Biology subjects

Lespinet, O.

Publications and source records attributed to Lespinet, O..

7 recordsLinked to original sources

bioRxiv2026

Interspecies Differential Gene Expression Analysis with Regularized Phylogenetic Linear Models

Comparative transcriptomic datasets are increasingly used to investigate the molecular basis of phenotypic diversification across species. However, finding genes that are differentially expressed (DE) between lineages remains challenging, for two main reasons. First, the random evolutionary drift can blur the signal left by lineage-specific shifts in mean expression, and induces phylogenetic correlations that, if ignored, can widely inflate the False Discovery Rate (FDR), i.e., the amount of spuriously detected genes. Second, DE analysis from RNA-Seq data involves multiple testing on many genes for a small number of individual measurements with high noise, and requires dedicated statistical tools. Traditional DE tools, such as limma, and classical Phylogenetic Comparative Methods (PCMs), such as the Expression Variance and Evolution (EVE) model, are both designed to tackle one of these two challenges alone, but both fail in the context of inter-species RNA-Seq data. In this work, we present phyloDE, a new tool for inter-species DE, that aims at taking the best from both approaches. On simulations based on a recently published four-species rodent dataset, we show that, contrary to other methods, phyloDE correctly controls the FDR in all settings, while keeping a reasonable power. When reanalyzing the empirical dataset, phyloDE discovers more DE genes that exhibit consistent changes in their cis-regulatory landscape compared to EVE in all the experimental settings. The method is implemented in R, with an interface inheriting from limma.

evolutionary biology↗

bioRxiv2024

SYNTERUPTOR: mining genomic islands for non-classical specialised metabolite gene clusters

Microbial specialised metabolite biosynthetic gene clusters (SMBGCs) are a formidable source of natural products of pharmaceutical interest. With the multiplication of genomic data available, very efficient bioinformatic tools for automatic SMBGC detection have been developed. Nevertheless, most of these tools identify SMBGCs based on sequence similarity with enzymes typically involved in specialised metabolism and thus may miss SMBGCs coding for under characterised enzymes. Here we present SYNTERUPTOR (https://bioi2.i2bc.paris-saclay.fr/synteruptor), a program that identifies genomic islands, known to be enriched in SMBGCs, in the genomes of closely related species. With this tool, we identified a SMBGC in the genome of Streptomyces ambofaciens ATCC23877, undetected by earlier versions of antiSMASH, and experimentally demonstrated that it directs the biosynthesis of two metabolites, one of which was identified as sphydrofuran. SYNTERUPTOR is also a valuable resource for the delineation of individual SMBGCs within antiSMASH regions that may encompass multiple clusters, and for refining the boundaries of these SMBGCs.

bioinformatics↗

bioRxiv2023

The Ribosome Profiling landscape of yeast reveals a high diversity in pervasive translation

Pervasive translation is a widespread phenomenon that plays an important role in de novo gene birth; however, its underlying mechanisms remain unclear. Based on multiple Ribosome Profiling (Ribo-Seq) datasets, we investigated the RiboSeq landscape of coding and noncoding regions of yeast. Therefore, we developed a representation framework which allows the visual representation and rational classification of the entire diversity of Ribo-Seq signals that could be observed in yeast. We show that if coding regions are restricted to specific areas of the Ribo-Seq landscape, noncoding regions are associated with a wide diversity of translation signals and, conversely, populate the entire yeast Ribo-Seq landscape. Specifically, we reveal that noncoding regions are associated with canonical translation signals, but also with non-canonical ones absent from coding regions, and which appear to be a hallmark of pervasive translation. Notably, we report thousands of translated noncoding ORFs among which, 251 led to detectable products with Mass Spectrometry while being characterized by a wide range of translation specificities. Overall, we show that pervasive translation is not random with noncoding ORF translation signals being consistent across Ribo-Seq experiments. Finally, we show that the translation signal of noncoding ORFs is not explained by features related to the emergence of function, but rather determined by the translation start codon and the codon distribution in their two alternative frames. Overall, our results enable us to propose a topology of the pervasive Ribo-Seq landscape of a species, and open the way to future comparative analyses of this translation landscape under different conditions.

evolutionary biology↗

bioRxiv2022

Detection of orthologous genes with expression shifts linked to nickel hyperaccumulation across Eudicots

