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23 Sep 2022
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MATEdb, a data repository of high-quality metazoan transcriptome assemblies to accelerate phylogenomic studies

MATEdb: a new phylogenomic-driven database for Metazoa

Recommended by ORCID_LOGO based on reviews by 2 anonymous reviewers

The development (and standardization) of high-throughput sequencing techniques has revolutionized evolutionary biology, to the point that we almost see as normal fine-detail studies of genome architecture evolution (Robert et al., 2022), adaptation to new habitats (Rahi et al., 2019), or the development of key evolutionary novelties (Hilgers et al., 2018), to name three examples. One of the fields that has benefited the most is phylogenomics, i.e. the use of genome-wide data for inferring the evolutionary relationships among organisms. Dealing with such amount of data, however, has come with important analytical and computational challenges. Likewise, although the steady generation of genomic data from virtually any organism opens exciting opportunities for comparative analyses, it also creates a sort of “information fog”, where it is hard to find the most appropriate and/or the higher quality data. I have personally experienced this not so long ago, when I had to spend several weeks selecting the most complete transcriptomes from several phyla, moving back and forth between the NCBI SRA repository and the relevant literature.

In an attempt to deal with this issue, some research labs have committed their time and resources to the generation of taxa- and topic-specific databases (Lathe et al., 2008), such as MolluscDB (Liu et al., 2021), focused on mollusk genomics, or EukProt (Richter et al., 2022), a protein repository representing the diversity of eukaryotes. A new database that promises to become an important resource in the near future is MATEdb (Fernández et al., 2022), a repository of high-quality genomic data from Metazoa. MATEdb has been developed from publicly available and newly generated transcriptomes and genomes, prioritizing quality over quantity. Upon download, the user has access to both raw data and the related datasets: assemblies, several quality metrics, the set of inferred protein-coding genes, and their annotation. Although it is clear to me that this repository has been created with phylogenomic analyses in mind, I see how it could be generalized to other related problems such as analyses of gene content or evolution of specific gene families. In my opinion, the main strengths of MATEdb are threefold:

  1. Rosa Fernández and her team have carefully scrutinized the genomic data available in several repositories to retrieve only the most complete transcriptomes and genomes, saving a lot of time in data mining to the user.
  2. These data have been analyzed to provide both the assembly and the set of protein-coding genes, easing the computational burden that usually accompanies these pipelines. Interestingly, all the data have been analyzed with the same software and parameters, facilitating comparisons among taxa.
  3. Genomic analysis can be intimidating, and even more for inexperienced users. That is particularly important when it comes to transcriptome and genome assembly because it has an effect in all downstream analyses. I believe that having access to already analyzed data softens this transition. The users can move forward on their research while they learn how to generate and analyze their data at their own pace.

On a negative note, I see two main drawbacks. First, as of today (September 16th, 2022) this database is in an early stage and it still needs to incorporate a lot of animal groups. This has been discussed during the revision process and the authors are already working on it, so it is only a matter of time until all major taxa are represented. Second, there is a scalability issue. In its current format it is not possible to select the taxa of interest and the full database has to be downloaded, which will become more and more difficult as it grows. Nonetheless, with the appropriate resources it would be easy to find a better solution. There are plenty of examples that could serve as inspiration, so I hope this does not become a big problem in the future.

Altogether, I and the researchers that participated in the revision process believe that MATEdb has the potential to become an important and valuable addition to the metazoan phylogenomics community. Personally, I wish it was available just a few months ago, it would have saved me so much time.

References

Fernández R, Tonzo V, Guerrero CS, Lozano-Fernandez J, Martínez-Redondo GI, Balart-García P, Aristide L, Eleftheriadi K, Vargas-Chávez C (2022) MATEdb, a data repository of high-quality metazoan transcriptome assemblies to accelerate phylogenomic studies. bioRxiv, 2022.07.18.500182, ver. 4 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2022.07.18.500182

Hilgers L, Hartmann S, Hofreiter M, von Rintelen T (2018) Novel Genes, Ancient Genes, and Gene Co-Option Contributed to the Genetic Basis of the Radula, a Molluscan Innovation. Molecular Biology and Evolution, 35, 1638–1652. https://doi.org/10.1093/molbev/msy052

Lathe W, Williams J, Mangan M, Karolchik, D (2008). Genomic data resources: challenges and promises. Nature Education, 1(3), 2.

