Association Mapping for Improving Fiber Quality in Upland Cottons

Abstract

Improved fiber yield is considered a constant goal of upland cotton (Gossypium hirsutum) breeding worldwide, but the understanding of the genetic basis controlling yield-related traits remains limited. 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. Nowadays, the availability of genomic tools and resources is leading to a new revolution of plant breeding, as they facilitate the study of the genotype and its relationship with the phenotype, in particular for complex traits. Next Generation Sequencing (NGS) technologies are allowing the mass sequencing of genomes and transcriptomes, which is producing a vast array of genomic information with the development of high-throughput genotyping, phenotyping will be a major challenge for genetic mapping studies. We believe that high-quality phenotyping and appropriate experimental design coupled with new statistical models will accelerate progress in dissecting the genetic architecture of complex traits.