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Whole-genome sequencing (WGS) allows for a comprehensive view of the sequence of the human genome. We present and apply integrated methodologic steps for interrogating WGS data to characterize the genetic architecture of 10 heart- and blood-related traits in a sample of 1,860 African Americans. In order to evaluate the contribution of regulatory and non-protein coding regions of the genome, we conducted aggregate tests of rare variation across the entire genomic landscape using a sliding window, complemented by an annotation-based assessment of the genome using predefined regulatory elements and within the first intron of all genes. These tests were performed treating all variants equally as well as with individual variants weighted by a measure of predicted functional consequence. Significant findings were assessed in 1,705 individuals of European ancestry. After these steps, we identified and replicated components of the genomic landscape significantly associated with heart- and blood-related traits. For two traits, lipoprotein(a) levels and neutrophil count, aggregate tests of low-frequency and rare variation were significantly associated across multiple motifs. For a third trait, cardiac troponin T, investigation of regulatory domains identified a locus on chromosome 9. These practical approaches for WGS analysis led to the identification of informative genomic regions and also showed that defined non-coding regions, such as first introns of genes and regulatory domains, are associated with important risk factor phenotypes. This study illustrates the tractable nature of WGS data and outlines an approach for characterizing the genetic architecture of complex traits.

Characterizing meiotic recombination rates across the genomes of nonhuman primates is important for understanding the genetics of primate populations, performing genetic analyses of phenotypic variation and reconstructing the evolution of human recombination. Rhesus macaques (Macaca mulatta) are the most widely used nonhuman primates in biomedical research. We constructed a high-resolution genetic map of the rhesus genome based on whole genome sequence data from Indian-origin rhesus macaques. The genetic markers used were approximately 18 million SNPs, with marker density 6.93 per kb across the autosomes. We report that the genome-wide recombination rate in rhesus macaques is significantly lower than rates observed in apes or humans, while the distribution of recombination across the macaque genome is more uniform. These observations provide new comparative information regarding the evolution of recombination in primates.

Hemophilia A (HA) is an X-linked bleeding disorder caused by deleterious mutations in the coagulation factor VIII gene (F8). To date, F8 mutations have been documented predominantly in European subjects and in American subjects of European descent. Information on F8 variants in individuals of more diverse ethnic backgrounds is limited.To discover novel and rare F8 variants, and to characterize F8 variants in diverse population backgrounds.We analyzed 2535 subjects, including 26 different ethnicities, whose data were available from the 1000 Genomes Project (1000G) phase 3 dataset, for F8 variants and their potential functional impact.We identified 3030 single nucleotide variants, 31 short deletions and insertions (Indels) and a large, 497 kb, deletion. Among all variants, 86.4% were rare variants and 55.6% were novel. Eighteen variants previously associated with HA were found in our study. Most of these 'HA variants' were ethnic-specific with low allele frequency; however, one variant (p.M2257V) was present in 27% of African subjects. The p.E132D, p.T281A, p.A303V and p.D422H 'HA variants' were identified only in males. Twelve novel missense variants were predicted to be deleterious. The large deletion was discovered in eight female subjects without affecting F8 transcription and the transcription of genes on the X chromosome.Characterizing F8 in the 1000G project highlighted the complexity of F8 variants and the importance of interrogating genetic variants on multiple ethnic backgrounds for associations with bleeding and thrombosis. The haplotype analysis and the orientation of duplicons that flank the large deletion suggested that the deletion was recurrent and originated by homologous recombination.

INTRODUCTION A majority of imbalances in DNA methylation between homologous chromosomes in humans are sequence-dependent; the DNA sequence differences between the two chromosomes cause differences in the methylation state of neighboring cytosines on the same chromosome. The analyses of this sequence-dependent allele-specific methylation (SD-ASM) traditionally involved measurement of average methylation levels across many cells. Detailed understanding of SD-ASM at the single-cell and single-chromosome levels is lacking. This gap in understanding may hide the connection between SD-ASM, ubiquitous stochastic cell-to-cell and chromosome-to-chromosome variation in DNA methylation, and the puzzling and evolutionarily conserved patterns of intermediate methylation at gene regulatory loci. RATIONALE Whole-genome bisulfite sequencing (WGBS) provides the ultimate single-chromosome level of resolution and comprehensive whole-genome coverage required to explore SD-ASM. However, the exploration of the link between SD-ASM, stochastic variation in DNA methylation, and gene regulation requires deep coverage by WGBS across tissues and individuals and the context of other epigenomic marks and gene transcription. RESULTS We constructed maps of allelic imbalances in DNA methylation, histone marks, and gene transcription in 71 epigenomes from 36 distinct cell and tissue types from 13 donors. Deep (1691-fold) combined WGBS read coverage across 49 methylomes revealed CpG methylation imbalances exceeding 30% differences at 5% of the loci, which is more conservative than previous estimates in the 8 to 10% range; a similar value (8%) is observed in our dataset when we lowered our threshold for detecting allelic imbalance to 20% methylation difference between the two alleles. Extensive sequence-dependent CpG methylation imbalances were observed at thousands of heterozygous regulatory loci. Stochastic switching, defined as random transitions between fully methylated and unmethylated states of DNA, occurred at thousands of regulatory loci bound by transcription factors (TFs). Our results explain the conservation of intermediate methylation states at regulatory loci by showing that the intermediate methylation reflects the relative frequencies of fully methylated and fully unmethylated epialleles. SD-ASM is explainable by different relative frequencies of methylated and unmethylated epialleles for the two alleles. The differences in epiallele frequency spectra of the alleles at thousands of TF-bound regulatory loci correlated with the differences in alleles’ affinities for TF binding, which suggests a mechanistic explanation for SD-ASM. We observed an excess of rare variants among those showing SD-ASM, which suggests that an average human genome harbors at least ~200 detrimental rare variants that also show SD-ASM. The methylome’s sensitivity to genetic variation is unevenly distributed across the genome, which is consistent with buffering of housekeeping genes against the effects of random mutations. By contrast, less essential genes with tissue-specific expression patterns show sensitivity, thus providing opportunity for evolutionary innovation through changes in gene regulation. CONCLUSION Analysis of allelic epigenome maps provides a unifying model that links sequence-dependent allelic imbalances of the epigenome, stochastic switching at gene regulatory loci, selective buffering of the regulatory circuitry against the effects of random mutations, and disease-associated genetic variation.

