Search

Although next-generation sequencing is widely used in cancer to profile tumors and detect variants, most somatic variant callers used in these pipelines identify variants at the lowest possible granularity, single-nucleotide variants (SNV). As a result, multiple adjacent SNVs are called individually instead of as a multi-nucleotide variants (MNV). With this approach, the amino acid change from the individual SNV within a codon could be different from the amino acid change based on the MNV that results from combining SNV, leading to incorrect conclusions about the downstream effects of the variants. Here, we analyzed 10,383 variant call files (VCF) from the Cancer Genome Atlas (TCGA) and found 12,141 incorrectly annotated MNVs. Analysis of seven commonly mutated genes from 178 studies in cBioPortal revealed that MNVs were consistently missed in 20 of these studies, whereas they were correctly annotated in 15 more recent studies. At the BRAF V600 locus, the most common example of MNV, several public datasets reported separate BRAF V600E and BRAF V600M variants instead of a single merged V600K variant. VCFs from the TCGA Mutect2 caller were used to develop a solution to merge SNV to MNV. Our custom script used the phasing information from the SNV VCF and determined whether SNVs were at the same codon and needed to be merged into MNV before variant annotation. This study shows that institutions performing NGS sequencing for cancer genomics should incorporate the step of merging MNV as a best practice in their pipelines. Significance: Identification of incorrect mutation calls in TCGA, including clinically relevant BRAF V600 and KRAS G12, will influence research and potentially clinical decisions.

Introduction Tumor mutational burden (TMB) has emerged as a clinically relevant biomarker that may be associated with immune checkpoint inhibitor efficacy. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment. Objective Here we describe the in-depth evaluation of bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples from a phase III clinical trial. Methods In the CheckMate 026 clinical trial, TMB was retrospectively assessed in 312 patients with non-small-cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or standard-of-care chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne® CDx assay. Results TMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearman’s r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. WES and FoundationOne CDx outputs were highly correlated (Spearman’s r = 0.90). Conclusions Parameter variation can impact TMB calculations, highlighting the need for standardization. Encouragingly, differences between assays could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms, and centers is achievable.

The UK Biobank Exome Sequencing Consortium (UKB-ESC) is a private-public partnership between the UK Biobank (UKB) and eight biopharmaceutical companies that will complete the sequencing of exomes for all ~500,000 UKB participants. Here, we describe the early results from ~200,000 UKB participants and the features of this project that enabled its success. The biopharmaceutical industry has increasingly used human genetics to improve success in drug discovery. Recognizing the need for large-scale human genetics data, as well as the unique value of the data access and contribution terms of the UKB, the UKB-ESC was formed. As a result, exome data from 200,643 UKB enrollees are now available. These data include ~10 million exonic variants-a rich resource of rare coding variation that is particularly valuable for drug discovery. The UKB-ESC precompetitive collaboration has further strengthened academic and industry ties and has provided teams with an opportunity to interact with and learn from the wider research community.

The UK Biobank Exome Sequencing Consortium (UKB-ESC) is a unique private/public partnership between the UK Biobank and eight biopharma companies that will sequence the exomes of all ∼500,000 UK Biobank participants. Here we describe early results from the exome sequence data generated by this consortium for the first ∼200,000 UKB subjects and the key features of this project that enabled the UKB-ESC to come together and generate this data.Exome sequencing data from the first 200,643 UKB enrollees are now accessible to the research community. Approximately 10M variants were observed within the targeted regions, including: 8,086,176 SNPs, 370,958 indels and 1,596,984 multi-allelic variants. Of the ∼8M variants observed, 84.5% are coding variants and include 2,139,318 (25.3%) synonymous, 4,549,694 (53.8%) missense, 453,733 (5.4%) predicted loss-of-function (LOF) variants (initiation codon loss, premature stop codons, stop codon loss, splicing and frameshift variants) affecting at least one coding transcript. This open access data provides a rich resource of coding variants for rare variant genetic studies, and is particularly valuable for drug discovery efforts that utilize rare, functionally consequential variants.Over the past decade, the biopharma industry has increasingly leveraged human genetics as part of their drug discovery and development strategies. This shift was motivated by technical advances that enabled cost-effective human genetics research at scale, the emergence of electronic health records and biobanks, and a maturing understanding of how human genetics can increase the probability of successful drug development. Recognizing the need for large-scale human genetics data to drive drug discovery, and the unique value of the open data access policies and contribution terms of the UK Biobank, the UKB-ESC was formed. This precompetitive collaboration has further strengthened the ties between academia and industry and provided teams an unprecedented opportunity to interact with and learn from the wider research community.

Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community.

