Quality Of Sequencing Data Research Articles

Abstract GS2-01: Age-related breast cancer risk estimates for the general population based on sequencing of cancer predisposition genes in 19,228 breast cancer patients and 20,211 matched unaffected controls from US based cohorts in the CARRIERS study

Abstract Background: Clinical germline genetic testing of cancer predisposition gene panels is used to identify women at increased risk for breast cancer. The identification of pathogenic mutations in established high and moderate predisposition genes may result in improved risk management of breast cancer for tested patients and their family members through tailored screening, prophylactic surgeries, or chemoprevention. However, the risks of breast cancer associated with mutations in these genes have likely been overestimated for many women in the general population because previous studies have focused on individuals with a family history of breast and/or ovarian cancer, early onset disease, or triple negative breast cancer. The goal of the “CAnceR RIsk Estimates Related to Susceptibility” (CARRIERS) study is to estimate breast cancer risks associated with mutations in hereditary cancer panel genes in the general population. Methods: Germline DNA samples from blood or saliva were obtained from 39,439 breast cancer patients and matched unaffected controls from six US-based cohorts (BWHS, CPSII, CTS, MEC, NHS1, NHS2, WHI). DNA was subjected to dual bar-coded QIAseq multiplex PCR-based amplification of 1733 target regions covering all coding regions of 37 cancer predisposition genes and sequenced. Mutation calling was conducted with Haplotype Caller and Vardict. Results: High quality sequence data was obtained for 38,990 of 39,439 samples (98.9%) and for 99.3% of target regions. Pathogenic mutations in 12 known breast cancer predisposition genes were identified 4.5% of all breast cancer cases and 2.1% of controls; and in 6.7% of African American breast cancer cases and 1.8% of controls. Differences in mutation frequencies were observed by age with mutations in 7.8% of cases diagnosed £50 years of age and 4.0% of cases diagnosed over age 50. Mutations in ATM, BRCA1, BRCA2, and PALB2 were enriched 2 to 3-fold in cases diagnosed under age 50 relative to older cases. No change in frequency of CHEK2 mutations by age was observed. In case-control analyses mutations in BRCA1, BRCA2 and PALB2 were significantly associated with a high risk of breast cancer (odds ratio (OR)>4.0). Of these, BRCA1 and BRCA2 displayed ORs of 13.5 and 16.6 in the £50 age group, but only 5.7 and 3.2 in the >50 age group. Only minor age-specific effects were observed for PALB2. Mutations in ATM and CHEK2 were associated with moderate risks of breast cancer (OR=2.0 to 4.0) in the younger age group, but not in the older age group. Conclusions: Results from the CARRIERS cohort-based study establish that mutations in known breast cancer predisposition genes are associated with only moderate risks of breast cancer in the general population. However, risks are substantially increased for BRCA1 and BRCA2 but not ATM, CHEK2 or PALB2 mutations in those £50 years of age. The age-related estimates of breast cancer risk for each of the hereditary cancer panel genes in this study may inform selection of individuals in the general population who may benefit from genetic testing and associated risk management strategies. Citation Format: Couch FJ, Hu C, Hart SN, Gnanaolivu RD, Lilyquist J, Lee KY, Gao C, Eckloff B, Samara R, Klebba J, Auer P, Bernstein L, Gaudet M, Haiman C, Palmer JR, Yao S, Domchek SM, Weitzel JN, Goldgar DE, Nathanson KL, Kraft P, Polley EC. Age-related breast cancer risk estimates for the general population based on sequencing of cancer predisposition genes in 19,228 breast cancer patients and 20,211 matched unaffected controls from US based cohorts in the CARRIERS study [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr GS2-01.

Bacterial genome sequencing and analysis: paving the way for a Switzerland-wide molecular epidemiological surveillance platform.

Facing multidrug resistant (MDR) bacterial pathogens is one of the most important challenges for our society. The spread of highly virulent and resistant pathogens can be described using molecular typing technologies; in particular, whole genome sequencing (WGS) data can be usedf or molecular typing purposes with high resolution. WGS data analysis can explain the spatiotemporal patterns of pathogen transmission. However, the transmission between compartments (human, animal, food, environment) is very complex. Interoperable and curated metadata are a key requirement for fully understanding this complexity. In addition, high quality sequence data are a key element between centres using WGS data for diagnostic and epidemiological applications. We aim to describe steps to improve WGS data analysis and to implement a molecular surveillance platform allowing integration of high resolution WGS typing data and epidemiological data.