Summary Background The von Willebrand factor (VWF) gene is highly polymorphic, with variants correlated with VWF antigen levels, adhesion activity, clearance and factor VIII binding. VWF mutations are detected in patients with von Willebrand disease (VWD), whereas polymorphic variants could be associated with thrombosis. However, information on the ethnic diversity of VWF variants and their association with diseases is limited. Objectives To characterize novel VWF variants from different ethnicities in the general population. Patients/Methods We analyzed samples from 1092 subjects of 14 ethnicities available in the 1000 Genomes database for VWF variants and their potential functional impacts. Results We identified 2728 SNPs and 91 insertions and deletions that had a high level of ethnic diversity, with Africans having the highest number of variants. The highest level of diversity was found in the D′ and D2 domains. Among 94 non-synonymous variants, 31 were predicted to be deleterious, including 19 that were previously associated with VWD. Most of these ‘VWD variants’ had allele frequencies consistent with disease incidence in European subjects, but some had a significantly higher frequency in other ethnicities. The mutations R2185Q, H817Q and M740I associated with type 1 and type 2N VWD were present in more than 13% of African subjects. Conclusions These results highlight the complexity of VWF variations in different ethnic groups and emphasize the importance of interrogating variations on multiple ethnic backgrounds for associations with bleeding and thrombosis.

Next-generation sequencing is a powerful approach for discovering genetic variation. Sensitive variant calling and haplotype inference from population sequencing data remain challenging. We describe methods for high-quality discovery, genotyping, and phasing of SNPs for low-coverage (approximately 5×) sequencing of populations, implemented in a pipeline called SNPTools. Our pipeline contains several innovations that specifically address challenges caused by low-coverage population sequencing: (1) effective base depth (EBD), a nonparametric statistic that enables more accurate statistical modeling of sequencing data; (2) variance ratio scoring, a variance-based statistic that discovers polymorphic loci with high sensitivity and specificity; and (3) BAM-specific binomial mixture modeling (BBMM), a clustering algorithm that generates robust genotype likelihoods from heterogeneous sequencing data. Last, we develop an imputation engine that refines raw genotype likelihoods to produce high-quality phased genotypes/haplotypes. Designed for large population studies, SNPTools' input/output (I/O) and storage aware design leads to improved computing performance on large sequencing data sets. We apply SNPTools to the International 1000 Genomes Project (1000G) Phase 1 low-coverage data set and obtain genotyping accuracy comparable to that of SNP microarray.

The goal of the International HapMap Project is to determine the common patterns of DNA sequence variation in the human genome and to make this information freely available in the public domain. An international consortium is developing a map of these patterns across the genome by determining the genotypes of one million or more sequence variants, their frequencies and the degree of association between them, in DNA samples from populations with ancestry from parts of Africa, Asia and Europe. The HapMap will allow the discovery of sequence variants that affect common disease, will facilitate development of diagnostic tools, and will enhance our ability to choose targets for therapeutic intervention. © 2003 Nature Publishing Group.

Historical episodes of natural selection can skew the frequencies of genetic variants, leaving a signature that can persist for many tens or even hundreds of thousands of years. However, formal tests for selection based on allele frequency skew require strong assumptions about demographic history and mutation, which are rarely well understood. Here, we develop an empirical approach to test for signals of selection that compares patterns of genetic variation at a candidate locus with matched random regions of the genome collected in the same way. We apply this approach to four genes that have been implicated in syndromes of impaired neurological development, comparing the pattern of variation in our re-sequencing data with a large-scale, genomic data set that provides an empirical null distribution. We confirm a previously reported signal at FOXP2, and find a novel signal of selection centered at AHI1, a gene that is involved in motor and behavior abnormalities. The locus is marked by many high frequency derived alleles in non-Africans that are of low frequency in Africans, suggesting that selection at this or a closely neighboring gene occurred in the ancestral population of non-Africans. Our study also provides a prototype for how empirical scans for ancient selection can be carried out once many genomes are sequenced.