Although next-generation sequencing assays are routinely carried out using samples from cancer trials, the sequencing data are not always of the required quality. There is a need to evaluate the performance of tissue collection sites and provide feedback about the quality of next-generation sequencing data. This study used a modeling approach based on whole exome sequencing quality control (QC) metrics to evaluate the relative performance of sites participating in the Bristol Myers Squibb Immuno-Oncology clinical trials sample collection. We identified several events for the sample swap. Overall, most sites performed well and few showed poor performance. These findings can increase awareness of sample failure and improve the quality of samples.

Purpose Hearing loss (HL) is the most common sensory disorder in children. Prompt molecular diagnosis may guide screening and management; especially in syndromic cases when HL is the single presenting feature. Exome sequencing (ES)is an appealing diagnostic tool for HL as the genetic causes are highly heterogeneous. Methods ES was performed on a prospective cohort of 43 probands with HL. Sequence data were analyzed for primary and secondary findings. Capture and coverage analysis was performed for genes and variants associated with HL. Results The diagnostic rate using ES was 37.2% compared to 15.8% with clinical HL panel. Secondary findings were discovered in three patients. For 247 genes associated with HL, 94.7% of the exons were targeted for capture and 81.7% of these exons were covered at 20× or greater. Further analysis of 454 randomly selected HL-associated variants showed 89% were targeted for capture and 75% were covered at a read depth of at least 20×. Conclusion ES has an improved yield to clinical testing and may capture diagnoses not initially considered due to subtle clinical phenotypes. Technical challenges were identified, including inadequate capture and coverage of HL genes. Additional considerations of ES include secondary findings, cost, and turnaround time.

PURPOSE: As massively parallel sequencing is increasingly being used for clinical decision-making, it has become critical to understand parameters that affect sequencing quality and to establish methods for measuring and reporting clinical sequencing standards. In this report, we propose a definition for reduced coverage regions and have established a set of standards for variant calling in clinical sequencing applications. METHODS: To enable sequencing centers to assess the regions of poor sequencing quality in their own data, we optimized and used a tool (ExCid) to identify reduced coverage loci within genes or regions of particular interest. We used this framework to examine sequencing data from 500 patients generated in ten projects from sequencing centers in the NHGRI/NCI Clinical Sequencing Exploratory Research (CSER) Consortium. RESULTS: This approach identified reduced coverage regions in clinically relevant genes, including known clinically relevant loci that were uniquely missed at individual centers, in multiple centers, and in all centers. CONCLUSIONS: This report provides a process roadmap for clinical sequencing centers looking to perform similar analyses on their data.

KRAS is the most common oncogenic driver in lung adenocarcinoma (LUAC). We previously reported that STK11/LKB1 (KL) or TP53 (KP) comutations define distinct subgroups of KRAS-mutant LUAC. Here, we examine the efficacy of PD-1 inhibitors in these subgroups. Objective response rates to PD-1 blockade differed significantly among KL (7.4%), KP (35.7%), and K-only (28.6%) subgroups (P < 0.001) in the Stand Up To Cancer (SU2C) cohort (174 patients) with KRAS-mutant LUAC and in patients treated with nivolumab in the CheckMate-057 phase III trial (0% vs. 57.1% vs. 18.2%; P = 0.047). In the SU2C cohort, KL LUAC exhibited shorter progression-free (P < 0.001) and overall (P = 0.0015) survival compared with KRASMUT;STK11/LKB1WT LUAC. Among 924 LUACs, STK11/LKB1 alterations were the only marker significantly associated with PD-L1 negativity in TMBIntermediate/High LUAC. The impact of STK11/LKB1 alterations on clinical outcomes with PD-1/PD-L1 inhibitors extended to PD-L1–positive non–small cell lung cancer. In Kras-mutant murine LUAC models, Stk11/Lkb1 loss promoted PD-1/PD-L1 inhibitor resistance, suggesting a causal role. Our results identify STK11/LKB1 alterations as a major driver of primary resistance to PD-1 blockade in KRAS-mutant LUAC. Significance: This work identifies STK11/LKB1 alterations as the most prevalent genomic driver of primary resistance to PD-1 axis inhibitors in KRAS-mutant lung adenocarcinoma. Genomic profiling may enhance the predictive utility of PD-L1 expression and tumor mutation burden and facilitate establishment of personalized combination immunotherapy approaches for genomically defined LUAC subsets. Cancer Discov; 8(7); 822–35. ©2018 AACR. See related commentary by Etxeberria et al., p. 794. This article is highlighted in the In This Issue feature, p. 781