Analysis in case-control sequencing association studies with different sequencing depths.

With the advent of next-generation sequencing, investigators have access to higher quality sequencing data. However, to sequence all samples in a study using next generation sequencing can still be prohibitively expensive. One potential remedy could be to combine next generation sequencing data from cases with publicly available sequencing data for controls, but there could be a systematic difference in quality of sequenced data, such as sequencing depths, between sequenced study cases and publicly available controls. We propose a regression calibration (RC)-based method and a maximum-likelihood method for conducting an association study with such a combined sample by accounting for differential sequencing errors between cases and controls. The methods allow for adjusting for covariates, such as population stratification as confounders. Both methods control type I error and have comparable power to analysis conducted using the true genotype with sufficiently high but different sequencing depths. We show that the RC method allows for analysis using naive variance estimate (closely approximates true variance in practice) and standard software under certain circumstances. We evaluate the performance of the proposed methods using simulation studies and apply our methods to a combined data set of exome sequenced acute lung injury cases and healthy controls from the 1000 Genomes project.

Improving the quality and workflow of bacterial genome sequencing and analysis: paving the way for a Switzerland-wide molecular epidemiological surveillance platform.

Facing multidrug resistant (MDR) bacterial pathogens is one of the most important challenges for our society. The spread of highly virulent and resistant pathogens can be described using molecular typing technologies; in particular, whole genome sequencing (WGS) data can be used for molecular typing purposes with high resolution. WGS data analysis can explain the spatiotemporal patterns of pathogen transmission. However, the transmission between compartments (human, animal, food, environment) is very complex. Interoperable and curated metadata are a key requirement for fully understanding this complexity. In addition, high quality sequence data are a key element between centres using WGS data for diagnostic and epidemiological applications. We aim to describe steps to improve WGS data analysis and to implement a molecular surveillance platform allowing integration of high resolution WGS typing data and epidemiological data.

Alfred: interactive multi-sample BAM alignment statistics, feature counting and feature annotation for long- and short-read sequencing.

SummaryHarmonizing quality control (QC) of large-scale second and third-generation sequencing datasets is key for enabling downstream computational and biological analyses. We present Alfred, an efficient and versatile command-line application that computes multi-sample QC metrics in a read-group aware manner, across a wide variety of sequencing assays and technologies. In addition to standard QC metrics such as GC bias, base composition, insert size and sequencing coverage distributions it supports haplotype-aware and allele-specific feature counting and feature annotation. The versatility of Alfred allows for easy pipeline integration in high-throughput settings, including DNA sequencing facilities and large-scale research initiatives, enabling continuous monitoring of sequence data quality and characteristics across samples. Alfred supports haplo-tagging of BAM/CRAM files to conduct haplotype-resolved analyses in conjunction with a variety of next-generation sequencing based assays. Alfred’s companion web application enables interactive exploration of results and comparison to public datasets.Availability and implementationAlfred is open-source and freely available at https://tobiasrausch.com/alfred/.Supplementary information Supplementary data are available at Bioinformatics online.

High-Throughput Sequencing Strategy for miR-146b-regulated circRNA Expression in Hepatic Stellate Cells.

BackgroundThis study was designed to detect and analyze miR-146b-mediated circular RNA (circRNA) expression in hepatic stellate cells.Material/MethodsThe experiment was divided into a control group and a siRNA-miR-146b group. The interference efficiency of siRNA-miR-146b was confirmed by real-time quantitative reverse transcription PCR (qRT-PCR) and the cells were collected, and total RNA was collected for high flux sequencing. The miRNA-targeted carcass were predicted. Finally, the expression of 5 circRNAs was verified by qRT-PCR.ResultsmiR-146b expression in the siRNA-miR-146b group was significantly lower than that in the control group. The quality of the original sequencing data and the processed data satisfied with the analysis, and the expression of circRNAs was modulated after the reduction of miR-146b. Among them, 18 circRNAs were upregulated, while 77 circRNAs were downregulated in the miR-146b group compared with the control group. The gene prediction showed that hsa_circ1887 was the largest contact point in miRNA and circRNA regulatory networks. qRT-PCR showed that rno-circRNA-469, rno-circRNA-1138, rno-circRNA-2168 and rno-circRAN-1907 were significantly reduced, while circRNA-1984 was significantly promoted in the siRNA-miR-146b group compared with the control group, which were consistent with the measurements by high-throughput sequencing technique.ConclusionsmiR-146b could regulate the expression of circRNAs in HSCs, which might take part in the formation and development of hepatic fibrosis.

