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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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Cellular needs and conditions vary from cell to cell and change within individual cells over time. For example, the required enzymes and energetic demands of stomach cells are different from those of fat storage cells, skin cells, blood cells, and nerve cells. Furthermore, a digestive cell works much harder to process and break down nutrients during the time that closely follows a meal compared with many hours after a meal. As these cellular demands and conditions vary, so do the amounts and...
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Related Experiment Video

Updated: Jul 1, 2025

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics
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Prioritizing Maize Metabolic Gene Regulators through Multi-Omic Network Integration.

Fabio Gomez-Cano, Jonas Rodriguez, Peng Zhou

    Biorxiv : the Preprint Server for Biology
    |March 11, 2024
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    Summary
    This summary is machine-generated.

    This study integrates multiple data types to build transcription factor (TF)-target networks in plants. This approach reveals novel TF functions and aids in understanding gene regulation for improved crop traits.

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    Area of Science:

    • Plant systems biology
    • Genomics
    • Molecular biology

    Background:

    • Gene regulatory networks control plant phenotypic traits through transcription factor (TF) and target gene interactions.
    • Understanding these networks is crucial for plant systems biology and crop improvement.

    Purpose of the Study:

    • To construct comprehensive TF-target networks by integrating diverse biological datasets.
    • To functionally annotate TFs and identify novel regulatory roles in plant biological processes.

    Main Methods:

    • Integrated 46 co-expression networks, 283 protein-DNA interaction (PDI) assays, and 16 million SNPs for expression quantitative trait loci (eQTL) analysis.
    • Generated four types of TF-target networks: co-expression, PDI, trans-eQTL, and cis-eQTL combined with PDIs.
    • Employed three network integration strategies and evaluated them using TF loss-of-function mutants and random network analyses.

    Main Results:

    • Successfully constructed integrated TF-target networks by analyzing approximately 4.6 million interactions.
    • Identified transcriptional regulators for multiple biological processes in plants.
    • Discovered potential functionally redundant TF paralogs using network topology.
    • Validated known TF functions and uncovered novel ones, providing insights for future research.

    Conclusions:

    • The multi-omic data integration approach provides a robust framework for dissecting plant gene regulatory networks.
    • This methodology can be applied to maize and other plant systems for a deeper understanding of gene function and regulation.
    • Findings offer valuable information for designing future experiments and potentially improving crop traits.