Systematic assessment of copy number variant detection via genome-wide SNP genotyping

SNP genotyping has emerged as a technology to incorporate copy number variants (CNVs) into genetic analyses of human traits. However, the extent to which SNP platforms accurately capture CNVs remains unclear. Using independent, sequence-based CNV maps, we find that commonly used SNP platforms have limited or no probe coverage for a large fraction of CNVs. Despite this, in 9 samples we inferred 368 CNVs using Illumina SNP genotyping data and experimentally validated over two-thirds of these. We also developed a method (SNP-Conditional Mixture Modeling, SCIMM) to robustly genotype deletions using as few as two SNP probes. We find that HapMap SNPs are strongly correlated with 82% of common deletions, but the newest SNP platforms effectively tag about 50%. We conclude that currently available genome-wide SNP assays can capture CNVs accurately, but improvements in array designs, particularly in duplicated sequences, are necessary to facilitate more comprehensive analyses of genomic variation.     

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.     

A genome-wide map of diversity in Plasmodium falciparum

Genetic variation allows the malaria parasite Plasmodium falciparum to overcome chemotherapeutic agents, vaccines and vector control strategies and remain a leading cause of global morbidity and mortality. Here we describe an initial survey of genetic variation across the P. falciparum genome. We performed extensive sequencing of 16 geographically diverse parasites and identified 46,937 SNPs, demonstrating rich diversity among P. falciparum parasites (pi = 1.16 x 10(-3)) and strong correlation with gene function. We identified multiple regions with signatures of selective sweeps in drug-resistant parasites, including a previously unidentified 160-kb region with extremely low polymorphism in pyrimethamine-resistant parasites. We further characterized 54 worldwide isolates by genotyping SNPs across 20 genomic regions. These data begin to define population structure among African, Asian and American groups and illustrate the degree of linkage disequilibrium, which extends over relatively short distances in African parasites but over longer distances in Asian parasites. We provide an initial map of genetic diversity in P. falciparum and demonstrate its potential utility in identifying genes subject to recent natural selection and in understanding the population genetics of this parasite.     

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 genome-wide association meta-analysis identifies new childhood obesity loci

Multiple genetic variants have been associated with adult obesity and a few with severe obesity in childhood; however, less progress has been made in establishing genetic influences on common early-onset obesity. We performed a North American, Australian and European collaborative meta-analysis of 14 studies consisting of 5,530 cases (≥95th percentile of body mass index (BMI)) and 8,318 controls (<50th percentile of BMI) of European ancestry. Taking forward the eight newly discovered signals yielding association with P < 5 × 10(-6) in nine independent data sets (2,818 cases and 4,083 controls), we observed two loci that yielded genome-wide significant combined P values near OLFM4 at 13q14 (rs9568856; P = 1.82 × 10(-9); odds ratio (OR) = 1.22) and within HOXB5 at 17q21 (rs9299; P = 3.54 × 10(-9); OR = 1.14). Both loci continued to show association when two extreme childhood obesity cohorts were included (2,214 cases and 2,674 controls). These two loci also yielded directionally consistent associations in a previous meta-analysis of adult BMI(1).     

Estimate of human gene number provided by genome-wide analysis using Tetraodon nigroviridis DNA sequence

The number of genes in the human genome is unknown, with estimates ranging from 50,000 to 90,000 (refs 1, 2), and to more than 140,000 according to unpublished sources. We have developed 'Exofish', a procedure based on homology searches, to identify human genes quickly and reliably. This method relies on the sequence of another vertebrate, the pufferfish Tetraodon nigroviridis, to detect conserved sequences with a very low background. Similar to Fugu rubripes, a marine pufferfish proposed by Brenner et al. as a model for genomic studies, T. nigroviridis is a more practical alternative with a genome also eight times more compact than that of human. Many comparisons have been made between F. rubripes and human DNA that demonstrate the potential of comparative genomics using the pufferfish genome. Application of Exofish to the December version of the working draft sequence of the human genome and to Unigene showed that the human genome contains 28,000-34,000 genes, and that Unigene contains less than 40% of the protein-coding fraction of the human genome.     

A genome-wide association study of metabolic traits in human urine

We present a genome-wide association study of metabolic traits in human urine, designed to investigate the detoxification capacity of the human body. Using NMR spectroscopy, we tested for associations between 59 metabolites in urine from 862 male participants in the population-based SHIP study. We replicated the results using 1,039 additional samples of the same study, including a 5-year follow-up, and 992 samples from the independent KORA study. We report five loci with joint P values of association from 3.2 × 10(-19) to 2.1 × 10(-182). Variants at three of these loci have previously been linked with important clinical outcomes: SLC7A9 is a risk locus for chronic kidney disease, NAT2 for coronary artery disease and genotype-dependent response to drug toxicity, and SLC6A20 for iminoglycinuria. Moreover, we identify rs37369 in AGXT2 as the genetic basis of hyper-β-aminoisobutyric aciduria.     

A genome-wide association study identifies susceptibility loci for Wilms tumor

Wilms tumor is the most common renal malignancy of childhood. To identify common variants that confer susceptibility to Wilms tumor, we conducted a genome-wide association study in 757 individuals with Wilms tumor (cases) and 1,879 controls. We evaluated ten SNPs in regions significantly associated at P < 5 × 10(-5) in two independent replication series from the UK (769 cases and 2,814 controls) and the United States (719 cases and 1,037 controls). We identified clear significant associations at 2p24 (rs3755132, P = 1.03 × 10(-14); rs807624, P = 1.32 × 10(-14)) and 11q14 (rs790356, P = 4.25 × 10(-15)). Both regions contain genes that are plausibly related to Wilms tumorigenesis. We also identified candidate association signals at 5q14, 22q12 and Xp22.     

