数字农科院2.0

Genome-Wide Association Mapping And Genomic P.rediction Analyses Reveal The G enetic Architecture Of Grain Yield And Flowering Time Under Drought And Heat Stress Conditions In Maize

文献类型: 外文期刊

作者: Magorokosho, Cosmos;Hao, Zhuanfang;Makumbi, Dan;Liu, Yubo;Lu, Yanli;Gowda, Manje;Olsen, Michael S.;Cairns, Jill E.;Babu, Raman;Babu, Raman;Wang, Nan;Wang, Nan;Zhang, Xuecai;Prasanna, Boddupalli M.;San Vicente, Felix;Yuan, Yibing;Lu, Yanli;Yuan, Yibing;Yuan, Yibing;Zhang, Ao

作者机构:

关键词: maize; association mapping; genomic prediction; drought stress; heat stress; combined drought and heat stress

期刊名称: FRONTIERS IN PLANT SCIENCE

ISSN: 1664-462X

年卷期: 2019 年 9 卷

页码:

摘要: Drought stress (DS) is a major constraint to maize yield production. Heat stress (HS) alone and in combination with DS are likely to become the increasing constraints. Association mapping and genomic prediction (GP) analyses were conducted in a collection of 300 tropical and subtropical maize inbred lines to reveal the genetic architecture of grain yield and flowering time under well-watered (WW), DS, HS, and combined DS and HS conditions. Out of the 381,165 genotyping-by-sequencing SNPs, 1549 SNPs were significantly associated with all the 12 trait-environment combinations, the average PVE (phenotypic variation explained) by these SNPs was 4.33%, and 541 of them had a PVE value greater than 5%. These significant associations were clustered into 446 genomic regions with a window size of 20 Mb per region, and 673 candidate genes containing the significantly associated SNPs were identified. In addition, 33 hotspots were identified for 12 trait-environment combinations and most were located on chromosomes 1 and 8. Compared with single SNP-based association mapping, the haplotype-based associated mapping detected fewer number of significant associations and candidate genes with higher PVE values. All the 688 candidate genes were enriched into 15 gene ontology terms, and 46 candidate genes showed significant differential expression under the WW and DS conditions. Association mapping results identified few overlapped significant markers and candidate genes for the same traits evaluated under different managements, indicating the genetic divergence between the individual stress tolerance and the combined drought and HS tolerance. The GP accuracies obtained from the marker-trait associated SNPs were relatively higher than those obtained from the genome-wide SNPs for most of the target traits. The genetic architecture information of the grain yield and flowering time revealed in this study, and the genomic regions identified for the different trait-environment combinations are useful in accelerating the efforts on rapid development of the stress-tolerant maize germplasm through marker-assisted selection and/or genomic selection.

分类号:

  • 相关文献

[1]Alternative Splicing In Tea Plants Was Extensively Triggered By Drought, Heat And Their Combined Stresses. Ding, Zhaotang,Qiu, Chen,Xie, Hui,Wang, Yu,Ding, Yiqian,Qian, Wenjun. 2020

[2]Genetic Dissection Of Drought And H.eat-Responsive Agronomic Traits In W heat. 李龙,,毛新国,,王景一,,昌小平,,景蕊莲. 2019

[3]Genome-Wide Association Study And Genomic P.rediction Analyses Of Drought S tress Tolerance In China In A Collection Of Off-Pvp Maize Inbred Lines. Liang, Xiaoling,Wang, Nan,Weng, Jianfeng,Nair, Sudha,Zhang, Degui,Yang, Jie,Li, Xinhai,Liu, Bojuan,Song, Jie,Zhang, Xuecai,Hao, Zhuanfang,San Vicente, Felix,Yong, Hongjun,Li, Mingshun,Zhou, Yueheng. 2019

[4]Transcriptome And Gwas Analyses Reveal Candidate Gene For Seminal Root Length Of Maize Seedlings Under Drought Stress. Wang, Tianyu,Guo, Jian,Yang, Deguang,Li, Yongxiang,Song, Yanchun,Shi, Yunsu,Zhang, Dengfeng,Li, Chunhui,Li, Yu,Zhang, Xiaoqiong. 2020

[5]Spatio-Temporal Transcriptional Dynamics Of Maize L.ong Non-Coding Rnas Responsive T o Drought Stress. Zhao, Jun,Zhang, Xia,Pang, Junling,Ma, Xuhui. 2019

[6]DissectingthemaizedirectandindirectdefenseresponseagainstAsianCornBorer. 汪海,李圣彦,查象敏,朱莉,黄大昉,郎志宏. 2015

[7]TheDifferentialTranscriptionNetworkbetweenEmbryoandEndospermintheEarlyDevelopingMaizeSeed. XiaoduoLu,DijunChen,DefengShu,ZhaoZhang,WeixuanWang,ChristianKlukas,Ling-lingChen,YunliuFan,MingChen,ChunyiZhang. 2015

