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18 Feb 2021
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Traces of transposable element in genome dark matter co-opted by flowering gene regulation networks

Using small fragments to discover old TE remnants: the Duster approach empowers the TE detection

Recommended by ORCID_LOGO based on reviews by Josep Casacuberta and 1 anonymous reviewer

Transposable elements are the raw material of the dark matter of the genome, the foundation of the next generation of genes and regulation networks". This sentence could be the essence of the paper of Baud et al. (2021). Transposable elements (TEs) are endogenous mobile genetic elements found in almost all genomes, which were discovered in 1948 by Barbara McClintock (awarded in 1983 the only unshared Medicine Nobel Prize so far). TEs are present everywhere, from a single isolated copy for some elements to more than millions for others, such as Alu. They are founders of major gene lineages (HET-A, TART and telomerases, RAG1/RAG2 proteins from mammals immune system; Diwash et al, 2017), and even of retroviruses (Xiong & Eickbush, 1988). However, most TEs appear as selfish elements that replicate, land in a new genomic region, then start to decay and finally disappear in the midst of the genome, turning into genomic ‘dark matter’ (Vitte et al, 2007). The mutations (single point, deletion, recombination, and so on) that occur during this slow death erase some of their most notable features and signature sequences, rendering them completely unrecognizable after a few million years. Numerous TE detection tools have tried to optimize their detection (Goerner-Potvin & Bourque, 2018), but further improvement is definitely challenging. This is what Baud et al. (2021) accomplished in their paper. They used a simple, elegant and efficient k-mer based approach to find small signatures that, when accumulated, allow identifying very old TEs. Using this method, called Duster, they improved the amount of annotated TEs in the model plant Arabidopsis thaliana by 20%, pushing the part of this genome occupied by TEs up from 40 to almost 50%. They further observed that these very old Duster-specific TEs (i.e., TEs that are only detected by Duster) are, among other properties, close to genes (much more than recent TEs), not targeted by small RNA pathways, and highly associated with conserved regions across the rosid family. In addition, they are highly associated with flowering or stress response genes, and may be involved through exaptation in the evolution of responses to environmental changes. TEs are not just selfish elements: more and more studies have shown their key role in the evolution of their hosts, and tools such as Duster will help us better understand their impact.


Baud, A., Wan, M., Nouaud, D., Francillonne, N., Anxolabéhère, D. and Quesneville, H. (2021). Traces of transposable elements in genome dark matter co-opted by flowering gene regulation networks. bioRxiv, 547877, ver. 5 peer-reviewed and recommended by PCI Genomics.doi:
Bourque, G., Burns, K.H., Gehring, M. et al. (2018) Ten things you should know about transposable elements. Genome Biology 19:199. doi:
Goerner-Potvin, P., Bourque, G. Computational tools to unmask transposable elements. Nature Reviews Genetics 19:688–704 (2018)
Jangam, D., Feschotte, C. and Betrán, E. (2017) Transposable element domestication as an adaptation to evolutionary conflicts. Trends in Genetics 33:817-831. doi:
Vitte, C., Panaud, O. and Quesneville, H. (2007) LTR retrotransposons in rice (Oryza sativa, L.): recent burst amplifications followed by rapid DNA loss. BMC Genomics 8:218. doi:
Xiong, Y. and Eickbush, T. H. (1988) Similarity of reverse transcriptase-like sequences of viruses, transposable elements, and mitochondrial introns. Molecular Biology and Evolution 5: 675–690. doi:

Traces of transposable element in genome dark matter co-opted by flowering gene regulation networksAgnes Baud, Mariene Wan, Danielle Nouaud, Nicolas Francillonne, Dominique Anxolabehere, Hadi Quesneville<p>Transposable elements (TEs) are mobile, repetitive DNA sequences that make the largest contribution to genome bulk. They thus contribute to the so-called 'dark matter of the genome', the part of the genome in which nothing is immediately recogn...Bioinformatics, Evolutionary genomics, Functional genomics, Plants, Structural genomics, Viruses and transposable elementsFrancois SabotAnonymous, Josep Casacuberta2020-04-07 17:12:12 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.


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.

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.

3. Trapnell C, Pachter L, Salzberg SL (2009) TopHat: discovering splice junctions with RNA-Seq. Bioinformatics, 25, 1105–1111.

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
14 Sep 2023
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Expression of cell-wall related genes is highly variable and correlates with sepal morphology

The same but different: How small scale hidden variations can have large effects

Recommended by ORCID_LOGO based on reviews by Sandra Corjito and 1 anonymous reviewer

For ages, we considered only single genes, or just a few, in order to understand the relationship between phenotype and genotype in response to environmental challenges. Recently, the use of meaningful groups of genes, e.g. gene regulatory networks, or modules of co-expression, allowed scientists to have a larger view of gene regulation. However, all these findings were based on contrasted genotypes, e.g. between wild-types and mutants, as the implicit assumption often made is that there is little transcriptomic variability within the same genotype context. 

