Press Release Ecofect - 21 September 2020

DGINN, an automated pipeline to Detect Genetic INNovations

Adaptive evolution has shaped major biological processes. Finding the protein-coding genes and the sites that have been subjected to adaptation during evolutionary time is a major endeavor. However, very few methods fully automate the identification of positively selected genes, and widespread sources of genetic innovations as gene duplication and recombination are absent from most pipelines. Thanks to a collaborative work between teams from the Biometry and Evolutive Biology Laboratory (LBBE, UMR CNRS 5558, Lyon 1 University) and the International Center for Research In infectiology (CIRI, Inserm U1111, CNRS, ENS Lyon, Lyon 1 University) and funded by the Ecofect LabEx under the GrASP project, we developed DGINN, a highly-flexible and public pipeline to Detect Genetic INNovations and adaptive evolution in protein-coding genes. DGINN automates, from a gene’s sequence, all steps of the evolutionary analyses necessary to detect the aforementioned innovations, including the search for homologues in databases, assignation of orthology groups, identification of duplication and recombination events, as well as detection of positive selection using five methods to increase precision and ranking of genes when a large panel is analyzed. DGINN was validated on nineteen genes with previously-characterized evolutionary histories in primates, including some engaged in host-pathogen arms-races. Our results confirm and expand results from the literature, including novel findings on the Guanylate-binding protein family, GBPs. This establishes DGINN as an efficient tool to automatically detect genetic innovations and adaptive evolution in diverse datasets, from the user’s gene of interest to large gene lists in any species range.

Keywords : Adaptation, positive selection, duplication, bioinformatics pipeline, recombination, evolution of protein-coding genes, genetic conflict, host-pathogen interaction, primates, HIV, virus.

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Important ! The pipeline is publicly available on GitHub and as a Docker.
 

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