Applying Ancestry and Sex Computation as a Quality Control Tool in Targeted Next-Generation Sequencing.

OBJECTIVES: To apply techniques for ancestry and sex computation from next-generation sequencing (NGS) data as an approach to confirm sample identity and detect sample processing errors. METHODS: We combined a principal component analysis method with k-nearest neighbors classification to compute the ancestry of patients undergoing NGS testing. By combining this calculation with X chromosome copy number data, we determined the sex and ancestry of patients for comparison with self-report. We also modeled the sensitivity of this technique in detecting sample processing errors. RESULTS: We applied this technique to 859 patient samples with reliable self-report data. Our k-nearest neighbors ancestry screen had an accuracy of 98.7% for patients reporting a single ancestry. Visual inspection of principal component plots was consistent with self-report in 99.6% of single-ancestry and mixed-ancestry patients. Our model demonstrates that approximately two-thirds of potential sample swaps could be detected in our patient population using this technique. CONCLUSIONS: Patient ancestry can be estimated from NGS data incidentally sequenced in targeted panels, enabling an inexpensive quality control method when coupled with patient self-report.

Improving performance of multigene panels for genomic analysis of cancer predisposition.

PURPOSE: Screening multiple genes for inherited cancer predisposition expands opportunities for cancer prevention; however, reports of variants of uncertain significance (VUS) may limit clinical usefulness. We used an expert-driven approach, exploiting all available information, to evaluate multigene panels for inherited cancer predisposition in a clinical series that included multiple cancer types and complex family histories. METHODS: For 1,462 sequential patients referred for testing by BROCA or ColoSeq multigene panels, genomic DNA was sequenced and variants were interpreted by multiple experts using International Agency for Research on Cancer guidelines and incorporating evolutionary conservation, known and predicted variant consequences, and personal and family cancer history. Diagnostic yield was evaluated for various presenting conditions and family-history profiles. RESULTS: Of 1,462 patients, 12% carried damaging mutations in established cancer genes. Diagnostic yield varied by clinical presentation. Actionable results were identified for 13% of breast and colorectal cancer patients and for 4% of cancer-free subjects, based on their family histories of cancer. Incidental findings explaining cancer in neither the patient nor the family were present in 1.7% of subjects. Less than 1% of patients carried VUS in BRCA1 or BRCA2. For all genes combined, initial reports contained VUS for 10.5% of patients, which declined to 7.5% of patients after reclassification based on additional information. CONCLUSIONS: Individualized interpretation of gene panels is a complex medical activity. Interpretation by multiple experts in the context of personal and family histories maximizes actionable results and minimizes reports of VUS.Genet Med 18 10, 974-981.

MSIplus for Integrated Colorectal Cancer Molecular Testing by Next-Generation Sequencing.

Molecular analysis of colon cancers currently requires multiphasic testing that uses various assays with different performance characteristics, adding cost and time to patient care. We have developed a single, next-generation sequencing assay to simultaneously evaluate colorectal cancers for mutations in relevant cancer genes (KRAS, NRAS, and BRAF) and for tumor microsatellite instability (MSI). In a sample set of 61 cases, the assay demonstrated overall sensitivity of 100% and specificity of 100% for identifying cancer-associated mutations, with a practical limit of detection at 2% mutant allele fraction. MSIplus was 97% sensitive (34 of 35 MSI-positive cases) and 100% specific (42 of 42 MSI-negative cases) for ascertaining MSI phenotype in a cohort of 78 tumor specimens. These performance characteristics were slightly better than for conventional multiplex PCR MSI testing (97% sensitivity and 95% specificity), which is based on comparison of microsatellite loci amplified from tumor and matched normal material, applied to the same specimen cohort. Because the assay uses an amplicon sequencing approach, it is rapid and appropriate for specimens with limited available material or fragmented DNA. This integrated testing strategy offers several advantages over existing methods, including a lack of need for matched normal material, sensitive and unbiased detection of variants in target genes, and an automated analysis pipeline enabling principled and reproducible identification of cancer-associated mutations and MSI status simultaneously.

Microsatellite instability detection by next generation sequencing.

BACKGROUND: Microsatellite instability (MSI) is a useful phenotype in cancer diagnosis and prognosis. Nevertheless, methods to detect MSI status from next generation DNA sequencing (NGS) data are underdeveloped. METHODS: We developed an approach to detect the MSI phenotype using NGS (mSINGS). The method was used to evaluate mononucleotide microsatellite loci that were incidentally sequenced after targeted gene enrichment and could be applied to gene or exome capture panels designed for other purposes. For each microsatellite locus, the number of differently sized repeats in experimental samples were quantified and compared to a population of normal controls. Loci were considered unstable if the experimental number of repeats was statistically greater than in the control population. MSI status was determined by the fraction of unstable microsatellite loci. RESULTS: We examined data from 324 samples generated using targeted gene capture assays of 3 different sizes, ranging from a 0.85-Mb to a 44-Mb exome design and incorporating from 15 to 2957 microsatellite markers. When we compared mSING results to MSI-PCR as a gold standard for 108 cases, we found the approach to be both diagnostically sensitive (range of 96.4% to 100% across 3 panels) and specific (range of 97.2% to 100%) for determining MSI status. The fraction of unstable microsatellite markers calculated from sequencing data correlated with the number of unstable loci detected by conventional MSI-PCR testing. CONCLUSIONS: NGS data can enable highly accurate detection of MSI, even from limited capture designs. This novel approach offers several advantages over existing PCR-based methods.

Bioinformatics Resource Manager v2.3: an integrated software environment for systems biology with microRNA and cross-species analysis tools.

BACKGROUND: MicroRNAs (miRNAs) are noncoding RNAs that direct post-transcriptional regulation of protein coding genes. Recent studies have shown miRNAs are important for controlling many biological processes, including nervous system development, and are highly conserved across species. Given their importance, computational tools are necessary for analysis, interpretation and integration of high-throughput (HTP) miRNA data in an increasing number of model species. The Bioinformatics Resource Manager (BRM) v2.3 is a software environment for data management, mining, integration and functional annotation of HTP biological data. In this study, we report recent updates to BRM for miRNA data analysis and cross-species comparisons across datasets. RESULTS: BRM v2.3 has the capability to query predicted miRNA targets from multiple databases, retrieve potential regulatory miRNAs for known genes, integrate experimentally derived miRNA and mRNA datasets, perform ortholog mapping across species, and retrieve annotation and cross-reference identifiers for an expanded number of species. Here we use BRM to show that developmental exposure of zebrafish to 30 uM nicotine from 6-48 hours post fertilization (hpf) results in behavioral hyperactivity in larval zebrafish and alteration of putative miRNA gene targets in whole embryos at developmental stages that encompass early neurogenesis. We show typical workflows for using BRM to integrate experimental zebrafish miRNA and mRNA microarray datasets with example retrievals for zebrafish, including pathway annotation and mapping to human ortholog. Functional analysis of differentially regulated (p<0.05) gene targets in BRM indicates that nicotine exposure disrupts genes involved in neurogenesis, possibly through misregulation of nicotine-sensitive miRNAs. CONCLUSIONS: BRM provides the ability to mine complex data for identification of candidate miRNAs or pathways that drive phenotypic outcome and, therefore, is a useful hypothesis generation tool for systems biology. The miRNA workflow in BRM allows for efficient processing of multiple miRNA and mRNA datasets in a single software environment with the added capability to interact with public data sources and visual analytic tools for HTP data analysis at a systems level. BRM is developed using Java™ and other open-source technologies for free distribution (http://www.sysbio.org/dataresources/brm.stm).