Elucidating the 3D Genome Landscape

2023 Fiscal Year Final Research Report

• Project/Area Number: 17K15050
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: System genome science
• Research Institution: Kochi University (2023); The University of Tokyo (2018-2022); Hiroshima University (2017)
• Principal Investigator: Sugawara Takeshi 高知大学, データサイエンスセンター, 特任講師 (60713005)
• Project Period (FY): 2017-04-01 – 2024-03-31
• Keywords: ゲノム構造変化 / 数理モデル / データ駆動

Outline of Final Research Achievements

The initial plan aimed to quantify genome structural landscapes using a data-driven modeling approach with bulk Hi-C data, and to comprehensively describe genome structural changes accompanying cell cycle and cell differentiation. However, due to difficulties in sampling, the methodological direction was reconsidered. The newly proposed method utilizes single-cell Hi-C data and generative models to visualize genome 3D structural changes dependent on the cell cycle in detail. This approach compensates for the scarcity of data and uniquely extracts dynamic information from static data. Consequently, this development has advanced genome structure estimation to a new phase, and the progress was presented at academic conferences. In the future, the method is planned to be applied to the analysis of genome structural transitions during cell differentiation, indicating potential expansion into new research areas.

Free Research Field

ゲノム生物学、生物物理学

Academic Significance and Societal Importance of the Research Achievements

本研究は、Hi-Cデータ駆動型モデリング手法を用いてゲノム構造地形を定量化し、細胞状態変化に伴うゲノム構造変化を統一的に記述する点で学術的意義がある。細胞周期や細胞分化に伴うゲノム構造変化の数理的枠組みを細胞集団データから提案することを目指したが、サンプリングの困難さから軌道修正を行った。新提案手法は、単一細胞データと生成モデルを用いてゲノム3次元構造変化を詳細に可視化し、データ数の少なさを生成モデルで補う点に萌芽性があり、静的データから動的情報を抽出する手法にも独創性がある。この手法は他の単一細胞データ解析にも応用可能で、遺伝子動態やゲノム構造の多様性の解析に貢献し、社会的意義も大きい。