SeekFusion - A Clinically Validated Fusion Transcript Detection Pipeline for PCR-Based Next-Generation Sequencing of RNA.

Jagadheshwar Balan,Jesse Voss,Benjamin R Kipp,Aditya Raghunathan,Kevin C Halling,Cris Ida,Robert Jenkins,Neiladri Saha,Surendra Dasari,Patrick R Blackburn,Asha Nair,Eric W Klee,Christian A Ross,Garrett Jenkinson,Gavin R Oliver,Emily G Barr Fritcher,Tejaswi Koganti,Caterina Giannini,Christopher Zysk

doi:10.3389/fgene.2021.739054

Abstract

Detecting gene fusions involving driver oncogenes is pivotal in clinical diagnosis and treatment of cancer patients. Recent developments in next-generation sequencing (NGS) technologies have enabled improved assays for bioinformatics-based gene fusions detection. In clinical applications, where a small number of fusions are clinically actionable, targeted polymerase chain reaction (PCR)-based NGS chemistries, such as the QIAseq RNAscan assay, aim to improve accuracy compared to standard RNA sequencing. Existing informatics methods for gene fusion detection in NGS-based RNA sequencing assays traditionally use a transcriptome-based spliced alignment approach or a de-novo assembly approach. Transcriptome-based spliced alignment methods face challenges with short read mapping yielding low quality alignments. De-novo assembly-based methods yield longer contigs from short reads that can be more sensitive for genomic rearrangements, but face performance and scalability challenges. Consequently, there exists a need for a method to efficiently and accurately detect fusions in targeted PCR-based NGS chemistries. We describe SeekFusion, a highly accurate and computationally efficient pipeline enabling identification of gene fusions from PCR-based NGS chemistries. Utilizing biological samples processed with the QIAseq RNAscan assay and in-silico simulated data we demonstrate that SeekFusion gene fusion detection accuracy outperforms popular existing methods such as STAR-Fusion, TOPHAT-Fusion and JAFFA-hybrid. We also present results from 4,484 patient samples tested for neurological tumors and sarcoma, encompassing details on some novel fusions identified.

Highlights

Gene fusions are potentially pathogenic events that result from genomic structural rearrangements including inversions, translocations, and interstitial deletions
The accuracy of SeekFusion was highest among the benchmarked tools, followed by JAFFA-hybrid, STAR-Fusion and TOPHATFusion (Figure 4A)
We have developed a novel bioinformatics pipeline to enable accurate and precise gene fusion detection for commonly used RNA unique molecular indexes (UMI)-based amplicon next-generation sequencing (NGS) assays

Summary

Introduction

Gene fusions are potentially pathogenic events that result from genomic structural rearrangements including inversions, translocations, and interstitial deletions. RNA sequencing (RNA-Seq) assays for gene fusion detection provide improvements in throughput, sensitivity and specificity over traditional DNA and protein-based approaches like fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC) (Wang et al, 2009; Abel et al, 2014; Moskalev et al, 2014; Pekar-Zlotin et al, 2015; Haynes et al, 2019). RNA-based strategies to detect gene fusions use transcriptome-wide sequencing with ribosomal RNA-depleted, fractionated messenger RNA or target specific genes of interest using polymerase chain reaction (PCR) based amplicon RNASeq, or bait hybridization (capture and ligation) using assays such as QIAGEN’s QIAseq RNAscan panel or Illumina’s SureSelect RNA capture (Wang et al, 2009; Blomquist et al, 2013; Drilon et al, 2015). QIAseq NGS assay panels have been demonstrated to provide robust correlation with RT-PCR and low PCR-bias (Wong et al, 2019), and so was the chemistry used in this study (see Methods, Library Preparation and Sequencing section)

Methods

Results

Conclusion