scholarly journals Validation of multiplex PCR sequencing assay of SIV

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Ryan V. Moriarty ◽  
Nicolas Fesser ◽  
Matthew S. Sutton ◽  
Vanessa Venturi ◽  
Miles P. Davenport ◽  
...  
Keyword(s):  
Multiplex Pcr ◽  
Sequence Data ◽  
Point Mutations ◽  
Low Frequency ◽  
False Positives ◽  
Starting Material ◽  
Detection Sensitivity ◽  
Clinical Samples ◽  
Sequencing Data ◽  
Viral Cdna

Abstract Background The generation of accurate and reproducible viral sequence data is necessary to understand the diversity present in populations of RNA viruses isolated from clinical samples. While various sequencing methods are available, they often require high quality templates and high viral titer to ensure reliable data. Methods We modified a multiplex PCR and sequencing approach to characterize populations of simian immunodeficiency virus (SIV) isolated from nonhuman primates. We chose this approach with the aim of reducing the number of required input templates while maintaining fidelity and sensitivity. We conducted replicate sequencing experiments using different numbers of quantified viral RNA (vRNA) or viral cDNA as input material. We performed assays with clonal SIVmac239 to detect false positives, and we mixed SIVmac239 and a variant with 24 point mutations (SIVmac239-24X) to measure variant detection sensitivity. Results We found that utilizing a starting material of quantified viral cDNA templates had a lower rate of false positives and increased reproducibility when compared to that of quantified vRNA templates. This study identifies the importance of rigorously validating deep sequencing methods and including replicate samples when using a new method to characterize low frequency variants in a population with a small number of templates. Conclusions Because the need to generate reproducible and accurate sequencing data from diverse viruses from low titer samples, we modified a multiplex PCR and sequencing approach to characterize SIV from populations from non-human primates. We found that increasing starting template numbers increased the reproducibility and decreased the number of false positives identified, and this was further seen when cDNA was used as a starting material. Ultimately, we highlight the importance of vigorously validating methods to prevent overinterpretation of low frequency variants in a sample.

scholarly journals Validation of multiplex PCR sequencing assay of SIV

2020 ◽  
Author(s):  
Ryan V Moriarty ◽  
Nico Fesser ◽  
Matthew S Sutton ◽  
Vanessa Venturi ◽  
Miles P Davenport ◽  
...  
Keyword(s):  
Multiplex Pcr ◽  
Sequence Data ◽  
Point Mutations ◽  
Low Frequency ◽  
False Positives ◽  
Starting Material ◽  
Detection Sensitivity ◽  
Clinical Samples ◽  
Sequencing Data ◽  
Viral Cdna

Abstract Background: The generation of accurate and reproducible viral sequence data is necessary to understand the diversity present in populations of RNA viruses isolated from clinical samples. While various sequencing methods are available, they often require high quality templates and high viral titer to ensure reliable data. Methods: We modified a multiplex PCR and sequencing approach to characterize populations of simian immunodeficiency virus (SIV) isolated from nonhuman primates. We chose this approach with the aim of reducing the number of required input templates while maintaining fidelity and sensitivity. We conducted replicate sequencing experiments using different numbers of quantified viral RNA (vRNA) or viral cDNA as input material. We performed assays with clonal SIVmac239 to detect false positives, and we mixed SIVmac239 and a variant with 24 point mutations (SIVmac239-24X) to measure variant detection sensitivity. Results: We found that utilizing a starting material of quantified viral cDNA templates had a lower rate of false positives and increased reproducibility when compared to that of quantified vRNA templates. This study identifies the importance of rigorously validating deep sequencing methods and including replicate samples when using a new method to characterize low frequency variants in a population with a small number of templates. Conclusions: Because the need to generate reproducible and accurate sequencing data from diverse viruses from low titer samples, we modified a multiplex PCR and sequencing approach to characterize SIV from populations from non-human primates. We found that increasing starting template numbers increased the reproducibility and decreased the number of false positives identified, and this was further seen when cDNA was used as a starting material. Ultimately, we highlight the importance of vigorously validating methods to prevent overinterpretation of low frequency variants in a sample.

scholarly journals Validation of multiplex PCR sequencing assay of SIV

2021 ◽  
Author(s):  
Ryan V Moriarty ◽  
Nico Fesser ◽  
Matthew S Sutton ◽  
Vanessa Venturi ◽  
Miles P Davenport ◽  
...  
Keyword(s):  
Multiplex Pcr ◽  
Sequence Data ◽  
Point Mutations ◽  
Low Frequency ◽  
False Positives ◽  
Starting Material ◽  
Clinical Samples ◽  
Sequencing Data ◽  
Input Material ◽  
Viral Cdna

