Metabolome genome-wide association study provides biochemical and genetic insights into natural variation of primary metabolites in sesame

被引:2
|
作者
Song, Shengnan [1 ]
Zhang, Liangxiao [1 ]
Zhao, Yan [2 ]
Sheng, Chen [1 ]
Zhou, Wangyi [1 ]
Dossou, Senouwa Segla Koffi [1 ]
Wang, Linhai [1 ]
You, Jun [1 ]
Zhou, Rong [1 ]
Wei, Xin [3 ]
Zhang, Xiurong [1 ]
机构
[1] Chinese Acad Agr Sci, Oil Crops Res Inst, Key Lab Biol & Genet Improvement Oil Crops, Minist Agr, Wuhan 430062, Hubei, Peoples R China
[2] Chinese Acad Sci, Natl Ctr Gene Res, CAS Ctr Excellence Mol Plant Sci, Inst Plant Physiol & Ecol,State Key Lab Plant Mol, Shanghai 200233, Peoples R China
[3] Shanghai Normal Univ, Coll Life Sci, Shanghai Key Lab Plant Mol Sci, Shanghai 200234, Peoples R China
来源
PLANT JOURNAL | 2022年 / 112卷 / 04期
基金
中国国家自然科学基金;
关键词
primary metabolites; genetic variations; genome-wide association study; candidate gene; overexpression; superior allele; sesame; FATTY-ACID COMPOSITIONS; ACETYL-COA CARBOXYLASE; SERINE CARBOXYPEPTIDASES; OIL CONTENT; ARABIDOPSIS; PROTEIN; TRANSFORMATION; BIOSYNTHESIS; DETERMINANTS; EXPRESSION;
D O I
10.1111/tpj.15995
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Plants' primary metabolites are of great importance from the survival and nutritional perspectives. However, the genetic bases underlying the profiles of primary metabolites in oilseed crops remain largely unclear. As one of the main oilseed crops, sesame (Sesamum indicum L.) is a potential model plant for investigating oil metabolism in plants. Therefore, the objective of this study is to disclose the genetic variants associated with variation in the content of primary metabolites in sesame. We performed a comprehensive metabolomics analysis of primary metabolites in 412 diverse sesame accessions using gas chromatography-mass spectrometry and identified a total of 45 metabolites, including fatty acids, monoacylglycerols (MAGs), and amino acids. Genome-wide association study unveiled 433 significant single-nucleotide polymorphism loci associated with variation in primary metabolite contents in sesame. By integrating diverse genomic analyses, we identified 10 key candidate causative genes of variation in MAG, fatty acid, asparagine, and sucrose contents. Among them, SiDSEL was significantly associated with multiple traits. SiCAC3 and SiKASI were strongly associated with variation in oleic acid and linoleic acid contents. Overexpression of SiCAC3, SiKASI, SiLTPI.25, and SiLTPI.26 in transgenic Arabidopsis and Saccharomyces cerevisiae revealed that SiCAC3 is a potential target gene for improvement of unsaturated fatty acid levels in crops. Furthermore, we found that it may be possible to breed several quality traits in sesame simultaneously. Our results provide valuable genetic resources for improving sesame seed quality and our understanding of oilseed crops' primary metabolism.
