Identification of stable quantitative trait loci (QTLs) for fiber quality traits across multiple environments in Gossypium hirsutum recombinant inbred line population. (December 2016) - Jamshed, Muhammad; Jia, Fei; Gong, Juwu; Palanga, Koffi; Shi, Yuzhen; Li, Junwen; Shang, Haihong; Liu, Aiying; Chen, Tingting; Zhang, Zhen; Cai, Juan; Ge, Qun; et al.
Abstract Background The identification of quantitative trait loci (QTLs) that are stable and consistent across multiple environments and populations plays an essential role in marker-assisted selection (MAS). In the present study, we used 28, 861 simple sequence repeat (SSR) markers, which included 12, 560Gossypium raimondii (D genome) sequence-based SSR markers to identify polymorphism between two upland cotton strains 0–153 and sGK9708. A total of 851 polymorphic primers were finally selected and used to genotype 196 recombinant inbred lines (RIL) derived from a cross between 0 and 153 and sGK9708 and used to construct a linkage map. The RIL population was evaluated for fiber quality traits in six locations in China for five years. Stable QTLs identified in this intraspecific cross could be used in future cotton breeding program and with fewer obstacles. Results The map covered a distance of 4, 110 cM, which represents about 93.2 % of the upland cotton genome, and with an average distance of 5.2 cM between adjacent markers. We identified 165 QTLs for fiber quality traits, of which 47 QTLs were determined to be stable across multiple environments. Most of these QTLs aggregated into clusters with two or more traits. A total of 30 QTL clusters were identified which consisted of 103 QTLs. Sixteen clusters in the At sub-genome comprised 44 QTLs, whereas 14 clusters in the Dt sub-genome that included 59 QTLs for fiber quality were identified. Four chromosomes, including chromosome 4 (c4), c7, c14, and c25 were rich in clusters harboring 5, 4, 5, and 6 clusters respectively. A meta-analysis was performed using Biomercator V4.2 to integrate QTLs from 11 environmental datasets on the RIL populations of the above mentioned parents and previous QTL reports. Among the 165 identified QTLs, 90 were identified as common QTLs, whereas the remaining 75 QTLs were determined to be novel QTLs. The broad sense heritability estimates of fiber quality traits were high for fiber length (0.93), fiber strength (0.92), fiber micronaire (0.85), and fiber uniformity (0.80), but low for fiber elongation (0.27). Meta-clusters on c4, c7, c14 and c25 were identified as stable QTL clusters and were considered more valuable in MAS for the improvement of fiber quality of upland cotton. Conclusion Multiple environmental evaluations of an intraspecific RIL population were conducted to identify stable QTLs. Meta-QTL analyses identified a common chromosomal region that plays an important role in fiber development. Therefore, QTLs identified in the present study are an ideal candidate for MAS in cotton breeding programs to improve fiber quality.