Impact of index hopping and bias towards the reference allele on accuracy of genotype calls from low-coverage sequencing

BackgroundInherent sources of error and bias that affect the quality of sequence data include index hopping and bias towards the reference allele. The impact of these artefacts is likely greater for low-coverage data than for high-coverage data because low-coverage data has scant information and many standard tools for processing sequence data were designed for high-coverage data. With the proliferation of cost-effective low-coverage sequencing, there is a need to understand the impact of these errors and bias on resulting genotype calls from low-coverage sequencing.ResultsWe used a dataset of 26 pigs sequenced both at 2× with multiplexing and at 30× without multiplexing to show that index hopping and bias towards the reference allele due to alignment had little impact on genotype calls. However, pruning of alternative haplotypes supported by a number of reads below a predefined threshold, which is a default and desired step of some variant callers for removing potential sequencing errors in high-coverage data, introduced an unexpected bias towards the reference allele when applied to low-coverage sequence data. This bias reduced best-guess genotype concordance of low-coverage sequence data by 19.0 absolute percentage points.ConclusionsWe propose a simple pipeline to correct the preferential bias towards the reference allele that can occur during variant discovery and we recommend that users of low-coverage sequence data be wary of unexpected biases that may be produced by bioinformatic tools that were designed for high-coverage sequence data.

Optimised isolation method for RNA extraction suitable for RNA sequencing from feline teeth collected in a clinical setting and at post mortem

Advanced next generation sequencing approaches have started to reveal the cellular and molecular complexity of the microenvironment in many tissues. It is challenging to obtain high quality RNA from mineralised tissues. We developed an optimised method of RNA extraction from feline teeth collected in a clinical setting and at post mortem. Teeth were homogenised in phenol-guanidinium solution at near-freezing temperatures and followed by solid-phase nucleic acid extraction utilising a commercially available kit. This method produced good RNA yields and improved RNA quality based on RNA integrity numbers equivalent (RINe) from an average of 3.6 to 5.6. No correlation was found between RNA purity parameters measured by A260:280 or A230:260 ratios and degree of RNA degradation. This implies that RNA purity indicators cannot be reliably used as parameters of RNA integrity. Two reference genes (GAPDH, RPS19) showed significant changes in expression levels by qPCR at low and moderate RINe values, while RPL17 was stable at all RINe values tested. Furthermore, we investigated the effect of quantity and quality of RNA on the quality of the resultant RNA sequencing (RNA-Seq) data. Thirteen RNA-seq data showed similar duplication and mapping rates (94 to 95%) against the feline genome regardless of RINe values. However one low yield sample with a high RINe value showed a high duplication rate and it was an outlier on the RNA-seq multidimensional scaling plot. We conclude that the overall yield of RNA was more important than quality of RNA for RNA-seq quality control. These results will guide researchers who wish to perform RNA extractions from mineralised tissues, especially if collecting in a clinical setting with the recognised restraints that this imposes.

EasyQC: Tool with Interactive User Interface for Efficient Next-Generation Sequencing Data Quality Control.