Abstract Background: The generation of accurate and reproducible viral sequence data is necessary to understand the diversity present in populations of RNA viruses isolated from clinical samples. While various sequencing methods are available, they often require high quality templates and high viral titer to ensure reliable data.Methods: We modified a multiplex PCR and sequencing approach to characterize populations of simian immunodeficiency virus (SIV) isolated from nonhuman primates. We chose this approach with the aim of reducing the number of required input templates while maintaining fidelity and sensitivity. We conducted replicate sequencing experiments using different numbers of quantified viral RNA (vRNA) or viral cDNA as input material. We performed assays with clonal SIVmac239 to detect false positives, and we mixed SIVmac239 and a variant with 24 point mutations (SIVmac239-24X) to measure variant detection sensitivity.Results: We found that utilizing a starting material of quantified viral cDNA templates had a lower rate of false positives and increased reproducibility when compared to that of quantified vRNA templates. This study identifies the importance of rigorously validating deep sequencing methods and including replicate samples when using a new method to characterize low frequency variants in a population with a small number of templates.Conclusions: Because the need to generate reproducible and accurate sequencing data from diverse viruses from low titer samples, we modified a multiplex PCR and sequencing approach to characterize SIV from populations from non-human primates. We found that increasing starting template numbers increased the reproducibility and decreased the number of false positives identified, and this was further seen when cDNA was used as a starting material. Ultimately, we highlight the importance of vigorously validating methods to prevent overinterpretation of low frequency variants in a sample.

scholarly journals Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: An inter-laboratory study

2019 ◽  
Author(s):  
Ronan M. Doyle ◽  
Denise M. O’Sullivan ◽  
Sean D. Aller ◽  
Sebastian Bruchmann ◽  
Taane Clark ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Laboratory Study ◽  
Clinical Microbiology ◽  
Sequence Data ◽  
Clinical Samples ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data

AbstractBackgroundAntimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a ‘one-stop’ test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data sequenced from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants and identify problem cases and factors that lead to discordant results.MethodsWe produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams (‘participants’) were provided these sequence data without any other contextual information. Each participant used their own pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime.ResultsIndividual participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment a different antibiotic would have been recommended for each isolate by at least one participant.ConclusionsWe found that participants produced discordant predictions from identical WGS data. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases and standardisation in the comparisons between genotype and resistance phenotypes will be fundamental before AST prediction using WGS can be successfully implemented in standard clinical microbiology laboratories.

VHVT: An ultra-sensitive somatic mutation detection and performance assessment program.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 1588-1588 ◽  
Author(s):  
Jilong Liu ◽  
Zu Liu ◽  
Shaomin Cheng ◽  
Fengming Guo ◽  
Meihua Tan ◽  
...  
Keyword(s):  
Somatic Mutation ◽  
Mutation Detection ◽  
Low Frequency ◽  
Allelic Frequency ◽  
Driver Mutations ◽  
Clinical Samples ◽  
Sequencing Error ◽  
Sequencing Data ◽  
Standard Data ◽  
Somatic Mutation Detection

1588 Background: NGS as a high throughput technique is particular valuable for cancer given its ability to detect multiple driver mutations. While reads contain SNVs and short InDels can be mapped to the right position using gatk-like programs, a program designed for germline mutation detection, reads contain long InDels such as EGFR EX19 deletions often wrongly mapped especially when deletions near the ends of the reads. Thus, gatk would not recognize these reads, consequently underestimate the mutation allelic frequency, and even missed out InDels when supporting reads were rare. Methods: Here we present a variation hotspot validation toolkit (VHVT), a validation based method to precisely detect the ultra-low frequency somatic mutations. As far as we know, it is the first specialized somatic mutation detection software. First, reference sequences aimed at the hotspot mutations were assembled, then reads were be mapped to the new assembled reference to precisely distinguish the supporting reads. Moreover, log odds (LOD) and Poisson mathematical model were integrated to control sequencing error, as a result, VHVT can achieve a limitation of detection at 0.01% with sensitivity and specificity above 95% and 99% respectively. In addition, we developed a method to quantitatively assess the performance of variation detection program using standard reference data. By mapping to the reconstructed reference, all supporting reads will be detected in sequencing data, and comparing theses with the number of supporting reads delivered by a program we can define recognition ratio of supporting reads. Results: Our reference standard data showed that VHVT can recognize average 30% more support reads than gatk for EGFR EX19 deletions. In a total 498 NSCLC clinical samples test, VHVT detected actionable mutations in 289 samples. 243 positive mutations were verified (168 by SANGER sequencing, 75 by ddPCR) with concordance rate at 100%. Conclusions: Taken all together, our results demonstrated the robust performance of VHVT for somatic mutation detection and program assessment and thus facilitate the development of personalized cancer therapy.

