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タイトル: | eSPRESSO: topological clustering of single-cell transcriptomics data to reveal informative genes for spatio–temporal architectures of cells |
著者: | Mori, Tomoya Takase, Toshiro Lan, Kuan-Chun Yamane, Junko Alev, Cantas https://orcid.org/0000-0002-4879-8782 (unconfirmed) Kimura, Azuma Osafune, Kenji Yamashita, Jun K. Akutsu, Tatsuya https://orcid.org/0000-0001-9763-797X (unconfirmed) Kitano, Hiroaki Fujibuchi, Wataru |
著者名の別形: | 森, 智弥 山根, 順子 木村, 東 長船, 健二 山下, 潤 阿久津, 達也 藤渕, 航 |
キーワード: | Spatio–temporal tissue reconstruction Cellular organization Spatial discriminator gene Self-organizing map clustering Markov chain Monte Carlo optimization Developmental trajectory |
発行日: | 15-Jun-2023 |
出版者: | Springer Nature BMC |
誌名: | BMC Bioinformatics |
巻: | 24 |
論文番号: | 252 |
抄録: | [Background] Bioinformatics capability to analyze spatio–temporal dynamics of gene expression is essential in understanding animal development. Animal cells are spatially organized as functional tissues where cellular gene expression data contain information that governs morphogenesis during the developmental process. Although several computational tissue reconstruction methods using transcriptomics data have been proposed, those methods have been ineffective in arranging cells in their correct positions in tissues or organs unless spatial information is explicitly provided. [Results] This study demonstrates stochastic self-organizing map clustering with Markov chain Monte Carlo calculations for optimizing informative genes effectively reconstruct any spatio–temporal topology of cells from their transcriptome profiles with only a coarse topological guideline. The method, eSPRESSO (enhanced SPatial REconstruction by Stochastic Self-Organizing Map), provides a powerful in silico spatio–temporal tissue reconstruction capability, as confirmed by using human embryonic heart and mouse embryo, brain, embryonic heart, and liver lobule with generally high reproducibility (average max. accuracy = 92.0%), while revealing topologically informative genes, or spatial discriminator genes. Furthermore, eSPRESSO was used for temporal analysis of human pancreatic organoids to infer rational developmental trajectories with several candidate ‘temporal’ discriminator genes responsible for various cell type differentiations. [Conclusions] eSPRESSO provides a novel strategy for analyzing mechanisms underlying the spatio–temporal formation of cellular organizations. |
著作権等: | © The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. |
URI: | http://hdl.handle.net/2433/285249 |
DOI(出版社版): | 10.1186/s12859-023-05355-4 |
PubMed ID: | 37322439 |
出現コレクション: | 学術雑誌掲載論文等 |
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