Liu F, Li Y, Yu H, Zhang L, Hu J, Bao Z, Wang S (2021) MolluscDB: an integrated functional and evolutionary genomics database for the hyper-diverse animal phylum Mollusca. Nucleic Acids Research, 49, D988–D997. https://doi.org/10.1093/nar/gkaa918

Rahi ML, Mather PB, Ezaz T, Hurwood DA (2019) The Molecular Basis of Freshwater Adaptation in Prawns: Insights from Comparative Transcriptomics of Three Macrobrachium Species. Genome Biology and Evolution, 11, 1002–1018. https://doi.org/10.1093/gbe/evz045

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

Robert NSM, Sarigol F, Zimmermann B, Meyer A, Voolstra CR, Simakov O (2022) Emergence of distinct syntenic density regimes is associated with early metazoan genomic transitions. BMC Genomics, 23, 143. https://doi.org/10.1186/s12864-022-08304-2

MATEdb, a data repository of high-quality metazoan transcriptome assemblies to accelerate phylogenomic studiesRosa Fernandez, Vanina Tonzo, Carolina Simon Guerrero, Jesus Lozano-Fernandez, Gemma I Martinez-Redondo, Pau Balart-Garcia, Leandro Aristide, Klara Eleftheriadi, Carlos Vargas-Chavez<p style="text-align: justify;">With the advent of high throughput sequencing, the amount of genomic data available for animals (Metazoa) species has bloomed over the last decade, especially from transcriptomes due to lower sequencing costs and ea...Bioinformatics, Evolutionary genomics, Functional genomicsSamuel Abalde2022-07-20 07:30:39 View
15 Sep 2022
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EukProt: A database of genome-scale predicted proteins across the diversity of eukaryotes

EukProt enables reproducible Eukaryota-wide protein sequence analyses

Recommended by ORCID_LOGO based on reviews by 2 anonymous reviewers

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

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

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

Wilkinson MD, Dumontier M, Aalbersberg IjJ, Appleton G, Axton M, Baak A, Blomberg N, Boiten J-W, da Silva Santos LB, Bourne PE, Bouwman J, Brookes AJ, Clark T, Crosas M, Dillo I, Dumon O, Edmunds S, Evelo CT, Finkers R, Gonzalez-Beltran A, Gray AJG, Groth P, Goble C, Grethe JS, Heringa J, ’t Hoen PAC, Hooft R, Kuhn T, Kok R, Kok J, Lusher SJ, Martone ME, Mons A, Packer AL, Persson B, Rocca-Serra P, Roos M, van Schaik R, Sansone S-A, Schultes E, Sengstag T, Slater T, Strawn G, Swertz MA, Thompson M, van der Lei J, van Mulligen E, Velterop J, Waagmeester A, Wittenburg P, Wolstencroft K, Zhao J, Mons B (2016) The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3, 160018. https://doi.org/10.1038/sdata.2016.18

EukProt: A database of genome-scale predicted proteins across the diversity of eukaryotesDaniel J. Richter, Cédric Berney, Jürgen F. H. Strassert, Yu-Ping Poh, Emily K. Herman, Sergio A. Muñoz-Gómez, Jeremy G. Wideman, Fabien Burki, Colomban de Vargas<p style="text-align: justify;">EukProt is a database of published and publicly available predicted protein sets selected to represent the breadth of eukaryotic diversity, currently including 993 species from all major supergroups as well as orpha...Bioinformatics, Evolutionary genomicsGavin Douglas2022-06-08 14:19:28 View
23 Aug 2022
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A novel lineage of the Capra genus discovered in the Taurus Mountains of Turkey using ancient genomics

Goat ancient DNA analysis unveils a new lineage that may have hybridized with domestic goats

Recommended by 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 
West and East Caucasus Tur modern lineages. Also, analysis of the genomic data and mitochondrial haplotypes reveals hybridization between the Tur and the Bezoar wild lineages. Interestingly, authors also find an uneven amount of Tur ancestry among Neolithic domestic goats, with European domestic goats showing evidence of this ancient Tur ancestry, whereas Neolithic Iranian domestic goats do not, a pattern that is also observed in some modern European domestic goats.

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.

