A Nested 2-Level Cross-Validation Ensemble Learning Pipeline Suggests a Negative Pressure Against Crosstalk snoRNA-mRNA Interactions in Saccharomyces cerevisiae

J Comput Biol. 2020 Mar;27(3):390-402. doi: 10.1089/cmb.2019.0464.

Abstract

The growing number of RNA-mediated regulation mechanisms identified in the past decades suggests a widespread impact of RNA-RNA interactions. The efficiency of the regulation relies on highly specific and coordinated interactions while simultaneously repressing the formation of opportunistic complexes. However, the analysis of RNA interactomes is highly challenging because of the large number of potential partners, discrepancy of the size of RNA families, and the inherent noise in interaction predictions. We designed a recursive two-step cross-validation pipeline to capture the specificity of noncoding RNA (ncRNA) messenger RNA (mRNA) interactomes. Our method has been designed to detect significant loss or gain of specificity between ncRNA-mRNA interaction profiles. Applied to small nucleolar RNA-mRNA in Saccharomyces cerevisiae, our results suggest the existence of a repression of ncRNA affinities with mRNAs and thus the existence of an evolutionary pressure leveling down such interactions.

Keywords: RNA interactome; ensemble learning; leveling pressure.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology / methods*
  • Databases, Genetic
  • Gene Expression Regulation, Fungal
  • Gene Regulatory Networks
  • RNA, Fungal / metabolism
  • RNA, Messenger / metabolism*
  • RNA, Untranslated / metabolism*
  • Saccharomyces cerevisiae / genetics*

Substances

  • RNA, Fungal
  • RNA, Messenger
  • RNA, Untranslated