Transcript-targeted analysis reveals isoform alterations and double-hop fusions in breast cancer

Abstract

Namba et al develop a new pipeline called MuSTA to enable the efficient assembly of transcriptome from long-read sequencing data of breast cancer samples. This method enables the authors to discover subtype-specific isoforms, find that fusion transcript structures depend on their genomic context and identify a double-hop fusion that results in aberrant expression of an endogenous retroviral gene.