Hartasànchez and collaborators (2023) decided to challenge both views: they used a single genotype instead of two, the famous A. thaliana Col0, and numerous plants, and considered whole gene networks related to sepal morphology and its variations. They used a clever approach, combining high-level phenotyping and gene expression to better understand phenomena and regulations underlying sepal morphologies. Using multiple controls, they showed that basic variations in the expression of genes related to the cell wall regulation, as well as the ones involved in chloroplast metabolism, influenced the global transcriptomic pattern observed in sepal while being in near-identical genetic background and controlling for all other experimental conditions. 

The paper of Hartasànchez et al. is thus a tremendous call for humility in biology, as we saw in their work that we just understand the gross machinery. However, the Devil is in the details: understanding those very small variations that may have a large influence on phenotypes, and thus on local adaptation to environmental challenges, is of great importance in these times of climatic changes.


Hartasánchez DA, Kiss A, Battu V, Soraru C, Delgado-Vaquera A, Massinon F, Brasó-Vives M, Mollier C, Martin-Magniette M-L, Boudaoud A, Monéger F. 2023. Expression of cell-wall related genes is highly variable and correlates with sepal morphology. bioRxiv, ver. 4, peer-reviewed and recommended by Peer Community in Genomics.

Expression of cell-wall related genes is highly variable and correlates with sepal morphologyDiego A. Hartasánchez, Annamaria Kiss, Virginie Battu, Charline Soraru, Abigail Delgado-Vaquera, Florian Massinon, Marina Brasó-Vives, Corentin Mollier, Marie-Laure Martin-Magniette, Arezki Boudaoud, Françoise Monéger<p style="text-align: justify;">Control of organ morphology is a fundamental feature of living organisms. There is, however, observable variation in organ size and shape within a given genotype. Taking the sepal of Arabidopsis as a model, we inves...Bioinformatics, Epigenomics, PlantsFrancois Sabot2023-03-14 19:10:15 View
07 Feb 2023
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RAREFAN: A webservice to identify REPINs and RAYTs in bacterial genomes

A workflow for studying enigmatic non-autonomous transposable elements across bacteria

Recommended by ORCID_LOGO based on reviews by Sophie Abby and 1 anonymous reviewer

Repetitive extragenic palindromic sequences (REPs) are common repetitive elements in bacterial genomes (Gilson et al., 1984; Stern et al., 1984). In 2011, Bertels and Rainey identified that REPs are overrepresented in pairs of inverted repeats, which likely form hairpin structures, that they referred to as “REP doublets forming hairpins” (REPINs). Based on bioinformatics analyses, they argued that REPINs are likely selfish elements that evolved from REPs flanking particular transposes (Bertels and Rainey, 2011). These transposases, so-called REP-associated tyrosine transposases (RAYTs), were known to be highly associated with the REP content in a genome and to have characteristic upstream and downstream flanking REPs (Nunvar et al., 2010). The flanking REPs likely enable RAYT transposition, and their horizontal replication is physically linked to this process. In contrast, Bertels and Rainey hypothesized that REPINs are selfish elements that are highly replicated due to the similarity in arrangement to these RAYT-flanking REPs, but independent of RAYT transposition and generally with no impact on bacterial fitness (Bertels and Rainey, 2011).

This last point was especially contentious, as REPINs are highly conserved within species (Bertels and Rainey, 2023), which is unusual for non-beneficial bacterial DNA (Mira et al., 2001). Bertels and Rainey have since refined their argument to be that REPINs must provide benefits to host cells, but that there are nonetheless signatures of intragenomic conflict in genomes associated with these elements (Bertels and Rainey, 2023). These signatures reflect the divergent levels of selections driving REPIN distribution: selection at the level of each DNA element and selection on each individual bacterium. I found this observation particularly interesting as I and my colleague recently argued that these divergent levels of selection, and the interaction between them, is key to understanding bacterial pangenome diversity (Douglas and Shapiro, 2021). REPINs could be an excellent system for investigating these levels of selection across bacteria more generally.

The problem is that REPINs have not been widely characterized in bacterial genomes, partially because no bioinformatic workflow has been available for this purpose. To address this problem, Fortmann-Grote et al. (2023) developed RAREFAN, which is a web server for identifying RAYTs and associated REPINs in a set of input genomes. The authors showcase their tool by applying it to 49 Stenotrophomonas maltophilia genomes and providing examples of how to identify and assess RAYT-REPIN hits. The workflow requires several manual steps, but nonetheless represents a straightforward and standardized approach. Overall, this workflow should enable RAYTs and REPINs to be identified across diverse bacterial species, which will facilitate further investigation into the mechanisms driving their maintenance and spread.


