Jennifer Parla

A comparative analysis of exome capture

BackgroundHuman exome resequencing using commercial target capture kits has been and is being used for sequencing large numbers of individuals to search for variants associated with various human diseases. We rigorously evaluated the capabilities of two solution exome capture kits. These analyses help clarify the strengths and limitations of those data as well as systematically identify variables that should be considered in the use of those data.ResultsEach exome kit performed well at capturing the targets they were designed to capture, which mainly corresponds to the consensus coding sequences (CCDS) annotations of the human genome. In addition, based on their respective targets, each capture kit coupled with high coverage Illumina sequencing produced highly accurate nucleotide calls. However, other databases, such as the Reference Sequence collection (RefSeq), define the exome more broadly, and so not surprisingly, the exome kits did not capture these additional regions.ConclusionsCommercial exome capture kits provide a very efficient way to sequence select areas of the genome at very high accuracy. Here we provide the data to help guide critical analyses of sequencing data derived from these products.

Whole Genome Sequencing Defines the Genetic Heterogeneity of Familial Pancreatic Cancer

UNLABELLED Pancreatic cancer is projected to become the second leading cause of cancer-related death in the United States by 2020. A familial aggregation of pancreatic cancer has been established, but the cause of this aggregation in most families is unknown. To determine the genetic basis of susceptibility in these families, we sequenced the germline genomes of 638 patients with familial pancreatic cancer and the tumor exomes of 39 familial pancreatic adenocarcinomas. Our analyses support the role of previously identified familial pancreatic cancer susceptibility genes such as BRCA2, CDKN2A, and ATM, and identify novel candidate genes harboring rare, deleterious germline variants for further characterization. We also show how somatic point mutations that occur during hematopoiesis can affect the interpretation of genome-wide studies of hereditary traits. Our observations have important implications for the etiology of pancreatic cancer and for the identification of susceptibility genes in other common cancer types. SIGNIFICANCE The genetic basis of disease susceptibility in the majority of patients with familial pancreatic cancer is unknown. We whole genome sequenced 638 patients with familial pancreatic cancer and demonstrate that the genetic underpinning of inherited pancreatic cancer is highly heterogeneous. This has significant implications for the management of patients with familial pancreatic cancer.

Validation and assessment of variant calling pipelines for next-generation sequencing

BackgroundThe processing and analysis of the large scale data generated by next-generation sequencing (NGS) experiments is challenging and is a burgeoning area of new methods development. Several new bioinformatics tools have been developed for calling sequence variants from NGS data. Here, we validate the variant calling of these tools and compare their relative accuracy to determine which data processing pipeline is optimal.ResultsWe developed a unified pipeline for processing NGS data that encompasses four modules: mapping, filtering, realignment and recalibration, and variant calling. We processed 130 subjects from an ongoing whole exome sequencing study through this pipeline. To evaluate the accuracy of each module, we conducted a series of comparisons between the single nucleotide variant (SNV) calls from the NGS data and either gold-standard Sanger sequencing on a total of 700 variants or array genotyping data on a total of 9,935 single-nucleotide polymorphisms. A head to head comparison showed that Genome Analysis Toolkit (GATK) provided more accurate calls than SAMtools (positive predictive value of 92.55% vs. 80.35%, respectively). Realignment of mapped reads and recalibration of base quality scores before SNV calling proved to be crucial to accurate variant calling. GATK HaplotypeCaller algorithm for variant calling outperformed the UnifiedGenotype algorithm. We also showed a relationship between mapping quality, read depth and allele balance, and SNV call accuracy. However, if best practices are used in data processing, then additional filtering based on these metrics provides little gains and accuracies of >99% are achievable.ConclusionsOur findings will help to determine the best approach for processing NGS data to confidently call variants for downstream analyses. To enable others to implement and replicate our results, all of our codes are freely available at http://metamoodics.org/wes.

708 Common and 2010 rare DISC1 locus variants identified in 1542 subjects: analysis for association with psychiatric disorder and cognitive traits.

A balanced t(1;11) translocation that transects the Disrupted in schizophrenia 1 (DISC1) gene shows genome-wide significant linkage for schizophrenia and recurrent major depressive disorder (rMDD) in a single large Scottish family, but genome-wide and exome sequencing-based association studies have not supported a role for DISC1 in psychiatric illness. To explore DISC1 in more detail, we sequenced 528 kb of the DISC1 locus in 653 cases and 889 controls. We report 2718 validated single-nucleotide polymorphisms (SNPs) of which 2010 have a minor allele frequency of <1%. Only 38% of these variants are reported in the 1000 Genomes Project European subset. This suggests that many DISC1 SNPs remain undiscovered and are essentially private. Rare coding variants identified exclusively in patients were found in likely functional protein domains. Significant region-wide association was observed between rs16856199 and rMDD (P=0.026, unadjusted P=6.3 × 10−5, OR=3.48). This was not replicated in additional recurrent major depression samples (replication P=0.11). Combined analysis of both the original and replication set supported the original association (P=0.0058, OR=1.46). Evidence for segregation of this variant with disease in families was limited to those of rMDD individuals referred from primary care. Burden analysis for coding and non-coding variants gave nominal associations with diagnosis and measures of mood and cognition. Together, these observations are likely to generalise to other candidate genes for major mental illness and may thus provide guidelines for the design of future studies.

