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通过元QTL分析和区域关联图谱相结合揭示的玉米产量相关性状的候选基因座

Candidate Loci for Yield-Related Traits in Maize Revealed by a Combination of MetaQTL Analysis and Regional Association Mapping.

作者信息

Chen Lin, An Yixin, Li Yong-Xiang, Li Chunhui, Shi Yunsu, Song Yanchun, Zhang Dengfeng, Wang Tianyu, Li Yu

机构信息

Institute of Crop Sciences, National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, China.

出版信息

Front Plant Sci. 2017 Dec 22;8:2190. doi: 10.3389/fpls.2017.02190. eCollection 2017.

Abstract

Maize grain yield and related traits are complex and are controlled by a large number of genes of small effect or quantitative trait loci (QTL). Over the years, a large number of yield-related QTLs have been identified in maize and deposited in public databases. However, integrating and re-analyzing these data and mining candidate loci for yield-related traits has become a major issue in maize. In this study, we collected information on QTLs conferring maize yield-related traits from 33 published studies. Then, 999 of these QTLs were iteratively projected and subjected to meta-analysis to obtain metaQTLs (MQTLs). A total of 76 MQTLs were found across the maize genome. Based on a comparative genomics strategy, several maize orthologs of rice yield-related genes were identified in these MQTL regions. Furthermore, three potential candidate genes (Gene ID: GRMZM2G359974, GRMZM2G301884, and GRMZM2G083894) associated with kernel size and weight within three MQTL regions were identified using regional association mapping, based on the results of the meta-analysis. This strategy, combining MQTL analysis and regional association mapping, is helpful for functional marker development and rapid identification of candidate genes or loci.

摘要

玉米籽粒产量及相关性状复杂,受大量微效基因或数量性状位点(QTL)控制。多年来,已在玉米中鉴定出大量与产量相关的QTL,并存储于公共数据库中。然而,整合和重新分析这些数据以及挖掘产量相关性状的候选位点已成为玉米研究中的一个主要问题。在本研究中,我们从33项已发表的研究中收集了赋予玉米产量相关性状的QTL信息。然后,对其中999个QTL进行迭代投影并进行元分析以获得元QTL(MQTL)。在玉米基因组中总共发现了76个MQTL。基于比较基因组学策略,在这些MQTL区域中鉴定出了几个水稻产量相关基因的玉米直系同源基因。此外,根据元分析结果,利用区域关联作图在三个MQTL区域内鉴定出了三个与籽粒大小和重量相关的潜在候选基因(基因ID:GRMZM2G359974、GRMZM2G301884和GRMZM2G083894)。这种结合MQTL分析和区域关联作图的策略有助于功能标记开发以及快速鉴定候选基因或位点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7281/5744402/670480294ade/fpls-08-02190-g0001.jpg

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