MutMap: a versatile tool for identification of mutant loci and mapping of genes

Abstract

With the advancement of sequencing technologies and improvement in data analysis tools, draft genomes of many organisms are readily available. Accessibility to such draft genome sequences assists researchers, especially, plant breeders, to rapidly identify genomic regions contributing to the observed phenotypic variation leading to identification of candidate genes for a particular trait. Traditionally gene mapping is a complex, time-consuming and costly affair requiring large mapping populations and abundant molecular markers spread across the entire linkage groups. With the emergence of re-sequencing techniques, quick mapping of genes has become possible with reduced time and cost by using approaches like SHOREmap, NGM and MutMap methodologies. Among these, MutMap is widely used because it is more focused on causal SNPs. This is made possible by generating a backcross population of the mutant genotype with the parent (wild type), thereby removing the false SNPs and retaining only the SNPs linked to the mutant phenotype. Improved and specialized methods of MutMap like MutMap+, MutMap-Gap, and QTL-Seq have also emerged to expand the horizon of application of MutMap approach. The Mutmap+ methodology is specially designed for capturing those traits where the homozygous mutant leads to either lethality or sterility. MutMap-Gap methodology identifies the mutation site present in the gap regions of the reference genome, whereas QTL-Seq is an improved version of MutMap, specially designed for mapping of quantitative trait loci (QTLs). All these methods are akin to bulked segregant analysis popularly employed for mapping simply inherited traits. These methods escape the requirement of genotyping all the individuals of the mapping population and generation of high-density linkage maps for mapping of the gene for the trait of interest. This article reviews various Next Generation Sequencing-based gene mapping technologies with more emphasis on MutMap and its modifications, and discusses their advantages and proven applications for gene mapping for subsequent crop improvement.