Genetic studies of killer whales ( Orcinus orca ) historically relied on markers from mitochondrial DNA or microsatellites, which are cost‐effective, but the difficulties in cross‐laboratory standardization have limited global data integration. Transitioning to whole genome sequencing (WGS) has advanced our understanding of killer whale population structure and demographic histories; however, the costs of WGS remain a limiting factor for studying many individuals. Targeted Single Nucleotide Polymorphism (SNP) genotyping provides a cost‐effective, reproducible alternative, yet it can be susceptible to ascertainment bias whereby markers discovered in a limited set of reference populations may fail to capture genetic diversity in unrepresented populations. Here, we evaluate ascertainment bias in a custom RNA bait enrichment kit targeting 1346 SNPs, originally identified in a dataset of North Pacific, Icelandic, and Southern Ocean killer whales. Specifically, we compare the relationships among 25 killer whales representing the species' global range inferred from 225,281 unlinked genome‐wide SNPs to the same relationships inferred from the 1346 SNPs targeted by the capture baits, with both sets subsampled from WGS data. Comparing principal component analyses (PCAs), the targeted subset recapitulated broad‐scale global population structure and clustering patterns consistent with the larger WGS dataset. We found a high correlation between the targeted bait PCA and the WGS PCA ( r = 0.961). However, the observed value fell below expectations based on random sampling ( p < 0.01). This deviation was likely driven by samples belonging to lineages not included in the original SNP discovery panel, suggesting a small level of ascertainment bias. Consequently, some unique genetic variation in these excluded lineages remains unrepresented, specifically impacting inference of the relationships to and among lower‐latitude populations. While this targeted enrichment panel is a robust tool for elucidating major evolutionary differentiation and facilitating cross‐laboratory comparisons, it is less reliable for detecting fine‐scale structure in unrepresented, genetically divergent populations.
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Baumgartner et al. (2026) studied this question.
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