Bertels F, Rainey PB (2023) Ancient Darwinian replicators nested within eubacterial genomes. BioEssays, 45, 2200085.

Bertels F, Rainey PB (2011) Within-Genome Evolution of REPINs: a New Family of Miniature Mobile DNA in Bacteria. PLOS Genetics, 7, e1002132.

Douglas GM, Shapiro BJ (2021) Genic Selection Within Prokaryotic Pangenomes. Genome Biology and Evolution, 13, evab234.

Fortmann-Grote C, Irmer J von, Bertels F (2023) RAREFAN: A webservice to identify REPINs and RAYTs in bacterial genomes. bioRxiv, 2022.05.22.493013, ver. 4 peer-reviewed and recommended by Peer Community in Genomics.

Gilson E, Clément J m., Brutlag D, Hofnung M (1984) A family of dispersed repetitive extragenic palindromic DNA sequences in E. coli. The EMBO Journal, 3, 1417–1421.

Mira A, Ochman H, Moran NA (2001) Deletional bias and the evolution of bacterial genomes. Trends in Genetics, 17, 589–596.

Nunvar J, Huckova T, Licha I (2010) Identification and characterization of repetitive extragenic palindromes (REP)-associated tyrosine transposases: implications for REP evolution and dynamics in bacterial genomes. BMC Genomics, 11, 44.

Stern MJ, Ames GF-L, Smith NH, Clare Robinson E, Higgins CF (1984) Repetitive extragenic palindromic sequences: A major component of the bacterial genome. Cell, 37, 1015–1026.

RAREFAN: A webservice to identify REPINs and RAYTs in bacterial genomesFrederic Bertels, Julia von Irmer, Carsten Fortmann-Grote<p style="text-align: justify;">Compared to eukaryotes, repetitive sequences are rare in bacterial genomes and usually do not persist for long. Yet, there is at least one class of persistent prokaryotic mobile genetic elements: REPINs. REPINs are ...Bacteria and archaea, Bioinformatics, Evolutionary genomics, Viruses and transposable elementsGavin Douglas2022-06-07 08:21:34 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 ( and the entire database is available for download ( 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.

Burki F, Roger AJ, Brown MW, Simpson AGB (2020) The New Tree of Eukaryotes. Trends in Ecology & Evolution, 35, 43–55.

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.

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.

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
24 Feb 2023
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MacSyFinder v2: Improved modelling and search engine to identify molecular systems in genomes

A unique and customizable approach for functionally annotating prokaryotic genomes

Recommended by ORCID_LOGO based on reviews by Kwee Boon Brandon Seah and Max Emil Schön

Macromolecular System Finder (MacSyFinder) v2 (Néron et al., 2023) is a newly updated approach for performing functional annotation of prokaryotic genomes (Abby et al., 2014). This tool parses an input file of protein sequences from a single genome (either ordered by genome location or unordered) and identifies the presence of specific cellular functions (referred to as “systems”). These systems are called based on two criteria: (1) that the "quorum" of a minimum set of core proteins involved is reached the “quorum” of a minimum set of core proteins being involved that are present, and (2) that the genes encoding these proteins are in the expected genomic organization (e.g., within the same order in an operon), when ordered data is provided. I believe the MacSyFinder approach represents an improvement over more commonly used methods exactly because it can incorporate such information on genomic organization, and also because it is more customizable.

Before properly appreciating these points, it is worth noting the norms and key challenges surrounding high-throughput functional annotation of prokaryotic genomes. Genome sequences are being added to online repositories at increasing rates, which has led to an enormous amount of bacterial genome diversity available to investigate (Altermann et al., 2022). A key aspect of understanding this diversity is the functional annotation step, which enables genes to be grouped into more biologically interpretable categories. For instance, gene calls can be mapped against existing Clusters of Orthologous Genes, which are themselves grouped into general categories such as ‘Transcription’ and ‘Lipid metabolism’ (Galperin et al., 2021).

This approach is valuable but is primarily used for global summaries of functional annotations within a genome: for example, it could be useful to know that a genome is particularly enriched for genes involved in lipid metabolism. However, knowing that a particular gene is involved in the general process of lipid metabolism is less likely to be actionable. In other words, the desired specificity of a gene’s functional annotation will depend on the exact question being investigated. There is no shortage of functional ontologies in genomics that can be applied for this purpose (Douglas and Langille, 2021), and researchers are often overwhelmed by the choice of which functional ontology to use. In this context, giving researchers the ability to precisely specify the gene families and operon structures they are interested in identifying across genomes provides useful control over what precise functions they are profiling. Of course, most researchers will lack the information and/or expertise to fully take advantage of MacSyFinder’s customizable features, but having this option for specialized purposes is valuable.

