Comprehensive identification and analysis of human accelerated regulatory DNA.

It has long been hypothesized that changes in gene regulation have played an important role in human evolution, but regulatory DNA has been much more difficult to study compared with protein-coding regions. Recent large-scale studies have created genome-scale catalogs of DNase I hypersensitive sites (DHSs), which demark potentially functional regulatory DNA. To better define regulatory DNA that has been subject to human-specific adaptive evolution, we performed comprehensive evolutionary and population genetics analyses on over 18 million DHSs discovered in 130 cell types. We identified 524 DHSs that are conserved in nonhuman primates but accelerated in the human lineage (haDHS), and estimate that 70% of substitutions in haDHSs are attributable to positive selection. Through extensive computational and experimental analyses, we demonstrate that haDHSs are often active in brain or neuronal cell types; play an important role in regulating the expression of developmentally important genes, including many transcription factors such as SOX6, POU3F2, and HOX genes; and identify striking examples of adaptive regulatory evolution that may have contributed to human-specific phenotypes. More generally, our results reveal new insights into conserved and adaptive regulatory DNA in humans and refine the set of genomic substrates that distinguish humans from their closest living primate relatives.

A powerful and flexible statistical framework for testing hypotheses of allele-specific gene expression from RNA-seq data.

Variation in gene expression is thought to make a significant contribution to phenotypic diversity among individuals within populations. Although high-throughput cDNA sequencing offers a unique opportunity to delineate the genome-wide architecture of regulatory variation, new statistical methods need to be developed to capitalize on the wealth of information contained in RNA-seq data sets. To this end, we developed a powerful and flexible hierarchical Bayesian model that combines information across loci to allow both global and locus-specific inferences about allele-specific expression (ASE). We applied our methodology to a large RNA-seq data set obtained in a diploid hybrid of two diverse Saccharomyces cerevisiae strains, as well as to RNA-seq data from an individual human genome. Our statistical framework accurately quantifies levels of ASE with specified false-discovery rates, achieving high reproducibility between independent sequencing platforms. We pinpoint loci that show unusual and biologically interesting patterns of ASE, including allele-specific alternative splicing and transcription termination sites. Our methodology provides a rigorous, quantitative, and high-resolution tool for profiling ASE across whole genomes.

Clusters of adaptive evolution in the human genome.

Considerable work has been devoted to identifying regions of the human genome that have been subjected to recent positive selection. Although detailed follow-up studies of putatively selected regions are critical for a deeper understanding of human evolutionary history, such studies have received comparably less attention. Recently, we have shown that ALMS1 has been the target of recent positive selection acting on standing variation in Eurasian populations. Here, we describe a careful follow-up analysis of genetic variation across the ALMS1 region, which unexpectedly revealed a cluster of substrates of positive selection. Specifically, through the analysis of SNP data from the HapMap and Human Genome Diversity Project-Centre d'Etude du Polymorphisme Humain samples as well sequence data from the region, we find compelling evidence for three independent and distinct signals of recent positive selection across this 3 Mb region surrounding ALMS1. Moreover, we analyzed the HapMap data to identify other putative clusters of independent selective events and conservatively discovered 19 additional clusters of adaptive evolution. This work has important implications for the interpretation of genome-scans for positive selection in humans and more broadly contributes to a better understanding of how recent positive selection has shaped genetic variation across the human genome.

Signatures of positive selection apparent in a small sample of human exomes.

Exome sequences, which comprise all protein-coding regions, are promising data sets for studies of natural selection because they offer unbiased genome-wide estimates of polymorphism while focusing on the portions of the genome that are most likely to be functionally important. We examine genomic patterns of polymorphism within 10 diploid autosomal exomes of European and African descent. Using coalescent simulations, we show how polymorphism, site frequency spectra, and intercontinental divergence in these samples would be influenced by different modes of positive selection. We examine putatively selected loci from four previous genome-wide scans of SNP genotypes and demonstrate that these regions indeed show unusual population genetic patterns in the exome data. Using a series of conservative criteria based on exome polymorphism, we are able to fine-scale map signatures of selection, in many cases pinpointing a single candidate SNP. We also identify and evaluate novel candidate selection genes that show unusual patterns of polymorphism. We sequence a portion of one novel candidate locus, IVL, in 74 individuals from multiple continents and examine global genetic diversity. Thus, we confirm, narrow, and supplement existing catalogs of putative targets of selection, and show that exome data sets, which are likely to soon become common, will be powerful tools for identifying adaptive genetic variation.

Tracking footprints of artificial selection in the dog genome.

