Male-biased Mutation Rates and the Overestimation of Extrapair Paternity: Problem, Solution, and Illustration Using Thick-Billed Murres (Uria lomvia, Alcidae)

The widespread utility of hypervariable loci in genetic studies derives from the high mutation rate, and thus the high polymorphism, of these loci. Recent evidence suggests that mutation rates can be extremely high and may be male biased (occurring in the male germ-line). These two factors combined...

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Bibliographic Details
Published in:Journal of Heredity
Main Authors: Ibarguchi, G., Gissing, G. J., Gaston, A. J., Boag, P. T., Friesen, V. L.
Format: Text
Language:English
Published: Oxford University Press 2004
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Online Access:http://jhered.oxfordjournals.org/cgi/content/short/95/3/209
https://doi.org/10.1093/jhered/esh029
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Summary:The widespread utility of hypervariable loci in genetic studies derives from the high mutation rate, and thus the high polymorphism, of these loci. Recent evidence suggests that mutation rates can be extremely high and may be male biased (occurring in the male germ-line). These two factors combined may result in erroneous overestimates of extrapair paternity, since legitimate offspring with novel alleles will have more mismatches with respect to the biological father than the biological mother. As mutations are male driven, increasing the number of hypervariable loci screened may simply increase the number of mismatches between fathers and their legitimate offspring. Here we describe a simple statistic, the probability of resemblance ( P R ), to distinguish between mismatches due to parental misassignment versus mutation in either sex or null alleles. We apply this method to parentage data on thick-billed murres ( Uria lomvia ), and demonstrate that, without considering either mutations or male-biased mutation rates, cases of extrapair paternity (7% in this study) would be grossly overestimated (14.5%–22%). The probability of resemblance can be utilized in parentage studies of any sexually reproducing species when allele or haplotype frequency data are available for putative parents and offspring. We suggest calculating this probability to correctly categorize legitimate offspring when mutations and null alleles may cause mismatches.