The advent of next-generation sequencing (NGS) technologies has revolutionized the world of genomic research. Millions of sequences are generated in a short period of time and they provide intriguing insights to the researcher. Many NGS platforms have evolved over a period of time and their efficiency has been ever increasing. Still, primarily because of the chemistry, glitch in the sequencing machine and human handling errors, some artifacts tend to exist in the final sequence data set. These sequence errors have a profound impact on the downstream analyses and may provide misleading information. Hence, filtering of these erroneous reads has become inevitable and myriad of tools are available for this purpose. However, many of them are accessible as a command line interface that requires the user to enter each command manually. Here, we report EasyQC, a tool for NGS data quality control (QC) with a graphical user interface providing options to carry out trimming of NGS reads based on quality, length, homopolymer, and ambiguous bases. EasyQC also possesses features such as format converter, paired end merger, adapter trimmer, and a graph generator that generates quality distribution, length distribution, GC content, and base composition graphs. Comparison of raw and processed sequence data sets using EasyQC suggested significant increase in overall quality of the sequences. Testing of EasyQC using NGS data sets on a standalone desktop proved to be relatively faster. EasyQC is developed using PERL modules and can be executed in Windows and Linux platforms. With the various QC features, easy interface for end users, and cross-platform compatibility, EasyQC would be a valuable addition to the already existing tools facilitating better downstream analyses.

Poorly Differentiated Nonkeratinizing Squamous Cell Carcinoma of the Thymus

Thymic carcinoma represents a rare and poorly understood type of thymic epithelial neoplasm that has been the subject of much controversy. Poorly differentiated nonkeratinizing squamous cell carcinoma, also known as lymphoepithelioma-like thymic carcinoma, is a rare variant of thymic carcinoma that has not been adequately characterized in the literature. The clinicopathologic, immunohistochemical, ultrastructural, and molecular features of 25 cases are reported. The patients were 19 men and 6 women, ranging in age from 20 to 85 years (mean: 60 y). The tumors presented clinically as anterior mediastinal masses with chest pain and shortness of breath or were found incidentally on imaging studies. Tumor size ranged from 2.0 to 13.5 cm in greatest diameter. Most of the tumors were small, well-circumscribed and confined to the mediastinum. Five cases presented with large, bulky, and infiltrative masses. Histologically, the hallmark of these tumors was a neoplastic proliferation of large, round to oval cells with vesicular nuclei, prominent eosinophilic nucleoli, and scant cytoplasm. Two histologic growth patterns were identified: tumors with a heavy lymphoplasmacytic stroma (lymphoepithelioma-like pattern), and tumors showing abundant desmoplastic stroma (desmoplastic pattern). Immunohistochemical stains showed strong positivity of the tumor cells for cytokeratin AE1/AE3, CK5/6, CK18, MOC31, p16, p40, and p63. MIB-1 showed on average 35% nuclear positivity. CD117 was positive in 21/25 cases and CD5 in 20/25 cases. Epstein-Barr encoded RNA in situ hybridization was positive in only 1 case. Electron microscopy in 4 cases showed primitive round to oval cells with prominent nucleoli, scant cytoplasm and immature cell junctions. Molecular features were studied by next-generation sequencing using high quality sequence data obtained from 18 patients. Variants with allele frequency between 5% and 45% and quality scores >50 were classified as somatic. A total of 16/18 cases had one or more somatic variants of unknown significance. One case showed an IDH1 p. R132C mutation, also of unknown significance. No "actionable" genes amenable to currently available targeted therapies were identified in this cohort. Clinical follow-up was obtained in 20 patients; 14 patients were alive and well with no evidence of disease between 1.5 and 16 years after diagnosis (median survival: 4 y; mean: 5.5 y). Most survivors had relatively small tumors (<5 cm. diameter), were in stage I and II at diagnosis and showed clear surgical margins. Five patients died of their tumors with metastases to bone, brain, chest wall, lungs and lymph nodes; all were in advanced stages and showed positive margins. Prognosis for these tumors appears to be correlated with the staging and status of the margins at the time of initial surgery.

Perspectives on topology of the human m1A methylome at single nucleotide resolution.

N1-methyladenosine was recently reported to be a chemical modification in mRNA. However, while we identified hundreds of m1A sites in the human transcriptome in a previous work, others have detected only nine sites in cytosolic and mitochondrial mRNAs. Herein, we provide additional evidence that hundreds of m1A sites are present in the human transcriptome. Moreover, we show that both the improper bioinformatic tools and the poor quality of sequencing data in a previous study led to the failure in identifying the majority of m1A sites. Our analysis hence provides an explanation of the divergence in the prevalence of this newly discovered mRNA mark.

