Detecting and estimating contamination of human DNA samples in sequencing and array-based genotype data.

DNA sample contamination is a serious problem in DNA sequencing studies and may result in systematic genotype misclassification and false positive associations. Although methods exist to detect and filter out cross-species contamination, few methods to detect within-species sample contamination are available. In this paper, we describe methods to identify within-species DNA sample contamination based on (1) a combination of sequencing reads and array-based genotype data, (2) sequence reads alone, and (3) array-based genotype data alone. Analysis of sequencing reads allows contamination detection after sequence data is generated but prior to variant calling; analysis of array-based genotype data allows contamination detection prior to generation of costly sequence data. Through a combination of analysis of in silico and experimentally contaminated samples, we show that our methods can reliably detect and estimate levels of contamination as low as 1%. We evaluate the impact of DNA contamination on genotype accuracy and propose effective strategies to screen for and prevent DNA contamination in sequencing studies.

Large-scale allelotype of pancreaticobiliary carcinoma provides quantitative estimates of genome-wide allelic loss.

Studies of the allelotype of human cancers have provided valuable insights into those chromosomes targeted for genetic inactivation during tumorigenesis. We present the comprehensive allelotype of 82 xenografted pancreatic or biliary cancers using 386 microsatellite markers and spanning the entire genome at an average coverage of 10 cM. Allelic losses were nonrandomly distributed across the genome and most prevalent for chromosome arms 9p, 17p, and 18q (>60%), sites of the known tumor suppressor genes CDKN2A, TP53, and MADH4. Moderate rates of loss (at any one locus) were noted for chromosome arms 3p, 6q, 8p, 17q, 18p, 21q, and 22q (40-60%). A mapping of individual loci of allelic loss revealed 11 "hot spots" of loss of heterozygosity (>30%) in addition to loci near known tumor suppressor genes, corresponding to 3p, 4q, 5q, 6q, 8p, 12q, 14q, 21q, 22q, and the X chromosome. The average genomic fractional allelic loss was 15.3% of all tested markers for the 82 xenografted cancers, with allelic loss affecting as little as 1.5% to as much as 32.1% of tested loci, a remarkable 20-fold range. We determined the chromosome location (in cM) of each of the 386 markers used based on mapping data available from the National Center for Biotechnology Information, and we provide the first distance-based estimates of chromosome material lost in a human epithelial cancer. Specifically, we found that the cumulative size of allelic losses ranged from 58 to 1160 cM, with an average loss of 561.32 cM/tumor. We compared the genomic fractional allelic loss of each xenografted cancer with known clinicopathological features for each patient and found a significant correlation with smoking status (P < 0.01). These findings offer new loci for investigation of the genetic alterations common to pancreaticobiliary cancers and aid the understanding of mechanisms of allelic loss in human carcinogenesis.

Novel genetic locus implicated for HIV-1 acquisition with putative regulatory links to HIV replication and infectivity: a genome-wide association study.

Fifty percent of variability in HIV-1 susceptibility is attributable to host genetics. Thus identifying genetic associations is essential to understanding pathogenesis of HIV-1 and important for targeting drug development. To date, however, CCR5 remains the only gene conclusively associated with HIV acquisition. To identify novel host genetic determinants of HIV-1 acquisition, we conducted a genome-wide association study among a high-risk sample of 3,136 injection drug users (IDUs) from the Urban Health Study (UHS). In addition to being IDUs, HIV-controls were frequency-matched to cases on environmental exposures to enhance detection of genetic effects. We tested independent replication in the Women's Interagency HIV Study (N=2,533). We also examined publicly available gene expression data to link SNPs associated with HIV acquisition to known mechanisms affecting HIV replication/infectivity. Analysis of the UHS nominated eight genetic regions for replication testing. SNP rs4878712 in FRMPD1 met multiple testing correction for independent replication (P=1.38x10(-4)), although the UHS-WIHS meta-analysis p-value did not reach genome-wide significance (P=4.47x10(-7) vs. P<5.0x10(-8)) Gene expression analyses provided promising biological support for the protective G allele at rs4878712 lowering risk of HIV: (1) the G allele was associated with reduced expression of FBXO10 (r=-0.49, P=6.9x10(-5)); (2) FBXO10 is a component of the Skp1-Cul1-F-box protein E3 ubiquitin ligase complex that targets Bcl-2 protein for degradation; (3) lower FBXO10 expression was associated with higher BCL2 expression (r=-0.49, P=8x10(-5)); (4) higher basal levels of Bcl-2 are known to reduce HIV replication and infectivity in human and animal in vitro studies. These results suggest new potential biological pathways by which host genetics affect susceptibility to HIV upon exposure for follow-up in subsequent studies.