Rhesus macaques (Macaca mulatta) are the most widely used nonhuman primate in biomedical research, have the largest natural geographic distribution of any nonhuman primate, and have been the focus of much evolutionary and behavioral investigation. Consequently, rhesus macaques are one of the most thoroughly studied nonhuman primate species. However, little is known about genome-wide genetic variation in this species. A detailed understanding of extant genomic variation among rhesus macaques has implications for the use of this species as a model for studies of human health and disease, as well as for evolutionary population genomics. Whole-genome sequencing analysis of 133 rhesus macaques revealed more than 43.7 million single-nucleotide variants, including thousands predicted to alter protein sequences, transcript splicing, and transcription factor binding sites. Rhesus macaques exhibit 2.5-fold higher overall nucleotide diversity and slightly elevated putative functional variation compared with humans. This functional variation in macaques provides opportunities for analyses of coding and noncoding variation, and its cellular consequences. Despite modestly higher levels of nonsynonymous variation in the macaques, the estimated distribution of fitness effects and the ratio of nonsynonymous to synonymous variants suggest that purifying selection has had stronger effects in rhesus macaques than in humans. Demographic reconstructions indicate this species has experienced a consistently large but fluctuating population size. Overall, the results presented here provide new insights into the population genomics of nonhuman primates and expand genomic information directly relevant to primate models of human disease.

Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.

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. © 2005 Nature Publishing Group., link_to_OA_fulltext

Whole genome analysis in large samples from a single population is needed to provide adequate power to assess relative strengths of natural selection across different functional components of the genome. In this study, we analyzed next-generation sequencing data from 962 European Americans, and found that as expected approximately 60% of the top 1% of positive selection signals lie in intergenic regions, 33% in intronic regions, and slightly over 1% in coding regions. Several detailed functional annotation categories in intergenic regions showed statistically significant enrichment in positively selected loci when compared to the null distribution of the genomic span of ENCODE categories. There was a significant enrichment of purifying selection signals detected in enhancers, transcription factor binding sites, microRNAs and target sites, but not on lincRNA or piRNAs, suggesting different evolutionary constraints for these domains. Loci in "repressed or low activity regions" and loci near or overlapping the transcription start site were the most significantly over-represented annotations among the top 1% of signals for positive selection.

The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies., Wellcome Trust (London, England) (Core Award 090532/Z/09/Z), Wellcome Trust (London, England) (Senior Investigator Award 095552/Z/11/Z ), Wellcome Trust (London, England) (WT095908), Wellcome Trust (London, England) (WT109497), Wellcome Trust (London, England) (WT098051), Wellcome Trust (London, England) (WT086084/Z/08/Z), Wellcome Trust (London, England) (WT100956/Z/13/Z ), Wellcome Trust (London, England) (WT097307), Wellcome Trust (London, England) (WT0855322/Z/08/Z ), Wellcome Trust (London, England) (WT090770/Z/09/Z ), Wellcome Trust (London, England) (Major Overseas program in Vietnam grant 089276/Z.09/Z), Medical Research Council (Great Britain) (grant G0801823), Biotechnology and Biological Sciences Research Council (Great Britain) (grant BB/I02593X/1), Biotechnology and Biological Sciences Research Council (Great Britain) (grant BB/I021213/1), Zhongguo ke xue ji shu qing bao yan jiu suo. Office of 863 Programme of China (2012AA02A201), National Basic Research Program of China (2011CB809201), National Basic Research Program of China (2011CB809202), National Basic Research Program of China (2011CB809203), National Natural Science Foundation of China (31161130357), Shenzhen Municipal Government of China (grant ZYC201105170397A), Canadian Institutes of Health Research (grant 136855), Quebec Ministry of Economic Development, Innovation, and Exports (PSR-SIIRI-195), Germany. Bundesministerium für Bildung und Forschung (0315428A), Germany. Bundesministerium für Bildung und Forschung (01GS08201), Germany. Bundesministerium für Bildung und Forschung (BMBF-EPITREAT grant 0316190A), Deutsche Forschungsgemeinschaft (Emmy Noether Grant KO4037/1-1), Beatriu de Pinos Program (2006 BP-A 10144), Beatriu de Pinos Program (2009 BP-B 00274), Spanish National Institute for Health (grant PRB2 IPT13/0001-ISCIII-SGEFI/FEDER), Japan Society for the Promotion of Science (fellowship number PE13075), Marie Curie Actions Career Integration (grant 303772), Fonds National Suisse del la Recherche, SNSF, Scientifique (31003A_130342), National Center for Biotechnology Information (U.S.) (U54HG3067), National Center for Biotechnology Information (U.S.) (U54HG3273), National Center for Biotechnology Information (U.S.) (U01HG5211), National Center for Biotechnology Information (U.S.) (U54HG3079), National Center for Biotechnology Information (U.S.) (R01HG2898), National Center for Biotechnology Information (U.S.) (R01HG2385), National Center for Biotechnology Information (U.S.) (RC2HG5552), National Center for Biotechnology Information (U.S.) (U01HG6513), National Center for Biotechnology Information (U.S.) (U01HG5214), National Center for Biotechnology Information (U.S.) (U01HG5715), National Center for Biotechnology Information (U.S.) (U01HG5718), National Center for Biotechnology Information (U.S.) (U01HG5728), National Center for Biotechnology Information (U.S.) (U41HG7635), National Center for Biotechnology Information (U.S.) (U41HG7497), National Center for Biotechnology Information (U.S.) (R01HG4960), National Center for Biotechnology Information (U.S.) (R01HG5701), National Center for Biotechnology Information (U.S.) (R01HG5214), National Center for Biotechnology Information (U.S.) (R01HG6855), National Center for Biotechnology Information (U.S.) (R01HG7068), National Center for Biotechnology Information (U.S.) (R01HG7644), National Center for Biotechnology Information (U.S.) (DP2OD6514), National Center for Biotechnology Information (U.S.) (DP5OD9154), National Center for Biotechnology Information (U.S.) (R01CA166661), National Center for Biotechnology Information (U.S.) (R01CA172652), National Center for Biotechnology Information (U.S.) (P01GM99568), National Center for Biotechnology Information (U.S.) (R01GM59290), National Center for Biotechnology Information (U.S.) (R01GM104390), National Center for Biotechnology Information (U.S.) (T32GM7790), National Center for Biotechnology Information (U.S.) (R01HL87699), National Center for Biotechnology Information (U.S.) (R01HL104608), National Center for Biotechnology Information (U.S.) (T32HL94284), National Center for Biotechnology Information (U.S.) (HHSN268201100040C), National Center for Biotechnology Information (U.S.) (HHSN272201000025C), Lundbeck Foundation (grant R170-2014-1039, Simons Foundation (SFARI award SF51), National Science Foundation (U.S.) (Research Fellowship DGE-1147470)

