Detection of favorable alleles for yield and yield components by association mapping in upland cotton
- 13 Downloads
Association mapping based on linkage disequilibrium provides a promising tool for dissecting the genetic basis underlying complex traits. To reveal the genetic variations of yield and yield components traits in upland cotton, 403 upland cotton accessions were collected and analyzed by 560 genome-wide simple sequence repeats (SSRs). A diverse panel consisting of 403 upland cotton accessions was grown in six different environments, and the yield and yield component traits were measured, and 560 SSR markers covering the whole genome were mapped. Association studies were performed to uncover the genotypic and phenotypic variations using a mixed linear model. Favorable alleles and typical accessions for yield traits were identified. A total of 201 markers were polymorphic, revealing 394 alleles. The average gene diversity and polymorphism information content were 0.556 and 0.483, respectively. Based on a population structure analysis, 403 accessions were divided into two subgroups. A mixed linear model analysis of the association mapping detected 43 marker loci according to the best linear unbiased prediction and in at least three of the six environments(− lgP > 1.30, P < 0.05). Among the 43 associated markers, five were associated with more than two traits simultaneously and nine were coincident with those identified previously. Based on phenotypic effects, favorable alleles and typical accessions that contained the elite allele loci related to yield traits were identified and are widely used in practical breeding. This study detected favorable quantitative trait loci’s alleles and typical accessions for yield traits, these are excellent genetic resources for future high-yield breeding by marker-assisted selection in upland cotton in China.
KeywordsAssociation analysis Molecular marker Upland cotton Yield traits
This program was financially supported by National Natural Science Foundation of China (31260340; 31560410) and National Key R&D Program of China (2017YFD0101600). We thank Nie Xinhui from Shihezi University for help with the analysis.
Compliance with ethical standards
Conflict of interest
All authors declare that they have no conflict of interest. Chengguang Dong declares that he does not have conflict of interest. Juan Wang declares that he does not have conflict of interest. Quanjia Chen declares that she does not have conflict of interest. Yu Yu declares that he does not have conflict of interest. Baocheng Li declares that he does not have conflict of interest.
Research involving human and animal participants
This article does not contain any studies with human participants or animals performed by any of the authors.
- Ai XT, Li XY, Qin WB, Sun GQ, Tuer XJ, Mo M (2005) The extend study on genetic composition of upland cotton breeding in Xinjiang. Mol Plant Breed 3:575–578Google Scholar
- Huang ZK (2007) The cultivars and their pedigree of cotton in China. China Agriculture Press, BeijingGoogle Scholar
- Lacape JM, Gawrysiak G, Cao TV, Viot C, Llewellyn D, Liu SM, Jacobs J, Becker D, Vianna Barroso PA, Assunçãog JH et al (2013) Mapping QTLs for traits related to phenology, morphology and yield components in an inter-specific Gossypium hirsutum × G. barbadense cotton RIL population. Field Crop Res 144:256–267CrossRefGoogle Scholar
- Li XS, Chen ZZ (2010) Correctly using SPSS software for principal components analysis. Stat Res 27:105–108Google Scholar
- Ulloa M, Meredith WR (2000) Genetic linkage map and QTL analysis of agronomic and fiber quality traits in an intraspecific population. J Cotton Sci 4:161–170Google Scholar
- Wang BH, Guo WZ, Zhu XF, Wu YT, Huang NT, Zhang TZ (2007) QTL mapping of yield and yield components for elite hybrid derived-RILs in upland cotton. Acta Genet Sin 34:35–45Google Scholar
- Yin JM, Wu YT, Zhang J, Zhang TZ, Guo WZ, Zhu XF (2002) Tagging and mapping of QTLs controlling lint yield and yield components in upland cotton (Gossypium hirsutum L.) using SSR and RAPD markers. Chin J Biotechnol 18:162–166Google Scholar