IntroductionTumor mutational burden (TMB) has emerged as a clinically relevant biomarker that may be associated with immune checkpoint inhibitor efficacy. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment.ObjectiveHere we describe the in-depth evaluation of bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples from a phase 3 clinical trial.MethodsIn the CheckMate 026 clinical trial, TMB was retrospectively assessed in 312 patients with non-small cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or standard-of-care chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne®CDx assay.ResultsTMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearman’s r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. WES and FoundationOne CDx outputs were highly correlated (Spearman’s r = 0.90).ConclusionsParameter variation can impact TMB calculations, highlighting the need for standardization. Encouragingly, differences between assays could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms, and centers is achievable.Key PointsTumor mutational burden (TMB) is a clinically relevant biomarker for efficacy of immunotherapy in patients with cancerVariations in TMB assessment parameters can shift the final TMB value. Harmonization and standardization are important to the successful clinical implementation of TMB testingTMB values assessed by different methods are highly correlated. Harmonization of TMB testing in patients with cancer is therefore achievable

Summary Durable responses and encouraging survival have been demonstrated with immune checkpoint inhibitors in small-cell lung cancer (SCLC), but predictive markers are unknown. We used whole exome sequencing to evaluate the impact of tumor mutational burden on efficacy of nivolumab monotherapy or combined with ipilimumab in patients with SCLC from the nonrandomized or randomized cohorts of CheckMate 032. Patients received nivolumab (3 mg/kg every 2 weeks) or nivolumab plus ipilimumab (1 mg/kg plus 3 mg/kg every 3 weeks for four cycles, followed by nivolumab 3 mg/kg every 2 weeks). Efficacy of nivolumab ± ipilimumab was enhanced in patients with high tumor mutational burden. Nivolumab plus ipilimumab appeared to provide a greater clinical benefit than nivolumab monotherapy in the high tumor mutational burden tertile.

Background: Metastatic or surgically unresectable urothelial cancer (UC) is a disease with high unmet need. Nivolumab monotherapy demonstrated clinical benefit in patients with platinum-resistant UC (CheckMate 275; NCT02387996). Because not all patients respond to nivolumab therapy, identifying biomarkers for response is of critical importance. In the CheckMate 275 cohort, higher tumor mutational burden (TMB) was associated with longer overall survival (OS) (1). Previous studies have shown that certain mutational signatures, combinations of mutation types arising from specific mutagenesis processes, were associated with mutational burden and clinical outcome in UC (2,3). We hypothesized that specific mutational signatures may be associated with response to nivolumab in CheckMate 275. Methods: Whole exome sequencing data and clinical annotations for 139 archival, tumor-normal paired samples from patients enrolled in the CheckMate 275 cohort were collected and analyzed. Sequencing reads were processed and somatic variants called as described previously (4). Percentage of mutations across 30 mutational signatures were generated using deconstructSigs, which infers signature activity with given known signatures (5). Association of the most prevalent mutational signatures with TMB, previously known clinical biomarkers, and clinical efficacy (OS, progression free survival [PFS], and objective response [OR]) were examined. Results: We identified age-related (signature 1), endogenous mutagenesis-related APOBEC (signatures 2 and 13) and UV-induced (signature 7) as the most prevalent mutational signatures in UC. When examining their correlations with TMB, signature 1 showed negative correlation, signatures 2 and 13 showed high positive correlation, and signature 7 showed low correlation. Higher signature 2 scores were associated with better OS, but were poor predictors for PFS and OR. Overall, while signature 2 added predictive value over previously known clinical biomarkers such as PD-L1 expression, serum hemoglobin level, and presence of liver metastasis, it did not improve on the predictive performance of TMB. Conclusions: An APOBEC-related mutational signature (signature 2) was associated with OS in patients with advanced UC treated with nivolumab. This signature was correlated with TMB and did not improve upon TMB as a predictive biomarker. Our work demonstrates the importance of including TMB as a covariate when analyzing mutational signatures. References: 1. Galsky MD et al. Ann Oncol 2017;28(suppl 5). Abstract 848PD 2. Glaser AP et al. Oncotarget 2018;9:4537-48 3. Roberts SA et al. Nat Genet 2013;45:970-6 4. Carbone DP et al. NEJM 2017;376:2415-26 5. Forbes SA et al. Nucleic Acids Res 2017;45:D777-83 Citation Format: G. Celine Han, Peter M. Szabo, Abdel Saci, Alice M. Walsh, Natallia Kalinava, Ariella Sasson, Bruce Fischer, Matthew D. Galsky, Padmanee Sharma. Mutational signatures as biomarkers of response to nivolumab in metastatic bladder cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4890.

Human leukocyte antigens (HLA) genes play an important role in the success of organ transplantation and are associated with autoimmune and infectious diseases. Current DNA based genotyping methods, including Sanger sequence-based typing (SSBT), have identified a high degree of polymorphism. This level of polymorphism makes high-resolution HLA genotyping challenging, resulting in ambiguous typing results due to an inability to resolve phase and/or defining polymorphisms lying outside the region amplified. Next generation sequencing (NGS) may resolve the issue through the combination of clonal amplification, which provides phase information, and the ability to sequence larger regions of genes, including introns, without the additional effort or cost associated with current methods. The NGS HLA sequencing project of the 16IHIW aimed to discuss the different approaches to; (i) template preparation including short and long range PCR amplicons, exome capture and whole genome; (ii) sequencing platforms, including GS 454 FLX, Ion Torrent PGM, Illumina MiSeq/HiSeq and Pacific Biosciences SMRT; (iii) data analysis, specifically allele calling software. The pilot studies presented at the workshop demonstrated that although individual sequencers have very different performance characteristics, all produced sequence data suitable for the resolution of HLA genotyping ambiguities. The developments presented at this workshop clearly highlight the potential benefits of NGS in the HLA laboratory.

