wang S, Coin LJM (2018) Chiron: translating nanopore raw signal directly into nucleotide sequence using deep learning. GigaScience, 7, giy037. https://doi.org/10.1093/gigascience/giy037
3. Trapnell C, Pachter L, Salzberg SL (2009) TopHat: discovering splice junctions with RNA-Seq. Bioinformatics, 25, 1105–1111. https://doi.org/10.1093/bioinformatics/btp120
|A deep dive into genome assemblies of non-vertebrate animals||Nadège Guiglielmoni, Ramón Rivera-Vicéns, Romain Koszul, Jean-François Flot||<p style="text-align: justify;">Non-vertebrate species represent about ∼95% of known metazoan (animal) diversity. They remain to this day relatively unexplored genetically, but understanding their genome structure and function is pivotal for expan...||Bioinformatics, Evolutionary genomics||Francois Sabot||Valentina Peona, Benjamin Istace, Cécile Monat, Yann Bourgeois||2021-11-10 17:47:31||View|
09 Oct 2020
An evaluation of pool-sequencing transcriptome-based exon capture for population genomics in non-model speciesEmeline Deleury, Thomas Guillemaud, Aurélie Blin & Eric Lombaert https://doi.org/10.1101/583534
Assessing a novel sequencing-based approach for population genomics in non-model speciesRecommended by Thomas Derrien and Sebastian E. Ramos-Onsins based on reviews by Valentin Wucher and 1 anonymous reviewer
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.
 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
|An evaluation of pool-sequencing transcriptome-based exon capture for population genomics in non-model species||Emeline Deleury, Thomas Guillemaud, Aurélie Blin & Eric Lombaert||<p>Exon capture coupled to high-throughput sequencing constitutes a cost-effective technical solution for addressing specific questions in evolutionary biology by focusing on expressed regions of the genome preferentially targeted by selection. Tr...||Bioinformatics, Population genomics||Thomas Derrien||2020-02-26 09:21:11||View|
23 Aug 2022
A novel lineage of the Capra genus discovered in the Taurus Mountains of Turkey using ancient genomicsKevin G. Daly, Benjamin S. Arbuckle, Conor Rossi, Valeria Mattiangeli, Phoebe A. Lawlor, Marjan Mashkour, Eberhard Sauer, Joséphine Lesur, Levent Atici, Cevdet Merih Erek, Daniel G. Bradley https://doi.org/10.1101/2022.04.08.487619
Goat ancient DNA analysis unveils a new lineage that may have hybridized with domestic goatsRecommended by Laura Botigué based on reviews by Torsten Günther and 1 anonymous reviewer
The genomic analysis of ancient remains has revolutionized the study of the past over the last decade. On top of the discoveries related to human evolution, plant and animal archaeogenomics has been used to gain new insights into the domestication process and the dispersal of domestic forms.
In this study, Daly and colleagues analyse the genomic data from seven goat specimens from the Epipalaeolithic recovered from the Direkli Cave in the Taurus Mountains in southern Turkey. They also generate new genomic data from Capra lineages across the phylogeny, contributing to the availability of genomic resources for this genus. Analysis of the ancient remains is compared to modern genomic variability and sheds light on the complexity of the Tur wild Capra lineages and their relationship with domestic goats and their wild ancestors.
Authors find that during the Late Pleistocene in the Taurus Mountains wild goats from the Tur lineage, today restricted to the Caucasus region, were not rare and cohabited with Bezoar, the wild goats that are the ancestors of domestic goats. They identify the Direkli Cave specimens as a lineage separate from the
A modified D statistic, Dex, is developed to examine the contribution of the ancient Tur lineage in domestic goats through time and space. Dex measures the relative degree of allele sharing, derived specifically in a selected genome or group of genomes, and may have some utility in genera with complex admixture histories or admixture from ghost lineages. Results confirm that Neolithic European goat had an excess of allele sharing with this ancient Tur lineage, something that is absent in contemporary goats eastwards or in modern goats.
