Indel sensitive and comprehensive variant/mutation detection from RNA sequencing data for precision medicine

Abstract

BackgroundRNA-seq is the most commonly used sequencing application. Not only does it measure gene expression but it is also an excellent media to detect important structural variants such as single nucleotide variants (SNVs), insertion/deletion (Indels) or fusion transcripts. However, detection of these variants is challenging and complex from RNA-seq. Here we describe a sensitive and accurate analytical pipeline which detects various mutations at once for translational precision medicine.MethodsThe pipeline incorporates most sensitive aligners for Indels in RNA-Seq, the best practice for data preprocessing and variant calling, and STAR-fusion is for chimeric transcripts. Variants/mutations are annotated, and key genes can be extracted for further investigation and clinical actions. Three datasets were used to evaluate the performance of the pipeline for SNVs, indels and fusion transcripts.ResultsFor the well-defined variants from NA12878 by GIAB project, about 95% and 80% of sensitivities were obtained for SNVs and indels, respectively, in matching RNA-seq. Comparison with other variant specific tools showed good performance of the pipeline. For the lung cancer dataset with 41 known and oncogenic mutations, 39 were detected by the pipeline with STAR aligner and all by the GSNAP aligner. An actionable EML4 and ALK fusion was also detected in one of the tumors, which also demonstrated outlier ALK expression. For 9 fusions spiked-into RNA-seq libraries with different concentrations, the pipeline was able to detect all in unfiltered results although some at very low concentrations may be missed when filtering was applied.ConclusionsThe new RNA-seq workflow is an accurate and comprehensive mutation profiler from RNA-seq. Key or actionable mutations are reliably detected from RNA-seq, which makes it a practical alternative source for personalized medicine.Electronic supplementary materialThe online version of this article (10.1186/s12920-018-0391-5) contains supplementary material, which is available to authorized users.

Maximizing Small Biopsy Patient Samples: Unified RNA-Seq Platform Assessment of over 120,000 Patient Biopsies

“…Furthermore, in addition to quantifying expression through gene counts, sequencing of RNA transcripts enables the detection and identification of both known and novel translocation (e.g., fusion) events. Single-nucleotide variants (SNVs), and insertions and deletions (indels) that are present in germline or somatic DNA, can also be detected by RNA-Seq if the gene is expressed in a particular specimen (i.e., expressed variants) [ 18 , 19 , 20 ]. Additionally, the mitochondrial genome can be interrogated by measuring quantitative expression of transcripts, as well as variant detection [ 21 , 22 ].…”

Performance of an RNA-Based Next-Generation Sequencing Assay for Combined Detection of Clinically Actionable Fusions and Hotspot Mutations in NSCLC

“…Apart from these observations, data from singlecell RNA-seq support that oncogenic or actionable SNVs/ indels are detectable in RNA-seq from lung adenocarcinoma, notably, but the selection of proper bioinformatics alignment tools for indel detection is essential. 17,18 Our observations here suggest that the Vision variant caller and Archer's bioinformatics pipeline overall are sufficiently robust for detecting such type of alterations in a clinical setting.…”

Matrilineal analysis of mutations in the DMD gene in a multigenerational South Indian cohort using DMD gene panel sequencing

“…Recently several novel therapies targeting specific DMD mutations (including stop-codon read-through agents, exonskipping antisense oligonucleotides (AONs) etc.) that target and restore Dystrophin function (Aartsma-Rus et al, 2009;Babbs et al, 2020;Haas et al, 2015;Laing et al, 2011;Ousterout et al, 2015;Reinig et al, 2017) have been developed. An early and accurate molecular diagnosis is critical for most of these therapies (Aartsma-rus et al, 2016).…”

“…Even though MLPA is a cost-effective method for diagnosis of CNV alterations in the DMD gene, it cannot give the genomic breakpoints of the deletion or duplication event. Also, MLPA has a higher propensity to miss small indels (<20 bp) and cannot detect single-nucleotide variants (SNVs) and deep intronic mutations (Aartsma-rus et al, 2016;Prodduturi et al, 2018). Patients showing symptoms but negative for DMD mutation using MLPA are tested using NGS techniques to detect SNVs or other small indels.…”