A genome-wide association study identifies six susceptibility loci for chronic lymphocytic leukemia

We conducted a genome-wide association study of 299,983 tagging SNPs for chronic lymphocytic leukemia (CLL) and performed validation in two additional series totaling 1,529 cases and 3,115 controls. We identified six previously unreported CLL risk loci at 2q13 (rs17483466; P = 2.36 x 10(-10)), 2q37.1 (rs13397985, SP140; P = 5.40 x 10(-10)), 6p25.3 (rs872071, IRF4; P = 1.91 x 10(-20)), 11q24.1 (rs735665; P = 3.78 x 10(-12)), 15q23 (rs7176508; P = 4.54 x 10(-12)) and 19q13.32 (rs11083846, PRKD2; P = 3.96 x 10(-9)). These data provide the first evidence for the existence of common, low-penetrance susceptibility to a hematological malignancy and new insights into disease causation in CLL.     

A genome-wide association study identifies three new risk loci for Kawasaki disease

We performed a genome-wide association study (GWAS) of Kawasaki disease in Japanese subjects using data from 428 individuals with Kawasaki disease (cases) and 3,379 controls genotyped at 473,803 SNPs. We validated the association results in two independent replication panels totaling 754 cases and 947 controls. We observed significant associations in the FAM167A-BLK region at 8p22-23 (rs2254546, P = 8.2 × 10(-21)), in the human leukocyte antigen (HLA) region at 6p21.3 (rs2857151, P = 4.6 × 10(-11)) and in the CD40 region at 20q13 (rs4813003, P = 4.8 × 10(-8)). We also replicated the association of a functional SNP of FCGR2A (rs1801274, P = 1.6 × 10(-6)) identified in a recently reported GWAS of Kawasaki disease. Our findings provide new insights into the pathogenesis and pathophysiology of Kawasaki disease.     

A new multipoint method for genome-wide association studies by imputation of genotypes

Genome-wide association studies are set to become the method of choice for uncovering the genetic basis of human diseases. A central challenge in this area is the development of powerful multipoint methods that can detect causal variants that have not been directly genotyped. We propose a coherent analysis framework that treats the problem as one involving missing or uncertain genotypes. Central to our approach is a model-based imputation method for inferring genotypes at observed or unobserved SNPs, leading to improved power over existing methods for multipoint association mapping. Using real genome-wide association study data, we show that our approach (i) is accurate and well calibrated, (ii) provides detailed views of associated regions that facilitate follow-up studies and (iii) can be used to validate and correct data at genotyped markers. A notable future use of our method will be to boost power by combining data from genome-wide scans that use different SNP sets.     

A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci

We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10?12) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10?11) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10??) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10?11) and a tag SNP for NAT2 acetylation status (P = 4 × 10?11), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis.     

A genome-wide association study identifies two new risk loci for Graves' disease

Graves' disease is a common autoimmune disorder characterized by thyroid stimulating hormone receptor autoantibodies (TRAb) and hyperthyroidism. To investigate the genetic architecture of Graves' disease, we conducted a genome-wide association study in 1,536 individuals with Graves' disease (cases) and 1,516 controls. We further evaluated a group of associated SNPs in a second set of 3,994 cases and 3,510 controls. We confirmed four previously reported loci (in the major histocompatibility complex, TSHR, CTLA4 and FCRL3) and identified two new susceptibility loci (the RNASET2-FGFR1OP-CCR6 region at 6q27 (P(combined) = 6.85 × 10(-10) for rs9355610) and an intergenic region at 4p14 (P(combined) = 1.08 × 10(-13) for rs6832151)). These newly associated SNPs were correlated with the expression levels of RNASET2 at 6q27, of CHRNA9 and of a previously uncharacterized gene at 4p14, respectively. Moreover, we identified strong associations of TSHR and major histocompatibility complex class II variants with persistently TRAb-positive Graves' disease.     

A mixed-model approach for genome-wide association studies of correlated traits in structured populations

Genome-wide association studies (GWAS) are a standard approach for studying the genetics of natural variation. A major concern in GWAS is the need to account for the complicated dependence structure of the data, both between loci as well as between individuals. Mixed models have emerged as a general and flexible approach for correcting for population structure in GWAS. Here, we extend this linear mixed-model approach to carry out GWAS of correlated phenotypes, deriving a fully parameterized multi-trait mixed model (MTMM) that considers both the within-trait and between-trait variance components simultaneously for multiple traits. We apply this to data from a human cohort for correlated blood lipid traits from the Northern Finland Birth Cohort 1966 and show greatly increased power to detect pleiotropic loci that affect more than one blood lipid trait. We also apply this approach to an Arabidopsis thaliana data set for flowering measurements in two different locations, identifying loci whose effect depends on the environment.     

A genome-wide association study identifies three loci associated with susceptibility to uterine fibroids

Uterine fibroids are a common benign tumor of the female genital tract. We conducted a genome-wide association study in which 457,044 SNPs were analyzed in 1,607 individuals with clinically diagnosed uterine fibroids and 1,428 female controls. SNPs showing suggestive associations (P < 5 × 10(-5)) were further genotyped in 3,466 additional cases and 3,245 female controls. Three loci on chromosomes 10q24.33, 22q13.1 and 11p15.5 revealed genome-wide significant associations with uterine fibroids. The SNPs showing the most significant association in a combination analysis at each of these loci were rs7913069 (P = 8.65 × 10(-14), odds ratio (OR) = 1.47), rs12484776 (P = 2.79 × 10(-12), OR = 1.23) and rs2280543 (P = 3.82 × 10(-12), OR = 1.39), respectively. Subsequent fine mapping of these regions will be necessary to pinpoint the causal variants. Our findings should shed light on the pathogenesis of uterine fibroids.