Yuzhen Shi, Aiying Liu, Junwen Li, Jinfa Zhang, Shaoqi Li, Jinfeng Zhang, Liujun Ma, Rui He, Weiwu Song, Lixue Guo, Quanwei Lu, Xianghui Xiang, Wankui Gong, Juwu Gong, Qun Ge, Haihong Shang, Xiaoying Deng, Jingtao Pan & Youlu Yuan

Theoretical and Applied Genetics - July 2020; vol. 133:2075–2093

Abstract

Key message

Background-independent (BI) and stably expressed (SE) quantitative trait loci (QTLs) were identified using two sets of introgression lines across multiple environments. Genetic background more greatly affected fiber quality traits than environmental factors. Sixty-one SE-QTLs, including two BI-QTLs, were novel and 48 SE-QTLs, including seven BI-QTLs, were previously reported.

Abstract

Cotton fiber quality traits are controlled by QTLs and are susceptible to environmental influence. Fiber quality improvement is an essential goal in cotton breeding but is hindered by limited knowledge of the genetic basis of fiber quality traits. In this study, two sets of introgression lines of Gossypium hirsutum × G. barbadense were used to dissect the QTL stability of three fiber quality traits (fiber length, strength and micronaire) across environments using 551 simple sequence repeat markers selected from our high-density genetic map. A total of 76 and 120 QTLs were detected in the CCRI36 and CCRI45 backgrounds, respectively. Nine BI-QTLs were found, and 78 (41.71%) of the detected QTLs were reported previously. Thirty-nine and 79 QTLs were SE-QTLs in at least two environments in the CCRI36 and CCRI45 backgrounds, respectively. Forty-eight SE-QTLs, including seven BI-QTLs, were confirmed in previous reports, and 61 SE-QTLs, including two BI-QTLs, were considered novel. These results indicate that genetic background more strongly impacts on fiber quality traits than environmental factors. Twenty-three clusters with BI- and/or SE-QTLs were identified, 19 of which harbored favorable alleles from G. barbadense for two or three fiber quality traits. This study is the first report using two sets of introgression lines to identify fiber quality QTLs across environments in cotton, providing insights into the effect of genetic backgrounds and environments on the QTL expression of fiber quality and important information for the genetic basis underlying fiber quality traits toward QTL cloning and molecular breeding.

See https://link.springer.com/article/10.1007/s00122-020-03578-0

Figure 2: a–e Chromosomal locations of QTLs for three traits of fiber quality in the CSSLs populations. E, environment; numbers preceding E: the number of environments in which the QTL was detected. Red QTLs, CCRI36-background QTLs; blue QTLs, CCRI45-background QTLs (color figure online)