Theoretical and Applied Genetics

, Volume 131, Issue 4, pp 985–998 | Cite as

Genetic analysis of multi-environmental spring wheat trials identifies genomic regions for locus-specific trade-offs for grain weight and grain number

  • Sivakumar Sukumaran
  • Marta Lopes
  • Susanne Dreisigacker
  • Matthew Reynolds
Original Article


Key message

GWAS on multi-environment data identified genomic regions associated with trade-offs for grain weight and grain number.


Grain yield (GY) can be dissected into its components thousand grain weight (TGW) and grain number (GN), but little has been achieved in assessing the trade-off between them in spring wheat. In the present study, the Wheat Association Mapping Initiative (WAMI) panel of 287 elite spring bread wheat lines was phenotyped for GY, GN, and TGW in ten environments across different wheat growing regions in Mexico, South Asia, and North Africa. The panel genotyped with the 90 K Illumina Infinitum SNP array resulted in 26,814 SNPs for genome-wide association study (GWAS). Statistical analysis of the multi-environmental data for GY, GN, and TGW observed repeatability estimates of 0.76, 0.62, and 0.95, respectively. GWAS on BLUPs of combined environment analysis identified 38 loci associated with the traits. Among them four loci—6A (85 cM), 5A (98 cM), 3B (99 cM), and 2B (96 cM)—were associated with multiple traits. The study identified two loci that showed positive association between GY and TGW, with allelic substitution effects of 4% (GY) and 1.7% (TGW) for 6A locus and 0.2% (GY) and 7.2% (TGW) for 2B locus. The locus in chromosome 6A (79–85 cM) harbored a gene TaGW2-6A. We also identified that a combination of markers associated with GY, TGW, and GN together explained higher variation for GY (32%), than the markers associated with GY alone (27%). The marker-trait associations from the present study can be used for marker-assisted selection (MAS) and to discover the underlying genes for these traits in spring wheat.



The wheat association Mapping Initiative


Best linear unbiased predictions


Mixed linear models


Generalized linear models



This work was implemented by CIMMYT as part of the MasAgro in collaboration with CIMMYT, made possible by the generous support of SAGARPA, IWYP, and ARCADIA Any opinions, findings, conclusion, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of SAGARPA, IWYP, and ARCADIA.

Author contributions

SS, MR, ML conceived the study. SS, MR, SD genotyped the panel. SS did the genetic analysis and wrote the manuscript. All authors read, made constructive comments, and approved the manuscript.

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest.

Supplementary material

122_2017_3037_MOESM1_ESM.tif (1.4 mb)
Supplementary material 1 (TIFF 1449 kb) Supplementary Fig. 1. Linkage disequilibrium (LD) plot of the chromosome 3B region showing high LD of the markers associated with the traits. Markers used were RAC875_c1997_2590 (85 cM), RAC875_c5427_447 (91 cM), BobWhite_c35398_181 (95 cM), and wsnp_CAP12_c2297_1121142 (119 cM)
122_2017_3037_MOESM2_ESM.tif (1.7 mb)
Supplementary material 2 (TIFF 1770 kb) Supplementary Fig. 2. Linkage disequilibrium (LD) plot of the chromosome 6A showing the high LD region (77–85 cM). Markers in chromosome 6A were wsnp_Ra_c61979_62215037 (77 cM), wsnp_Ku_rep_c72681_72356010 (78 cM), wsnp_Ra_rep_c100410_86374467 (79 cM), wsnp_Ku_rep_c112734_95776957 (80 cM), wsnp_Ex_c34545_42832894 (81 cM), wsnp_RFL_Contig4424_5193532 (82 cM), wsnp_Ex_c341_667884 (83 cM), wsnp_Ku_c4296_7807837 (84 cM), wsnp_Ra_c11269_18309313 (85 cM) and Excalibur_rep_c111263_307 (86 cM)
122_2017_3037_MOESM3_ESM.tif (1.7 mb)
Supplementary material 3 (TIFF 1756 kb) Supplementary Fig. 3. Linkage disequilibrium plot (LD) of the 5A region 90–98 cM showing the SNP at 98 cM is not in high LD with the SNPs from 89–98 cM. Markers in chromosome 5A were wsnp_Ra_c12183_19587379 (89 cM), wsnp_Ex_c5998_10513766 (90 cM), wsnp_Ex_rep_c66689_65010988 (91 cM), wsnp_RFL_Contig2265_1693968 (92 cM), wsnp_Ex_rep_c109532_92292121 (93 cM), wsnp_Ra_c3966_7286546 (94 cM), IAAV108 (95 cM), wsnp_BF484028B_Td_2_1 (96 cM), wsnp_Ex_c790_1554988 (97 cM), and wsnp_Ku_c42416_50159250 (98 cM)
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Supplementary material 4 (TIFF 1366 kb)
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Supplementary material 13 (XLSX 10 kb)


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Global Wheat ProgramInternational Maize and Wheat Improvement Center (CIMMYT)Mexico CityMexico
  2. 2.CIMMYTEmek, AnkaraTurkey

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