Ascertainment Bias in Spatially Structured Populations: A Case Study in the Eastern Fence Lizard

Despite increased interest in applying single nucleotide polymorphism (SNP) data to questions in natural systems, one unresolved issue is to what extent the ascertainment bias induced during the SNP discovery phase will impact available analysis methods. Although most studies addressing ascertainmen...

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Bibliographic Details
Published in:The Journal of heredity 2007-07, Vol.98 (4), p.331-336
Main Authors: Rosenblum, Erica Bree, Novembre, John
Format: Article
Language:English
Subjects:
Animals
Bias
Case studies
Gene Flow - physiology
Gene Frequency
Genetic diversity
Genetics, Population
Lacertilia
Lizards - genetics
Polymorphism
Polymorphism, Single Nucleotide
Reptiles & amphibians
Research methodology
Sceloporus undulatus
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Summary:Despite increased interest in applying single nucleotide polymorphism (SNP) data to questions in natural systems, one unresolved issue is to what extent the ascertainment bias induced during the SNP discovery phase will impact available analysis methods. Although most studies addressing ascertainment bias have focused on human populations, it is not clear whether existing methods will work when applied to other species with more complex demographic histories and more significant levels of population structure. Here we present findings from an empirical approach to exploring the effect of population structure on issues of ascertainment bias in the Eastern Fence Lizard, Sceloporus undulatus. We find that frequency spectra and summary statistics were highly sensitive to SNP discovery strategy, necessitating careful selection of the initial ascertainment panel. Randomly selected ascertainment panels performed equally well as ascertainment panels chosen to jointly sample geographic, phenotypic, and genetic diversity. Geographically restricted panels resulted in larger biases. Additionally, we found existing ascertainment bias correction methods, which were not developed for geographically structured data sets, were largely effective at reducing the impact of ascertainment bias. Because bias correction methods performed well even when underlying assumptions were violated, our results suggest tools are currently available to analyze SNP data in structured populations.
ISSN:0022-1503
1465-7333
DOI:10.1093/jhered/esm031