Background

The development of multicellular organisms starts from single cells that undergo a coordinated process of cell division, morphogenesis and cell differentiation. Cell divisions constitute a genealogical tree, which can provide a framework for understanding how and when cell fate decisions are made. Cell lineage visualization has relied on following successive cell divisions of developing organisms under the microscope. Recent developments in imaging technologies have simplified this process, making it possible to image larger numbers of cells at a time. In parallel, genetic lineage recorders have been developed, which make it possible to reconstruct the entire lineage history of a complex organism. A complex goal, however, is to integrate the description of cell relationships with information about the spatial distribution and identities of the cells those divisions produce. It is not uncommon in biology, however, that as technologies are developed allowing further investigation of biological phenomena, the software to handle vast amounts of data lags behind. To bridge this gap, in their work, Salvador-Martinez et al (1) present CeLaVi (Cell Lineage Visualization tool), which is a web-based tool that allows users to navigate and explore cell lineage while also making it possible to visualize the spatial distribution, identities and properties of cells. Moreover, it allows 3D viewing and annotation of various cell qualities, including gene expression, cell type and tissue layer. They present this software as open-source, with example datasets and video tutorials http://www.celavi.pro.

Key findings and developments

Key developments.

Developments. CeLaVi is built using HTML5, Ajax, jQuery, CSS and the visualization libraries D3.js and Plotly.js. It was tested in multiple operating systems (Linux, MacOS, Windows) and browsers (Chrome, Firefox, Safari). The user interface consists of two interactive spaces: the lineage viewer, and the 3D viewer, which are tightly integrated. The users can explore various features including visualizing individual branches of the cell lineage tree, exploring the spatial distribution of cells in 3D, visualizing the spatial distribution of cell clones, selecting cells to display their lineage history, and visualizing the clonal relationship of any cell to others in 3D. To visualize a cell lineage tree and relate it to a 3D representation of the positions of each cell, two files are required: one containing the lineage tree, and one containing the 3D coordinates of the same cells.

The authors then describe in detail the two viewers, with the following key points:

Lineage tree viewer. CeLaVi’s lineage tree viewer can accommodate very large trees while retaining tree legibility. The viewer allows the user to focus on specific branches of the lineage tree by expanding, collapsing or pruning selected branches. Interacting with each cell in the lineage tree can provide specific cell information, for instance, cell ID, and total number of descendants.

3D viewer. CeLaVi’s 3D viewer renders cells as spheres, which users can interact with. It allows visualizing the degree of lineage relationship of all cells relative to one selected cell, showing the nested set of clones to which the cell belongs.

Information visualization. CeLaVi allows visualizing cell clones, and multiple clones originating at a given tree depth can be simultaneously visualized with unique colour coding. The software allows users to save selected cells or cell clones with customized annotations. The software allows two important pieces of further information to be uploaded and associated with the two viewer windows, namely, cell type information (a file containing cell annotations), and gene expression data, to see relative expression levels of a gene of interest.

Key findings.

The authors then include 4 example datasets in which they demonstrate CeLaVi’s features. These include a) C. elegans L1 larva including information from previous studies, on 357 cells viewed using confocal microscopy; b) Ciona intestinalis gastrula combining previously available 3D imaging and gene expression data; c) Parhyale hawaiensis limb, including previously available data from fluorescently-labeled embryos imaged with multi-view light-sheet microscopy at high spatiotemporal resolution over several days of embryogenesis; d) in silico organoid, from a simulation of morphogenesis.

Altogether, the authors present CeLaVi as the first interactive web-based visualization tool for cell lineages, with simple representations of that enables fast rendering in 3D, which is key for data exploration.

What I like about this paper

I like this preprint for three key things: first, that usually software lags behind technological advances that make certain types of experiments possible, which usually results in analysis being challenging for some time, until the relevant software tools catch up and allow it. I like that the authors bridge this gap here. The second reason is that I like the principles of open science and open access, and here the authors make their tool available to the scientific community. Not only that, but it is web-based and simple to use, translating as greater accessibility. Finally, the title is great!

References

1. Salvador-Martinez et al, CeLaVi: an interactive cell lineage visualization tool, bioRxiv, 2020.

 

doi: https://doi.org/10.1242/prelights.26642

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