Extensive research into gene fusions in cancer and other diseases has led to the discovery of novel biomarkers and therapeutic targets. Concurrently, various bioinformatics tools have been developed for fusion detection in RNA sequencing data, which, in the age of increasing affordability of sequencing, have delivered a large-scale identification of transcriptomic abnormalities. Historically, the focus of fusion transcript research was predominantly on coding RNAs and their resultant proteins, often overlooking non-coding RNAs (ncRNAs). This chapter discusses how ncRNAs are integral players in the landscape of gene fusions, detailing their contributions to the formation of gene fusions and their presence in chimeric transcripts. We delve into both linear and the more recently identified circular fusion RNAs, providing a comprehensive overview of the computational methodologies used to detect ncRNA-involved gene fusions. Additionally, we examine the inherent biases and limitations of these bioinformatics approaches, offering insights into the challenges and future directions in this dynamic field.

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Architects and Partners: The Dual Roles of Non-coding RNAs in Gene Fusion Events

  • Ryley Dorney,
  • Laís Reis-das-Mercês,
  • Ulf Schmitz

摘要

Extensive research into gene fusions in cancer and other diseases has led to the discovery of novel biomarkers and therapeutic targets. Concurrently, various bioinformatics tools have been developed for fusion detection in RNA sequencing data, which, in the age of increasing affordability of sequencing, have delivered a large-scale identification of transcriptomic abnormalities. Historically, the focus of fusion transcript research was predominantly on coding RNAs and their resultant proteins, often overlooking non-coding RNAs (ncRNAs). This chapter discusses how ncRNAs are integral players in the landscape of gene fusions, detailing their contributions to the formation of gene fusions and their presence in chimeric transcripts. We delve into both linear and the more recently identified circular fusion RNAs, providing a comprehensive overview of the computational methodologies used to detect ncRNA-involved gene fusions. Additionally, we examine the inherent biases and limitations of these bioinformatics approaches, offering insights into the challenges and future directions in this dynamic field.