Genetic Dissection of Mature Root Characteristics by Genome-Wide Association Studies in Rapeseed ( L.).

Sani Ibrahim, Keqi Li, Nazir Ahmad, Lieqiong Kuang, Salisu Bello Sadau, Ze Tian, Lintao Huang, Xinfa Wang, Xiaoling Dun, Hanzhong Wang
Author Information
  1. Sani Ibrahim: Key Laboratory of Biology and Genetic Improvement of Oil Crops, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Wuhan 430062, China.
  2. Keqi Li: Key Laboratory of Biology and Genetic Improvement of Oil Crops, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Wuhan 430062, China.
  3. Nazir Ahmad: Key Laboratory of Biology and Genetic Improvement of Oil Crops, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Wuhan 430062, China. ORCID
  4. Lieqiong Kuang: Key Laboratory of Biology and Genetic Improvement of Oil Crops, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Wuhan 430062, China.
  5. Salisu Bello Sadau: State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China.
  6. Ze Tian: Key Laboratory of Biology and Genetic Improvement of Oil Crops, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Wuhan 430062, China.
  7. Lintao Huang: Key Laboratory of Biology and Genetic Improvement of Oil Crops, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Wuhan 430062, China.
  8. Xinfa Wang: Key Laboratory of Biology and Genetic Improvement of Oil Crops, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Wuhan 430062, China.
  9. Xiaoling Dun: Key Laboratory of Biology and Genetic Improvement of Oil Crops, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Wuhan 430062, China.
  10. Hanzhong Wang: Key Laboratory of Biology and Genetic Improvement of Oil Crops, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Wuhan 430062, China.

Abstract

Roots are complicated quantitative characteristics that play an essential role in absorbing water and nutrients. To uncover the genetic variations for root-related traits in rapeseed, twelve mature root traits of a association panel were investigated in the field within three environments. All traits showed significant phenotypic variation among genotypes, with heritabilities ranging from 55.18% to 79.68%. Genome-wide association studies (GWAS) using 20,131 SNPs discovered 172 marker-trait associations, including 103 significant SNPs (-log10 () > 4.30) that explained 5.24-20.31% of the phenotypic variance. With the linkage disequilibrium r > 0.2, these significant associations were binned into 40 quantitative trait loci (QTL) clusters. Among them, 14 important QTL clusters were discovered in two environments and/or with phenotypic contributions greater than 10%. By analyzing the genomic regions within 100 kb upstream and downstream of the peak SNPs within the 14 loci, 334 annotated genes were found. Among these, 32 genes were potentially associated with root development according to their expression analysis. Furthermore, the protein interaction network using the 334 annotated genes gave nine genes involved in a substantial number of interactions, including a key gene associated with root development, This research provides the groundwork for deciphering ' genetic variations and improving its root system architecture.

Keywords

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Grants

  1. 2020BBB061/Key Research and Development Program in Hubei Province
  2. CAAS-ZDRW202109/Agricultural Science and Technology Innovation Project
  3. 2019CFB617/Natural Foundation of Hubei Province
  4. CAAS-ASTIP-2013-OCRI/Agricultural Science and Technology Innovation Project
  5. CARS-12/China Agriculture Research System of MOF and MARA

Word Cloud

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