Standard Next-generation Sequencing Research Articles

Transcriptional analysis of viral mRNAs reveals common transcription patterns in cells infected by five different filoviruses.

Filoviruses are notorious viral pathogens responsible for high-consequence diseases in humans and non-human primates. Transcription of filovirus mRNA shares several common features with transcription in other non-segmented negative-strand viruses, including differential expression of genes located across the viral genome. Transcriptional patterns of Ebola virus (EBOV) and Marburg virus (MARV) have been previously described using traditional, laborious methods, such as northern blots and in vivo labeling of viral mRNAs. More recently, however, the availability of the next generation sequencing (NGS) technology has offered a more straightforward approach to assess transcriptional patterns. In this report, we analyzed the transcription patterns of four ebolaviruses—EBOV, Sudan (SUDV), Bundibugyo (BDBV), and Reston (RESTV) viruses—in two different cell lines using standard NGS library preparation and sequencing protocols. In agreement with previous reports mainly focused on EBOV and MARV, the remaining filoviruses used in this study also showed a consistent transcription pattern, with only minor variations between the different viruses. We have also analyzed the proportions of the three mRNAs transcribed from the GP gene, which are characteristic of the genus Ebolavirus and encode the glycoprotein (GP), the soluble GP (sGP), and the small soluble GP (ssGP). In addition, we used NGS methodology to analyze the transcription pattern of two previously described recombinant MARV. This analysis allowed us to correct our construction design, and to make an improved version of the original MARV expressing reporter genes.

Abstract 418: Highly efficient duplex DNA tagging strategy improves accuracy of detecting ultra-low-frequency mutations through consensus read reconstruction

Abstract Introduction: Molecular diagnostics and precise personalized care continue to increase the sensitivity and specificity requirements for detecting low (~5%) to ultra-low (<1%) frequency actionable mutations by next generation sequencing (NGS). These low-frequency variants often occur below the reliable limit of detection of standard NGS as they are confounded by errors introduced during the NGS workflow. We have developed adapters containing unique molecular identifiers (UMIs) that permit tagging of double-stranded DNA and statistical reconstruction of reads sequenced as duplicates. These novel adapters are compatible with standard library preparation and enrichment methods and reagents, yet provide significantly enhanced error correction. Methods: Libraries were prepared from the 3 most commonly used oncology sample types: genomic, FFPE, or plasma-derived, cell-free DNA, using a standard, commercially available kit combined with standard adapters or the novel duplex UMI adapters. The libraries were enriched with a custom xGen Lockdown Panel targeting a 75 kb polymorphic region, and then deep sequencing and variant calling were performed. A consensus read building tool was developed to collapse PCR duplicates based on molecular barcodes, and the tool was used to evaluate the utility of UMIs in error correction. Results: Compared to standard adapters, the duplex adapters presented comparable or better library yield and mean deduplicated sequencing depth for all sample types and input masses tested. To evaluate variant-calling accuracy, we established mixtures of DNA of known SNP genotype to mimic ultra-low-frequency variant samples. For genomic DNA samples, DNA from NA12878 and NA24385 were mixed to generate minor allele frequency (MAF) down to 0.1%, and variant calls were evaluated against annotations in Genome in a Bottle. Commercial FFPE and cell-free DNA samples were genotyped and mixed to present MAF at 0.5%. When standard adapters were used, variants present at the MAF were detected with 90% sensitivity for all sample types, but only under conditions that also called >4,000 false positives, resulting in a positive predictive value (PPV) of <3%. Using the duplex UMI adapters in conjunction with consensus read construction, >90% detection sensitivity was achieved for genomic and cell-free DNA samples with 0 false positives, resulting in 100% PPV, a >40-fold error suppression. For FFPE DNA samples, the duplex adapters provided >30-fold PPV improvement compared to standard adapters. Conclusions: The duplex UMI adapters eliminate background NGS errors by collapsing duplicated reads using their unique tags. This leads to unprecedented accuracy in detecting true low-frequency variants, regardless of the input DNA source. Such advances are key to refining diagnostics and improving precision cancer care. Citation Format: Jiashi Wang, Kevin Lai, Madelyn Light, Layla Katiraee, Kristina Giorda, Mirna Jarosz, Yun Bao, Criss Walworth, David Kupec, Caifu Chen. Highly efficient duplex DNA tagging strategy improves accuracy of detecting ultra-low-frequency mutations through consensus read reconstruction [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 418.

