RNASTAR: an RNA STructural Alignment Repository that provides insight into the evolution of natural and artificial RNAs.
Automated RNA alignment algorithms often fail to recapture the essential conserved sites that are critical for function. To assist in the refinement of these algorithms, we manually curated a set of 148 alignments with a total of 9600 unique sequences, in which each alignment was backed by at least one crystal or NMR structure. These alignments included both naturally and artificially selected molecules. We used principles of isostericity to improve the alignments from an average of 83%-94% isosteric base pairs. We expect that this alignment collection will assist in a wide range of benchmarking efforts and provide new insight into evolutionary principles governing change in RNA structural motifs. The improved alignments have been contributed to the Rfam database.
Department of Chemistry and Biochemistry, University of Colorado at Boulder, Boulder, Colorado 80309, USA.
Jeremy
J
Widmann
Jesse
J
Stombaugh
Daniel
D
McDonald
Jana
J
Chocholousova
Paul
P
Gardner
Matthew K
MK
Iyer
Zongzhi
Z
Liu
Catherine A
CA
Lozupone
John
J
Quinn
Sandra
S
Smit
Shandy
S
Wikman
Jesse R R
JR
Zaneveld
Rob
R
Knight
D000465:Algorithms; D001483:Base Sequence; D030561:Databases, Nucleic Acid; D019143:Evolution, Molecular; D009682:Magnetic Resonance Spectroscopy; D008958:Models, Molecular; D008969:Molecular Sequence Data; D009690:Nucleic Acid Conformation; D059372:Nucleotide Motifs; D012313:RNA / Q000737:chemistry*; D016415:Sequence Alignment
D012313:RNA