targeted-rna-sequencing-assay-to-characterize-gene-expression-genomic

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

RNA sequencing (RNAseq) is a versatile method that can be utilized to detect and characterize gene expression, mutations, gene fusions, and noncoding ...

The Ohio State University

Targeted, capture-based DNA sequencing is a cost-effective method to focus sequencing on a coding region or other customized region of the genome. There are multiple targeted sequencing methods available, but none has been systematically investigated and compared. We evaluated four commercially available custom-targeted DNA technologies for next-generation sequencing with respect to on-target sequencing, uniformity, and ability to detect single-nucleotide variations (SNVs) and copy number variations. The technologies that used sonication for DNA fragmentation displayed impressive uniformity of capture, whereas the others had shorter preparation times, but sacrificed uniformity. One of those technologies, which uses transposase for DNA fragmentation, has a drawback requiring sample pooling, and the last one, which uses restriction enzymes, has a limitation depending on restriction enzyme digest sites. Although all technologies displayed some level of concordance for calling SNVs, the technologies that require restriction enzymes or transposase missed several SNVs largely because of the lack of coverage. All technologies performed well for copy number variation calling when compared to single-nucleotide polymorphism arrays. These results enable laboratories to compare these methods to make informed decisions for their intended applications.

Comparison of custom capture for targeted next-generation DNA sequencing.

Next-generation sequencing has aided characterization of genomic variation. While whole-genome sequencing may capture all possible mutations, whole-exome sequencing remains cost-effective and captures most phenotype-altering mutations. Initial strategies for exome enrichment utilized a hybridization-based capture approach. Recently, amplicon-based methods were designed to simplify preparation and utilize smaller DNA inputs. We evaluated two hybridization capture-based and two amplicon-based whole-exome sequencing approaches, utilizing both Illumina and Ion Torrent sequencers, comparing on-target alignment, uniformity, and variant calling. While the amplicon methods had higher on-target rates, the hybridization capture-based approaches demonstrated better uniformity. All methods identified many of the same single-nucleotide variants, but each amplicon-based method missed variants detected by the other three methods and reported additional variants discordant with all three other technologies. Many of these potential false positives or negatives appear to result from limited coverage, low variant frequency, vicinity to read starts/ends, or the need for platform-specific variant calling algorithms. All methods demonstrated effective copy-number variant calling when evaluated against a single-nucleotide polymorphism array. This study illustrates some differences between whole-exome sequencing approaches, highlights the need for selecting appropriate variant calling based on capture method, and will aid laboratories in selecting their preferred approach.

Evaluation of Hybridization Capture Versus Amplicon-Based Methods for Whole-Exome Sequencing.

Massively parallel sequencing technologies have enabled characterization of genomic alterations across multiple tumor types. Efforts have focused on identifying driver mutations because they represent potential targets for therapy. However, because of the presence of driver and passenger mutations, it is often challenging to assign the clinical relevance of specific mutations observed in patients. Currently, there are multiple databases and tools that provide in silico assessment for potential drivers; however, there is no comprehensive resource for mutations with functional characterization. Therefore, we created an expert-curated database of potentially actionable driver mutations for molecular pathologists to facilitate annotation of cancer genomic testing. We reviewed scientific literature to identify variants that have been functionally characterized in vitro or in vivo as driver mutations. We obtained the chromosome location and all possible nucleotide positions for each amino acid change and uploaded them to the Cancer Driver Log (CanDL) database with associated literature reference indicating functional driver evidence. In addition to a simple interface, the database allows users to download all or selected genes as a comma-separated values file for incorporation into their own analysis pipeline. Furthermore, the database includes a mechanism for third-party contributions to support updates for novel driver mutations. Overall, this freely available database will facilitate rapid annotation of cancer genomic testing in molecular pathology laboratories for mutations.

Jharna Miya

Department of Internal Medicine,
Division of Medical Oncology,
Comprehensive Cancer Center,
Department of Internal Medicine, Division of Medical Oncology, Comprehensive Cancer Center

The Ohio State University

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Jharna Miya

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Internal Medicine,Division of Medical Oncology,Comprehensive Cancer Center,Department of Internal Medicine, Division of Medical Oncology, Comprehensive Cancer Center

The Ohio State University

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Department of Internal Medicine,
Division of Medical Oncology,
Comprehensive Cancer Center,
Department of Internal Medicine, Division of Medical Oncology, Comprehensive Cancer Center