Seventeen percent of NGS 50 gene panel variants are not expressed in RNAseq.

12118Background: Next Generation Sequencing (NGS) has gained widespread clinical adoption for the determination of molecular targets for therapy in oncology. Standard NGS panels evaluate DNA only. ...

Abstract PD1-03: Clinically actionable pathogenic mutations that may be missed by conventional NGS-based testing: An analysis of 80,000 patients

Abstract Background: In appropriately tested patients with a personal or family history of cancer, the comprehensive assessment of inherited mutations in cancer susceptibility genes is crucial to clinical decision making. Conventional laboratory methods based on NGS (next-generation sequencing) focus on the detection of certain mutation types, notably single nucleotide variants (SNVs) and small insertions/deletions (indels), in readily accessible protein coding regions of the patients' DNA. These methods may be augmented to also detect mid-sized copy number changes (del/dup events). However, other types of clinically significant alterations can be invisible to these approaches, and for this reason their impact has been less well studied. We investigated the prevalence of such mutations in a large patient population focusing on 19 genes included in the NCCN guidelines for hereditary breast and ovarian cancer. Methods: A diverse set of technical methods beyond conventional NGS sequencing were implemented to detect and confirm the presence of DNA alterations in over 80,000 patients. These patients were physician-referred for genetic testing and almost all had a directly relevant personal and/or family history. Pathogenicity was rigorously assessed using a method based on the ACMG 2015 guidelines. Among the technical methods used were long-read single molecule sequencing, breakpoint detection, MLPA, microarrays, and de novo methods for homopolymer associated mutations. Results: Over 8.6% of patients with a pathogenic, potentially actionable germline mutation in one (or more) of the 19 NCCN genes harbored a mutation not easily detected by conventional sequencing or del/dup methods. In the subset of 11 NCCN genes specifically associated with breast cancer, the prevalence was slightly lower (6.8%) yet still substantial. No single class of mutation was responsible for this; rather a diversity of laboratory technical challenges were present. These included both challenging mutation types and also alterations that lie within challenging regions of these 19 genes. Data from the Precision FDA effort are consistent with these findings, showing >10-fold higher error rates for many such events when using standard NGS approaches alone. Conclusions: Our study explored the boundaries of conventional laboratory methods and found that a significant fraction of pathogenic mutations in patients are of types that require specialized biochemical or bioinformatics methods to be used. Accurate reporting of these technically “hard” mutations is crucial to the correct diagnosis and management of cancer patients and their families, and omission of these methods can lead to high false negative rates. Based on our review of published studies, as well as a separate interlaboratory study (see associated abstract by Lincoln et al.), these methods are not yet uniformly implemented. Moreover, as some of these same genes are becoming relevant to therapeutic selection based on somatic mutation profiles, these same considerations will soon arise in tumor testing, we suspect. Citation Format: Lincoln SE, Truty R, Zook J, Aradhya S, Salit ML, Nussbaum RL. Clinically actionable pathogenic mutations that may be missed by conventional NGS-based testing: An analysis of 80,000 patients [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr PD1-03.

