Sequence differences at orthologous microsatellites inflate estimates of human-chimpanzee differentiation

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Date
2014-11-18
Authors
Kwong, Michelle
Pemberton, Trevor J
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Abstract Background Microsatellites---contiguous arrays of 2–6 base-pair motifs---have formed the cornerstone of population-genetic studies for over two decades. Their genotype data typically takes the form of PCR fragment lengths obtained using locus-specific primer pairs to amplify the genomic region encompassing the microsatellite. Recently, we reported a dataset of 5,795 human and 84 chimpanzee individuals with genotypes at 246 human-derived autosomal microsatellites as a resource to facilitate interspecies comparisons. A major assumption underlying this dataset is that PCR amplicons at orthologous microsatellites are commensurable between species. Results We find this assumption to be frequently incorrect owing to discordance in microsatellite organization and variability, as well as nontrivial length imbalances caused by small species-specific indels in microsatellite flanking sequences. Converting PCR fragment lengths into the repeat numbers they represent at 138 microsatellites whose organization and variability was found to be highly similar in both species, we show that interspecies incommensurability among PCR amplicons can inflate F ST and D PS estimates by up to 10.6%. Separate investigations of determinants of microsatellite variability in humans and chimpanzees uncover similar patterns with mean and maximum numbers of repeats, as well as numbers and ranges of distinct alleles, all important factors in predicting heterozygosity. In contrast, across microsatellites, numbers of repeats were significantly smaller in chimpanzees than in humans, while numbers and ranges of distinct alleles were instead larger. Conclusions Our findings have fundamental implications for interspecies comparisons using microsatellites and offer new opportunities for more accurate comparisons of patterns of human and chimpanzee genetic variation in numerous areas of application.
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BMC Genomics. 2014 Nov 18;15(1):990