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Identification and Classification of Conserved RNA Secondary Structures in the Human Genome

Overview of attention for article published in PLoS Computational Biology, April 2006
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Title
Identification and Classification of Conserved RNA Secondary Structures in the Human Genome
Published in
PLoS Computational Biology, April 2006
DOI 10.1371/journal.pcbi.0020033
Pubmed ID
Authors

Jakob Skou Pedersen, Gill Bejerano, Adam Siepel, Kate Rosenbloom, Kerstin Lindblad-Toh, Eric S Lander, Jim Kent, Webb Miller, David Haussler

Abstract

The discoveries of microRNAs and riboswitches, among others, have shown functional RNAs to be biologically more important and genomically more prevalent than previously anticipated. We have developed a general comparative genomics method based on phylogenetic stochastic context-free grammars for identifying functional RNAs encoded in the human genome and used it to survey an eight-way genome-wide alignment of the human, chimpanzee, mouse, rat, dog, chicken, zebra-fish, and puffer-fish genomes for deeply conserved functional RNAs. At a loose threshold for acceptance, this search resulted in a set of 48,479 candidate RNA structures. This screen finds a large number of known functional RNAs, including 195 miRNAs, 62 histone 3'UTR stem loops, and various types of known genetic recoding elements. Among the highest-scoring new predictions are 169 new miRNA candidates, as well as new candidate selenocysteine insertion sites, RNA editing hairpins, RNAs involved in transcript auto regulation, and many folds that form singletons or small functional RNA families of completely unknown function. While the rate of false positives in the overall set is difficult to estimate and is likely to be substantial, the results nevertheless provide evidence for many new human functional RNAs and present specific predictions to facilitate their further characterization.

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Geographical breakdown

Country Count As %
United States 23 6%
United Kingdom 4 <1%
Germany 3 <1%
Denmark 3 <1%
France 2 <1%
Brazil 2 <1%
Korea, Republic of 1 <1%
Sweden 1 <1%
Colombia 1 <1%
Other 11 3%
Unknown 353 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 115 28%
Researcher 105 26%
Student > Master 38 9%
Student > Bachelor 27 7%
Professor > Associate Professor 24 6%
Other 56 14%
Unknown 39 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 212 52%
Biochemistry, Genetics and Molecular Biology 79 20%
Computer Science 31 8%
Immunology and Microbiology 7 2%
Medicine and Dentistry 7 2%
Other 25 6%
Unknown 43 11%