2018 Fiscal Year Final Research Report
Development of informatics techniques for analysis developmental lineages
| Project/Area Number |
16H06155
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| Research Category |
Grant-in-Aid for Young Scientists (A)
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| Allocation Type | Single-year Grants |
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| Research Field |
System genome science
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| Research Institution | The University of Tokyo |
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Principal Investigator |
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| Research Collaborator |
YAMAGATA kazuo
FUNAHASHI akira
YOKOTA ryo
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Keywords | 着床前胚 / 4Dイメージング / 力学モデル / 系譜解析 / トラッキング / 深層学習 |
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| Outline of Final Research Achievements |
In this work, with the aim at quantitatively analyzing developmental lineages of preimplantation embryos, we developed a collection of techniques for 4D image segmentation and tracking, statistical analysis of cellular lineages, and a mechanical simulation of embryogenesis.
In the image analysis, we improved the method of identifying cells in the embryo and eventually proposed a deep convolutional network for the 3D image segmentation. In the statistical analysis of cellular lineages, we proposed a method to estimate the latent state of cells from the patterns of cell divisions in the lineages.
Lastly, we constructed a mechanical model to reproduce the developmental process of the embryo.By employing these techniques, we have investigated how the culture condition changes the division pattern and synchronization of divisions, how the structural change in a whole embryo is related with the cell cycles of the individual cells.
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| Free Research Field |
定量生物学
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| Academic Significance and Societal Importance of the Research Achievements |
本研究では、マウス着床前胚を対象として、バイオイメージングデータを元に発生系譜を解析する新たな情報技術を構築しました。これらの技術は、胚の発生過程に生じる様々な異変をより定量的にかつ統計的に解析することを可能とします。これらの技術を応用することで発生プロセスの原理を解明することは、胚の発生がどのように決定しているのか、また胚の発生速度の変化や発生の停止に培養状態などはどう影響しているのか、を客観的に評価することを可能とし、胚の健康を改善する培養条件の改良などに応用できると期待されます。
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