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Molecular Breeding

, 39:149 | Cite as

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

  • Huixian Xing
  • Yanchao Yuan
  • Haijun Zhang
  • Liyuan Wang
  • Lili Mao
  • Jincai Tao
  • Xianlin Wang
  • Wei Feng
  • Haoran Wang
  • Qingkang Wang
  • Ze Wei
  • Guihua Zhang
  • Xiangliu Liu
  • Zhongye Li
  • Xian-Liang SongEmail author
  • Xue-Zhen SunEmail author
Article
  • 54 Downloads

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.

Keywords

Genome-wide association study Single-locus and multi-locus models SNP Lint percentage Seed index Cotton 

Notes

Author 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.

Funding information

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.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

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ESM 1 (XLSX 216 kb)
11032_2019_1063_MOESM2_ESM.pdf (1.5 mb)
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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Huixian Xing
    • 1
  • Yanchao Yuan
    • 1
    • 2
  • Haijun Zhang
    • 1
  • Liyuan Wang
    • 1
  • Lili Mao
    • 1
  • Jincai Tao
    • 1
  • Xianlin Wang
    • 1
  • Wei Feng
    • 1
  • Haoran Wang
    • 1
  • Qingkang Wang
    • 1
  • Ze Wei
    • 1
  • Guihua Zhang
    • 3
  • Xiangliu Liu
    • 1
  • Zhongye Li
    • 1
  • Xian-Liang Song
    • 1
    Email author
  • Xue-Zhen Sun
    • 1
    Email author
  1. 1.State Key Laboratory of Crop Biology/Agronomy CollegeShandong Agricultural UniversityTaianChina
  2. 2.College of Life Sciences, Key Lab of Plant Biotechnology in Universities of Shandong ProvinceQingdao Agricultural UniversityQingdaoChina
  3. 3.Heze Academy of Agricultural SciencesHezeChina

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