Oncogene Concatenated Enriched Amplicon Nanopore Sequencing for rapid, accurate, and affordable somatic mutation detection.
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ABSTRACT:
SUBMITTER: Thirunavukarasu D
PROVIDER: S-EPMC8419911 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveWe aimed to evaluate the performance of nanopore amplicon sequencing detection for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in clinical samples.MethodWe carried out a single-center, prospective cohort study in a Wuhan hospital and collected a total of 86 clinical samples, including 54 pharyngeal swabs, 31 sputum samples, and 1 fecal sample, from 86 patients with coronavirus disease 2019 (COVID-19) from Feb 20 to May 15, 2020. We performed parallel detection with nanopore-based genome amplification and sequencing (NAS) on the Oxford Nanopore Technologies (ONT) minION platform and routine reverse transcription quantitative polymerase chain reaction (RT-qPCR). In addition, 27 negative control samples were detected using the two methods. The sensitivity and specificity of NAS were evaluated and compared with those of RT-qPCR.ResultsThe viral read number and reference genome coverage were both significantly different between the two groups of samples, and the latter was a better indicator for SARS-CoV-2 detection. Based on the reference genome coverage, NAS revealed both high sensitivity (96.5%) and specificity (100%) compared with RT-qPCR (80.2 and 96.3%, respectively), although the samples had been stored for half a year before the detection. The total time cost was less than 15 h, which was acceptable compared with that of RT-qPCR (∼2.5 h). In addition, the reference genome coverage of the viral reads was in line with the cycle threshold value of RT-qPCR, indicating that this number could also be used as an indicator of the viral load in a sample. The viral load in sputum might be related to the severity of the infection, particularly in patients within 4 weeks after onset of clinical manifestations, which could be used to evaluate the infection.ConclusionOur results showed the high sensitivity and specificity of the NAS method for SARS-CoV-2 detection compared with RT-qPCR. The sequencing results were also used as an indicator of the viral load to display the viral dynamics during infection. This study proved the wide application prospect of nanopore sequencing detection for SARS-CoV-2 and may more knowledge about the clinical characteristics of COVID-19.
| S-EPMC9019561 | biostudies-literature
Project description:Molecular markers are essential for cancer diagnosis, clinical trial enrollment, and some surgical decision making, motivating ultra-rapid, intraoperative variant detection. Sequencing-based detection is considered the gold standard approach, but typically takes hours to perform due to time-consuming DNA extraction, targeted amplification, and library preparation times. In this work, we present a proof-of-principle approach for sub-1 hour targeted variant detection using real-time DNA sequencers. By modifying existing protocols, optimizing for diagnostic time-to-result, we demonstrate confirmation of a hot-spot mutation from tumor tissue in ~52 minutes. To further reduce time, we explore rapid, targeted Loop-mediated Isothermal Amplification (LAMP) and design a bioinformatics tool-LAMPrey-to process sequenced LAMP product. LAMPrey's concatemer aware alignment algorithm is designed to maximize recovery of diagnostically relevant information leading to a more rapid detection versus standard read alignment approaches. Using LAMPrey, we demonstrate confirmation of a hot-spot mutation (250x support) from tumor tissue in less than 30 minutes.
| S-EPMC9284968 | biostudies-literature
Project description:Accurate detection of somatic mutations is still a challenge in cancer analysis. Here we present NeuSomatic, the first convolutional neural network approach for somatic mutation detection, which significantly outperforms previous methods on different sequencing platforms, sequencing strategies, and tumor purities. NeuSomatic summarizes sequence alignments into small matrices and incorporates more than a hundred features to capture mutation signals effectively. It can be used universally as a stand-alone somatic mutation detection method or with an ensemble of existing methods to achieve the highest accuracy.
| S-EPMC6399298 | biostudies-literature
Project description:Genome sequencing has shown strong capabilities in the initial stages of the COVID-19 pandemic such as pathogen identification and virus preliminary tracing. While the rapid acquisition of SARS-CoV-2 genome from clinical specimens is limited by their low nucleic acid load and the complexity of the nucleic acid background. To address this issue, we modified and evaluated an approach by utilizing SARS-CoV-2-specific amplicon amplification and Oxford Nanopore PromethION platform. This workflow started with the throat swab of the COVID-19 patient, combined reverse transcript PCR, and multi-amplification in one-step to shorten the experiment time, then can quickly and steadily obtain high-quality SARS-CoV-2 genome within 24 h. A comprehensive evaluation of the method was conducted in 42 samples: the sequencing quality of the method was correlated well with the viral load of the samples; high-quality SARS-CoV-2 genome could be obtained stably in the samples with Ct value up to 39.14; data yielding for different Ct values were assessed and the recommended sequencing time was 8 h for samples with Ct value of less than 20; variation analysis indicated that the method can detect the existing and emerging genomic mutations as well; Illumina sequencing verified that ultra-deep sequencing can greatly improve the single read error rate of Nanopore sequencing, making it as low as 0.4/10,000 bp. In summary, high-quality SARS-CoV-2 genome can be acquired by utilizing the amplicon amplification and it is an effective method in accelerating the acquisition of genetic resources and tracking the genome diversity of SARS-CoV-2.
