Environmental Association Analyses in Plants and the Influence of Methodological Decisions

Area of Science:

• Plant sciences
• Genomics
• Ecology

Background:

• Climate change necessitates understanding plant environmental adaptation for conservation and crop improvement.
• Environmental association analyses (EAAs) are landscape genomic tools to identify genetic markers linked to environmental factors.
• A comprehensive review of 138 EAA studies in plants reveals diverse methodologies across analysis stages.

Purpose of the Study:

• To review existing Environmental Association Analysis (EAA) methodologies in plants.
• To compare the performance of four common EAA models using rice genetic data.
• To identify challenges in EAA and their application to crop breeding for climate resilience.

Main Methods:

• Systematic literature review of 138 plant EAA studies.
• Comparative analysis of four EAA models: MLM, LFMM, FarmCPU, and BLINK.
• Utilized genetic data from traditional Vietnamese rice (Oryza sativa) varieties.

Main Results:

• Significant diversity in EAA methods was observed across marker filtering, model selection, significance criteria, and downstream analyses.
• Recent Genome-Wide Association Study (GWAS) models (FarmCPU, BLINK) detected a higher proportion of significant markers compared to MLM and LFMM.
• Between 0 and 22 environmentally associated markers overlapped across models, with some linked to abiotic stress response genes.

Conclusions:

• Comparing EAA study results is challenging due to methodological variations.
• Recent GWAS models show promise for identifying environmentally adaptive loci in plants.
• Further research is needed to effectively apply EAA findings to breeding climate-resilient crop varieties.