False Positive Variants Research Articles

Abstract 5690: Optimized molecular barcoding enables accurate targeted mutation detection in circulating cell-free DNA (cfDNA)

Abstract The evaluation of cfDNA allows novel approaches to noninvasive detection of actionable alterations, resistance mechanisms, and tumor monitoring in patients with cancer. Importantly, tumor-specific DNA fragments represent a small minority of the cfDNA and can be obscured by false positive (FP) variants introduced by chemical damage and sequencer error. To address this, we improved key processes in the design of NGS libraries, including a new molecular barcoding approach, that maximize molecular recovery while eliminating spurious variants. We engineered a set of Illumina sequencing chemistry compatible adaptors incorporating unique molecular identifiers (barcodes) enabling reconstruction of the sequence of both strands of the original DNA molecule. These barcodes incorporate a number of key design improvements as compared to published methodologies, which enhance sequencer cluster density, thereby increasing library diversity and molecular recovery. Our new design identified both chemical and sequencer errors, reducing incorrect base calls to rates below 5e-7. We validated our methodology for use in cfDNA using both dilution experiments and patient blood samples with known oncogenic alterations via a custom capture panel targeting actionable genomic alterations in a 55kb region. By identifying the molecular origin of each read, we found that the sensitivity of detection obtained from barcoded libraries followed ideal binomial sampling expectations. We obtained an average molecular depth of 1,000 molecules per site from the plasma extracted from a single blood collection tube, which corresponded to an 80% sensitivity of detection of known oncogenic single-nucleotide and indel mutations at 0.15% mutant allele frequency (MAF) in cfDNA with no FP calls. Furthermore, we successfully detected known gene-fusions at 0.5%, and amplifications (>10 copies) down to 1% MAF. We designed and validated a custom-engineered error-correcting sequencing adapters, ideal for broad range of applications requiring high accuracy detection of ultra-low frequency alterations. Note: This abstract was not presented at the meeting. Citation Format: Carlo G. Artieri, Kyle A. Beauchamp, Valentina S. Vysotskaia, Noah C. Welker, Eric A. Evans, Clement Chu, Haluk Tezcan, Imran S. Haque. Optimized molecular barcoding enables accurate targeted mutation detection in circulating cell-free DNA (cfDNA) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5690. doi:10.1158/1538-7445.AM2017-5690

Abstract 3732: Analytical performance of TruSight® Tumor 170 on small nucleotide variations and gene amplifications using DNA from formalin-fixed, paraffin-embedded (FFPE) solid tumor samples

Abstract Expanding the paradigm of solid tumor profiling from single-gene testing to comprehensive panels presents many challenges. One such challenges is the ability of these panels to detect genetic alterations from FFPE samples, where the DNA is of low abundance and often heavily compromised. Despite these challenges, next-generation sequencing (NGS) offers the ability to assess multiple variants simultaneously in an ever-expanding list of relevant tumor genes. To that end, Illumina developed a comprehensive, hybrid capture-based NGS assay targeting 170 key cancer genes that is FFPE optimized. The assay consists of a DNA workflow for the identification of single and multiple nucleotide variants (SNVs, MNVs), small insertions and deletions (indels), gene amplifications, as well as a RNA workflow for the identification of splice variants and gene fusions. Following sequencing on the NextSeq® or HiSeq® instruments, the analytical pipeline initiates variant calling. The DNA aligner and variant callers were first optimized against the simulated read data from >40,000 COSMIC[1] mutations reported in the exons of the 170 genes. To reduce false positive variant calling due to systematic errors, each variant call was evaluated against its locus specific background error distribution. This distribution was compiled from a panel of FFPE normal samples and was also used to normalize against systematic bias in read coverage to increase the accuracy of amplification calling. Furthermore, gene amplification calling was improved by the addition of enhancer probes to the hybrid capture pool. The analytical sensitivity and specificity of TruSight® Tumor 170* was assessed on a large collection of FFPE samples and reference material. A panel of 72 cancer samples, including multiple tissue types, reference standards, and cell line and FFPE mixes were used to evaluate the limit of detection. The samples contained 533 SNVs, 80 indels including deletions up to 30 base pairs and insertions up to 31 base pairs, 4 MNVs, and 31 gene amplifications, characterized by orthogonal testing methods. Using 40 ng DNA input, detection sensitivity of the >1000 variants (including replicates) tested at variant allele frequencies down to ~5% was at 99.6%, while detection sensitivity of gene amplifications as low as 1.45x to 2.2x was at 98%. For limit of blank samples, a panel of 24 normal samples was used. Again using 40 ng DNA input, we show >99% specificity for small variant calling and >95% specificity for gene amplification calling. These data demonstrates the TruSight® Tumor 170 is able to detect multiple variant types within a single sample at low nucleic acid input, while exhibiting high analytical sensitivity and specificity for low allele fraction detection. [1] Forbes, et al. (2015) *For Research Use Only. Not for use in diagnostic procedures. Citation Format: Danny Chou, Xiao Chen, Austin Purdy, Li Teng, Byron Luo, Chen Zhao, Laurel Ball, Allan Castaneda, Katie Clark, Brian Crain, Anthony Daulo, Manh Do, Tingting Du, Sarah Dumm, Yonmee Han, Michael Havern, Chia-Ling Hsieh, Tingting Jiang, Suzanne Johansen, Scott Lang, Rachel Liang, Jennifer S. LoCoco, Jaime McLean, Yousef Nassiri, Jason Rostron, Jennifer Silhavy, June Snedecor, Natasha Talago, Kevin Wu, Clare Zlatkov, Ali Kuraishy, Karen Gutekunst, Sohela De Rozieres, Matthew Friedenberg, Han-Yu Chuang, Anne C. Jager. Analytical performance of TruSight® Tumor 170 on small nucleotide variations and gene amplifications using DNA from formalin-fixed, paraffin-embedded (FFPE) solid tumor samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3732. doi:10.1158/1538-7445.AM2017-3732