The synthesis, secretion and clearance of von Willebrand factor (VWF) are regulated by genetic variations in coding and promoter regions of the VWF gene. We have previously identified 19 single nucleotide polymorphisms (SNPs), primarily in introns that are associated with VWF antigen levels in subjects of European descent. In this study, we conducted race by gender analyses to compare the association of VWF SNPs with VWF antigen among 10,434 healthy Americans of European (EA) or African (AA) descent from the Atherosclerosis Risk in Communities (ARIC) study. Among 75 SNPs analyzed, 13 and 10 SNPs were associated with VWF antigen levels in EA male and EA female subjects, respectively. However, only one SNP (RS1063857) was significantly associated with VWF antigen in AA females and none was in AA males. Haplotype analysis of the ARIC samples and studying racial diversities in the VWF gene from the 1000 genomes database suggest a greater degree of variations in the VWF gene in AA subjects as compared to EA subjects. Together, these data suggest potential race and gender divergence in regulating VWF expression by genetic variations.

VWF is extensively glycosylated with biantennary core fucosylated glycans. Most N-linked and O-linked glycans on VWF are sialylated. FVIII is also glycosylated, with a glycan structure similar to that of VWF. ST3GAL sialyltransferases catalyze the transfer of sialic acids in the α2,3 linkage to termini of N- and O-glycans. This sialic acid modification is critical for VWF synthesis and activity. We analyzed genetic and phenotypic data from the Atherosclerosis Risk in Communities (ARIC) study for the association of single nucleotide polymorphisms (SNPs) in the ST3GAL4 gene with plasma VWF levels and FVIII activity in 12,117 subjects. We also analyzed ST3GAL4 SNPs found in 2,535 subjects of 26 ethnicities from the 1000 Genomes (1000G) project for ethnic diversity, SNP imputation, and ST3GAL4 haplotypes. We identified 14 and 1,714 ST3GAL4 variants in the ARIC GWAS and 1000G databases respectively, with 46% being ethnically diverse in their allele frequencies. Among the 14 ST3GAL4 SNPs found in ARIC GWAS, the intronic rs2186717, rs7928391, and rs11220465 were associated with VWF levels and with FVIII activity after adjustment for age, BMI, hypertension, diabetes, ever-smoking status, and ABO. This study illustrates the power of next-generation sequencing in the discovery of new genetic variants and a significant ethnic diversity in the ST3GAL4 gene. We discuss potential mechanisms through which these intronic SNPs regulate ST3GAL4 biosynthesis and the activity that affects VWF and FVIII.

Summary Background The considerable genetic predisposition to deep vein thrombosis (DVT) is only partially accounted for by known genetic risk variants. Rare single-nucleotide variants (SNVs) of the coding areas of hemostatic genes may explain part of this missing heritability. The ADAMTS13 and VWF genes encode two interconnected proteins with fundamental hemostatic functions, the disruption of which may result in thrombosis. Objectives To study the distribution and burden of rare coding SNVs of ADAMTS13 and VWF found by sequencing in cases and controls of DVT. Patients/Methods The protein-coding areas of 186 hemostatic/proinflammatory genes were sequenced by next-generation technology in 94 thrombophilia-negative patients with DVT and 98 controls. Gene-specific information on ADAMTS13 and VWF was used to study the association between DVT and rare coding SNVs of the two genes. Results More than 70 billion base pairs of raw sequence data were produced to sequence the 700-kb target area with a median redundancy of × 45 in 192 individuals. Most of the 4366 SNVs identified were rare and non-synonymous, indicating pathogenetic potential. Rare (frequency of