Interspecific gene flow is not uncommon among mammals, but the case of Capra has the additional motivation of understanding the origins of the domestic species. This work uncovers an ancient Tur lineage that is different from the modern ones and is additionally found in another geographic area. Furthermore, evidence shows that this ancient lineage exhibits substantial amounts of allele sharing with the wild ancestor of the domestic goat, but also with the Neolithic Eurasian domestic goats, highlighting the complexity of the domestication process.
This work has also important implications in understanding the effect of over-hunting and habitat disruption during the Anthropocene on the evolution of the Capra genus. The availability of more ancient specimens and better coverage of the modern genomic variability can help quantifying the lineages that went lost and identify the causes of their extinction.
This work is limited by the current availability of whole genomes from modern Capra specimens, but pieces of evidence as well that an effort is needed to obtain more genomic data from ancient goats from different geographic ranges to determine to what extent these lineages contributed to goat domestication.
Daly KG, Arbuckle BS, Rossi C, Mattiangeli V, Lawlor PA, Mashkour M, Sauer E, Lesur J, Atici L, Cevdet CM and Bradley DG (2022) A novel lineage of the Capra genus discovered in the Taurus Mountains of Turkey using ancient genomics. bioRxiv, 2022.04.08.487619, ver. 5 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2022.04.08.487619
|A novel lineage of the Capra genus discovered in the Taurus Mountains of Turkey using ancient genomics||Kevin G. Daly, Benjamin S. Arbuckle, Conor Rossi, Valeria Mattiangeli, Phoebe A. Lawlor, Marjan Mashkour, Eberhard Sauer, Joséphine Lesur, Levent Atici, Cevdet Merih Erek, Daniel G. Bradley||<p>Direkli Cave, located in the Taurus Mountains of southern Turkey, was occupied by Late Epipaleolithic hunters-gatherers for the seasonal hunting and processing of game including large numbers of wild goats. We report genomic data from new and p...||Evolutionary genomics, Population genomics, Vertebrates||Laura Botigué||2022-04-15 12:05:47||View|
06 Jul 2021
A pipeline to detect the relationship between transposable elements and adjacent genes in host genomesCaroline Meguerditchian, Ayse Ergun, Veronique Decroocq, Marie Lefebvre, Quynh-Trang Bui https://doi.org/10.1101/2021.02.25.432867
A new tool to cross and analyze TE and gene annotationsRecommended by Emmanuelle Lerat based on reviews by 2 anonymous reviewers
Transposable elements (TEs) are important components of genomes. Indeed, they are now recognized as having a major role in gene and genome evolution (Biémont 2010). In particular, several examples have shown that the presence of TEs near genes may influence their functioning, either by recruiting particular epigenetic modifications (Guio et al. 2018) or by directly providing new regulatory sequences allowing new expression patterns (Chung et al. 2007; Sundaram et al. 2014). Therefore, the study of the interaction between TEs and their host genome requires tools to easily cross-annotate both types of entities. In particular, one needs to be able to identify all TEs located in the close vicinity of genes or inside them. Such task may not always be obvious for many biologists, as it requires informatics knowledge to develop their own script codes.
In their work, Meguerdichian et al. (2021) propose a command-line pipeline that takes as input the annotations of both genes and TEs for a given genome, then detects and reports the positional relationships between each TE insertion and their closest genes. The results are processed into an R script to provide tables displaying some statistics and graphs to visualize these relationships.
This tool has the potential to be very useful for performing preliminary analyses before studying the impact of TEs on gene functioning, especially for biologists. Indeed, it makes it possible to identify genes close to TE insertions. These identified genes could then be specifically considered in order to study in more detail the link between the presence of TEs and their functioning. For example, the identification of TEs close to genes may allow to determine their potential role on gene expression.
