Manu Setty -- Computational modeling of lineage decision mechanisms using single-cell data
|Starts:||16:00 22 Mar 2021|
|Ends:||17:00 22 Mar 2021|
|What is it:||Seminar|
|Organiser:||Department of Mathematics|
|Who is it for:||University staff, External researchers, Current University students|
Join us for this seminar by Manu Setty (Fred Hutch, WA, USA) as part of the North West Seminar Series in Mathematical Biology and Data Sciences. Details of the full series can be found here https://www.cms.livjm.ac.uk/APMSeminar/
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Abstract: How a cell decides its lineage is a long-standing and enigmatic question in molecular biology. Single-cell technologies offer unprecedented scale and resolution to study the cellular differentiation process and enable the alignment of cells into a unified trajectory representing their developmental progression. I will describe Palantir, the first single-cell trajectory detection algorithm to view the differentiation process as a probabilistic change in cell potential. Palantir models differentiation as a Markov process to compute the lineage biases and differentiation potential, a measure of plasticity, for all cells. Palantir modeling enables an accurate identification of lineage decision regions and associated gene expression and regulatory dynamics. I will then describe our study to characterize the spatial and temporal trajectories of mouse endoderm development. Combining Palantir modeling with a large-scale single-cell data, we uncovered an unexpected plasticity of embryonic epiblast cells to differentiate to the surrounding extra-embryonic endoderm at implantation and the concomitant emergence of the spatial signal in the endoderm. Our analysis further demonstrated the convergence of embryonic definitive and extra-embryonic visceral endoderm cells into spatially organized organ territories in the gut-tube at mid-gestation.
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Role: Assistant Prof
Organisation: Fred Hutchinson Cancer Centre
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