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Related Concept Videos

RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
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Ribosome Profiling02:24

Ribosome Profiling

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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
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Related Experiment Video

Updated: Apr 29, 2026

Sequencing Small Non-coding RNA from Formalin-fixed Tissues and Serum-derived Exosomes from Castration-resistant Prostate Cancer Patients
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Transcriptome profiling of prostate tumor and matched normal samples by RNA-Seq.

W Zhai1, X-d Yao, Y-f Xu

  • 1Department of Urology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China. jacky_zw2002@hotmail.com.

European Review for Medical and Pharmacological Sciences
|May 29, 2014
PubMed
Summary

RNA-Sequencing (RNA-Seq) identified differentially expressed genes and a lincRNA in prostate tumors. This lincRNA, antisense to CAND1, is repressed in tumors, suggesting a potential role in cancer progression.

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Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • RNA-Sequencing (RNA-Seq) offers high-resolution gene expression analysis in cancer research.
  • RNA-Seq surpasses cDNA microarray in sensitivity and reduced noise.

Purpose of the Study:

  • Identify protein-coding genes and long non-coding RNAs (lincRNAs) with differential expression between tumor and normal tissues.
  • Investigate potential biomarkers for prostate cancer.

Main Methods:

  • Analyzed transcriptome datasets from 10 human prostate tumor and matched normal tissues.
  • Utilized RNA-Sequencing technology for gene expression profiling.
  • Aligned short reads to human RefSeq genes and lincRNAs.

Main Results:

  • Identified 10 RefSeq genes differentially expressed (p < 0.05) between tumor and normal samples.
  • Discovered a lincRNA antisense to CAND1, repressed in prostate tumors (p < 0.1).
  • Observed an inverse expression pattern between CAND1 and its antisense lincRNA in tumor versus normal tissues.

Conclusions:

  • RNA-Sequencing is valuable for cancer biomarker development.
  • The identified lincRNA and its interaction with CAND1 warrant further functional investigation in prostate cancer.