[8]A Study Of Genomic Prediction Of 12 Important Traits In The Domesticated Yak (Bos Grunniens). Jia, Congjun,Ma, Xiaoming,Chu, Min,Lei, Qinhui,Ding, Xuezhi,Yan, Ping,Jia, Congjun,Wu, Xiaoyun,Pei, Jie,Bao, Pengjia,Pei, Jie,Bao, Pengjia,Ding, Xuezhi,Chu, Min,Lei, Qinhui,Wu, Xiaoyun,Ma, Xiaoming,Fu, Donghai,Fu, Donghai,Guo, Xian,Yan, Ping,Liang, Chunnian,Guo, Xian,Wen, Zhiping. 2019

[9]Genetic Relatedness And The Ratio Of Subpopulation-Common Alleles Are Related In Genomic Prediction Across Structured Subpopulations In Maize. Li, DD, Wang, PX, Gu, RL, Fu, JJ, Xu, ZX, Lyle, D, Peng, YL, Wang, GY, Zhang, HW. 2019

[10]Genomic Prediction And Association Analysis With Models Including Dominance Effects For Important Traits In Chinese Simmental Beef Cattle. Liu, Y, Xu, L, Wang, ZZ, Xu, L, Chen, Y, Zhang, LP, Xu, LY, Gao, X, Gao, HJ, Zhu, B, Li, JY. 2019

[11]Accuracy Assessment Of Plant Height U.sing An Unmanned Aerial V ehicle For Quantitative Genomic Analysis In Bread Wheat. Hassan, MA, Yang, MJ, Fu, LP, Rasheed, A, Zheng, BY, Xia, XC, Xiao, YG, He, ZH. 2019

[12]Genome Wide Association Study And G.enomic Prediction For Fatty A cid Composition In Chinese Simmental Beef Cattle Using High Density Snp Array. Zhu, B, Niu, H, Zhang, WG, Wang, ZZ, Liang, YH, Guan, L, Guo, P, Chen, Y, Zhang, LP, Guo, Y, Ni, HM, Gao, X, Gao, HJ, Xu, LY, Li, JY. 2017

[13]Genomic Prediction For 25 Agronomic A.nd Quality Traits In A lfalfa (Medicago Sativa). Jia, CJ, Zhao, FP, Wang, XM, Han, JL, Zhao, HM, Liu, GB, Wang, Z. 2018

[14]Chemosensory systems in predatory mites: From ecology to genome. Su Yaozong,Zhang Bo,Xu Xuenong. 2021

[15]Chemosensory systems in predatory mites: From ecology to genome. Su Yaozong,Zhang Bo,Xu Xuenong. 2021

[16]Hybrid Breeding Of Rice Via Genomic Selection. 张帆,黎志康. 2020

[17]Fast Genomic Prediction Of Breeding V.alues Using Parallel Markov C hain Monte Carlo With Convergence Diagnosis. Guo, P, Zhu, B, Niu, H, Wang, ZZ, Liang, YH, Chen, Y, Zhang, LP, Ni, HM, Guo, Y, Hay, EA, Gao, X, Gao, HJ, Wu, XL, Xu, LY, Li, JY. 2018

[18]A Stacking Ensemble Learning Framework for Genomic Prediction. Mang Liang,Tianpeng Chang,Bingxing An,Xinghai Duan,Lili Du,Xiaoqiao Wang,Jian Miao,Lingyang Xu,Xue Gao,Lupei Zhang,Junya Li,Huijiang Gao. 2021

[19]Dissection Of Complicate Genetic Architecture A.nd Breeding Perspective Of C ottonseed Traits By Genome-Wide Association Study. Xia, Qiuju,Xiang, Haitao,Ma, Jun,Xu, Haiming,Du, Xiongming,Sun, Gaofei,Jia, Yinhua,Pan, Zhaoe,He, Shoupu,Quan, Zhiwu,Shi, Weijun,Jenkins, Johnie N.,Du, Xiongming,Sun, Junling,Zhu, Jun,Zhang, Gengyun,Xiao, Songhua,Pang, Baoyin,Liu, Jianguang,Lou, Xiangyang,Gong, Wenfang,Wang, Liru,Liu, Shouye. 2018

[20]Association Mapping Analysis Of Fiber Y.ield And Quality Traits I n Upland Cotton (Gossypium Hirsutum L.). Ademe, Mulugeta Seyoum,Du, Xiongming,Li, Lin,Ma, Zhiying,Sun, Junling,Cai, Zhongmin,Wang, Liru,Zhu, Haiyong,Jia, Yinhua,He, Shoupu,Wang, Qinglian,Yang, Jinlong,Zhang, Jinbiao,Pang, Baoyin,Zhang, Xin,Liu, Jinhai,Qin, Hongde,Zhang, Xuelin,Zhou, Guanyin,Li, Zhikun,Huang, Aifen,Pan, Zhaoe,Yang, Jun,Liu, Hui,Yi, Xianda. 2017

作者其他论文 更多>>