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Related Concept Videos

RNA-seq03:21

RNA-seq

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 microarray-based...
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Ribosome Profiling

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.
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Related Experiment Video

Updated: May 9, 2026

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level
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CoLIde: a bioinformatics tool for CO-expression-based small RNA Loci Identification using high-throughput sequencing

Irina Mohorianu1, Matthew Benedict Stocks, John Wood

  • 1University of East Anglia; School of Computing Sciences; Norwich, UK.

RNA Biology
|July 16, 2013
PubMed
Summary

Identifying small RNA (sRNA) loci is crucial for understanding RNA silencing. A new method, CoLIde, integrates genomic location with expression patterns and size distribution to accurately detect sRNA loci in plants and animals.

Keywords:
expression levelhigh throughput sequencingmiRNAmicroRNApatternsRNAsRNA locisRNAomesmall RNA

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Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Small RNAs (sRNAs) are key regulators in RNA silencing, with sequencing revealing complex populations in plants and animals.
  • Identifying individual sRNA transcripts (sRNA loci) is challenging due to massive sequencing data and reliance on genomic location alone.

Purpose of the Study:

  • To develop a novel computational approach, CoLIde, for accurate sRNA loci detection.
  • To improve the identification of biologically relevant sRNA units by integrating multiple data types.

Main Methods:

  • CoLIde combines genomic location with expression patterns and size class distribution of sRNAs.
  • A locus is defined as a genomic region with a shared expression pattern and proximity.
  • The method analyzes biological relevance using size class distribution and is applicable to various sample types and replicates.

Main Results:

  • CoLIde reliably identifies known sRNA loci.
  • The method demonstrates improved performance on plant and animal sequencing data compared to existing techniques.
  • CoLIde successfully integrates genomic location, expression variation, and size distribution for locus identification.

Conclusions:

  • CoLIde offers a robust and improved method for sRNA loci detection.
  • The approach enhances the analysis of complex sRNA populations in diverse organisms.
  • CoLIde is available in the UEA Small RNA Workbench for broader accessibility.