Biémont C (2010). A brief history of the status of transposable elements: from junk DNA to major players in evolution. Genetics, 186, 1085–1093. https://doi.org/10.1534/genetics.110.124180
Chung H, Bogwitz MR, McCart C, Andrianopoulos A, ffrench-Constant RH, Batterham P, Daborn PJ (2007). Cis-regulatory elements in the Accord retrotransposon result in tissue-specific expression of the Drosophila melanogaster insecticide resistance gene Cyp6g1. Genetics, 175, 1071–1077. https://doi.org/10.1534/genetics.106.066597
Guio L, Vieira C, González J (2018). Stress affects the epigenetic marks added by natural transposable element insertions in Drosophila melanogaster. Scientific Reports, 8, 12197. https://doi.org/10.1038/s41598-018-30491-w
Meguerditchian C, Ergun A, Decroocq V, Lefebvre M, Bui Q-T (2021). A pipeline to detect the relationship between transposable elements and adjacent genes in host genomes. bioRxiv, 2021.02.25.432867, ver. 4 peer-reviewed and recommended by Peer Community In Genomics. https://doi.org/10.1101/2021.02.25.432867
Sundaram V, Cheng Y, Ma Z, Li D, Xing X, Edge P, Snyder MP, Wang T (2014). Widespread contribution of transposable elements to the innovation of gene regulatory networks. Genome Research, 24, 1963–1976. https://doi.org/10.1101/gr.168872.113
|A pipeline to detect the relationship between transposable elements and adjacent genes in host genomes||Caroline Meguerditchian, Ayse Ergun, Veronique Decroocq, Marie Lefebvre, Quynh-Trang Bui||<p>Understanding the relationship between transposable elements (TEs) and their closest positional genes in the host genome is a key point to explore their potential role in genome evolution. Transposable elements can regulate and affect gene expr...||Bioinformatics, Viruses and transposable elements||Emmanuelle Lerat||2021-03-03 15:08:34||View|
05 May 2021
A primer and discussion on DNA-based microbiome data and related bioinformatics analysesGavin M. Douglas and Morgan G. I. Langille https://doi.org/10.31219/osf.io/3dybg
A hitchhiker’s guide to DNA-based microbiome analysisRecommended by Danny Ionescu based on reviews by Nicolas Pollet, Rafael Cuadrat and 1 anonymous reviewer
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 , the Earth Microbiome Project , the Extreme Microbiome Project, and MetaSUB .
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  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 , KBase  and MG-RAST .
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  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  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.
 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
 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
 Mason C, Afshinnekoo E, Ahsannudin S, Ghedin E, Read T, Fraser C, Dudley J, Hernandez M, Bowler C, Stolovitzky G, Chernonetz A, Gray A, Darling A, Burke C, Łabaj PP, Graf A, Noushmehr H, Moraes s., Dias-Neto E, Ugalde J, Guo Y, Zhou Y, Xie Z, Zheng D, Zhou H, Shi L, Zhu S, Tang A, Ivanković T, Siam R, Rascovan N, Richard H, Lafontaine I, Baron C, Nedunuri N, Prithiviraj B, Hyat S, Mehr S, Banihashemi K, Segata N, Suzuki H, Alpuche Aranda CM, Martinez J, Christopher Dada A, Osuolale O, Oguntoyinbo F, Dybwad M, Oliveira M, Fernandes A, Oliveira M, Fernandes A, Chatziefthimiou AD, Chaker S, Alexeev D, Chuvelev D, Kurilshikov A, Schuster S, Siwo GH, Jang S, Seo SC, Hwang SH, Ossowski S, Bezdan D, Udekwu K, Udekwu K, Lungjdahl PO, Nikolayeva O, Sezerman U, Kelly F, Metrustry S, Elhaik E, Gonnet G, Schriml L, Mongodin E, Huttenhower C, Gilbert J, Hernandez M, Vayndorf E, Blaser M, Schadt E, Eisen J, Beitel C, Hirschberg D, Schriml L, Mongodin E, The MetaSUB International Consortium (2016) The Metagenomics and Metadesign of the Subways and Urban Biomes (MetaSUB) International Consortium inaugural meeting report. Microbiome, 4, 24. https://doi.org/10.1186/s40168-016-0168-z
