Exponential distance statistics to detect the effects of population subdivision.

Statistical tests are needed to determine whether spatial structure has had a significant effect on the genetic differentiation of subpopulations. Here we introduce a new family of statistics based on a sum of an exponential function of the distances between individuals, which can be used with any genetic distance (e.g., nucleotide differences, number of nonshared alleles, or separation on a phylogenetic tree). The power of the tests to detect genetic differentiation in Wright-Fisher island models and stepping stone models was calculated for various sample sizes, rates of migration and mutation, and definitions of spatial neighborhoods. We found that our new test was in some cases more powerful than the Ks* statistic of Hudson et al. (Mol. Biol. Evol. 9, 138-151, 1992), but in all cases was slightly less powerful than both a traditional chi2 test without lumping of rare haplotypes and the S(nn) test of Hudson (Genetics 155, 2011-2014, 2000). However, when we applied our new tests to three data sets, we found in some cases highly significant results that were missed by the other tests.

Dynamics of microsatellite divergence under stepwise mutation and proportional slippage/point mutation models.

Recently Kruglyak, Durrett, Schug, and Aquadro showed that microsatellite equilibrium distributions can result from a balance between polymerase slippage and point mutations. Here, we introduce an elaboration of their model that keeps track of all parts of a perfect repeat and a simplification that ignores point mutations. We develop a detailed mathematical theory for these models that exhibits properties of microsatellite distributions, such as positive skewness of allele lengths, that are consistent with data but are inconsistent with the predictions of the stepwise mutation model. We use our theoretical results to analyze the successes and failures of the genetic distances (delta(mu))(2) and D(SW) when used to date four divergences: African vs. non-African human populations, humans vs. chimpanzees, Drosophila melanogaster vs. D. simulans, and sheep vs. cattle. The influence of point mutations explains some of the problems with the last two examples, as does the fact that these genetic distances have large stochastic variance. However, we find that these two features are not enough to explain the problems of dating the human-chimpanzee split. One possible explanation of this phenomenon is that long microsatellites have a mutational bias that favors contractions over expansions.

Selective mapping: a strategy for optimizing the construction of high-density linkage maps.

Historically, linkage mapping populations have consisted of large, randomly selected samples of progeny from a given pedigree or cell lines from a panel of radiation hybrids. We demonstrate that, to construct a map with high genome-wide marker density, it is neither necessary nor desirable to genotype all markers in every individual of a large mapping population. Instead, a reduced sample of individuals bearing complementary recombinational or radiation-induced breakpoints may be selected for genotyping subsequent markers from a large, but sparsely genotyped, mapping population. Choosing such a sample can be reduced to a discrete stochastic optimization problem for which the goal is a sample with breakpoints spaced evenly throughout the genome. We have developed several different methods for selecting such samples and have evaluated their performance on simulated and actual mapping populations, including the Lister and Dean Arabidopsis thaliana recombinant inbred population and the GeneBridge 4 human radiation hybrid panel. Our methods quickly and consistently find much-reduced samples with map resolution approaching that of the larger populations from which they are derived. This approach, which we have termed selective mapping, can facilitate the production of high-quality, high-density genome-wide linkage maps.

Quantification of homoplasy for nucleotide transitions and transversions and a reexamination of assumptions in weighted phylogenetic analysis.

Nucleotide transitions are frequently down-weighted relative to transversions in phylogenetic analysis. This is based on the assumption that transitions, by virtue of their greater evolutionary rate, exhibit relatively more homoplasy and are therefore less reliable phylogenetic characters. Relative amounts of homoplastic and consistent transition and transversion changes in mitochondrial protein coding genes were determined from character-state reconstructions on a highly corroborated phylogeny of mammals. We found that although homoplasy was related to evolutionary rates and was greater for transitions, the absolute number of consistent transitions greatly exceeded the number of consistent transversions. Consequently, transitions provided substantially more useful phylogenetic information than transversions. These results suggest that down-weighting transitions may be unwarranted in many cases. This conclusion was supported by the fact that a range of transition: transversion weighting schemes applied to various mitochondrial genes and genomic partitions rarely provided improvement in phylogenetic estimates relative to equal weighting, and in some cases weighting transitions more heavily than transversions was most effective.

Equilibrium distributions of microsatellite repeat length resulting from a balance between slippage events and point mutations.

We describe and test a Markov chain model of microsatellite evolution that can explain the different distributions of microsatellite lengths across different organisms and repeat motifs. Two key features of this model are the dependence of mutation rates on microsatellite length and a mutation process that includes both strand slippage and point mutation events. We compute the stationary distribution of allele lengths under this model and use it to fit DNA data for di-, tri-, and tetranucleotide repeats in humans, mice, fruit flies, and yeast. The best fit results lead to slippage rate estimates that are highest in mice, followed by humans, then yeast, and then fruit flies. Within each organism, the estimates are highest in di-, then tri-, and then tetranucleotide repeats. Our estimates are consistent with experimentally determined mutation rates from other studies. The results suggest that the different length distributions among organisms and repeat motifs can be explained by a simple difference in slippage rates and that selective constraints on length need not be imposed.