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Position: Home > Articles > Analysis of Meta-QTL and Candidate Genes Related to Yield Components in Maize Acta Agronomica Sinica 2013,39 (6) 969-978

玉米产量相关性状Meta-QTL及候选基因分析

作  者:
江培顺;张焕欣;吕香玲;郝转芳;李博;李明顺;王宏伟;慈晓科;张世煌
单  位:
中国农业科学院作物科学研究所/作物分子育种国家工程实验室;沈阳农业大学特种玉米研究所
关键词:
玉米;产量性状;元分析;Meta-QTL;候选基因
摘  要:
借助IBM2 2008 Neighbors高密度玉米遗传图谱整合了1994—2012年文献发表的玉米产量性状(穗行数、行粒数、粒重)584个QTL。采用元分析方法,确定了22个穗行数、7个行粒数和44个粒重Meta-QTL。根据B73基因组序列进行产量相关基因的重定位,在Meta-QTL区段内分别获得10个玉米产量基因和12个与水稻7个产量基因同源的候选基因,分别位于玉米染色体Bins1.04、1.06、1.07、2.04、2.06、3.04、4.05、4.07、4.09、5.03、5.04、5.05、7.02、8.03、9.03、10.06和10.07。玉米产量性状Meta-QTL及相关候选基因分析可以为分子标记辅助育种和基因克隆提供有用的信息。
译  名:
Analysis of Meta-QTL and Candidate Genes Related to Yield Components in Maize
作  者:
JIANG Pei-Shun , ZHANG Huan-Xin , Lü Xiang-Ling , HAO Zhuan-Fang , LI Bo , LI Ming-Shun , WANG Hong-Wei , CI Xiao-Ke , ZHANG Shi-Huang , LI Xin-Hai , SHI Zhen-Sheng , and WENG Jian-Feng Special Maize Institute, Shenyang Agricultural University, Shenyang 110161, China; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/National Engineer Laboratory of Crop Molecular Breeding, Beijing 100081, China
关键词:
Maize; Yield component; Meta-analysis; Meta-QTL; Candidate gene
摘  要:
In this study, 584 QTLs related to grain yield components (row number, kernel number per row and kernel weight) in maize were integrated from the published papers between 1994 and 2012 using the reference map of IBM2 2008 Neighbors high density maize genetic map. By Meta-analysis method, 73 Meta-QTLs for grain yield components were estimated, including 22 QTLs for row number, 7 QTLs for kernel number per row and 44 QTLs for kernel weight. With the B73 genome sequences, 10 maize genes and 12 rice homologous candidate genes related to yield components were comparatively and electronically mapped in consensus map, and these genes are located in maize chromosome Bins 1.04, 1.06, 1.07, 2.04, 2.06, 3.04, 4.05, 4.07, 4.09, 5.03, 5.04, 5.05, 7.02, 8.03, 9.03, 10.06, and 10.07. The analysis of Meta-QTL and candidate genes related to grain yield components will provide useful information for marker-assisted selection breeding and gene cloning in maize.

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