Feasibility of amplicon-based targeted next-generation sequencing of colorectal cancer in endoscopic biopsies

Objective: To investigate whether small endoscopic biopsies of colorectal cancer were sufficient for quality and accurate mutational analysis by amplicon-based next-generation sequencing (NGS). Methods: By using an amplicon-based targeted NGS panel for mutational detection on Illumina Miseq platform, a total of 109 formalin-fixed and paraffin-embedded (FFPE) endoscopic biopsies of colorectal cancer were retrospectively selected, based on specific histopathologic criteria, from January 2012 to June 2016 at West China Hospital of Sichuan University and Peking University Third Hospital. Twelve of these biopsies had corresponding FFPE surgical resection specimens. Quality control parameters of NGS testing were analyzed and NGS results were confirmed by other methods. Mutation calls of the 12 paired endoscopic biopsies and surgical resections were compared. Results: Of the endoscopic biopsy specimens, 97.2% (106/109) had sufficient DNA and qualified sequencing library. NGS generated excellent sequencing data, with a median of 848× for median read depth and 95.7% for uniformity. The success rate of NGS was 95.4% (104/109). Conventional methods confirmed the results of NGS for KRAS and BRAF, and the concordance rate was 100.0%. The clinically actionable mutations detected in the 12 paired endoscopic biopsies and surgical resections were concordant. Conclusion: FFPE endoscopic biopsies of colorectal cancer is suitable for targeted NGS, providing quality sequencing data and accurate mutational information to guide targeted therapy.

Abstract 3647: Prior DNA repair improves the read quality in next-generation sequencing of cell-free tumor DNA

Abstract The cell-free tumor DNA (ctDNA) in patient's plasma is a noninvasive tumor biomarker. The detection of ctDNA is helpful to evaluate tumor progression, tumor response to the therapy, and subtyping of tumor cells. Targeting next-generation sequencing (NGS) technology provides a sensitive and specific technique for ctDNA detection. It can detect multiple tumor-related gene mutations. However, collection of high quality of cell-free DNA (cfDNA) may not be available in some cases. The quality of cfDNA in plasma is impacted by multiple factors, such as plasma collection and storage conditions, DNase activity in the blood, and the apoptotic and necrotic status of the tumor. These factors affect the integrity of cfDNA, leading to full or partial degradation of cfDNA, including double-strand DNA breaks and single strand DNA nicking. Lesions on cfDNA decrease the usability of ctDNA by digital PCR and targeted NGS. Due to amount limitation of cfDNA in some cases, the repair of damaged cfDNA could be a necessary rescue step in producing viable libraries for NGS. CfDNA was extracted from the plasma with Zymo Research's Quick-cfDNA Serum and Plasma kit and was quantified by realtime PCR with Alu primer sets. The size of cfDNA was about 160 base pairs, as estimated by Agilent Tapestation 2200 with the High Sensitivity DNA kit. The DNA repair of cfDNA was conducted with PreCR Repair Mix of New England BioLabs. The sequencing library was prepared with Accel-Amplicon 56G Oncology Panel of Swift Biosciences and sequenced in Illumina's MiSeq. The quality of sequencing data was determined with FastQC. Compared to PreCR Repair Mix treated cfDNA samples, fastQ data from some of untreated cfDNA samples showed failed per base sequencing quality, about 50% of sequencing cycles with the mean quality score below 30. The per sequencing quality score of these cfDNA samples failed also to pass the quality filter. The read size distribution analysis indicated that about 60 to 70% of read sized between 30 to 45 bases and about 75 to 80% of read was smaller than 75 bases. However, sequencing data from same cfDNA samples treated with PreCR Repair Mix show a greatly improved sequencing quality. Both per base sequencing quality and per sequencing quality score passed quality filter. The above 97% of reads sized over 92 bases, complying with the requirement of 56G Oncology Panel. In conclusion, the DNA repair process before library preparation is necessary to rescue damaged cfDNA for amplicon-based NGS. Citation Format: Hong Yin, Adam H. Greer, Glenn Mills. Prior DNA repair improves the read quality in next-generation sequencing of cell-free tumor DNA [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 3647.