Abstract LB-249: Examination of analytical factors impacting concordance of plasma-tumor testing by next-generation sequencing (NGS)

Abstract The increased usage of circulating tumor DNA (ctDNA) sequencing for oncology clinical research demonstrates a critical need for sensitive and specific testing. While we have observed a high degree of concordance between single tumor mutations in tumor and plasma, several recent studies have highlighted a lack of concordance between plasma and tumor panel NGS gene panel testing due to biological and technical factors. To explore further these factors and benchmark ctDNA NGS testing services, a set of matched plasma, tumor, and normal samples from 24 subjects were acquired from three biobanking companies. Replicate 2 ml-plasma samples were tested by four ctDNA sequencing companies, and matching tumor/normal samples were tested by two tumor sequencing companies. Concordance was measured by comparing plasma mutations to tumor mutations as well as comparing mutations among the same plasma tested by the ctDNA companies. While our experience with NGS of matched samples from clinical trials typically identifies ~30% of patients with no detectable mutation and therefore likely not shedding tumor DNA, with the retrospectively collected commercial samples ~60% lacked detectable high confidence mutations, likely due to quality control issues with sample collection. We also found variation in the concordance of ctDNA mutation detection rates among the four vendors, due to significant differences in DNA yield and assay sensitivity. While factors such as tumor heterogeneity and timing of plasma-tumor collection can lower concordance rates, the majority of discordance in our study was due to technical rather than biological variation. Assay analytical variance and the impact of reporting false positive variants are key factors that need to be addressed as plasma-based NGS testing is more widely incorporated into translational and clinical research. Examples illustrating the complexity of the analyses and giving support for confidence in ctDNA testing results will be given. Citation Format: Daniel Stetson, Brian Dougherty, Ambar Ahmed, Tristan Lubinski, Aleksandra Markovets, Kenneth Thress, Robert McEwen, Gaia Schiavon, David Whitston, Barrett Nuttall, J. Carl Barrett. Examination of analytical factors impacting concordance of plasma-tumor testing by next-generation sequencing (NGS) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-249. doi:10.1158/1538-7445.AM2017-LB-249

AfterQC: automatic filtering, trimming, error removing and quality control for fastq data

BackgroundSome applications, especially those clinical applications requiring high accuracy of sequencing data, usually have to face the troubles caused by unavoidable sequencing errors. Several tools have been proposed to profile the sequencing quality, but few of them can quantify or correct the sequencing errors. This unmet requirement motivated us to develop AfterQC, a tool with functions to profile sequencing errors and correct most of them, plus highly automated quality control and data filtering features. Different from most tools, AfterQC analyses the overlapping of paired sequences for pair-end sequencing data. Based on overlapping analysis, AfterQC can detect and cut adapters, and furthermore it gives a novel function to correct wrong bases in the overlapping regions. Another new feature is to detect and visualise sequencing bubbles, which can be commonly found on the flowcell lanes and may raise sequencing errors. Besides normal per cycle quality and base content plotting, AfterQC also provides features like polyX (a long sub-sequence of a same base X) filtering, automatic trimming and K-MER based strand bias profiling.ResultsFor each single or pair of FastQ files, AfterQC filters out bad reads, detects and eliminates sequencer’s bubble effects, trims reads at front and tail, detects the sequencing errors and corrects part of them, and finally outputs clean data and generates HTML reports with interactive figures. AfterQC can run in batch mode with multiprocess support, it can run with a single FastQ file, a single pair of FastQ files (for pair-end sequencing), or a folder for all included FastQ files to be processed automatically. Based on overlapping analysis, AfterQC can estimate the sequencing error rate and profile the error transform distribution. The results of our error profiling tests show that the error distribution is highly platform dependent.ConclusionMuch more than just another new quality control (QC) tool, AfterQC is able to perform quality control, data filtering, error profiling and base correction automatically. Experimental results show that AfterQC can help to eliminate the sequencing errors for pair-end sequencing data to provide much cleaner outputs, and consequently help to reduce the false-positive variants, especially for the low-frequency somatic mutations. While providing rich configurable options, AfterQC can detect and set all the options automatically and require no argument in most cases.

GLM-based optimization of NGS data analysis: A case study of Roche 454, Ion Torrent PGM and Illumina NextSeq sequencing data.

BackgroundThere are various next-generation sequencing techniques, all of them striving to replace Sanger sequencing as the gold standard. However, false positive calls of single nucleotide variants and especially indels are a widely known problem of basically all sequencing platforms.MethodsWe considered three common next-generation sequencers—Roche 454, Ion Torrent PGM and Illumina NextSeq—and applied standard as well as optimized variant calling pipelines. Optimization was achieved by combining information of 23 diverse parameters characterizing the reported variants and generating individually calibrated generalized linear models. Models were calibrated using amplicon-based targeted sequencing data (19 genes, 28,775 bp) from seven to 12 myelodysplastic syndrome patients. Evaluation of the optimized pipelines and platforms was performed using sequencing data from three additional myelodysplastic syndrome patients.ResultsUsing standard analysis methods, true mutations were missed and the obtained results contained many artifacts—no matter which platform was considered. Analysis of the parameters characterizing the true and false positive calls revealed significant platform- and variant specific differences. Application of optimized variant calling pipelines considerably improved results. 76% of all false positive single nucleotide variants and 97% of all false positive indels could be filtered out. Positive predictive values could be increased by factors of 1.07 to 1.27 in case of single nucleotide variant calling and by factors of 3.33 to 53.87 in case of indel calling. Application of the optimized variant calling pipelines leads to comparable results for all next-generation sequencing platforms analyzed. However, regarding clinical diagnostics it needs to be considered that even the optimized results still contained false positive as well as false negative calls.

Variant profiling of evolving prokaryotic populations.

Genomic heterogeneity of bacterial species is observed and studied in experimental evolution experiments and clinical diagnostics, and occurs as micro-diversity of natural habitats. The challenge for genome research is to accurately capture this heterogeneity with the currently used short sequencing reads. Recent advances in NGS technologies improved the speed and coverage and thus allowed for deep sequencing of bacterial populations. This facilitates the quantitative assessment of genomic heterogeneity, including low frequency alleles or haplotypes. However, false positive variant predictions due to sequencing errors and mapping artifacts of short reads need to be prevented. We therefore created VarCap, a workflow for the reliable prediction of different types of variants even at low frequencies. In order to predict SNPs, InDels and structural variations, we evaluated the sensitivity and accuracy of different software tools using synthetic read data. The results suggested that the best sensitivity could be reached by a union of different tools, however at the price of increased false positives. We identified possible reasons for false predictions and used this knowledge to improve the accuracy by post-filtering the predicted variants according to properties such as frequency, coverage, genomic environment/localization and co-localization with other variants. We observed that best precision was achieved by using an intersection of at least two tools per variant. This resulted in the reliable prediction of variants above a minimum relative abundance of 2%. VarCap is designed for being routinely used within experimental evolution experiments or for clinical diagnostics. The detected variants are reported as frequencies within a VCF file and as a graphical overview of the distribution of the different variant/allele/haplotype frequencies. The source code of VarCap is available at https://github.com/ma2o/VarCap. In order to provide this workflow to a broad community, we implemeted VarCap on a Galaxy webserver, which is accessible at http://galaxy.csb.univie.ac.at.

Improvements and impacts of GRCh38 human reference on high throughput sequencing data analysis

Analyses of high throughput sequencing data starts with alignment against a reference genome, which is the foundation for all re-sequencing data analyses. Each new release of the human reference genome has been augmented with improved accuracy and completeness. It is presumed that the latest release of human reference genome, GRCh38 will contribute more to high throughput sequencing data analysis by providing more accuracy. But the amount of improvement has not yet been quantified. We conducted a study to compare the genomic analysis results between the GRCh38 reference and its predecessor GRCh37. Through analyses of alignment, single nucleotide polymorphisms, small insertion/deletions, copy number and structural variants, we show that GRCh38 offers overall more accurate analysis of human sequencing data. More importantly, GRCh38 produced fewer false positive structural variants. In conclusion, GRCh38 is an improvement over GRCh37 not only from the genome assembly aspect, but also yields more reliable genomic analysis results.

Prevalence of RNA Editing Events Affecting Coding Regions in Pediatric Leukemia

Introduction: Post-transcriptional modification of RNA, known as RNA-editing, has been shown to occur in many species including human. A recent study using genomic data from adult solid tumors generated by The Cancer Genome Atlas project (TCGA) investigated the potential effects of RNA editing on cancer cell viability, invasion potential, cancer pathogenesis and drug sensitivity (Han, et al., Cancer Cell 2015). Historically, there have been mixed reports regarding the prevalence of RNA editing in human cells, partly due to substantial difficulties in distinguishing RNA editing events from mapping artifacts in next-generation sequencing (NGS) data. In this study, we developed a suite of computational analysis tools to enable precise mapping of RNA-Seq in order to carry out the first systematic investigation of RNA editing events affecting coding regions in pediatric leukemia.Methods: We developed a knowledge-guided accurate RNA-Seq mapping pipeline named StrongArm to maximize mapping accuracy and efficiency. StrongArm performs multiple mappings with different aligners and databases, and uses a set of competition heuristics to choose an optimal mapping, thereby reducing the mapping error rate and bias introduced by any single aligner, especially for error-prone splice junction sites and paralogs. The analysis was performed on 17 leukemia samples including 10 acute myeloid leukemia subtype M7 (AMLM7) and 7 Ph-like acute lymphoblastic leukemia (Ph-like ALL), which were profiled using RNA-Seq of tumor samples and whole-genome sequencing or whole-exome sequencing of paired tumor and normal DNA samples. The single nucleotide variants (SNVs) detected in RNA-Seq, but absent in DNA samples, were considered putative editing events and were further processed to remove additional false positives that could not be corrected by the mapping pipeline alone. These false positive variants, arising from paralog mapping artifacts, genetic polymorphisms, nano exons, and sequencing errors at homopolymer loci introduced by reverse transcription, account for 96% to 99% of putative DNA-RNA coding variants in the leukemia samples.Results: Using 17 leukemia samples, we identified a total of 103 RNA editing events in coding regions affecting 43 unique loci, 92% of which were canonical A-to-G or C-to-T editing; 62 (61%) and 66 (64%) of the 103 editing events match those in the RNA editing database DARNED and RADAR, respectively. Seventy-eight (76%) of 103 editing events resulted in missense variants, suggesting that they may potentially affect protein function. The four most prevalent RNA editing events were present in 30% our leukemia samples, including COG3 I635V (n=12), BLCAP Q5R (n=10), CDK13 Q103R (n=9) and AZIN1 S367G (n=6). Previous studies have shown that AZIN1 S367G and COG3 I635V impact cell proliferation, and that BLCAP Q5R is correlated with survival rate in renal clear cell carcinoma (Han, et al., Cancer Cell 2015), while the impact of CDK13 Q103R in leukemia is unknown. Interestingly, three of four candidate "master" driver editing sites identified in TCGA solid tumors, AZIN1 S367G, COPA I164V, and COG3 I635V were also present in our data set, while GRIA2 R764G is absent, as GRIA2 is not expressed in leukemia.Conclusions and Discussion: Leveraging an accurate mapping pipeline for RNA-seq data, we found that pediatric leukemia samples have fewer RNA-editing events (3 to 14 per sample) in coding exons, comparable to the informative coding RNA-editing events identified in adult solid tumors from the TCGA. Notably, 3 out of the 4 most common RNA-editing sites in our leukemia samples have been reported to have functional effects on cell survival / proliferation or have been correlated with patient survival rate in adult solid tumors, indicating that RNA-editing in coding regions may have a functional impact on leukemia tumorigenesis. DisclosuresMullighan:Incyte: Membership on an entity's Board of Directors or advisory committees; Amgen: Speakers Bureau; Loxo Oncology: Research Funding.

