Population genetic inferences using immune gene SNPs mirror patterns inferred by microsatellites

Area of Science:

• Population genetics
• Conservation genetics
• Genomics

Background:

• Single nucleotide polymorphisms (SNPs) are increasingly used in population genetic analyses, but their correlation with traditional microsatellite markers is not fully understood.
• Determining the number of SNPs required for reliable population genetic parameter estimation is crucial for study design.

Purpose of the Study:

• To compare the efficacy of single nucleotide polymorphisms (SNPs) versus microsatellites for estimating population genetic parameters in the gopher tortoise (Gopherus polyphemus).
• To assess the correlation between SNP and microsatellite data for various genetic metrics, including heterozygosity, allelic richness, and population structure.
• To determine the minimum number of SNPs needed to achieve comparable results to microsatellite analyses.

Main Methods:

• Compared a SNP dataset (17,901 SNPs from 16 tortoises) with two microsatellite datasets (10 microsatellites from 101 and 16 tortoises).
• Analyzed observed heterozygosity, expected heterozygosity, allelic richness, FST, and population structure using STRUCTURE and Principal Component Analysis (PCA).

Main Results:

• SNPs and microsatellites showed correlations for observed heterozygosity, expected heterozygosity, and FST, but not consistently for allelic richness.
• More than 800 SNPs were needed for allelic richness and heterozygosity correlation, while only 100 SNPs were sufficient for FST correlation.
• PCA revealed four clusters across all datasets, while STRUCTURE analysis varied (2 clusters for SNPs, 3 for partial microsatellites, 4 for full microsatellites).

Conclusions:

• Next-generation sequencing (NGS) typically yields far more SNPs than necessary for correlating with microsatellite parameter estimates.
• SNP data can effectively mirror diversity, FST, and PCA results obtained from microsatellites, particularly in small populations.
• These findings are relevant for endangered and threatened species, where small population sizes are common and genetic drift is a significant factor.