2021
DOI: 10.1002/ece3.7959
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BASE: A novel workflow to integrate nonubiquitous genes in comparative genomics analyses for selection

Abstract: Selection can shape the evolution of protein-coding genes by preventing changes in their sequences (purifying selection) or through the fixation of novel adaptive variants (positive selection).Quantifying its nature and strength is a key step to understand the diverse evolutionary histories of orthologous genes across different species and clades. Statistical models of molecular evolution have proven to be fundamental approaches to investigate such processes and can be divided into those based on comparing div… Show more

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Cited by 5 publications
(3 citation statements)
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“…We tested each gene for positive selection via branch-site models (branch-site neutral versus branch-site selection) using codeml from PAML (30), as implemented in BASE (31). We also used BUSTED from the HyPhy software suite (32, 33).…”
Section: Methodsmentioning
confidence: 99%
“…We tested each gene for positive selection via branch-site models (branch-site neutral versus branch-site selection) using codeml from PAML (30), as implemented in BASE (31). We also used BUSTED from the HyPhy software suite (32, 33).…”
Section: Methodsmentioning
confidence: 99%
“…The amino acid alignments were then retro translated to nucleotides using pal2nal [ 61 ], and Gblocks was used to exclude spurious signals coming from misalignments [ 62 ]. We then inferred instances of positive selection using the branch-site model implemented in codeml [ 63 ]; all codeml analyses were carried out using BASE [ 64 ]. Separate analyses were performed using each terminal branch of our phylogeny as the foreground.…”
Section: Methodsmentioning
confidence: 99%
“…An essential metric to detect the selection type driving such sequence evolution is the nucleic acid and amino acid substitution rate, namely, the nonsynonymous ( d N ) to synonymous ( d S ) substitution rate ratio (ω = d N / d S ). This measure has proven to be useful for understanding different evolutionary processes in comparative genomics ( Clark et al 2003 ; Chuang and Li 2004 ; Felsenstein and Felenstein 2004 ; Stark et al 2007 ; Egan et al 2008 ; Fedorova et al 2008 ; Sánchez et al 2011 ; Pan et al 2013 ; Parker et al 2013 ; Li et al 2014 ; Bast et al 2018 ; Glover et al 2019 ; Liu et al 2019 ; Forni et al 2021 ; Policarpo et al 2021 ). Such evolutionary analyses have profited from massive amounts of data derived from next-generation sequencing technologies, making comparative genomics analyses more attainable.…”
Section: Introductionmentioning
confidence: 99%