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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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Regulation of Expression Occurs at Multiple Steps02:24

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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.
Transcription results in the generation of precursor (pre-mRNA) that consists of both exons and introns, which needs further processing before being translated to a...
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What is Gene Expression?01:42

What is Gene Expression?

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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
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Cis-regulatory Sequences02:02

Cis-regulatory Sequences

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RNA Polymerase II Accessory Proteins02:36

RNA Polymerase II Accessory Proteins

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Proteins that regulate transcription can do so either via direct contact with RNA Polymerase or through indirect interactions facilitated by adaptors, mediators, histone-modifying proteins, and nucleosome remodelers. Direct interactions to activate transcription is seen in bacteria as well as in some eukaryotic genes. In these cases, upstream activation sequences are adjacent to the promoters, and the activator proteins interact directly with the transcriptional machinery. For example, in...
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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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Related Experiment Video

Updated: May 24, 2025

Prediction and Validation of Gene Regulatory Elements Activated During Retinoic Acid Induced Embryonic Stem Cell Differentiation
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Learning to Discover Regulatory Elements for Gene Expression Prediction.

Xingyu Su, Haiyang Yu, Degui Zhi

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    Summary
    This summary is machine-generated.

    Seq2Exp accurately predicts gene expression by identifying key DNA regulatory elements. This new method enhances gene expression prediction and discovers influential genomic regions.

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    Area of Science:

    • Genomics
    • Computational Biology
    • Bioinformatics

    Background:

    • Predicting gene expression from DNA sequences is crucial for understanding gene regulation.
    • Identifying regulatory elements that control gene expression remains a significant challenge in genomics.

    Purpose of the Study:

    • To introduce Seq2Exp, a novel Sequence to Expression network designed to discover and extract regulatory elements driving gene expression.
    • To improve the accuracy of gene expression prediction by capturing causal relationships between DNA sequences, epigenomic signals, and regulatory elements.

    Main Methods:

    • Seq2Exp decomposes epigenomic signals and DNA sequences conditioned on causal active regulatory elements.
    • An information bottleneck with Beta distribution is employed to integrate effects and filter non-causal components.
    • The approach aims to explicitly model the causal link between regulatory elements and gene expression.

    Main Results:

    • Seq2Exp demonstrates superior performance over existing baseline methods in gene expression prediction tasks.
    • The method successfully identifies influential genomic regions, outperforming traditional peak detection methods like MACS3.
    • Experimental validation confirms the effectiveness of Seq2Exp in discovering regulatory elements.

    Conclusions:

    • Seq2Exp offers a powerful new tool for gene expression prediction and regulatory element discovery.
    • The model's ability to capture causal relationships enhances our understanding of gene regulation.
    • The source code is available, facilitating further research and application in the field.