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A computational modeling of pri-miRNA expression

Hansi Zheng1, Saidi Wang1, Xiaoman Li2

  • 1Department of Computer Science, University of Central Florida, Orlando, Florida, United States of America.

Plos One
|January 2, 2024
PubMed

Insights

This study models primary microRNA (miRNA) expression using associated messenger RNAs (mRNAs). Associated mRNAs, distinct from target mRNAs, reveal new insights into miRNA biogenesis and gene regulation.

Area of Science:

  • Molecular Biology
  • Genetics
  • Gene Regulation

Background:

  • MicroRNAs (miRNAs) are key regulators of gene expression.
  • Research predominantly focuses on mature miRNAs, leaving primary miRNA (pri-miRNA) expression poorly understood.
  • Understanding pri-miRNA expression is crucial for a comprehensive view of miRNA biogenesis.

Purpose of the Study:

  • To develop a model for predicting pri-miRNA expression.
  • To investigate the relationship between pri-miRNA expression and mRNA expression.
  • To identify novel regulatory mechanisms in gene expression.

Main Methods:

  • Expression data from 1829 diverse biological samples (primary cells, cell lines, tissues) were analyzed.
  • Statistical modeling was employed to correlate pri-miRNA expression with mRNA expression.
  • Associated mRNAs were identified and their functional enrichment analyzed.

Main Results:

  • Pri-miRNA expression can be accurately modeled by the expression of specific sets of associated mRNAs.
  • Associated mRNAs differ functionally and sequence-wise from the target mRNAs of the corresponding miRNA.
  • While most associated mRNAs are conserved across conditions, approximately 20% exhibit condition-specific expression patterns.

Conclusions:

  • The study introduces the concept of 'associated mRNAs' as predictors of pri-miRNA expression.
  • Associated mRNAs offer new functional insights and highlight condition-specific regulatory roles.
  • This work advances the understanding of miRNA biogenesis and broader gene transcriptional regulation.

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