Analytical Validation of a Next-Generation Sequencing Assay to Monitor Immune Responses in Solid Tumors

We have developed a next-generation sequencing assay to quantify biomarkers of the host immune response in formalin-fixed, paraffin-embedded (FFPE) tumor specimens. This assay aims to provide clinicians with a comprehensive characterization of the immunologic tumor microenvironment as a guide for therapeutic decisions on patients with solid tumors. The assay relies on RNA-sequencing (seq) to semiquantitatively measure the levels of 43 transcripts related to anticancer immune responses and 11 transcripts that reflect the relative abundance of tumor-infiltrating lymphocytes, as well as on DNA-seq to estimate mutational burden. The assay has a clinically relevant 5-day turnaround time and can be conducted on as little as 2.5 ng of RNA and 1.8 ng of genomic DNA extracted from three to five standard FFPE sections. The standardized next-generation sequencing workflow produced sequencing reads adequate for clinical testing of matched RNA and DNA from several samples in a single run. Assay performance for gene-specific sensitivity, linearity, dynamic range, and detection threshold was estimated across a wide range of actual and artificial FFPE samples selected or generated to address preanalytical variability linked to specimen features (eg, tumor-infiltrating lymphocyte abundance, percentage of necrosis), and analytical variability linked to assay features (eg, batch size, run, day, operator). Analytical precision studies demonstrated that the assay is highly reproducible and accurate compared with established orthogonal approaches.

Novel Primer Sets for Next Generation Sequencing-Based Analyses of Water Quality.

Next generation sequencing (NGS) has rapidly become an invaluable tool for the detection, identification and relative quantification of environmental microorganisms. Here, we demonstrate two new 16S rDNA primer sets, which are compatible with NGS approaches and are primarily for use in water quality studies. Compared to 16S rRNA gene based universal primers, in silico and experimental analyses demonstrated that the new primers showed increased specificity for the Cyanobacteria and Proteobacteria phyla, allowing increased sensitivity for the detection, identification and relative quantification of toxic bloom-forming microalgae, microbial water quality bioindicators and common pathogens. Significantly, Cyanobacterial and Proteobacterial sequences accounted for ca. 95% of all sequences obtained within NGS runs (when compared to ca. 50% with standard universal NGS primers), providing higher sensitivity and greater phylogenetic resolution of key water quality microbial groups. The increased selectivity of the new primers allow the parallel sequencing of more samples through reduced sequence retrieval levels required to detect target groups, potentially reducing NGS costs by 50% but still guaranteeing optimal coverage and species discrimination.

P3.02b-025 Rapid and Highly Sensitive EGFRdelEx19 and KRAS Exon 2 Mutation Detection in EBUS-TBNA Specimen of Lung Adenocarcinoma: Topic: EGFR Biomarkers

First-line treatment with afatinib prolongs overall survival in patients with metastatic non-small-cell lung cancer (NSCLC) harboring EGFR exon 19 deletion mutations. Conversely, somatic KRAS mutations are negative predictors for benefit from EGFR-targeting agents. Rapid availability of these biomarker results is mandatory to prevent delayed or inferior treatments. Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is well-established for lung cancer diagnosis and staging. Next generation sequencing (NGS) via targeted resequencing allows simultaneous interrogation for multiple mutations, but has its limitations based on the amount of tumor tissue required and assay times. RT-PCR using Light-Cycler technology (LC-RTPCR) is a rapid and sensitive assay to detect somatic mutations in various tissues from NSCLC patients. The study’s aim was to analyze if LC-RTPCR is feasible for rapid EGFRdelE×19 and KRAS Exon 2 mutation detection in EBUS-TBNA samples and to compare results with results obtained via standard NGS mutation analyses. 48 surplus EBUS-TBNA samples (38 lymph nodes, 10 primary tumor) from 47 patients with pulmonary adenocarcinoma were analyzed. Two samples were collected per lymph node. One was used for routine cytology, the other was freshly frozen (ff). DNA from ff-biopsies was extracted using Genomic DNA buffer set (QIAgen, Germany). Mutation analysis by LC-RTPCR was conducted as previously described. NGS was performed on MiSeq (Illumina) via targeted resequencing using a customized multiplex-PCR panel covering 36 exons from 11 genes. Mutations were annotated with a minimum frequency of 2%. Processing time was approximately 4 days for NGS and 2 hours for LC-RTPCR analyses. NGS of EBUS-TBNA samples was technically feasible for both markers in 22 (46%) samples, for EGFR testing in 32 (67%) samples, and for KRAS in 23 (48%) samples. EGFRdelEx19 mutations were detected in four (8.3% of intention-to-screen), and KRAS Exon 2 mutations in 15 cases (31%) cases. LC-RTPCR was technically feasible in all cases. All mutations detected by NGS were also detected by LC-RTPCR. LC-RTPCR detected three additional KRAS Exon 2 mutations and three additional EGFRdelEx19 mutations. NGS detected additional mutations in 4 cases (2 EGFR Exon 21, 1 KRAS Codon 61, 1 PIK3CA). LC-RTPCR is a rapid, highly sensitive method to detect mutations of immediate therapeutic relevance, such as EGFRdelEx19 and KRAS Exon 2 mutations, in limited EBUS-TBNA specimens from metastatic NSCLC patients. It is of value as rapid and sensitive initial assay in a two-step diagnostic process for first-line treatment decision, incorporating broader biomarker panels as second step.