Background Whole exome capture sequencing allows researchers to cost-effectively sequence the coding regions of the genome. Although the exome capture sequencing methods have become routine and well established, there is currently a lack of tools specialized for variant calling in this type of data. Results Using statistical models trained on validated whole-exome capture sequencing data, the Atlas2 Suite is an integrative variant analysis pipeline optimized for variant discovery on all three of the widely used next generation sequencing platforms (SOLiD, Illumina, and Roche 454). The suite employs logistic regression models in conjunction with user-adjustable cutoffs to accurately separate true SNPs and INDELs from sequencing and mapping errors with high sensitivity (96.7%). Conclusion We have implemented the Atlas2 Suite and applied it to 92 whole exome samples from the 1000 Genomes Project. The Atlas2 Suite is available for download at http://sourceforge.net/projects/atlas2/. In addition to a command line version, the suite has been integrated into the Genboree Workbench, allowing biomedical scientists with minimal informatics expertise to remotely call, view, and further analyze variants through a simple web interface. The existing genomic databases displayed via the Genboree browser also streamline the process from variant discovery to functional genomics analysis, resulting in an off-the-shelf toolkit for the broader community.

von Willebrand factor (VWF) is an essential component of hemostasis and has been implicated in thrombosis. Multimer size and the amount of circulating VWF are known to impact hemostatic function. We associated 78 VWF single nucleotide polymorphisms (SNPs) and haplotypes constructed from those SNPs with VWF antigen level in 7856 subjects of European descent. Among the nongenomic factors, age and body mass index contributed 4.8% and 1.6% of VWF variation, respectively. The SNP rs514659 (tags O blood type) contributed 15.4% of the variance. Among the VWF SNPs, we identified 18 SNPs that are associated with levels of VWF. The correlative SNPs are either intronic (89%) or silent exonic (11%). Although SNPs examined are distributed throughout the entire VWF gene without apparent cluster, all the positive SNPs are located in a 50-kb region. Exons in this region encode for VWF D2, D′, and D3 domains that are known to regulate VWF multimerization and storage. Mutations in the D3 domain are also associated with von Willebrand disease. Fifteen of these 18 correlative SNPs are in 2 distinct haplotype blocks. In summary, we identified a cluster of intronic VWF SNPs that associate with plasma levels of VWF, individually or additively, in a large cohort of healthy subjects.

Background Massively parallel sequencing readouts of epigenomic assays are enabling integrative genome-wide analyses of genomic and epigenomic variation. Pash 3.0 performs sequence comparison and read mapping and can be employed as a module within diverse configurable analysis pipelines, including ChIP-Seq and methylome mapping by whole-genome bisulfite sequencing. Results Pash 3.0 generally matches the accuracy and speed of niche programs for fast mapping of short reads, and exceeds their performance on longer reads generated by a new generation of massively parallel sequencing technologies. By exploiting longer read lengths, Pash 3.0 maps reads onto the large fraction of genomic DNA that contains repetitive elements and polymorphic sites, including indel polymorphisms. Conclusions We demonstrate the versatility of Pash 3.0 by analyzing the interaction between CpG methylation, CpG SNPs, and imprinting based on publicly available whole-genome shotgun bisulfite sequencing data. Pash 3.0 makes use of gapped k-mer alignment, a non-seed based comparison method, which is implemented using multi-positional hash tables. This allows Pash 3.0 to run on diverse hardware platforms, including individual computers with standard RAM capacity, multi-core hardware architectures and large clusters.

Background Genetic studies of populations from the Indian subcontinent are of great interest because of India's large population size, complex demographic history, and unique social structure. Despite recent large-scale efforts in discovering human genetic variation, India's vast reservoir of genetic diversity remains largely unexplored. Results To analyze an unbiased sample of genetic diversity in India and to investigate human migration history in Eurasia, we resequenced one 100-kb ENCODE region in 92 samples collected from three castes and one tribal group from the state of Andhra Pradesh in south India. Analyses of the four Indian populations, along with eight HapMap populations (692 samples), showed that 30% of all SNPs in the south Indian populations are not seen in HapMap populations. Several Indian populations, such as the Yadava, Mala/Madiga, and Irula, have nucleotide diversity levels as high as those of HapMap African populations. Using unbiased allele-frequency spectra, we investigated the expansion of human populations into Eurasia. The divergence time estimates among the major population groups suggest that Eurasian populations in this study diverged from Africans during the same time frame (approximately 90 to 110 thousand years ago). The divergence among different Eurasian populations occurred more than 40,000 years after their divergence with Africans. Conclusions Our results show that Indian populations harbor large amounts of genetic variation that have not been surveyed adequately by public SNP discovery efforts. Our data also support a delayed expansion hypothesis in which an ancestral Eurasian founding population remained isolated long after the out-of-Africa diaspora, before expanding throughout Eurasia.

