Bioinformatics Seminars

Bioinformatics Seminar

Time: 10:45am Tuesdays.
Venue:
Level 7 Seminar Room 2, WEHI1

30 October 2018

Mintie: identifying cryptic variants in cancer transcriptomes using RNA-seq data

Marek Cmero
Murdoch Children

Gene fusions, tandem duplications and other transcriptomic structural variants can modify gene function and have important implications in cancer prognosis and treatment decisions. While calling fusions from RNA-seq data is well established, 'cryptic' variants such as fusions with non-gene sequence, tandem duplications, novel splice sites or other complex variants, are difficult to detect using existing approaches. While some of these events are possible to detect from DNA sequencing, others can be the result of variants affecting the transcriptional machinery and are only visible in the transcriptome.

To identify these variants in cancer transcriptomes, we developed Mintie, an integrated pipeline for the detection of cryptic variants using RNA-seq data. The Mintie pipeline first performs de novo assembly of transcripts. Next, novel transcripts are selected and all transcripts are then quantified using pseudo-alignment. Finally, differential expression versus controls is performed to identify over-expressed novel transcripts in each sample. Mintie also performs comprehensive annotation and visualisation of candidate cryptic variants.

In order to demonstrate Mintie, we ran the pipeline on a cohort of high-risk B-ALL patients, which included a subset of patients with poor outcome but no detected driver variant. In this subset, we identified several novel candidate driver cryptic variants. One such variant was a gene-disrupting cryptic fusion involving a truncation of the tumour suppressor gene RB1. We believe Mintie will be able to identify new cancer driver mechanisms across a range of cancer types.



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