The size, shape, and behavior of the modern domesticated dog has been sculpted by artificial selection for at least 14,000 years. The genetic substrates of selective breeding, however, remain largely unknown. Here, we describe a genome-wide scan for selection in 275 dogs from 10 phenotypically diverse breeds that were genotyped for over 21,000 autosomal SNPs. We identified 155 genomic regions that possess strong signatures of recent selection and contain candidate genes for phenotypes that vary most conspicuously among breeds, including size, coat color and texture, behavior, skeletal morphology, and physiology. In addition, we demonstrate a significant association between HAS2 and skin wrinkling in the Shar-Pei, and provide evidence that regulatory evolution has played a prominent role in the phenotypic diversification of modern dog breeds. Our results provide a first-generation map of selection in the dog, illustrate how such maps can rapidly inform the genetic basis of canine phenotypic variation, and provide a framework for delineating the mechanistic basis of how artificial selection promotes rapid and pronounced phenotypic evolution.

Highly punctuated patterns of population structure on the X chromosome and implications for African evolutionary history.

It is well known that average levels of population structure are higher on the X chromosome compared to autosomes in humans. However, there have been surprisingly few analyses on the spatial distribution of population structure along the X chromosome. With publicly available data from the HapMap Project and Perlegen Sciences, we show a strikingly punctuated pattern of X chromosome population structure. Specifically, 87% of X-linked HapMap SNPs within the top 1% of F(ST) values cluster into five distinct loci. The largest of these regions spans 5.4 Mb and contains 66% of the most highly differentiated HapMap SNPs on the X chromosome. We demonstrate that the extreme clustering of highly differentiated SNPs on the X chromosome is not an artifact of ascertainment bias, nor is it specific to the populations genotyped in the HapMap Project. Rather, additional analyses and resequencing data suggest that these five regions have been substrates of recent and strong adaptive evolution. Finally, we discuss the implications that patterns of X-linked population structure have on the evolutionary history of African populations.

Population genomic analysis of ALMS1 in humans reveals a surprisingly complex evolutionary history.

Mutations in the human gene ALMS1 result in Alström Syndrome, which presents with early childhood obesity and insulin resistance leading to Type 2 diabetes. Previous genomewide scans for selection in the HapMap data based on linkage disequilibrium and population structure suggest that ALMS1 was subject to recent positive selection. Through a detailed population genomic analysis of existing genomewide data sets and new resequencing data obtained in geographically diverse populations, we find that the signature of selection at ALMS1 is considerably more complex than what would be expected for an idealized model of a selective sweep acting on a newly arisen advantageous mutation. Specifically, we observed three highly divergent and globally dispersed haplogroups, two of which carry a set of seven derived nonsynonymous single nucleotide polymorphisms that are nearly fixed in Asian populations. Our data suggest that the interaction of human demographic history and positive selection on standing variation in Eurasian populations approximately 15 thousand years ago parsimoniously explains the spectrum of extant ALMS1 variation. These results provide new insights into the evolutionary history of ALMS1 in humans and suggest that selective events identified in genomewide scans may be more complex than currently appreciated.

Gene-expression variation within and among human populations.

Understanding patterns of gene-expression variation within and among human populations will provide important insights into the molecular basis of phenotypic diversity and the interpretation of patterns of expression variation in disease. However, little is known about how gene-expression variation is apportioned within and among human populations. Here, we characterize patterns of natural gene-expression variation in 16 individuals of European and African ancestry. We find extensive variation in gene-expression levels and estimate that approximately 83% of genes are differentially expressed among individuals and that approximately 17% of genes are differentially expressed among populations. By decomposing total gene-expression variation into within- versus among-population components, we find that most expression variation is due to variation among individuals rather than among populations, which parallels observations of extant patterns of human genetic variation. Finally, we performed allele-specific quantitative polymerase chain reaction to demonstrate that cis-regulatory variation in the lymphocyte adaptor protein (SH2B adapter protein 3) contributes to differential expression between European and African samples. These results provide the first insight into how human population structure manifests itself in gene-expression levels and will help guide the search for regulatory quantitative trait loci.

Prevalence and predictors of BRCA1 and BRCA2 mutations in a population-based study of breast cancer in white and black American women ages 35 to 64 years.

Although well studied in families at high-risk, the roles of mutations in the BRCA1 and BRCA2 genes are poorly understood in breast cancers in the general population, particularly in Black women and in age groups outside of the very young. We examined the prevalence and predictors of BRCA1 and BRCA2 mutations in 1,628 women with breast cancer and 674 women without breast cancer who participated in a multicenter population-based case-control study of Black and White women, 35 to 64 years of age. Among cases, 2.4% and 2.3% carried deleterious mutations in BRCA1 and BRCA2, respectively. BRCA1 mutations were significantly more common in White (2.9%) versus Black (1.4%) cases and in Jewish (10.2%) versus non-Jewish (2.0%) cases; BRCA2 mutations were slightly more frequent in Black (2.6%) versus White (2.1%) cases. Numerous familial and demographic factors were significantly associated with BRCA1 and, to a lesser extent, BRCA2 carrier status, when examined individually. In models considering all predictors together, early onset ages in cases and in relatives, family history of ovarian cancer, and Jewish ancestry remained strongly and significantly predictive of BRCA1 carrier status, whereas BRCA2 predictors were fewer and more modest in magnitude. Both the combinations of predictors and effect sizes varied across racial/ethnic and age groups. These results provide first-time prevalence estimates for BRCA1/BRCA2 in breast cancer cases among understudied racial and age groups and show key predictors of mutation carrier status for both White and Black women and women of a wide age spectrum with breast cancer in the general population.

