Identification of Activated Transcription Factors from Microarray Gene Expression Data of Kampo Medicine-Treated Mice

Rui Yamaguchi[1] (ruiy@ims.u-tokyo.ac.jp)
Masahiro Yamamoto[2][3] (yamamoto_masahiro@mail.tsumura.co.jp)
Seiya Imoto[1] (imoto@ims.u-tokyo.ac.jp)
Masao Nagasaki[1] (masao@ims.u-tokyo.ac.jp)
Ryo Yoshida[4] (yoshidar@ism.ac.jp)
Kenji Tsuiji[2] (di055036@sc.itc.keio.ac.jp)
Atsushi Ishige[2] (ishige@sc.itc.keio.ac.jp)
Hiroaki Asou[3] (asou@tmig.or.jp)
Kenji Watanabe[2] (toyokeio@sc.itc.keio.ac.jp)
Satoru Miyano[1] (miyano@ims.u-tokyo.ac.jp)

[1]Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan
[2]Department of Kampo medicine, Keio University School of Medicine 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan
[3]Department of Neuro-glia cell biology, Tokyo Metropolitan Institute of Gerontology, 35-2 Sakaecho, Itabashi-ku, Tokyo 173-0015, Japan
[4]The Institute of Statistical Mathematics 4-6-7 Minami-Azabu, Minato-ku, Tokyo 106-8569, Japan

Abstract

We propose an approach to identify activated transcription factors from gene expression data using a statistical test. Applying the method, we can obtain a synoptic map of transcription factor activities which helps us to easily grasp the system’s behavior. As a real data analysis, we use a case-control experiment data of mice treated by a drug of Kampo medicine remedying degraded myelin sheath of nerves in central nervous system. Kampo medicine is Japanese traditional herbal medicine. Since the drug is not a single chemical compound but extracts of multiple medicinal herb, the effector sites are possibly multiple. Thus it is hard to understand the action mechanism and the system’s behavior by investigating only few highly expressed individual genes. Our method gives summary for the system’s behavior with various functional annotations, e.g. TFAs and gene ontology, and thus offer clues to understand it in more holistic manner.

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