scholarly journals Simultaneous Detection of Seven Human Coronaviruses by Multiplex PCR and MALDI-TOF MS

COVID ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 5-17
Author(s):  
Tingting Liu ◽  
Lin Kang ◽  
Yanwei Li ◽  
Jing Huang ◽  
Zishuo Guo ◽  
...  
Keyword(s):  
Multiplex Pcr ◽  
Real Time ◽  
Real Time Pcr ◽  
Simultaneous Detection ◽  
Detection Sensitivity ◽  
Clinical Samples ◽  
Maldi Tof Ms ◽  
Maldi Tof ◽  
Human Coronaviruses ◽  
Tof Ms

Human coronaviruses (HCoVs) are associated with a range of respiratory symptoms. The discovery of severe acute respiratory syndrome (SARS)-CoV, Middle East respiratory syndrome, and SARS-CoV-2 pose a significant threat to human health. In this study, we developed a method (HCoV-MS) that combines multiplex PCR with matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS), to detect and differentiate seven HCoVs simultaneously. The HCoV-MS method had high specificity and sensitivity, with a 1–5 copies/reaction detection limit. To validate the HCoV-MS method, we tested 163 clinical samples, and the results showed good concordance with real-time PCR. Additionally, the detection sensitivity of HCoV-MS and real-time PCR was comparable. The HCoV-MS method is a sensitive assay, requiring only 1 μL of a sample. Moreover, it is a high-throughput method, allowing 384 samples to be processed simultaneously in 30 min. We propose that this method be used to complement real-time PCR for large-scale screening studies.

scholarly journals Altered Subgenomic RNA Expression in SARS-CoV-2 B.1.1.7 Infections

2021 ◽  
Author(s):  
Matthew D Parker ◽  
Benjamin B. Lindsey ◽  
Dhruv R Shah ◽  
Sharon Hsu ◽  
Alexander J Keeley ◽  
...  
Keyword(s):  
Sequence Data ◽  
Expression Profiles ◽  
Direct Consequence ◽  
Fold Increase ◽  
Clinical Severity ◽  
Clinical Samples ◽  
Rna Expression ◽  
Sequencing Data ◽  
Subgenomic Rna ◽  
Nucleotide Mutation

AbstractSARS-CoV-2 lineage B.1.1.7 viruses are more transmissible, may lead to greater clinical severity, and result in modest reductions in antibody neutralization. subgenomic RNA (sgRNA) is produced by discontinuous transcription of the SARS-CoV-2 genome and is a crucial step in the SARS-CoV-2 life cycle. Applying our tool (periscope) to ARTIC Network Oxford Nanopore genomic sequencing data from 4400 SARS-CoV-2 positive clinical samples, we show that normalised sgRNA expression profiles are significantly increased in B.1.1.7 infections (n=879). This increase is seen over the previous dominant circulating lineage in the UK, B.1.177 (n=943), which is independent of genomic reads, E gene cycle threshold and days since symptom onset at sampling. A noncanonical sgRNA which could represent ORF9b is found in 98.4% of B.1.1.7 SARS-CoV-2 infections compared with only 13.8% of other lineages, with a 16-fold increase in median expression. We hypothesise that this is a direct consequence of a triple nucleotide mutation in nucleocapsid (28280:GAT>CAT, D3L) creating a transcription regulatory-like sequence complementary to a region 3’ of the genomic leader. These findings provide a unique insight into the biology of B.1.1.7 and support monitoring of sgRNA profiles in sequence data to evaluate emerging potential variants of concern.One Sentence SummaryThe recently emerged and more transmissible SARS-CoV-2 lineage B.1.1.7 shows greater subgenomic RNA expression in clinical infections and enhanced expression of a noncanonical subgenomic RNA near ORF9b.

scholarly journals A simple multiplex polymerase chain reaction assay for rapid identification of the common pathogenic dermatophytes:Trichophyton interdigitale, Trichophyton rubrum, and Epidermophyton floccosum

2021 ◽  
Author(s):  
Sama Faramarzi ◽  
Marjan Motamedi ◽  
Ali Rezaei-Matehkolaei ◽  
Shima Aboutalebian ◽  
Saham Ansari ◽  
...  
Keyword(s):  
Polymerase Chain Reaction ◽  
Multiplex Pcr ◽  
Multiplex Polymerase Chain Reaction ◽  
Trichophyton Rubrum ◽  
Sequence Data ◽  
Clinical Samples ◽  
Chain Reaction ◽  
Internal Transcribed Spacer Region ◽  
Epidermophyton Floccosum ◽  
Polymerase Chain

