Seminars and Symposia
IDAC Seminar, 3 June 2016
|Secretariat, Alumni Association, IDAC|
|Date||Friday,3 June 2016, 16:00～|
|Room||Seminar-shitsu 1, IDAC Research building 7F|
|Title||Weighted Enrichment Method for Prediction of Transcription Regulators from Transcriptome data|
|Speaker||Eiryo Kawakami, Ph.D.|
|Affiliation||Center for Integrative Medical Sciences, RIKEN|
|Person-in-charge||Yohei Hayashi（Cell Resource Center for Biomedical Research・ext.8572）|
|Abstract||Most of cellular properties such as metabolism, cell cycle, differentiation, and stress response result from the gene expression. The regulation of the gene expression is mainly made by transcription factors (TFs), which bind to specific DNA sequences controlling the rate of transcription. Thus, identifying responsible TFs is an important first step in understanding regulatory mechanisms of both healthy and pathogenic cellular states.
In spite of extensive research on TFs, it is still difficult to comprehensively ascertain the activation state of each TF because of rather complicated layers of post-translational regulation. On the other hand, we can now measure genome-wide mRNA expression level using microarray or RNA-seq technology. Therefore, one of the most promising computational approaches is to estimate activation of TFs from high-throughput transcriptome data.
For the estimation, we constructed a gene regulatory network (GRN) utilizing over 3500 ChIP-seq and ChIP on chip data. The GRN contains probability of regulation that has not been considered in existing GRNs based on the TF binding motif. In addition, we developed a novel framework for Gene Set Enrichment Analysis, namely weighted Parametric Gene Set Analysis (wPGSA), considering the probabilistic relationships in the GRN, which enables us to estimate activation states of over 450 TFs with high accuracy from transcriptome data.
In this talk, we would like to overview the wPGSA framework for utilizing vast amount of public data. Application and validation of the method also will be discussed.
Eiryo Kawakami, Shinji Nakaoka, Tazro Ohta, and Hiroaki Kitano, (2016), Nucleic Acids Research, doi: 10.1093/nar/gkw355