Decoding basic GWAS: The beginnerrsquo;s guide

Abstract

A genome-wide association study (GWAS) is a research approach used to identify genomic variants that are statistically associated with a particular trait or trait of interest. GWAS study finds associated genes with traits/diseases throughout the genome using SNP’s (Single Nucleotide Polymorphism) to determine the location of these genes. SNP can determine the genetic diversity between closely related individuals. GWAS is an efficient approach to study the mechanism behind the complex trait viz., metabolic, or biochemical pathway. The various statistical tools are necessary for computation of association between various genotypes. GWAS mainly uses Minor Allele Frequency (MAF), Linkage Disequilibrium (LD) and P-value to analyze SNPs. On the determination of this value Manhattan Plot was drawn and then association between phenotype and concern genotype was determined. The technique is used for advancement of crops in terms of biotic resistance, abiotic tolerance, improvement in yield and metabolic composition of various crops viz., Maize, Rice, Wheat, Cotton, etc. Any other mapping not as robust as GWAS in terms of discovering the candidate gene, unknown biochemical pathway, finding specific genetic association, etc. Genome-wide association studies (GWAS) have been even more successful in plants than in humans. Mapping approaches can be extended to dissect adaptive genetic variation from structured background variation in an ecological context. These methods, when combined with the increasing capacity and decreasing costs of next-generation sequencing, will allow GWAS in non-model species. As GWAS utilizes a large population, they get a chance to screen a large number of SNPs there by helping to get results more proper.