The remarkable capacity of plants to tolerate and accumulate tremendous amount of nickel is a complex adaptative trait that appeared independently in more than 700 species distributed in about fifty families. Nickel hyperaccumulation is thus proposed as a model to investigate the evolution of complex traits in plants. However, the mechanisms involved in nickel hyperaccumulation are still poorly understood in part because comparative transcriptomic analyses struggle to identify genes linked to this trait from a wide diversity of species. In this work, we have implemented a methodology based on the quantification of the expression of orthologous groups and phylogenetic comparative methods to identify genes which expression is correlated to the nickel hyperaccumulation trait. More precisely, we performed de novo transcriptome assembly and reads quantification for each species on its own transcriptome using available RNA-Seq datasets from 15 nickel hyperaccumulator and non-accumulator species. Assembled contigs were associated to orthologous groups built using proteomes predicted from completed plant genome sequences. We then analyzed the transcription profiles of 5953 orthologous groups from distant species using a phylogenetic ANOVA. We identified 31 orthologous groups with an expression shift associated with nickel hyperaccumulation. These orthologous groups correspond to genes that have been previously implicated in nickel accumulation, and to new candidates involved in this trait. We thus believe that this method can be successfully applied to identify genes linked to other complex traits from a wide diversity of species.

plant biology↗

bioRxiv2022

Benchmark of Differential Gene Expression Analysis Methods for Inter-species RNA-Seq Data using a Phylogenetic Simulation Framework

Inter-species RNA-Seq datasets are increasingly common, and have the potential to answer new questions on gene expression patterns across the evolution. Single species differential expression analysis is a now well studied problem, that benefits from sound statistical methods. Extensive reviews on biological or synthetic datasets have provided the community with a clear picture on the relative performances of the available tools in various settings. Such benchmarks are still missing in the inter-species gene expression context. In this work, we take a first step in this direction by developing and implementing a new simulation framework. This tool builds on both the RNA-Seq and the Phylogenetic Comparative Methods literatures to generate realistic count datasets, while taking into account the phylogenetic relationships between the samples. We illustrate the features of this new framework through a targeted simulation study, that reveals some of the strengths and weaknesses of both the classical and phylogenetic approaches for inter-species differential expression analysis. The tool has been integrated in the R package compcodeR freely available on Bioconductor.

bioinformatics↗

bioRxiv2021

Intergenic ORFs as elementary structural modules of de novo gene birth and protein evolution

The noncoding genome plays an important role in de novo gene birth and in the emergence of genetic novelty. Nevertheless, how noncoding sequences properties could promote the birth of novel genes and shape the evolution and the structural diversity of proteins remains unclear. Therefore, by combining different bioinformatic approaches, we characterized the fold potential diversity of the amino acid sequences encoded by all intergenic ORFs (Open Reading Frames) of S. cerevisiae with the aim of (i) exploring whether the large structural diversity observed in proteomes is already present in noncoding sequences, and (ii) estimating the potential of the noncoding genome to produce novel protein bricks that can either give rise to novel genes or be integrated into pre-existing proteins, thus participating in protein structure diversity and evolution. We showed that amino acid sequences encoded by most yeast intergenic ORFs contain the elementary building blocks of protein structures. Moreover, they encompass the large structural diversity of canonical proteins with strikingly the majority predicted as foldable. Then, we investigated the early stages of de novo gene birth by identifying intergenic ORFs with a strong translation signal in ribosome profiling experiments and by reconstructing the ancestral sequences of 70 yeast de novo genes. This enabled us to highlight sequence and structural factors determining de novo gene emergence. Finally, we showed a strong correlation between the fold potential of de novo proteins and the one of their ancestral amino acid sequences, reflecting the relationship between the noncoding genome and the protein structure universe.

evolutionary biology↗

bioRxiv2020

Dynamics of the compartmentalized Streptomyces chromosome during metabolic differentiation

Streptomyces are among the most prolific bacterial producers of specialized metabolites, including antibiotics. The linear chromosome is partitioned into a central region harboring core genes and two extremities enriched in specialized metabolite biosynthetic gene clusters (SMBGCs). The molecular mechanisms governing structure and function of these compartmentalized genomes remain mostly unknown. Here we show that in exponential phase, chromosome structure correlates with genetic compartmentalization: conserved, large and highly transcribed genes form boundaries that segment the central part of the chromosome into domains, whereas the terminal ends are transcriptionally, largely quiescent compartments with different structural features. Onset of metabolic differentiation is accompanied by remodeling of chromosome architecture from an open to a rather closed conformation, in which the SMBGCs are expressed forming new boundaries. Altogether, our results reveal that S. ambofaciens linear chromosome is partitioned into structurally distinct entities, indicating a link between chromosome folding, gene expression and genome evolution.

microbiology↗