For a population with a large effective population size and a goal to detect subtle differentiation, which strategy is most powerful?

• A. SNPs with many loci
• B. Microsatellites with few loci
• C. SNPs with few loci
• D. Microsatellites with many loci

Answer: (A)

The key idea is that detecting subtle population differences in a large effective population size requires broad genome-wide sampling to capture small shifts in allele frequencies. When populations are large, drift moves allele frequencies only a little, so no single locus stands out as informative. Pooling information across many independent loci adds up the signal, making it possible to detect faint structure that a few markers would miss. SNPs are ideal for this because they are abundant across the genome and inexpensive to genotype at thousands or millions of sites, giving you dense, uniform coverage. Their low mutation rate also reduces problems like homoplasy, which can blur true relationships at highly variable markers. In contrast, using many loci that are microsatellites would be powerful only if you could sample a very large number; with few loci, the overall power remains limited and practical issues like allelic scoring errors and higher mutation rates can muddle the signal. So, combining many SNP loci provides the strongest, most reliable detection of subtle differentiation in large populations.