您好，欢迎访问四川省农业科学院 机构知识库！

Genome-wide association study of grain yield and related traits using a collection of advanced indica rice breeding lines for irrigated ecosystems

文献类型： 外文期刊

作者： Liang, Shanshan 2 ; Wu, Liwen 3 ; Ren, Guangjun 5 ; Zhao, Xiangqian 2 ; Zhou, Meixue 1 ; McNeil, David 1 ; Ye, Guoyou 2 ;

作者机构： 1.Univ Tasmania, Private Bag 98, Hobart, Tas 7001, Australia

2.IRRI, Genet & Biotechnol Div, Los Banos, Laguna, Philippines

3.China Natl Rice Res Inst, State Key Lab Rice Biol, Chinese Natl Ctr Rice Improvement, Hangzhou 310006, Zhejiang, Peoples R China

4.Chinese Acad Agr Sci, Agr Genom Inst Shenzhen, Shenzhen 518120, Peoples R China

5.Sichuan Acad Agr Sci, Inst Crop Sci, Chengdu 610066, Sichuan, Peoples R China

关键词： Rice;Yield-related traits;QTL;Genome-wide association studies (GWAS);Genotyping-by-sequencing

期刊名称：FIELD CROPS RESEARCH （ 影响因子：5.224； 五年影响因子：6.19 ）

ISSN：

年卷期：

页码：

收录情况： SCI

摘要： Genome-wide association study (GWAS) is an effective approach for the identification of marker-trait associations (MTA) using more diverse germplasm not constrained by specific crossing. This study used a collection of 327 advanced indica breeding lines and varieties genotyped using a genotyping-by-sequencing method and phenotyped in eight environments to identify MTA for grain yield (GY) and 10 related traits. The current panel of indica breeding lines were divided into two subpopulations by three analytical methods including STRUCTURE, principal component analysis (PCA) and neighbour joining (NJ) tree. STRUCTURE and PCA gave the same classification of genotypes while the NJ tree results are slight difference in assigning genotypes to subpopulation from STRCUTURE and PCA. Wide variation was observed for all the 11 traits in the whole panel and the two subpopulations inferred by STRUCTURE analysis. Linkage disequilibrium (LD) analysis showed that LD decay varied across the chromosomes and average pairwise squared correlation coefficient (r(2)) dropped to half of its maximum value (r(2)=0.25) within a physical distance of 200 kb in the whole population. A MLM model controlling both population structure and cryptic relatedness was chosen to identify MTA for all the 11 tested traits. A total of 452 MTA that were delineated into 43 QTL were identified for all traits but PB, SB, and SR with 39 QTL being not reported before. Three QTL on chromosome 6, 9 and 12 were identified for GY but only in DS2. The numbers of QTL identified for the remaining traits varied from two to 26. Most of the detected QTL were found in only one environment. Four QTL were located in the regions containing genes/QTL previously identified for other related traits. The effects of identified QTL were relatively small with the highest percentage of phenotypic variance explained by a single QTL being 9.6%. The identified QTL are directly relevant to and can be more effectively used in breeding programs. (C) 2016 Elsevier B.V. All rights reserved.

  • 相关文献

[1]QTL mapping of grain appearance quality traits and grain weight using a recombinant inbred population in rice (Oryza sativa L.). Qiu Ling,Lu Xian-jun,Ren Juan-sheng,Wu Xian-ting,Su Xiang-wen,Ren Guang-jun,Zeng Li-hua,Qiu Ling,Gao Yong-ming. 2016

[2]Identification of QTLs for Yield-Related Traits in the Recombinant Inbred Line Population Derived from the Cross Between a Synthetic Hexaploid Wheat-Derived Variety Chuanmai 42 and a Chinese Elite Variety Chuannong 16. Li Jun,Wei Hui-ting,Li Chao-su,Yang Wu-yun,Chen Fang,Wu Yuan-qi. 2011

[3]Characterization of a cell wall invertase gene TaCwi-A1 on common wheat chromosome 2A and development of functional markers. Dongyun Ma,Jun Yan,Zhonghu He,Ling Wu,Xianchun Xia.

[4]QTL mapping for resistance of maize to grey leaf spot. Leng, Yifeng,Li, Lujiang,Wu, Yuanqi,Cao, Moju,Rong, Tingzhao,He, Wenzhu,Yang, Lin,Leng, Yifeng,Zhang, Biao,Yang, Junpin,Kang, Jiwei,Tang, Haitao,Deng, Luchang,Chen, Yunping. 2018

[5]Usefulness of the cloned and fine-mapped genes/QTL for grain yield and related traits in indica rice breeding for irrigated ecosystems. Zhou, Meixue,McNeil, David,Liang, Shanshan,Zhao, Xiangqian,Ye, Guoyou,Sun, Chenxiao,Ren, Guangjun.

[6]水稻抽穗扬花期耐热性的QTL分析. 张涛,杨莉,蒋开锋,黄敏,孙群,陈温福,郑家奎. 2008

[7]水稻再生能力和头季稻产量性状的QTL定位及其遗传效应分析. 谭震波,沈利爽,陆朝福,陈英,朱立煌,周开达,袁祚廉. 1997

[8]小麦成熟期QTL定位与分析. 王利彬,程敦公,任勇,张业伦,穆平,张玉梅,刘建军,李豪圣,赵振东,郝元峰,曹新有. 2018

[9]小麦穗长QTL鉴定及其遗传分析. 姚琦馥,周界光,王健,陈黄鑫,杨瑶瑶,刘倩,闫磊,王瑛,周景忠,崔凤娟,蒋云,马建. 2023

[10]甘薯SRAP连锁图构建淀粉含量QTL检测. 谭文芳,何俊蓉,蒲志刚,王大一,张正圣,詹付凤,阎文昭. 2005

[11]重要育种亲本川麦44对衍生品种的遗传贡献. 罗江陶,郑建敏,邓清燕,刘培勋,蒲宗君. 2021

[12]杂交籼稻子粒QTL标记遗传距离与粒重、粒重杂种优势的相关性. 曹应江,郑家奎,蒋开锋,张涛,杨莉,杨乾华,万先齐,罗婧. 2012

[13]地方小麦品种贵协3号赤霉病抗性QTL的定位与效应鉴定. 郑首航,何员江,陶军,张华,吴舸,邹凤亮,杜小英,欧俊梅,雷加容,闫海生,贾海燕,任勇. 2023

[14]小麦慢白粉病QTL对条锈病和叶锈病的兼抗性. 陈新民,何中虎,伍玲,白斌,李在峰,夏先春. 2014

[15]小麦成熟期QTL定位与分析. 王利彬,程敦公,任勇,张业伦,穆平,张玉梅,刘建军,李豪圣,赵振东,郝元峰,曹新有. 2018

[16]玉米RFLP连锁图谱构建及大斑病QTL定位. 向道权,杨俊品,戴景瑞. 2002

[17]不同生态环境下冬小麦籽粒大小相关性状的QTL分析. 张秀英,伍玲,王瑞,海林,游光霞,闫长生,肖世和. 2009

[18]小麦温敏不育系SCT-1育性基因初步定位分析. 蒲宗君,李式昭,李俊,杨恩年. 2015

[19]水稻子粒硒含量的遗传及QTL检测. 杨莉,张涛,郑家奎,金良,郑建敏,文春阳,杨乾华. 2010

[20]小麦品种川麦107对条锈病成株抗性的QTL定位. 王忠伟,伍玲,Ravi P Singh,J Huerta-Espino,何中虎,胡嘉,陈放,夏先春. 2010

作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：四川省农业科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台