Genome-Wide Estimation of the Spontaneous Mutation Rate of Human Adenovirus 5 by High-Fidelity Deep Sequencing.

Rates of spontaneous mutation determine the ability of viruses to evolve, infect new hosts, evade immunity and undergo drug resistance. Contrarily to RNA viruses, few mutation rate estimates have been obtained for DNA viruses, because their high replication fidelity implies that new mutations typically fall below the detection limits of Sanger and standard next-generation sequencing. Here, we have used a recently developed high-fidelity deep sequencing technique (Duplex Sequencing) to score spontaneous mutations in human adenovirus 5 under conditions of minimal selection. Based on >200 single-base spontaneous mutations detected throughout the entire viral genome, we infer an average mutation rate of 1.3 × 10−7 per base per cell infection cycle. This value is similar to those of other, large double-stranded DNA viruses, but an order of magnitude lower than those of single-stranded DNA viruses, consistent with the possible action of post-replicative repair. Although the mutation rate did not vary strongly along the adenovirus genome, we found several sources of mutation rate heterogeneity. First, two regions mapping to transcription units L3 and E1B-IVa2 were significantly depleted for mutations. Second, several point insertions/deletions located within low-complexity sequence contexts appeared recurrently, suggesting mutational hotspots. Third, mutation probability increased at GpC dinucleotides. Our findings suggest that host factors may influence the distribution of spontaneous mutations in human adenoviruses and potentially other nuclear DNA viruses.

Fast genotyping of known SNPs through approximate k-mer matching.

As the volume of next-generation sequencing (NGS) data increases, faster algorithms become necessary. Although speeding up individual components of a sequence analysis pipeline (e.g. read mapping) can reduce the computational cost of analysis, such approaches do not take full advantage of the particulars of a given problem. One problem of great interest, genotyping a known set of variants (e.g. dbSNP or Affymetrix SNPs), is important for characterization of known genetic traits and causative disease variants within an individual, as well as the initial stage of many ancestral and population genomic pipelines (e.g. GWAS). We introduce lightweight assignment of variant alleles (LAVA), an NGS-based genotyping algorithm for a given set of SNP loci, which takes advantage of the fact that approximate matching of mid-size k-mers (with k = 32) can typically uniquely identify loci in the human genome without full read alignment. LAVA accurately calls the vast majority of SNPs in dbSNP and Affymetrix's Genome-Wide Human SNP Array 6.0 up to about an order of magnitude faster than standard NGS genotyping pipelines. For Affymetrix SNPs, LAVA has significantly higher SNP calling accuracy than existing pipelines while using as low as ∼5 GB of RAM. As such, LAVA represents a scalable computational method for population-level genotyping studies as well as a flexible NGS-based replacement for SNP arrays. LAVA software is available at http://lava.csail.mit.edu bab@mit.edu Supplementary data are available at Bioinformatics online.

