Genome-wide association mapping and genomic prediction of agronomical traits and breeding values in Iranian wheat under rain-fed and well-watered conditions

Abstract

Background The markers detected by genome-wide association study (GWAS) make it possible to dissect genetic structure and diversity at many loci. This can enable a wheat breeder to reveal and used genomic loci controlling drought tolerance. This study was focused on determining the population structure of Iranian 208 wheat landraces and 90 cultivars via genotyping-by-sequencing (GBS) and also on detecting marker-trait associations (MTAs) by GWAS and genomic prediction (GS) of wheat agronomic traits for drought-tolerance breeding. GWASs were conducted using both the original phenotypes (pGWAS) and estimated breeding values (eGWAS). The bayesian ridge regression (BRR), genomic best linear unbiased prediction (gBLUP), and ridge regression-best linear unbiased prediction (rrBLUP) approaches were used to estimate breeding values and estimate prediction accuracies in genomic selection. Results Population structure analysis using 2,174,975 SNPs revealed four genetically distinct sub-populations from wheat accessions. D-Genome harbored the lowest number of significant marker pairs and the highest linkage disequilibrium (LD), reflecting different evolutionary histories of wheat genomes. From pGWAS, BRR, gBLUP, and rrBLUP, 284, 363, 359 and 295 significant MTAs were found under normal and 195, 365, 362 and 302 under stress conditions, respectively. The gBLUP with the most similarity (80.98 and 71.28% in well-watered and rain-fed environments, correspondingly) with the pGWAS method in the terms of discovered significant SNPs, suggesting the potential of gBLUP in uncovering SNPs. Results from gene ontology revealed that 29 and 30 SNPs in the imputed dataset were located in protein-coding regions for well-watered and rain-fed conditions, respectively. gBLUP model revealed genetic effects better than other models, suggesting a suitable tool for genome selection in wheat. Conclusion We illustrate that Iranian landraces of bread wheat contain novel alleles that are adaptive to drought stress environments. gBLUP model can be helpful for fine mapping and cloning of the relevant QTLs and genes, and for carrying out trait introgression and marker-assisted selection in both normal and drought environments in wheat collections.

Genome-wide association mapping of genomic regions associated with drought stress tolerance at seedling and reproductive stages in bread wheat

“…Overall, there were significant differences in the distribution of MTAs associated with the seedling and adult plant traits on different chromosomes, with 45.50% of MTAs identified on the A sub-genome, 37.79% in the B sub-genome, and only 16.69% in the D sub-genome. These findings align with the previous findings of lower genetic diversity and occurrence of higher LD in the D genome (Mwadzingeni et al, 2017;Bhatta et al, 2018;Sukumaran et al, 2018;Abou-Elwafa and Shehzad, 2021;El Gataa et al, 2022;Rabieyan et al, 2022). Furthermore, among the MTAs detected using all three models, as many as 19 significant SNPs associated with adult plant traits at different locations were found to be overlapped with as many as 13 significant SNPs associated with different seedling traits.…”

“…Drought tolerance is a complex quantitative trait governed by many genes, some of which have minor effects while others have major effects (Kumar et al, 2012). Further, it has low heritability owing to its polygenic inheritance and significant genotype by environment interaction (Sukumaran et al, 2018;El Gataa et al, 2022;Rabieyan et al, 2022). Drought tolerance can be improved genetically by identifying sources of stress-tolerant traits and/or genotypes, and introgressing and mobilizing the genomic regions controlling these traits into locally adapted cultivars (Shelake et al, 2022).…”

Genetic analyses and prediction for lodging‑related traits in a diverse Iranian hexaploid wheat collection

“…We repeated this process 100 times for each prediction method. A correlation (r) between the BLUPs and GEBVs was calculated over both the training and validation sets to measure GP accuracy 110 – 112 .…”

Role of Temporal Zn Fertilization along with Zn Solubilizing Bacteria in Enhancing Zinc Content, Uptake, and Zinc Use Efficiency in Wheat Genotypes and Its Implications for Agronomic Biofortification

“…This deficiency results in reduced Zn content in grains. Wheat (Triticum aestivum L.) stands out as the predominant staple cereal, globally cultivated on over 240 million hectares of land, with production exceeding 778 million tonnes [11], being as is an important staple crop in many parts of the world, and it does contribute significantly to the calorie and protein intake of various populations (25%) [12][13][14], however, it is inherently deficient in bioavailable Zn [15,16]. New wheat genotypes were developed through hybridization of synthetic hexaploid wheat lines derived from the wild ancestor "Aegilops tauschii" and cultivated wheat species Triticum durum.…”