Mutations in Alström protein impair terminal differentiation of cardiomyocytes.

Cardiomyocyte cell division and replication in mammals proceed through embryonic development and abruptly decline soon after birth. The process governing cardiomyocyte cell cycle arrest is poorly understood. Here we carry out whole-exome sequencing in an infant with evidence of persistent postnatal cardiomyocyte replication to determine the genetic risk factors. We identify compound heterozygous ALMS1 mutations in the proband, and confirm their presence in her affected sibling, one copy inherited from each heterozygous parent. Next, we recognize homozygous or compound heterozygous truncating mutations in ALMS1 in four other children with high levels of postnatal cardiomyocyte proliferation. Alms1 mRNA knockdown increases multiple markers of proliferation in cardiomyocytes, the percentage of cardiomyocytes in G2/M phases, and the number of cardiomyocytes by 10% in cultured cells. Homozygous Alms1-mutant mice have increased cardiomyocyte proliferation at 2 weeks postnatal compared with wild-type littermates. We conclude that deficiency of Alström protein impairs postnatal cardiomyocyte cell cycle arrest.

Imputation-based genomic coverage assessments of current human genotyping arrays.

Microarray single-nucleotide polymorphism genotyping, combined with imputation of untyped variants, has been widely adopted as an efficient means to interrogate variation across the human genome. "Genomic coverage" is the total proportion of genomic variation captured by an array, either by direct observation or through an indirect means such as linkage disequilibrium or imputation. We have performed imputation-based genomic coverage assessments of eight current genotyping arrays that assay from ~0.3 to ~5 million variants. Coverage was determined separately in each of the four continental ancestry groups in the 1000 Genomes Project phase 1 release. We used the subset of 1000 Genomes variants present on each array to impute the remaining variants and assessed coverage based on correlation between imputed and observed allelic dosages. More than 75% of common variants (minor allele frequency > 0.05) are covered by all arrays in all groups except for African ancestry, and up to ~90% in all ancestries for the highest density arrays. In contrast, less than 40% of less common variants (0.01 < minor allele frequency < 0.05) are covered by low density arrays in all ancestries and 50-80% in high density arrays, depending on ancestry. We also calculated genome-wide power to detect variant-trait association in a case-control design, across varying sample sizes, effect sizes, and minor allele frequency ranges, and compare these array-based power estimates with a hypothetical array that would type all variants in 1000 Genomes. These imputation-based genomic coverage and power analyses are intended as a practical guide to researchers planning genetic studies.

Exome array analysis identifies new loci and low-frequency variants influencing insulin processing and secretion.

Insulin secretion has a crucial role in glucose homeostasis, and failure to secrete sufficient insulin is a hallmark of type 2 diabetes. Genome-wide association studies (GWAS) have identified loci contributing to insulin processing and secretion; however, a substantial fraction of the genetic contribution remains undefined. To examine low-frequency (minor allele frequency (MAF) 0.5-5%) and rare (MAF < 0.5%) nonsynonymous variants, we analyzed exome array data in 8,229 nondiabetic Finnish males using the Illumina HumanExome Beadchip. We identified low-frequency coding variants associated with fasting proinsulin concentrations at the SGSM2 and MADD GWAS loci and three new genes with low-frequency variants associated with fasting proinsulin or insulinogenic index: TBC1D30, KANK1 and PAM. We also show that the interpretation of single-variant and gene-based tests needs to consider the effects of noncoding SNPs both nearby and megabases away. This study demonstrates that exome array genotyping is a valuable approach to identify low-frequency variants that contribute to complex traits.