Clinical Next-Generation Sequencing Pipeline Outperforms a Combined Approach Using Sanger Sequencing and Multiplex Ligation-Dependent Probe Amplification in Targeted Gene Panel Analysis

Advances in next-generation sequencing (NGS) have facilitated parallel analysis of multiple genes enabling the implementation of cost-effective, rapid, and high-throughput methods for the molecular diagnosis of multiple genetic conditions, including the identification of BRCA1 and BRCA2 mutations in high-risk patients for hereditary breast and ovarian cancer. We clinically validated a NGS pipeline designed to replace Sanger sequencing and multiplex ligation-dependent probe amplification analysis and to facilitate detection of sequence and copy number alterations in a single test focusing on a BRCA1/BRCA2 gene analysis panel. Our custom capture library covers 46 exons, including BRCA1 exons 2, 3, and 5 to 24 and BRCA2 exons 2 to 27, with 20 nucleotides of intronic regions both 5' and 3' of each exon. We analyzed 402 retrospective patients, with previous Sanger sequencing and multiplex ligation-dependent probe amplification results, and 240 clinical prospective patients. One-hundred eighty-three unique variants, including sequence and copy number variants, were detected in the retrospective (n=95) and prospective (n=88) cohorts. This standardized NGS pipeline demonstrated 100% sensitivity and 100% specificity, uniformity, and high-depth nucleotide coverage per sample (approximately 7000 reads per nucleotide). Subsequently, the NGS pipeline was applied to the analysis of larger gene panels, which have shown similar uniformity, sample-to-sample reproducibility in coverage distribution, and sensitivity and specificity for detection of sequence and copy number variants.

Navigating highly homologous genes in a molecular diagnostic setting: a resource for clinical next-generation sequencing.

Next-generation sequencing (NGS) is now routinely used to interrogate large sets of genes in a diagnostic setting. Regions of high sequence homology continue to be a major challenge for short-read technologies and can lead to false-positive and false-negative diagnostic errors. At the scale of whole-exome sequencing (WES), laboratories may be limited in their knowledge of genes and regions that pose technical hurdles due to high homology. We have created an exome-wide resource that catalogs highly homologous regions that is tailored toward diagnostic applications. This resource was developed using a mappability-based approach tailored to current Sanger and NGS protocols. Gene-level and exon-level lists delineate regions that are difficult or impossible to analyze via standard NGS. These regions are ranked by degree of affectedness, annotated for medical relevance, and classified by the type of homology (within-gene, different functional gene, known pseudogene, uncharacterized noncoding region). Additionally, we provide a list of exons that cannot be analyzed by short-amplicon Sanger sequencing. This resource can help guide clinical test design, supplemental assay implementation, and results interpretation in the context of high homology.Genet Med 18 12, 1282-1289.

Development and Validation of a Mass Spectrometry–Based Assay for the Molecular Diagnosis of Mucin-1 Kidney Disease

Mucin-1 kidney disease, previously described as medullary cystic kidney disease type 1 (MCKD1, OMIM 174000), is an autosomal dominant tubulointerstitial kidney disease recently shown to be caused by a single-base insertion within the variable number tandem repeat region of the MUC1 gene. Because of variable age of disease onset and often subtle signs and symptoms, clinical diagnosis of mucin-1 kidney disease and differentiation from other forms of hereditary kidney disease have been difficult. The causal insertion resides in a variable number tandem repeat region with high GC content, which has made detection by standard next-generation sequencing impossible to date. The inherently difficult nature of this mutation required an alternative method for routine detection and clinical diagnosis of the disease. We therefore developed and validated a mass spectrometry-based probe extension assay with a series of internal controls to detect the insertion event using 24 previously characterized positive samples from patients with mucin-1 kidney disease and 24 control samples known to be wild type for the variant. Validation results indicate an accurate and reliable test for clinically establishing the molecular diagnosis of mucin-1 kidney disease with 100% sensitivity and specificity across 275 tests called.

Visual programming for next-generation sequencing data analytics.