| S-EPMC8043101 | biostudies-literature
Project description:Microbiome analysis through 16S rRNA gene sequencing is a crucial tool for understanding the microbial ecology of any habitat or ecosystem. However, workflows require large equipment, stable internet, and extensive computing power such that most of the work is performed far away from sample collection in both space and time. Performing amplicon sequencing and analysis at sample collection would have positive implications in many instances including remote fieldwork and point-of-care medical diagnoses. Here we present SituSeq, an offline and portable workflow for the sequencing and analysis of 16S rRNA gene amplicons using Nanopore sequencing and a standard laptop computer. SituSeq was validated by comparing Nanopore 16S rRNA gene amplicons, Illumina 16S rRNA gene amplicons, and Illumina metagenomes, sequenced using the same environmental DNA. Comparisons revealed consistent community composition, ecological trends, and sequence identity across platforms. Correlation between the abundance of taxa in each taxonomic level in Illumina and Nanopore data sets was high (Pearson's r > 0.9), and over 70% of Illumina 16S rRNA gene sequences matched a Nanopore sequence with greater than 97% sequence identity. On board a research vessel on the open ocean, SituSeq was used to analyze amplicon sequences from deep sea sediments less than 2 h after sequencing, and 8 h after sample collection. The rapidly available results informed decisions about subsequent sampling in near real-time while the offshore expedition was still underway. SituSeq is a portable and user-friendly workflow that helps to bring the power of microbial genomics and diagnostics to many more researchers and situations.
| S-EPMC10119094 | biostudies-literature
Project description:Accurate detection and analysis of somatic variants in cancer involve multiple third-party tools with complex dependencies and configurations, leading to laborious, error-prone, and time-consuming data conversions. This approach lacks accuracy, reproducibility, and portability, limiting clinical application. Musta was developed to address these issues as an end-to-end pipeline for detecting, classifying, and interpreting cancer mutations. Musta is based on a Python command-line tool designed to manage tumor-normal samples for precise somatic mutation analysis. The core is a Snakemake-based workflow that covers all key cancer genomics steps, including variant calling, mutational signature deconvolution, variant annotation, driver gene detection, pathway analysis, and tumor heterogeneity estimation. Musta is easy to install on any system via Docker, with a Makefile handling installation, configuration, and execution, allowing for full or partial pipeline runs. Musta has been validated at the CRS4-NGS Core facility and tested on large datasets from The Cancer Genome Atlas and the Beijing Institute of Genomics. Musta has proven robust and flexible for somatic variant analysis in cancer. It is user-friendly, requiring no specialized programming skills, and enables data processing with a single command line. Its reproducibility ensures consistent results across users following the same protocol.
| S-EPMC11311285 | biostudies-literature
Project description:The explosion of bioinformatics technologies in the form of next generation sequencing (NGS) has facilitated a massive influx of genomics data in the form of short reads. Short read mapping is therefore a fundamental component of next generation sequencing pipelines which routinely match these short reads against reference genomes for contig assembly. However, such techniques have seldom been applied to microbial marker gene sequencing studies, which have mostly relied on novel heuristic approaches. We propose NINJA Is Not Just Another OTU-Picking Solution (NINJA-OPS, or NINJA for short), a fast and highly accurate novel method enabling reference-based marker gene matching (picking Operational Taxonomic Units, or OTUs). NINJA takes advantage of the Burrows-Wheeler (BW) alignment using an artificial reference chromosome composed of concatenated reference sequences, the "concatesome," as the BW input. Other features include automatic support for paired-end reads with arbitrary insert sizes. NINJA is also free and open source and implements several pre-filtering methods that elicit substantial speedup when coupled with existing tools. We applied NINJA to several published microbiome studies, obtaining accuracy similar to or better than previous reference-based OTU-picking methods while achieving an order of magnitude or more speedup and using a fraction of the memory footprint. NINJA is a complete pipeline that takes a FASTA-formatted input file and outputs a QIIME-formatted taxonomy-annotated BIOM file for an entire MiSeq run of human gut microbiome 16S genes in under 10 minutes on a dual-core laptop.
