Comparing strategies to fine-map the association of common SNPs at chromosome 9p21 with type 2 diabetes and myocardial infarction

Noncoding variants at human chromosome 9p21 near CDKN2A and CDKN2B are associated with type 2 diabetes, myocardial infarction, aneurysm, vertical cup disc ratio and at least five cancers. Here we compare approaches to more comprehensively assess genetic variation in the region. We carried out targeted sequencing at high coverage in 47 individuals and compared the results to pilot data from the 1000 Genomes Project. We imputed variants into type 2 diabetes and myocardial infarction cohorts directly from targeted sequencing, from a genotyped reference panel derived from sequencing and from 1000 Genomes Project low-coverage data. Polymorphisms with frequency >5% were captured well by all strategies. Imputation of intermediate-frequency polymorphisms required a higher density of tag SNPs in disease samples than is available on first-generation genome-wide association study (GWAS) arrays. Our association analyses identified more comprehensive sets of variants showing equivalent statistical association with type 2 diabetes or myocardial infarction, but did not identify stronger associations than the original GWAS signals.     

Extremely low-coverage sequencing and imputation increases power for genome-wide association studies

Genome-wide association studies (GWAS) have proven to be a powerful method to identify common genetic variants contributing to susceptibility to common diseases. Here, we show that extremely low-coverage sequencing (0.1-0.5×) captures almost as much of the common (>5%) and low-frequency (1-5%) variation across the genome as SNP arrays. As an empirical demonstration, we show that genome-wide SNP genotypes can be inferred at a mean r(2) of 0.71 using off-target data (0.24× average coverage) in a whole-exome study of 909 samples. Using both simulated and real exome-sequencing data sets, we show that association statistics obtained using extremely low-coverage sequencing data attain similar P values at known associated variants as data from genotyping arrays, without an excess of false positives. Within the context of reductions in sample preparation and sequencing costs, funds invested in extremely low-coverage sequencing can yield several times the effective sample size of GWAS based on SNP array data and a commensurate increase in statistical power.     

Whole-genome sequencing and comprehensive variant analysis of a Japanese individual using massively parallel sequencing

We report the analysis of a Japanese male using high-throughput sequencing to × 40 coverage. More than 99% of the sequence reads were mapped to the reference human genome. Using a Bayesian decision method, we identified 3,132,608 single nucleotide variations (SNVs). Comparison with six previously reported genomes revealed an excess of singleton nonsense and nonsynonymous SNVs, as well as singleton SNVs in conserved non-coding regions. We also identified 5,319 deletions smaller than 10 kb with high accuracy, in addition to copy number variations and rearrangements. De novo assembly of the unmapped sequence reads generated around 3 Mb of novel sequence, which showed high similarity to non-reference human genomes and the human herpesvirus 4 genome. Our analysis suggests that considerable variation remains undiscovered in the human genome and that whole-genome sequencing is an invaluable tool for obtaining a complete understanding of human genetic variation.     

A general approach to single-nucleotide polymorphism discovery

Single-nucleotide polymorphisms (SNPs) are the most abundant form of human genetic variation and a resource for mapping complex genetic traits. The large volume of data produced by high-throughput sequencing projects is a rich and largely untapped source of SNPs (refs 2, 3, 4, 5). We present here a unified approach to the discovery of variations in genetic sequence data of arbitrary DNA sources. We propose to use the rapidly emerging genomic sequence as a template on which to layer often unmapped, fragmentary sequence data and to use base quality values to discern true allelic variations from sequencing errors. By taking advantage of the genomic sequence we are able to use simpler yet more accurate methods for sequence organization: fragment clustering, paralogue identification and multiple alignment. We analyse these sequences with a novel, Bayesian inference engine, POLYBAYES, to calculate the probability that a given site is polymorphic. Rigorous treatment of base quality permits completely automated evaluation of the full length of all sequences, without limitations on alignment depth. We demonstrate this approach by accurate SNP predictions in human ESTs aligned to finished and working-draft quality genomic sequences, a data set representative of the typical challenges of sequence-based SNP discovery.     

Increased methylation variation in epigenetic domains across cancer types

Tumor heterogeneity is a major barrier to effective cancer diagnosis and treatment. We recently identified cancer-specific differentially DNA-methylated regions (cDMRs) in colon cancer, which also distinguish normal tissue types from each other, suggesting that these cDMRs might be generalized across cancer types. Here we show stochastic methylation variation of the same cDMRs, distinguishing cancer from normal tissue, in colon, lung, breast, thyroid and Wilms' tumors, with intermediate variation in adenomas. Whole-genome bisulfite sequencing shows these variable cDMRs are related to loss of sharply delimited methylation boundaries at CpG islands. Furthermore, we find hypomethylation of discrete blocks encompassing half the genome, with extreme gene expression variability. Genes associated with the cDMRs and large blocks are involved in mitosis and matrix remodeling, respectively. We suggest a model for cancer involving loss of epigenetic stability of well-defined genomic domains that underlies increased methylation variability in cancer that may contribute to tumor heterogeneity.     

