Computational identification of signals predictive for nuclear RNA exosome degradation pathway targeting.

ABSTRACT: The RNA exosome degrades transcripts in the nucleoplasm of mammalian cells. Its substrate specificity is mediated by two adaptors: the 'nuclear exosome targeting (NEXT)' complex and the 'poly(A) exosome targeting (PAXT)' connection. Previous studies have revealed some DNA/RNA elements that differ between the two pathways, but how informative these features are for distinguishing pathway targeting, or whether additional genomic features that are informative for such classifications exist, is unknown. Here, we leverage the wealth of available genomic data and develop machine learning models that predict exosome targets and subsequently rank the features the models use by their predictive power. As expected, features around transcript end sites were most predictive; specifically, the lack of

SUBMITTER: Wu M 

PROVIDER: S-EPMC9477074 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature