Computational Discovery of miR-TF Regulatory Modules in Human Genome Dang Hung Tran1,3, Kenji Satou1,2, Tu Bao Ho1, and Tho Hoan Pham1,3 1 Japan Advanced Institute of Science and Technology 2 Kanazawa University 3 Hanoi National University of Education Singapore  September 9-11, 2009

Outline Background Motivation Discover miR-TF modules Results and discussion Conclusion 平成31年2月22日

Gene regulation Conventional view by: Recent view by: Transcription factors (TF) Activate gene expression Depress gene expression Recent view by: Transcription factors Small RNAs (e.g. microRNAs) Depress gene expression 平成31年2月22日

What are microRNAs ? RNA world Recent concerning microRNAs Coding RNA Non-coding RNA Recent concerning Small non-coding RNAs microRNAs Class of small non-coding RNAs Bind to messenger RNAs Repress gene expression 平成31年2月22日

microRNA biogenesis 平成31年2月22日

Chen and Rajewsky Nature Reviews Genetics (2007) Research motivation Gene regulation Transcriptional level: by transcription factors (TF) Post-transcriptional level: by microRNAs (miRNA) How TFs and miRNAs function together? Investigate coordinated gene regulation by TFs and miRNAs may elucidate their functions. Chen and Rajewsky Nature Reviews Genetics (2007) We need to Identify regulatory modules that consist of miRNAs, Transcription Factor, and regulated genes (miR-TF module) 平成31年2月22日

Related works Detection of miRNA regulatory modules Tran et al. 2008, Joung et al. 2009, Liu et al. 2009 Concentrated on finding the relationship between miRNAs and their target genes Finding the relationships between TFs and miRNAs Cui et al. 2007, Shalgi et al. 2007, Zhou et al. 2008 Showed that miRNA mediated regulatory circuits are prevalent in the human genome But the combined roles of miRNAs and other factors in gene regulatory network still remains unanswered 平成31年2月22日

Problem Given Find TFs – genes binding information miRNAs – genes binding information Find miR-TF modules with biological meaning Each module consist of three components: TFs, miRNAs, and genes regulated by them 平成31年2月22日

Algorithm Going over all genes i For each i, search all subsets of miRNAs M’ For each M’, search all subsets of TFs T’ Find gene set G, bind by M’ and T’ If |G|>1 report modules and mark all the subsets of M’ and T’ Generally, the binding matrixes are relatively sparse and hence the computational complexity is reduced, therefore we are able to use an exhaustive searching algorithm to discover the optimal solutions within the given space 平成31年2月22日

Schematic description of the data set construction Experiment Databases miRNAs and TFs regulatory signatures from CRSD database CRSD integrates six well-known databases (e.g. UniGene, TRANSFAC, miRBASE) Dataset contains 267 miRNAs, 483 TFs, and 1253 regulated genes Performing algorithm Written in C++ Run on Linux operating system Schematic description of the data set construction 平成31年2月22日

Evaluation and findings (1/4) Tested binding data at a number of different confidence level (0.05, 0.01, 0.005, 0.001) Each module consists of three components The number modules found by our algorithm is as follows For further analysis, we selected the values of p1 and p2 equal to 0.01. (182 modules) 平成31年2月22日

Evaluation and findings (2/4) Some of miR-TF modules share a subset of miRNAs or TFs on regulation of the target genes For example: modules 66, 67, 68 Three modules share a common miRNA hsa-miR-125b Two of them share two miRNAs hsa-miR-125a and hsa-miR-125b Two of them have the same TF Zic3 etc. The coordinated regulation of target genes by miRNAs and TFs is more complicated Illustration of the three miR-TF modules (66, 67, 68) 平成31年2月22日

Evaluation and findings (3/4) It is hard to directly validate the miR-TF modules Using GO to validate modules with respect to biological processes The set of regulated genes and host genes of TFs in modules related to some specific GO terms 平成31年2月22日

Evaluation and findings (4/4) Found that some miRNAs and TFs in miR-TF modules have associations with cancer developments Several miRNAs related to lung and other human cancer 平成31年2月22日

Conclusion Proposed a comprehensive search method for discovering functional miR-TF modules Detected miR-TF modules Involved in specific biological processes (validation with GO) Contain miRNAs and TFs related to several types of cancer diseases Moreover, provided a view of combinatorial regulation of TFs and miRNAs 平成31年2月22日

Future work Algorithm does not consider the active behavioral characteristics of TFs Integrate some datasets of gene expression may help us to discover more coherent functional miR-TF modules 平成31年2月22日

THANK YOU ! 平成31年2月22日