 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
 Chen I-MA, Markowitz VM, Chu K, Palaniappan K, Szeto E, Pillay M, Ratner A, Huang J, Andersen E, Huntemann M, Varghese N, Hadjithomas M, Tennessen K, Nielsen T, Ivanova NN, Kyrpides NC (2017) IMG/M: integrated genome and metagenome comparative data analysis system. Nucleic Acids Research, 45, D507–D516. https://doi.org/10.1093/nar/gkw929
 Arkin AP, Cottingham RW, Henry CS, Harris NL, Stevens RL, Maslov S, Dehal P, Ware D, Perez F, Canon S, Sneddon MW, Henderson ML, Riehl WJ, Murphy-Olson D, Chan SY, Kamimura RT, Kumari S, Drake MM, Brettin TS, Glass EM, Chivian D, Gunter D, Weston DJ, Allen BH, Baumohl J, Best AA, Bowen B, Brenner SE, Bun CC, Chandonia J-M, Chia J-M, Colasanti R, Conrad N, Davis JJ, Davison BH, DeJongh M, Devoid S, Dietrich E, Dubchak I, Edirisinghe JN, Fang G, Faria JP, Frybarger PM, Gerlach W, Gerstein M, Greiner A, Gurtowski J, Haun HL, He F, Jain R, Joachimiak MP, Keegan KP, Kondo S, Kumar V, Land ML, Meyer F, Mills M, Novichkov PS, Oh T, Olsen GJ, Olson R, Parrello B, Pasternak S, Pearson E, Poon SS, Price GA, Ramakrishnan S, Ranjan P, Ronald PC, Schatz MC, Seaver SMD, Shukla M, Sutormin RA, Syed MH, Thomason J, Tintle NL, Wang D, Xia F, Yoo H, Yoo S, Yu D (2018) KBase: The United States Department of Energy Systems Biology Knowledgebase. Nature Biotechnology, 36, 566–569. https://doi.org/10.1038/nbt.4163
 Wilke A, Bischof J, Gerlach W, Glass E, Harrison T, Keegan KP, Paczian T, Trimble WL, Bagchi S, Grama A, Chaterji S, Meyer F (2016) The MG-RAST metagenomics database and portal in 2015. Nucleic Acids Research, 44, D590–D594. https://doi.org/10.1093/nar/gkv1322
|A primer and discussion on DNA-based microbiome data and related bioinformatics analyses||Gavin M. Douglas and Morgan G. I. Langille||<p style="text-align: justify;">The past decade has seen an eruption of interest in profiling microbiomes through DNA sequencing. The resulting investigations have revealed myriad insights and attracted an influx of researchers to the research are...||Bioinformatics, Metagenomics||Danny Ionescu||2021-02-17 00:26:46||View|
24 Sep 2020
A rapid and simple method for assessing and representing genome sequence relatednessM Briand, M Bouzid, G Hunault, M Legeay, M Fischer-Le Saux, M Barret https://doi.org/10.1101/569640
A quick alternative method for resolving bacterial taxonomy using short identical DNA sequences in genomes or metagenomesRecommended by B. Jesse Shapiro based on reviews by Gavin Douglas and 1 anonymous reviewer
The bacterial species problem can be summarized as follows: bacteria recombine too little, and yet too much (Shapiro 2019).
Arevalo P, VanInsberghe D, Elsherbini J, Gore J, Polz MF (2019) A Reverse Ecology Approach Based on a Biological Definition of Microbial Populations. Cell, 178, 820-834.e14. https://doi.org/10.1016/j.cell.2019.06.033
|A rapid and simple method for assessing and representing genome sequence relatedness||M Briand, M Bouzid, G Hunault, M Legeay, M Fischer-Le Saux, M Barret||<p>Coherent genomic groups are frequently used as a proxy for bacterial species delineation through computation of overall genome relatedness indices (OGRI). Average nucleotide identity (ANI) is a widely employed method for estimating relatedness ...||Bioinformatics, Metagenomics||B. Jesse Shapiro||Gavin Douglas||2019-11-07 16:37:56||View|
15 Dec 2022
Botrytis cinerea strains infecting grapevine and tomato display contrasted repertoires of accessory chromosomes, transposons and small RNAsAdeline Simon, Alex Mercier, Pierre Gladieux, Benoit Poinssot, Anne-Sophie Walker, Muriel Viaud https://doi.org/10.1101/2022.03.07.483234
Exploring genomic determinants of host specialization in Botrytis cinereaRecommended by Sebastien Duplessis based on reviews by Cecile Lorrain and Thorsten Langner
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.
