A generic, cost-effective, and scalable cell lineage analysis platform
- Tamir Biezuner1,2,6,
- Adam Spiro1,2,6,
- Ofir Raz1,2,
- Shiran Amir1,2,
- Lilach Milo1,2,
- Rivka Adar1,2,
- Noa Chapal-Ilani1,2,
- Veronika Berman1,2,
- Yael Fried3,
- Elena Ainbinder3,
- Galit Cohen4,
- Haim M. Barr4,
- Ruth Halaban5 and
- Ehud Shapiro1,2
- 1Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 761001, Israel;
- 2Department of Biological Chemistry, Weizmann Institute of Science, Rehovot 761001, Israel;
- 3Department of Biological Services, Weizmann Institute of Science, Rehovot 761001, Israel;
- 4Maurice and Vivienne Wohl Institute for Drug Discovery, G-INCPM, Weizmann Institute of Science, Rehovot 761001, Israel;
- 5Department of Dermatology, Yale University School of Medicine, New Haven, Connecticut 06520-8059, USA
- Corresponding author: Ehud.Shapiro{at}weizmann.ac.il
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↵6 These authors are joint first authors and contributed equally to this work.
Abstract
Advances in single-cell genomics enable commensurate improvements in methods for uncovering lineage relations among individual cells. Current sequencing-based methods for cell lineage analysis depend on low-resolution bulk analysis or rely on extensive single-cell sequencing, which is not scalable and could be biased by functional dependencies. Here we show an integrated biochemical-computational platform for generic single-cell lineage analysis that is retrospective, cost-effective, and scalable. It consists of a biochemical-computational pipeline that inputs individual cells, produces targeted single-cell sequencing data, and uses it to generate a lineage tree of the input cells. We validated the platform by applying it to cells sampled from an ex vivo grown tree and analyzed its feasibility landscape by computer simulations. We conclude that the platform may serve as a generic tool for lineage analysis and thus pave the way toward large-scale human cell lineage discovery.
Footnotes
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[Supplemental material is available for this article.]
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Article published online before print. Article, supplemental material, and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.202903.115.
- Received December 6, 2015.
- Accepted August 11, 2016.
This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.