Abstract 1428: Application of ONCO/REVEAL Lung &amp; Colon Cancer Panel in CRC samples and effect of DNA damage in FFPE samples

Abstract Introduction: The ONCO/REVEAL Lung&amp;Colon Caner Panel (LC103, Pillar Biosciences Inc.) interrogates regions in 22 genes that are frequently mutated in NSCLC and CRC. To evaluate the performance of ONCO/REVEAL Lung&amp;Colon Cancer Panel, we assessed a cohort of 207 colorectal cancer FFPE samples collected by a top-tier hospital in Shanghai between 2015 and 2016. Among them, 27 FFPE samples showed abnormally high numbers of low frequency variants (&amp;lt;2%) and were further investigated to assess the effect of DNA damage in somatic variant detection. Materials and Methods: DNA library preparation and sequencing: 10-20 ng of FFPE DNA (Quantitated by Qubit, Life Tech.) was used to prepare libraries using the LC103 panel. All libraries were subsequently sequenced on Illumina MiSeq sequencer. FFPE DNA repair: DNA extracted from 27 FFPE samples with a high number of low VAF (&amp;lt;2%) variants was treated with NEBNext FFPE DNA Repair Mix prior to library preparation. FFPE and DNA repaired FFPE were compared to analyze the effect of DNA damage in variant detection. Matched fresh frozen tumor tissue samples were also tested. Data analysis: PiVATTM (Pillar Biosciences Inc.) was used for data analysis. PCR errors and sequencing errors are reduced to be well below 1% VAF through the PiVAT error correction algorithm. Results: 100% successful rate of library preparation and sequencing: All of 207 FFPE samples yielded high quality sequencing data that detected mutant alleles at frequencies as low as 1%. Variant detection: A total of 414 somatic variants, including SNV and small indels, were identified above 2% VAF in 193 out of 207 samples. TP53 (38%), KRAS (24%), PIK3CA (12%), FBXW7 (9%) and PTEN (4%) were the most frequently mutated genes. CNVs were identified in EGFR, MET, ERBB2, KRAS and FGFR1 genes. The effect of DNA damage: The majority of detected variants between 1% and 2% VAF, are not known hotspot mutations. C:G&amp;gt;T:A mutations account for 73.8% of variants between 1% and 2% VAF. DNA repair by NEBNext FFPE DNA Repair Mix or other UDG enzymes reduced 1-2% VAF calls significantly, indicating that these variants are false positive calls. However, DNA repair enzymes used in our study could not eliminate false positive calls completely. Other mechanisms are suspected to contribute to the remaining low frequency calls. Variant between 2% and 5% VAF: In total, 33 somatic variants were detected at 2-5% VAF. There are many clinically actionable mutations or common driver mutations, including KRAS G12C (2.10%), KRAS G12D (2.21%), KRAS Q61L (2.74%), BRAF G469E (2.51%), PIK3CA E545K (2.08%, 2.39%, 4.78%), PIK3CA E545G (4.61%), PIK3CA Q546K (4.51%), PIK3CA H1047R (2.80%). Conclusions: The ONCO/REVEAL Lung&amp;Colon Caner Panel is a robust and sensitive NGS Assay for the detection of somatic variants. DNA damage confounds variant identification in FFPE samples between 1 and 5% frequency. Citation Format: Jianfeng Xiao, Jiajie Tang, Xiangzhi Liu, Xiaoyan Tian. Application of ONCO/REVEAL Lung &amp; Colon Cancer Panel in CRC samples and effect of DNA damage in FFPE 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 1428.