It has been widely appreciated that the genome sequence is shaping the future biomedical research. The genome sequence provides a general framework for assembling fragmentary DNA information into landscape of biological structure and function [1]. The rapid advances in DNA sequencing technology are revolutionizing biomedical research. Starting in 2005, a variety of massively parallel sequencing instruments such as the Roche/454, the Life Technologies SOLiD, and the Illumina platforms which were largely different from the Sanger-based capillary sequencing were used to sequence the human and model organism genomes. Although each instrument has its own attributes, all massively parallel sequences machines share some common remarkable features [2]. First, the initial preparatory steps are reduced and simplified. Second, amplification of the library fragments is needed for all platforms. Third, sequencing reactions are performed and detected automatically. In the past decade, the amount of sequence output per run has been dramatically increased, the per-base cost of DNA sequencing has plummeted by ~100,000-fold, and base-calling accuracy has been largely improved. The current second-generation sequencing machines can read ~250 billion bases in a week. When sequencing becomes simple and inexpensive, it is being routinely applied to biomedical research. To create comprehensive catalogues of genomic variants, the next-generation sequencing technologies have been used to produce sequence data in the 1000 Genomes Project. It plans to sequence more than 2000 individuals to find essentially all single-nucleotide polymorphisms (SNPs), insertions/deletions (indels), and structural variants with frequency >1% across the genome and >0.1% in protein-coding regions. After the project is completed by 2012, the full spectrum of human genomic variation in large, diverse sample sets will have been identified. The further reduction of cost and improvement of base-calling accuracy will uncover the genetic architectures of complex diseases and make clinical use of genome sequencing a routine practice and create great opportunities for genomic medicine. Many layers of epigenomic information are being mapped by next-generation sequencing. Chromatic modification and protein binding can be mapped by chromatin immunoprecipitation sequencing (ChIP-Seq). The genome-wide single-base resolution of DNA methylation map has been performed by bisulfate sequencing, in which the methylated cytosines have been chemically modified. Massively parallel sequencing have also been applied to microRNA and mRNA profiling (RNA-Seq) to more accurately measure expressions of microRNA and mRNA, identify variability in microRNA sequence and mRNA sequence, and detect splice form of mRNA expressions. Massively parallel sequencing platforms have significantly increased our ability to study the human genome and provided powerful new tools for genomic medicine. However, these technologies have also required profound changes to the data analysis. The major obstacle in genomic research is no longer data production. The major challenge in genome sequencing is the methods for data storages, transfer, and data analysis. The classical statistical methods and computational algorithms are inadequate for analyzing the unprecedented amount of genomic sequence data. Novel analytic strategies for exploring new features of sequencing data, integrating various genomic and epigenomic data, unraveling the structure, organization, and function of the human genome, understanding fundamental principles of genomic biology, and discovering genetic and nongenetic bases of diseases are urgently needed. This special issue includes six high-quality papers, which were selected after undergoing rigorous peer review. We briefly describe the papers in the following. The first paper (V. Costa et al., 2010) provides a comprehensive survey of the RNA sequencing methodology. RNA sequencing is a major platform in the next-generation sequencing (NGS), aiming to accurately determine expression levels of specific genes, differential splicing, and allele-specific expression of transcripts at the transcriptome level. So far, RNA sequencing remains the most complex (NGS) application. The authors focus on the challenges that RNA sequencing presents both from a biological and a bioinformatics point of view. In the second paper (Y. Qi et al., 2010), the authors apply high-throughput sequencing of microRNAs in adenovirus type 3 (AD3) infected human laryngeal epithelial (Hep2) cells. Using the SOLiD sequencing technology, analysis of microRNAs profiles identified 492 precursor microRNAs in the AD3 infected Hep2 cells and 540 precursor microRNAs in the control. Among them, 44 and 36 microRNAs showed high and lower expression in the AD3 infected cells than the control, respectively. The study demonstrates that NGS is efficient and powerful for microRNA profiling in the virus-infected cell lines. L. Cui et al. (2010) also apply SOLiD sequencing to profile microRNAs involved in the host response to enterovirus 71 (EV71) infection. They found 64 microRNAs whose expression levels changed from more than 2-fold in response to EV71 infection in Hep2 cells. Functional analysis like Gene Ontology enrichment test revealed that many of these microRNAs might be involved in neurological process, immune response, and cell death pathways, which have known to be associated with the extreme virulence of EV71. As authors stated, this is the first paper on host microRNAs expression alteration in response to EV71 infection. W. Wang et al. (2010) use another NGS technology, ChIP-Seq, to find the targeting microRNA genes of a transcription factor, EGR1, in human erythroleukemia cell line K562. They found EGR1 binding sites near the promoters of 124 distinct microRNA genes, accounting for about 42% of the miRNAs which have high-confidence predicted promoters (294). They also found that EGR1 binds to another 63 pre-miRNAs. This study provides the first global binding profile between the transcription factor EGR1 and its targeting miRNA genes in PMA-treated K562 cells. S. Hasson et al. (2010) report the cloning of cDNA sequences encoding four groups or isoforms of the haemostasis-disruptive Serine protease proteins (SPs) from the venom glands of Echis ocellatus, whose bite is the leading cause of death and morbidity in Africa. Based on their observation of the extraordinary level of interspecific and intergeneric sequence conservation exhibited by the Echis ocellatus EoSPs and analogous serine proteases from other viper species, the authors speculate that antibodies to representative molecules should neutralise the biological function of this important group of venom toxins in vipers that are distributed throughout Africa, the Middle East, and the Indian subcontinent. The last paper (Z. Zhao and C. Jiang 2010) conducts a comparative genome-wide polymorphism-fixation analysis of human codons, as previously investigators often analyze either interspecies fixed substitutions or intraspecies nucleotide polymorphisms, but not both data types simultaneously. The authors report many features in the recent codon evolution. They conclude that fixation process could effectively and quickly correct the volatile changes introduced by polymorphisms so that codon changes could be gradual and directional and that codon composition could be kept relatively stable during evolution. As numerous mutation data have been identified by sequencing and many more will be identified by NGS in the near future, such analysis may help us understand mutational process in the recent genome evolution.

