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A genome-wide association study uncovers novel genomic regions and candidate genes of yield-related traits in upland cotton

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A total of 62 SNPs associated with yield-related traits were identified by a GWAS. Based on significant SNPs, two candidate genes pleiotropically increase lint yield.

Abstract

Improved fibre yield is considered a constant goal of upland cotton (Gossypium hirsutum) breeding worldwide, but the understanding of the genetic basis controlling yield-related traits remains limited. To better decipher the molecular mechanism underlying these traits, we conducted a genome-wide association study to determine candidate loci associated with six yield-related traits in a population of 719 upland cotton germplasm accessions; to accomplish this, we used 10,511 single-nucleotide polymorphisms (SNPs) genotyped by an Illumina CottonSNP63K array. Six traits, including the boll number, boll weight, lint percentage, fruit branch number, seed index and lint index, were assessed in multiple environments; large variation in all phenotypes was detected across accessions. We identified 62 SNP loci that were significantly associated with different traits on chromosomes A07, D03, D05, D09, D10 and D12. A total of 689 candidate genes were screened, and 27 of them contained at least one significant SNP. Furthermore, two genes (Gh_D03G1064 and Gh_D12G2354) that pleiotropically increase lint yield were identified. These identified SNPs and candidate genes provide important insights into the genetic control underlying high yields in G. hirsutum, ultimately facilitating breeding programmes of high-yielding cotton.

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Acknowledgements

This work was supported by the National Key Research and Development Program (2016YFD0101405), the China Agriculture Research System (CARS-18-08), the Science and Technology Support Program of Hebei Province (16226307D) and the Top Talent Fund of Hebei Province.

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  1. Zhengwen Sun and Xingfen Wang contributed equally to this work.

Authors and Affiliations

  1. North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Key Laboratory for Crop Germplasm Resources of Hebei Province, Hebei Agricultural University, Baoding, 071001, China

    Zhengwen Sun, Xingfen Wang, Zhengwen Liu, Qishen Gu, Yan Zhang, Zhikun Li, Huifeng Ke, Jun Yang, Jinhua Wu, Liqiang Wu, Guiyin Zhang, Caiying Zhang & Zhiying Ma

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  1. Zhengwen Sun
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  2. Xingfen Wang
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  3. Zhengwen Liu
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  4. Qishen Gu
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  5. Yan Zhang
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  13. Zhiying Ma
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Correspondence to Caiying Zhang or Zhiying Ma.

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The experiments were performed in compliance with the current laws of China.

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Communicated by Brent Hulke.

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122_2018_3162_MOESM1_ESM.docx

Figure S1. Manhattan plots showing the GWAS results for BN per plant in different environments. Figure S2. Manhattan plots showing the GWAS results for BW in different environments. Figure S3. Manhattan plots showing the GWAS results for LP in different environments. Figure S4. Manhattan plots showing the GWAS results for FBN per plant in different environments. Figure S5. Manhattan plots showing the GWAS results for the SI in different environments. Figure S6. Manhattan plots showing the GWAS results for the LI in different environments. (DOCX 3772 kb)

122_2018_3162_MOESM2_ESM.xlsx

Table S1. Phenotypic variation for six yield-related traits in the association population. Table S2. ANOVA results for and H2 of six yield-related traits. Table S3. Summary of SNPs that are significantly associated with six yield-related traits. Table S4. List of all 689 candidate genes associated with yield-related traits. Table S5. KEGG pathway and GO analysis results of all candidate genes involved in yield-related traits. Table S6. List of candidate genes in the top five KEGG pathways. (XLSX 279 kb)

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Sun, Z., Wang, X., Liu, Z. et al. A genome-wide association study uncovers novel genomic regions and candidate genes of yield-related traits in upland cotton. Theor Appl Genet 131, 2413–2425 (2018). https://doi.org/10.1007/s00122-018-3162-y

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