Computational Challenges in miRNA Target Predictions: To Be or Not to Be a True Target?

被引:52
|
作者
Barbato, Christian
Arisi, Ivan [3 ]
Frizzo, Marcos E. [2 ]
Brandi, Rossella [3 ]
Da Sacco, Letizia [1 ]
Masotti, Andrea [1 ]
机构
[1] Bambino Gesu Pediat Hosp, Gene Express Microarrays Lab, I-00165 Rome, Italy
[2] Univ Fed Rio Grande do Sul, ICBS, Dept Ciencias Morfol, BR-90050170 Porto Alegre, RS, Brazil
[3] Fdn EBRI Rita Levi Montalcini, European Brain Res Inst, Neurogenom Facil, I-00143 Rome, Italy
关键词
MAMMALIAN MICRORNA TARGETS; MESSENGER-RNA EXPRESSION; IDENTIFICATION; GENE; CELLS; DIFFERENTIATION; BIOINFORMATICS; ARGONAUTE; PROTEINS; ANIMALS;
D O I
10.1155/2009/803069
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
All microRNA (miRNA) target-finder algorithms return lists of candidate target genes. How valid is that output in a biological setting? Transcriptome analysis has proven to be a useful approach to determine mRNA targets. Time course mRNA microarray experiments may reliably identify downregulated genes in response to overexpression of specific miRNA. The approach may miss some miRNA targets that are principally downregulated at the protein level. However, the high-throughput capacity of the assay makes it an effective tool to rapidly identify a large number of promising miRNA targets. Finally, loss and gain of function miRNA genetics have the clear potential of being critical in evaluating the biological relevance of thousands of target genes predicted by bioinformatic studies and to test the degree to which miRNA-mediated regulation of any "validated" target functionally matters to the animal or plant. Copyright (C) 2009 Christian Barbato et al.
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页数:9
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