Background/Aims: In a family with congenital hyperinsulinism (HI), first described in the 1950s by McQuarrie, we examined the genetic locus and clinical phenotype of a novel form of dominant HI. Methods: We surveyed 25 affected individuals, 7 of whom participated in tests of insulin dysregulation (24-hour fasting, oral glucose and protein tolerance tests). To identify the disease locus and potential disease-associated mutations we performed linkage analysis, whole transcriptome sequencing, whole genome sequencing, gene capture, and next generation sequencing. Results: Most affecteds were diagnosed with HI before age one and 40% presented with a seizure. All affecteds responded well to diazoxide. Affecteds failed to adequately suppress insulin secretion following oral glucose tolerance test or prolonged fasting; none had protein-sensitive hypoglycemia. Linkage analysis mapped the HI locus to Chr10q21-22, a region containing 48 genes. Three novel noncoding variants were found in hexokinase 1 (HK1) and one missense variant in the coding region of DNA2. Conclusion: Dominant, diazoxide-responsive HI in this family maps to a novel locus on Chr10q21-22. HK1 is the more attractive disease gene candidate since a mutation interfering with the normal suppression of HK1 expression in beta-cells could readily explain the hypoglycemia phenotype of this pedigree.

Background: Integrated analysis of multi-omic data is important in understanding oncogenesis, pathology, and drug mechanism of action. Formalin-fixed, paraffin-embedded (FFPE) tissues comprise the bulk of archival specimens in hospitals and clinical trials. Commercial kits are commonly used to extract RNA, DNA, or protein for biomarker studies; however, high-quality extractions are challenging due to crosslinking. We explored the feasibility of performing proteomic, transcriptomic, and genetic analysis from limited FFPE samples collected in clinical trials through a pilot study in colorectal cancer (CRC) and normal tissue. Methods: Qiagen kits were employed, with some modifications, to extract nucleic acid and protein from FFPE sample lysates that would be amenable to next-generation sequencing and liquid chromatography/mass-spectrometry (LC/MS) proteomic profiling. Commercially sourced FFPE slides from CRC biopsies and normal colon, heart, and skin samples were processed (n = 10 each; ~600-mm2 by 5-μm/slice). RNA-seq library preparation was performed using the Illumina® TruSeq Access kit. Label-free LC/MS proteomic analysis was carried out using trypsin/Lys-C-digested protein fragments on an EASY-nLC™ 1200 coupled to a Q Exactive™ Plus (Thermo Fisher). MS data were processed with MaxQuant to estimate protein abundance (Cox and Mann, Nat Biotech 2008). Results: Of 40 samples tested, 38 yielded quantifiable nucleic acid and protein of sufficient quality for transcriptional and proteomic analyses. Mean RNA yield was ~300 ng (150 ng-1.2 µg). RNA degradation was significant, with a mean DV>200 of 45% (Agilent Bioanalyzer). Mean DNA yield was 530 ng, with a mean fragment size of 2 kb. Mean protein yield was 50 µg (1 µg-300 µg). RNA libraries had a mapping rate range of 85%-90% and a coding rate range of 70%-80%; ~16,000 genes were reliable detected (log2 TPM > 1). The number of unique proteins detected ranged from 3,000 to 4,000 for CRC, normal colon, and heart samples; skin samples averaged 1,000 proteins and had the lowest overall yield. Correlation of RNA and protein expression for the same genes was weak (Spearman's rho ~0.3-0.4) at the per-sample level but statistically significant. Using linear models, we identified differentially expressed transcripts and proteins between the CRC and normal colon samples. Pathway enrichment analysis of both modalities indicated changes in cell cycle, which is consistent with rapid growth of tumor cells. Changes in nucleoside metabolism, extracellular matrix remodeling, and innate immune response were more apparent at the protein level. Conclusion: We found that multi-omic analysis was feasible with FFPE samples, and proteomics can be used to validate RNA results. Additionally, proteomics reveal post-translational events, such as extracellular matrix remodeling, that provide unique insights into cancer pathology. Citation Format: Vishal Patel, Ji Gao, Mingyi Liu, Aiqing He, Xi-Tao Wang, Kathryn Vanderlaag, Ariella Sasson, Stefan Kirov, Sunil Kuppasani, Omar J. Jabado, Kandasamy Ravi, Ashok Dongre, Julie Carman, Heidi LeBlanc. Integrated analysis of colorectal carcinoma by co-extraction of RNA, DNA and protein from FFPE tumor samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2707.