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
|Botrytis cinerea strains infecting grapevine and tomato display contrasted repertoires of accessory chromosomes, transposons and small RNAs||Adeline Simon, Alex Mercier, Pierre Gladieux, Benoit Poinssot, Anne-Sophie Walker, Muriel Viaud||<p style="text-align: justify;">The fungus <em>Botrytis cinerea</em> is a polyphagous pathogen that encompasses multiple host-specialized lineages. While several secreted proteins, secondary metabolites and retrotransposons-derived small RNAs have...||Fungi, Structural genomics, Viruses and transposable elements||Sebastien Duplessis||Cecile Lorrain, Thorsten Langner||2022-03-15 11:15:48||View|
23 Mar 2022
Chromosomal rearrangements with stable repertoires of genes and transposable elements in an invasive forest-pathogenic fungusArthur Demene, Benoit Laurent, Sandrine Cros-Arteil, Christophe Boury, Cyril Dutech https://doi.org/10.1101/2021.03.09.434572
Comparative genomics in the chestnut blight fungus Cryphonectria parasitica reveals large chromosomal rearrangements and a stable genome organizationRecommended by Sebastien Duplessis based on reviews by Benjamin Schwessinger and 1 anonymous reviewer
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).
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
|Chromosomal rearrangements with stable repertoires of genes and transposable elements in an invasive forest-pathogenic fungus||Arthur Demene, Benoit Laurent, Sandrine Cros-Arteil, Christophe Boury, Cyril Dutech||<p style="text-align: justify;">Chromosomal rearrangements have been largely described among eukaryotes, and may have important consequences on evolution of species. High genome plasticity has been often reported in Fungi, which may explain their ...||Evolutionary genomics, Fungi||Sebastien Duplessis||2021-03-12 14:18:20||View|
12 Jul 2022
Chromosome-level genome assembly and annotation of two lineages of the ant Cataglyphis hispanica: steppingstones towards genomic studies of hybridogenesis and thermal adaptation in desert antsHugo Darras, Natalia de Souza Araujo, Lyam Baudry, Nadège Guiglielmoni, Pedro Lorite, Martial Marbouty, Fernando Rodriguez, Irina Arkhipova, Romain Koszul, Jean-François Flot, Serge Aron https://doi.org/10.1101/2022.01.07.475286
A genomic resource for ants, and moreRecommended by Nadia Ponts based on reviews by Isabel Almudi and Nicolas Nègre
The ant species Cataglyphis hispanica is remarkably well adapted to arid habitats of the Iberian Peninsula where two hybridogenetic lineages co-occur, i.e., queens mating with males from the other lineage produce only non-reproductive hybrid workers whereas reproductive males and females are produced by parthenogenesis (Lavanchy and Schwander, 2019). For these two reasons, the genomes of these lineages, Chis1 and Chis2, are potential gold mines to explore the genetic bases of thermal adaptation and the evolution of alternative reproductive modes.
Nowadays, sequencing technology enables assembling all kinds of genomes provided genomic DNA can be extracted. More difficult to achieve is high-quality assemblies with just as high-quality annotations that are readily available to the community to be used and re-used at will (Byrne et al., 2019; Salzberg, 2019). The challenge was successfully completed by Darras and colleagues, the generated resource being fully available to the community, including scripts and command lines used to obtain the proposed results.
