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09.06.16 Simons lab demonstrate power of statistical analysis to resolve multipotency in lineage labelling

last modified Jun 14, 2016 02:50 PM
In their Genes & Development paper, Ben Simons' group apply statistical analysis to quantify lineage tracing, and show that it is possible to resolve whether stem cells in developing tissues are multipotent.
09.06.16 Simons lab demonstrate power of statistical analysis to resolve multipotency in lineage labelling

3D whole mount of prostate epithelium 2 weeks after lineage tracing of basal stem cells

Quantitative lineage tracing strategies to resolve multipotency in tissue-specific stem cells

Wuidart A et al. (2016) Genes Dev. Jun 9 [Epub ahead of print] . Print volume: June 1, 30 (11)

Abstract

Lineage tracing has become the method of choice to study the fate and dynamics of stem cells (SCs) during development, homeostasis, and regeneration. However, transgenic and knock-in Cre drivers used to perform lineage tracing experiments are often dynamically, temporally, and heterogenously expressed, leading to the initial labeling of different cell types and thereby complicating their interpretation. Here, we developed two methods: the first one based on statistical analysis of multicolor lineage tracing, allowing the definition of multipotency potential to be achieved with high confidence, and the second one based on lineage tracing at saturation to assess the fate of all SCs within a given lineage and the “flux” of cells between different lineages. Our analysis clearly shows that, whereas the prostate develops from multipotent SCs, only unipotent SCs mediate mammary gland (MG) development and adult tissue remodeling. These methods offer a rigorous framework to assess the lineage relationship and SC fate in different organs and tissues.

 

Journal cover image reproduced under Creative Commons License CC BY 4.0.

Read more about the Simons lab.

Studying development to understand disease

The Gurdon Institute is funded by Wellcome and Cancer Research UK to study the biology of development, and how normal growth and maintenance go wrong in cancer and other diseases.

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