High-Throughput Sequencing

Publisher Summary Advances in DNA sequencing methods have a major impact on several biological fields, with microbiology being the first field to experience the benefits of knowing the exact sequence of a genome. This advantage held by the microbiology field was a result of the more compact nature of many microbial genomes, the long-standing history of microbes as model organisms in biological research, and the initial limitations of DNA sequencing chemistry and bioinformatic methods that restricted both the scale and the scope of genomic analysis. The whole genome sequencing of microbial life forms made it feasible to perform functional annotations of genomes and strengthened the motivation of the scientific community to sequence the genomes of several species of medical, environmental, evolutionary, and/or societal importance. With the invention of advanced DNA sequencing methods, exemplified by next-generation sequencers, biological sciences have again been presented with significant opportunities that had not been particularly feasible with more traditional methods. Microbiology has been able to benefit significantly from the functionality of next-generation sequencing. The massive data output of next-generation systems now enables scientists to use whole genome sequencing to identify a microbial isolate rapidly, as well as study microbial sequence variation without having to use various cloning and gene reporter techniques to help isolate the mutation(s) of interest. The independence of the next-generation workflow from microbiological culturing procedures has also promoted the success of metagenomic studies, the results of which have led to the reassessment of long-held scientific views regarding the diversity and interaction within microbial communities.

Exome Sequencing of Familial Bipolar Disorder

IMPORTANCE Complex disorders, such as bipolar disorder (BD), likely result from the influence of both common and rare susceptibility alleles. While common variation has been widely studied, rare variant discovery has only recently become feasible with next-generation sequencing. OBJECTIVE To utilize a combined family-based and case-control approach to exome sequencing in BD using multiplex families as an initial discovery strategy, followed by association testing in a large case-control meta-analysis. DESIGN, SETTING, AND PARTICIPANTS We performed exome sequencing of 36 affected members with BD from 8 multiplex families and tested rare, segregating variants in 3 independent case-control samples consisting of 3541 BD cases and 4774 controls. MAIN OUTCOMES AND MEASURES We used penalized logistic regression and 1-sided gene-burden analyses to test for association of rare, segregating damaging variants with BD. Permutation-based analyses were performed to test for overall enrichment with previously identified gene sets. RESULTS We found 84 rare (frequency <1%), segregating variants that were bioinformatically predicted to be damaging. These variants were found in 82 genes that were enriched for gene sets previously identified in de novo studies of autism (19 observed vs. 10.9 expected, P = .0066) and schizophrenia (11 observed vs. 5.1 expected, P = .0062) and for targets of the fragile X mental retardation protein (FMRP) pathway (10 observed vs. 4.4 expected, P = .0076). The case-control meta-analyses yielded 19 genes that were nominally associated with BD based either on individual variants or a gene-burden approach. Although no gene was individually significant after correction for multiple testing, this group of genes continued to show evidence for significant enrichment of de novo autism genes (6 observed vs 2.6 expected, P = .028). CONCLUSIONS AND RELEVANCE Our results are consistent with the presence of prominent locus and allelic heterogeneity in BD and suggest that very large samples will be required to definitively identify individual rare variants or genes conferring risk for this disorder. However, we also identify significant associations with gene sets composed of previously discovered de novo variants in autism and schizophrenia, as well as targets of the FRMP pathway, providing preliminary support for the overlap of potential autism and schizophrenia risk genes with rare, segregating variants in families with BD.

Establishing the baseline level of repetitive element expression in the human cortex

BackgroundAlthough nearly half of the human genome is comprised of repetitive sequences, the expression profile of these elements remains largely uncharacterized. Recently developed high throughput sequencing technologies provide us with a powerful new set of tools to study repeat elements. Hence, we performed whole transcriptome sequencing to investigate the expression of repetitive elements in human frontal cortex using postmortem tissue obtained from the Stanley Medical Research Institute.ResultsWe found a significant amount of reads from the human frontal cortex originate from repeat elements. We also noticed that Alu elements were expressed at levels higher than expected by random or background transcription. In contrast, L1 elements were expressed at lower than expected amounts.ConclusionsRepetitive elements are expressed abundantly in the human brain. This expression pattern appears to be element specific and can not be explained by random or background transcription. These results demonstrate that our knowledge about repetitive elements is far from complete. Further characterization is required to determine the mechanism, the control, and the effects of repeat element expression.