The authors particularly describe that lineage Chis2 has 27 chromosomes, against 26 or 27 for lineage Chis1, with a Robertsonian translocation identified by chromosome conformation capture (Duan et al., 2010, 2012) in the two Queens sequenced. Transcript-supported gene annotation provided 11,290 high-quality gene models. In addition, an ant-tailored annotation pipeline identified 56 different families of repetitive elements in both Chis1 and Chis2 lineages of C. hispanica spread in a little over 15 % of the genome. Altogether, the genomes of Chis1 and Chis2 are highly similar and syntenic, with some level of polymorphism raising questions about their evolutionary story timeline. In particular, the uniform distribution of polymorphisms along the genomes shakes up a previous hypothesis of hybridogenetic lineage pairs determined by ancient non-recombining regions (Linksvayer, Busch and Smith, 2013).
I recommend this paper because the science behind is both solid and well-explained. The provided resource is of high quality, and accompanied by a critical exploration of the perspectives brought by the results. These genomes are excellent resources to now go further in exploring the possible events at the genome level that accompanied the remarkable thermal adaptation of the ants Cataglyphis, as well as insights into the genetics of hybridogenetic lineages.
Beyond the scientific value of the resources and insights provided by the work performed, I also recommend this article because it is an excellent example of Open Science (Allen and Mehler, 2019; Sarabipour et al., 2019), all data methods and tools being fully and easily accessible to whoever wants/needs it.
Allen C, Mehler DMA (2019) Open science challenges, benefits and tips in early career and beyond. PLOS Biology, 17, e3000246. https://doi.org/10.1371/journal.pbio.3000246
Byrne A, Cole C, Volden R, Vollmers C (2019) Realizing the potential of full-length transcriptome sequencing. Philosophical Transactions of the Royal Society B: Biological Sciences, 374, 20190097. https://doi.org/10.1098/rstb.2019.0097
Darras H, de Souza Araujo N, Baudry L, Guiglielmoni N, Lorite P, Marbouty M, Rodriguez F, Arkhipova I, Koszul R, Flot J-F, Aron S (2022) Chromosome-level genome assembly and annotation of two lineages of the ant Cataglyphis hispanica: stepping stones towards genomic studies of hybridogenesis and thermal adaptation in desert ants. bioRxiv, 2022.01.07.475286, ver. 3 peer-reviewed and recommended by Peer community in Genomics. https://doi.org/10.1101/2022.01.07.475286
Duan Z, Andronescu M, Schutz K, Lee C, Shendure J, Fields S, Noble WS, Anthony Blau C (2012) A genome-wide 3C-method for characterizing the three-dimensional architectures of genomes. Methods, 58, 277–288. https://doi.org/10.1016/j.ymeth.2012.06.018
Duan Z, Andronescu M, Schutz K, McIlwain S, Kim YJ, Lee C, Shendure J, Fields S, Blau CA, Noble WS (2010) A three-dimensional model of the yeast genome. Nature, 465, 363–367. https://doi.org/10.1038/nature08973
Lavanchy G, Schwander T (2019) Hybridogenesis. Current Biology, 29, R9–R11. https://doi.org/10.1016/j.cub.2018.11.046
Linksvayer TA, Busch JW, Smith CR (2013) Social supergenes of superorganisms: Do supergenes play important roles in social evolution? BioEssays, 35, 683–689. https://doi.org/10.1002/bies.201300038
Salzberg SL (2019) Next-generation genome annotation: we still struggle to get it right. Genome Biology, 20, 92. https://doi.org/10.1186/s13059-019-1715-2
Sarabipour S, Debat HJ, Emmott E, Burgess SJ, Schwessinger B, Hensel Z (2019) On the value of preprints: An early career researcher perspective. PLOS Biology, 17, e3000151. https://doi.org/10.1371/journal.pbio.3000151
|Chromosome-level genome assembly and annotation of two lineages of the ant Cataglyphis hispanica: steppingstones towards genomic studies of hybridogenesis and thermal adaptation in desert ants||Hugo Darras, Natalia de Souza Araujo, Lyam Baudry, Nadège Guiglielmoni, Pedro Lorite, Martial Marbouty, Fernando Rodriguez, Irina Arkhipova, Romain Koszul, Jean-François Flot, Serge Aron||<p style="text-align: justify;"><em>Cataglyphis</em> are thermophilic ants that forage during the day when temperatures are highest and sometimes close to their critical thermal limit. Several Cataglyphis species have evolved unusual reproductive ...||Evolutionary genomics||Nadia Ponts||Nicolas Nègre, Isabel Almudi||2022-01-13 16:47:30||View|
