De novo assembly and genotyping of variants using colored de Bruijn graphs

Detecting genetic variants that are highly divergent from a reference sequence remains a major challenge in genome sequencing. We introduce de novo assembly algorithms using colored de Bruijn graphs for detecting and genotyping simple and complex genetic variants in an individual or population. We provide an efficient software implementation, Cortex, the first de novo assembler capable of assembling multiple eukaryotic genomes simultaneously. Four applications of Cortex are presented. First, we detect and validate both simple and complex structural variations in a high-coverage human genome. Second, we identify more than 3 Mb of sequence absent from the human reference genome, in pooled low-coverage population sequence data from the 1000 Genomes Project. Third, we show how population information from ten chimpanzees enables accurate variant calls without a reference sequence. Last, we estimate classical human leukocyte antigen (HLA) genotypes at HLA-B, the most variable gene in the human genome.     

A high-resolution survey of deletion polymorphism in the human genome

Recent work has shown that copy number polymorphism is an important class of genetic variation in human genomes. Here we report a new method that uses SNP genotype data from parent-offspring trios to identify polymorphic deletions. We applied this method to data from the International HapMap Project to produce the first high-resolution population surveys of deletion polymorphism. Approximately 100 of these deletions have been experimentally validated using comparative genome hybridization on tiling-resolution oligonucleotide microarrays. Our analysis identifies a total of 586 distinct regions that harbor deletion polymorphisms in one or more of the families. Notably, we estimate that typical individuals are hemizygous for roughly 30-50 deletions larger than 5 kb, totaling around 550-750 kb of euchromatic sequence across their genomes. The detected deletions span a total of 267 known and predicted genes. Overall, however, the deleted regions are relatively gene-poor, consistent with the action of purifying selection against deletions. Deletion polymorphisms may well have an important role in the genetics of complex traits; however, they are not directly observed in most current gene mapping studies. Our new method will permit the identification of deletion polymorphisms in high-density SNP surveys of trio or other family data.     

Complex SNP-related sequence variation in segmental genome duplications

There is uncertainty about the true nature of predicted single-nucleotide polymorphisms (SNPs) in segmental duplications (duplicons) and whether these markers genuinely exist at increased density as indicated in public databases. We explored these issues by genotyping 157 predicted SNPs in duplicons and control regions in normal diploid genomes and fully homozygous complete hydatidiform moles. Our data identified many true SNPs in duplicon regions and few paralogous sequence variants. Twenty-eight percent of the polymorphic duplicon sequences we tested involved multisite variation, a new type of polymorphism representing the sum of the signals from many individual duplicon copies that vary in sequence content due to duplication, deletion or gene conversion. Multisite variations can masquerade as normal SNPs when genotyped. Given that duplicons comprise at least 5% of the genome and many are yet to be annotated in the genome draft, effective strategies to identify multisite variation must be established and deployed.     

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.     

A framework for variation discovery and genotyping using next-generation DNA sequencing data

Recent advances in sequencing technology make it possible to comprehensively catalog genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious, and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (i) initial read mapping; (ii) local realignment around indels; (iii) base quality score recalibration; (iv) SNP discovery and genotyping to find all potential variants; and (v) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We here discuss the application of these tools, instantiated in the Genome Analysis Toolkit, to deep whole-genome, whole-exome capture and multi-sample low-pass (～4×) 1000 Genomes Project datasets.     

Reliable identification of large numbers of candidate SNPs from public EST data

High-resolution genetic analysis of the human genome promises to provide insight into common disease susceptibility. To perform such analysis will require a collection of high-throughput, high-density analysis reagents. We have developed a polymorphism detection system that uses public-domain sequence data. This detection system is called the single nucleotide polymorphism pipeline (SNPpipeline). The analytic core of the SNPpipeline is composed of three components: PHRED, PHRAP and DEMIGLACE. PHRED and PHRAP are components of a sequence analysis suite developed to perform the semi-automated analysis required for large-scale genomes (provided courtesy of P. Green). Using these informatics tools, which examine redundant raw expressed sequence tag (EST) data, we have identified more than 3,000 candidate single-nucleotide polymorphisms (SNPs). Empiric validation studies of a set of 192 candidates indicate that 82% identify variation in a sample of ten Centre d'Etudes Polymorphism Humain (CEPH) individuals. Our results suggest that existing sequence resources may serve as a valuable source for identifying genetic variation.     