BackgroundHigh-throughput or next-generation sequencing (NGS) technologies have become an established and affordable experimental framework in biological and medical sciences for all basic and translational research. Processing and analyzing NGS data is challenging. NGS data are big, heterogeneous, sparse, and error prone. Although a plethora of tools for NGS data analysis has emerged in the past decade, (i) software development is still lagging behind data generation capabilities, and (ii) there is a ‘cultural’ gap between the end user and the developer.TextGeneric software template libraries specifically developed for NGS can help in dealing with the former problem, whilst coupling template libraries with visual programming may help with the latter. Here we scrutinize the state-of-the-art low-level software libraries implemented specifically for NGS and graphical tools for NGS analytics. An ideal developing environment for NGS should be modular (with a native library interface), scalable in computational methods (i.e. serial, multithread, distributed), transparent (platform-independent), interoperable (with external software interface), and usable (via an intuitive graphical user interface). These characteristics should facilitate both the run of standardized NGS pipelines and the development of new workflows based on technological advancements or users’ needs. We discuss in detail the potential of a computational framework blending generic template programming and visual programming that addresses all of the current limitations.ConclusionIn the long term, a proper, well-developed (although not necessarily unique) software framework will bridge the current gap between data generation and hypothesis testing. This will eventually facilitate the development of novel diagnostic tools embedded in routine healthcare.

Practical Acute Myeloid Leukemia (AML) Biomarker Testing Using Next-Generation Sequencing (NGS) Technology: A Comprehensive, Rapid, Inexpensive and Flexible Approach

The diagnostic category of AML includes a very heterogeneous group of neoplasms but progress has been made in recent years to identify biologically and clinically relevant genomic biomarkers that aid in further sub classification, provide more accurate prognostic information and supply targets for tumor-specific therapy and monitoring of residual disease. At this time, clinically relevant biomarkers include single nucleotide variants (SNVs), small insertions and deletions (indels) and a variety of translocations. They involve many different genes, including CEBPA, which is a highly G/C nucleotide-rich gene that is extremely difficult to evaluate using standard NGS methods. Because of the number and complexity of biomarkers, it has been a challenge for clinical laboratories to provide testing that is of practical clinical use; most approaches require multiple testing modalities, including less than satisfactory commercial sequencing panels, resulting in poor clinical testing service with respect to biomarker coverage, turn-around time and cost.We have developed an integrated "laboratory-developed" NGS-based approach that evaluates all current, clinically relevant AML biomarkers simultaneously (including CEBPA and identity markers for post-transplant chimerism evaluation), in as little as 2.5 days (<6 hrs hands-on time) for a total cost of only a few hundred dollars per sample. The method is flexible with respect to future, custom addition of newly discovered biomarkers and can be used on any of the Life Technologies or Illumina NGS platforms. Briefly, the method involves extraction of both DNA and RNA, the use of 3 slightly different techniques for initial library preparation (one each for CEBPA, other small variants, and translocations), followed by addition of indexed sequencing ends for either of the major sequencing technologies, pooling of the libraries and sequencing. The data analysis pipeline is rapid and simple to use and was custom created using predominantly readily available software.The method was used successfully to evaluate 50 patient blood/liquid bone marrow aspirate samples and 25 custom-designed DNA synthetics containing previously identified variants in ASXL1, BRINP3, CEBPA, DNMT3A, EZH2, FLT3, GATA1, GATA2, HNRNPK, IDH1, IDH2, KIT, KRAS, KMT2A(a.k.a. MLL), NPM1, NRAS, PHF6, PTPN11, RAD21, RUNX1, SMC1A, SMC3, STAG2, TET2, TP53, U2AF1, WT1, and translocations CBFB/MYH11, DEK/NUP214, KMT2A(a.k.a.MLL)/X=any partner, PML/RARA, NUMA1/RARA, STAT5B/RARA, ZBTB16/RARA, RBM15/MKL1, RPN1/MECOM, RUNX1/RUNX1T1 with 100% concordance and reproducibility. It has a reliable sensitivity of at least 1% and further evaluation is underway to establish the limit of detection for each target-type using ultra-deep sequencing, to determine acceptability for residual disease detection. The assay was shown to be 100% specific when challenged with normal samples.This integrated approach is novel and makes maximal use of available sequencing technology to simplify clinical biomarker evaluation, as required for practical management of patients with AML. DisclosuresNo relevant conflicts of interest to declare.