Abstract 4331: High-throughput whole-genome sequencing of formalin fixed, paraffin-embedded tissues from colorectal cancer patients

Abstract Formalin-fixed, paraffin-embedded (FFPE) storage is a universally-adopted, cost-effective and long-term solution for tissue storage. Given the abundance of FFPE clinical samples, they provide a good source of tissue for genome sequencing studies. However, the extraction of nucleic acids from FFPE tissues yield highly fragmented DNA of variable quality. The poor quality and low yield make it difficult to generate adequate sequencing libraries for genomic studies. For a population cancer genome study, we optimized a procedure for whole-genome sequencing on FFPE tumor and normal tissue of colorectal cancer patients. This pilot study aimed to first identify changes in DNA copy number using low-pass sequencing, with the additional goal of later adding structural variant and gene fusion detection and single nucleotide variant analysis with deeper sequencing. We processed, sequenced and analyzed 193 patients. These FFPE samples had varying storage characteristics. We optimized the initial extraction quality thresholds, DNA extraction and library preparation to generate high quality sequencing data. We identified an initial sample quality and library threshold to hold the best correlation for sequencing quality. Optimal yield and DNA size from extracted FFPE was achieved by using Promega's LEV DNA FFPE Extraction Kit. Library prep optimization involved using mechanical shearing of DNA to increase overall library size for structural variant detection as well as using unique dual index adapters to identify index swapping artifacts during sequencing. An additional cleanup was also performed post-fragmentation to increase overall library size. Overall, we successfully developed a robust protocol for conducting whole genome sequencing on FFPE tumor samples. Citation Format: Matthew Kubit, Christina Wood-Bouwens, Sue Grimes, John Bell, GiWon Shin, Billy Lau, Mickey Miller, Kenneth Day, Helaman Escobar, Hanlee Ji, Lincoln Nadauld, Paul Van Hummelen. High-throughput whole-genome sequencing of formalin fixed, paraffin-embedded tissues from colorectal cancer patients [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 4331.

Identification and removal of sequencing artifacts produced by mispriming during reverse transcription in multiple RNA-seq technologies.

The quality of RNA sequencing data relies on specific priming by the primer used for reverse transcription (RT-primer). Nonspecific annealing of the RT-primer to the RNA template can generate reads with incorrect cDNA ends and can cause misinterpretation of data (RT mispriming). This kind of artifact in RNA-seq based technologies is underappreciated and currently no adequate tools exist to computationally remove them from published data sets. We show that mispriming can occur with as little as two bases of complementarity at the 3′ end of the primer followed by intermittent regions of complementarity. We also provide a computational pipeline that identifies cDNA reads produced from RT mispriming, allowing users to filter them out from any aligned data set. Using this analysis pipeline, we identify thousands of mispriming events in a dozen published data sets from diverse technologies including short RNA-seq, total/mRNA-seq, HITS-CLIP, and GRO-seq. We further show how RT mispriming can lead to misinterpretation of data. In addition to providing a solution to computationally remove RT-misprimed reads, we also propose an experimental solution to completely avoid RT-mispriming by performing RNA-seq using thermostable group II intron derived reverse transcriptase (TGIRT-seq).

The Quality Sequencing Minimum (QSM): providing comprehensive, consistent, transparent next generation sequencing data quality assurance.

Next generation sequencing (NGS) is routinely used in clinical genetic testing. Quality management of NGS testing is essential to ensure performance is consistently and rigorously evaluated. Three primary metrics are used in NGS quality evaluation: depth of coverage, base quality and mapping quality. To provide consistency and transparency in the utilisation of these metrics we present the Quality Sequencing Minimum (QSM). The QSM defines the minimum quality requirement a laboratory has selected for depth of coverage (C), base quality (B) and mapping quality (M) and can be applied per base, exon, gene or other genomic region, as appropriate. The QSM format is CX_BY(P Y)_MZ(P Z). X is the parameter threshold for C, Y the parameter threshold for B, P Y the percentage of reads that must reach Y, Z the parameter threshold for M, P Z the percentage of reads that must reach Z. The data underlying the QSM is in the BAM file, so a QSM can be easily and automatically calculated in any NGS pipeline. We used the QSM to optimise cancer predisposition gene testing using the TruSight Cancer Panel (TSCP). We set the QSM as C50_B10(85)_M20(95). Test regions falling below the QSM were automatically flagged for review, with 100/1471 test regions QSM-flagged in multiple individuals. Supplementing these regions with 132 additional probes improved performance in 85/100. We also used the QSM to optimise testing of genes with pseudogenes such as PTEN and PMS2. In TSCP data from 960 individuals the median number of regions that passed QSM per sample was 1429 (97%). Importantly, the QSM can be used at an individual report level to provide succinct, comprehensive quality assurance information about individual test performance. We believe many laboratories would find the QSM useful. Furthermore, widespread adoption of the QSM would facilitate consistent, transparent reporting of genetic test performance by different laboratories.