Accurate identification of genetic variants from next-generation sequencing (NGS) data is essential for immediate large-scale genomic endeavors such as the 1000 Genomes Project, and is crucial for further genetic analysis based on the discoveries. The key challenge in single nucleotide polymorphism (SNP) discovery is to distinguish true individual variants (occurring at a low frequency) from sequencing errors (often occurring at frequencies orders of magnitude higher). Therefore, knowledge of the error probabilities of base calls is essential. We have developed Atlas-SNP2, a computational tool that detects and accounts for systematic sequencing errors caused by context-related variables in a logistic regression model learned from training data sets. Subsequently, it estimates the posterior error probability for each substitution through a Bayesian formula that integrates prior knowledge of the overall sequencing error probability and the estimated SNP rate with the results from the logistic regression model for the given substitutions. The estimated posterior SNP probability can be used to distinguish true SNPs from sequencing errors. Validation results show that Atlas-SNP2 achieves a false-positive rate of lower than 10%, with an ∼5% or lower false-negative rate.

Complex human diseases are known to have a significant genetic component. Despite some important successes (Altshuler et al. 2000; Hugot et al. 2001), the elucidation of the underlying genetic determinants have proven resistant to standard methods. Linkage analysis using affected sib pairs has limited power to uncover such signals, as each individual functional variant contributes only modestly to disease risk (Risch 2000). Large-scale association studies that would allow genome-wide mapping in large collections of cases with matched controls have therefore been proposed (e.g., Kruglyak 1999; Risch 2000). Some of the barriers to adopting such strategies, including the need to establish large-case control populations (Geschwind et al. 2001; Shmulewitz et al. 2001; Cupples et al. 2003) and develop comprehensive SNP resources (dbSNP), have been overcome. In addition, the International HapMap project (The International HapMap Consortium 2003) is completing a first draft of a whole genome haplotype map in the Centre d'Etude du Polymorphisme Humain (CEU) population by the end of 2004. The Hap-Map effort will yield a broad view of the genetic architecture of human populations and allow for the efficient selection of the most informative tagging SNPs for subsequent association studies. The remaining requirement to fully enable large-scale genetic association studies is the development of truly cost-effective and scalable SNP genotyping technologies. These methods must allow hundreds of thousands of markers to be efficiently and accurately scored in thousands of patients. The first generation of SNP genotyping technologies were based on single amplification reactions for each locus and were not appropriate for these largescale, whole-genome studies. Recent advances have assayed thousands of random SNPs using ultra high-density wafer hybridizations (Matsuzaki et al. 2004) but will not allow the advantages of the tagging SNP approach to be fully realized because these technologies will not be able to convert all the informative tagging SNPs and/or putative functional SNPs into working genotyping assays. Multiplexed genotyping technologies that allow the multiplexing of hundreds of targeted SNPs have recently been developed based on various versions of the Oligo Ligation Assay (OLA) (Grossman et al. 1994; Samiotaki et al. 1994; Oliphant et al. 2002). These technologies would still demand a fairly large infrastructure in order to process the thousands of reactions necessary per patient. Here, we describe an advanced Molecular Inversion Probe (MIP) genotyping technology (Hardenbol et al. 2003) that combines the strengths of all of the above methods. MIP exploits the advantages of the OLA methodologies but can be more highly multiplexed due to a unique unimolecular method of action and an enzymology that combines the specificity of both ligase and polymerase enzymes. This assay enables the use of >12,000 oligo probes to simultaneously interrogate human genomic DNA and, following a single PCR, detect the results via a single universal tag DNA chip array. The application of MIP to generate a haplotype map of Chromosome 12 in CEU families (The International HapMap Consortium 2003) as part of the Human HapMap project has yielded 3,509,052 genotypes from 38,429 assays. In this study we analyze the important features of the assay performance that will enable MIP to be effectively used for many future largescale studies.

Background Indels are an important cause of human variation and central to the study of human disease. The 1000 Genomes Project Low-Coverage Pilot identified over 1.3 million indels shorter than 50 bp, of which over 890 were identified as potentially disruptive variants. Yet, despite their ubiquity, the local genomic characteristics of indels remain unexplored. Results Herein we describe population- and minor allele frequency-based differences in linkage disequilibrium and imputation characteristics for indels included in the 1000 Genomes Project Low-Coverage Pilot for the CEU, YRI and CHB+JPT populations. Common indels were well tagged by nearby SNPs in all studied populations, and were also tagged at a similar rate to common SNPs. Both neutral and functionally deleterious common indels were imputed with greater than 95% concordance from HapMap Phase 3 and OMNI SNP sites. Further, 38 to 56% of low frequency indels were tagged by low frequency SNPs. We were able to impute heterozygous low frequency indels with over 50% concordance. Lastly, our analysis also revealed evidence of ascertainment bias. This bias prevents us from extending the applicability of our results to highly polymorphic indels that could not be identified in the Low-Coverage Pilot. Conclusions Although further scope exists to improve the imputation of low frequency indels, our study demonstrates that there are already ample opportunities to retrospectively impute indels for prior genome-wide association studies and to incorporate indel imputation into future case/control studies.