A hybrid likelihood model for sequence-based disease association studies.

In the past few years, case-control studies of common diseases have shifted their focus from single genes to whole exomes. New sequencing technologies now routinely detect hundreds of thousands of sequence variants in a single study, many of which are rare or even novel. The limitation of classical single-marker association analysis for rare variants has been a challenge in such studies. A new generation of statistical methods for case-control association studies has been developed to meet this challenge. A common approach to association analysis of rare variants is the burden-style collapsing methods to combine rare variant data within individuals across or within genes. Here, we propose a new hybrid likelihood model that combines a burden test with a test of the position distribution of variants. In extensive simulations and on empirical data from the Dallas Heart Study, the new model demonstrates consistently good power, in particular when applied to a gene set (e.g., multiple candidate genes with shared biological function or pathway), when rare variants cluster in key functional regions of a gene, and when protective variants are present. When applied to data from an ongoing sequencing study of bipolar disorder (191 cases, 107 controls), the model identifies seven gene sets with nominal p-values0.05, of which one MAPK signaling pathway (KEGG) reaches trend-level significance after correcting for multiple testing.

Assessment of Whole-Exome Sequence Data in Attempted Suicide within a Bipolar Disorder Cohort

Suicidal behavior is a complex and devastating phenotype with a heritable component that has not been fully explained by existing common genetic variant analyses. This study represents the first large-scale DNA sequencing project designed to assess the role of rare functional genetic variation in suicidal behavior risk. To accomplish this, whole-exome sequencing data for ∼19,000 genes were generated for 387 bipolar disorder subjects with a history of suicide attempt and 631 bipolar disorder subjects with no prior suicide attempts. Rare functional variants were assessed in all exome genes as well as pathways hypothesized to contribute to suicidal behavior risk. No result survived conservative Bonferroni correction, though many suggestive findings have arisen that merit additional attention. In addition, nominal support for past associations in genes, such as BDNF, and pathways, such as the hypothalamic-pituitary-adrenal axis, was also observed. Finally, a novel pathway was identified that is driven by aldehyde dehydrogenase genes. Ultimately, this investigation explores variation left largely untouched by existing efforts in suicidal behavior, providing a wealth of novel information to add to future investigations, such as meta-analyses.

Mutations in the pancreatic secretory enzymes CPA1 and CPB1 are associated with pancreatic cancer

Significance Much of the inherited susceptibility to pancreatic cancer remains unexplained. Germline variants that cause protein misfolding and impaired secretion of pancreatic enzymes such as CPA1 (encoding carboxypeptidase A1) can cause pancreatic acinar cell endoplasmic reticulum (ER) stress. We investigated the hypothesis that pancreatic cancer could arise from germline variants in genes encoding pancreatic secretory enzymes that induce pancreatic acinar cell stress. We find ∼1% of 1,579 patients with pancreatic cancer vs. 1 of 2,012 controls have germline variants in the genes encoding CPA1 and CPB1 (carboxypeptidase B1) that impair secretion of its protein product and induce ER stress. These findings implicate pancreatic acinar cell stress as a mechanism of pancreatic cancer susceptibility. To evaluate whether germline variants in genes encoding pancreatic secretory enzymes contribute to pancreatic cancer susceptibility, we sequenced the coding regions of CPB1 and other genes encoding pancreatic secretory enzymes and known pancreatitis susceptibility genes (PRSS1, CPA1, CTRC, and SPINK1) in a hospital series of pancreatic cancer cases and controls. Variants in CPB1, CPA1 (encoding carboxypeptidase B1 and A1), and CTRC were evaluated in a second set of cases with familial pancreatic cancer and controls. More deleterious CPB1 variants, defined as having impaired protein secretion and induction of endoplasmic reticulum (ER) stress in transfected HEK 293T cells, were found in the hospital series of pancreatic cancer cases (5/986, 0.5%) than in controls (0/1,045, P = 0.027). Among familial pancreatic cancer cases, ER stress-inducing CPB1 variants were found in 4 of 593 (0.67%) vs. 0 of 967 additional controls (P = 0.020), with a combined prevalence in pancreatic cancer cases of 9/1,579 vs. 0/2,012 controls (P < 0.01). More ER stress-inducing CPA1 variants were also found in the combined set of hospital and familial cases with pancreatic cancer than in controls [7/1,546 vs. 1/2,012; P = 0.025; odds ratio, 9.36 (95% CI, 1.15–76.02)]. Overall, 16 (1%) of 1,579 pancreatic cancer cases had an ER stress-inducing CPA1 or CPB1 variant, compared with 1 of 2,068 controls (P < 0.00001). No other candidate genes had statistically significant differences in variant prevalence between cases and controls. Our study indicates ER stress-inducing variants in CPB1 and CPA1 are associated with pancreatic cancer susceptibility and implicate ER stress in pancreatic acinar cells in pancreatic cancer development.