Agronomy (Jun 2023)

Population Genomics Unravels the Characteristic Relationship between Introgression and Geographical Distribution in Upland Cotton

  • Chao Shen,
  • Zheng Cao,
  • Zhiyong Xu,
  • Lejun Ouyang,
  • Xumin Zhang,
  • Zhishan Guo,
  • Jieli Yu,
  • Rong Chen,
  • Wenxi Huang

DOI
https://doi.org/10.3390/agronomy13071781
Journal volume & issue
Vol. 13, no. 7
p. 1781

Abstract

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Introgression is an important driver of new genetic variation that increases species and genetic diversity. However, the relationship between introgression and geographic distribution of upland cotton is still unclear. Herein, we explored geographically comprehensive genomic data based on 890 upland cotton accessions to decipher the degree of introgression between different geographic distributions and its effect on selection and fiber quality. We found introgression intervals to exist across different geographic distributions. Introgression is affected by the similarity of the environment in which they live, and those with similar ecological environments tend to share the same introgression area. Introgression is affected by artificial selection. A genome-wide association study (GWAS) meta-analysis was performed with 6 fiber traits and identified 261 quantitative trait loci (QTLs). We found that 67 QTLs had introgression signals, and the genome interval size was 118.81 Mb, while 123 QTLs had selection signals, and the genomic interval was 28.38 Mb. These results provide insights into the population-scaled introgression landscape, suggesting that introgression contributed to the cotton genetic improvement, which provides a useful reference for studying intraspecific introgressions from different geographical distributions in other species.

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