Understanding the relationship between chemical structure and function is a ubiquitous problem within the fields of chemistry and biology. Simulation approaches attack the problem utilizing physics to understand a given process at the particle level. Unfortunately, these approaches are often too expensive for many problems of interest. Informatics approaches attack the problem with empirical analysis of descriptions of chemical structure. The issue in these methods is how to describe molecules in a manner that facilitates accurate and general calculation of molecular properties. Here, we present a novel approach that utilizes aspects of simulation and informatics in order to formulate structure-property relationships. We show how supervised learning can be utilized to overcome the sampling problem in simulation approaches. Likewise, we show how learning can be achieved based on molecular descriptions that are rooted in the physics of dynamic intermolecular forces. We apply the approach to three problems including the analysis of corticosteroid binding globulin ligand binding affinity, identification of formylpeptide receptor ligands, and identification of resveratrol analogues capable of inhibiting activation of transcription factor nuclear factor kappaB.

500 RSE capture primers designed using Antholigo. The genomic position (HG19) of the primers as well as the sequence and spacing between primers is provided in addition to other design criteria metrics including deltaG, Tm, and GC%. Table S2: List of qPCR primers and probe sequences designed to amplify regions within several genes (ACTB, EGFR, CLEC16A, BRCA2, CETP, KCNJ2, KCNE1, NOS3) as well as five MHC locations (MHC-1, MHC-2, MHC-3, MHC-4 and MHC-5 as indicated by arrows in Fig. 5a). Table S3: PCR primer location and sequences designed to validate high-confidence variant calls from NGS results. Table S4: Results from Sanger validation of high confidence variants identified by NGS. Table S5: 46 RSE primers designed to capture the four genes (~700 kb in total) in order to examine the effect of RSE primer spacing on capture efficiency (Fig. 3). Figure S1: Read segregation problems caused by reference sequence error in regional duplication. A 2.5 kb duplication (a) within the MHC presented difficulties during the alignment of reads to this region. Reads at the beginning and ends of the duplicated regions segregated cleanly due to polymorphic differences between the duplications. But reads aligning to the middle of the duplication identified a variant position (marked by an *) (b). Sanger sequencing of this region identified that the reference sequence incorrectly identified the * base in the second duplication as a T, when it was actually a C, creating a false variant position. After correcting the reference sequence (c), the central reads segregated correctly and the false variant was eliminated. (PDF 1372 kb)

Background & Aims Very early onset inflammatory bowel disease (VEO-IBD), IBD diagnosed at 5 years of age or younger, frequently presents with a different and more severe phenotype than older-onset IBD. We investigated whether patients with VEO-IBD carry rare or novel variants in genes associated with immunodeficiencies that might contribute to disease development. Methods Patients with VEO-IBD and parents (when available) were recruited from the Children's Hospital of Philadelphia from March 2013 through July 2014. We analyzed DNA from 125 patients with VEO-IBD (age, 3 wk to 4 y) and 19 parents, 4 of whom also had IBD. Exome capture was performed by Agilent SureSelect V4, and sequencing was performed using the Illumina HiSeq platform. Alignment to human genome GRCh37 was achieved followed by postprocessing and variant calling. After functional annotation, candidate variants were analyzed for change in protein function, minor allele frequency less than 0.1%, and scaled combined annotation-dependent depletion scores of 10 or less. We focused on genes associated with primary immunodeficiencies and related pathways. An additional 210 exome samples from patients with pediatric IBD (n = 45) or adult-onset Crohn's disease (n = 20) and healthy individuals (controls, n = 145) were obtained from the University of Kiel, Germany, and used as control groups. Results Four hundred genes and regions associated with primary immunodeficiency, covering approximately 6500 coding exons totaling more than 1 Mbp of coding sequence, were selected from the whole-exome data. Our analysis showed novel and rare variants within these genes that could contribute to the development of VEO-IBD, including rare heterozygous missense variants in IL10RA and previously unidentified variants in MSH5 and CD19 . Conclusions In an exome sequence analysis of patients with VEO-IBD and their parents, we identified variants in genes that regulate B- and T-cell functions and could contribute to pathogenesis. Our analysis could lead to the identification of previously unidentified IBD-associated variants.

