Multi-locus inference of population structure: a comparison between single nucleotide polymorphisms and microsatellites.

Although growing numbers of single nucleotide polymorphisms (SNPs) and microsatellites (short tandem repeat polymorphisms or STRPs) are used to infer population structure, their relative properties in this context remain poorly understood. SNPs and STRPs mutate differently, suggesting multi-locus genotypes at these loci might differ in ability to detect population structure. Here, we use coalescent simulations to measure the power of sets of SNPs and STRPs to identify population structure. To maximize the applicability of our results to empirical studies, we focus on the popular STRUCTURE analysis and evaluate the role of several biological and practical factors in the detection of population structure. We find that: (1) fewer unlinked STRPs than SNPs are needed to detect structure at recent divergence times <0.3 N(e) generations; (2) accurate estimation of the number of populations requires many fewer STRPs than SNPs; (3) for both marker types, declines in power due to modest gene flow (N(e)m=1.0) are largely negated by increasing marker number; (4) variation in the STRP mutational model affects power modestly; (5) SNP haplotypes (θ=1, no recombination) provide power comparable with STRP loci (θ=10); (6) ascertainment schemes that select highly variable STRP or SNP loci increase power to detect structure, though ascertained data may not be suitable to other inference; and (7) when samples are drawn from an admixed population and one of its parent populations, the reduction in power to detect two populations is greater for STRPs than SNPs. These results should assist the design of multi-locus studies to detect population structure in nature.

Rates of deleterious mutation and the evolution of sex in Caenorhabditis.

A variety of models propose that the accumulation of deleterious mutations plays an important role in the evolution of breeding systems. These models make predictions regarding the relative rates of protein evolution and deleterious mutation in taxa with contrasting modes of reproduction. Here we compare available coding sequences from one obligately outcrossing and two primarily selfing species of Caenorhabditis to explore the potential for mutational models to explain the evolution of breeding system in this clade. If deleterious mutations interact synergistically, the mutational deterministic hypothesis predicts that a high genomic deleterious mutation rate (U) will offset the reproductive disadvantage of outcrossing relative to asexual or selfing reproduction. Therefore, C. elegans and C. briggsae (both largely selfing) should both exhibit lower rates of deleterious mutation than the obligately outcrossing relative C. remanei. Using a comparative approach, we estimate U to be equivalent (and < 1) among all three related species. Stochastic mutational models, Muller's ratchet and Hill-Robertson interference, are expected to cause reductions in the effective population size in species that rarely outcross, thereby allowing deleterious mutations to accumulate at an elevated rate. We find only limited support for more rapid molecular evolution in selfing lineages. Overall, our analyses indicate that the evolution of breeding system in this group is unlikely to be explained solely by available mutational models.

Failure of the ILD to determine data combinability for slow loris phylogeny.

Tests for incongruence as an indicator of among-data partition conflict have played an important role in conditional data combination. When such tests reveal significant incongruence, this has been interpreted as a rationale for not combining data into a single phylogenetic analysis. In this study of lorisiform phylogeny, we use the incongruence length difference (ILD) test to assess conflict among three independent data sets. A large morphological data set and two unlinked molecular data sets--the mitochondrial cytochrome b gene and the nuclear interphotoreceptor retinoid binding protein (exon 1)--are analyzed with various optimality criteria and weighting mechanisms to determine the phylogenetic relationships among slow lorises (Primates, Loridae). When analyzed separately, the morphological data show impressive statistical support for a monophyletic Loridae. Both molecular data sets resolve the Loridae as paraphyletic, though with different branching orders depending on the optimality criterion or character weighting used. When the three data partitions are analyzed in various combinations, an inverse relationship between congruence and phylogenetic accuracy is observed. Nearly all combined analyses that recover monophyly indicate strong data partition incongruence (P = 0.00005 in the most extreme case), whereas all analyses that recover paraphyly indicate lack of significant incongruence. Numerous lines of evidence verify that monophyly is the accurate phylogenetic result. Therefore, this study contributes to a growing body of information affirming that measures of incongruence should not be used as indicators of data set combinability.

Microsatellite variation and recombination rate in the human genome.

Background (purifying) selection on deleterious mutations is expected to remove linked neutral mutations from a population, resulting in a positive correlation between recombination rate and levels of neutral genetic variation, even for markers with high mutation rates. We tested this prediction of the background selection model by comparing recombination rate and levels of microsatellite polymorphism in humans. Published data for 28 unrelated Europeans were used to estimate microsatellite polymorphism (number of alleles, heterozygosity, and variance in allele size) for loci throughout the genome. Recombination rates were estimated from comparisons of genetic and physical maps. First, we analyzed 61 loci from chromosome 22, using the complete sequence of this chromosome to provide exact physical locations. These 61 microsatellites showed no correlation between levels of variation and recombination rate. We then used radiation-hybrid and cytogenetic maps to calculate recombination rates throughout the genome. Recombination rates varied by more than one order of magnitude, and most chromosomes showed significant suppression of recombination near the centromere. Genome-wide analyses provided no evidence for a strong positive correlation between recombination rate and polymorphism, although analyses of loci with at least 20 repeats suggested a weak positive correlation. Comparisons of microsatellites in lowest-recombination and highest-recombination regions also revealed no difference in levels of polymorphism. Together, these results indicate that background selection is not a major determinant of microsatellite variation in humans.

New body mass estimates for Omomys carteri, a middle Eocene primate from North America.

We report new body mass estimates for the North American Eocene primate Omomys carteri. These estimates are based on postcranial measurements and a variety of analytical methods, including bivariate regression, multiple regression, and principal components analysis (PCA). All body mass estimation equations show high coefficients of determination (R2), and some equations exhibit low prediction errors in accuracy tests involving extant species of body size similar to O. carteri. Equations derived from PCA-summarized data and multiple regression generally perform better than those based on single variables. The consensus of estimates and their statistics suggests a body mass range of 170-290 g. This range is similar to previous estimates for this species based on first molar area (Gingerich, J Hum Evol 10:345-374, 1981; Conroy, Int J Primatol 8:115-137, 1987).