References

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 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<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, VertebratesLaura Botigué2022-04-15 12:05:47 View
18 Jul 2022
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CulebrONT: a streamlined long reads multi-assembler pipeline for prokaryotic and eukaryotic genomes

A flexible and reproducible pipeline for long-read assembly and evaluation

Recommended by based on reviews by Benjamin Istace and Valentine Murigneux

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

CulebrONT: a streamlined long reads multi-assembler pipeline for prokaryotic and eukaryotic genomesJulie Orjuela, Aurore Comte, Sébastien Ravel, Florian Charriat, Tram Vi, Francois Sabot, Sébastien Cunnac<p style="text-align: justify;">Using long reads provides higher contiguity and better genome assemblies. However, producing such high quality sequences from raw reads requires to chain a growing set of tools, and determining the best workflow is ...BioinformaticsRaúl Castanera Valentine Murigneux2022-02-22 16:21:25 View
13 Jul 2022
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Nucleosome patterns in four plant pathogenic fungi with contrasted genome structures

Genome-wide chromatin and expression datasets of various pathogenic ascomycetes

Recommended by and based on reviews by Ricardo C. Rodríguez de la Vega and 1 anonymous reviewer

Plant pathogenic fungi represent serious economic threats. These organisms are rapidly adaptable, with plastic genomes containing many variable regions and evolving rapidly. It is, therefore, useful to characterize their genetic regulation in order to improve their control. One of the steps to do this is to obtain omics data that link their DNA structure and gene expression. 
In this paper, Clairet et al. (2022) studied the nucleosome positioning and gene expression of four plant pathogenic ascomycete species (Leptosphaeria maculans, Leptosphaeria maculans 'lepidii', Fusarium graminearum, Botrytis cinerea). The genomes of these species contain different compositions of transposable elements (from 4 to 30%), and present an equally variable compartmentalization. The authors established MNAse-seq and RNA-seq maps of these genomes in axenic cultures. Thanks to an ad-hoc tool allowing the visualization of MNA-seq data in combination with other "omics" data, they were able to compare the maps of the different species between them and to study different types of correlation. This tool, called MSTS for "MNase-Seq Tool Suite", allows for example to perform limited analyses on certain genetic subsets in an ergonomic way. 
In the fungi studied, nucleosomes are positioned every 161 to 172 bp, with intra-genome variations such as AT-rich regions but, surprisingly, particularly dense nucleosomes in the Lmb genome. The authors discuss the differences between these organisms with respect to this nucleosome density, the expression profile, and the structure and transposon composition of the different genomes. These data and insights thus represent interesting resources for researchers interested in the evolution of ascomycete genomes and their adaptation. For this, and for the development of the MSTS tool, we recommend this preprint.

References

Clairet C, Lapalu N, Simon A, Soyer JL, Viaud M, Zehraoui E, Dalmais B, Fudal I, Ponts N (2022) Nucleosome patterns in four plant pathogenic fungi with contrasted genome structures. bioRxiv, 2021.04.16.439968, ver. 4 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2021.04.16.439968

Nucleosome patterns in four plant pathogenic fungi with contrasted genome structuresColin Clairet, Nicolas Lapalu, Adeline Simon, Jessica L. Soyer, Muriel Viaud, Enric Zehraoui, Berengere Dalmais, Isabelle Fudal, Nadia Ponts<p style="text-align: justify;">Fungal pathogens represent a serious threat towards agriculture, health, and environment. Control of fungal diseases on crops necessitates a global understanding of fungal pathogenicity determinants and their expres...Epigenomics, FungiSébastien Bloyer2021-04-17 10:32:41 View
13 Jul 2022
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Karyorelict ciliates use an ambiguous genetic code with context-dependent stop/sense codons

An accident frozen in time: the ambiguous stop/sense genetic code of karyorelict ciliates

Recommended by based on reviews by Vittorio Boscaro and 2 anonymous reviewers

Several variations of the “universal” genetic code are known. Among the most striking are those where a codon can either encode for an amino acid or a stop signal depending on the context. Such ambiguous codes are known to have evolved in eukaryotes multiple times independently, particularly in ciliates – eight different codes have so far been discovered (1). We generally view such genetic codes are rare ‘variants’ of the standard code restricted to single species or strains, but this might as well reflect a lack of study of closely related species. In this study, Seah and co-authors (2) explore the possibility of codon reassignment in karyorelict ciliates closely related to Parduczia sp., which has been shown to contain an ambiguous genetic code (1). Here, single-cell transcriptomics are used, along with similar available data, to explore the possibility of codon reassignment across the diversity of Karyorelictea (four out of the six recognized families). Codon reassignments were inferred from their frequencies within conserved Pfam (3) protein domains, whereas stop codons were inferred from full-length transcripts with intact 3’-UTRs.