| S-EPMC4731464 | biostudies-literature
Project description:BackgroundHigh-throughput sequencing is rapidly becoming common practice in clinical diagnosis and cancer research. Many algorithms have been developed for somatic single nucleotide variant (SNV) detection in matched tumor-normal DNA sequencing. Although numerous studies have compared the performance of various algorithms on exome data, there has not yet been a systematic evaluation using PCR-enriched amplicon data with a range of variant allele fractions. The recently developed gold standard variant set for the reference individual NA12878 by the NIST-led "Genome in a Bottle" Consortium (NIST-GIAB) provides a good resource to evaluate admixtures with various SNV fractions.ResultsUsing the NIST-GIAB gold standard, we compared the performance of five popular somatic SNV calling algorithms (GATK UnifiedGenotyper followed by simple subtraction, MuTect, Strelka, SomaticSniper and VarScan2) for matched tumor-normal amplicon and exome sequencing data.ConclusionsWe demonstrated that the five commonly used somatic SNV calling methods are applicable to both targeted amplicon and exome sequencing data. However, the sensitivities of these methods vary based on the allelic fraction of the mutation in the tumor sample. Our analysis can assist researchers in choosing a somatic SNV calling method suitable for their specific needs.
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Project description:Rapid, cost-effective identification of genetic variants in small candidate genomic regions remains a challenge, particularly for less well equipped or lower throughput laboratories. The application of Oxford Nanopore Technologies' MinION sequencer has the potential to fulfil this requirement. We demonstrate a proof of concept for a multiplexing assay that pools PCR amplicons for MinION sequencing to enable sequencing of multiple templates from multiple individuals, which could be applied to gene-targeted diagnostics. A combined strategy of barcoding and sample pooling was developed for simultaneous multiplex MinION sequencing of 100 PCR amplicons. The amplicons are family-specific, spanning a total of 30 loci in DNA isolated from 82 human neurodevelopmental cases and family members. The target regions were chosen for further interrogation because a potentially disease-causative variant had been identified in affected individuals following Illumina exome sequencing. The pooled MinION sequences were deconvoluted by aligning to custom references using the minimap2 aligner software. Our multiplexing approach produced an interpretable and expected sequence from 29 of the 30 targeted genetic loci. The sequence variant which was not correctly resolved in the MinION sequence was adjacent to a five nucleotide homopolymer. It is already known that homopolymers present a resolution problem with the MinION approach. Interestingly despite equimolar quantities of PCR amplicon pooled for sequencing, significant variation in the depth of coverage (127×-19,626×; mean = 8321×, std err = 452.99) was observed. We observed independent relationships between depth of coverage and target length, and depth of coverage and GC content. These relationships demonstrate biases of the MinION sequencer for longer templates and those with lower GC content. We demonstrate an efficient approach for variant discovery or confirmation from short DNA templates using the MinION sequencing device. With less than 130 × depth of coverage required for accurate genotyping, the methodology described here allows for rapid highly multiplexed targeted sequencing of large numbers of samples in a minimally equipped laboratory with a potential cost as much 200 × less than that from Sanger sequencing.
| S-EPMC9122479 | biostudies-literature
Project description:Nanopore sensing has emerged as a versatile approach to detection and identification of biomolecules. Presently, researchers rely on experience and intuition for choosing or modifying the nanopores to detect a target analyte. The field would greatly benefit from a computational method that could relate the atomic-scale geometry of the nanopores and analytes to the blockade nanopore currents they produce. Existing computational methods are either computationally too expensive to be used routinely in experimental laboratories or not sensitive enough to account for the atomic structure of the pore and the analytes. Here, we demonstrate a robust and inexpensive computational approach-the steric exclusion model (SEM) of nanopore conductance-that is orders of magnitude more efficient than all-atom MD and yet is sensitive enough to account for the atomic structure of the nanopore and the analyte. The method combines the computational efficiency of a finite element solver with the atomic precision of a nanopore conductance map to yield unprecedented speed and accuracy of ionic current prediction. We validate our SEM approach through comparison with the current blockades computed using the all-atom molecular dynamics method for a range of proteins confined to a solid-state nanopore, biological channels embedded in a lipid bilayer membranes, and blockade currents produced by DNA homopolymers in MspA. We illustrate potential applications of SEM by computing blockade currents produced by nucleosome proteins in a solid-state nanopore, individual amino acids in MspA, and by testing the effect of point mutations on amino acid distinguishability. We expect our SEM approach to become an integral part of future development of the nanopore sensing field.
| S-EPMC6489136 | biostudies-literature