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

Abstract

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 .

Polygenic risk scores for autoimmune related diseases are significantly different and skewed in cancer exceptional responders

“…SNPs in each PRS model were annotated with credible regions based on LD-annot [24]and the genes located in the regions were collected. Genes were then ranked by gene level score: ∑ β i N i where N i is the number of alleles in the NEER cohort for each SNP and β i is the coefficient for the corresponding SNP in the PRS., The R package fgsea[25] was used to compute gene set enrichment analysis based on the GO Biological Process (GOBP) ontology.…”

“…SNPs in each PRS model were annotated with credible regions based on LD-annot [24]and the genes located in the regions were collected. Genes were then ranked by gene level score:…”

Genomic responses to parallel temperature gradients in the eelgrass Zostera marina in adjacent bays

“…To characterize parallel associations with temperature at the SNP level between the two bays, we directly compared the genomic positions of outlier SNPs from the LFMM and OutFLANK analyses. At the gene level, we used LD‐Annot version 0.4 with r 2 = .9 (Prunier et al, 2019) to first identify the genes in linkage disequilibrium with candidate SNPs and then compared lists to detect overlapping genes. Finally, to determine whether there was overlap at the functional level, we tested whether the outlier‐associated gene sets were enriched for particular gene ontology (GO) terms using TopGO version 2.40.0 (Alexa & Rahnenführer, 2009) in R. We used a possible gene universe of all genes within linkage disequilibrium ( r 2 = .9) of the full set of SNPs, rather than the full set of annotated genes.…”

Bio-computing approaches and tools for identification of single nucleotide polymorphisms: a comprehensive review

“…Found SNPs area available at their individual dbSNP entries (http://www.ncbi.nlm.nih.gov/SNP/) (Sachidanandam et al, 2001). Prunier et al (2019) came up with a tool named LD annot to find annotations of polymorphisms based on phenomenon of LD. Authors define that a polymorphism may not be directly responsible for some phenotype but there can be some other polymorphism in neighbouring area with short physical distance which might be causative of some disease.…”

“…The sampling size, number of tested SNPs and candidate SNPs were also different for these datasets. This enabled performance evaluation of the tool (Prunier et al, 2019).…”