Abstract
The candidate gene approach has been a pioneer in the field of genetic epidemiology, identifying risk alleles and their association with clinical traits. With the advent of rapidly changing technology, there has been an explosion of in silico tools available to researchers, giving them fast, efficient resources and reliable strategies important to find casual gene variants for candidate or genome wide association studies (GWAS). In this review, following a description of candidate gene prioritisation, we summarise the approaches to single nucleotide polymorphism (SNP) prioritisation and discuss the tools available to assess functional relevance of the risk variant with consideration to its genomic location. The strategy and the tools discussed are applicable to any study investigating genetic risk factors associated with a particular disease. Some of the tools are also applicable for the functional validation of variants relevant to the era of GWAS and next generation sequencing (NGS).
Highlights
Candidate gene studies have been at the forefront of genetic association studies i.e. identifying risk variants associated with a particular disease
The SNPinfo Web Server [46] provides many efficient, comprehensive and user friendly tools suited for various purposes such as GenePipe, GenomePipe (Functional single nucleotide polymorphism (SNP) selection), LinkagePipe (SNP selection in one genomic loci of interest), TagSNP, FuncPred and SNPseq, making this a one stop website for initial SNP investigation from scratch
Recent advances in high-throughput experimental technologies like whole-genome gene expression profiling, the genome wide association studies (GWAS), generation DNA, RNA sequencing and CHIP-seq scan the genome for disease associated genetic variants and add knowledge to gene function, regulation, SNP prioritisation resources [123,124]
Summary
Candidate gene studies have been at the forefront of genetic association studies i.e. identifying risk variants associated with a particular disease. The SNPinfo Web Server (http:// snpinfo.niehs.nih.gov/) [46] provides many efficient, comprehensive and user friendly tools suited for various purposes such as GenePipe (for Candidate gene selection), GenomePipe (Functional SNP selection), LinkagePipe (SNP selection in one genomic loci of interest), TagSNP, FuncPred (querying SNP function prediction) and SNPseq (viewing SNPs in their genomic region context, with information on CpG sites), making this a one stop website for initial SNP investigation from scratch. The international HapMap project (http://hapmap.ncbi.nlm.nih.gov/) took the initiative of genotyping sections of human populations worldwide to bring the haplotype map, and accelerate the search for Haplotypes and tag SNPs to narrow down on statistically significant, reviewed disease associated loci, while understanding the patterns of genetic distribution in humans from diverse regions [5] It currently provides this data to allow further analysis and interpretation of GWAS results with the use of imputation. Lirnet (http://www.cs.washington.edu/homes/suinlee/ lirnet/) [122] uses a learning strategy to overcome problems of low population size and correlating SNP effect on gene expression due to large genomic regions being in LD for any given trait, i.e. it learns the ‘regulatory potential’ of a SNP through a Bayesian method from its previously known genomic context (such as regulatory networks and features existing and relevant to the gene) and gives an estimate of likelihood of effecting gene expression
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