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Overexpressing Long Noncoding RNAs Using Gene-activating CRISPR
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Identification and Expression Analysis of Long Intergenic Noncoding RNAs.

Ming-An Sun1, Rihong Zhai2, Qing Zhang3

  • 1Epigenomics and Computational Biology Lab, Biocomplexity Institute of Virginia Tech, Blacksburg, VA, USA. mingansun@gmail.com.

Methods in Molecular Biology (Clifton, N.J.)
|March 7, 2018
PubMed
Summary
This summary is machine-generated.

This protocol details computational analysis for long intergenic noncoding RNAs (lincRNAs) using RNA-Seq data. It provides a step-by-step guide for identifying and analyzing these important RNA molecules.

Keywords:
CPATCufflinksDifferential expressionNoncoding RNARNA-SeqSTARlincRNAlncRNA

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Long intergenic noncoding RNAs (lincRNAs) are increasingly recognized for their biological roles.
  • RNA sequencing (RNA-Seq) technologies have accelerated the discovery of novel lincRNAs.
  • Computational analysis of lincRNA data remains a significant challenge in the field.

Purpose of the Study:

  • To present a comprehensive, step-by-step computational protocol for lincRNA analysis.
  • To address the challenges in analyzing lincRNA data derived from RNA-Seq.
  • To provide a standardized workflow for researchers in the field.

Main Methods:

  • Read processing and alignment of RNA-Seq data.
  • Transcript assembly for novel RNA discovery.
  • LincRNA identification and functional annotation.
  • Differential expression analysis to compare lincRNA levels.

Main Results:

  • A robust and reproducible protocol for lincRNA computational analysis.
  • Facilitation of accurate identification and annotation of lincRNAs.
  • Enabling differential expression analysis for lincRNA studies.

Conclusions:

  • The presented protocol simplifies and standardizes the computational analysis of lincRNAs.
  • This workflow aids in the effective study of lincRNA functions and roles.
  • The protocol is valuable for researchers utilizing RNA-Seq for lincRNA discovery and analysis.