TITLE

Bioinformatic discovery of microRNA precursors from human ESTs and introns

AUTHOR(S)
Li, Sung-Chou; Pan, Chao-Yu; Lin, Wen-chang
PUB. DATE
January 2006
SOURCE
BMC Genomics;2006, Vol. 7, p164
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Background: MicroRNAs (miRNAs) function in many physiological processes, and their discovery is beneficial for further studying their physiological functions. However, many of the miRNAs predicted from genomic sequences have not been experimentally validated to be authentic expressed RNA transcripts, thereby decreasing the reliability of miRNA discovery. To overcome this problem, we examined expressed transcripts - ESTs and intronic sequences - to identify novel miRNAs as well as their target genes. Results: To facilitate our approach, we developed our scanning method using criteria based on the features of 207 known human pre-miRNAs to discriminate miRNAs from random sequences. We identified 208 candidate hairpins in human ESTs and human reference gene intronic sequences, 52 of which are known pre-miRNAs. The discovery pipeline performance was further assessed using 130 newly updated pre-miRNA and randomly selected sequences. We achieved sensitivity of 85% (110/130) and overall specificity of 49.7% using this method. Because miRNAs are evolutionarily conserved regulators of gene expression, it is expected that their host genes and target genes should have respective phylogenetic orthologs. Our results confirmed that, in certain mammals, the host genes carrying the same miRNAs are orthologs, as previously reported. Moreover, this observation is also the case for some of the miRNA target genes. Conclusion: We have predicted 208 human pre-miRNA candidates and over 10,000 putative human target genes. Using sequence information from ESTs and introns ensures that the predicted pre-miRNA candidates are expressed and the combined expression transcription information from ESTs and introns makes our prediction results more decisive with regard to expressed premiRNAs.
ACCESSION #
28858676

 

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