Results show the reassignment of UAA and UAG stop codons to code for glutamine (Q) and the reassignment of the UGA stop codon into tryptophan (W). This occurs only within the coding sequences, whereas the end of transcription is marked by UGA as the main stop codon, and to a lesser extent by UAA. In agreement with a previous model proposed that explains the functioning of ambiguous codes (1,4), the authors observe a depletion of in-frame UGAs before the UGA codon that indicates the stop, thus avoiding premature termination of transcription. The inferred codon reassignments occur in all studied karyorelicts, including the previously studied Parduczia sp. Despite the overall clear picture, some questions remain. Data for two out of six main karyorelict lineages are so far absent and the available data for Cryptopharyngidae was inconclusive; the phylogenetic affinities of Cryptopharyngidae have also been questioned (5). This indicates the need for further study of this interesting group of organisms. As nicely discussed by the authors, experimental evidence could further strengthen the conclusions of this paper, including ribosome profiling, mass spectrometry – as done for Condylostoma (1) – or even direct genetic manipulation. 

The uniformity of the ambiguous genetic code across karyorelicts might at first seem dull, but when viewed in a phylogenetic context character distribution strongly suggest that this genetic code has an ancient origin in the karyorelict ancestor ~455 Ma in the Proterozoic (6). This ambiguous code is also not a rarity of some obscure species, but it is shared by ciliates that are very diverse and ecologically important. The origin of the karyorelict code is also intriguing. Adaptive arguments suggest that it could confer robustness to mutations causing premature stop codons. However, we lack evidence for ambiguous codes being linked to specific habitats of lifestyles that could account for it. Instead, the authors favor the neutral view of an ancient “frozen accident”, fixed stochastically simply because it did not pose a significant selective disadvantage. Once a stop codon is reassigned to an amino acid, it is increasingly difficult to revert this without the deleterious effect of prematurely terminating translation. At the end, the origin of the genetic code itself is thought to be a frozen accident too (7).

References

1. Swart EC, Serra V, Petroni G, Nowacki M. Genetic codes with no dedicated stop codon: Context-dependent translation termination. Cell 2016;166: 691–702. https://doi.org/10.1016/j.cell.2016.06.020

2. Seah BKB, Singh A, Swart EC (2022) Karyorelict ciliates use an ambiguous genetic code with context-dependent stop/sense codons. bioRxiv, 2022.04.12.488043. ver. 4 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2022.04.12.488043

3. Mistry J, Chuguransky S, Williams L, Qureshi M, Salazar GA, Sonnhammer ELL, Tosatto SCE, Paladin L, Raj S, Richardson LJ, Finn RD, Bateman A. Pfam: The protein families database in 2021, Nuc Acids Res 2020;49: D412-D419. https://doi.org/10.1093/nar/gkaa913

4. Alkalaeva E, Mikhailova T. Reassigning stop codons via translation termination: How a few eukaryotes broke the dogma. Bioessays. 2017;39. https://doi.org/10.1002/bies.201600213

5. Xu Y, Li J, Song W, Warren A. Phylogeny and establishment of a new ciliate family, Wilbertomorphidae fam. nov. (Ciliophora, Karyorelictea), a highly specialized taxon represented by Wilbertomorpha colpoda gen. nov., spec. nov. J Eukaryot Microbiol. 2013;60: 480–489. https://doi.org/10.1111/jeu.12055

6. Fernandes NM, Schrago CG. A multigene timescale and diversification dynamics of Ciliophora evolution. Mol Phylogenet Evol. 2019;139: 106521. https://doi.org/10.1016/j.ympev.2019.106521

7. Crick FH. The origin of the genetic code. J Mol Biol. 1968;38: 367–379. https://doi.org/10.1016/0022-2836(68)90392-6

Karyorelict ciliates use an ambiguous genetic code with context-dependent stop/sense codonsBrandon Kwee Boon Seah, Aditi Singh, Estienne Carl Swart<p style="text-align: justify;">In ambiguous stop/sense genetic codes, the stop codon(s) not only terminate translation but can also encode amino acids. Such codes have evolved at least four times in eukaryotes, twice among ciliates (<em>Condylost...Bioinformatics, Evolutionary genomicsIker Irisarri2022-05-02 11:06:10 View
12 Jul 2022
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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

A genomic resource for ants, and more

Recommended by 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. 

