RNA Sequencing Based Whole Transcriptome Analysis Detected Precisely All Fusion Transcripts in Leukemias

Abstract Introduction: Fusion transcript is a chimeric RNA encoded by a fusion gene or by two different genes by subsequent trans-splicing. Detection of fusion transcripts is an integral part of routine diagnostics of hematological malignancies. However, most of previous analytical methods couldn't detect all fusion transcripts in leukemia. In this study, we developed accurate fusion transcript detection methood using whole transcriptome sequencing, fusion gene detection software and expression analysis. Methods: RNA sequencing (RNA-seq) for whole transcriptome was performed in 11 patients with hematological malignancies (4 AML, 2 APL, 2 ALL, and 3 CML) having fusion transcripts detected by multiplex RT-PCR (HemaVision, DNA Diagnostic, Risskov, Denmark). Library were prepared with 1 ug of total RNA for each sample by TruSeq mRNA Sample Prep kit (Illumina, San Diego, USA). The libraries were quantified using qPCR according to the qPCR Quantification Protocol Guide (KAPA Library Quantificatoin kits for Illumina Sequecing platforms) and qualified using the TapeStation D1000 ScreenTape (Agilent Technologies, Santa Clara, USA). Indexed libraries were then sequenced using the HiSeq2500 platform (Illumina). The data obtained from the sequencing was analyzed using STAR-Fusion (v1.2.0). Novel fusion transcripts were confirmed by conventional sequencing. Results: Using STAR-Fusion, average number of fusion candidates per sample was 949.8 (range, 286-1752). To exclude false positive results and obtain true positive results, we developed the following filtering algorithm. First filtering criterion is to have more than 5 junction reads, the second is to detect more than one number of spanning reads, and the third criterion is to be in-frame fusion, which type of fusion can actually synthesize intact protein. Fusion candidates remaining after applying the above three filtering criteria were 1-3 per sample. All known fusion transcripts (PML--RARA, RUNX--RUNX1T1, CBFB--MYH11, KMT2A--MLLT3, BCR--ABL1, DEK--NUP214, ETV6--RUNX1) by multiplex RT-PCR were also detected in RNA-seq. In addition, 10 novel fusion transcripts (IGKV4-1--IGKC, IGLV1-47--IGLC2, HBA2--HBB, DEFA3--MBNL1, HBB--HBA2, MPO--HBA2, HBS1L--AHI1, HBB--HBA2, IGKV4-1--IGKC, SS18L1--ADRM1) were detected and among them, 6 fusions were confirmed by conventional sequencing. Conclusions: Whole transcriptome sequencing and optimized filtering algorithms successfully detected all known fusion transcripts and various novel fusions. Disclosures No relevant conflicts of interest to declare.