Fast and accurate genotype imputation in genome-wide association studies through pre-phasing

The 1000 Genomes Project and disease-specific sequencing efforts are producing large collections of haplotypes that can be used as reference panels for genotype imputation in genome-wide association studies (GWAS). However, imputing from large reference panels with existing methods imposes a high computational burden. We introduce a strategy called 'pre-phasing' that maintains the accuracy of leading methods while reducing computational costs. We first statistically estimate the haplotypes for each individual within the GWAS sample (pre-phasing) and then impute missing genotypes into these estimated haplotypes. This reduces the computational cost because (i) the GWAS samples must be phased only once, whereas standard methods would implicitly repeat phasing with each reference panel update, and (ii) it is much faster to match a phased GWAS haplotype to one reference haplotype than to match two unphased GWAS genotypes to a pair of reference haplotypes. We implemented our approach in the MaCH and IMPUTE2 frameworks, and we tested it on data sets from the Wellcome Trust Case Control Consortium 2 (WTCCC2), the Genetic Association Information Network (GAIN), the Women's Health Initiative (WHI) and the 1000 Genomes Project. This strategy will be particularly valuable for repeated imputation as reference panels evolve.     

Fine-scale structural variation of the human genome

Inversions, deletions and insertions are important mediators of disease and disease susceptibility. We systematically compared the human genome reference sequence with a second genome (represented by fosmid paired-end sequences) to detect intermediate-sized structural variants >8 kb in length. We identified 297 sites of structural variation: 139 insertions, 102 deletions and 56 inversion breakpoints. Using combined literature, sequence and experimental analyses, we validated 112 of the structural variants, including several that are of biomedical relevance. These data provide a fine-scale structural variation map of the human genome and the requisite sequence precision for subsequent genetic studies of human disease.     

Human genome sequence variation and the influence of gene history,mutation and recombination

Variation in the human genome sequence is key to understanding susceptibility to disease in modern populations and the history of ancestral populations. Unlocking this information requires knowledge of the patterns and underlying causes of human sequence diversity. By applying a new population-genetic framework to two genome-wide polymorphism surveys, we find that the human genome contains sizeable regions (stretching over tens of thousands of base pairs) that have intrinsically high and low rates of sequence variation. We show that the primary determinant of these patterns is shared genealogical history. Only a fraction of the variation (at most 25%) is due to the local mutation rate. By measuring the average distance over which genealogical histories are typically preserved, these data provide the first genome-wide estimate of the average extent of correlation among variants (linkage disequilibrium). The results are best explained by extreme variability in the recombination rate at a fine scale, and provide the first empirical evidence that such recombination 'hot spots' are a general feature of the human genome and have a principal role in shaping genetic variation in the human population.     

Distribution and functional impact of DNA copy number variation in the rat

The abundance and dynamics of copy number variants (CNVs) in mammalian genomes poses new challenges in the identification of their impact on natural and disease phenotypes. We used computational and experimental methods to catalog CNVs in rat and found that they share important functional characteristics with those in human. In addition, 113 one-to-one orthologous genes overlap CNVs in both human and rat, 80 of which are implicated in human disease. CNVs are nonrandomly distributed throughout the genome. Chromosome 18 is a cold spot for CNVs as well as evolutionary rearrangements and segmental duplications, suggesting stringent selective mechanisms underlying CNV genesis or maintenance. By exploiting gene expression data available for rat recombinant inbred lines, we established the functional relationship of CNVs underlying 22 expression quantitative trait loci. These characteristics make the rat an excellent model for studying phenotypic effects of structural variation in relation to human complex traits and disease.     

