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What is Gene Expression?01:42

What is Gene Expression?

197.2K
Overview
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
Genetic Information Flows from DNA to RNA to Protein
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...
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What is Gene Expression?01:36

What is Gene Expression?

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A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is comprised  of nucleotides and proteins are comprised of amino acids, a mediator is required to convert the information encoded in DNA into proteins. This mediator is the messenger RNA (mRNA). mRNA copies the blueprint from DNA by a process called transcription. In eukaryotes, transcription occurs in the nucleus by complementary base-pairing with the DNA template. The mRNA is then...
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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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Chromatin Position Affects Gene Expression02:35

Chromatin Position Affects Gene Expression

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Chromatin is the massive complex of DNA and proteins packaged inside the nucleus. The complexity of chromatin folding and how it is packaged inside the nucleus greatly influences  access to genetic information. Generally, the nucleus' periphery is considered transcriptionally repressive, while the cell's interior is considered a transcriptionally active area. 
Topologically Associated Domains (TADs)
The 3-dimensional positioning of chromatin in the nucleus influences the...
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Cell Specific Gene Expression01:58

Cell Specific Gene Expression

16.6K
Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
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mRNA Stability and Gene Expression02:51

mRNA Stability and Gene Expression

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The structure and stability of mRNA molecules regulates gene expression, as mRNAs are a key step in the pathway from gene to protein. In eukaryotes, the half-life of mRNA varies from a few minutes up to several days. mRNA stability is essential in growth and development. The absence of the proteins regulating its stability, such as tristetraprolin in mice, can cause systemic issues, including bone marrow overgrowth, inflammation, and autoimmunity.
Cis-acting Elements involved in mRNA stability
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Related Experiment Video

Updated: Feb 16, 2026

RNA-Seq Analysis of Differential Gene Expression in Electroporated Chick Embryonic Spinal Cord
11:13

RNA-Seq Analysis of Differential Gene Expression in Electroporated Chick Embryonic Spinal Cord

Published on: November 1, 2014

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CORNAS: coverage-dependent RNA-Seq analysis of gene expression data without biological replicates.

Joel Z B Low1,2, Tsung Fei Khang3,4, Martti T Tammi1

  • 1Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, 50603, Malaysia.

BMC Bioinformatics
|January 4, 2018
PubMed
Summary
This summary is machine-generated.

A new Bayesian method uses RNA sequencing coverage to estimate true gene counts, improving differential gene expression analysis in RNA-Seq experiments with limited data.

Keywords:
Bayesian statisticsDifferential gene expressionIlluminaRNA-SeqSequencing coverageUnreplicated experiments

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Current RNA-Seq analysis methods assume normalized counts represent true gene counts, ignoring potential variations.
  • Existing statistical models for RNA sequencing (RNA-Seq) do not explicitly incorporate sequencing coverage information.
  • This can lead to inaccuracies in identifying differentially expressed genes, especially with limited replicates or low coverage.

Purpose of the Study:

  • To develop a novel statistical method for RNA-Seq analysis that incorporates sequencing coverage information.
  • To improve the accuracy of estimating true gene counts from observed RNA-Seq data.
  • To enhance differential gene expression analysis in challenging experimental conditions.

Main Methods:

  • Developed a fast Bayesian approach to estimate the posterior distribution of true gene counts.
  • Utilized sequencing coverage data, derived from RNA sample concentration, as a key parameter.
  • Integrated this coverage parameter into a differential gene expression analysis pipeline.

Main Results:

  • The new Bayesian method demonstrates superior or comparable performance to existing tools like NOISeq and GFOLD.
  • Simulations and experiments with real unreplicated data validate the method's effectiveness.
  • Successfully incorporated sequencing coverage into RNA-Seq differential expression analysis.

Conclusions:

  • The developed method effectively addresses analytical bottlenecks in RNA-Seq experiments with few replicates and low sequencing coverage.
  • The CORNAS (Coverage-dependent RNA-Seq) software implements this novel approach.
  • This method offers a valuable tool for more accurate gene expression analysis in RNA-Seq studies.