Dataset Information

VEXOR: an integrative environment for prioritization of functional variants in fine-mapping analysis.

ABSTRACT:

Motivation

The identification of the functional variants responsible for observed genome-wide association studies (GWAS) signals is one of the most challenging tasks of the post-GWAS research era. Several tools have been developed to annotate genetic variants by their genomic location and potential functional implications. Each of these tools has its own requirements and internal logic, which forces the user to become acquainted with each interface.

Results

From an awareness of the amount of work needed to analyze a single locus, we have built a flexible, versatile and easy-to-use web interface designed to help in prioritizing variants and predicting their potential functional implications. This interface acts as a single-point of entry linking association results with reference tools and relevant experiments.

Availability and implementation

VEXOR is an integrative web application implemented through the Shiny framework and available at: http://romix.genome.ulaval.ca/vexor.

Contact

arnaud.droit@crchuq.ulaval.ca.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Lemacon A

PROVIDER: S-EPMC5860431 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Publications

VEXOR: an integrative environment for prioritization of functional variants in fine-mapping analysis.

Lemaçon Audrey A Joly Beauparlant Charles C Soucy Penny P Allen Jamie J Easton Douglas D Kraft Peter P Simard Jacques J Droit Arnaud A

Bioinformatics (Oxford, England) 20170501 9

<h4>Motivation</h4>The identification of the functional variants responsible for observed genome-wide association studies (GWAS) signals is one of the most challenging tasks of the post-GWAS research era. Several tools have been developed to annotate genetic variants by their genomic location and potential functional implications. Each of these tools has its own requirements and internal logic, which forces the user to become acquainted with each interface.<h4>Results</h4>From an awareness of th ...[more]

PMID: 28453673

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Project description:Coronary artery disease (CAD) is the leading cause of mortality and morbidity driven by both genetic and environmental risk factors. Meta-analyses of genome-wide association studies (GWAS) have identified multiple single nucleotide polymorphisms (SNPs) associated with CAD and myocardial infarction (MI) susceptibility in multi-ethnic populations. The majority of these variants reside in non-coding regulatory regions and are co-inherited with hundreds of candidate regulatory SNPs. Herein, we use integrative genomic, epigenomic, and transcriptomic fine-mapping in human coronary artery smooth muscle cells (HCASMC) and tissues to identify causal regulatory variation and mechanisms responsible for CAD associations. Using these genome-wide maps we prioritize 65 candidate variants and perform allele-specific binding and expression analyses on 7 top candidates. We validate our findings in two independent cohorts of diseased human arterial expression quantitative trait loci (eQTL), which together demonstrate fundamental links between CAD associations and regulatory function in the appropriate disease context. We performed ATAC-seq, ChIP-seq, and RNA-seq on human coronary artery smooth muscle cells grown in SmGM-2 Smooth Muscle Growth Medium-2 including hEGF, insulin, hFGF-B and FBS, but without antibiotics (Lonza, #CC-3182). For ATAC-seq and RNA-seq we performed stimulations with growth factors (TGF-B1, PDGF-BB, PDGF-DD) versus serum-free control. We conducted two biological replicates for each condition using independent donors. For ATAC-seq experiments, sequencing was completed on an Illumina Hiseq 2500, paired-end 50bp reads. For ChIP-seq we performed immunoprecipitations using H3K27ac (Abcam ab4729). We conducted two biological replicates using HCASMC from independent donors, and also did an IgG control for these studies. For RNA-seq we also conducted two replicates using HCASMC from independent donors. For both ChIP-seq and RNA-seq experiments, sequencing was completed on an Illumina HiSeq 2500, paired-end 100bp reads. We also performed ex-vivo ATAC-seq on frozen tissues (isolated media) from normal and atherosclerotic human coronary arteries, using three independent donors for each. Sequencing was also completed on an Illumina HiSeq 2500, paired end 50bp reads.

Dataset Information

VEXOR: an integrative environment for prioritization of functional variants in fine-mapping analysis.

Motivation

Results

Availability and implementation

Contact

Supplementary information

Publications

VEXOR: an integrative environment for prioritization of functional variants in fine-mapping analysis.

Similar Datasets

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