Evolutionary exploitation of miRNA by phylogeny tree construction Presentation: Shaojun Tang* Shizhao Zhou** *Genetics Institute, College of Medicine, University of Florida **Computer information and science engineering, University of Florida Mentor: Tamer Kahveci

Outline Part I: What and why miRNA ? Part II: Gene regulation governed by transcription binding and miRNA targeting. Part III: Phylogeny tree construction of miRNA from different organism. Part IV: Multiply sequence alignment analysis to identify evolutionary conserved miRNAs.

Part I: What and why miRNA.  What is miRNA. Ribonucleic acid(RNA) molecules of about 21–23 nucleotides long, which regulation gene expression.

 Function of miRNA 1: Mature miRNA molecules are partially complementary to one or more message RNA (mRNA) molecules, which down-regulate gene expression 2: miRNA regulation of gene expression are associated with many disease and even cancer.

 Current research of miRNA 1: more than 700 miRNAs are identified in humans 2: miRNA regulation of gene transcription is important, but poorly understood and addressed. 3: miRNA can be a powerful tool in helping solve many disease or cancer in human.

Part II Gene regulation governed by transcription factor and miRNA  Transcription factor (sequence-specific DNA binding factor) Specific factors such as protein, that binds to particular DNA sequence and thereby controls the gene transcription from DNA to RNA. Transcription factor Gene Binding site

Methods 1: Database of transcription factor, human pathway genes, miRNA targets. 2: Calculate occurrence of transcription factor(the gene controlling factors) and downstream miRNA target sites. Pathway A TF-kTF-m TAR-iTF-k TAR-i TAR-j Gene-1 Gene-n PathwayTFTAR A k = 2 m=1 i=2 J=1 B

Results 871 pathways each associated with a group(20) of high- frequency transcription factor and miRNA targets. Important for study pathway gene regulation and disease.

Part III: Phylogeny tree construction  Data for analysis All available miRNA sequences from Human, mice, drosophila and virus.  Algorithm Dynamic program to generate scoring-matrix, follow by implementing UPGMA method to cluster miRNA sequences.  Methods Using two approaches for self-verification and more powerful evidence.

Method implementation-1 Forward-construction (low => high) Individual miRNA Cluster of miRNA Overlap miRNAs

Finding pairwise clusters of miRNA Cluster of miRNAs individual miRNAs Closely related miRNA cluster

Method implementation-2 Backward-construction miRNA clusters from UPGMA Individual miRNA

Data  Organisms KSHV Kaposi's sarcoma-associated herpesvirus EBV Epstein-Barr virus Dm Drosophila melanogaster Mm Mus_musculus Hs Homo_Sapiens  Groups of phylogeny tress 1: KSHV => Dm => Hs 2: Ebv => Dm => Mm

 Results of a Single group 1): Forward construction 3 tables from Edit(0, 1, 1) : (0, 1 3) : Percentage 2 ): Backward construction 3 tables from Edit(0, 1, 1) : (0, 1 3) : Percentage

Conclusion 1: The association of transcription factor binding site and miRNA targets given the pathway can provide useful information for research related to pathways. 2: The UPGMA construction of phylogeny tree may provide useful information for clustering evolutionary conserved genes in any given organism,. 3: while our two methods of miRNA pairwise construction among organism may shield light on future research in miRNA evolution, regulation and function.

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