Amplicon Based Panel Targeted Resequencing Identified ZRSR2 As a Potential New Favorable Marker in Pediatric AML

Introduction:Acute myeloid leukemia (AML) is one of the most threatening malignancies in children and adolescents. The accumulation of mutations in leukemia stem cells (LSC) is believed to lead to the development of leukemia. Cyto- and molecular genetics already identified several aberrations which are relevant in leukemogenesis, prognosis and therapy. Nevertheless, the molecular landscape and clonal evolution of AML and its clinical relevance, especially for pediatric patients, is not yet well described. Next Generation Sequencing (NGS) as an emerging sequencing technology provides the possibility to generate sequence data of high quality and detect genetic aberrations in a minimum of time. The aim of this study was to apply amplicon based panel targeted resequencing by using the TruSight Myeloid Panel (Illumina) to identify variants in 54 genes.MethodsPatients:In total 150 samples derived from pediatric patients diagnosed with AML at the time of initial diagnosis or relapse were analysed regarding their mutational profile. All patients treated according to the AML-BFM therapy protocols (n=103) were chosen to determine the potential impact in prognosis.Sequencing and analysis of variantsSequencing with the TruSight Myeloid panel (Illumina) was performed on a MiseqDX. The sequencing panel is designed to identify somatic mutations associated with myeloid malignancies in 54 genes. To define variants, we excluded intronic, synonymous and variants with an allele frequency below 5% and a read depth below 50 reads. False positive variants were excluded by including healthy donors and reference samples.Variants were detected and analysed using Variant studio (Illumina) and Sophia DDM (Sophia Genetics). Almost all variants were detectable in both software, although great insertions and deletions were detectable only by Sophia DDM.ResultsIn the cohort of 150 patients, we detected 408 mutations in the 54 genes included in the panel (fig. 1). 26% of the patients showed more than 4, 24% 3, 24% 2, 17% 1 and 9% of the patients showed 0 mutations. Four and more mutations occurred mostly in AML FAB M1 (n=17) and patients with a complex karyotype (n=6). Treatment related AML show less mutations compared to primary AML.Within the group of patients treated according the 1st line AML-BFM protocol (n=103), CEBPA, FLT3, KIT, NRAS, KRAS, NPM1 or WT1 mutations did not have prognostic relevance. Interestingly, we were able to detect mutations in ZRSR2 in 21 patients in total (SNVs in 6, InDels in 9 and splice acceptor variants in 6 patients). 15 patients were part of the group of patients who were treated according to the 1st line AML-BFM protocol. ZRSR2 encodes an essential splicing factor and the encoded protein associates with the U2 auxiliary factor heterodimer and may play a role in network interactions during spliceosome assembly [RefSeq 2008]. The presence of a ZRSR2 mutation seems to be associated with better EFS and lower cumulative incidence of relapse, respectively (fig.2). Even if patients with favourable cytogenetics were excluded, patients with mutated ZRSR2 might have better EFS (fig.2).Conclusions:Amplicon based panel targeted resequencing with the TruSight Myeloid panel provides the possibility to detect mutations in 54 genes associated to myeloid malignancies within 3 days. This will enable a faster and possible more precise characterisation of pediatric AML, either for risk group stratification or the addition of more specific treatment options. Due to the limited number of patients, the results concerning the prognostic relevance of ZRSR2 need to be confirmed in a larger patient group. [Display omitted] [Display omitted] [Display omitted] DisclosuresReinhardt:Jazz Pharma: Other: Travel Accomodation; Celgene: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Boehringer Ingelheim: Membership on an entity's Board of Directors or advisory committees.

Deamination Effects in Formalin-Fixed, Paraffin-Embedded Tissue Samples in the Era of Precision Medicine

Deamination of nucleotides causes C:G>T:A changes in formalin-fixed, paraffin-embedded (FFPE) tissue samples and produces false positives during next-generation sequencing (NGS). Uracil DNA glycosylase (UDG) helps eliminate this issue, but the effect of UDG in different tissue preparation conditions has not been rigorously studied. To investigate whether UDG can reduce false-positive single-nucleotide variant (SNV) calls, we used tumor and normal tissues from gastric adenocarcinoma patients prepared using different fixation times and pH conditions. FFPE tumor blocks >10 years were also evaluated for the comparison. We performed semiconductor-based NGS to evaluate nucleotide changes and used UDG to test deamination-related effects. Sequencing quality parameters mildly worsened with prolonged fixation time, acidic pH, and delayed fixation. SNV calls and C:G>T:A changes increased after >48 hours of fixation. In both recently prepared and old FFPE tissue blocks, UDG treatment reduced deamination-induced nucleotide changes. In the recently prepared samples, both high-quality SNVs and mean target coverage were remarkably increased on treatment with UDG. However, the quality of NGS results from old-age samples varied irrespective of UDG treatment. In conclusion, based on our findings, we believe that when performing NGS on recently embedded blocks, it is important to consider that certain poorly fixed samples may be at the risk of being deaminated, which can be corrected with UDG treatment.

