Meiotic recombination is a fundamental cellular mechanism in sexually reproducing organisms and its different forms, crossing over and gene conversion both play an important role in shaping genetic variation in populations. Here, we describe a coalescent-based full-likelihood Markov chain Monte Carlo (MCMC) method for jointly estimating the crossing-over, gene-conversion, and mean tract length parameters from population genomic data under a Bayesian framework. Although computationally more expensive than methods that use approximate likelihoods, the relative efficiency of our method is expected to be optimal in theory. Furthermore, it is also possible to obtain a posterior sample of genealogies for the data using this method. We first check the performance of the new method on simulated data and verify its correctness. We also extend the method for inference under models with variable gene-conversion and crossing-over rates and demonstrate its ability to identify recombination hotspots. Then, we apply the method to two empirical data sets that were sequenced in the telomeric regions of the X chromosome of Drosophila melanogaster. Our results indicate that gene conversion occurs more frequently than crossing over in the su-w and su-s gene sequences while the local rates of crossing over as inferred by our program are not low. The mean tract lengths for gene-conversion events are estimated to be ∼70 bp and 430 bp, respectively, for these data sets. Finally, we discuss ideas and optimizations for reducing the execution time of our algorithm.

The prevalence of common chronic non-communicable diseases (CNCDs) far overshadows the prevalence of both monogenic and infectious diseases combined. All CNCDs, also called complex genetic diseases, have a heritable genetic component that can be used for pre-symptomatic risk assessment. Common single nucleotide polymorphisms (SNPs) that tag risk haplotypes across the genome currently account for a non-trivial portion of the germ-line genetic risk and we will likely continue to identify the remaining missing heritability in the form of rare variants, copy number variants and epigenetic modifications. Here, we describe a novel measure for calculating the lifetime risk of a disease, called the genetic composite index (GCI), and demonstrate its predictive value as a clinical classifier. The GCI only considers summary statistics of the effects of genetic variation and hence does not require the results of large-scale studies simultaneously assessing multiple risk factors. Combining GCI scores with environmental risk information provides an additional tool for clinical decision-making. The GCI can be populated with heritable risk information of any type, and thus represents a framework for CNCD pre-symptomatic risk assessment that can be populated as additional risk information is identified through next-generation technologies.

Morphological diversity within closely related species is an essential aspect of evolution and adaptation. Mutations in the Melanocortin 1 receptor (Mc1r) gene contribute to pigmentary diversity in natural populations of fish, birds, and many mammals. However, melanism in the gray wolf, Canis lupus, is caused by a different melanocortin pathway component, the K locus, that encodes a beta-defensin protein that acts as an alternative ligand for Mc1r. We show that the melanistic K locus mutation in North American wolves derives from past hybridization with domestic dogs, has risen to high frequency in forested habitats, and exhibits a molecular signature of positive selection. The same mutation also causes melanism in the coyote, Canis latrans, and in Italian gray wolves, and hence our results demonstrate how traits selected in domesticated species can influence the morphological diversity of their wild relatives.

The domestic dog exhibits greater diversity in body size than any other terrestrial vertebrate. We used a strategy that exploits the breed structure of dogs to investigate the genetic basis of size. First, through a genome-wide scan, we identified a major quantitative trait locus (QTL) on chromosome 15 influencing size variation within a single breed. Second, we examined genetic variation in the 15-megabase interval surrounding the QTL in small and giant breeds and found marked evidence for a selective sweep spanning a single gene (IGF1), encoding insulin-like growth factor 1. A single IGF1 single-nucleotide polymorphism haplotype is common to all small breeds and nearly absent from giant breeds, suggesting that the same causal sequence variant is a major contributor to body size in all small dogs.

Reduced birth weight and slow neonatal growth are risks correlated with the development of common diseases in adulthood. The Human Growth Hormone/Chorionic Somatomammotropin (hGH/CSH) gene cluster (48 kb) at 17q22-24, consisting of one pituitary-expressed postnatal (GH1) and four placental genes (GH2, CSH1, CSH2 and CSHL1) may contribute to common variation in intrauterine and infant growth, and also to the regulation of feto-maternal and adult glucose metabolism. In contrast to GH1, there are limited genetic data on the hGH/CSH genes expressed in utero. We report the first survey of sequence variation encompassing all five hGH/CSH genes. Resequencing identified 113 SNPs/indels (ss86217675-ss86217787 in dbSNP) including 66 novel variants, and revealed remarkable differences in diversity patterns among the homologous duplicated genes as well as between the study populations of European (Estonians), Asian (Han Chinese) and African (Mandenkalu) ancestries. A dominant feature of the hGH/CSH region is hyperactive gene conversion, with the rate exceeding tens to hundreds of times the rate of reciprocal crossing-over and resulting in near absence of linkage disequilibrium. The initiation of gene conversion seems to be uniformly distributed because the data do not predict any recombination hotspots. Signatures of different selective constraints acting on each gene indicate functional specification of the hGH/CSH genes. Most strikingly, the GH2 coding for placental growth hormone shows strong intercontinental diversification (Fst= 0.41-0.91; p<10−6) indicative of balancing selection, whereas the flanking CSH1 exhibits low population differentiation (Fst=0.03-0.09), low diversity (non-Africans π=8-9 × 10−5, Africans π= 8.2 × 10−4), and one dominant haplotype worldwide, consistent with purifying selection. The results imply that the success of an association study targeted to duplicated genes may be enhanced by prior resequencing of the study population in order to determine polymorphism distribution and relevant tag-SNPs.

We resequenced 876 short fragments in a sample of 96 individuals of Arabidopsis thaliana that included stock center accessions as well as a hierarchical sample from natural populations. Although A. thaliana is a selfing weed, the pattern of polymorphism in general agrees with what is expected for a widely distributed, sexually reproducing species. Linkage disequilibrium decays rapidly, within 50 kb. Variation is shared worldwide, although population structure and isolation by distance are evident. The data fail to fit standard neutral models in several ways. There is a genome-wide excess of rare alleles, at least partially due to selection. There is too much variation between genomic regions in the level of polymorphism. The local level of polymorphism is negatively correlated with gene density and positively correlated with segmental duplications. Because the data do not fit theoretical null distributions, attempts to infer natural selection from polymorphism data will require genome-wide surveys of polymorphism in order to identify anomalous regions. Despite this, our data support the utility of A. thaliana as a model for evolutionary functional genomics.

A systematic global survey of genomic DNA sequence polymorphism in Arabidopsis thaliana reveals that standard genetic tests for selection do not apply to this species but supports its status as a model organism.