Dissecting the genetic architecture of complex traits is an ongoing challenge for geneticists. Two complementary approaches for genetic mapping, linkage mapping and association mapping have led to successful dissection of complex traits in many crop species. Both of these methods detect quantitative trait loci (QTL) by identifying marker–trait associations, and the only fundamental difference between them is that between mapping populations, which directly determine mapping resolution and power. Based on this difference, we first summarize in this review the advances and limitations of family-based mapping and natural population-based mapping instead of linkage mapping and association mapping. We then describe statistical methods used for improving detection power and computational speed and outline emerging areas such as large-scale meta-analysis for genetic mapping in crops. In the era of next-generation sequencing, there has arisen an urgent need for proper population design, advanced statistical strategies, and precision phenotyping to fully exploit high-throughput genotyping
Grain protein content (GPC) affects rice nutrition quality. Here, we identify two stable quantitative trait loci (QTLs), qGPC-1 and qGPC-10, controlling GPC in a mapping population derived from indica and japonica cultivars crossing. Map-based cloning reveals that OsGluA2, encoding a glutelin type-A2 precursor, is the candidate gene underlying qGPC-10. It functions as a positive regulator of GPC and has a pleiotropic effect on rice grain quality. One SNP located in OsGluA2 promoter region is associated with its transcript expression level and GPC diversity. Polymorphisms of this nucleotide can divide all haplotypes into low (OsGluA2LET) and high (OsGluA2HET) expression types. Population genetic and evolutionary analyses reveal that OsGluA2LET, mainly present in japonica accessions, originates from wild rice. However, OsGluA2HET, the dominant type in indica, is acquired through mutation of OsGluA2LET. Our results shed light on the understanding of natural variations of GPC between indica and japonica subspecies.