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Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data
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Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data

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Transcriptome Sequencing for the Detection of Chimeric Transcripts

Hsueh-Ting Chu1,2

  • 1Department of Computer Science and Information Engineering, Asia University, No. 500, Liufeng Road, Wufeng District, Taichung City, 413, Taiwan. htchu@asia.edu.tw.

Methods in Molecular Biology (Clifton, N.J.)
|December 16, 2015
PubMed

Insights

Chimeric transcripts in cancer cells can be biomarkers and therapeutic targets. This study discusses detection methods using high-throughput sequencing, including assembly-based and alignment-based approaches for analyzing short read sequence data.

Area of Science:

  • Genomics
  • Bioinformatics
  • Cancer Biology

Background:

  • Chimeric transcripts are observed in various cancer cells.
  • These transcripts are potential biomarkers and therapeutic targets.
  • High-throughput sequencing technologies enable investigation of chimeric transcripts and associated gene expression.

Purpose of the Study:

  • To discuss methods for detecting chimeric transcripts.
  • To highlight the role of sequencing technologies in understanding genomic variations and interactions.

Main Methods:

  • Review of detection methods for chimeric transcripts from short read sequence data.
  • Discussion of assembly-based and alignment-based approaches.

Main Results:

  • Chimeric transcripts are detectable using modern sequencing technologies.
  • Both assembly-based and alignment-based methods are applicable for their investigation.

Conclusions:

  • Detection methods for chimeric transcripts are crucial for cancer research.
  • Understanding chimeric transcripts aids in identifying genomic structural variations and interactions.
Keywords:
Cancer genesChimeric transcriptDe novo assemblyFusion genesTranscriptome sequencing

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