Dissection of complicate genetic architecture and breeding perspective of cottonseed traits by genome-wide association study
Xiongming Du,
Shouye Liu,
Junling Sun,
Gengyun Zhang,
Yinhua Jia,
Zhaoe Pan,
Haitao Xiang,
Shoupu He,
Qiuju Xia,
Songhua Xiao,
Weijun Shi,
Zhiwu Quan,
Jianguang Liu,
Jun Ma,
Baoyin Pang,
Liru Wang,
Gaofei Sun,
Wenfang Gong,
Johnie N. Jenkins,
Xiangyang Lou,
Jun Zhu,
Haiming Xu
Affiliations
Xiongming Du
Institute of Cotton Research of Chinese Academy of Agricultural Sciences (ICR, CAAS), State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture
Shouye Liu
Institute of crop science and Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University
Junling Sun
Institute of Cotton Research of Chinese Academy of Agricultural Sciences (ICR, CAAS), State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture
Gengyun Zhang
Shenzhen Huada Gene Research Institute
Yinhua Jia
Institute of Cotton Research of Chinese Academy of Agricultural Sciences (ICR, CAAS), State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture
Zhaoe Pan
Institute of Cotton Research of Chinese Academy of Agricultural Sciences (ICR, CAAS), State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture
Haitao Xiang
Shenzhen Huada Gene Research Institute
Shoupu He
Institute of Cotton Research of Chinese Academy of Agricultural Sciences (ICR, CAAS), State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture
Qiuju Xia
Shenzhen Huada Gene Research Institute
Songhua Xiao
Institute of industrial Crops, Jiangsu Academy of Agricultural Sciences
Weijun Shi
Economic Crop Research Institute, Xinjiang Academy of Agricultural Science
Zhiwu Quan
Shenzhen Huada Gene Research Institute
Jianguang Liu
Institute of industrial Crops, Jiangsu Academy of Agricultural Sciences
Jun Ma
Economic Crop Research Institute, Xinjiang Academy of Agricultural Science
Baoyin Pang
Institute of Cotton Research of Chinese Academy of Agricultural Sciences (ICR, CAAS), State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture
Liru Wang
Institute of Cotton Research of Chinese Academy of Agricultural Sciences (ICR, CAAS), State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture
Gaofei Sun
Department of Computer Science and Information Engineering, Anyang Institute of Technology
Wenfang Gong
Institute of Cotton Research of Chinese Academy of Agricultural Sciences (ICR, CAAS), State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture
Johnie N. Jenkins
USDA-ARS at Mississippi State
Xiangyang Lou
Department of Pediatrics, Biostatistics Division Arkansas Children‘s Hospital Research Institute School of Medicine, University of Arkansas for Medical Sciences
Jun Zhu
Institute of crop science and Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University
Haiming Xu
Institute of crop science and Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University
Abstract Background Cottonseed is one of the most important raw materials for plant protein, oil and alternative biofuel for diesel engines. Understanding the complex genetic basis of cottonseed traits is requisite for achieving efficient genetic improvement of the traits. However, it is not yet clear about their genetic architecture in genomic level. GWAS has been an effective way to explore genetic basis of quantitative traits in human and many crops. This study aims to dissect genetic mechanism seven cottonseed traits by a GWAS for genetic improvement. Results A genome-wide association study (GWAS) based on a full gene model with gene effects as fixed and gene-environment interaction as random, was conducted for protein, oil and 5 fatty acids using 316 accessions and ~ 390 K SNPs. Totally, 124 significant quantitative trait SNPs (QTSs), consisting of 16, 21, 87 for protein, oil and fatty acids (palmitic, linoleic, oleic, myristic, stearic), respectively, were identified and the broad-sense heritability was estimated from 71.62 to 93.43%; no QTS-environment interaction was detected for the protein, the palmitic and the oleic contents; the protein content was predominantly controlled by epistatic effects accounting for 65.18% of the total variation, but the oil content and the fatty acids except the palmitic were mainly determined by gene main effects and no epistasis was detected for the myristic and the stearic. Prediction of superior pure line and hybrid revealed the potential of the QTSs in the improvement of cottonseed traits, and the hybrid could achieve higher or lower genetic values compared with pure lines. Conclusions This study revealed complex genetic architecture of seven cottonseed traits at whole genome-wide by mixed linear model approach; the identified genetic variants and estimated genetic component effects of gene, gene-gene and gene-environment interaction provide cotton geneticist or breeders new knowledge on the genetic mechanism of the traits and the potential molecular breeding design strategy.