Sampling within the genome for measuring within-population diversity: trade-offs between markers

Area of Science:

• Population Genetics
• Genomics
• Evolutionary Biology

Background:

• Estimating genetic diversity is crucial for understanding population dynamics.
• Discrepancies arise when using different marker systems, complicating interpretation.
• The influence of genomic and population heterogeneity on these estimates is not fully understood.

Purpose of the Study:

• To identify causes of contradictory diversity estimates from different marker systems.
• To assess the impact of marker sampling strategies on whole-genome diversity estimates.
• To provide recommendations for effective gene diversity surveys.

Main Methods:

• Simulated diverse evolutionary scenarios (population size, migration, gene flow heterogeneity).
• Computed population diversity for whole genomes and marker-specific subsets.
• Analyzed rank correlations between diversity estimates under various scenarios.

Main Results:

• Genomic heterogeneity (GH) and population heterogeneity (PH) varied significantly with evolutionary scenarios.
• GH and PH were key factors influencing rank correlations between marker-based diversity estimates.
• Strong positive correlation between estimates and PH was observed across all marker systems.
• Low GH required fewer microsatellites for whole-genome diversity prediction; increasing GH necessitated more loci or AFLP markers.

Conclusions:

• Population heterogeneity strongly influences the reliability of genetic diversity estimates.
• Genomic heterogeneity dictates the number and type of markers needed for accurate diversity assessment.
• Strategic marker selection based on genomic and population heterogeneity is essential for robust gene diversity surveys.