*4.2.1 GWAS*

Over the years, GWAS has been implemented across a wide variety of crops such as soybean, maize, common bean, sorghum, and rice [55, 138–141]. GWAS identifies genetic variants across the genome and associates the variants with the target phenotype. The commonly used GWAS approach involves identifying single nucleotide polymorphism (SNPs) markers and testing each marker for evidence of an association between the marker and the trait of interest. The marker-trait association approach relies on linkage disequilibrium (LD) between markers and causal polymorphisms [142, 143]. To minimize false genotype–phenotype association that may arise from population structure, a linear mixed model analysis option is usually implemented. The application of GWAS has contributed significantly to identifying candidate genes; identified markers can be mapped to reference genomes, and thereafter candidate genes can be identified [143]. Once genomic regions of a target trait and the corresponding alleles at each locus are identified, the allele can be incorporated into another variety through crosses. The resultant progenies with the desired allele combination can be subjected to marker-assisted selection. GWAS in combination with marker-assisted breeding offers great gains for improving quantitative traits with low heritability [136].

## *4.2.2 QTL mapping*

QTLs are phenotypically defined regions on the chromosome that contribute to allelic variation for a biological trait [144]. QTL technique has become a popular approach [144, 145] used to study complex traits [146, 147]. The application of QTL analysis in crop improvement was reported by several authors [82, 148]. Regions on the chromosomes that significantly affect variations of quantitative traits are identifiable through QTL mapping. The ability to locate chromosomal region (s) is

#### *A Review on the Cooking Attributes of African Yam Bean (*Sphenostylis stenocarpa*) DOI: http://dx.doi.org/10.5772/intechopen.99674*

important in identifying target genes and in understanding the genetic mechanism of genetic variation. Majorly, QTL mapping reveals information on QTL's having a significant effect on trait variation, and also answers the question to what extent is the variation due to additive, dominant, and epistasis effects of the QTL? The mapping of QTL also shows the genetic correlation of different traits and also answers the question does the QTL interact with the environment? [149]. The ability of QTL mapping to unravel and, at the same time provide answers to genetic questions makes it a powerful technique in crop improvement.
