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Characterization and Identification of MicroRNA Core Promoters in Four Model Species

Overview of attention for article published in PLoS Computational Biology, March 2007
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Title
Characterization and Identification of MicroRNA Core Promoters in Four Model Species
Published in
PLoS Computational Biology, March 2007
DOI 10.1371/journal.pcbi.0030037
Pubmed ID
Authors

Xuefeng Zhou, Jianhua Ruan, Guandong Wang, Weixiong Zhang

Abstract

MicroRNAs are short, noncoding RNAs that play important roles in post-transcriptional gene regulation. Although many functions of microRNAs in plants and animals have been revealed in recent years, the transcriptional mechanism of microRNA genes is not well-understood. To elucidate the transcriptional regulation of microRNA genes, we study and characterize, in a genome scale, the promoters of intergenic microRNA genes in Caenorhabditis elegans, Homo sapiens, Arabidopsis thaliana, and Oryza sativa. We show that most known microRNA genes in these four species have the same type of promoters as protein-coding genes have. To further characterize the promoters of microRNA genes, we developed a novel promoter prediction method, called common query voting (CoVote), which is more effective than available promoter prediction methods. Using this new method, we identify putative core promoters of most known microRNA genes in the four model species. Moreover, we characterize the promoters of microRNA genes in these four species. We discover many significant, characteristic sequence motifs in these core promoters, several of which match or resemble the known cis-acting elements for transcription initiation. Among these motifs, some are conserved across different species while some are specific to microRNA genes of individual species.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 328 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 3%
United Kingdom 6 2%
Germany 3 <1%
Greece 2 <1%
Norway 2 <1%
India 2 <1%
Mexico 2 <1%
Sweden 1 <1%
Brazil 1 <1%
Other 9 3%
Unknown 291 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 91 28%
Researcher 75 23%
Student > Master 40 12%
Professor > Associate Professor 30 9%
Student > Bachelor 21 6%
Other 47 14%
Unknown 24 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 191 58%
Biochemistry, Genetics and Molecular Biology 45 14%
Medicine and Dentistry 20 6%
Computer Science 13 4%
Neuroscience 6 2%
Other 20 6%
Unknown 33 10%