The other MacSyFinder feature that I find especially noteworthy is that it can incorporate genomic organization (e.g., of genes ordered in operons) when calling systems. This is a rare feature among commonly used tools for functional annotation and likely results in much higher specificity. As the authors note, this capability makes the co-occurrence of paralogs, and other divergent genes that share sequence similarity, to contribute less noise (i.e., they result in fewer false positive calls).

It is important to emphasize that these features are not new additions in MacSyFinder v2, but there are many other valuable changes. Most practically, this release is written in Python 3, rather than the obsolete Python 2.7, and was made more computationally efficient, which will enable MacSyFinder to be more widely used and more easily maintained moving forward. In addition, the search algorithm for analyzing individual proteins was fundamentally updated as well. The authors show that their improvements to the search algorithm result in an 8% and 20% increase in the number of identified calls for single and multi-locus secretion systems, respectively. Taken together, MacSyFinder v2 represents both practical and scientific improvements over the previous version, which will be of great value to the field. 


Abby SS, Néron B, Ménager H, Touchon M, Rocha EPC (2014) MacSyFinder: A Program to Mine Genomes for Molecular Systems with an Application to CRISPR-Cas Systems. PLOS ONE, 9, e110726.

Altermann E, Tegetmeyer HE, Chanyi RM (2022) The evolution of bacterial genome assemblies - where do we need to go next? Microbiome Research Reports, 1, 15.

Douglas GM, Langille MGI (2021) A primer and discussion on DNA-based microbiome data and related bioinformatics analyses. Peer Community Journal, 1.

Galperin MY, Wolf YI, Makarova KS, Vera Alvarez R, Landsman D, Koonin EV (2021) COG database update: focus on microbial diversity, model organisms, and widespread pathogens. Nucleic Acids Research, 49, D274–D281.

Néron B, Denise R, Coluzzi C, Touchon M, Rocha EPC, Abby SS (2023) MacSyFinder v2: Improved modelling and search engine to identify molecular systems in genomes. bioRxiv, 2022.09.02.506364, ver. 2 peer-reviewed and recommended by Peer Community in Genomics.

MacSyFinder v2: Improved modelling and search engine to identify molecular systems in genomesBertrand Néron, Rémi Denise, Charles Coluzzi, Marie Touchon, Eduardo P. C. Rocha, Sophie S. Abby<p style="text-align: justify;">Complex cellular functions are usually encoded by a set of genes in one or a few organized genetic loci in microbial genomes. Macromolecular System Finder (MacSyFinder) is a program that uses these properties to mod...Bacteria and archaea, Bioinformatics, Functional genomicsGavin Douglas Kwee Boon Brandon Seah, Max Emil Schön2022-09-09 10:30:31 View
01 May 2024
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Evolution of ion channels in cetaceans: A natural experiment in the tree of life

Positive selection acted upon cetacean ion channels during the aquatic transition

Recommended by ORCID_LOGO based on reviews by 2 anonymous reviewers

The transition of cetaceans (whales, dolphins, and porpoises) from terrestrial to aquatic lifestyles is a striking example of natural selection driving major phenotypic changes (Figure 1). For instance, cetaceans have evolved the ability to withstand high pressure and to store oxygen for long periods, among other adaptations (Das et al. 2023). Many phenotypic changes, such as shifts in organ structure, have been well-characterized through fossils (Thewissen et al. 2009). Although such phenotypic transitions are now well understood, we have only a partial understanding of the underlying genetic mechanisms. Scanning for signatures of adaptation in genes related to phenotypes of interest is one approach to better understand these mechanisms. This was the focus of Uribe and colleagues’ (2024) work, who tested for such signatures across cetacean protein-coding genes.


Cetacean fossils

Figure 1: The skeletons of Ambulocetus (an early whale; top) and Pakicetus (the earliest known cetacean, which lived about 50 million years ago; bottom). Copyright: J. G. M. Thewissen. Displayed here with permission from the copyright holder.


The authors were specifically interested in investigating the evolution of ion channels, as these proteins play fundamental roles in physiological processes. An important aspect of their work was to develop a bioinformatic pipeline to identify orthologous ion channel genes across a set of genomes. After applying their bioinformatic workflow to 18 mammalian species (including nine cetaceans), they conducted tests to find out whether these genes showed signatures of positive selection in the cetacean lineage. For many ion channel genes, elevated ratios of non-synonymous to synonymous substitution rates were detected (for at least a subset of sites, and not necessarily the entire coding region of the genes). The genes concerned were enriched for several functions, including heart and nervous system-related phenotypes.

One top gene hit among the putatively selected genes was SCN5A, which encodes a sodium channel expressed in the heart. Interestingly, the authors noted a specific amino acid replacement, which is associated with sensitivity to the toxin tetrodotoxin in other lineages. This substitution appears to have occurred in the common ancestor of toothed whales, and then was reversed in the ancestor of bottlenose dolphins. The authors describe known bottlenose dolphin interactions with toxin-producing pufferfish that could result in high tetrodotoxin exposure, and thus perhaps higher selection for tetrodotoxin resistance. Although this observation is intriguing, the authors emphasize it requires experimental confirmation.