Are commercial providers a viable option for clinical bacterial sequencing?

Bacterial whole-genome sequencing in the clinical setting has the potential to bring major improvements to infection control and clinical practice. Sequencing instruments are not currently available in the majority of routine microbiology laboratories worldwide, but an alternative is to use external sequencing providers. To foster discussion around this we investigated whether send-out services were a viable option. Four providers offering MiSeq sequencing were selected based on cost and evaluated based on the service provided and sequence data quality. DNA was prepared from five methicillin-resistant Staphylococcus aureus (MRSA) isolates, four of which were investigated during a previously published outbreak in the UK together with a reference MRSA isolate (ST22 HO 5096 0412). Cost of sequencing per isolate ranged from £155 to £342 and turnaround times from DNA postage to arrival of sequence data ranged from 12 to 63 days. Comparison of commercially generated genomes against the original sequence data demonstrated very high concordance, with no more than one single nucleotide polymorphism (SNP) difference on core genome mapping between the original sequences and the new sequence for all four providers. Multilocus sequence type could not be assigned based on assembly for the two cheapest sequence providers due to fragmented assemblies probably caused by a lower output of sequence data per isolate. Our results indicate that external providers returned highly accurate genome data, but that improvements are required in turnaround time to make this a viable option for use in clinical practice.

Rqc: A Bioconductor Package for Quality Control of High-Throughput Sequencing Data

As sequencing costs drop with the constant improvements in the field, next-generation sequencing becomes one of the most used technologies in biological research. Sequencing technology allows the detailed characterization of events at the molecular level, including gene expression, genomic sequence and structural variants. Such experiments result in billions of sequenced nucleotides and each one of them is associated to a quality score. Several software tools allow the quality assessment of whole experiments. However, users need to switch between software environments to perform all steps of data analysis, adding an extra layer of complexity to the data analysis workflow. We developed Rqc, a Bioconductor package designed to assist the analyst during assessment of high-throughput sequencing data quality. The package uses parallel computing strategies to optimize large data sets processing, regardless of the sequencing platform. We created new data quality visualization strategies by using established analytical procedures. That improves the ability of identifying patterns that may affect downstream procedures, including undesired sources technical variability. The software provides a framework for writing customized reports that integrates seamlessly to the R/Bioconductor environment, including publication-ready images. The package also offers an interactive tool to generate quality reports dynamically. Rqc is implemented in R and it is freely available through the Bioconductor project (https://bioconductor.org/packages/Rqc/) for Windows, Linux and Mac OS X operating systems.

Bi-level error correction for PacBio long reads.

The latest sequencing technologies such as the Pacific Biosciences (PacBio) and Oxford Nanopore machines can generate long reads at the length of thousands of nucleic bases which is much longer than the reads at the length of hundreds generated by Illumina machines. However, these long reads are prone to much higher error rates, for example 15%, making downstream analysis and applications very difficult. Error correction is a process to improve the quality of sequencing data. Hybrid correction strategies have been recently proposed to combine Illumina reads of low error rates to fix sequencing errors in the noisy long reads with good performance. In this paper, we propose a new method named Bicolor, a bi-level framework of hybrid error correction for further improving the quality of PacBio long reads. At the first level, our method uses a de Bruijn graph-based error correction idea to search paths in pairs of solid -mers iteratively with an increasing length of -mer. At the second level, we combine the processed results under different parameters from the first level. In particular, a multiple sequence alignment algorithm is used to align those similar long reads, followed by a voting algorithm which determines the final base at each position of the reads. We compare the superior performance of Bicolor with three state-of-the-art methods on three real data sets. Results demonstrate that Bicolor always achieves the highest identity ratio. Bicolor also achieves a higher alignment ratio () and a higher number of aligned reads than the current methods on two data sets. On the third data set, our method is closely competitive to the current methods in terms of number of aligned reads and genome coverage. The C++ source codes of our algorithm are freely available at https://github.com/yuansliu/Bicolor.