Targeted resequencing projects can generate massive amount of data in the form of short nucleic acid sequences. These sequences are aligned to a reference genome and stored in BAM (Binary Alignment/Map) files in most cases. A growing challenge for biomedical researchers is to rapidly summarize large BAM files (typically 5 to 25 GB) to evaluate data quality and guide follow-up steps. Here, we present an R package and report template, "bamchop", that retrieves targeted resequencing information from a BAM file and illustrates it in a standardized format. This program is applicable to all resequencing data that investigates selected genomie regions, ranging from a small number of mutation hotspots to a complete human exome. Bamchop reports the sequencing quality and coverage, mapping confidence, strand and nucleic acid bias, and other information about the targeted regions and genomie background. A bamchop report is the product of Sweave framework that requires the LaTeX document preparation system and the R statistical environment. In applying it to a variety of resequencing projects, we determined that bamchop is a powerful tool for both bioinformaticians and bench scientists to conveniently assess their resequencing data. The source code of bamchop is available from https://github.com/CBMi-BiC/bamchop.

Many common and well-documented (CWD) HLA alleles have only been partially characterized. The DNA sequence of these incomplete alleles, as published in the IMGT/HLA database, is most often limited to exons that code for the extracellular domains of the mature protein. Here we describe the application of next-generation sequencing technology to obtain full length genomic sequence from a single long-range PCR amplicon for 15 common and well-documented HLA Class I alleles. This technology is well suited to fill in the gaps of the current HLA allele sequence database which is largely incomplete. A more comprehensive catalog of HLA allele sequences would be beneficial in the evaluation of mismatches in transplantation, studies of population genetics, the evolution of HLAs, regulatory mechanisms and HLA expression, and issues related to the genomic organization of the MHC.

Summary: Here, we report the development of a filtering framework designed for efficient identification of both polyclonal and independent errors within SOLiD sequence data. The filtering utilizes the quality values reported by SOLiD's primary analysis for the identification of the two different types of errors. The filtering framework facilitates the passage of high-quality data into a variety of functional genomics applications, including de novo assemblers and sequence matching programs for SNP calling, improving the output quality and reducing resources necessary for analysis. Availability: This error analysis framework is written in Perl and runs on Mac OS and Linux/Unix systems. The filter, documentation and sample Excel files for quality analysis are available at http://hts.rutgers.edu/filter and are distributed as Open Source software under the GPLv3.0. Contact: tmichael@waksman.rutgers.edu Supplementary information: Supplementary data is available at Bioinformatics online.

BACKGROUND AND AIM: Therapeutic goals for Crohn's disease (CD) have evolved from a mere control of symptoms to the concept of deep remission (DR), including clinical and biomarker remission and mucosal healing (MH). Biologic therapy with anti-TNFα is effective in achieving MH. Yet, CD is a transmural disease, characterized by a progressive bowel damage leading to complications. This is the first pediatric study prospectively evaluating the efficacy of anti-TNFα therapy in inducing clinical remission, MH and transmural healing (TH) in ileal CD. METHODS: Pediatric patients (pts) with ileal CD starting biological therapy with Infliximab or Adalimumab were prospectively enrolled. All pts were Naive to biologics. Clinical activity (Pediatric Crohn's Disease Activity Index, PCDAI), laboratory tests (CRP, ESR), endoscopic activity (simple endoscopic score, SES-CD) and transmural disease assessed by small intestine contrast ultrasonography (SICUS) were evaluated before starting (T0) and after 9-12 months of therapy (T1). Complete MH was defined as a SES-CD of 0-1, partial MH as 50% decrease vs T0. At US the evaluated parameters were: extension of disease (cm), bowel wall thickness >3 mm (BWT), bowel wall vascularity, stratification of the BW (BWS), presence of stricture, fistulae and abscess. Wilcoxon signed rank test was used for pair comparison (T1-T0). RESULTS: 26 pts (mean age 13.3 ± 4, 16 males) were included. The mean PCDAI, ileal SES-CD, CRP, ESR, BWT and disease extension values significantly decreased at T1 (table). Increased bowel wall vascularity was present in 80% of pts at T0 and in 24% at T1 (p

