Genome-wide association study of agronomic traits in bread wheat reveals novel putative alleles for future breeding programs

Abstract

Background: Identification of loci for agronomic traits and characterization of their genetic architecture are crucial in marker-assisted selection (MAS). Genome-wide association studies (GWAS) have increasingly been used as potent tools in identifying marker-trait associations (MTAs). The introduction of new adaptive alleles in the diverse genetic backgrounds may help to improve grain yield of old or newly developed varieties of wheat to balance supply and demand throughout the world. Landraces collected from different climate zones can be an invaluable resource for such adaptive alleles.

Results: GWAS was performed using a collection of 298 Iranian bread wheat varieties and landraces to explore the genetic basis of agronomic traits during 2016-2018 cropping seasons under normal (well-watered) and stressed (rain-fed) conditions. A high-quality genotyping by sequencing (GBS) dataset was obtained using either all original single nucleotide polymorphism (SNP, 10938 SNPs) or with additional imputation (46,862 SNPs) based on W7984 reference genome. The results confirm that the B genome carries the highest number of significant marker pairs in both varieties (49,880, 27.37%) and landraces (55,086, 28.99%). The strongest linkage disequilibrium (LD) between pairs of markers was observed on chromosome 2D (0.296). LD decay was lower in the D genome, compared to the A and B genomes. Association mapping under two tested environments yielded a total of 313 and 394 significant (-log₁₀ P >3) MTAs for the original and imputed SNP data sets, respectively. Gene ontology results showed that 27 and 27.5% of MTAs of SNPs in the original set were located in protein-coding regions for well-watered and rain-fed conditions, respectively. While, for the imputed data set 22.6 and 16.6% of MTAs represented in protein-coding genes for the well-watered and rain-fed conditions, respectively.

Conclusions: Our finding suggests that Iranian bread wheat landraces harbor valuable alleles that are adaptive under drought stress conditions. MTAs located within coding genes can be utilized in genome-based breeding of new wheat varieties. Although imputation of missing data increased the number of MTAs, the fraction of these MTAs located in coding genes were decreased across the different sub-genomes.

Keywords: Agronomic traits; GWAS; Gene annotation; MTAs; Wheat.

Fig. 1

The distribution of SNPs according to different MAF for the original and imputed datasets

Fig. 2

Principal component analysis of Iranian accessions using original SNPs (A), and imputed SNPs (B)

Fig. 3

Cluster analysis using Kinship matrix of original data (A) and imputed data (B) for Iranian wheat accessions

Fig. 4

The dendrogram of Neighbor-Joining clustering constructed using 10,938 (A) and 46,862 (B) SNPs and 90 Iranian hexaploid wheat varieties

Fig. 5

The dendrogram of Neighbor-Joining clustering constructed using 10,938 (A) and 46,862 (B) SNPs and 208 Iranian hexaploid wheat landraces collected from different zones

Fig. 6

Manhattan and QQ-plots of highly associated haplotypes for agronomic traits under well-watered and rain-fed conditions. A) seed number per spike, B) spike length, C) thousand kernel weight, D) peduncle length. X axis represents chromosomes: 1)1A, 2) 1B, 3) 1D, 4) 2A, 5) 2B, 6) 2D, 7) 3A, 8) 3B, 9) 3D, 10) 4A, 11) 4B, 12) 4D, 13) 5A, 14) 5B, 15) 5D, 16) 6A, 17) 6B, 18) 6D, 19) 7A, 20) 7B, 21)7D