引用
收藏
页码:1051 / 1069
页数:19
相关论文
共 50 条
  • [1] Metabolome-Based Genome-Wide Association Study Provides Genetic Insights Into the Natural Variation of Foxtail Millet
    Wei, Wei
    Li, Shuangdong
    Wang, Yixiang
    Wang, Bin
    Fan, Guangyu
    Zeng, Qisen
    Zhao, Fang
    Xu, Congping
    Zhang, Xiaolei
    Tang, Tang
    Feng, Xiaolei
    Shi, Jian
    Shi, Gaolei
    Zhang, Weiqin
    Song, Guoliang
    Li, Huan
    Wang, Feng
    Zhang, Yali
    Li, Xinru
    Wang, Dequan
    Zhang, Wenying
    Pei, Jingjing
    Wang, Xiaoming
    Zhao, Zhihai
    [J]. FRONTIERS IN PLANT SCIENCE, 2021, 12
  • [2] Genome-wide association study of eigenvectors provides genetic insights into selective breeding for tomato metabolites
    Yang, Junwei
    Liang, Bin
    Zhang, Yuemei
    Liu, Yun
    Wang, Shengyuan
    Yang, Qinqin
    Geng, Xiaolin
    Liu, Simiao
    Wu, Yaoyao
    Zhu, Yingfang
    Lin, Tao
    [J]. BMC BIOLOGY, 2022, 20 (01)
  • [3] Genome-wide association study of eigenvectors provides genetic insights into selective breeding for tomato metabolites
    Junwei Yang
    Bin Liang
    Yuemei Zhang
    Yun Liu
    Shengyuan Wang
    Qinqin Yang
    Xiaolin Geng
    Simiao Liu
    Yaoyao Wu
    Yingfang Zhu
    Tao Lin
    [J]. BMC Biology, 20
  • [4] Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism
    Chen, Wei
    Gao, Yanqiang
    Xie, Weibo
    Gong, Liang
    Lu, Kai
    Wang, Wensheng
    Li, Yang
    Liu, Xianqing
    Zhang, Hongyan
    Dong, Huaxia
    Zhang, Wan
    Zhang, Lejing
    Yu, Sibin
    Wang, Gongwei
    Lian, Xingming
    Luo, Jie
    [J]. NATURE GENETICS, 2014, 46 (07) : 714 - 721
  • [6] Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism
    Wei Chen
    Yanqiang Gao
    Weibo Xie
    Liang Gong
    Kai Lu
    Wensheng Wang
    Yang Li
    Xianqing Liu
    Hongyan Zhang
    Huaxia Dong
    Wan Zhang
    Lejing Zhang
    Sibin Yu
    Gongwei Wang
    Xingming Lian
    Jie Luo
    [J]. Nature Genetics, 2014, 46 : 714 - 721
  • [7] Genome-wide association study provides genetic insights into natural variation in watermelon rind thickness and single fruit weight
    Gong, Chengsheng
    Lu, Xuqiang
    Zhu, Hongju
    Anees, Muhammad
    He, Nan
    Liu, Wenge
    [J]. FRONTIERS IN PLANT SCIENCE, 2022, 13
  • [8] Metabolome-Based Genome-Wide Association Study of Duck Meat Leads to Novel Genetic and Biochemical Insights
    Liu, Dapeng
    Zhang, He
    Yang, Youyou
    Liu, Tong
    Guo, Zhanbao
    Fan, Wenlei
    Wang, Zhen
    Yang, Xinting
    Zhang, Bo
    Liu, Hongfei
    Tang, Hehe
    Yu, Daxin
    Yu, Simeng
    Gai, Kai
    Mou, Qiming
    Cao, Junting
    Hu, Jian
    Tang, Jing
    Hou, Shuisheng
    Zhou, Zhengkui
    [J]. ADVANCED SCIENCE, 2023, 10 (18)
  • [9] Genome-wide association analysis provides molecular insights into natural variation in watermelon seed size
    Gong, Chengsheng
    Zhao, Shengjie
    Yang, Dongdong
    Lu, Xuqiang
    Anees, Muhammad
    He, Nan
    Zhu, Hongju
    Zhao, Yong
    Liu, Wenge
    [J]. HORTICULTURE RESEARCH, 2022, 9
  • [10] An integrated hyperspectral imaging and genome-wide association analysis platform provides spectral and genetic insights into the natural variation in rice
    Hui Feng
    Zilong Guo
    Wanneng Yang
    Chenglong Huang
    Guoxing Chen
    Wei Fang
    Xiong Xiong
    Hongyu Zhang
    Gongwei Wang
    Lizhong Xiong
    Qian Liu
    [J]. Scientific Reports, 7