The authors also recapitulated the previously described observation (Yim et al. 2014; Huelsmann et al. 2019) that cetaceans have fewer protein-coding genes compared to terrestrial mammals, on average. This signal has previously been hypothesized to partially reflect adaptive gene loss. For example, specific gene loss events likely decreased the risk of developing blood clots while diving (Huelsmann et al. 2019). Uribe and colleagues also considered overall gene turnover rate, which encompasses gene copy number variation across lineages, and found the cetacean gene turnover rate to be three times higher than that of terrestrial mammals. Finally, they found that cetaceans have a higher proportion of ion channel genes (relative to all protein-coding genes in a genome) compared to terrestrial mammals. 

Similar investigations of the relative non-synonymous to synonymous substitution rates across cetacean and terrestrial mammal orthologs have been conducted previously, but these have primarily focused on dolphins as the sole cetacean representative (McGowen et al. 2012; Nery et al. 2013; Sun et al. 2013). These projects have also been conducted across a large proportion of orthologous genes, rather than a subset with a particular function. Performing proteome-wide investigations can be valuable in that they summarize the genome-wide signal, but can suffer from a high multiple testing burden. More generally, investigating a more targeted question, such as the extent of positive selection acting on ion channels in this case, or on genes potentially linked to cetaceans’ increased brain sizes (McGowen et al. 2011) or hypoxia tolerance (Tian et al. 2016), can be easier to interpret, as opposed to summarizing broader signals. However, these smaller-scale studies can also experience a high multiple testing burden, especially as similar tests are conducted across numerous studies, which often is not accounted for (Ioannidis 2005). In addition, integrating signals across the entire genome will ultimately be needed given that many genetic changes undoubtedly underlie cetaceans’ phenotypic diversification. As highlighted by the fact that past genome-wide analyses have produced some differing biological interpretations (McGowen et al. 2012; Nery et al. 2013; Sun et al. 2013), this is not a trivial undertaking. 

Nonetheless, the work performed in this preprint, and in related research, is valuable for (at least) three reasons. First, although it is a challenging task, a better understanding of the genetic basis of cetacean phenotypes could have benefits for many aspects of cetacean biology, including conservation efforts. In addition, the remarkable phenotypic shifts in cetaceans make the question of what genetic mechanisms underlie these changes intrinsically interesting to a wide audience. Last, since the cetacean fossil record is especially well-documented (Thewissen et al. 2009), cetaceans represent an appealing system to validate and further develop statistical methods for inferring adaptation from genetic data. Uribe and colleagues’ (2024) analyses provide useful insights relevant to each of these points, and have generated intriguing hypotheses for further investigation.


Das, K., Sköld, H., Lorenz, A., Parmentier, E. 2023. Who are the marine mammals? In: “Marine Mammals: A Deep Dive into the World of Science”. Brennecke, D., Knickmeier, K., Pawliczka, I., Siebert, U., Wahlberg, M (editors). Springer, Cham. p. 1–14.

Huelsmann, M., Hecker, N., Springer, M., S., Gatesy, J., Sharma, V., Hiller, M. 2019. Genes lost during the transition from land to water in cetaceans highlight genomic changes associated with aquatic adaptations. Science Advances. 5(9):eaaw6671.

Ioannidis, J., P., A. 2005. Why most published research findings are false. PLOS Medicine. 2(8):e124.

McGowen MR, Montgomery SH, Clark C, Gatesy J. 2011. Phylogeny and adaptive evolution of the brain-development gene microcephalin (MCPH1) in cetaceans. BMC Evolutionary Biology. 11(1):98.

McGowen MR, Grossman LI, Wildman DE. 2012. Dolphin genome provides evidence for adaptive evolution of nervous system genes and a molecular rate slowdown. Proceedings of the Royal Society B: Biological Sciences. 279(1743):3643–3651.

Nery, M., F., González, D., J., Opazo, J., C. 2013. How to make a dolphin: molecular signature of positive selection in cetacean genome. PLOS ONE. 8(6):e65491.

Sun, Y.-B., Zhou, W.-P., Liu, H.-Q., Irwin, D., M., Shen, Y.-Y., Zhang, Y.-P. 2013. Genome-wide scans for candidate genes involved in the aquatic adaptation of dolphins. Genome Biology and Evolution. 5(1):130–139.

Tian, R., Wang, Z., Niu, X., Zhou, K., Xu, S., Yang, G. 2016. Evolutionary genetics of hypoxia tolerance in cetaceans during diving. Genome Biology and Evolution. 8(3):827–839.

Thewissen, J., G., M., Cooper, L., N., George, J., C., Bajpai, S. 2009. From land to water: the origin of whales, dolphins, and porpoises. Evolution: Education and Outreach. 2(2):272–288.

