The search for loci under selection: trends, biases and progress

Area of Science:

• Evolutionary genomics
• Population genetics
• Ecological genetics

Background:

• Outlier analysis (OA) and environmental association analyses (EAA) are common methods to detect genetic selection.
• These approaches offer insights into the genetic underpinnings of local adaptation.
• However, their application to empirical, field-based data has not been comprehensively reviewed.

Purpose of the Study:

• To synthesize trends and biases in the application of OA and EAA using Single Nucleotide Polymorphisms (SNPs) in empirical studies.
• To identify factors influencing the detection of selection signatures.
• To provide recommendations for improving the design and reporting of future studies.

Main Methods:

• A systematic review of 66 empirical studies employing OA and EAA with SNPs.
• Analysis of trends across biological systems, sequencing methods, analytical approaches, parameters, and environmental variables.
• Evaluation of the influence of sampling effort (genomic and biological) on detecting selection.

Main Results:

• Significant variability was observed in the use and reporting of environmental data and statistical parameters.
• Linkage disequilibrium and the number of unique SNP associations were infrequently reported.
• The proportion of putatively adaptive SNPs decreased with an increased number of SNPs analyzed.
• Genomic sampling effort had a greater impact than biological sampling effort on identifying selected SNPs.

Conclusions:

• Standardized reporting of geographical coordinates, environmental data, model parameters, linkage disequilibrium, and genetic structure is crucial for repeatability and synthesis.
• Establishing reporting standards for OA and EAA will enhance transparency and comparability in SNP-based selection studies.
• These standards will advance landscape and evolutionary genomics research.