Aim Capture and sequence by NGS the 4Mb of the MHC and derive genotypes of 33 MHC genes (HLA and non-HLAs) using Omixon Target HLA Typing software. Methods We applied our Region Specific Extraction method to target and capture 4Mb of the MHC region with custom designed capture oligos on 7 samples having known HLA genotypes: 5 homozygous cell lines (COX, DBB, JVM, PGF, and QBL) and 2 heterozygous samples (mixture of PGF and COX DNA, and a standard lab control). Each sample was whole-genome amplified, prepared for sequencing using Illumina TruSeq DNA sample prep kit and size selected for DNA fragments ranging from 300-400 bp. Paired-end 2x100bp sequencing was performed on the Illumina HiSeq. Each sample was genotyped for 33 genes within the MHC by Omixon Target using all paired-end reads. Derived genotypes were compared to known genotypes from the IMGT/HLA database for the cell lines and Sanger sequencing for the heterozygous control sample. Results We sequenced 7 samples throughout the 4Mb of the MHC region. On average, each sample had 284 million reads which were analyzed with Omixon Target. The 33 genes examined were Class I HLA-A, B, C, E, F, G, H, J, K, L, and V, Class II genes HLA-DMA, DMB, DOA, DOB, DPA1, DPB1, DQA1, DQB1, DRA, DRB1, DRB3, DRB4, DRB5, Class II pseudogenes HLA-DRB2, DRB6, DRB7, DRB8, DRB9, and MHC related genes MICA, MICB, TAP1, and TAP2. Omixon Target provided genotypes for 90% of the possible alleles; the remaining 10% of alleles (no genotype) were Class II pseudogenes. The average depth across the alleles ranged from 50–3000, a small percentage of the overall reads per sample. In the cases where the true HLA genotype was known, we determined the correct allele with 93% accuracy. Conclusions Our method of capturing and sequencing the MHC coupled with Omixon Target has yielded highly accurate genotypes for 33 HLA and non-HLA, MHC genes. This work sets the stage for further detailed characterization of the MHC and derivation of clinically relevant HLA typing from MHC NGS data. Major: Omixon, Inc.: Other: Contractor. Hague: Omixon, Inc.: Other: Contractor. Berces: Omixon, Inc.: Employee; Stockholder.

Aim To sequence the full length of HLA Class I genes using single molecule real-time (SMRT ® ) sequencing technology. Methods Two samples were amplified by Long-Range PCR at HLA-A, B, C loci. Full lengths of these genes (∼3.2 kb) were generated with custom designed, barcoded primers targeting 5’UTR and 3’UTR. DNA libraries were prepared by ligating SMRTbell™ adaptors to the HLA amplicons. This produced closed-circular structures consisting of a double-stranded insert (full length HLA amplicon), and a single-stranded hairpin loop (SMRTbell™) on either end. Sequencing primer was annealed to the open/single-stranded portion of the hairpin adaptor. Streptavidin-bound DNA polymerase was added to the primer-template complex enabling the binding of the template to the bottom of nano-sized wells on the SMRT Cell. DNA synthesis of fluorescently labeled nucleotides was observed in real-time on the PacBio ® RS instrument. The pooled libraries were run on 6 SMRT Cells using either 45 or 90 minute data collection time per SMRT Cell. Individual sequence reads ⩾1,000 bases were parsed by sample-specific barcode sequence and were then aligned using BWA-SW. Alignment data were analyzed with SAM Tools and custom written code. Results Sequence and Alignment Statistics: [ Table 1 ]. Conclusions We demonstrate real-time sequencing of HLA genes from single DNA molecules. This technology offers great potential for HLA genotyping and further characterization of the MHC due to the length and phase of sequences obtained, speed, and ease of sample prep. Ranade: Pacific Biosciences Inc.: Employee. Sethuraman: Pacific Biosciences Inc.: Employee. Chin: Pacific Biosciences Inc.: Employee. Robinson: Pacific Biosciences Inc.: Employee.

Aim To evaluate newly available high-throughput sequencing technologies for HLA genotyping. Methods Two samples were amplified at HLA-A, B, C, DRB1, and DQB1. The full length of HLA Class I genes were amplified with custom designed primers from 5′UTR to 3′UTR. HLA Class II were amplified from Exon 2 to Exon 4 using primers from GenDx. A separate DNA library was prepared from each long-range PCR amplicon using platform-specific library prep kits (NEB, Ipswich, MA). For the Ion Torrent run, the pool of 10 libraries was clonally amplified by emulsion PCR and was sequenced using the 200 bp kit and a 316 chip on the Ion Torrent PGM (Life Technologies). Paired-end 2 × 150 bp sequencing of the Illumina libraries was performed on the MiSeq system. Sequence alignment utilized BWA-SW software. Further analysis was conducted using SAM tools and custom written code. Sequence analysis was performed in parallel with NGSEngine (GenDx). Results Sequencing and alignment metrics were as follows:[ Table 1 ] Consensus sequence of aligned reads was 100% accurate for both platforms. Definitive HLA genotypes were obtained without any ambiguity (alternative genotypes) and were concordant with the known alleles of these samples. Conclusions Newly developed high-throughput sequencing systems hold great promise for a new method of HLA genotyping. These new technologies are capable of eliminating all ambiguity currently encountered with existing methods. As such the advancement from high resolution to allele level HLA typing is approaching. Rozemuller: GenDx: Employee. Penning: GenDx: Employee. Mulder: GenDx: Employee.

