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Analysis of the Genetic Structure and Diversity of Upland Cotton Groups in Different Planting Areas Based on SNP Markers

Jungduo Wang, Zeliang Zhang, Zhaolong Gong, Yajun Liang, Xiantao Ai, Zhiwei Sang, Jiangping Guo, Xueyuan Li, Juyun Zheng
doi: https://doi.org/10.1101/2021.06.11.448075
Jungduo Wang
1Cash Crops Research Institute of Xinjiang Academy of Agricultural Science (XAAS), Urumqi 830001, Xinjiang, P. R. China
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Zeliang Zhang
1Cash Crops Research Institute of Xinjiang Academy of Agricultural Science (XAAS), Urumqi 830001, Xinjiang, P. R. China
2Engineering Research Centre of Cotton, Ministry of Education/College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi, 830052
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Zhaolong Gong
1Cash Crops Research Institute of Xinjiang Academy of Agricultural Science (XAAS), Urumqi 830001, Xinjiang, P. R. China
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Yajun Liang
1Cash Crops Research Institute of Xinjiang Academy of Agricultural Science (XAAS), Urumqi 830001, Xinjiang, P. R. China
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Xiantao Ai
1Cash Crops Research Institute of Xinjiang Academy of Agricultural Science (XAAS), Urumqi 830001, Xinjiang, P. R. China
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Zhiwei Sang
2Engineering Research Centre of Cotton, Ministry of Education/College of Agriculture, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi, 830052
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Jiangping Guo
1Cash Crops Research Institute of Xinjiang Academy of Agricultural Science (XAAS), Urumqi 830001, Xinjiang, P. R. China
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Xueyuan Li
1Cash Crops Research Institute of Xinjiang Academy of Agricultural Science (XAAS), Urumqi 830001, Xinjiang, P. R. China
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  • For correspondence: xjmh2338@163.com zjypp8866@126.com
Juyun Zheng
1Cash Crops Research Institute of Xinjiang Academy of Agricultural Science (XAAS), Urumqi 830001, Xinjiang, P. R. China
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  • For correspondence: xjmh2338@163.com zjypp8866@126.com
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Abstract

Genetic diversity, kinship and population genetic structure analyses of Gossypium hirsutum germplasm can provide a better understanding of the origin and evolution of G. hirsutum biodiversity. In this study, 1313331 SNP molecular markers were used to construct a phylogenetic tree of each sample using MEGAX, to perform population structure analysis by ADMIXTURE software and principal component analysis (PCA) by EIGENSOFT software, and to estimate relatedness using SPAGeDi. ADMIXTURE software divided the experimental cotton population into 16 subgroups, and the Gossypium hirsutum samples could be roughly clustered according to source place, but there were some overlapping characteristics among samples. The experimental cotton population was divided into six groups according to source to calculate the genetic diversity index (H), and the obtained value (0.306) was close to that for germplasm collected by others in China. Cluster 4 had a relatively high genetic diversity level (0.390). The degrees of genetic differentiation within the experimental cotton population groups were low (the population differentiation indexes ranged from 0.02368 to 0.10664). The genetic distance among cotton accessions varied from 0.000332651 to 0.562664014, with an average of 0.25240429. The results of this study may provide a basis for mining elite alleles and using them for subsequent association analysis.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://ngdc.cncb.ac.cn/gsa

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted June 12, 2021.
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Analysis of the Genetic Structure and Diversity of Upland Cotton Groups in Different Planting Areas Based on SNP Markers
Jungduo Wang, Zeliang Zhang, Zhaolong Gong, Yajun Liang, Xiantao Ai, Zhiwei Sang, Jiangping Guo, Xueyuan Li, Juyun Zheng
bioRxiv 2021.06.11.448075; doi: https://doi.org/10.1101/2021.06.11.448075
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Analysis of the Genetic Structure and Diversity of Upland Cotton Groups in Different Planting Areas Based on SNP Markers
Jungduo Wang, Zeliang Zhang, Zhaolong Gong, Yajun Liang, Xiantao Ai, Zhiwei Sang, Jiangping Guo, Xueyuan Li, Juyun Zheng
bioRxiv 2021.06.11.448075; doi: https://doi.org/10.1101/2021.06.11.448075

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