References

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 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<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 genomicsNadia Ponts Nicolas Nègre, Isabel Almudi2022-01-13 16:47:30 View
06 May 2022
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A deep dive into genome assemblies of non-vertebrate animals

Diving, and even digging, into the wild jungle of annotation pathways for non-vertebrate animals

Recommended by ORCID_LOGO 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.

References

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 animalsNadège 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 genomicsFrancois Sabot Valentina Peona, Benjamin Istace, Cécile Monat, Yann Bourgeois2021-11-10 17:47:31 View
08 Apr 2022
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POSTPRINT

Phylogenetics in the Genomic Era

“Phylogenetics in the Genomic Era” brings together experts in the field to present a comprehensive synthesis

Recommended by and

E-book: Phylogenetics in the Genomic Era (Scornavacca et al. 2021)

This book was not peer-reviewed by PCI Genomics. It has undergone an internal review by the editors.

Accurate reconstructions of the relationships amongst species and the genes encoded in their genomes are an essential foundation for almost all evolutionary inferences emerging from downstream analyses. Molecular phylogenetics has developed as a field over many decades to build suites of models and methods to reconstruct reliable trees that explain, support, or refute such inferences. The genomic era has brought new challenges and opportunities to the field, opening up new areas of research and algorithm development to take advantage of the accumulating large-scale data. Such ‘big-data’ phylogenetics has come to be known as phylogenomics, which broadly aims to connect molecular and evolutionary biology research to address questions centred on relationships amongst taxa, mechanisms of molecular evolution, and the biological functions of genes and other genomic elements. This book brings together experts in the field to present a comprehensive synthesis of Phylogenetics in the Genomic Era, covering key conceptual and methodological aspects of how to build accurate phylogenies and how to apply them in molecular and evolutionary research. The paragraphs below briefly summarise the five constituent parts of the book, highlighting the key concepts, methods, and applications that each part addresses. Being organised in an accessible style, while presenting details to provide depth where necessary, and including guides describing real-world examples of major phylogenomic tools, this collection represents an invaluable resource, particularly for students and newcomers to the field of phylogenomics.

Part 1: Phylogenetic analyses in the genomic era

Modelling how sequences evolve is a fundamental cornerstone of phylogenetic reconstructions. This part of the book introduces the reader to phylogenetic inference methods and algorithmic optimisations in the contexts of Markov, Maximum Likelihood, and Bayesian models of sequence evolution. The main concepts and theoretical considerations are mapped out for probabilistic Markov models, efficient tree building with Maximum Likelihood methods, and the flexibility and robustness of Bayesian approaches. These are supported with practical examples of phylogenomic applications using the popular tools RAxML and PhyloBayes. By considering theoretical, algorithmic, and practical aspects, these chapters provide readers with a holistic overview of the challenges and recent advances in developing scalable phylogenetic analyses in the genomic era.

Part 2: Data quality, model adequacy

This part focuses on the importance of considering the appropriateness of the evolutionary models used and the accuracy of the underlying molecular and genomic data. Both these aspects can profoundly affect the results when applying current phylogenomic methods to make inferences about complex biological and evolutionary processes. A clear example is presented for methods for building multiple sequence alignments and subsequent filtering approaches that can greatly impact phylogeny inference. The importance of error detection in (meta)barcode sequencing data is also highlighted, with solutions offered by the MACSE_BARCODE pipeline for accurate taxonomic assignments. Orthology datasets are essential markers for phylogenomic inferences, but the overview of concepts and methods presented shows that they too face challenges with respect to model selection and data quality. Finally, an innovative approach using ancestral gene order reconstructions provides new perspectives on how to assess gene tree accuracy for phylogenomic analyses. By emphasising through examples the importance of using appropriate evolutionary models and assessing input data quality, these chapters alert readers to key limitations that the field as a whole strives to address.

Part 3: Resolving phylogenomic conflicts

Conflicting phylogenetic signals are commonplace and may derive from statistical or systematic bias. This part of the book addresses possible causes of conflict, discordance between gene trees and species trees and how processes that lead to such conflicts can be described by phylogenetic models. Furthermore, it provides an overview of various models and methods with examples in phylogenomics including their pros and cons. Outlined in detail is the multispecies coalescent model (MSC) and its applications in phylogenomics. An interesting aspect is that different phylogenetic signals leading to conflict are in fact a key source of information rather than a problem that can – and should – be used to point to events like introgression or hybridisation, highlighting possible future trends in this research area. Last but not least, this part of the book also addresses inferring species trees by concatenating single multiple sequence alignments (gene alignments) versus inferring the species tree based on ensembles of single gene trees pointing out advantages and disadvantages of both approaches. As an important take home message from these chapters, it is recommended to be flexible and identify the most appropriate approach for each dataset to be analysed since this may tremendously differ depending on the dataset, setting, taxa, and phylogenetic level addressed by the researcher.