A draft genome sequence of an invasive mosquito: an Italian Aedes albopictus

The draft genome sequence of Italian specimens of the Asian tiger mosquito Aedes (Stegomyia) albopictus (Diptera: Culicidae) was determined using a standard NGS (next generation sequencing) approach. The size of the assembled genome is comparable to that of Aedes aegypti; the two mosquitoes are also similar as far as the high content of repetitive DNA is concerned, most of which is made up of transposable elements. Although, based on BUSCO (Benchmarking Universal Single-Copy Orthologues) analysis, the genome assembly reported here contains more than 99% of protein-coding genes, several of those are expected to be represented in the assembly in a fragmented state. We also present here the annotation of several families of genes (tRNA genes, miRNA genes, the sialome, genes involved in chromatin condensation, sex determination genes, odorant binding proteins and odorant receptors). These analyses confirm that the assembly can be used for the study of the biology of this invasive vector of disease.

In Silico HLA Typing Using Standard RNA-Seq Sequence Reads.

Next-generation sequencing (NGS) enables high-throughput transcriptome profiling using the RNA-Seq assay, resulting in billions of short sequence reads. Worldwide adoption has been rapid: many laboratories worldwide generate transcriptome sequence reads daily. Here, we describe methods for obtaining a sample's human leukocyte antigen (HLA) class I and II types and HLA expression using standard NGS RNA-Seq sequence reads. We demonstrate the application using our algorithm, seq2HLA, and a publicly available RNA-Seq dataset from the Burkitt lymphoma cell line Raji.

Combined examination of sequence and copy number variations in human deafness genes improves diagnosis for cases of genetic deafness.

BackgroundCopy number variations (CNVs) are the major type of structural variation in the human genome, and are more common than DNA sequence variations in populations. CNVs are important factors for human genetic and phenotypic diversity. Many CNVs have been associated with either resistance to diseases or identified as the cause of diseases. Currently little is known about the role of CNVs in causing deafness. CNVs are currently not analyzed by conventional genetic analysis methods to study deafness. Here we detected both DNA sequence variations and CNVs affecting 80 genes known to be required for normal hearing.MethodsCoding regions of the deafness genes were captured by a hybridization-based method and processed through the standard next-generation sequencing (NGS) protocol using the Illumina platform. Samples hybridized together in the same reaction were analyzed to obtain CNVs. A read depth based method was used to measure CNVs at the resolution of a single exon. Results were validated by the quantitative PCR (qPCR) based method.ResultsAmong 79 sporadic cases clinically diagnosed with sensorineural hearing loss, we identified previously-reported disease-causing sequence mutations in 16 cases. In addition, we identified a total of 97 CNVs (72 CNV gains and 25 CNV losses) in 27 deafness genes. The CNVs included homozygous deletions which may directly give rise to deleterious effects on protein functions known to be essential for hearing, as well as heterozygous deletions and CNV gains compounded with sequence mutations in deafness genes that could potentially harm gene functions.ConclusionsWe studied how CNVs in known deafness genes may result in deafness. Data provided here served as a basis to explain how CNVs disrupt normal functions of deafness genes. These results may significantly expand our understanding about how various types of genetic mutations cause deafness in humans.

