RESEARCH INTERESTS
RNA is considered by many to be the primordial molecule of life. The major component of the ribosome—the most ancient organelle, which is shared between all living things—is ribosomal (r)RNA; which also forms the catalytic center necessary for protein production. The instructions needed for producing proteins is encoded within messenger (m)RNA, which is decoded by the ribosome by way of transfer (t)RNA. Beyond the classical RNAs involved in protein synthesis, a wide array of noncoding (nc)RNAs exist that mediate important biological processes: e.g. regulation of gene expression, mRNA splicing, post-transcriptional modification, chromatin structure, and more. In the vast majority of cases, we know almost nothing about the function of ncRNA (the transcriptional “dark matter”); however, function is inferred from differential expression/processing of that RNA (e.g. in diseases such as cancer) or from its evolutionary conservation.
An important feature of all functional RNAs, is the central role played by molecular structure. RNAs can fold back on themselves to form complex 2D (base paired) and 3D (atomic arrangement) shapes. These shapes govern how RNAs interact with other biomolecules (e.g. proteins, nucleic acids and small-molecules), form catalytic centers, determine molecular stability (e.g. lifetime) of RNA, and more. The major goal of the Moss Lab is to identify RNA sequences with a high propensity to form structure, deduce that structure and then determine the function of that RNA and the roles played by its structure. To do this we use tools from three different disciplines:
Bioinformatics: Extensive databases of 2D RNA structural motifs and their experimentally-measured free energies of folding are available. These data are incorporated into folding algorithms that can attempt to predict the native RNA 2D structure. Predicted structures and energies can be complemented by sequence analysis and other bioinformatic approaches to identify RNAs (or regions of RNA) that are likely to fold into functional structures. We are interested in adapting or improving approaches for structured RNA discovery; particularly in creating protocols that best make use of existing algorithms to exploit the unique features of our targets of interest.
Biochemistry: Prediction of an RNA structure based on the thermodynamics alone is expected to yield a structure that has roughly 70% of the base pairs predicted correctly. This is due to limitations in the model used and inaccuracies in the measured thermodynamics of small motifs. To overcome these limitations, it is possible to use biochemical structure probing, where small molecules that react with nucleotides in a structure-specific manner are used to constrain (or validate) predicted structures. We are particularly interested in coupling probing experiments to high-throughput sequencing readout of modifications sites to gain structural information for large transcripts or even transcriptomes.
Biology: RNA biology is an incredibly active field and one that is greatly facilitated by the presence of a wide array of modern tools (e.g. RNA-Seq, CRISPR/Cas9, etc.). We are applying these tools to understand the biological roles RNAs that we discover and the significance of their modeled structures. This can range from assessing their effects on gene expression, processing, identifying interactors within the cell (e.g. proteins) and more. Although a linear progression can be inferred from bioinformatics, to biochemistry and biology, each approach also informs the others and we tackle RNA holistically.
PROJECTS
Currently we have three major research areas:
Improving methods for RNA motif discovery and characterization - bioinformatics, biochemical data and sequence analyses are combined in the ScanFold pipeline to deduce functional structured RNAs in long sequences or whole genomes. These structured RNAs serve as the bases for generating biological hypotheses and, more recently, for therapeutic targeting: e.g. our recent work with the Matthew Disney lab on drugging SARS-CoV-2.
Analyses of functional structured RNAs in human genes - the methods developed above are being applied to uncover biologically and medically significant functional elements in human RNAs: e.g. our work on the MYC proto-oncogene.
Analyses of functional structured RNAs in pathogenic organisms - Our approaches are being applied to discover functional elements in pathogens, such as SARS-CoV-2, HIV, Zika, EBV and others.