A region of approximately one megabase of human Chromosome 12 shows extensive linkage disequilibrium in Utah residents with ancestry from northern and western Europe. This strikingly large linkage disequilibrium block was analyzed with statistical and experimental methods to determine whether natural selection could be implicated in shaping the current genome structure. Extended Haplotype Homozygosity and Relative Extended Haplotype Homozygosity analyses on this region mapped a core region of the strongest conserved haplotype to the exon 1 of the Spinocerebellar ataxia type 2 gene (SCA2). Direct DNA sequencing of this region of the SCA2 gene revealed a significant association between a pre-expanded allele [(CAG)8CAA(CAG)4CAA(CAG)8] of CAG repeats within exon 1 and the selected haplotype of the SCA2 gene. A significantly negative Tajima's D value (−2.20, p < 0.01) on this site consistently suggested selection on the CAG repeat. This region was also investigated in the three other populations, none of which showed signs of selection. These results suggest that a recent positive selection of the pre-expansion SCA2 CAG repeat has occurred in Utah residents with European ancestry., Synopsis Natural selection ultimately acts on the genetic variants existing among human populations. Therefore, there are “footprints” that the selective force has left behind in the human genome. In this study, Yu et al. identified an extremely large region on Chromosome 12 that is under positive selection in Utah residents with European ancestry by characterizing the correlation patterns of genomic variants. Further analyses on this interval suggested that selection centered on one of the many forms of Spinocerebellar ataxia type-2 (SCA2) gene. The selected form was next demonstrated to associate with one short version of the disease-causing CAG repeat in the SCA2 gene. These results suggest that the CAG repeat was positively selected. An abnormally long version of CAGs can cause SCA2, a neurodegenerative disease that severely impairs the abilities of body movement. The authors showed how they unraveled natural selection acting on the SCA2 gene. Their findings might lead to the discovery of the biological functions of this gene and its CAG repeat. This kind of study holds potential to facilitate the finding of common disease genes.

Background Rhesus macaques are the most widely utilized nonhuman primate model in biomedical research. Previous efforts have validated fewer than 900 single nucleotide polymorphisms (SNPs) in this species, which limits opportunities for genetic studies related to health and disease. Extensive information about SNPs and other genetic variation in rhesus macaques would facilitate valuable genetic analyses, as well as provide markers for genome-wide linkage analysis and the genetic management of captive breeding colonies. Results We used the available rhesus macaque draft genome sequence, new sequence data from unrelated individuals and existing published sequence data to create a genome-wide SNP resource for Indian-origin rhesus monkeys. The original reference animal and two additional Indian-origin individuals were resequenced to low coverage using SOLiD™ sequencing. We then used three strategies to validate SNPs: comparison of potential SNPs found in the same individual using two different sequencing chemistries, and comparison of potential SNPs in different individuals identified with either the same or different sequencing chemistries. Our approach validated approximately 3 million SNPs distributed across the genome. Preliminary analysis of SNP annotations suggests that a substantial number of these macaque SNPs may have functional effects. More than 700 non-synonymous SNPs were scored by Polyphen-2 as either possibly or probably damaging to protein function and these variants now constitute potential models for studying functional genetic variation relevant to human physiology and disease. Conclusions Resequencing of a small number of animals identified greater than 3 million SNPs. This provides a significant new information resource for rhesus macaques, an important research animal. The data also suggests that overall genetic variation is high in this species. We identified many potentially damaging non-synonymous coding SNPs, providing new opportunities to identify rhesus models for human disease.

Background Rare coding variants constitute an important class of human genetic variation, but are underrepresented in current databases that are based on small population samples. Recent studies show that variants altering amino acid sequence and protein function are enriched at low variant allele frequency, 2 to 5%, but because of insufficient sample size it is not clear if the same trend holds for rare variants below 1% allele frequency. Results The 1000 Genomes Exon Pilot Project has collected deep-coverage exon-capture data in roughly 1,000 human genes, for nearly 700 samples. Although medical whole-exome projects are currently afoot, this is still the deepest reported sampling of a large number of human genes with next-generation technologies. According to the goals of the 1000 Genomes Project, we created effective informatics pipelines to process and analyze the data, and discovered 12,758 exonic SNPs, 70% of them novel, and 74% below 1% allele frequency in the seven population samples we examined. Our analysis confirms that coding variants below 1% allele frequency show increased population-specificity and are enriched for functional variants. Conclusions This study represents a large step toward detecting and interpreting low frequency coding variation, clearly lays out technical steps for effective analysis of DNA capture data, and articulates functional and population properties of this important class of genetic variation.