Combination of RNA- and exome sequencing: Increasing specificity for identification of somatic point mutations and indels in acute leukaemia

Handling of large data sets from whole exome sequencing is a challenge, not the least because of the high risk of detecting false positive variants. Furthermore, there is still no consensus regarding what stage filtering of variants is performed in the bioinformatics pipeline to produce consistent result sets, the extent of filtering and how this is most optimal performed. We hypothesized that combination of coding transcriptome and exomes enables precise identification of both somatic single nucleotide and indel variants early in the bioinformatics process, superseding the need for extensive annotation and validation from external databases.Exome and RNA-sequencing were performed on diagnosis-remission paired bone marrow samples from 5 cytogenetically normal AML, i.e. sequencing of 20 samples in total. Intersection of rare exome and RNA variants, exclusively found in the diagnostic samples, yielded a median of 6 somatic point mutations and small indels, ranging from 3 to 21. Close correlation between routine diagnostic biomarkers was observed in 29/30 laboratory tests, with the exception of a large FLT3 internal tandem repeat, whereas WT1 with nonsense mutation lacked RNA transcripts. Additionally, the assay revealed mutations in DNMT3A, IDH2, TET2 and IL32 frame shift, not encompassed by routine panel.We thus describe a procedure to effectively reduce observations to a focused subset of high specificity. The approach is applicable to precise screening of both putative driver mutations and, often heterogeneous, discrete patient specific somatic combinations.

Next Generation Sequencing of Pooled Samples: Guideline for Variants’ Filtering

Sequencing large number of individuals, which is often needed for population genetics studies, is still economically challenging despite falling costs of Next Generation Sequencing (NGS). Pool-seq is an alternative cost- and time-effective option in which DNA from several individuals is pooled for sequencing. However, pooling of DNA creates new problems and challenges for accurate variant call and allele frequency (AF) estimation. In particular, sequencing errors confound with the alleles present at low frequency in the pools possibly giving rise to false positive variants. We sequenced 996 individuals in 83 pools (12 individuals/pool) in a targeted re-sequencing experiment. We show that Pool-seq AFs are robust and reliable by comparing them with public variant databases and in-house SNP-genotyping data of individual subjects of pools. Furthermore, we propose a simple filtering guideline for the removal of spurious variants based on the Kolmogorov-Smirnov statistical test. We experimentally validated our filters by comparing Pool-seq to individual sequencing data showing that the filters remove most of the false variants while retaining majority of true variants. The proposed guideline is fairly generic in nature and could be easily applied in other Pool-seq experiments.

Integration of 60,000 exomes and ACMG guidelines question the role of Catecholaminergic Polymorphic Ventricular Tachycardia-associated variants.

Catecholaminergic Polymorphic Ventricular Tachycardia (CPVT) is a highly lethal cardiac arrhythmia disease occurring during exercise or psychological stress. CPVT has an estimated prevalence of 1:10,000 and has mainly been associated with variants in calcium-regulating genes. Identification of potential false-positive pathogenic variants was conducted by searching the Exome Aggregation Consortium (ExAC) database (n = 60,706) for variants reported to be associated with CPVT. The pathogenicity of the interrogated variants was assessed using guidelines from the American College of Medical Genetics and Genomics (ACMG) and in silico prediction tools. Of 246 variants 38 (15%) variants previously associated with CPVT were identified in the ExAC database. We predicted the CPVT prevalence to be 1:132. The ACMG standards classified 29% of ExAC variants as pathogenic or likely pathogenic. The in silico predictions showed a reduced probability of disease-causing effect for the variants identified in the exome database (p < 0.001). We have observed a large overrepresentation of previously CPVT-associated variants in a large exome database. Based on the frequency of CPVT in the general population, it is less likely that the previously proposed variants are associated with a highly penetrant monogenic form of the disease.

Contamination-controlled high-throughput whole genome sequencing for influenza A viruses using the MiSeq sequencer.

Accurate full-length genomic sequences are important for viral phylogenetic studies. We developed a targeted high-throughput whole genome sequencing (HT-WGS) method for influenza A viruses, which utilized an enzymatic cleavage-based approach, the Nextera XT DNA library preparation kit, for library preparation. The entire library preparation workflow was adapted for the Sentosa SX101, a liquid handling platform, to automate this labor-intensive step. As the enzymatic cleavage-based approach generates low coverage reads at both ends of the cleaved products, we corrected this loss of sequencing coverage at the termini by introducing modified primers during the targeted amplification step to generate full-length influenza A sequences with even coverage across the whole genome. Another challenge of targeted HTS is the risk of specimen-to-specimen cross-contamination during the library preparation step that results in the calling of false-positive minority variants. We included an in-run, negative system control to capture contamination reads that may be generated during the liquid handling procedures. The upper limits of 99.99% prediction intervals of the contamination rate were adopted as cut-off values of contamination reads. Here, 148 influenza A/H3N2 samples were sequenced using the HTS protocol and were compared against a Sanger-based sequencing method. Our data showed that the rate of specimen-to-specimen cross-contamination was highly significant in HTS.