High-throughput sequencing provides insights into genome variation and evolution in Salmonella Typhi

Isolates of Salmonella enterica serovar Typhi (Typhi), a human-restricted bacterial pathogen that causes typhoid, show limited genetic variation. We generated whole-genome sequences for 19 Typhi isolates using 454 (Roche) and Solexa (Illumina) technologies. Isolates, including the previously sequenced CT18 and Ty2 isolates, were selected to represent major nodes in the phylogenetic tree. Comparative analysis showed little evidence of purifying selection, antigenic variation or recombination between isolates. Rather, evolution in the Typhi population seems to be characterized by ongoing loss of gene function, consistent with a small effective population size. The lack of evidence for antigenic variation driven by immune selection is in contrast to strong adaptive selection for mutations conferring antibiotic resistance in Typhi. The observed patterns of genetic isolation and drift are consistent with the proposed key role of asymptomatic carriers of Typhi as the main reservoir of this pathogen, highlighting the need for identification and treatment of carriers.     

Global patterns of human mitochondrial DNA and Y-chromosome structure are not influenced by higher migration rates of females versus males

Global-scale patterns of human population structure may be influenced by the rate of migration among populations that is nearly eight times higher for females than for males. This difference is attributed mainly to the widespread practice of patrilocality, in which women move into their mates' residences after marriage. Here we directly test this hypothesis by comparing global patterns of DNA sequence variation on the Y chromosome and mitochondrial DNA (mtDNA) in the same panel of 389 individuals from ten populations (four from Africa and two each from Europe, Asia and Oceania). We introduce a new strategy to assay Y-chromosome variation that identifies a high density of single-nucleotide polymorphisms, allows complete sequencing of all individuals rather than relying on predetermined markers and provides direct sequence comparisons with mtDNA. We found the overall proportion of between-group variation (Phi(ST)) to be 0.334 for the Y chromosome and 0.382 for mtDNA. Genetic differentiation between populations was similar for the Y chromosome and mtDNA at all geographic scales that we tested. Although patrilocality may be important at the local scale, patterns of genetic structure on the continental and global scales are not shaped by the higher rate of migration among females than among males.     

A high-resolution HLA and SNP haplotype map for disease association studies in the extended human MHC

The proteins encoded by the classical HLA class I and class II genes in the major histocompatibility complex (MHC) are highly polymorphic and are essential in self versus non-self immune recognition. HLA variation is a crucial determinant of transplant rejection and susceptibility to a large number of infectious and autoimmune diseases. Yet identification of causal variants is problematic owing to linkage disequilibrium that extends across multiple HLA and non-HLA genes in the MHC. We therefore set out to characterize the linkage disequilibrium patterns between the highly polymorphic HLA genes and background variation by typing the classical HLA genes and >7,500 common SNPs and deletion-insertion polymorphisms across four population samples. The analysis provides informative tag SNPs that capture much of the common variation in the MHC region and that could be used in disease association studies, and it provides new insight into the evolutionary dynamics and ancestral origins of the HLA loci and their haplotypes.     

Patterns of single-nucleotide polymorphisms in candidate genes for blood-pressure homeostasis.

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.     

The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes

Genetic association studies are viewed as problematic and plagued by irreproducibility. Many associations have been reported for type 2 diabetes, but none have been confirmed in multiple samples and with comprehensive controls. We evaluated 16 published genetic associations to type 2 diabetes and related sub-phenotypes using a family-based design to control for population stratification, and replication samples to increase power. We were able to confirm only one association, that of the common Pro12Ala polymorphism in peroxisome proliferator-activated receptor-gamma(PPARgamma) with type 2 diabetes. By analysing over 3,000 individuals, we found a modest (1.25-fold) but significant (P=0.002) increase in diabetes risk associated with the more common proline allele (85% frequency). Moreover, our results resolve a controversy about common variation in PPARgamma. An initial study found a threefold effect, but four of five subsequent publications failed to confirm the association. All six studies are consistent with the odds ratio we describe. The data implicate inherited variation in PPARgamma in the pathogenesis of type 2 diabetes. Because the risk allele occurs at such high frequency, its modest effect translates into a large population attributable risk-influencing as much as 25% of type 2 diabetes in the general population.     

