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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...
Ribosome Profiling02:24

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.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...
RACE - Rapid Amplification of cDNA Ends02:35

RACE - Rapid Amplification of cDNA Ends

Rapid Amplification of cDNA Ends, or RACE, is one of the most effective methods to obtain a full-length cDNA from an mRNA sequence between a known internal region to the unknown sequence at the 5’ or 3’ end. The unknown region is cloned in the cDNA by a gene-specific primer that binds the known end, and a hybrid primer that attaches a predefined anchor sequence to the unknown end of the cDNA. The sequence in between is amplified by PCR with an anchor primer and a gene-specific primer.
Since the...
In-situ Hybridization02:31

In-situ Hybridization

In situ hybridization (ISH) is a technique used to detect and localize specific DNA or RNA molecules in cells, tissue, or tissue sections using a labeled probe. The technique was first used in 1969 for the investigation of nucleic acids. It is currently an essential tool in scientific research and clinical settings, especially for diagnostic purposes.
Types of probes and labels
A probe is a complementary strand of DNA or RNA that binds to corresponding nucleotide sequences in a cell. Many...

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Related Experiment Video

Updated: May 21, 2026

AQRNA-seq for Quantifying Small RNAs
05:12

AQRNA-seq for Quantifying Small RNAs

Published on: February 2, 2024

Hybridization-based reconstruction of small non-coding RNA transcripts from deep sequencing data.

Chikako Ragan1, Bryan J Mowry, Denis C Bauer

  • 1The University of Queensland, Queensland Brain Institute, Brisbane, Qld. 4072, Australia. c.ragan@uq.edu.au

Nucleic Acids Research
|June 19, 2012
PubMed
Summary
This summary is machine-generated.

NorahDesk is a new tool for detecting small non-coding RNAs (ncRNAs) from RNA sequencing data. It improves upon existing methods by analyzing read coverage and RNA structure, excelling at identifying piwi-interacting RNAs (piRNAs).

Related Experiment Videos

Last Updated: May 21, 2026

AQRNA-seq for Quantifying Small RNAs
05:12

AQRNA-seq for Quantifying Small RNAs

Published on: February 2, 2024

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • RNA sequencing technology (RNA-Seq) allows for comprehensive RNA profiling.
  • Existing tools for non-coding RNA (ncRNA) detection may not fully utilize RNA-Seq data.
  • Accurate detection of small ncRNAs, including microRNAs (miRNAs) and piwi-interacting RNAs (piRNAs), is crucial.

Purpose of the Study:

  • To present NorahDesk, a novel, unbiased, and universally applicable method for small ncRNA detection from RNA-Seq data.
  • To improve the accuracy and scope of ncRNA annotation by leveraging RNA-Seq data's full information content.
  • To evaluate NorahDesk's performance, particularly for miRNAs and piRNAs, and compare it with existing tools.

Main Methods:

  • NorahDesk utilizes small RNA sequence data's coverage distribution.
  • Incorporates thermodynamic assessments of secondary structure for reliable prediction.
  • Applies the method to publicly available mouse RNA-Seq data from various tissues (brain, skeletal muscle, testis, ovary).

Main Results:

  • NorahDesk demonstrates effective prediction and annotation of ncRNA classes.
  • Compared to Dario and mirDeep2, NorahDesk produces longer transcripts with higher read coverage.
  • This enhanced performance makes NorahDesk particularly suitable for predicting both known and novel piRNAs.

Conclusions:

  • NorahDesk represents a significant advancement in small ncRNA detection from RNA-Seq data.
  • The method's ability to analyze coverage distribution and secondary structure enhances prediction accuracy.
  • NorahDesk is especially valuable for the discovery and characterization of piRNAs.