Learning the RNA World by structural covariations

Many apparently noncoding RNA transcripts are observed for which we don't know the purpose of their existence. Identifying an RNA transcript with a conserved structure is important support for a possible structural RNA function for that transcript. This question is different from structure prediction because any RNA folds into some structure, regardless of whether that structure has any conserved biological function. We have produced a statistical test to assess when an RNA alignment presents evidence of a conserved RNA structure. The program named R-scape (RNA structural covariations above phylogenetic expectation) is computationally lightweight (which is unusual for structural RNA applications). And here is R-scape's webserver.

As more noncoding RNA transcripts are investigated, a picture emerges in which a substantial number of transcripts appear to perform roles where neither the actual RNA sequence nor any RNA structure are relevant, instead depending just on the fact that they are transcribed. Others appear to encode some small previously unidentified peptides. In this context, identifying a (possibly scarce) subset of transcripts with a conserved RNA structure becomes a special pursuit that could unveil new RNA functions in a background of other noncoding RNA transcripts.

This laboratory develops computational probabilistic models to understand RNA structure. We also work with models of sequence evolution in order to bring phylogenetic power to the question of remote homology recognition.

Reach to us

Department of Molecular & Cellular Biology
Northwest Building
52 Oxford Street
Harvard University
Cambridge MA 02138, USA

R-scape

RNA Structural Covariations Above Phylogenetic Expectation.

Current version:

R-scape_v2.0.0.k (August 2022).

New From The Lab

New version to appear in IUBMB Life:
Thirteen dubious ways to detect conserved structural RNAs . W Gao, A Yang, E Rivas, September 2022
Work with (then undergraduates) William Gao and Ann Yang where we investigate and critically discuss the practice of inferring conserved RNA structure by comparative sequence analysis. We provide new methods on how to approach and decide which of the numerous long non-coding RNAs (lncRNAs) have biologically relevant structures.
Fitness Functions for RNA Structure Design . M Ward, E Courtney, E Rivas, June 2022
Max Ward's work testing different fitness functions for RNA design. The probability of a structure given the sequence, the most effective fitness function for the RNA design problem.