Uribe, C., Nery, M., Zavala, K., Mardones, G., Riadi, G., Opazo, J. 2024. Evolution of ion channels in cetaceans: A natural experiment in the tree of life. bioRxiv, ver. 8 peer-reviewed and recommended by Peer Community in Genomics.

Yim, H.-S., Cho, Y., S., Guang, X., Kang, S., G., Jeong, J.-Y., Cha, S.-S., Oh, H.-M., Lee, J.-H., Yang, E., C., Kwon, K., K., et al. 2014. Minke whale genome and aquatic adaptation in cetaceans. Nature Genetics. 46(1):88–92.


Evolution of ion channels in cetaceans: A natural experiment in the tree of lifeCristóbal Uribe, Mariana F. Nery, Kattina Zavala, Gonzalo A. Mardones, Gonzalo Riadi & Juan C. Opazo<p>Cetaceans could be seen as a natural experiment within the tree of life in which a mammalian lineage changed from terrestrial to aquatic habitats. This shift involved extensive phenotypic modifications, which represent an opportunity to explore...Evolutionary genomicsGavin Douglas2023-07-04 20:53:46 View
02 Apr 2021
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Semi-artificial datasets as a resource for validation of bioinformatics pipelines for plant virus detection

Toward a critical assessment of virus detection in plants

Recommended by based on reviews by Alexander Suh and 1 anonymous reviewer

The advent of High Throughput Sequencing (HTS) since the last decade has revealed previously unsuspected diversity of viruses as well as their (sometimes) unexpected presence in some healthy individuals. These results demonstrate that genomics offers a powerful tool for studying viruses at the individual level, allowing an in-depth inventory of those that are infecting an organism. Such approaches make it possible to study viromes with an unprecedented level of detail, both qualitative and quantitative, which opens new venues for analyses of viruses of humans, animals and plants. Consequently, the diagnostic field is using more and more HTS, fueling the need for efficient and reliable bioinformatics tools. 

Many such tools have already been developed, but in plant disease diagnostics, validation of the bioinformatics pipelines used for the detection of viruses in HTS datasets is still in its infancy. There is an urgent need for benchmarking the different tools and algorithms using well-designed reference datasets generated for this purpose. This is a crucial step to move forward and to improve existing solutions toward well-standardized bioinformatics protocols. This context has led to the creation of the Plant Health Bioinformatics Network (PHBN), a Euphresco network project aiming to build a bioinformatics community working on plant health. One of their objectives is to provide researchers with open-access reference datasets allowing to compare and validate virus detection pipelines. 

In this framework, Tamisier et al. [1] present real, semi-artificial, and completely artificial datasets, each aimed at addressing challenges that could affect virus detection. These datasets comprise real RNA-seq reads from virus-infected plants as well as simulated virus reads. Such a work, providing open-access datasets for benchmarking bioinformatics tools, should be encouraged as they are key to software improvement as demonstrated by the well-known success story of the protein structure prediction community: their pioneer community-wide effort, called Critical Assessment of protein Structure Prediction (CASP)[2], has been providing research groups since 1994 with an invaluable way to objectively test their structure prediction methods, thereby delivering an independent assessment of state-of-art protein-structure modelling tools. Following this success, many other bioinformatic community developed similar “competitions”, such as RNA-puzzles [3] to predict RNA structures, Critical Assessment of Function Annotation [4] to predict gene functions, Critical Assessment of Prediction of Interactions [5] to predict protein-protein interactions, Assemblathon [6] for genome assembly, etc. These are just a few examples from a long list of successful initiatives. Such efforts enable rigorous assessments of tools, stimulate the developers’ creativity, but also provide user communities with a state-of-art evaluation of available tools.

Inspired by these success stories, the authors propose a “VIROMOCK challenge” [7], asking researchers in the field to test their tools and to provide feedback on each dataset through a repository. This initiative, if well followed, will undoubtedly improve the field of virus detection in plants, but also probably in many other organisms. This will be a major contribution to the field of viruses, leading to better diagnostics and, consequently, a better understanding of viral diseases, thus participating in promoting human, animal and plant health.   


