keyword in microRNA or target gene :
 
     
 
Introduction
     
    What is miRNAMap?
 
MicroRNAs (miRNAs) are small noncoding RNA molecules, which are capable of negatively regulating gene expression to control many cellular mechanisms. In this work, we develop a resource, miRNAMap 2.0, to collect experimental verified microRNAs and experimental verified miRNA target genes in human, mouse, rat, and other metazoan genomes. In addition to known miRNA targets, three computational tools previously developed, such as miRanda, RNAhybrid and TargetScan, were applied for identifying miRNA targets in 3' -UTR of genes. In order to reduce the false positive prediction of miRNA targets, several criteria are supported for filtering the putative miRNA targets. Furthermore, miRNA expression profiles can provide valuable clues for investigating the properties of miRNAs, such tissue specificity and differential expression in cancer/normal cell. Therefore, we performed the Q-PCR experiments for monitoring the expression profiles of 224 human miRNAs in eighteen major normal tissues in human . The cross-reference between the miRNA expression profiles and the expression profiles of its target genes can provide effective viewpoint to understand the regulatory functions of the miRNA. Besides, the interface is also redesigned and enhanced. The miRNAMap release 2.0 is now available at http://miRNAMap.mbc.nctu.edu.tw/.
     
    The advancements and new features miRNAMap 2.0.
   
Features miRNAMap 1.0 miRNAMap 2.0
Known miRNAs miRBase (version 6.0) miRBase (version 9.2)
Supported species human, mouse, rat and dog 2 insects, 9 vertebrates and 1 worm
Experimental miRNA targets Surveying literature TarBase and Surveying literature
miRNA expression profiling Lu. et al miRNA profiling in human Lu. et al miRNA profiling in human
Q-PCR miRNA profiling in human
Expression profiles of miRNA targets
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NCBI-GEO-GDS596 (76 human tissues)
miRNA target prediction tools miRanda miRanda, RNAhybrid and TargetScan
Criteria for filtering the predicted miRNA targets
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Criterion 1: predicted by at least two tools
Criterion 2: target genes contained multiple sites
Criterion 3: target site is accessible
Accessible region of miRNA target sites
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Sfold
Tissue specificity of human miRNAs
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Q-PCR miRNA profiling (18 human tissues)
       
 
Developers
     
 
  Dr.Hsien-Da Huang
Department of Biological Science and Technology, Institute of Bioinformatics National Chiao-Tung University, HsinChu, Taiwan
 

Yi-Hsuan Chen
Molecular Medicine Research Center , Chang Gung University , Tao-Yuan 333, Taiwan

  Gian-Hung Chen
Molecular Medicine Research Center , Chang Gung University , Tao-Yuan 333, Taiwan
  Sheng-Da Hsu
Department of Biological Science and Technology, Institute of Bioinformatics National Chiao-Tung University, HsinChu, Taiwan
  Chia-Huei Chu
Department of Biological Science and Technology, Institute of Bioinformatics National Chiao-Tung University, HsinChu, Taiwan
  Shu-Jen Chen
Molecular Medicine Research Center , Chang Gung University , Tao-Yuan 333, Taiwan
  Hua-Chien Chen
Molecular Medicine Research Center , Chang Gung University , Tao-Yuan 333, Taiwan
  Paul Wei-Che Hsu
Department of Biological Science and Technology, Institute of Bioinformatics National Chiao-Tung University, HsinChu, Taiwan
  Yung-Hao Wong
Department of Biological Science and Technology, Institute of Bioinformatics National Chiao-Tung University, HsinChu, Taiwan
  Shu-Jen Chen
Molecular Medicine Research Center , Chang Gung University , Tao-Yuan 333, Taiwan
       
 
Softwares
 
   
 
Sfold
A web server for statistical folding and rational design of nucleic acids.

mfold

A web server for prediction RNA secondary structure.

miRanda

Finds potential target sites for miRNAs in genomic sequence.
TargetScanS
Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets.
RNAhybrid
Fast and effective prediction of microRNA/target duplexes.
MicroTar
microRNA target prediction from RNA duplexes.
       
