Molecular basis for the recognition of low-frequency polyadenylation signals by mPSF

Lin Huang1, Hsu-Feng Chu1, Liang Tong1

  • 1Department of Biological Sciences, Columbia University, New York, NY 10027, United States.

Nucleic Acids Research
|September 10, 2025
PubMed

Insights

The study reveals how low-frequency polyadenylation signals are recognized by mammalian polyadenylation specificity factor (mPSF). Structural analysis shows distinct binding modes for these signals, explaining their lower occurrence in gene regulation.

Area of Science:

  • Molecular Biology
  • Genetics
  • Biochemistry

Background:

  • Pre-mRNA 3'-end processing relies on the polyadenylation signal (PAS), a hexanucleotide motif.
  • Mammalian polyadenylation specificity factor (mPSF) recognizes the PAS hexamer.
  • While AAUAAA and AUUAAA dominate, the recognition of low-frequency PAS hexamers remains unclear.

Purpose of the Study:

  • To investigate the molecular basis for the recognition of low-frequency polyadenylation signals by mPSF.
  • To determine the binding affinities and structural basis for mPSF interaction with various PAS hexamers.

Main Methods:

  • Determination of binding affinities (Kd values) for multiple PAS hexamers.
  • Cryo-electron microscopy (cryo-EM) to resolve structures of human mPSF bound to AAUAAU and AGUAAA at high resolution (3.1 Å and 2.5 Å).

Main Results:

  • Binding affinities generally inversely correlate with PAS hexamer frequency.
  • Observed good cleavage activity for low-frequency hexamers AAGAAA and AACAAA.
  • Cryo-EM structures revealed that low-frequency hexamers bind similarly to AAUAAA, with specific base modifications (e.g., disrupted Hoogsteen base pair in AAUAAU, conformational change in AGUAAA's G2 base) enabling interaction with CPSF30.

Conclusions:

  • The study elucidates the molecular mechanisms underlying the recognition of diverse polyadenylation signals by mPSF.
  • Structural insights explain how low-frequency PAS variants maintain functional interactions, contributing to the complexity of gene expression regulation.

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