Marker-trait association analyses revealed major novel QTLs for grain yield and related traits in durum wheat

Abstract

The growing global demand for wheat for food is rising due to the influence of population growth and climate change. The dissection of complex traits by employing a genome-wide association study (GWAS) allows the identification of DNA markers associated with complex traits to improve the productivity of crops. We used GWAS with 10,045 single nucleotide polymorphism (SNP) markers to search for genomic regions associated with grain yield and related traits based on diverse panels of Ethiopian durum wheat. In Ethiopia, multi-environment trials of the genotypes were carried out at five locations. The genotyping was conducted using the 25k Illumina Wheat SNP array to explore population structure, linkage disequilibrium (LD), and marker-trait associations (MTAs). For GWAS, the multi-locus Fixed and Random Model Circulating Probability Unification (FarmCPU) model was applied. Broad-sense heritability estimates were high, ranging from 0.63 (for grain yield) to 0.97 (for thousand-kernel weight). The population structure based on principal component analysis, and model-based cluster analysis revealed two genetically distinct clusters with limited admixtures. The LD among SNPs declined within the range of 2.02–10.04 Mbp with an average of 4.28 Mbp. The GWAS scan based on the mean performance of the genotypes across the environments identified 44 significant MTAs across the chromosomes. Twenty-six of these MTAs are novel, whereas the remaining 18 were previously reported and confirmed in this study. We also identified candidate genes for the novel loci potentially regulating the traits. Hence, this study highlights the significance of the Ethiopian durum wheat gene pool for improving durum wheat globally. Furthermore, a breeding strategy focusing on accumulating favorable alleles at these loci could improve durum wheat production in the East African highlands and elsewhere.

Genome-Wide Association Studies for Identification of Novel QTLs Related to Agronomic Traits in Horsegram (Macrotyloma uniflorum)

“…Advance technology like Genotype-By-Sequencing (GBS) which is also cheap and cost effective is now used widely for identification of genome-wide high throughput SNPs (Single Nucleotide Polymorphism) which are further utilized for diversity analysis, linkage and association mapping studies (Wang, et al, 2020). Furthermore, Marker Trait Association (MAS) studies are promising strategies and has been widely utilized to understand the underlying genetic architecture of important agronomic traits like grain yield and consensus abiotic stress tolerance in wheat, salinity tolerance in rice, heat stress in tomato, seed quality in Pea, forage quality in auto-tetraploid alfalfa, and biotic stress in pepper (Alsamir & Hameed, 2019;Gali, et al, 2019;Lin, et al, 2020;Liu, et al, 2019;Mulugeta, et al, Despite one effort with conventional QTL mapping technique, wherein QTLs related to plant height (1) and primary branches (3) and secondary branches (3) has been reported in the horsegram using bi-parental segregating population (RILs). However, no efforts have been made to generate accurate genotypes with diverse panel to characterize and understand their genetic potential and associate them with agronomically important 4 traits.…”

Genome-wide association studies for identification of novel QTLs related to four agronomic traits in Horsegram (Macrotyloma uniflorum)

“…Advance technology like Genotype-By-Sequencing (GBS) which is also cheap and cost effective is now used widely for identi cation of genome-wide high throughput SNPs (Single Nucleotide Polymorphism) which are further utilized for diversity analysis, linkage and association mapping studies (Wang, et al, 2020). Furthermore, Marker Trait Association (MAS) studies are promising strategies and has been widely utilized to understand the underlying genetic architecture of important agronomic traits like grain yield and consensus abiotic stress tolerance in wheat, salinity tolerance in rice, heat stress in tomato, seed quality in Pea, forage quality in auto-tetraploid alfalfa, and biotic stress in pepper (Alsamir & Hameed, 2019;Gali, et al, 2019;Lin, et al, 2020;Liu, et al, 2019;Mulugeta, et Despite one effort with conventional QTL mapping technique, wherein QTLs related to plant height (1) and primary branches (3) and secondary branches (3) has been reported in the horsegram using bi-parental segregating population (RILs). However, no efforts have been made to generate accurate genotypes with diverse panel to characterize and understand their genetic potential and associate them with agronomically important traits.…”