Association mapping in plants in the post-GWAS genomics era

Area of Science:

• Genetics and Genomics
• Plant Breeding
• Bioinformatics

Background:

• DNA markers and statistical tools enabled identification of genomic regions controlling quantitative traits.
• Quantitative trait loci (QTL) interval mapping and genome-wide association studies (GWAS) were initial methods, each with limitations.
• The field has advanced into a post-GWAS era, leveraging existing and new data with sophisticated analyses.

Purpose of the Study:

• To review historical and current approaches for genome-wide association studies (GWAS) in plants.
• To discuss the utilization of GWAS results for crop improvement.
• To explore advancements and resources in the post-GWAS era for identifying causal variants and enhancing crop breeding.

Main Methods:

• Review of quantitative trait loci (QTL) interval mapping and genome-wide association studies (GWAS).
• Discussion of improvements addressing GWAS limitations: multi-locus/multi-trait analysis, joint linkage association mapping.
• Exploration of post-GWAS methods: meta-analysis, pathway analysis, methylation QTL, functional characterization, machine learning for high-dimensional data.

Main Results:

• GWAS has been applied to major crops like maize, wheat, rice, sorghum, and soybean.
• Improvements have been made to address computational demands, multiple testing, false discoveries, and rare alleles in GWAS.
• The post-GWAS era focuses on identifying causal variants, functional characterization, and utilizing advanced data analysis techniques.

Conclusions:

• GWAS and its advancements have significantly contributed to understanding trait genetics and marker-assisted selection in crops.
• The post-GWAS era offers powerful tools and resources for precise identification of causal variants and accelerating crop improvement.
• Continued development and application of these genomic approaches are crucial for future agricultural advancements.