Biology subjects

Benitiere, F.

Publications and source records attributed to Benitiere, F..

7 recordsLinked to original sources

bioRxiv2026

gVCF2CNV: a scalable pipeline for CNV detection from whole-genome sequencing data

Motivation: Copy-number variants (CNVs) contribute to human disease and population trait variation. CNV detection from large whole-genome sequencing cohorts remains computationally demanding, as most methods require BAM or CRAM files. Genomic VCF (gVCF) files are smaller, routinely generated by standard variant-calling workflows, and contain the read depth and allelic information needed for CNV detection. However, gVCF files are not directly compatible with established CNV callers that rely on Log R Ratio (LRR) and B Allele Frequency (BAF) signals. Results: We present gVCF2CNV, a Nextflow pipeline that converts gVCF files into Log R Ratio and B Allele Frequency signals compatible with established CNV callers. Applied to 12,509 individuals from the SPARK cohort, gVCF2CNV generated signals at an average of 2.7 million SNV positions per individual and completed signal extraction in 4 hours using 192 CPUs. CNV calling with PennCNV and QuantiSNP identified candidate CNVs across a broad size range, with trio-based Mendelian precision reaching approximately 80% or higher for deletions of at least 30 kb and duplications of at least 5 kb. Application to 414,824 individuals from the All of Us cohort was completed in 96 hours, demonstrating feasibility at biobank scale. These results show that gVCF files can serve as a scalable input for CNV detection in large WGS cohorts. Availability and Implementation: gVCF2CNV is available at https://github.com/JacquemontLab/gVCF2CNV, implemented as a Nextflow pipeline with Perl and Python components, supported on Linux. Contact: mame.seynabou.diop@umontreal.ca

bioinformatics↗

bioRxiv2026

MCNV2 (Mendelian CNV Validation): Mendelian Precision for CNV quality assessment

SummaryDetection of copy number variations from genomic sequencing and array data is prone to high false-positive rates. Distinguishing true variation from false positives remains challenging as quality metrics depend on technologies used, the quality of the data, and the calling algorithm. Mendelian inheritance in parent-offspring trios offers a powerful method to detect false positives, yet no tool exists to systematically compute, explore, optimize, and interpret the precision of CNV calls accordingly. Here we present Mendelian CNV Validation (MCNV2), an R package implementing Mendelian Precision (MP), as a reproducible metric for standardized CNV quality assessment. MCNV2 provides a command-line interface for pipeline integration and an interactive Shiny application for real-time exploration of MP across CNV types, size categories, and quality metrics. Availability and ImplementationMCNV2 is available at https://github.com/JacquemontLab/MCNV2-Mendelian-CNV-Validation. Contactmame.seynabou.diop@umontreal.ca Supplementary InformationSupplementary information are available at https://mcnv2-mendelian-cnv-validation.readthedocs.io/en/latest/

genetics↗

bioRxiv2026

Breaking the species barrier: recurrent genomic introgressions from very distant lineages in a ciliate

The process of speciation, through which two reproductively isolated species emerge from an ancestral population, is often gradual, including a period during which gene flow still occurs, and hence speciation remains reversible. However, if isolation persists, the progressive accumulation of genetic incompatibilities ultimately locks the speciation process, reaching the point where hybrid offspring are inviable or sterile. In plants and animals, the establishment of species barriers is quite rapid: beyond a net genetic divergence of 0.02 substitutions per synonymous site, interspecific introgressions become extremely rare. Here we report that in ciliates, species barriers can be broken despite huge genetic divergence. We show that the genome of Paramecium sonneborni contains hundreds of DNA segments that were acquired by recurrent horizontal transfers from multiple very distant lineages (synonymous divergence [~]1 substitution/site). These segments approach the size of full-length chromosomes, which indicates that they were introgressed by inter-specific mating. These data show that in the ancestry of P. sonneborni, hybridization events with highly divergent species occurred repeatedly and led to viable and fertile offspring. We propose that this unexpected promiscuous sexual behavior is made possible by the fact that paramecia separate somatic and germline functions in two types of nuclei: the elimination of non-self DNA fragments during the development of the somatic genome allows individuals of a species to remain phenotypically the same, despite recurrent genetic flow from distant species into their germline. Significance StatementAn important issue in evolutionary biology is to understand the process of speciation, i.e. how two reproductively isolated species emerge from an ancestral population. Various factors can initiate the speciation process, but whatever the initial factor, once two populations become reproductively isolated, they start accumulating genetic incompatibilities. In plants and animals these incompatibilities accumulate rapidly, preventing the formation of viable and fertile hybrids, except between very closely related species. We show here that this rule does not apply to all eukaryotes. We discovered that the unicellular eukaryote Paramecium sonneborni recurrently acquired large DNA segments via hybridization with very distantly related species. This unexpected phenomenon highlights the diversity of factors that affect the delineation of species across eukaryotes.