Part 4: Functional evolutionary genomics

In this part of the book the focus shifts to functional considerations of phylogenomics approaches both in terms of molecular evolution and adaptation and with respect to gene expression. The utility of multi-species analysis is clearly presented in the context of annotating functional genomic elements through quantifying evolutionary constraint and protein-coding potential. An historical perspective on characterising rates of change highlights how phylogenomic datasets help to understand the modes of molecular evolution across the genome, over time, and between lineages. These are contextualised with respect to the specific aim of detecting signatures of adaptation from protein-coding DNA alignments using the example of the MutSelDP-ω∗ model. This is extended with the presentation of the generally rare case of adaptive sequence convergence, where consideration of appropriate models and knowledge of gene functions and phenotypic effects are needed. Constrained or relaxed, selection pressures on sequence or copy-number affect genomic elements in different ways, making the very concept of function difficult to pin down despite it being fundamental to relate the genome to the phenotype and organismal fitness. Here gene expression provides a measurable intermediate, for which the Expression Comparison tool from the Bgee suite allows exploration of expression patterns across multiple animal species taking into account anatomical homology. Overall, phylogenomics applications in functional evolutionary genomics build on a rich theoretical history from molecular analyses where integration with knowledge of gene functions is challenging but critical.

Part 5: Phylogenomic applications

Rather than attempting to review the full extent of applications linked to phylogenomics, this part of the book focuses on providing detailed specific insights into selected examples and methods concerning i) estimating divergence times, and ii) species delimitation in the era of ‘omics’ data. With respect to estimating divergence times, an exemplary overview is provided for fossil data recovered from geological records, either using fossil data as calibration points with an extant-species-inferred phylogeny, or using a fossilised birth-death process as a mechanistic model that accounts for lineage diversification. Included is a tutorial for a joint approach to infer phylogenies and estimate divergence times using the RevBayes software with various models implemented for different applications and datasets incorporating molecular and morphological data. An interesting excursion is outlined focusing on timescale estimates with respect to viral evolution introducing BEAGLE, a high-performance likelihood-calculation platform that can be used on multi-core systems. As a second major subject, species delimitation is addressed since currently the increasing amount of available genomic data enables extensive inferences, for instance about the degree of genetic isolation among species and ancient and recent introgression events. Describing the history of molecular species delimitation up to the current genomic era and presenting widely used computational methods incorporating single- and multi-locus genomic data, pros and cons are addressed. Finally, a proposal for a new method for delimiting species based on empirical criteria is outlined. In the closing chapter of this part of the book, BPP (Bayesian Markov chain Monte Carlo program) for analysing multi-locus sequence data under the multispecies coalescent (MSC) model with and without introgression is introduced, including a tutorial. These examples together provide accessible details on key conceptual and methodological aspects related to the application of phylogenetics in the genomic era.

References

Scornavacca C, Delsuc F, Galtier N (2021) Phylogenetics in the Genomic Era. https://hal.inria.fr/PGE/

Phylogenetics in the Genomic EraCéline Scornavacca, Frédéric Delsuc, Nicolas Galtier<p style="text-align: justify;">Molecular phylogenetics was born in the middle of the 20th century, when the advent of protein and DNA sequencing offered a novel way to study the evolutionary relationships between living organisms. The first 50 ye...Bacteria and archaea, Bioinformatics, Evolutionary genomics, Functional genomics, Fungi, Plants, Population genomics, Vertebrates, Viruses and transposable elementsRobert Waterhouse2022-03-15 17:43:52 View
23 Mar 2022
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Chromosomal rearrangements with stable repertoires of genes and transposable elements in an invasive forest-pathogenic fungus

Comparative genomics in the chestnut blight fungus Cryphonectria parasitica reveals large chromosomal rearrangements and a stable genome organization

Recommended by 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). 

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

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<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, FungiSebastien Duplessis2021-03-12 14:18:20 View