Genetic analysis of yield and fiber quality traits in upland cotton (Gossypium hirsutum L.) cultivated in different ecological regions of China

Journal of Cotton Research

[Background] Cotton is an important fiber crop worldwide. The yield potential of current genotypes of cotton can be exploited through hybridization. However, to develop superior hybrids with high yield and fiber quality traits, information of genetic control of traits is prerequisite. Therefore, genetic analysis plays pivotal role in plant breeding.

[Results] In present study, North Carolina II mating design was used to cross 5 female parents with 6 male parents to produce 30 intraspecific F1 cotton hybrids. All plant materials were tested in three different ecological regions of China during the year of 2016–2017. Additive-dominance-environment (ADE) genetic model was used to estimate the genetic effects and genotypic and phenotypic correlation of yield and fiber quality traits. Results showed that yield traits except lint percentage were mainly controlled by genetic and environment interaction effects, whereas lint percentage and fiber quality traits were determined by main genetic effects. Moreover, dominant and additive-environment interaction effects had more influence on yield traits, whereas additive and dominance-environment interaction effects were found to be predominant for fiber traits. Broad-sense and its interaction heritability were significant for all yield and most of fiber quality traits. Narrow-sense and its interaction heritability were non-significant for boll number and seed cotton yield. Correlation analysis indicated that seed cotton yield had significant positive correlation with other yield attributes and non-significant with fiber quality traits. All fiber quality traits had significant positive correlation with each other except micronaire.

[Conclusions] Results of current study provide important information about genetic control of yield and fiber quality traits. Further, this study identified that parental lines, e.g., SJ48–1, ZB-1, 851–2, and DT-8 can be utilized to improve yield and fiber quality traits in cotton.

[Title] Genetic analysis of yield and fiber quality traits in upland cotton (Gossypium hirsutum L.) cultivated in different ecological regions of China

[Authors] SHAHZAD Kashif+, LI Xue+, QI Tingxiang, GUO Liping, TANG Huini, ZHANG Xuexian, WANG Hailin, ZHANG Meng, ZHANG Bingbing, QIAO Xiuqin, XING Chaozhu* & WU Jianyong*

Journal of Cotton Research. 2019, 2: 14

https://doi.org/10.1186/s42397-019-0031-4

https://jcottonres.biomedcentral.com/articles/10.1186/s42397-019-0031-4

JCR-QTL mapping for fiber quality and yield-related traits across multiple generations in segregating population of CCRI 70

Journal of Cotton Reseach

[Background] Cotton is a significant economic crop that plays an indispensable role in many domains. Gossypium hirsutum L. is the most important fiber crop worldwide and contributes to more than 95% of global cotton production. Identifying stable quantitative trait locus (QTLs) controlling fiber quality and yield related traits are necessary prerequisites for marker-assisted selection (MAS).

[Results] A genetic linkage map was constructed with 312 simple sequence repeat (SSR) loci and 35 linkage groups using JoinMap 4.0; the map spanned 1 929.9 cM, with an average interval between two markers of 6.19 cM, and covered approximately 43.37% of the cotton genome. A total of 74 QTLs controlling fiber quality and 41 QTLs controlling yield-related traits were identified in 4 segregating generations. These QTLs were distributed across 20 chromosomes and collectively explained 1.01%~27.80% of the observed phenotypic variations. In particular, 35 stable QTLs could be identified in multiple generations, 25 common QTLs were consistent with those in previous studies, and 15 QTL clusters were found in 11 chromosome segments.

[Conclusion] These studies provide a theoretical basis for improving cotton yield and fiber quality for molecular marker-assisted selection.

[Title] QTL mapping for fiber quality and yield-related traits across multiple generations in segregating population of CCRI 70

[Authors] DENG Xiaoying, GONG Juwu, LIU Aiying, SHI Yuzhen, GONG Wankui, GE Qun, LI Junwen, SHANG Haihong, WU Yuxiang & YUAN Youlu

Journal of Cotton Research. 2019, 2:13

https://doi.org/10.1186/s42397-019-0029-y

https://jcottonres.biomedcentral.com/articles/10.1186/s42397-019-0029-y