Characterization of MinION nanopore data for resequencing analyses

The Oxford Nanopore Technologies MinION is a new device, based on nanopore sequencing that is able to generate reads of tens of kilobases in length with faster sequencing time with respect to other platforms. To evaluate the capability of nanopore data to be exploited for resequencing analyses we used the largest MinION data set to date and we compared with Illumina and Pacific Biosciences technologies. By using five different mapping approaches we estimated that the global sequencing error rate of MinION reads, mainly caused by inserted and deleted bases, is around 11%. The study of error distribution showed that substituted, inserted and deleted bases are not randomly distributed along the reads, but mainly occur in specific nucleotide patterns, generating a significant number of genomic loci that can be misclassified as false-positive variants. With 40× sequencing coverage, MinION data can produce at best around one false substitution and insertion every 10-50 kb, and one false deletion every 1000 bp, making use of this technology still challenging for small-sized variant discovery. We also analyzed depth of coverage distribution and we demonstrated that nanopore sequencing is a uniform process that generates sequences randomly and independently without classical sources of bias such as GC-content and mappability. Owing to these properties, the MinION data can be readily used to detect genomic regions involved in copy number variants with high accuracy, outperforming other state-of-the-art sequencing methods in terms of both sensitivity and specificity.

Variations in the Genome: The Mutation Detection 2015 Meeting on Detection, Genome Sequencing, and Interpretation.

The content of the 13th Mutation Detection meeting (Leiden, April 2015) is summarized in this report. Topics discussed at the meeting included current challenges of clinical NGS, advances in bioinformatics, data quality control, single cell analysis and RNA sequencing, among others. Social, ethical and regulatory challenges of genomic data handling and data sharing were the focus of an expert panel debate. The 14th International Symposium on Variants in the Genome will take place in Santiago de Compostela, June 5-8, 2017. http://isv.variome.org.

Abstract 3616: Fix the fixation: effect of formalin fixation on targeted sequencing, variant calling and gene expression

Abstract Tumor biopsies are often Formalin-Fixed and Paraffin-Embedded (FFPE) for histological staining, genetic testing and archival purposes. Formalin treatment preserves tissue by crosslinking proteins, but can lead to mutation of the nucleic acid bases that can be detected by next-generation sequencing (NGS) methods despite being unrelated to the cancer. Studies have shown that certain fixation protocols are compatible with high quality nucleic acid isolation and variant calling by NGS. These studies used tissue fixed with 10% neutral buffered formalin for 24 hours, a standard protocol in the pathology field. In practice, however, FFPE sample handling varies from site-to-site. As we processed FFPE samples from various sites, we found that the quality of the isolated nucleic acids and subsequent sequencing results varied substantially. We hypothesized that this is due to deviations from the standard protocol such as improperly buffered reagents, variation in the fixation time and temperature, microwaving, and varied storage conditions of the samples. To understand the role of formalin fixation on the quality of the isolated nucleic acids and subsequent NGS analyses, we subjected the widely studied cell line NA12878 to various formalin fixation conditions. We then performed an augmented target enrichment and sequencing assay on both the DNA and RNA isolated from fresh frozen (FF) and formalin fixed (FFPE) NA12878 samples. We assessed raw nucleic acid quality, library quality, alignment rate, duplication rate, on-target efficiency and variant concordance between FF and FFPE. We noted substantial negative effects on sequencing library quality associated with sample incubation in unbuffered formalin, at high temperatures, and long periods of time (e.g. 3 days rather than 1 day). These harshly treated samples also showed poor alignment qualities, higher duplication rates, and lower mapping qualities. At the small variant level, they showed an increase in global C&amp;gt;T deamination (CG-&amp;gt;TA, 50% FFPE vs 35% in FF) and oxidation (CG-&amp;gt;AT, 15% FFPE vs 10% FF) rates. Variants caused by formalin fixation were most commonly detected at low (&amp;lt;5%) allele frequencies (AFs). When compared to gold set mutations in NA12878, we observed 80% false negative and 60% false positive variants in harshly treated samples. We are performing a similar analysis with RNA isolated from FF and FFPE NA12878 samples to understand the role of formalin on RNA variant and gene expression assays. Using the results of this study, we intend to provide guidance on optimal fixation conditions for NGS applications. It is crucial to fix tissues in buffered formalin for less than 24hr at room temperature to preserve nucleic acid integrity and amenability for downstream NGS assays. We also demonstrate how a deeper understanding of the effects of formalin can improve variant calling from FFPE tissues, especially at lower AFs where formalin-related errors have the greatest impact. Citation Format: Ravi Alla, Shujun Luo, Elena Helman, Sean M. Boyle, Michael J. Clark, Kirk Scott, Parin Sripakdeevong, Mirian Karbelashvili, Deanna M. Church, Michael Snyder, John West, Richard Chen. Fix the fixation: effect of formalin fixation on targeted sequencing, variant calling and gene expression. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3616.

