Author:
Xiong Xuehang,Li Jianxin,Su Pingping,Duan Haiyang,Sun Li,Xu Shuhao,Sun Yan,Zhao Haidong,Chen Xiaoyang,Ding Dong,Zhang Xuehai,Tang Jihua
Abstract
AbstractBackgroundThe chlorophyll content (CC) is a key factor affecting maize photosynthetic efficiency and the final yield. However, its genetic basis remains unclear. The development of statistical methods has enabled researchers to design and apply various GWAS models, including MLM, MLMM, SUPER, FarmCPU, BLINK and 3VmrMLM. Comparative analysis of their results can lead to more effective mining of key genes.ResultsThe heritability of CC was 0.86. Six statistical models (MLM, BLINK, MLMM, FarmCPU, SUPER, and 3VmrMLM) and 1.25 million SNPs were used for the GWAS. A total of 140 quantitative trait nucleotides (QTNs) were detected, with 3VmrMLM and MLM detecting the most (118) and fewest (3) QTNs, respectively. The QTNs were associated with 481 genes and explained 0.29-10.28% of the phenotypic variation. Additionally, 10 co-located QTNs were detected by at least two different models or methods, three co-located QTNs were identified in at least two different environments, and six co-located QTNs were detected by different models or methods in different environments. Moreover, 69 candidate genes within or near these stable QTNs were screened based on the B73 (RefGen_v2) genome.GRMZM2G110408(ZmCCS3) was identified by multiple models and in multiple environments. The functional characterization of this gene indicated the encoded protein likely contributes to chlorophyll biosynthesis. In addition, the CC differed significantly between the haplotypes of the significant QTN in this gene, and CC was higher for haplotype 1.ConclusionThis study’s results broaden our understanding of the genetic basis of CC, mining key genes related to CC and may be relevant for the ideotype-based breeding of new maize varieties with high photosynthetic efficiency.
Funder
National Natural Science Foundation of China
Henan Province Science and Technology Attack Project
China Postdoctoral Science Foundation
First-class Postdoctoral Research Grant in Henan Province
Research Start-up Fund for Youth Talents of Henan Agricultural University
Open Project Funding of the State Key Laboratory of Crop Stress Adaptation and Improvement
Publisher
Springer Science and Business Media LLC
Cited by
2 articles.
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