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Resequencing a core collection of upland cotton identifies genomic variation and loci influencing fiber quality and yield

Abstract

Upland cotton is the most important natural-fiber crop. The genomic variation of diverse germplasms and alleles underpinning fiber quality and yield should be extensively explored. Here, we resequenced a core collection comprising 419 accessions with 6.55-fold coverage depth and identified approximately 3.66 million SNPs for evaluating the genomic variation. We performed phenotyping across 12 environments and conducted genome-wide association study of 13 fiber-related traits. 7,383 unique SNPs were significantly associated with these traits and were located within or near 4,820 genes; more associated loci were detected for fiber quality than fiber yield, and more fiber genes were detected in the D than the A subgenome. Several previously undescribed causal genes for days to flowering, fiber length, and fiber strength were identified. Phenotypic selection for these traits increased the frequency of elite alleles during domestication and breeding. These results provide targets for molecular selection and genetic manipulation in cotton improvement.

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Fig. 1: Phylogenetic tree, PCA, genetic structure and LD decay of the 419 accessions.
Fig. 2: Identification of the FD causal gene GhCIP1 on chromosome Dt03.
Fig. 3: Identification of the FD causal gene GhUCE on chromosome Dt03.
Fig. 4: Identification of the FL causal gene GhFL1 on chromosome At10.
Fig. 5: Identification of the FL causal gene GhFL2 on chromosome Dt11.
Fig. 6: Identification of the causal FS gene for the peak on chromosome At07.
Fig. 7

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Acknowledgements

We thank the National Mid-term Gene Bank for Cotton at the Cotton Research Institute, Chinese Academy of Agricultural Sciences, for providing the original collection seeds. We thank T. Zhang for releasing resequencing data for wild cotton accessions. This work was supported by the Fund of the China Agriculture Research System (CARS18-08) and the Science and Technology Support Program of Hebei Province (16226307D) to Z.M.; the National Major Science and Technology Program (2016ZX08005003-005) to X.W.; the National Key Research and Development Program (2016YFD0100203) to X.D., (2016YFD0101405) to Y.Z., and (2016YFD0100306) to S.H.; and the National Science and Technology Support Program (2013BAD01B03) to X.D.

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Contributions

Z.M., X.W., X.D., and S.T. designed the analyses. Z.M., X.W., X.D., S.H., Y.Z., Zhihao Liu, and R.L. performed sequencing, genomic-variant, and GWAS analyses. X.W., G.Z., L. Wu, J.P., and S.T. managed the project. J.S., L. Wu, Z. Li, G.Z., J.Y., Y.J., Q.G., Z. Pan, X.L., Z.S., P.D., Zhengwen Liu, W.G., J. Wu, M.W., H. Liu, K.F., H.K., J. Wang, H. Lan, G.W., L. Wang, B.P., and Z. Peng performed field experiments and phenotyping. X.W., G.S., Y.J., Z.S., Zhengwen Liu, and N.W. performed data integration. Y.Z., Zhengwen Liu, and Z.S. performed transcriptome analyses. J.S., L. Wang, Y.J., and H.K. prepared the population material. Y.Z., Y.Y., and X.W. conducted gene expression analysis and functional validation. X.W. and Z.M. designed the research and wrote the manuscript. S.H., Y.Z., S.T., and X.D. designed the research and revised the manuscript. Z.M. and X.D. conceived the research.

Corresponding authors

Correspondence to Zhiying Ma or Xingfen Wang or Shilin Tian or Xiongming Du.

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Supplementary Tables and Figures

Supplementary Figures 1–23 and Supplementary Tables 3, 6, 8, 9, 11–13 and 15

41588_2018_119_MOESM2_ESM.pdf

Reporting Summary

Supplementary Table 1

The list of 419 cotton accessions used in this study and their sequenced information

Supplementary Table 2

Statistics of different SNP mutation types for 419 accessions

Supplementary Table 4

Tracy-Widom statistics of eigenvalues from PCA analysis of 419 accessions

Supplementary Table 5

The ancestry proportion estimates for each accession when the ancestral population was specified as three

Supplementary Table 7

Number of SNP variation of different genes between core collection and wild races

Supplementary Table 10

List of the associated SNPs and genes for 13 traits

Supplementary Table 14

SNPs, elite alleles and their frequency of 13 traits in wild races, early- and modern-varieties

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Ma, Z., He, S., Wang, X. et al. Resequencing a core collection of upland cotton identifies genomic variation and loci influencing fiber quality and yield. Nat Genet 50, 803–813 (2018). https://doi.org/10.1038/s41588-018-0119-7

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