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Articles by Thomas Bataillon
Natural variation in root exudate composition in the genetically structured Arabidopsis thaliana in the Iberian Peninsula
Introduction Plant root exudates encompass a vast array of primary (e.g. carbohydrates, amino acids, and organic acids) and secondary metabolites (e.g. flavonoids, terpenoids, and alkaloids) that shape the physical, chemical, and biological properties of the soil (Oburger & Jones, 2018). They also facilitate nutrient cycling and mediate biotic interactions in the rhizosphere, thereby fostering a healthy soil ecosystem (Badri & Vivanco, 2009; Rasmann & Hiltpold, 2022).
Natural variation in root exudate composition in the genetically structured Arabidopsis thaliana in the Iberian Peninsula
Abstract Plant root exudates are involved in nutrient acquisition, microbial partnerships, and inter-organism signaling. Yet, little is known about the genetic and environmental drivers of root exudate variation at large geographical scales, which may help understand evolutionary trajectories of plants in heterogeneous environments. We quantified natural variation in chemical composition of Arabidopsis thaliana root exudates in 105 Iberian accessions.
Estimating gene conversion tract length and rate from PacBio HiFi data
Abstract Gene conversions are broadly defined as the transfer of genetic material from a 'donor' to an 'acceptor' sequence and can happen both in meiosis and mitosis. They are a subset of non-crossover events and like crossover events, gene conversion can generate new combinations of alleles, erode linkage disequilibrium, and even counteract the mutation load by reverting germline mutations through GC-biased gene conversion.
fastDFE: fast and flexible inference of the distribution of fitness effects
Abstract Estimating the distribution of fitness effects (DFE) of new mutations is of fundamental importance in evolutionary biology, ecology, and conservation. However, existing methods for DFE estimation suffer from limitations, such as slow computation speed and limited scalability. To address these issues, we introduce fastDFE, a Python-based software package, offering fast and flexible DFE inference from site-frequency spectrum (SFS) data.
fastDFE: fast and flexible joint inference of the distribution of fitness effects
Abstract Estimating the distribution of fitness effects (DFE) of new mutations is of fundamental importance in evolutionary biology, ecology, and conservation. However, existing methods for DFE estimation suffer from limitations, such as slow computation speed and limited scalability. To address these issues, we introduce fastDFE, a Python-based software package, offering fast and flexible DFE inference from site-frequency spectrum (SFS) data.
Comparison of the full distribution of fitness effects of new amino acid mutations across great apes
New Results View ORCID ProfileDavid Castellano, Moisès Coll Macià, Paula Tataru, Thomas Bataillon, Kasper Munch doi: https://doi.org/10.1101/696971 Abstract The distribution of fitness effects (DFE) is central to many questions in evolutionary biology. However, little is known about the differences in DFEs between closely related species. We use more than 9,000 coding genes orthologous one-to-one across great apes, gibbons, and macaques to assess the stability of the DFE across great apes.
Selective sweeps under dominance and self-fertilisation
AbstractA major research goal in evolutionary genetics is to uncover loci experiencing adaptation from genomic sequence data. One approach relies on finding 'selective sweep' patterns, where segregating adaptive alleles reduce diversity at linked neutral loci. Recent years have seen an expansion in modelling cases of 'soft' sweeps, where the common ancestor of derived variants predates the onset of selection.
The fitness landscape of the codon space across environments
The fitness landscape of the codon space across environments Inês Fragata, Sebastian Matuszweski, Mark A. Schmitz, Thomas Bataillon, Jeffrey D. Jensen, Claudia Bank bioRxiv 252395; doi: https://doi.org/10.1101/252395
Identifying drivers of parallel evolution: A regression model approach
Identifying drivers of parallel evolution: A regression model approach Susan F Bailey, Qianyun Guo, Thomas Bataillon bioRxiv 118695; doi: https://doi.org/10.1101/118695
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