evolutionary biology↗

bioRxiv2025

Genetic and Cortical Cell-Type Liability Architecture of Autism

Autism Spectrum Disorders (ASD) can result from rare genetic variants interfering with brain development. Whether their effects converge on specific cortical cell types remains unresolved. Previous studies have focused on a narrow set of high-confidence ASD (hcASD) genes, which were enriched in neuronal cell types during prenatal development. By contrast, studies of postnatal cerebral cortex have repeatedly associated ASD with transcriptional changes in both neurons and glia. To comprehensively map ASD genetic liability across cortical cell types, we conducted a functional genetic burden analysis with 124,416 individuals, including ASD probands and unaffected family members. We examined six classes of rare gene-disrupting variants aggregated across a complete spectrum of transcriptomic cell types of the human prefrontal cortex throughout development. We show that cellular liabilities in ASD delineate a broad and developmentally dynamic architecture. Likewise, we uncover high dependency on classes of variants with Loss-of-Function (LoF) and de novo linked to prenatal cells, while duplications, missense, and inherited variants increase liability through postnatal and glial cell types. Notably, inherited LoF variants uncover the contribution of microglia to ASD liability, also supported by transcriptomic evidence from postmortem ASD brains. Finally, we show that overall, variants disrupting genes differentially expressed in postmortem ASD brains significantly contribute to ASD liability, demonstrating convergence between disrupted transcriptomes and genetic liability. Together, our study offers an integrative, cell-type-aware framework for interpreting ASD risk genetics.

genomics↗

bioRxiv2024

Variation in the fitness impact of translationally optimal codons among animals

Early studies in invertebrate model organisms (fruit flies, nematodes) showed that their synonymous codon usage is under selective pressure to optimize translation efficiency in highly expressed genes (a process called translational selection). In contrast, mammals show little evidence of selection for translationally optimal codons. To understand this difference, we examined the use of synonymous codons in 223 metazoan species, covering a wide range of animal clades. For each species, we predicted the set of optimal codons based on the pool of tRNA genes present in its genome, and we analyzed how the frequency of optimal codons correlates with gene expression to quantify the intensity of translational selection (S). Surprisingly, few metazoans show clear signs of translational selection. As predicted by the nearly neutral theory, the highest values of S are observed in species with large effective population sizes (N e). Overall, however, N e appears to be a poor predictor of the intensity of translational selection, suggesting important differences in the fitness effect of synonymous codon usage across taxa. We propose that the few animal taxa that are clearly affected by translational selection correspond to organisms with strong constraints for a very rapid growth rate.

genomics↗

bioRxiv2024

GTDrift: A resource for exploring the interplay between genetic drift, genomic and transcriptomic characteristics in eukaryotes

We present GTDrift, a comprehensive data resource that enables explorations of genomic and transcriptomic characteristics alongside proxies of the intensity of genetic drift in individual species. This resource encompasses data for 1,506 eukaryotic species, including 1,413 animals and 93 green plants, and is organized in three components. The first two components contain approximations of the effective population size, which serve as indicators of the extent of random genetic drift within each species. In the first component, we meticulously investigated public databases to assemble data on life history traits such as longevity, adult body length and body mass for a set of 979 species. The second component includes estimations of the ratio between the rate of non-synonymous substitutions and the rate of synonymous substitutions (dN/dS) in protein-coding sequences for 1,324 species. This ratio provides an estimate of the efficiency of natural selection in purging deleterious substitutions. Additionally, we present polymorphism-derived Ne estimates for 66 species. The third component encompasses various genomic and transcriptomic characteristics. With this component, we aim to facilitate comparative transcriptomics analyses across species, by providing easy-to-use processed data for more than 16,000 RNA-seq samples across 491 species. These data include intron-centered alternative splicing frequencies, gene expression levels and sequencing depth statistics for each species, obtained with a homogeneous analysis protocol. To enable cross-species comparisons, we provide orthology predictions for conserved single-copy genes based on BUSCO gene sets. To illustrate the possible uses of this database, we identify the most frequently used introns for each gene and we assess how the sequencing depth available for each species affects our power to identify major and minor splice variants.

evolutionary biology↗

bioRxiv2022

Random genetic drift sets an upper limit on mRNA splicing accuracy in metazoans

Most eukaryotic genes undergo alternative splicing (AS), but the overall functional significance of this process remains a controversial issue. It has been noticed that the complexity of organisms (assayed by the number of distinct cell types) correlates positively with their genome-wide AS rate. This has been interpreted as evidence that AS plays an important role in adaptive evolution by increasing the functional repertoires of genomes. However, this observation also fits with a totally opposite interpretation: given that complex organisms tend to have small effective population sizes (Ne), they are expected to be more affected by genetic drift, and hence more prone to accumulate deleterious mutations that decrease splicing accuracy. Thus, according to this "drift barrier" theory, the elevated AS rate in complex organisms might simply result from a higher splicing error rate. To test this hypothesis, we analyzed 3,496 transcriptome sequencing samples to quantify AS in 53 metazoan species spanning a wide range of Ne values. Our results show a negative correlation between Ne proxies and the genome-wide AS rates among species, consistent with the drift barrier hypothesis. This pattern is dominated by low abundance isoforms, which represent the vast majority of the splice variant repertoire. We show that these low abundance isoforms are depleted in functional AS events, and most likely correspond to errors. Conversely, the AS rate of abundant isoforms, which are relatively enriched in functional AS events, tends to be lower in more complex species. All these observations are consistent with the hypothesis that variation in AS rates across metazoans reflects the limits set by drift on the capacity of selection to prevent gene expression errors.

evolutionary biology↗