LD-annot: A Bioinformatics Tool to Automatically Provide Candidate SNPs With Annotations for Genetically Linked Genes.

SNP annotation SNP chip analyses bioinformatics tool candidate SNP linkage disequilibrium variant call format (VCF)

Journal

Frontiers in genetics
ISSN: 1664-8021
Titre abrégé: Front Genet
Pays: Switzerland
ID NLM: 101560621

Informations de publication

Date de publication:
2019
Historique:
received: 02 07 2019
accepted: 28 10 2019
entrez: 19 12 2019
pubmed: 19 12 2019
medline: 19 12 2019
Statut: epublish

Résumé

A multitude of model and non-model species studies have now taken full advantage of powerful high-throughput genotyping advances such as SNP arrays and genotyping-by-sequencing (GBS) technology to investigate the genetic basis of trait variation. However, due to incomplete genome coverage by these technologies, the identified SNPs are likely in linkage disequilibrium (LD) with the causal polymorphisms, rather than be causal themselves. In addition, researchers could benefit from annotations for the identified candidate SNPs and, simultaneously, for all neighboring genes in genetic linkage. In such case, LD extent estimation surrounding the candidate SNPs is required to determine the regions encompassing genes of interest. We describe here an automated pipeline, "LD-annot," designed to delineate specific regions of interest for a given experiment and candidate polymorphisms on the basis of LD extent, and furthermore, provide annotations for all genes within such regions. LD-annot uses standard file formats, bioinformatics tools, and languages to provide identifiers, coordinates, and annotations for genes in genetic linkage with each candidate polymorphism. Although the focus lies upon SNP arrays and GBS data as they are being routinely deployed, this pipeline can be applied to a variety of datasets as long as genotypic data are available for a high number of polymorphisms and formatted into a vcf file. A checkpoint procedure in the pipeline allows to test several threshold values for linkage without having to rerun the entire pipeline, thus saving the user computational time and resources. We applied this new pipeline to four different sample sets: two breeding populations GBS datasets, one within-pedigree SNP set coming from whole genome sequencing (WGS), and a very large multi-varieties SNP dataset obtained from WGS, representing variable sample sizes, and numbers of polymorphisms. LD-annot performed within minutes, even when very high numbers of polymorphisms are investigated and thus will efficiently assist research efforts aimed at identifying biologically meaningful genetic polymorphisms underlying phenotypic variation. LD-annot tool is available under a GPL license from https://github.com/ArnaudDroitLab/LD-annot.

Identifiants

pubmed: 31850063
doi: 10.3389/fgene.2019.01192
pmc: PMC6889475
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1192

Informations de copyright

Copyright © 2019 Prunier, Lemaçon, Bastien, Jafarikia, Porth, Robert and Droit.

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Auteurs

Julien Prunier (J)

Genomics Center, Centre Hospitalier Universitaire de Québec-Université Laval Research Center, Quebec, QC, Canada.
Forestry Research Centre, Forestry Department, Université Laval, Quebec, QC, Canada.

Audrey Lemaçon (A)

Genomics Center, Centre Hospitalier Universitaire de Québec-Université Laval Research Center, Quebec, QC, Canada.

Alexandre Bastien (A)

Faculty of Agricultural and Food Science, Université Laval, Quebec, QC, Canada.

Mohsen Jafarikia (M)

Canadian Centre for Swine Improvement, Ottawa, ON, Canada.
Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada.

Ilga Porth (I)

Forestry Research Centre, Forestry Department, Université Laval, Quebec, QC, Canada.

Claude Robert (C)

Forestry Research Centre, Forestry Department, Université Laval, Quebec, QC, Canada.

Arnaud Droit (A)

Genomics Center, Centre Hospitalier Universitaire de Québec-Université Laval Research Center, Quebec, QC, Canada.

Classifications MeSH