Summary The ability to measure human aging from molecular profiles has practical implications in many fields, including disease prevention and treatment, forensics, and extension of life. Although chronological age has been linked to changes in DNA methylation, the methylome has not yet been used to measure and compare human aging rates. Here, we build a quantitative model of aging using measurements at more than 450,000 CpG markers from the whole blood of 656 human individuals, aged 19 to 101. This model measures the rate at which an individual’s methylome ages, which we show is impacted by gender and genetic variants. Furthermore, we show that differences in aging rates help explain epigenetic drift and are reflected in the transcriptome. Our model highlights specific components of the aging process and provides a quantitative read-out for studying the role of methylation in age-related disease.

We describe the Phase II HapMap, which characterizes over 3.1 million human single nucleotide polymorphisms (SNPs) genotyped in 270 individuals from four geographically diverse populations and includes 25-35% of common SNP variation in the populations surveyed. The map is estimated to capture untyped common variation with an average maximum r2 of between 0.9 and 0.96 depending on population. We demonstrate that the current generation of commercial genome-wide genotyping products captures common Phase II SNPs with an average maximum r2 of up to 0.8 in African and up to 0.95 in non-African populations, and that potential gains in power in association studies can be obtained through imputation. These data also reveal novel aspects of the structure of linkage disequilibrium. We show that 10-30% of pairs of individuals within a population share at least one region of extended genetic identity arising from recent ancestry and that up to 1% of all common variants are untaggable, primarily because they lie within recombination hotspots. We show that recombination rates vary systematically around genes and between genes of different function. Finally, we demonstrate increased differentiation at non-synonymous, compared to synonymous, SNPs, resulting from systematic differences in the strength or efficacy of natural selection between populations.

With the advent of dense maps of human genetic variation, it is now possible to detect positive natural selection across the human genome. Here we report an analysis of over 3 million polymorphisms from the International HapMap Project Phase 2 (HapMap2)1. We used 'longrange haplotype' methods, which were developed to identify alleles segregating in a population that have undergone recent selection2, and we also developed new methods that are based on cross-population comparisons to discover alleles that have swept to near-fixation within a population. The analysis reveals more than 300 strong candidate regions. Focusing on the strongest 22 regions, we develop a heuristic for scrutinizing these regions to identify candidate targets of selection. In a complementary analysis, we identify 26 non-synonymous, coding, single nucleotide polymorphisms showing regional evidence of positive selection. Examination of these candidates highlights three cases in which two genes in a common biological process have apparently undergone positive selection in the same population: LARGE and DMD, both related to infection by the Lassa virus3, in West Africa; SLC24A5 and SLC45A2, both involved in skin pigmentation4,5, in Europe; and EDAR and EDA2R, both involved in development of hair follicles6, in Asia. ©2007 Nature Publishing GroupCorrespondence and requests for materials should be addressed to P.C.S. (pardis@broad.mit.edu).. * These authors contributed equally to this work. † Lists of participants and affiliations appear at the end of the paper. Author Contributions P.C.S., P.V., B.F. and E.S.L. initiated the project. P.V., B.F. and P.C.S. developed key software. P.C.S., P.V., B.F., S.F.S., J.L., E.H., C.C., X.X., E.B., S.A.McC. and R.G. performed analysis. P.C.S., E.B. and E.H. performed experiments. P.C.S., E.S.L., P.V. and S.F.S. wrote the manuscript.Full Methods and any associated references are available in the online version of the paper at www.nature.com/nature.Supplementary Information is linked to the online version of the paper at www.nature.com/nature.Reprints and permissions information is available at www.nature.com/reprints. An increasing amount of information about genetic variation, together with new analytical methods, is making it possible to explore the recent evolutionary history of the human population. The first phase of the International Haplotype Map, including ~1 million single nucleotide polymorphisms (SNPs)7, allowed preliminary examination of natural selection in humans. Now, with the publication of the Phase 2 map (HapMap2)1 in a companion paper, over 3 million SNPs have been genotyped in 420 chromosomes from three continents (120 European (CEU), 120 African (YRI) and 180 Asian from Japan and China (JPT + CHB)). Europe PMC Funders GroupIn our analysis of HapMap2, we first implemented two widely used tests that detect recent positive selection by finding common alleles carried on unusually long haplotypes2. The two, the Long-Range Haplotype (LRH)8 and the integrated Haplotype Score (iHS)9 tests...

