Literature DB >> 34718944

Genetic diversity and population structure analysis for morphological traits in upland cotton (Gossypium hirsutum L.).

Pawan Kumar1, Somveer Nimbal2, Neeraj Budhlakoti3, Varsha Singh4, Rajvir Singh Sangwan1.   

Abstract

A total of 96 different genotypes of upland cotton (Gossypium hirsutum) were selected from the breeding material and germplasm available at CCS HAU, India, to find the novel marker-trait associations for morphological traits used for registration of variety in upland cotton. Twenty-three morphological traits of the selected genotypes were recorded in field trials conducted in two replication of randomized block design during Kharif 2018 and 2019. A total of 11 traits showed sufficient variations in the screened germplasm and the same were further used for association mapping. A total of 168 SSRs were used for genotyping, of which 97 SSRs showed polymorphism amplifying 293 different alleles with an average of 3.02 alleles per SSR. Clustering, principal component analysis, and population structure analysis advocated that the current germplasm panel has enough diversity to be considered for association mapping. A total of 20 significant marker-trait associations were identified by the mixed linear model (MLM) and compressed mixed linear model (CMLM), of which 15 were common to both models, hence considered as promising associations. To the best of our knowledge, it is a first attempt to identify the linked markers in relation to morphological traits for the cotton crop. Results of the present study will be highly useful in speeding up variety registration programmes of upland cotton complementing to Distinctiveness, Uniformity, and Stability (DUS) testing.
© 2021. The Author(s), under exclusive licence to Institute of Plant Genetics Polish Academy of Sciences.

Entities:  

Keywords:  CMLM; Cluster analysis; G. hirsutum; MLM; Morphological traits; PCA; Population structure

Mesh:

Year:  2021        PMID: 34718944     DOI: 10.1007/s13353-021-00667-8

Source DB:  PubMed          Journal:  J Appl Genet        ISSN: 1234-1983            Impact factor:   3.240


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