[1] Tamisier, L., Haegeman, A., Foucart, Y., Fouillien, N., Al Rwahnih, M., Buzkan, N., Candresse, T., Chiumenti, M., De Jonghe, K., Lefebvre, M., Margaria, P., Reynard, J.-S., Stevens, K., Kutnjak, D. and Massart, S. (2021) Semi-artificial datasets as a resource for validation of bioinformatics pipelines for plant virus detection. Zenodo, 4273791, version 4 peer-reviewed and recommended by Peer community in Genomics. doi:

[2] Critical Assessment of protein Structure Prediction” (CASP) -

[3] RNA-puzzles -

[4] Critical Assessment of Function Annotation (CAFA) -

[5] Critical Assessment of Prediction of Interactions (CAPI) -

[6] Assemblathon -

[7] VIROMOCK challenge -

Semi-artificial datasets as a resource for validation of bioinformatics pipelines for plant virus detectionLucie Tamisier, Annelies Haegeman, Yoika Foucart, Nicolas Fouillien, Maher Al Rwahnih, Nihal Buzkan, Thierry Candresse, Michela Chiumenti, Kris De Jonghe, Marie Lefebvre, Paolo Margaria, Jean Sébastien Reynard, Kristian Stevens, Denis Kutnjak, Séb...<p>The widespread use of High-Throughput Sequencing (HTS) for detection of plant viruses and sequencing of plant virus genomes has led to the generation of large amounts of data and of bioinformatics challenges to process them. Many bioinformatics...Bioinformatics, Plants, Viruses and transposable elementsHadi Quesneville2020-11-27 14:31:47 View
15 Mar 2024
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Convergent origin and accelerated evolution of vesicle-associated RhoGAP proteins in two unrelated parasitoid wasps

Using transcriptomics and proteomics to understand the expansion of a secreted poisonous armoury in parasitoid wasps genomes

Recommended by ORCID_LOGO based on reviews by Inacio Azevedo and 2 anonymous reviewers

Parasitoid wasps lay their eggs inside another arthropod, whose body is physically consumed by the parasitoid larvae. Phylogenetic inference suggests that Parasitoida are monophyletic, and that this clade underwent a strong radiation shortly after branching off from the Apocrita stem, some 236 million years ago (Peters et al. 2017). The increase in taxonomic diversity during evolutionary radiations is usually concurrent with an increase in genetic/genomic diversity, and is often associated with an increase in phenotypic diversity. Gene (or genome) duplication provides the evolutionary potential for such increase of genomic diversity by neo/subfunctionalisation of one of the gene paralogs, and is often proposed to be related to evolutionary radiations (Ohno 1970; Francino 2005).

In their recent preprint, Dominique Colinet and coworkers have explored the genetic and functional diversity of a Rho GTPase activating protein (RhoGAP) multigene family in two very divergent wasp clades within Parasitoida, namely Leptopilina (Figitidae) and Venturia (Ichneumonidae) (Colinet et al. 2024). Some members of the RhoGAP family are present in the venom of the parasitoid wasp Leptopilina boulardi as well as in other Leptopilina species, and are probably involved in the parasitic lifestyle by binding and inactivating host’s Rho GTPases, thereby interfering with the host’s immune response (Colinet et al. 2007).

Venom protein composition is highly variable, even between very closely related species, and is subject to rapid evolutionary changes. Although gene duplication and subsequent neo/subfunctionalisation have been frequently proposed as the main mechanism underlying this evolutionary diversification, observations are often compatible with alternative explanations, such as horizontal gene transfer, gene co-option or multifunctionalisation (Martinson et al. 2017; Alvarado et al. 2020; Huang et al. 2021; Undheim and Jenner 2021). Furthermore, high mutation rates in venom protein-encoding genes hinder phylogenetic hypothesis testing, and venom proteomics can be needed to verify transcriptomic predictions (Smith and Undheim 2018; von Reumont et al. 2022).

Colinet and coworkers (2024) have applied a combined transcriptomic, proteomic and functional approach to i) identify potential transcripts of the RhoGAP family in Leptopilina species using experimental and bioinformatic approaches; ii) experimentally identify proteins of the RhoGAP family in the venom of three Leptopilina species; iii) identify transcripts and proteins of the RhoGAP family in the ovarian calyx of Venturia canescens; and iv) perform phylogenetic and selection analyses on the extant sequences of these RhoGAP family genes to propose an evolutionary scenario for their origin and diversification. The most striking results are first the large diversity of RhoGAP sequences retrieved in the transcriptomes and proteomes of Leptopilina and of V. canescens, and second the high number of branches and positions identified to have evolved under positive selection. All the retrieved hits share a RhoGAP domain, either alone or in tandem, preceded in the case of Leptopilina RhoGAPs by a signal peptide that may be responsible for protein vehiculation for venom secretion. Further, for some of the protein positions identified to have evolved under positive selection, the authors have experimentally verified the functional impact of the changes by reverse genetic engineering.

The authors propose an evolutionary scenario to interpret the phylogenetic relationships among extant RhoGAP diversity in the clades under study. They posit that two independent, incomplete duplication events from the respectively ancestral RacGAP gene, followed by subsequent, lineage- and paralog-specific duplication events, lie at the origin of the wealth of diversity of in the Leptopilina venom RhoGAPs and of V. canescens ovarian calyx RhoGAPs. Notwithstanding, the global relationships presented in the work are not systematically consistent with this interpretation, e.g. regarding the absence of monophyly for Leptopilina RhoGAPs and Leptopilina RacGAP, and the same holds true for the respective V. canescens sequences. It may very well be that the high evolutionary rate of these genes has eroded the phylogenetic signal and prevented proper reconstruction, as the large differences between codon-based and amino acid-based phylogenies and the low support suggest. Explicit hypothesis testing, together with additional data from other taxa, may shed light onto the evolution of this gene family.

