Microsatellite evolution inferred from human-chimpanzee genomic sequence alignments - PubMed (original) (raw)
Microsatellite evolution inferred from human-chimpanzee genomic sequence alignments
Matthew T Webster et al. Proc Natl Acad Sci U S A. 2002.
Abstract
Most studies of microsatellite evolution utilize long, highly mutable loci, which are unrepresentative of the majority of simple repeats in the human genome. Here we use an unbiased sample of 2,467 microsatellite loci derived from alignments of 5.1 Mb of genomic sequence from human and chimpanzee to investigate the mutation process of tandemly repetitive DNA. The results indicate that the process of microsatellite evolution is highly heterogeneous, exhibiting differences between loci of different lengths and motif sizes and between species. We find a highly significant tendency for human dinucleotide repeats to be longer than their orthologues in chimpanzees, whereas the opposite trend is observed in mononucleotide repeat arrays. Furthermore, the rate of divergence between orthologues is significantly higher at longer loci, which also show significantly greater mutability per repeat number. These observations have important consequences for understanding the molecular mechanisms of microsatellite mutation and for the development of improved measures of genetic distance.
Figures
Figure 1
Effect of allele length on mutability per generation measured per locus (Upper) and per repeat unit (Lower) for microsatellites of repeat motif sizes 1–4 bp. Loci with allele lengths on the boundary between classes were placed in the higher category.
Figure 2
Results of simulations of microsatellite evolution in two species with constant mutation rates independent of allele length. Alleles were sampled from the final distribution on the basis of length in one species and a correction for unobserved reverse mutations was performed. Average mutability is plotted relative to its expected value given the simulated mutation rate. Both high (0.05 per generation) and low (0.0005 per generation) mutation rates were simulated, leading to expected average squared differences of 1 and 100, respectively.
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