Multi-environment QTL analysis using an updated genetic map of a widely distributed Seri x Babax spring wheat population

被引:3
|
作者
Liu, Caiyun [1 ]
Khodaee, Mehdi [2 ]
Lopes, Marta S. [3 ,4 ]
Sansaloni, Carolina [5 ]
Dreisigacker, Susanne [1 ]
Sukumaran, Sivakumar [1 ]
Reynolds, Matthew [1 ]
机构
[1] Int Maize & Wheat Improvement Ctr, Global Wheat Program, Km 45 Carretera Mexico Veracruz, El Batan 56237, Texcoco, Mexico
[2] IUT, Coll Agr, Dept Agron & Plant Breeding, Esfahan 841568311, Iran
[3] Int Maize & Wheat Improvement Ctr CIMMYT, Global Wheat Program, TR-06511 Ankara, Turkey
[4] Inst Food & Agr Res & Technol IRTA, Sustainable Field Crops Program, Lleida, Spain
[5] Int Maize & Wheat Improvement Ctr, Genet Resources Program, Km 45 Carretera Mexico Veracruz, El Batan 56237, Texcoco, Mexico
关键词
90K wheat SNPs; DArTseq; QTL mapping; Seri x Babax; Grain yield; QUANTITATIVE TRAIT LOCI; GRAIN-YIELD; PHYSIOLOGICAL TRAITS; DROUGHT; HEAT; POLYMORPHISM; ADAPTATION; DISSECTION; COMPONENTS; MARKERS;
D O I
10.1007/s11032-019-1040-1
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Seri/Babax spring wheat RIL population was developed to minimize the confounding effect of phenology in the genetic dissection of abiotic stress traits. An existing linkage map (< 500 markers) was updated with 6470 polymorphic Illumina iSelect 90K array and DArTseq SNPs to a genetic map of 5576.5 cM with 1748 non-redundant markers (1165 90K SNPs, 207 DArTseq SNPs, 183 AFLP, 111 DArT array, and 82 SSR) assigned to 31 linkage groups. We conducted QTL mapping for yield and related traits phenotyped in several major wheat growing areas in Egypt, Sudan, Iran, India, and Mexico (nine environments: heat, drought, heat plus drought, and yield potential). QTL analysis identified 39 (LOD 2.5-23.6; PVE 4.8-21.3%), 36 (LOD 2.5-15.4; PVE 2.9-21.4%), 30 (LOD 2.5-13.1; PVE 3.6-26.8%), 39 (LOD 2.7-14.4; PVE 2.6-15.9%), and 22 (LOD 2.8-4.8; PVE 6.8-12.9%) QTLs for grain yield, thousand-grain weight, grain number, days to heading, and plant height, respectively. The present study confirmed QTLs from previous studies and identified novel QTLs. QTL analysis based on high-yielding and low-yielding environmental clusters identified 11 QTLs (LOD 2.6-14.9; PVE 2.7-19.7%). The updated map thereby provides a better genome coverage (3.5-fold) especially on the D genome (4-fold), higher density (1.1-fold), and a good collinearity with the IWGSC RefSeq v1.0 genome, and increased the number of detected QTLs (5-fold) compared with the earlier map. This map serves as a useful genomic resource for genetic analyses of important traits on this wheat population that was widely distributed around the world.
引用
收藏
页数:15
相关论文
共 43 条
  • [1] Multi-environment QTL analysis using an updated genetic map of a widely distributed Seri × Babax spring wheat population
    Caiyun Liu
    Mehdi Khodaee
    Marta S. Lopes
    Carolina Sansaloni
    Susanne Dreisigacker
    Sivakumar Sukumaran
    Matthew Reynolds
    Molecular Breeding, 2019, 39
  • [2] Multi-parent multi-environment QTL analysis: an illustration with the EU-NAM Flint population
    Vincent Garin
    Marcos Malosetti
    Fred van Eeuwijk
    Theoretical and Applied Genetics, 2020, 133 : 2627 - 2638
  • [3] Multi-parent multi-environment QTL analysis: an illustration with the EU-NAM Flint population
    Garin, Vincent
    Malosetti, Marcos
    van Eeuwijk, Fred
    THEORETICAL AND APPLIED GENETICS, 2020, 133 (09) : 2627 - 2638
  • [4] Genotype x environment interaction analysis of multi-environment wheat trials in India using AMMI and GGE biplot models
    Singh, Charan
    Gupta, Arun
    Gupta, Vikas
    Kumar, Pradeep
    Sendhil, R.
