0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      A unified DNA‐ and RNA‐based NGS strategy for the analysis of multiple types of variants at the dual nucleic acid level in solid tumors

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Targeted next‐generation sequencing (NGS) is a powerful and suitable approach to comprehensively identify multiple types of variants in tumors. RNA‐based NGS is increasingly playing an important role in precision oncology. Both parallel and sequential DNA‐ and RNA‐based approaches are expensive, burdensome, and have long turnaround times, which can be impractical in clinical practice. A streamlined, unified DNA‐ and RNA‐based NGS approach is urgently needed in clinical practice.

          Methods

          A DNA/RNA co‐hybrid capture sequencing (DRCC‐Seq) approach was designed to capture pre‐capture DNA and RNA libraries in a single tube and convert them into one NGS library. The performance of the DRCC‐Seq approach was evaluated by a panel of reference standards and clinical samples.

          Results

          The average depth, DNA data ratio, capture ratio, and target coverage 250 (×) of the DNA panel data had a negative correlation with an increase in the proportion of RNA probes. The SNVs, indels, fusions, and MSI status were not affected by the proportion of RNA probes, but the copy numbers of the target genes were higher than expected in the standard materials, and many unexpected gene amplifications were found using D:R (1:2) and D:R (1:4) probe panels. The optimal ratio of DNA and RNA probes in the combined probe panel was 1:1 using the DRCC‐Seq approach. The DRCC‐Seq approach was feasible and reliable for detecting multiple types of variants in reference standards and real‐world clinical samples.

          Conclusions

          The DRCC‐Seq approach is more cost‐effective, with a shorter turnaround time and lower labor requirements than either parallel or sequential targeted DNA NGS and RNA NGS. It is feasible to identify multiple genetic variations at the DNA and RNA levels simultaneously in clinical practice.

          Abstract

          Genomic DNA was processed to pre‐capture the DNA NGS library through fragmentation, adaptor ligation, and PCR amplification. The total RNA was subjected to fragmentation and reverse transcription to generate the double‐stranded, fragmented cDNA. The pre‐capture RNA library was prepared through adaptor ligation and PCR amplification. The different indexes or barcodes were used during the DNA and RNA library preparation process to identify the DNA and RNA data from the same sample. The pre‐capture DNA and RNA libraries were mixed. Then, the library mixture was captured using the combined custom DNA and RNA panel probes in a single tube and converted to one sequencing library.

          Related collections

          Most cited references41

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Fast and accurate short read alignment with Burrows–Wheeler transform

          Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

            Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS--the 1000 Genome pilot alone includes nearly five terabases--make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing.

              Cancer is a disease driven by genetic variation and mutation. Exome sequencing can be utilized for discovering these variants and mutations across hundreds of tumors. Here we present an analysis tool, VarScan 2, for the detection of somatic mutations and copy number alterations (CNAs) in exome data from tumor-normal pairs. Unlike most current approaches, our algorithm reads data from both samples simultaneously; a heuristic and statistical algorithm detects sequence variants and classifies them by somatic status (germline, somatic, or LOH); while a comparison of normalized read depth delineates relative copy number changes. We apply these methods to the analysis of exome sequence data from 151 high-grade ovarian tumors characterized as part of the Cancer Genome Atlas (TCGA). We validated some 7790 somatic coding mutations, achieving 93% sensitivity and 85% precision for single nucleotide variant (SNV) detection. Exome-based CNA analysis identified 29 large-scale alterations and 619 focal events per tumor on average. As in our previous analysis of these data, we observed frequent amplification of oncogenes (e.g., CCNE1, MYC) and deletion of tumor suppressors (NF1, PTEN, and CDKN2A). We searched for additional recurrent focal CNAs using the correlation matrix diagonal segmentation (CMDS) algorithm, which identified 424 significant events affecting 582 genes. Taken together, our results demonstrate the robust performance of VarScan 2 for somatic mutation and CNA detection and shed new light on the landscape of genetic alterations in ovarian cancer.
                Bookmark

                Author and article information

                Contributors
                xiaohongduan@chosenmedtech.com
                qimingzhou@chosenmedtech.com
                Journal
                J Clin Lab Anal
                J Clin Lab Anal
                10.1002/(ISSN)1098-2825
                JCLA
                Journal of Clinical Laboratory Analysis
                John Wiley and Sons Inc. (Hoboken )
                0887-8013
                1098-2825
                25 October 2023
                October 2023
                : 37
                : 19-20 ( doiID: 10.1002/jcla.v37.19-20 )
                : e24977
                Affiliations
                [ 1 ] ChosenMed Clinical Laboratory (Beijing) Co. Ltd. Beijing China
                [ 2 ] Computer Network Information Center, Chinese Academy of Sciences Beijing China
                [ 3 ] WillingMed Technology Beijing Co., Ltd. Beijing China
                [ 4 ] ChosenMed Technology (Zhejiang) Co. Ltd. Zhejiang China
                [ 5 ] Institute of Disaster and Emergency Medicine, Medical College Tianjin University TianJin China
                Author notes
                [*] [* ] Correspondence

                Qiming Zhou and Xiaohong Duan, ChosenMed Clinical Laboratory (Beijing) Company Limited, Jinghai Industrial Park, Economic and Technological Development Area, Beijing 100176, China.

                Email: qimingzhou@ 123456chosenmedtech.com and xiaohongduan@ 123456chosenmedtech.com

                Author information
                https://orcid.org/0000-0003-1126-2324
                Article
                JCLA24977 JCLA-23-742.R1
                10.1002/jcla.24977
                10681543
                37877443
                6c679fa8-956e-4f37-9aca-6772c5091c62
                © 2023 The Authors. Journal of Clinical Laboratory Analysis published by Wiley Periodicals LLC.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 27 September 2023
                : 11 July 2023
                : 15 October 2023
                Page count
                Figures: 5, Tables: 1, Pages: 9, Words: 5518
                Funding
                Funded by: the National Human Genetic Resources Sharing Service Platform
                Award ID: 2005DKA21300
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                October 2023
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.3.5 mode:remove_FC converted:27.11.2023

                Clinical chemistry
                dna‐based ngs,genomic variations,next‐generation sequencing,rna‐based ngs

                Comments

                Comment on this article