Literature DB >> 29321342

Association between SSR markers and fibre traits in sea island cotton (Gossypium barbadense) germplasm resources.

Qi Ma1, Jing Zhao, Hai Lin, Xinzhu Ning, Ping Liu, Fujun Deng, Aijun Si, Jilian Li.   

Abstract

Identification of molecular markers associated with fibre traits can accelerate cotton marker-assisted selection (MAS) programmes. In this study, Gossypium barbadense germplasm accessions with diverse origins (n = 123) were used to perform association analysis of fibre traits with 120 polymorphic simple sequence repeat (SSR) markers. In total, 120 polymorphic primer pairs amplified 258 loci with a mean of 2.15 loci per primer. Population structure analysis identified three main clusters for the accessions, which indicated agreement of genetic and predefined populations. Marker-trait associations (n = 58) were detected for 10 fibre traits with 26 SSR markers located on 15 chromosomes. The R² (phenotypic variation explained) ranged from 3.19 to 15.21%. Two markers (NAU5465 and NAU3013) were found to be stably associated with boll number per plant (BNP) and fibre uniformity (UI), respectively. Four markers (BNL252, NAU3424,NAU3324 and CGR5202) associated with fibre quality traits preferentially clustered on the D8 chromosome, which was thus identified as an important candidate region for study molecular mechanisms underlying fibre quality and for use in breeding cotton cultivars for improving fibre quality. This study generated molecular data with a potential for better understanding of the genetic basis of the fibre traits and provided new markers for MAS in G. barbadense breeding programmes.

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Year:  2017        PMID: 29321342     DOI: 10.1007/s12041-017-0849-9

Source DB:  PubMed          Journal:  J Genet        ISSN: 0022-1333            Impact factor:   1.166


  1 in total

1.  Genome-wide association analysis reveals loci and candidate genes involved in fiber quality traits in sea island cotton (Gossypium barbadense).

Authors:  Xiujuan Su; Guozhong Zhu; Xiaohui Song; Haijiang Xu; Weixi Li; Xinzhu Ning; Quanjia Chen; Wangzhen Guo
Journal:  BMC Plant Biol       Date:  2020-06-22       Impact factor: 4.215

  1 in total

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