Dense genotyping identifies and localizes multiple common and rare variant association signals in celiac disease

Using variants from the 1000 Genomes Project pilot European CEU dataset and data from additional resequencing studies, we densely genotyped 183 non-HLA risk loci previously associated with immune-mediated diseases in 12,041 individuals with celiac disease (cases) and 12,228 controls. We identified 13 new celiac disease risk loci reaching genome-wide significance, bringing the number of known loci (including the HLA locus) to 40. We found multiple independent association signals at over one-third of these loci, a finding that is attributable to a combination of common, low-frequency and rare genetic variants. Compared to previously available data such as those from HapMap3, our dense genotyping in a large sample collection provided a higher resolution of the pattern of linkage disequilibrium and suggested localization of many signals to finer scale regions. In particular, 29 of the 54 fine-mapped signals seemed to be localized to single genes and, in some instances, to gene regulatory elements. Altogether, we define the complex genetic architecture of the risk regions of and refine the risk signals for celiac disease, providing the next step toward uncovering the causal mechanisms of the disease.     

Sequence variation in the human angiotensin converting enzyme.

Angiotensin converting enzyme (encoded by the gene DCP1, also known as ACE) catalyses the conversion of angiotensin I to the physiologically active peptide angiotensin II, which controls fluid-electrolyte balance and systemic blood pressure. Because of its key function in the renin-angiotensin system, many association studies have been performed with DCP1. Nearly all studies have associated the presence (insertion, I) or absence (deletion, D) of a 287-bp Alu repeat element in intron 16 with the levels of circulating enzyme or cardiovascular pathophysiologies. Many epidemiological studies suggest that the DCP1*D allele confers increased susceptibility to cardiovascular disease; however, other reports have found no such association or even a beneficial effect. We present here the complete genomic sequence of DCP1 from 11 individuals, representing the longest contiguous scan (24 kb) for sequence variation in human DNA. We identified 78 varying sites in 22 chromosomes that resolved into 13 distinct haplotypes. Of the variant sites, 17 were in absolute linkage disequilibrium with the commonly typed Alu insertion/deletion polymorphism, producing two distinct and distantly related clades. We also identified a major subdivision in the Alu deletion clade that enables further analysis of the traits associated with this gene. The diversity uncovered in DCP1 is comparable to that described for other regions in the human genome. The highly correlated structure in DCP1 raises important issues for the determination of functional DNA variants within genes and genetic studies in humans based on marker association.     

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.     

Genome-wide association study identifies susceptibility loci for IgA nephropathy

We carried out a genome-wide association study of IgA nephropathy, a major cause of kidney failure worldwide. We studied 1,194 cases and 902 controls of Chinese Han ancestry, with targeted follow up in Chinese and European cohorts comprising 1,950 cases and 1,920 controls. We identified three independent loci in the major histocompatibility complex, as well as a common deletion of CFHR1 and CFHR3 at chromosome 1q32 and a locus at chromosome 22q12 that each surpassed genome-wide significance (P values for association between 1.59 × 10?2? and 4.84 × 10?? and minor allele odds ratios of 0.63-0.80). These five loci explain 4-7% of the disease variance and up to a tenfold variation in interindividual risk. Many of the alleles that protect against IgA nephropathy impart increased risk for other autoimmune or infectious diseases, and IgA nephropathy risk allele frequencies closely parallel the variation in disease prevalence among Asian, European and African populations, suggesting complex selective pressures.     

