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Related Concept Videos

Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

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The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the...
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What is Gene Expression?01:36

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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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Regulation of Expression Occurs at Multiple Steps02:24

Regulation of Expression Occurs at Multiple Steps

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Gene expression can be regulated at almost every step from gene to protein. Transcription is the step that is most commonly regulated. This involves the binding of proteins to short regulatory sequences on the DNA. This association can either promote or inhibit the transcription of a gene associated with the respective sequence.
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Structure of a Gene01:30

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A gene is the fundamental unit of heredity. Every individual has two copies of each gene, one inherited from each parent. Although most people contain the same genes, there is a small fraction that is slightly different amongst people. A gene with a small difference in its sequence of DNA bases forms different alleles, contributing to different phenotypes.
However, only 1% of the DNA is composed of genes that encode proteins; the rest, 99% is non-coding DNA. This non-coding DNA performs...
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Ribosome Profiling02:24

Ribosome Profiling

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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
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Cap analysis of gene expression (CAGE) and noncoding regulatory elements.

Matteo Maurizio Guerrini1, Akiko Oguchi2, Akari Suzuki3

  • 1Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan. matteo.guerrini@riken.jp.

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Summary

Cap analysis of gene expression (CAGE) maps active human genomic regulatory elements. Integrating CAGE data with omics information enhances understanding of genetic variations and diseases.

Keywords:
CAGE sequencingEnhancers and promotersGWAS associationGenetic variationQTL integrationRNA CAP-trapping

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Area of Science:

  • Genomics
  • Molecular Biology
  • Immunology

Background:

  • Cap analysis of gene expression (CAGE) identifies RNA 5' ends.
  • High-throughput CAGE enables genome-wide identification of transcription start sites, promoters, and enhancers.

Purpose of the Study:

  • To review the utility of CAGE data for mapping active genomic regulatory elements.
  • To discuss the integration of CAGE data with omics and quantitative trait loci (QTL) data.
  • To explore the application of CAGE in understanding genetic variations' effects on human diseases.

Main Methods:

  • CAGE sequencing for transcript identification.
  • Genome-wide mapping of regulatory elements.
  • Integrative analysis with omics and QTL data.

Main Results:

  • CAGE provides cell type- and activation-specific maps of genomic regulatory elements.
  • CAGE data aids in interpreting the functional impact of genetic variations.
  • Immune cells are suitable for CAGE analysis due to accessibility.

Conclusions:

  • CAGE is instrumental for integrative genomic analyses.
  • CAGE enhances understanding of genome-wide association study (GWAS) variants outside annotated genes.
  • Integrating CAGE data can lead to improved disease insights and targeted therapies.