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一项关于水稻代谢、生长和随机变异的综合遗传研究揭示了潜在的碳/氮分配位点。

An Integrative Genetic Study of Rice Metabolism, Growth and Stochastic Variation Reveals Potential C/N Partitioning Loci.

作者信息

Li Baohua, Zhang Yuanyuan, Mohammadi Seyed Abolghasem, Huai Dongxin, Zhou Yongming, Kliebenstein Daniel J

机构信息

Department of Plant Sciences, University of California, Davis, One Shield Avenue CA 95616, USA.

Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China.

出版信息

Sci Rep. 2016 Jul 21;6:30143. doi: 10.1038/srep30143.

DOI:10.1038/srep30143
PMID:27440503
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4954952/
Abstract

Studying the genetic basis of variation in plant metabolism has been greatly facilitated by genomic and metabolic profiling advances. In this study, we use metabolomics and growth measurements to map QTL in rice, a major staple crop. Previous rice metabolism studies have largely focused on identifying genes controlling major effect loci. To complement these studies, we conducted a replicated metabolomics analysis on a japonica (Lemont) by indica (Teqing) rice recombinant inbred line population and focused on the genetic variation for primary metabolism. Using independent replicated studies, we show that in contrast to other rice studies, the heritability of primary metabolism is similar to Arabidopsis. The vast majority of metabolic QTLs had small to moderate effects with significant polygenic epistasis. Two metabolomics QTL hotspots had opposing effects on carbon and nitrogen rich metabolites suggesting that they may influence carbon and nitrogen partitioning, with one locus co-localizing with SUSIBA2 (WRKY78). Comparing QTLs for metabolomic and a variety of growth related traits identified few overlaps. Interestingly, the rice population displayed fewer loci controlling stochastic variation for metabolism than was found in Arabidopsis. Thus, it is possible that domestication has differentially impacted stochastic metabolite variation more than average metabolite variation.

摘要

基因组学和代谢组学分析技术的进步极大地推动了植物代谢变异遗传基础的研究。在本研究中,我们利用代谢组学和生长测量方法对主要粮食作物水稻进行数量性状基因座(QTL)定位。以往的水稻代谢研究主要集中在鉴定控制主效基因座的基因。为补充这些研究,我们对粳稻(Lemont)与籼稻(特青)的重组自交系群体进行了重复的代谢组学分析,并聚焦于初生代谢的遗传变异。通过独立的重复研究,我们发现与其他水稻研究不同,初生代谢的遗传力与拟南芥相似。绝大多数代谢QTL具有小到中等的效应,并伴有显著的多基因上位性。两个代谢组学QTL热点对富含碳和氮的代谢物具有相反的影响,表明它们可能影响碳和氮的分配,其中一个位点与SUSIBA2(WRKY78)共定位。比较代谢组学QTL和各种生长相关性状的QTL,发现重叠较少。有趣的是,水稻群体中控制代谢随机变异的位点比拟南芥中的少。因此,驯化可能对随机代谢物变异的影响比对平均代谢物变异的影响更大。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a45f/4954952/a16c23199533/srep30143-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a45f/4954952/40e56339ae7b/srep30143-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a45f/4954952/7694e6344e1a/srep30143-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a45f/4954952/a16c23199533/srep30143-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a45f/4954952/40e56339ae7b/srep30143-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a45f/4954952/7694e6344e1a/srep30143-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a45f/4954952/a16c23199533/srep30143-f4.jpg

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