Mutations in SWI/SNF chromatin remodeling complex gene ARID1B cause Coffin-Siris syndrome

We identified de novo truncating mutations in ARID1B in three individuals with Coffin-Siris syndrome (CSS) by exome sequencing. Array-based copy-number variation (CNV) analysis in 2,000 individuals with intellectual disability revealed deletions encompassing ARID1B in 3 subjects with phenotypes partially overlapping that of CSS. Taken together with published data, these results indicate that haploinsufficiency of the ARID1B gene, which encodes an epigenetic modifier of chromatin structure, is an important cause of CSS and is potentially a common cause of intellectual disability and speech impairment.     

Characterization of single-nucleotide polymorphisms in coding regions of human genes.

A major goal in human genetics is to understand the role of common genetic variants in susceptibility to common diseases. This will require characterizing the nature of gene variation in human populations, assembling an extensive catalogue of single-nucleotide polymorphisms (SNPs) in candidate genes and performing association studies for particular diseases. At present, our knowledge of human gene variation remains rudimentary. Here we describe a systematic survey of SNPs in the coding regions of human genes. We identified SNPs in 106 genes relevant to cardiovascular disease, endocrinology and neuropsychiatry by screening an average of 114 independent alleles using 2 independent screening methods. To ensure high accuracy, all reported SNPs were confirmed by DNA sequencing. We identified 560 SNPs, including 392 coding-region SNPs (cSNPs) divided roughly equally between those causing synonymous and non-synonymous changes. We observed different rates of polymorphism among classes of sites within genes (non-coding, degenerate and non-degenerate) as well as between genes. The cSNPs most likely to influence disease, those that alter the amino acid sequence of the encoded protein, are found at a lower rate and with lower allele frequencies than silent substitutions. This likely reflects selection acting against deleterious alleles during human evolution. The lower allele frequency of missense cSNPs has implications for the compilation of a comprehensive catalogue, as well as for the subsequent application to disease association.     

Chromosome-scale selective sweeps shape Caenorhabditis elegans genomic diversity

The nematode Caenorhabditis elegans is central to research in molecular, cell and developmental biology, but nearly all of this research has been conducted on a single strain of C. elegans. Little is known about the population genomic and evolutionary history of this species. We characterized C. elegans genetic variation using high-throughput selective sequencing of a worldwide collection of 200 wild strains and identified 41,188 SNPs. Notably, C. elegans genome variation is dominated by a set of commonly shared haplotypes on four of its six chromosomes, each spanning many megabases. Population genetic modeling showed that this pattern was generated by chromosome-scale selective sweeps that have reduced variation worldwide; at least one of these sweeps probably occurred in the last few hundred years. These sweeps, which we hypothesize to be a result of human activity, have drastically reshaped the global C. elegans population in the recent past.     

Choose your target

The technology of modifying endogenous genes has recently been extended from mice to Drosophila and sheep. Concurrently, genomic sequencing is uncovering thousands of previously uncharacterized genes. Armed with today's technologies, what are our best options for delineating the functions of these new genes?     

A single-nucleotide polymorphism tagging set for human drug metabolism and transport

Interindividual variability in drug response, ranging from no therapeutic benefit to life-threatening adverse reactions, is influenced by variation in genes that control the absorption, distribution, metabolism and excretion of drugs. We genotyped 904 single-nucleotide polymorphisms (SNPs) from 55 such genes in two population samples (European and Japanese) and identified a set of tagging SNPs that represents the common variation in these genes, both known and unknown. Extensive empirical evaluations, including a direct assessment of association with candidate functional SNPs in a new, larger population sample, validated the performance of these tagging SNPs and confirmed their utility for linkage-disequilibrium mapping in pharmacogenetics. The analyses also suggest that rare variation is not amenable to tagging strategies.     

Genome assembly comparison identifies structural variants in the human genome

Numerous types of DNA variation exist, ranging from SNPs to larger structural alterations such as copy number variants (CNVs) and inversions. Alignment of DNA sequence from different sources has been used to identify SNPs and intermediate-sized variants (ISVs). However, only a small proportion of total heterogeneity is characterized, and little is known of the characteristics of most smaller-sized (<50 kb) variants. Here we show that genome assembly comparison is a robust approach for identification of all classes of genetic variation. Through comparison of two human assemblies (Celera's R27c compilation and the Build 35 reference sequence), we identified megabases of sequence (in the form of 13,534 putative non-SNP events) that were absent, inverted or polymorphic in one assembly. Database comparison and laboratory experimentation further demonstrated overlap or validation for 240 variable regions and confirmed >1.5 million SNPs. Some differences were simple insertions and deletions, but in regions containing CNVs, segmental duplication and repetitive DNA, they were more complex. Our results uncover substantial undescribed variation in humans, highlighting the need for comprehensive annotation strategies to fully interpret genome scanning and personalized sequencing projects.