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Multi-environments and multi-models association mapping identified candidate genes of lint percentage and seed index in Gossypium hirsutum L.

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Abstract

Upland cotton (Gossypium hirsutum L.) accounts most of the natural fiber production worldwide. Lint percentage (LP) and seed index (SI) are important components of cotton fiber yield, which is a constant breeding goal of cotton. So, the loci underpinning LP and SI should be extensively dissected. Here, one single-locus and four multi-locus genome-wide association study (GWAS) models were employed to detect candidate loci for lint percentage and seed index under seven environments with 196 upland cotton accessions and 41,815 single nucleotide polymorphism (SNP) markers. Totally, 39 and 45 significant quantitative trait locus (QTL) were identified in at least two environments or two models, including 24 previously reported QTLs and six pleiotropic QTLs. Referred to the genome and gene expression database of TM-1, 614 candidate genes were detected for lint percentage and seed index, including 103 genes preferentially expressed in fiber or ovule. The gene Gh_A10G0378, functioned in potassium ion transport, was considered to be related to lint percentage. Collectively, the associated markers and promising genes detected herein will help to elucidate the genetic architecture of lint percentage and facilitate fiber yield improvement in cotton.

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Funding

This research was financially supported by the Natural Science Foundation of Shandong Province (ZR2017MC057), the System of Modern Agriculture Industrial Technology of Shandong Province (SDAIT-03-03/05), the Major Projects for Transgenic Breeding of China (2017ZX08005-004-006), the National Key Research and Development Program of China (2018YFD0100303), and the National Natural Science Foundation of China (31601253). We thank all the foundation of economic support.

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  1. Huixian Xing, Yanchao Yuan and Haijun Zhang contributed equally to this work.

Authors and Affiliations

  1. State Key Laboratory of Crop Biology/Agronomy College, Shandong Agricultural University, Taian, Shandong, China

    Huixian Xing, Yanchao Yuan, Haijun Zhang, Liyuan Wang, Lili Mao, Jincai Tao, Xianlin Wang, Wei Feng, Haoran Wang, Qingkang Wang, Ze Wei, Xiangliu Liu, Zhongye Li, Xian-Liang Song & Xue-Zhen Sun

  2. College of Life Sciences, Key Lab of Plant Biotechnology in Universities of Shandong Province, Qingdao Agricultural University, Changcheng Road 700, Qingdao, China

    Yanchao Yuan

  3. Heze Academy of Agricultural Sciences, Heze, China

    Guihua Zhang

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  1. Huixian Xing
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Contributions

XLS and XZS designed the experiments. HX, YY, and XLS wrote the manuscript. HX, YY, HZ, LW, LM, JT, XW, WF, HW, QW, ZW, XL, ZL, and GZ helped in collecting phenotype data. YY, HX, and HZ analyzed the results. HX, YY, and HZ performed most of the experiments and contributed equally to this work. All authors read and approved the final manuscript.

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Correspondence to Xian-Liang Song or Xue-Zhen Sun.

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Xing, H., Yuan, Y., Zhang, H. et al. Multi-environments and multi-models association mapping identified candidate genes of lint percentage and seed index in Gossypium hirsutum L.. Mol Breeding 39, 149 (2019). https://doi.org/10.1007/s11032-019-1063-7

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