Quantitative trait locus analysis of boll-related traits in an intraspecific population of Gossypium hirsutum

Abstract

Quantitative trait locus (QTL) mapping lays the foundation for marker-assisted selection (MAS) for lint yield and fiber quality in cotton (Gossypium hirsutum). Boll-related traits affect yield and fiber quality, but few studies have focused on bollrelated traits. Here, we detected QTLs related to cotton boll, yield and fiber quality traits using intraspecific F 2 and F 2:3 populations from the cross AQ 9 08-10604. A total of 91 QTLs for 17 traits related to boll, yield and fiber quality in the F 2 and F 2:3 populations were mapped, including 37 significant QTLs. Six pairs of common QTLs were detected, including two pairs for boll coat weight (BCW) in the same or similar positions on Chr. A10 and D1, two pairs for boll length (BL) in similar positions on Chr. A10 and A13, with a higher percentage of phenotype variation and two pairs for boll diameter (BD) in similar positions on Chr. A10 and D1. These results suggest that the traits BCW, BL and BD have high levels of stability. Five QTL clusters for the same or different traits were also identified on Chr. A10 (2), A13, D1 and D5. We also detected 64 epistatic QTLs for boll-and yield-related traits that play important roles in genetic variation. Correlation analysis revealed significant positive correlations between seed yield and boll number per plant and between boll weight and BCW, BL and BD. The results of this study enhance our understanding of the genetic basis of boll-related traits and will enable further MAS of upland cotton.

QTL Mapping and Heterosis Analysis for Fiber Quality Traits Across Multiple Genetic Populations and Environments in Upland Cotton

“…Thus, constructing different segregating populations from the same parental combination, identifying QTLs, and evaluating their expression levels and genetic basis of heterosis under multiple environments will allow us to map stable QTLs and accelerate the breeding process of better fiber quality species. Recently, a few studies on QTL mapping across multiple populations have been reported (Shen et al, 2005 ; Sun et al, 2012 ; Yu et al, 2013 ; Zhang et al, 2015 ), but the study of heterosis with related segregating populations has not been reported in upland cotton.…”

Mapping of fiber quality QTLs reveals useful variation and footprints of cotton domestication using introgression lines

“…These traits are also affected by biotic stressors, including premature senescence, Verticillium wilt, insects and weeds, and by abiotic stress conditions, including flooding, extreme temperatures and drought 11 12 . Researchers have detected QTLs associated with fiber properties from both intraspecific populations of G. hirsutum and interspecific crosses between G. hirsutum and G. barbadense , as well as their later generations 13 14 15 16 17 . At the same time, the large number of differentially expressed genes highlights the complex alteration of global gene expression machinery that resulted from human selection of a longer, stronger, and finer fiber.…”

“…Numerous genetic linkage maps also have been constructed from interspecific populations ( G. barbadense × G. hirsutum ) and are used in QTL mapping 22 23 24 25 . While genetic maps of interspecific populations are already plentiful, many genetic maps used for QTL mapping have also been constructed from intraspecific Upland cotton populations 16 26 27 28 29 . A high-density genetic linkage map would be greatly beneficial to the development of chromosome segment introgression lines (ILs) via marker-assisted selection (MAS).…”

QTL Mapping for Fiber Quality and Yield Traits Based on Introgression Lines Derived from Gossypium hirsutum × G. tomentosum

“…Based on the comprehensive analysis of clusters in this study, breeding programs targeting higher yields with superior fiber quality can focus on hotspot clustering areas and select around the region. The existence of hotspots and QTL clusters has proven that genes related to certain traits were more heavily focused in certain areas of the genome than others [ 5 , 43 ].…”