ArticlePLoS computational biology2014
A digital framework to build, visualize and analyze a gene expression atlas with cellular resolution in zebrafish early embryogenesis.
Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Unsupervised spatiotemporal classification of deformation patterns of embryonic tissues matches their fate map.iScience · 2025Article
- A deep learning framework for quantitative analysis of actin microridges.NPJ systems biology and applications · 2023Article
- Article
- Dynamics ofProceedings of the National Academy of Sciences of the United States of America · 2022Article
- Fishing forward and reverse: Advances in zebrafish phenomics.Mechanisms of development · 2018Review
- Synthesizing developmental trajectories.PLoS computational biology · 2017Article
- A cell-based computational model of early embryogenesis coupling mechanical behaviour and gene regulation.Nature communications · 2017Article
- An integrated modelling framework from cells to organism based on a cohort of digital embryos.Scientific reports · 2016Article
- Object-based representation and analysis of light and electron microscopic volume data using Blender.BMC bioinformatics · 2015Article
- Shaped singular spectrum analysis for quantifying gene expression, with application to the early Drosophila embryo.BioMed research international · 2015Article
- Shaped 3D singular spectrum analysis for quantifying gene expression, with application to the early zebrafish embryo.BioMed research international · 2015Article
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Authors and funding
12 authors.
Funding
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Abstract
A gene expression atlas is an essential resource to quantify and understand the multiscale processes of embryogenesis in time and space. The automated reconstruction of a prototypic 4D atlas for vertebrate early embryos, using multicolor fluorescence in situ hybridization with nuclear counterstain, requires dedicated computational strategies. To this goal, we designed an original methodological framework implemented in a software tool called Match-IT. With only minimal human supervision, our system is able to gather gene expression patterns observed in different analyzed embryos with phenotypic variability and map them onto a series of common 3D templates over time, creating a 4D atlas. This framework was used to construct an atlas composed of 6 gene expression templates from a cohort of zebrafish early embryos spanning 6 developmental stages from 4 to 6.3 hpf (hours post fertilization). They included 53 specimens, 181,415 detected cell nuclei and the segmentation of 98 gene expression patterns observed in 3D for 9 different genes. In addition, an interactive visualization software, Atlas-IT, was developed to inspect, supervise and analyze the atlas. Match-IT and Atlas-IT, including user manuals, representative datasets and video tutorials, are publicly and freely available online. We also propose computational methods and tools for the quantitative assessment of the gene expression templates at the cellular scale, with the identification, visualization and analysis of coexpression patterns, synexpression groups and their dynamics through developmental stages.
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