The work by Colinet and coworkers communicates sound, novel transcriptomic, proteomic and functional data from complex gene targets, consolidated from an important amount of experimental and bioinformatic work, and related to evolutionarily intriguing and complex phenotypes. These results, and the evolutionary hypothesis proposed to account for them, will be instrumental for our understanding of the evolution and diversity of vesicle-associated RhoGAPs in divergent parasitoid wasps.




Alvarado, G., Holland, S., R., DePerez-Rasmussen, J., Jarvis, B., A., Telander, T., Wagner, N., Waring, A., L., Anast, A., Davis, B., Frank, A., et al. (2020). Bioinformatic analysis suggests potential mechanisms underlying parasitoid venom evolution and function. Genomics 112(2), 1096–1104.

Colinet, D., Cavigliasso, F., Leobold, M., Pichon, A., Urbach, S., Cazes, D., Poullet, M., Belghazi, M., Volkoff, A-N., Drezen, J-M., Gatti, J-L., and Poirié, M. (2024). Convergent origin and accelerated evolution of vesicle-associated RhoGAP proteins in two unrelated parasitoid wasps. bioRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Genomics.

Colinet, D., Schmitz, A., Depoix, D., Crochard, D., and Poirié, M. (2007). Convergent Use of RhoGAP Toxins by eukaryotic parasites and bacterial pathogens. PLoS Pathogens 3(12), e203.

Francino, M.P. (2005). An adaptive radiation model for the origin of new gene functions. Nature Genetics 37, 573–577.

Huang, J., Chen, J., Fang, G., Pang, L., Zhou, S., Zhou, Y., Pan, Z., Zhang, Q., Sheng, Y., Lu, Y., et al. (2021). Two novel venom proteins underlie divergent parasitic strategies between a generalist and a specialist parasite. Nature Communications 12, 234.

Martinson, E., O., Mrinalini, Kelkar, Y. D., Chang, C-H., and Werren, J., H. 2017. The evolution of venom by co-option of single-copy genes. Current Biololgy 27(13), 2007-2013.e8.

Ohno, S. (1970). Evolution by gene duplication. New-York: Springer-Verlag.

Peters, R., S., Krogmann, L., Mayer, C., Donath, A., Gunkel, S., Meusemann, K., Kozlov, A., Podsiadlowski, L., Petersen, M., Lanfear, R., et al. (2017). Evolutionary history of the Hymenoptera. Current Biology 27(7), 1013–1018.

von Reumont, B., M., Anderluh, G., Antunes, A., Ayvazyan, N., Beis, D., Caliskan, F., Crnković, A., Damm, M., Dutertre, S., Ellgaard, L., et al. (2022). Modern venomics—Current insights, novel methods, and future perspectives in biological and applied animal venom research. GigaScience 11, giac048.

Smith, J., J., and Undheim, E., A., B. (2018). True lies: using proteomics to assess the accuracy of transcriptome-based venomics in centipedes uncovers false positives and reveals startling intraspecific variation in Scolopendra subspinipes. Toxins 10(3), 96.

Undheim, E., A., B., and Jenner, R., A. (2021). Phylogenetic analyses suggest centipede venom arsenals were repeatedly stocked by horizontal gene transfer. Nature Communications 12, 818.

Convergent origin and accelerated evolution of vesicle-associated RhoGAP proteins in two unrelated parasitoid waspsDominique Colinet, Fanny Cavigliasso, Matthieu Leobold, Appoline Pichon, Serge Urbach, Dominique Cazes, Marine Poullet, Maya Belghazi, Anne-Nathalie Volkoff, Jean-Michel Drezen, Jean-Luc Gatti, and Marylène Poirié<p>Animal venoms and other protein-based secretions that perform a variety of functions, from predation to defense, are highly complex cocktails of bioactive compounds. Gene duplication, accompanied by modification of the expression and/or functio...Evolutionary genomicsIgnacio Bravo2023-06-12 11:08:31 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 ORCID_LOGO 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).


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.

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.

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.

4. Alkalaeva E, Mikhailova T. Reassigning stop codons via translation termination: How a few eukaryotes broke the dogma. Bioessays. 2017;39.

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.

6. Fernandes NM, Schrago CG. A multigene timescale and diversification dynamics of Ciliophora evolution. Mol Phylogenet Evol. 2019;139: 106521.

7. Crick FH. The origin of the genetic code. J Mol Biol. 1968;38: 367–379.

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