Development of the next generation transcriptome analysis and its application

2021 Fiscal Year Final Research Report

• Project Area: Transomic Analysis of Metabolic Adaptation
• Project/Area Number: 17H06306
• Research Category: Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)
• Allocation Type: Single-year Grants
• Review Section: Biological Sciences
• Research Institution: The University of Tokyo
• Principal Investigator: Suzuki Yutaka 東京大学, 大学院新領域創成科学研究科, 教授 (40323646)
• Project Period (FY): 2017-06-30 – 2022-03-31
• Keywords: トランスクリプトーム / エピゲノム

Outline of Final Research Achievements

In this research, our research group has provided the next-generation sequence analysis platform, also including a series of template preparation platforms, and primary data analysis platforms to all research groups in this research area. At the same time, this research group has also independently developed and practiced the basic technology for elucidating the diversity of metabolic adaptation during drug response of cancer cells. With a particular focus on gene expression regulations, we attempted to increase the efficiency of transcriptome and epigenome analysis and systematically produce data on omics drug perturbation responses. An information analysis model was constructed across each omics hierarchy starting from the acquired data to understand the elastic response of the cancer cells in drug responses.

Free Research Field

ゲノム科学

Academic Significance and Societal Importance of the Research Achievements

本研究期間内に行った次世代シークエンスデータ産生支援は、特に公募班若手研究者との共同研究として成果を論文発表することができた。該当分野になじみのなかった特に若手研究者に対して、大規模オーミクスデータ産生/解析への参入を促すことができたと考えている。独自の課題であるがん細胞を対象とした多層オミクス解析について行ったトランスクリプトーム-エピゲノムネットワークにおける抗がん剤作用モジュールのカタログ化、その1細胞レベルへの計測の精密化を通じ、がん細胞薬剤応答の多様性の解明に向けて出発材料を創出することができたと考えている。