Comprehensive Diagnostic Testing for Stereocilin: An Approach for Analyzing Medically Important Genes with High Homology

Next-generation sequencing (NGS) technologies have revolutionized genetic testing by enabling simultaneous analysis of unprecedented numbers of genes. However, genes with high-sequence homology pose challenges to current NGS technologies. Because diagnostic sequencing is moving toward exome analysis, knowledge of these homologous genes is essential to avoid false positive and negative results. An example is the STRC gene, one of >70 genes known to contribute to the genetic basis of hearing loss. STRC is 99.6% identical to a pseudogene (pSTRC) and therefore inaccessible to standard NGS methodologies. The STRC locus is also known to be a common site for large deletions. Comprehensive diagnostic testing for inherited hearing loss therefore necessitates a combination of several approaches to avoid pseudogene interference. We have developed a clinical test that combines standard NGS and NGS-based copy number assessment supplemented with a long-range PCR-based Sanger or MiSeq assay to eliminate pseudogene contamination. By using this combination of assays we could identify biallelic STRC variants in 14% (95% CI, 8%-24%) of individuals with isolated nonsyndromic hearing loss who had previously tested negative on our 70-gene hearing loss panel, corresponding to a detection rate of 11.2% (95% CI, 6%-19%) for previously untested patients. This approach has broad applicability because medically significant genes for many disease areas include genes with high-sequence homology.

A catalog of HLA type, HLA expression, and neo-epitope candidates in human cancer cell lines

Cancer cell lines are a tremendous resource for cancer biology and therapy development. These multipurpose tools are commonly used to examine the genetic origin of cancers, to identify potential novel tumor targets, such as tumor antigens for vaccine devel­opment, and utilized to screen potential therapies in preclinical studies. Mutations, gene expression, and drug sensitivity have been determined for many cell lines using next-generation sequencing (NGS). However, the human leukocyte antigen (HLA) type and HLA expression of tumor cell lines, characterizations necessary for the development of cancer vaccines, have remained largely incomplete and, such information, when available, has been distributed in many publications. Here, we determine the 4-digit HLA type and HLA expression of 167 cancer and 10 non-cancer cell lines from publically available RNA-Seq data. We use standard NGS RNA-Seq short reads from “whole transcriptome” sequencing, map reads to known HLA types, and statistically determine HLA type, heterozygosity, and expression. First, we present previously unreported HLA Class I and II genotypes. Second, we determine HLA expression levels in each cancer cell line, providing insights into HLA downregulation and loss in cancer. Third, using these results, we provide a fundamental cell line “barcode” to track samples and prevent sample annotation swaps and contamination. Fourth, we integrate the cancer cell-line specific HLA types and HLA expression with available cell-line specific mutation information and existing HLA binding prediction algorithms to make a catalog of predicted antigenic mutations in each cell line. The compilation of our results are a fundamental resource for all researchers selecting specific cancer cell lines based on the HLA type and HLA expression, as well as for the development of immunotherapeutic tools for novel cancer treatment modalities.

DNA polymerases drive DNA sequencing-by-synthesis technologies: both past and present.

Next-generation sequencing (NGS) technologies have revolutionized modern biological and biomedical research. The engines responsible for this innovation are DNA polymerases; they catalyze the biochemical reaction for deriving template sequence information. In fact, DNA polymerase has been a cornerstone of DNA sequencing from the very beginning. Escherichia coli DNA polymerase I proteolytic (Klenow) fragment was originally utilized in Sanger’s dideoxy chain-terminating DNA sequencing chemistry. From these humble beginnings followed an explosion of organism-specific, genome sequence information accessible via public database. Family A/B DNA polymerases from mesophilic/thermophilic bacteria/archaea were modified and tested in today’s standard capillary electrophoresis (CE) and NGS sequencing platforms. These enzymes were selected for their efficient incorporation of bulky dye-terminator and reversible dye-terminator nucleotides respectively. Third generation, real-time single molecule sequencing platform requires slightly different enzyme properties. Enterobacterial phage ϕ29 DNA polymerase copies long stretches of DNA and possesses a unique capability to efficiently incorporate terminal phosphate-labeled nucleoside polyphosphates. Furthermore, ϕ29 enzyme has also been utilized in emerging DNA sequencing technologies including nanopore-, and protein-transistor-based sequencing. DNA polymerase is, and will continue to be, a crucial component of sequencing technologies.