DGINN, an automated and highly-flexible pipeline for the Detection of Genetic INNovations on protein-coding genes

Abstract

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. Here, 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 different 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. The results obtained with DGINN confirm and also expand results from the literature, establishing DGINN as an efficient tool to automatically detect genetic innovations and adaptive evolution in diverse datasets, from the user's gene of interest to a large gene list in any species range. Running Title: DGINN, an automated pipeline to Detect Genetic INNovations

Bacterial factors drive the differential targeting of Guanylate Binding Proteins toFrancisellaandShigella

“…GBPs are present as a multigene family in vertebrates. The GBP family exhibits signs of strong evolutionary pressure with gene loss, gene duplication and neofunctionalisation (1)(2)(3) indicative of a selective adaptation to pathogens. Eleven GBPs are encoded in mice while seven GBPs are present in humans (4).…”

Distinct evolutionary trajectories of SARS-CoV-2 interacting proteins in bats and primates identify important host determinants of COVID-19

“…To perform the phylogenetic and positive selection analyses, we used the Detection of genetic innovation DGINN bioinformatic pipeline (Picard et al, 2020) that entirely automates the analyses and combines several methods to test for selection across large datasets (Figure 1A). Briefly, from each of the 334 human reference gene sequences, DGINN automatically retrieved bat and primate homologs (from NCBI nr database), curated the coding sequences, and performed a codon-alignment followed by a gene phylogenetic reconstruction (Figure 1A, Table S1).…”

“…Finally, each aligned set of orthologs was used to measure rates of codon substitutions and to estimate whether the whole gene, as well as any codon, are evolving under positive selection. For this, DGINN uses a combination of methods from the following selection tools: HYPHY (BUSTED and MEME), PAML (Codeml M0, M1, M2, M7, M8, and associated Bayesian Empirical Bayes (BEB) for codon-specific analyses), and bpp (M0 NS , M1 NS , M2 NS , M7 NS , M8 NS , and associated Posterior Probabilities (PP) for codon-specific analyses) (Figure 1A, Methods for details, Picard et al 2020) (Guéguen et al, 2013; Pond et al, 2005; Yang, 2007).…”

“…Here, we aimed to identify key SARS-CoV adaptive loci and functional genomic differences between bats, which include the natural reservoir of SARS-CoVs, and primates, including humans. We performed high-throughput evolutionary and positive selection screens of 334 SARS-CoV-2 interacting proteins (Gordon et al, 2020) using the Detection of Genetic INNovation (DGINN) pipeline (Picard et al, 2020), followed by comprehensive functional-genetic analyses of seven VIPs of interest. We provide the results in the searchable VirHostNet 2.0 web portal.…”

Rapid evolution of mammalian HERC6 and independent duplication of a chimeric HERC5/6 gene in rodents and bats suggest an overlooked role of HERCs in antiviral innate immunity

“…While these studies have provided important insights into the diversification of HERCs, the evolutionary analyses have certain limitations: (i) the scarcity of species analyzed (only 12 species, versus 81 species with at least 10 species per order in this current study), (ii) the overrepresentation of primates compared to other mammalian species (seven primates, two to three carnivores, two artiodactyls and one perissodactyl), (iii) the integration of highly divergent species, which may bias the genetic inferences by increasing the number of false positives (37). Moreover, a recent study in primates have shown differences in HERC5 and HERC6 selective pressures (38). Therefore, how HERC5 and HERC6 genes have evolved within mammalian orders has not been fully deciphered.…”