Expanding the utility of transcriptome analysis for mutation detection in high-risk childhood precision oncology
Chelsea MayohiD, Paulette BarahonaiD, Angela LiniD, Lujing CuiiD, Pamela AjuyahiD, Ann Altekoester, Loretta M. S. LauiD, Dong-Anh Khuong-QuangiD, Patricia A. SullivaniD, Akanksha SenapatiiD, Sumanth NagabushaniD, Ashleigh Sullivan, Natacha OmeriD, Andrew S. MooreiD, Wayne NichollsiD, Raelene EndersbyiD, Nicholas G. GottardoiD, Geoffrey Brian McCowageiD, Luciano Dalla Pozza, Jordan R. HansfordiD, Seong Lin KhawiD, Paul WoodiD, Toby N. TrahairiD, Glenn M. MarshalliD, David Simon ZiegleriD, , Mark J. CowleyiD
Abstract
In precision oncology, whole transcriptome sequencing (RNA-seq) excels at identifying oncogenic fusions. Here, using a cohort of 477 high-risk paediatric tumours, we demonstrate that RNA-seq can identify all mutation classes found previously using whole genome sequencing (WGS) and provides additional functional insights into their pathogenicity. By incorporating reference-guided fusion, and reference-free structural variant (SV) detection algorithms with RNA abundance assessment, RNA-seq identified 96% of SVs and resolved 33 complex SVs that WGS failed to identify. Furthermore, RNA-seq identified 92% of all single nucleotide variants and small insertions and deletions. Importantly RNA-seq informed the pathogenicity assessment in 22% of variants through identification of allele specific expression or the functional consequence of splice-altering variants. The utility of RNA-seq extends beyond fusion identification to the interpretation of mutation pathogenicity and the discovery of important mutations that would otherwise go undetected. We propose that RNA-seq is an indispensable companion to WGS in precision medicine.
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