 
Databases
     
 
Ensembl
A software system which produces and maintains automatic annotation on selected eukaryotic genomes.

UCSC
Genome Browser

A site contains the reference sequence and working draft assemblies for a large collection of genomes.
GEO
Gene Expression Omnibus, a gene expression/molecular abundance repository supporting MIAME compliant data submissions, and a curated, online resource for gene expression data browsing, query and retrieval.
RefSeq
A site provide a comprehensive, integrated, non-redundant set of sequences, including genomic DNA, transcript (RNA), and protein products, for major research organisms.
HGNC
Giving unique and meaningful names to every human gene.
MGI
Mouse Genome Informatics (MGI) provides integrated access to data on the genetics, genomics, and biology of the laboratory mouse.
miRBase
A new home for microRNA data, incorporating the database and gene naming roles previously provided by the miRNA Registry, and including the new miRBase Target database.
       
 
References
 
1.
Hsu, P.W., Huang, H.D., Hsu, S.D., Lin, L.Z., Tsou, A.P., Tseng, C.P., Stadler, P.F., Washietl, S. and Hofacker, I.L. (2006) miRNAMap: genomic maps of microRNA genes and their target genes in mammalian genomes. Nucleic Acids Res, 34, D135-139.
2.
Ding, Y. , Chan, C.Y. and Lawrence, C.E. (2004) S fold web server for statistical folding and rational design of nucleic acids. Nucleic Acids Res. 32 Web Server issue , W135-W141.
3.
John, B., Enright, A.J., Aravin, A., Tuschl, T., Sander, C. and Marks, D.S. (2004) Human MicroRNA targets. PLoS Biol, 2, e363.
4.
Lewis, C. Burge, D. Bartel. (2005) Conserved Seed Pairing, Often Flanked by Adenosines, Indicates that Thousands of Human Genes are MicroRNA Targets. Cell, Volume 120, Issue 1, Pages 15-20 B.
5.
Rehmsmeier, M., Steffen, P., Hochsmann, M. and Giegerich, R. (2004) Fast and effective prediction of microRNA/target duplexes. Rna, 10, 1507-1517.
6.
Rahul Thadani and Martti T Tammi. (2006) MicroTar: predicting microRNA targets from RNA duplexes. BMC Bioinformatics, 7 (Suppl 5) : S20
7. Hubbard, T., Andrews, D., Caccamo, M., Cameron, G., Chen, Y., Clamp, M., Clarke, L., Coates, G., Cox, T., Cunningham, F. et al. (2005) Ensembl 2005. Nucleic Acids Res, 33, D447-453.
8.
Karolchik, D., Baertsch, R., Diekhans, M., Furey, T.S., Hinrichs, A., Lu, Y.T., Roskin, K.M., Schwartz, M., Sugnet, C.W., Thomas, D.J. et al. (2003) The UCSC Genome Browser Database. Nucleic Acids Res, 31, 51-54.
9. Tanya Barrett, Dennis B. Troup, Stephen E. Wilhite, Pierre Ledoux, Dmitry Rudnev, Carlos Evangelista, Irene F. Kim, Alexandra Soboleva, Maxim Tomashevsky and Ron Edgar. (2006) NCBI GEO: mining tens of millions of expression profilesˇXdatabase and tools update. Nucleic Acids Research, 2007, Vol. 35, Database issue D760-D765.
10. Pruitt KD, Tatusova, T, Maglott DR. (2005) NCBI Reference Sequence (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins.
Nucleic Acids Res, Jan 1;33(1):D501-D504.
11. Hum Genet. (2001) The HUGO Gene Nomenclature Committee (HGNC). Dec, 109(6):678-80.
12. Toxicol Pathol. Mouse genome informatics (MGI) resources for pathology and toxicology. 2007;35(3):456-7.
13. Griffiths-Jones, S., Grocock, R.J., van Dongen, S., Bateman, A. and Enright, A.J. (2006) miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res, 34, D140-144.
       

Department of Biological Science and Technology,
Institute of Bioinformatics National Chiao Tung University, Hsinchu, Taiwan
Contact with: bryan@mail.NCTU.edu.tw