    Tyagi, B. S.
    Singh, Gyanendra
    Chatrath, Ravish
    Singh, G. P.
    CROP BREEDING AND APPLIED BIOTECHNOLOGY, 2019, 19 (03): : 309 - 318
  • [5] Multi-environment QTL mapping reveals genetic architecture of fruit cracking in a tomato RIL Solanum lycopersicum x S-pimpinellifolium population
    Capel, Carmen
    Yuste-Lisbona, Fernando J.
    Lopez-Casado, Gloria
    Angosto, Trinidad
    Cuartero, Jesus
    Lozano, Rafael
    Capel, Juan
    THEORETICAL AND APPLIED GENETICS, 2017, 130 (01) : 213 - 222
  • [6] Multi-environment QTL analysis of grain morphology traits and fine mapping of a kernel-width QTL in Zheng58 x SK maize population
    Raihan, Mohammad Sharif
    Liu, Jie
    Huang, Juan
    Guo, Huan
    Pan, Qingchun
    Yan, Jianbing
    THEORETICAL AND APPLIED GENETICS, 2016, 129 (08) : 1465 - 1477
  • [7] Multi-environment analysis and improved mapping of a yield-related QTL on chromosome 3B of wheat
    Julien Bonneau
    Julian Taylor
    Boris Parent
    Dion Bennett
    Matthew Reynolds
    Catherine Feuillet
    Peter Langridge
    Diane Mather
    Theoretical and Applied Genetics, 2013, 126 : 747 - 761
  • [8] Multi-environment analysis and improved mapping of a yield-related QTL on chromosome 3B of wheat
    Bonneau, Julien
    Taylor, Julian
    Parent, Boris
    Bennett, Dion
    Reynolds, Matthew
    Feuillet, Catherine
    Langridge, Peter
    Mather, Diane
    THEORETICAL AND APPLIED GENETICS, 2013, 126 (03) : 747 - 761
  • [9] QTL mapping for foxtail millet plant height in multi-environment using an ultra-high density bin map
    Qiang He
    Hui Zhi
    Sha Tang
    Lu Xing
    Suying Wang
    Haigang Wang
    Aiying Zhang
    Yuhui Li
    Ming Gao
    Haijin Zhang
    Guoqiu Chen
    Shutao Dai
    Junxia Li
    Junjun Yang
    Huifang Liu
    Wei Zhang
    Yanchao Jia
    Shujie Li
    Jinrong Liu
    Zhijun Qiao
    Erhu Guo
    Guanqing Jia
    Jun Liu
    Xianmin Diao
    Theoretical and Applied Genetics, 2021, 134 : 557 - 572
  • [10] QTL mapping for foxtail millet plant height in multi-environment using an ultra-high density bin map
    He, Qiang
    Zhi, Hui
    Tang, Sha
    Xing, Lu
    Wang, Suying
    Wang, Haigang
    Zhang, Aiying
    Li, Yuhui
    Gao, Ming
    Zhang, Haijin
    Chen, Guoqiu
    Dai, Shutao
    Li, Junxia
    Yang, Junjun
    Liu, Huifang
    Zhang, Wei
    Jia, Yanchao
    Li, Shujie
    Liu, Jinrong
    Qiao, Zhijun
    Guo, Erhu
    Jia, Guanqing
    Liu, Jun
    Diao, Xianmin
    THEORETICAL AND APPLIED GENETICS, 2021, 134 (02) : 557 - 572