RAG: RNA-As-Graphs Database - Concepts, Analysis, and Features
Motivation: RNA's repertoire is growing rapidly with progress in RNA genomics. The
direct correlation between the conservation of RNA secondary structures with their
functional properties offers an opportunity for cataloging and classifying RNA secondary
motifs and, eventually, predicting novel motifs. Although several RNA databases have
been built, there are no comprehensive, quantitative schemes for cataloguing and
measuring the range and diversity of RNA's structural repertoire. Understanding RNAs
structural diversity is vital for identifying novel RNA structures.
Results: We describe an RNA-As-Graphs (RAG) Database that catalogues and ranks all
mathematically possible (including existing and candidate) RNA secondary motifs
derived from graphical enumeration results. As recently reported, we represent RNA
secondary structures as two-dimensional graphs, which specify the connectivity between
RNA secondary structural elements, such as loops, bulges, stems, and junctions. We
archive RNA tree motifs as "tree graphs" and other motif types, including pseudoknots,
as general graphs called "dual graphs". All RNA motifs are catalogued by graph vertex
number (equivalently, RNA sequence length) and ranked by topological complexity as
measured using the second smallest eigenvalue corresponding to the graph's (Laplacian)
matrix representation, a quantitative tool well known in graph analysis. RAG is an
intuitive but systematic cataloguing of all possible RNA secondary motifs; significantly,
it leads immediately to suggest candidates for novel RNA motifs. Exploring candidate
novel RNAs will likely stimulate searches for novel RNA motifs or submotifs, either
naturally occurring or produced synthetically in the laboratory via RNA design. The
RAG database can further be used to help identify structural and functional properties of
user-supplied RNA secondary structures. Thus, RAG's enumerated RNA motifs
contribute a useful resource for cataloguing, identifying and predicting RNA
motifs.
Availability: The database is accessible on the web at http://monod.biomath.nyu.edu/rna
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