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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...
Nonsense-mediated mRNA Decay02:27

Nonsense-mediated mRNA Decay

The Upf proteins that carry out nonsense-mediated decay (NMD) are found in all eukaryotic organisms, including humans. Each protein has an individual role, but they need to work in collaboration. Upf1 is an ATP-dependent RNA helicase that unwinds the RNA helix. Because Upf1 can unwind any RNA, Upf2 and Upf3 are required to help Upf1 discriminate between nonsense and normal mRNAs.
Usually, Upf3 binds to an Exon Junction Complex (EJC) at mRNA splice sites. If a ribosome fully translates the mRNA,...
Alternative RNA Splicing02:18

Alternative RNA Splicing

Alternative RNA splicing is the regulated splicing of exons and introns to produce different mature mRNAs from a single pre-mRNA. Unlike in constitutive splicing where a single gene produces a single type of mRNA, alternative splicing allows an organism to produce multiple proteins from a single gene and plays an important role in protein diversity.
There are five types of alternative RNA splicing that vary in the ways the pre-mRNA segments are removed or retained in the mature mRNA. The first...
lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA (lncRNA)...
RNA Splicing01:32

RNA Splicing

Splicing is the process by which eukaryotic RNA is edited before its translation into protein. The RNA strand transcribed from eukaryotic DNA is called the primary transcript. The primary transcripts that become mRNAs are called precursor messenger RNAs (pre-mRNAs). Eukaryotic pre-mRNA contains alternating sequences of exons and introns. Exons are nucleotide sequences that code for proteins, whereas introns are the non-coding regions. In RNA splicing, introns are removed and exons are bonded...

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Related Experiment Video

Updated: May 14, 2026

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis
12:44

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Published on: November 11, 2014

RNA-eXpress annotates novel transcript features in RNA-seq data.

Samuel C Forster1, Alexander M Finkel, Jodee A Gould

  • 1Centre for Innate Immunity and Infectious Diseases, Monash Institute of Medical Research, Monash University, Clayton, Victoria, Australia, 3168.

Bioinformatics (Oxford, England)
|February 12, 2013
PubMed
Summary
This summary is machine-generated.

RNA-eXpress is a new computational framework for transcriptional analysis. It identifies diverse genomic and transcriptional features from next-generation sequencing data, independent of existing annotations, offering a user-friendly solution.

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AQRNA-seq for Quantifying Small RNAs

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Last Updated: May 14, 2026

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis
12:44

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Published on: November 11, 2014

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
11:52

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

AQRNA-seq for Quantifying Small RNAs
05:12

AQRNA-seq for Quantifying Small RNAs

Published on: February 2, 2024

Area of Science:

  • Genomics
  • Transcriptomics
  • Bioinformatics

Background:

  • Next-generation sequencing (NGS) is a primary method for transcriptional analysis.
  • Existing computational tools often rely on prior transcript annotations, leading to bias and overlooking novel features.
  • Current methods may not capture all biologically relevant transcribed features, such as non-coding RNAs and RNA editing.

Purpose of the Study:

  • To develop a user-friendly, rapid, and computationally efficient framework for comprehensive feature annotation in transcriptional analysis.
  • To enable the identification of diverse genomic and transcriptional features independently of existing annotations.
  • To provide an accessible platform for both basic and advanced users in transcriptomic data analysis.

Main Methods:

  • The RNA-eXpress framework accepts mapped sequencing reads in Binary Alignment (BAM) format.
  • It processes data to identify transcripts and other genomic/transcriptional features.
  • The framework is designed for extensibility, allowing integration of new feature identification algorithms.

Main Results:

  • RNA-eXpress generates study-specific feature annotations in GTF format.
  • It provides comparison statistics, sequence extraction, and feature counts.
  • The framework successfully identifies transcripts and other features without relying on pre-existing gene annotations.

Conclusions:

  • RNA-eXpress offers a robust and accessible solution for comprehensive transcriptional feature annotation.
  • It overcomes limitations of annotation-dependent methods, enabling discovery of novel transcribed elements.
  • The framework's design facilitates broad adoption and future expansion for advanced transcriptomic research.