Evaluating the necessity of PCR duplicate removal from next-generation sequencing data and a comparison of approaches

BackgroundAnalyzing next-generation sequencing data is difficult because datasets are large, second generation sequencing platforms have high error rates, and because each position in the target genome (exome, transcriptome, etc.) is sequenced multiple times. Given these challenges, numerous bioinformatic algorithms have been developed to analyze these data. These algorithms aim to find an appropriate balance between data loss, errors, analysis time, and memory footprint. Typical analysis pipelines require multiple steps. If one or more of these steps is unnecessary, it would significantly decrease compute time and data manipulation to remove the step. One step in many pipelines is PCR duplicate removal, where PCR duplicates arise from multiple PCR products from the same template molecule binding on the flowcell. These are often removed because there is concern they can lead to false positive variant calls. Picard (MarkDuplicates) and SAMTools (rmdup) are the two main softwares used for PCR duplicate removal.ResultsApproximately 92 % of the 17+ million variants called were called whether we removed duplicates with Picard or SAMTools, or left the PCR duplicates in the dataset. There were no significant differences between the unique variant sets when comparing the transition/transversion ratios (p = 1.0), percentage of novel variants (p = 0.99), average population frequencies (p = 0.99), and the percentage of protein-changing variants (p = 1.0). Results were similar for variants in the American College of Medical Genetics genes. Genotype concordance between NGS and SNP chips was above 99 % for all genotype groups (e.g., homozygous reference).ConclusionsOur results suggest that PCR duplicate removal has minimal effect on the accuracy of subsequent variant calls.

TarSVM: Improving the accuracy of variant calls derived from microfluidic PCR-based targeted next generation sequencing using a support vector machine.

BackgroundTargeted sequencing of discrete gene sets is a cost effective strategy to screen subjects for monogenic forms of disease. One method to achieve this pairs microfluidic PCR with next generation sequencing. The PCR step of this pipeline creates challenges in accurate variant calling. This includes that most reads targeting a specific exon are duplicates that have been amplified from the PCR step. To reduce false positive variant calls from these experiments, previous studies have used threshold-based filtering of alternative allele depth ratio and manual inspection of the alignments. However even after manual inspection and filtering, many variants fail to be validated via Sanger sequencing. To improve the accuracy of variant calling from these experiments, we are challenged to design a variant filtering strategy that sufficiently models microfluidic PCR-specific issues.ResultsWe developed an open source variant filtering pipeline, targeted sequencing support vector machine (“tarSVM”), that uses a Support Vector Machine (SVM) and a new score the normalized allele dosage test to identify high quality variants from microfluidic PCR data. tarSVM maximizes training knowledge by selecting variants that are likely true and likely false variants by incorporating knowledge from the 1000 Genomes and the Exome Aggregation Consortium projects. tarSVM improves on previous approaches by synthesizing variant features from the Genome Analysis Toolkit and allele dosage information. We compared the accuracy of tarSVM versus existing variant quality filtering strategies on two cohorts (n = 474 and n = 1152), and validated our method on a third cohort (n = 75). In the first cohort, our method achieved 84.5 % accuracy of predicting whether or not a variant would be validated with Sanger sequencing versus 78.8 % for the second most accurate method. In the second cohort, our method had an accuracy of 73.3 %, versus 61.5 % for the second best method. Finally, our method had a false discovery rate of 5 % for the validation cohort.ConclusionstarSVM increases the accuracy of variant calling when using microfluidic PCR based targeted sequencing approaches. This results in higher confidence downstream analyses, and ultimately reduces the costs Sanger validation. Our approach is less labor intensive than existing approaches, and is available as an open source pipeline for read trimming, aligning, variant calling, and variant quality filtering on GitHub at https://github.com/christopher-gillies/TargetSpecificGATKSequencingPipeline.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1108-4) contains supplementary material, which is available to authorized users.

Correction: PCR-Free Enrichment of Mitochondrial DNA from Human Blood and Cell Lines for High Quality Next-Generation DNA Sequencing

[This corrects the article DOI: 10.1371/journal.pone.0139253.].