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Journal of Integrative Agriculture
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Genetic analysis of maize crude fat content by multi-locus genome-wide association study

Dan Lü1, Jianxin Li2, Xuehai Zhang2, Ran Zheng1, Aoni Zhang1, Jingyun Luo3, Bo Tong1, Hongbing Luo1, Jianbing Yan3, Min Deng1#

1 College of Agronomy, Hunan Agricultural University/Maize Engineering Technology Research Center of Hunan Province, Changsha 410128, China

2 National Key Laboratory of Wheat and Maize Crop Science/College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China

3 National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China

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摘要  

粗脂肪是玉米籽粒的重要营养成分。然而,目前玉米籽粒粗脂肪含量的遗传机制仍然不清晰前人研究使用单一模型进行玉米籽粒粗脂肪含量的全基因组关联分析GWAS),且群体数量有限,可能导致假阳性位点,阻碍功能基因的鉴定。因此,本研究利用495玉米自交系,结合125万个单核苷酸多态性标记SNP),利用6个模型进行GWAS分析,鉴定控制粗脂肪含量的数量性状核苷酸位点QTNs并挖掘关键基因。结果表明,粗脂肪含量变异范围较广0.62%~16.03%,且广义遗传力较高96.23%)。通过GWAS分析在6个模型中共检测到744个显著的QTNs,其中147QTNs定位在不同模型、环境和方法中。基于147个共定位的QTNs,在每个QTN的上下50 kb区间内搜索候选基因。最终筛选到8个与粗脂肪含量相关的候选基因(GRMZM2G169089GRMZM2G117935GRMZM2G002075GRMZM2G368838GRMZM2G058496GRMZM2G090669GRMZM2G001241GRMZM2G333454),这些基因在玉米自交系B73的籽粒发育过程中高表达。值得注意的是,GRMZM2G169089GRMZM2G117935GRMZM2G002075GRMZM2G368838参与了玉米籽粒亚油酸代谢途径、油脂代谢和籽粒生长发育等途径。此外,共表达网络分析显示,8个候选基因与30个已知基因具有很强的相关性。同时,候选基因编码的蛋白质与其他多种蛋白质相互作用,在玉米籽粒含油量和油酸代谢中起重要作用。候选基因的最佳单倍型可能在不降低玉米产量的情况下提高玉米籽粒的粗脂肪含量。这些结果拓宽了我们对玉米粗脂肪含量遗传机制的认识,并为高粗脂肪含量玉米育种标记辅助选择提供了便利。



Abstract  

Crude fat is an important nutritional component of maize kernels.  However, the genetic mechanisms underlying crude fat content in maize kernels remain elusive.  Previous studies used single-model genome-wide association studies (GWAS) with limited population sizes, which can result in false positives of loci and hinder the identification of functional genes.  Therefore, this study used a population consisting of 495 maize inbred lines, combined with 1.25 million single nucleotide polymorphisms (SNPs), and implemented GWAS using six models to identify quantitative trait nucleotides (QTNs) controlling crude fat content and to mine key genes.  The results revealed a wide variation in crude fat content (0.62–16.03%) and broad-sense heritability (96.23%).  In total, 744 significant QTNs were detected, with 147 co-located across different models, environments, and methods.  Based on the 147 co-located QTNs, candidate genes were searched at 50 kb up- and downstream intervals of each QTN.  We finally screened eight candidate genes (GRMZM2G169089, GRMZM2G117935, GRMZM2G002075, GRMZM2G368838, GRMZM2G058496, GRMZM2G090669, GRMZM2G001241, and GRMZM2G333454) related to crude fat content that exhibited high expression levels during kernel development in maize inbred line B73.  Notably, GRMZM2G169089, GRMZM2G117935, GRMZM2G002075, and GRMZM2G368838 are involved in the linoleic acid metabolic pathway, oil metabolism, kernel growth, and development in maize.  Furthermore, co-expression network analysis revealed that the eight candidate genes exhibited strong correlations with 30 known genes.  Proteins encoded by candidate genes interact with various other proteins and play an important role in oil content and oleic acid metabolism in maize kernels.  The best haplotypes of candidate genes might increase crude fat content without decreasing maize yield.  These results broaden the understanding of the genetic mechanism of crude fat content and facilitate marker-assisted selection for high-crude fat breeding programs for maize.

Keywords:  maize       crude fat content              GWAS              model              candidate gene  
Online: 12 November 2024  
Fund: 

This work was supported by the National Natural Science Foundation of China (32101700), the China Postdoctoral Science Foundation (2022M7111220, the Science and Technology Innovation Program of Hunan Province, China (2021RC2082), and the Postgraduate Scientific Research Innovation Project of Hunan Province, China (CX20230697).

Cite this article: 

Dan Lü, Jianxin Li, Xuehai Zhang, Ran Zheng, Aoni Zhang, Jingyun Luo, Bo Tong, Hongbing Luo, Jianbing Yan, Min Deng. 2024. Genetic analysis of maize crude fat content by multi-locus genome-wide association study. Journal of Integrative Agriculture, Doi:10.1016/j.jia.2024.11.014

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