Genetic diversity and structure of elite cotton germplasm (Gossypium hirsutum L.) using genome-wide SNP data
Cotton ( Gossypium spp.) is the most important natural textile fiber crop, and Gossypium hirsutum L. is responsible for 90% of the annual cotton crop in the world. Information on cotton genetic diversity and population structure is essential for new breeding lines. In this study, we analyzed populat...
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Published in: | Genetica Vol. 145; no. 4-5; pp. 409 - 416 |
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Main Authors: | , , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Cham
Springer International Publishing
01-10-2017
Springer Nature B.V |
Subjects: | |
Online Access: | Get full text |
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Summary: | Cotton (
Gossypium
spp.) is the most important natural textile fiber crop, and
Gossypium hirsutum
L. is responsible for 90% of the annual cotton crop in the world. Information on cotton genetic diversity and population structure is essential for new breeding lines. In this study, we analyzed population structure and genetic diversity of 288 elite
Gossypium hirsutum
cultivar accessions collected from around the world, and especially from China, using genome-wide single nucleotide polymorphisms (SNP) markers. The average polymorphsim information content (PIC) was 0.25, indicating a relatively low degree of genetic diversity. Population structure analysis revealed extensive admixture and identified three subgroups. Phylogenetic analysis supported the subgroups identified by STRUCTURE. The results from both population structure and phylogenetic analysis were, for the most part, in agreement with pedigree information. Analysis of molecular variance revealed a larger amount of variation was due to diversity within the groups. Establishment of genetic diversity and population structure from this study could be useful for genetic and genomic analysis and systematic utilization of the standing genetic variation in upland cotton. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0016-6707 1573-6857 |
DOI: | 10.1007/s10709-017-9976-8 |