Selectome update: quality control and computational improvements to a database of positive selection

Moretti, Sébastien; Laurenczy, Balazs; Gharib, Walid H.; Castella, Briséïs; Kuzniar, Arnold; Schabauer, Hannes; Studer, Romain A.; Valle, M.; Salamin, Nicolas; Stockinger, Heinz; Robinson‐Rechavi, Marc

doi:10.1093/nar/gkt1065

Cited by 71 publications

(105 citation statements)

References 23 publications

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“…We first asked whether the genes harboring GMAS exons were enriched with those undergoing positive selection. About 46% (246 out of 538) of GMAS genes were categorized as positively selected genes in the Selectome database (Moretti et al 2014). This fraction is significantly higher than that among all known human genes (10%) and that among genes undergoing AS (30%) based on the ENCODE RNA-seq data (Fig.…”

Section: Gmas-related Genes Exons and Snvs Undergo Positive Or Balamentioning

confidence: 99%

Alternative splicing modulated by genetic variants demonstrates accelerated evolution regulated by highly conserved proteins

et al. 2016

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Identification of functional genetic variants and elucidation of their regulatory mechanisms represent significant challenges of the post-genomic era. A poorly understood topic is the involvement of genetic variants in mediating post-transcriptional RNA processing, including alternative splicing. Thus far, little is known about the genomic, evolutionary, and regulatory features of genetically modulated alternative splicing (GMAS). Here, we systematically identified intronic tag variants for genetic modulation of alternative splicing using RNA-seq data specific to cellular compartments. Combined with our previous method that identifies exonic tags for GMAS, this study yielded 622 GMAS exons. We observed that GMAS events are highly cell type independent, indicating that splicing-altering genetic variants could have widespread function across cell types. Interestingly, GMAS genes, exons, and single-nucleotide variants (SNVs) all demonstrated positive selection or accelerated evolution in primates. We predicted that GMAS SNVs often alter binding of splicing factors, with SRSF1 affecting the most GMAS events and demonstrating global allelic binding bias. However, in contrast to their GMAS targets, the predicted splicing factors are more conserved than expected, suggesting that cis-regulatory variation is the major driving force of splicing evolution. Moreover, GMAS-related splicing factors had stronger consensus motifs than expected, consistent with their susceptibility to SNV disruption. Intriguingly, GMAS SNVs in general do not alter the strongest consensus position of the splicing factor motif, except the more than 100 GMAS SNVs in linkage disequilibrium with polymorphisms reported by genome-wide association studies. Our study reports many GMAS events and enables a better understanding of the evolutionary and regulatory features of this phenomenon.

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Section: Gmas-related Genes Exons and Snvs Undergo Positive Or Balamentioning

confidence: 99%

Alternative splicing modulated by genetic variants demonstrates accelerated evolution regulated by highly conserved proteins

et al. 2016

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“…To compare the results of VESPA to other pipelines and predictions of positive selection, we used a dataset of 18 gene families from the Selectome database (Moretti et al, 2014). A tarball of the data and results of the VESPA analysis of 18 gene families (i.e., input sequences, alignments, trees, codeml output, VESPA summary at each phase) have been provided in File S1.…”

Section: Resultsmentioning

confidence: 99%

“…We carried out two tests with the dataset from Selectome (Release 6) (Moretti et al, 2014). Firstly we wished to assess if the way in which VESPA automatically sets up all codon models, labeling of foreground lineages and LRTs produced comparable results with those from the Selectome pipeline.…”

Section: Resultsmentioning

confidence: 99%

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VESPA: Very large-scale Evolutionary and Selective Pressure Analyses

Webb

Walsh

O’Connell

2017

PeerJ Computer Science

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Background. Large-scale molecular evolutionary analyses of protein coding sequences requires a number of preparatory inter-related steps from finding gene families, to generating alignments and phylogenetic trees and assessing selective pressure variation. Each phase of these analyses can represent significant challenges, particularly when working with entire proteomes (all protein coding sequences in a genome) from a large number of species. Methods. We present VESPA, software capable of automating a selective pressure analysis using codeML in addition to the preparatory analyses and summary statistics. VESPA is written in python and Perl and is designed to run within a UNIX environment. Results. We have benchmarked VESPA and our results show that the method is consistent, performs well on both large scale and smaller scale datasets, and produces results in line with previously published datasets. Discussion. Large-scale gene family identification, sequence alignment, and phylogeny reconstruction are all important aspects of large-scale molecular evolutionary analyses. VESPA provides flexible software for simplifying these processes along with downstream selective pressure variation analyses. The software automatically interprets results from codeML and produces simplified summary files to assist the user in better understanding the results. VESPA may be found at the following website: http://www.mol-evol.org/VESPA.

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“…The FunFHMMer method has subdivided 2735 CATH superfamilies into 110 439 subfamilies (FunFams) with increased functional coherency [42]. Similarly, the Selectome database has predicted positive selection across thousands of vertebrate protein phylogenies, facilitating large-scale exploration of adaptive evolution [43].…”

Section: Detecting Functional Shifts In Sequencesmentioning

confidence: 99%