Background Conditions associated with sudden cardiac arrest/death (SCA/D) in youth often have a genetic etiology. While SCA/D is uncommon, a pro-active family screening approach may identify these inherited structural and electrical abnormalities prior to symptomatic events and allow appropriate surveillance and treatment. This study investigated the diagnostic utility of exome sequencing (ES) by evaluating the capture and coverage of genes related to SCA/D. Methods Samples from 102 individuals (13 with known molecular etiologies for SCA/D, 30 individuals without known molecular etiologies for SCA/D and 59 with other conditions) were analyzed following exome capture and sequencing at an average read depth of 100X. Reads were mapped to human genome GRCh37 using Novoalign, and post-processing and analysis was done using Picard and GATK. A total of 103 genes (2,190 exons) related to SCA/D were used as a primary filter. An additional 100 random variants within the targeted genes associated with SCA/D were also selected and evaluated for depth of sequencing and coverage. Although the primary objective was to evaluate the adequacy of depth of sequencing and coverage of targeted SCA/D genes and not for primary diagnosis, all patients who had SCA/D (known or unknown molecular etiologies) were evaluated with the project’s variant analysis pipeline to determine if the molecular etiologies could be successfully identified. Results The majority of exons (97.6 %) were captured and fully covered on average at minimum of 20x sequencing depth. The proportion of unique genomic positions reported within poorly covered exons remained small (4 %). Exonic regions with less coverage reflect the need to enrich these areas to improve coverage. Despite limitations in coverage, we identified 100 % of cases with a prior known molecular etiology for SCA/D, and analysis of an additional 30 individuals with SCA/D but no known molecular etiology revealed a diagnostic answer in 5/30 (17 %). We also demonstrated 95 % of 100 randomly selected reported variants within our targeted genes would have been picked up on ES based on our coverage analysis. Conclusions ES is a helpful clinical diagnostic tool for SCA/D given its potential to successfully identify a molecular diagnosis, but clinicians should be aware of limitations of available platforms from technical and diagnostic perspectives. Electronic supplementary material The online version of this article (doi:10.1186/s40246-015-0038-y) contains supplementary material, which is available to authorized users.

Background The ability to capture and sequence large contiguous DNA fragments represents a significant advancement towards the comprehensive characterization of complex genomic regions. While emerging sequencing platforms are capable of producing several kilobases-long reads, the fragment sizes generated by current DNA target enrichment technologies remain a limiting factor, producing DNA fragments generally shorter than 1 kbp. The DNA enrichment methodology described herein, Region-Specific Extraction (RSE), produces DNA segments in excess of 20 kbp in length. Coupling this enrichment method to appropriate sequencing platforms will significantly enhance the ability to generate complete and accurate sequence characterization of any genomic region without the need for reference-based assembly. Results RSE is a long-range DNA target capture methodology that relies on the specific hybridization of short (20-25 base) oligonucleotide primers to selected sequence motifs within the DNA target region. These capture primers are then enzymatically extended on the 3’-end, incorporating biotinylated nucleotides into the DNA. Streptavidin-coated beads are subsequently used to pull-down the original, long DNA template molecules via the newly synthesized, biotinylated DNA that is bound to them. We demonstrate the accuracy, simplicity and utility of the RSE method by capturing and sequencing a 4 Mbp stretch of the major histocompatibility complex (MHC). Our results show an average depth of coverage of 164X for the entire MHC. This depth of coverage contributes significantly to a 99.94 % total coverage of the targeted region and to an accuracy that is over 99.99 %. Conclusions RSE represents a cost-effective target enrichment method capable of producing sequencing templates in excess of 20 kbp in length. The utility of our method has been proven to generate superior coverage across the MHC as compared to other commercially available methodologies, with the added advantage of producing longer sequencing templates amenable to DNA sequencing on recently developed platforms. Although our demonstration of the method does not utilize these DNA sequencing platforms directly, our results indicate that the capture of long DNA fragments produce superior coverage of the targeted region. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2836-6) contains supplementary material, which is available to authorized users.

Background High-throughput sequencing (HTS) technologies are spearheading the accelerated development of biomedical research. Processing and summarizing the large amount of data generated by HTS presents a non-trivial challenge to bioinformatics. A commonly adopted standard is to store sequencing reads aligned to a reference genome in SAM (Sequence Alignment/Map) or BAM (Binary Alignment/Map) files. Quality control of SAM/BAM files is a critical checkpoint before downstream analysis. The goal of the current project is to facilitate and standardize this process. Results We developed bamchop, a robust program to efficiently summarize key statistical metrics of HTS data stored in BAM files, and to visually present the results in a formatted report. The report documents information about various aspects of HTS data, such as sequencing quality, mapping to a reference genome, sequencing coverage, and base frequency. Bamchop uses the R language and Bioconductor packages to calculate statistical matrices and the Sweave utility and associated LaTeX markup for documentation. Bamchop's efficiency and robustness were tested on BAM files generated by local sequencing facilities and the 1000 Genomes Project. Source code, instruction and example reports of bamchop are freely available from https://github.com/CBMi-BiG/bamchop. Conclusions Bamchop enables biomedical researchers to quickly and rigorously evaluate HTS data by providing a convenient synopsis and user-friendly reports.