Background and Purpose: The most common etiological agents of human dermatophytosis in various parts of the world are Trichophyton rubrum, Trichophyton interdigitale, and Epidermophyton floccosum. The main aim of this study was to design and evaluate a simple and straightforward multiplex polymerase chain reaction (PCR)assay for reliable identification/differentiation of these species in clinical isolates. Materials and Methods: The reliable sequences of several molecular targets of dermatophytes species were used to design a multiplex PCR for the identification of common pathogenic dermatophytes. The isolates and clinical specimens examined in this study included seven standard strains of dermatophytes, 101 isolates of dermatophytes and non-dermatophyte molds/yeasts which had already been identified by sequencing or PCR-restriction fragment length polymorphism (RFLP), and 155 clinical samples from patients suspected of cutaneous mycoses. Results: Species-specific primer pairs for T. rubrum and T. interdigitale/T. mentagrophytes were designed based on the sequence data of the translation elongation factor 1-alpha gene, and the primers for E. floccosum targeted the specific sequence of the internal transcribed spacer region (ITS). The multiplex PCR successfully detected T.rubrum, T. interdigitale/T. mentagrophytes, and E. floccosum strains that were identified by sequencing or PCR-RFLP. However, the primer pairs selected for T. interdigitale/T. mentagrophytes cross-reacted with Trichophyton tonsurans. In testing the PCR system directly for clinical samples, the proportion of positive multiplex PCR was higher than positive culture (68.1% vs. 55.4%, respectively). Conclusion: The multiplex assay could detect three common agents out of several causal agents of dermatophytosis, namely T. rubrum, T. interdigitale, and E. floccosum.Therefore, by adding pan-dermatophyte primers it can be used as a comprehensive detection/identification test.

scholarly journals Increased yields of duplex sequencing data by a series of quality control tools

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Gundula Povysil ◽  
Monika Heinzl ◽  
Renato Salazar ◽  
Nicholas Stoler ◽  
Anton Nekrutenko ◽  
...  
Keyword(s):  
Low Frequency ◽  
Variant Calling ◽  
Data Loss ◽  
Sequencing Data ◽  
Bioinformatics Pipeline ◽  
Consensus Sequences ◽  
Sequencing Errors ◽  
Data Output ◽  
Reverse Strand ◽  
Duplex Sequencing

Abstract Duplex sequencing is currently the most reliable method to identify ultra-low frequency DNA variants by grouping sequence reads derived from the same DNA molecule into families with information on the forward and reverse strand. However, only a small proportion of reads are assembled into duplex consensus sequences (DCS), and reads with potentially valuable information are discarded at different steps of the bioinformatics pipeline, especially reads without a family. We developed a bioinformatics toolset that analyses the tag and family composition with the purpose to understand data loss and implement modifications to maximize the data output for the variant calling. Specifically, our tools show that tags contain polymerase chain reaction and sequencing errors that contribute to data loss and lower DCS yields. Our tools also identified chimeras, which likely reflect barcode collisions. Finally, we also developed a tool that re-examines variant calls from raw reads and provides different summary data that categorizes the confidence level of a variant call by a tier-based system. With this tool, we can include reads without a family and check the reliability of the call, that increases substantially the sequencing depth for variant calling, a particular important advantage for low-input samples or low-coverage regions.

scholarly journals LncGSEA: a versatile tool to infer lncRNA associated pathways from large-scale cancer transcriptome sequencing data

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yanan Ren ◽  
Ting-You Wang ◽  
Leah C. Anderton ◽  
Qi Cao ◽  
Rendong Yang
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Clinical Samples ◽  
Sequencing Data ◽  
Multiple Cancer ◽  
Regulatory Pathways ◽  
Cancer Transcriptome ◽  
Versatile Tool

Abstract Background Long non-coding RNAs (lncRNAs) are a growing focus in cancer research. Deciphering pathways influenced by lncRNAs is important to understand their role in cancer. Although knock-down or overexpression of lncRNAs followed by gene expression profiling in cancer cell lines are established approaches to address this problem, these experimental data are not available for a majority of the annotated lncRNAs. Results As a surrogate, we present lncGSEA, a convenient tool to predict the lncRNA associated pathways through Gene Set Enrichment Analysis of gene expression profiles from large-scale cancer patient samples. We demonstrate that lncGSEA is able to recapitulate lncRNA associated pathways supported by literature and experimental validations in multiple cancer types. Conclusions LncGSEA allows researchers to infer lncRNA regulatory pathways directly from clinical samples in oncology. LncGSEA is written in R, and is freely accessible at https://github.com/ylab-hi/lncGSEA.

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