Genomic signatures of positive selection in humans and the limits of outlier approaches.

Identifying regions of the human genome that have been targets of positive selection will provide important insights into recent human evolutionary history and may facilitate the search for complex disease genes. However, the confounding effects of population demographic history and selection on patterns of genetic variation complicate inferences of selection when a small number of loci are studied. To this end, identifying outlier loci from empirical genome-wide distributions of genetic variation is a promising strategy to detect targets of selection. Here, we evaluate the power and efficiency of a simple outlier approach and describe a genome-wide scan for positive selection using a dense catalog of 1.58 million SNPs that were genotyped in three human populations. In total, we analyzed 14,589 genes, 385 of which possess patterns of genetic variation consistent with the hypothesis of positive selection. Furthermore, several extended genomic regions were found, spanning >500 kb, that contained multiple contiguous candidate selection genes. More generally, these data provide important practical insights into the limits of outlier approaches in genome-wide scans for selection, provide strong candidate selection genes to study in greater detail, and may have important implications for disease related research.

TRPV6 exhibits unusual patterns of polymorphism and divergence in worldwide populations.

A striking footprint of positive selection was recently identified on chromosome 7q34-35 that spans at least 115 kb and encompasses four known genes (KEL, TRPV5, TRPV6, EPHB6). The signature of selection was observed in only one of the two populations analyzed suggesting the action of geographically restricted selective pressures. However, as only two populations were analyzed, it remains unknown whether the signature of selection extends to additional populations. To address this issue and begin to dissect the evolutionary history of this region in more detail, we performed an in-depth population genetic analysis on TRPV6, which is a calcium-permeable ion channel thought to mediate the rate-limiting step of dietary calcium absorption. We demonstrate that the rate of TRPV6 protein evolution is significantly accelerated in the human lineage, but only for a haplotype defined by three non-synonymous SNPs (C157R, M378V and M681T) that are nearly fixed for the derived alleles in non-African populations. Interestingly, we found that these three non-synonymous SNPs have high posterior probabilities for being targets of positive selection and are therefore strong candidates for mediating the population-specific signatures of selection in this region. In addition, we resequenced the exons corresponding to the C157R, M378V and M681T polymorphisms in 90 geographically diverse individuals and characterized their global allele frequency distribution by genotyping them in 1064 individuals from 52 populations. These data strongly suggest that the TRPV6 haplotype defined by the derived alleles at C157R, M378V and M681T conferred a selective advantage that varied spatially, and perhaps temporally, during human history.

Facilitating genome navigation: survey sequencing and dense radiation-hybrid gene mapping.

Accurate and comprehensive sequence coverage for large genomes has been restricted to only a few species of specific interest. Lower sequence coverage (survey sequencing) of related species can yield a wealth of information about gene content and putative regulatory elements. But survey sequences lack long-range continuity and provide only a fragmented view of a genome. Here we show the usefulness of combining survey sequencing with dense radiation-hybrid (RH) maps for extracting maximum comparative genome information from model organisms. Based on results from the canine system, we propose that from now on all low-pass sequencing projects should be accompanied by a dense, gene-based RH map-construction effort to extract maximum information from the genome with a marginal extra cost.

Truncating BRCA1 mutations are uncommon in a cohort of hereditary prostate cancer families with evidence of linkage to 17q markers.

PURPOSE: A genome-wide scan of 175 hereditary prostate cancer families from the University of Michigan Prostate Cancer Genetics Project provided evidence of prostate cancer linkage to 17q markers near the BRCA1 gene. To examine the possibility that germ-line BRCA1 mutations were associated with hereditary prostate cancer, individuals from 93 families with evidence of linkage to chromosome 17q were screened for germ-line BRCA1 mutations. EXPERIMENTAL DESIGN: One individual from each of the 93 families, the majority with three or more cases of prostate cancer, were screened for BRCA1 mutations with denaturing high-performance liquid chromatography (HPLC). Fragments exhibiting denaturing HPLC variant patterns were additionally analyzed by direct sequencing. RESULTS: Sixty-five of the individuals selected for sequencing from 65 unrelated families were determined to have wild-type BRCA1 sequence by denaturing HPLC. One individual from a family with both prostate and ovarian cancer was found to have a truncating BRCA1 mutation (3829delT). An additional 27 germ-line variants were identified, including 15 missense variants. CONCLUSIONS: These sequencing results suggest that BRCA1 truncating mutations do not account for the linkage evidence on chromosome 17 observed in University of Michigan Prostate Cancer Genetics Project families. A recently completed combined genome scan has also detected linkage to 17q22, and studies are ongoing to identify the relevant prostate cancer susceptibility gene in this region.