水稻产量相关性状QTL定位

doi:10.3969/j.issn.1001-7216.2013.04.002

中国水稻科学 ›› 2013, Vol. 27 ›› Issue (4): 344-352.DOI: 10.3969/j.issn.1001-7216.2013.04.002

水稻产量相关性状QTL定位

赵建国²,蒋开锋¹ ,杨莉¹,杨乾华¹,万先齐¹,曹应江¹ ,游书梅¹,罗婧¹ ,张涛^1,* ,郑家奎^1,*

¹四川省农业科学院水稻高粱研究所/农业部西南水稻生物学与遗传育种重点实验室/国家水稻改良中心泸州分中心, 四川泸州646100；²重庆大学生物工程学院, 重庆400044；

收稿日期:2012-10-22 修回日期:2012-12-02 出版日期:2013-07-10 发布日期:2013-07-10
通讯作者: 张涛1,* ,郑家奎1,*
基金资助:
国家863计划资助项目(2011AAl0A101)；农业部超级稻专项；四川省财政基因工程项目(JYGC20111)；四川十二五水稻育种攻关计划资助项目(YZGG20111) 。

QTL Mapping for Yield Related Components in A RIL Population of Rice

ZHAO Jianguo²， JIANG Kaifeng¹，YANG Li¹，YANG Qianhua¹，WAN Xianqi¹，CAO Yingjiang¹，YOU Shumei¹，LUO Jing¹， ZHANG Tao ^1,* ， ZHENG Jiakui ^1,*

¹ Institute of Rice and Sorghum, Sichuan Academy of Agricultural Sciences/ Key Laboratory of Southwest Rice Biology and Genetic Breeding, Ministry of Agriculture/Luzhou Branch of National Rice Improvement Center, Luzhou 646100, China;² Bioengineering College, Chongqing University, Chongqing 400044, China;

Received:2012-10-22 Revised:2012-12-02 Online:2013-07-10 Published:2013-07-10
Contact: ZHANG Tao1,*， ZHENG Jiakui1,*

摘要/Abstract

摘要： 以来自泸恢99×日本晴F8代重组自交系的188个家系及双亲为研究材料，用在亲本间有多态性的207个DNA标记对群体进行基因型分析，构建了全长为2397 cM，标记间平均距离为12.29 cM,覆盖水稻基因组12条染色体的连锁图。于2011年正季分别在德阳和泸州两地种植于四川农业科学院水稻高粱研究所实验农场，考查了单株有效穗数、每穗颖花数、每穗实粒数、结实率、千粒重、单株产量、穗长和株高7个性状。用基于混合线性模型的QTL Network 2.0软件进行QTL定位、上位性分析及其与环境的互作分析。7个性状共检测到22个加性主效应QTL，位于除第6、11、12染色体外的9条染色体上，除每穗颖花数、每穗实粒数、结实率未检测到上位性效应外，其他5个性状共检测到7对上位性互作；另外只发现两个QTL与环境发生明显互作。所有加性×加性上位性互作的效应及贡献率均较小，未发现上位性互作效应与环境的显著互作。

关键词: 遗传图谱, 水稻产量因子, 上位性效应, QTL与环境互作

Abstract: A genetic linkage map consisting 207 DNA markers, was constructed based on a recombinant inbred line(RIL) population derived from a cross between indica Luhui 99 and japonica Nipponbare. The markers in the linkage map distributed on all the 12 rice chromosomes and covered 2397 cM of the genome with the average distance between the markers being 12.29 cM. In 2011, the parents and 188 RILs were grown in the experimental field at Luzhou and Deyang experimental farm of the Institute of Rice and Sorghum, Sichuan Academy of Agricultural Sciences. The statistic software of QTL Network 2.0 was applied to detect QTL, QTL×QTL epstatic effects and QTL×environment(QE)interaction for seven traits, including number of panicles per plant, number of spikelet per panicle, number of filled grains per panicle, seed setting rate, 1000grain weight, grain yield per plant, plant height. A total of 22 QTLs with significant additive effects covering all chromosomes except chromosomes 6, 11 and 12 and two QTL with significant QE interactions were detected. Seven pairs of QTLs showing significant additive ×additive epistatic effects were detected except three traits including number of spikelet per panicle, number of filled grains per panicle, and seed setting rate. Genetic contributions were generally low for QTL showing epistatic effects. No significant interaction between epistatic QTL and environment was detected.

Key words: genetic linkage map, rice yield components, epistatic effect, QTL×environment interaction

中图分类号:

赵建国2 ,蒋开锋1 ,杨莉1 ,杨乾华1 ,万先齐1 ,曹应江1 ,游书梅1 ,罗婧1 ,张涛1,* ,郑家奎1,*. 水稻产量相关性状QTL定位[J]. 中国水稻科学, 2013, 27(4): 344-352.

ZHAO Jianguo2， JIANG Kaifeng1，YANG Li1，YANG Qianhua1 ，WAN Xianqi1，CAO Yingjiang1，YOU Shumei1，LUO Jing1， ZHANG Tao1,*， ZHENG Jiakui1,*. QTL Mapping for Yield Related Components in A RIL Population of Rice[J]. Chinese Journal of Rice Science, 2013, 27(4): 344-352.

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水稻产量相关性状QTL定位

QTL Mapping for Yield Related Components in A RIL Population of Rice

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