11 Sep 2023
COVFlow: phylodynamics analyses of viruses from selected SARS-CoV-2 genome sequencesGonché Danesh, Corentin Boennec, Laura Verdurme, Mathilde Roussel, Sabine Trombert-Paolantoni, Benoit Visseaux, Stephanie Haim-Boukobza, Samuel Alizon https://doi.org/10.1101/2022.06.17.496544
A pipeline to select SARS-CoV-2 sequences for reliable phylodynamic analysesRecommended by Emmanuelle Lerat based on reviews by Gabriel Wallau and Bastien Boussau
Phylodynamic approaches enable viral genetic variation to be tracked over time, providing insight into pathogen phylogenetic relationships and epidemiological dynamics. These are important methods for monitoring viral spread, and identifying important parameters such as transmission rate, geographic origin and duration of infection . This knowledge makes it possible to adjust public health measures in real-time and was important in the case of the COVID-19 pandemic . However, these approaches can be complicated to use when combining a very large number of sequences. This was particularly true during the COVID-19 pandemic, when sequencing data representing millions of entire viral genomes was generated, with associated metadata enabling their precise identification.
Danesh et al.  present a bioinformatics pipeline, CovFlow, for selecting relevant sequences according to user-defined criteria to produce files that can be used directly for phylodynamic analyses. The selection of sequences first involves a quality filter on the size of the sequences and the absence of unresolved bases before being able to make choices based on the associated metadata. Once the sequences are selected, they are aligned and a time-scaled phylogenetic tree is inferred. An output file in a format directly usable by BEAST 2  is finally generated.
To illustrate the use of the pipeline, Danesh et al.  present an analysis of the Delta variant in two regions of France. They observed a delay in the start of the epidemic depending on the region. In addition, they identified genetic variation linked to the start of the school year and the extension of vaccination, as well as the arrival of a new variant. This tool will be of major interest to researchers analysing SARS-CoV-2 sequencing data, and a number of future developments are planned by the authors.
 Baele G, Dellicour S, Suchard MA, Lemey P, Vrancken B. 2018. Recent advances in computational phylodynamics. Curr Opin Virol. 31:24-32. https://doi.org/10.1016/j.coviro.2018.08.009
 Attwood SW, Hill SC, Aanensen DM, Connor TR, Pybus OG. 2022. Phylogenetic and phylodynamic approaches to understanding and combating the early SARS-CoV-2 pandemic. Nat Rev Genet. 23:547-562. https://doi.org/10.1038/s41576-022-00483-8
 Danesh G, Boennec C, Verdurme L, Roussel M, Trombert-Paolantoni S, Visseaux B, Haim-Boukobza S, Alizon S. 2023. COVFlow: phylodynamics analyses of viruses from selected SARS-CoV-2 genome sequences. bioRxiv, ver. 7 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2022.06.17.496544
 Bouckaert R, Heled J, Kühnert D, Vaughan T, Wu C-H et al. 2014. BEAST 2: a software platform for Bayesian evolutionary analysis. PLoS Comput Biol 10: e1003537. https://doi.org/10.1371/journal.pcbi.1003537
|COVFlow: phylodynamics analyses of viruses from selected SARS-CoV-2 genome sequences||Gonché Danesh, Corentin Boennec, Laura Verdurme, Mathilde Roussel, Sabine Trombert-Paolantoni, Benoit Visseaux, Stephanie Haim-Boukobza, Samuel Alizon||<p style="text-align: justify;">Phylodynamic analyses generate important and timely data to optimise public health response to SARS-CoV-2 outbreaks and epidemics. However, their implementation is hampered by the massive amount of sequence data and...||Bioinformatics, Evolutionary genomics||Emmanuelle Lerat||2022-12-12 09:04:01||View|