Comprehensive evaluation of mapping complex traits in wheat using genome-wide association studies

Area of Science:

• Agricultural Science
• Genetics
• Bioinformatics

Background:

• Genome-wide association studies (GWAS) are crucial for dissecting complex quantitative traits in crops.
• Wheat (Triticum aestivum) has been extensively studied using GWAS for various traits, including quality, stress tolerance, and yield.

Purpose of the Study:

• To provide a comprehensive overview of association mapping in wheat.
• To review advancements in statistical models, genotyping, and phenotyping for GWAS.
• To discuss the current status and future directions of GWAS in wheat breeding.

Main Methods:

• Literature review of published wheat GWAS.
• Analysis of statistical models, population design, and high-throughput platforms.
• Synthesis of reported marker-trait associations (MTAs) and their utilization.

Main Results:

• Over 86,000 wheat lines studied across numerous GWAS, identifying 46,940 loci.
• Significant progress in statistical modeling and technological platforms for GWAS.
• Limited current utilization of identified MTAs in breeding programs.

Conclusions:

• GWAS has generated a vast resource of MTAs for wheat improvement.
• Future breakthroughs lie in genomic selection, multi-omics, and machine learning integrated with GWAS.
• This review serves as a valuable resource for researchers entering wheat GWAS.