Genetic analysis of multi-environmental spring wheat trials identifies genomic regions for locus-specific trade-offs for grain weight and grain number
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.
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.
- Brinton J, Simmonds J, Minter F et al (2017a) Increased pericarp cell length underlies a major quantitative trait locus for grain weight in hexaploid wheat. New Phytol 6:1–6Google Scholar
- Brinton J, Simmonds J, Minter F et al (2017b) Increased pericarp cell length underlies a major QTL for grain weight in hexaploid wheat. bioRxiv 6:1–6Google Scholar
- Edae EA, Byrne PF, Manmathan H, Haley SD, Moragues M, Lopes MS, Reynolds MP (2013) Association mapping and nucleotide sequence variation in five drought tolerance candidate genes in spring wheat. Plant Genome 6(2). https://doi.org/10.3835/plantgenome2013.04.0010
- Griffiths S, Wingen L, Pietragalla J et al (2015) Genetic dissection of grain size and grain number trade-offs in CIMMYT wheat germplasm. PLoS ONE 10:1–18Google Scholar
- Jaiswal V, Gahlaut V, Mathur S et al (2015) Identification of novel SNP in promoter sequence of TaGW2-6A associated with grain weight and other agronomic traits in wheat (Triticum aestivum L.). PLoS One 10:1–15Google Scholar
- Pask AJD, Pietragalla J, Mullan DM, Reynolds MP (2012) Physiological breeding II: a field guide to wheat phenotyping. CimmytGoogle Scholar
- Schulthess AW, Reif JC, Ling J, Plieske J, Kollers S, Ebmeyer E, Korzun V, Argillier O, Stiewe G, Ganal MW, Röder (2017) The roles of pleiotropy and close linkage as revealed by association mapping of yield and correlated traits of wheat (Triticum aestivum L.). J Ex Bot 68(15):4089–4101CrossRefGoogle Scholar
- Sukumaran S, Crossa J, Jarquin D, Lopes M, Reynolds MP (2017) Genomic prediction with pedigree and genotype × environment interaction in spring wheat grown in South and West Asia, North Africa, and Mexico. G3 (Bethesda) 7(2):481–495. https://doi.org/10.1534/G3.116.036251
- Wei T, Simko V (2017) R package “corrplot”: Visualization of a correlation matrix (Version 0.84). Available from https://github.com/taiyun/corrplot. Accessed 12 Dec 2017