Detection of regulatory variation in mouse genes

Functional polymorphism in genes can be classified as coding variation, altering the amino-acid sequence of the encoded protein, or regulatory variation, affecting the level or pattern of expression of the gene. Coding variation can be recognized directly from DNA sequence, and consequently its frequency and characteristics have been extensively described. By contrast, virtually nothing is known about the extent to which gene regulation varies in populations. Yet it is likely that regulatory variants are important in modulating gene function: alterations in gene regulation have been proposed to influence disease susceptibility and to have been the primary substrate for the evolution of species. Here, we report a systematic study to assess the extent of cis-acting regulatory variation in 69 genes across four inbred mouse strains. We find that at least four of these genes show allelic differences in expression level of 1.5-fold or greater, and that some of these differences are tissue specific. The results show that the impact of regulatory variants can be detected at a significant frequency in a genomic survey and suggest that such variation may have important consequences for organismal phenotype and evolution. The results indicate that larger-scale surveys in both mouse and human could identify a substantial number of genes with common regulatory variation.     

High mutation rates have driven extensive structural polymorphism among human Y chromosomes

Although much structural polymorphism in the human genome has been catalogued, the kinetics of underlying change remain largely unexplored. Because human Y chromosomes are clonally inherited, it has been possible to capture their detailed relationships in a robust, worldwide genealogical tree. Examination of structural variation across this tree opens avenues for investigating rates of underlying mutations. We selected one Y chromosome from each of 47 branches of this tree and searched for large-scale variation. Four chromosomal regions showed extensive variation resulting from numerous large-scale mutations. Within the tree encompassed by the studied chromosomes, the distal-Yq heterochromatin changed length > or = 12 times, the TSPY gene array changed length > or = 23 times, the 3.6-Mb IR3/IR3 region changed orientation > or = 12 times and the AZFc region was rearranged > or = 20 times. After determining the total time spanned by all branches of this tree (approximately 1.3 million years or 52,000 generations), we converted these mutation counts to lower bounds on rates: > or = 2.3 x 10(-4), > or = 4.4 x 10(-4), > or = 2.3 x 10(-4) and > or = 3.8 x 10(-4) large-scale mutations per father-to-son Y transmission, respectively. Thus, high mutation rates have driven extensive structural polymorphism among human Y chromosomes. At the same time, we found limited variation in the copy number of Y-linked genes, which raises the possibility of selective constraints.     

Homology-based annotation yields 1,042 new candidate genes in the Drosophila melanogaster genome

The approach to annotating a genome critically affects the number and accuracy of genes identified in the genome sequence. Genome annotation based on stringent gene identification is prone to underestimate the complement of genes encoded in a genome. In contrast, over-prediction of putative genes followed by exhaustive computational sequence, motif and structural homology search will find rarely expressed, possibly unique, new genes at the risk of including non-functional genes. We developed a two-stage approach that combines the merits of stringent genome annotation with the benefits of over-prediction. First we identify plausible genes regardless of matches with EST, cDNA or protein sequences from the organism (stage 1). In the second stage, proteins predicted from the plausible genes are compared at the protein level with EST, cDNA and protein sequences, and protein structures from other organisms (stage 2). Remote but biologically meaningful protein sequence or structure homologies provide supporting evidence for genuine genes. The method, applied to the Drosophila melanogaster genome, validated 1,042 novel candidate genes after filtering 19,410 plausible genes, of which 12,124 matched the original 13,601 annotated genes. This annotation strategy is applicable to genomes of all organisms, including human.     

Common deletions and SNPs are in linkage disequilibrium in the human genome

Humans show great variation in phenotypic traits such as height, eye color and susceptibility to disease. Genomic DNA sequence differences among individuals are responsible for the inherited components of these complex traits. Reports suggest that intermediate and large-scale DNA copy number and structural variations are prevalent enough to be an important source of genetic variation between individuals. Because association studies to identify genomic loci associated with particular phenotypic traits have focused primarily on genotyping SNPs, it is important to determine whether common structural polymorphisms are in linkage disequilibrium with common SNPs, and thus can be assessed indirectly in SNP-based studies. Here we examine 100 deletion polymorphisms ranging from 70 bp to 7 kb. We show that common deletions and SNPs ascertained with similar criteria have essentially the same distribution of linkage disequilibrium with surrounding SNPs, indicating that these polymorphisms may share evolutionary history and that most deletion polymorphisms are effectively assayed by proxy in SNP-based association studies.