A generic, cost-effective and scalable cell lineage analysis platform
- Tamir Biezuner1,
- Adam Spiro1,
- Ofir Raz1,
- Shiran Amir1,
- Lilach Milo1,
- Rivka Adar1,
- Noa Chapal-Ilani1,
- Veronika Berman1,
- Yael Fried1,
- Elena Ainbinder1,
- Galit Cohen1,
- Haim M. Barr1,
- Ruth Halaban2 and
- Ehud Shapiro1,3
- ↵* Corresponding author; email: ehud.shapiro{at}weizmann.ac.il
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 towards large-scale human cell lineage discovery.
- Received December 6, 2015.
- Accepted August 11, 2016.
- Published by Cold Spring Harbor Laboratory Press
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/.