A haplotype map of the human genomeThe International HapMap Consortium* Inherited genetic variation has a critical but as yet largely uncharacterized role in human disease. Here we report a public database of common variation in the human genome: more than one million single nucleotide polymorphisms (SNPs) for which accurate and complete genotypes have been obtained in 269 DNA samples from four populations, including ten 500-kilobase regions in which essentially all information about common DNA variation has been extracted. These data document the generality of recombination hotspots, a block-like structure of linkage disequilibrium and low haplotype diversity, leading to substantial correlations of SNPs with many of their neighbours. We show how the HapMap resource can guide the design and analysis of genetic association studies, shed light on structural variation and recombination, and identify loci that may have been subject to natural selection during human evolution.

Our understanding of the development and maintenance of tissues has been greatly aided by large-scale gene expression analysis. However, tissues are invariably complex, and expression analysis of a tissue confounds the true expression patterns of its constituent cell types. Here we describe a novel strategy to access such complex samples. Single-cell RNA-seq expression profiles were generated, and clustered to form a two-dimensional cell map onto which expression data were projected. The resulting cell map integrates three levels of organization: the whole population of cells, the functionally distinct subpopulations it contains, and the single cells themselves—all without need for known markers to classify cell types. The feasibility of the strategy was demonstrated by analyzing the transcriptomes of 85 single cells of two distinct types. We believe this strategy will enable the unbiased discovery and analysis of naturally occurring cell types during development, adult physiology, and disease.

Sequence variation in human genes is largely confined to single-nucleotide polymorphisms (SNPs) and is valuable in tests of association with common diseases and pharmacogenetic traits. We performed a systematic and comprehensive survey of molecular variation to assess the nature, pattern and frequency of SNPs in 75 candidate human genes for blood-pressure homeostasis and hypertension. We assayed 28 Mb (190 kb in 148 alleles) of genomic sequence, comprising the 5' and 3' untranslated regions (UTRs), introns and coding sequence of these genes, for sequence differences in individuals of African and Northern European descent using high-density variant detection arrays (VDAs). We identified 874 candidate human SNPs, of which 22% were confirmed by DNA sequencing to reveal a discordancy rate of 21% for VDA detection. The SNPs detected have an average minor allele frequency of 11%, and 387 are within the coding sequence (cSNPs). Of all cSNPs, 54% lead to a predicted change in the protein sequence, implying a high level of human protein diversity. These protein-altering SNPs are 38% of the total number of such SNPs expected, are more likely to be population-specific and are rarer in the human population, directly demonstrating the effects of natural selection on human genes. Overall, the degree of nucleotide polymorphism across these human genes, and orthologous great ape sequences, is highly variable and is correlated with the effects of functional conservation on gene sequences.

We have developed a high-throughput method for analyzing the methylation status of hundreds of preselected genes simultaneously and have applied it to the discovery of methylation signatures that distinguish normal from cancer tissue samples. Through an adaptation of the GoldenGate genotyping assay implemented on a BeadArray platform, the methylation state of 1536 specific CpG sites in 371 genes (one to nine CpG sites per gene) was measured in a single reaction by multiplexed genotyping of 200 ng of bisulfite-treated genomic DNA. The assay was used to obtain a quantitative measure of the methylation level at each CpG site. After validating the assay in cell lines and normal tissues, we analyzed a panel of lung cancer biopsy samples (N = 22) and identified a panel of methylation markers that distinguished lung adenocarcinomas from normal lung tissues with high specificity. These markers were validated in a second sample set (N = 24). These results demonstrate the effectiveness of the method for reliably profiling many CpG sites in parallel for the discovery of informative methylation markers. The technology should prove useful for DNA methylation analyses in large populations, with potential application to the classification and diagnosis of a broad range of cancers and other diseases.

The human genome is thought to harbor 50,000 to 100,000 genes, of which about half have been sampled to date in the form of expressed sequence tags. An international consortium was organized to develop and map gene-based sequence tagged site markers on a set of two radiation hybrid panels and a yeast artificial chromosome library. More than 16,000 human genes have been mapped relative to a framework map that contains about 1000 polymorphic genetic markers. The gene map unifies the existing genetic and physical maps with the nucleotide and protein sequence databases in a fashion that should speed the discovery of genes underlying inherited human disease. The integrated resource is available through a site on the World Wide Web at http://www.ncbi.nlm.nih.gov/SCIENCE96/.