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SUMMARY:Modeling stem cell differentiation on multiple scales - Fabian The
 is (Helmholtz Center Munich)
DTSTART:20120508T150000Z
DTEND:20120508T160000Z
UID:TALK34786@talks.cam.ac.uk
CONTACT:Florian Markowetz
DESCRIPTION:Stem cell maintenance and differentiation are two tightly inte
 rconnected processes\, reflected in the architecture of the underlying tra
 nscriptional network. Different aspects of these cellular decision process
 es have been modeled with different experimental and theoretical technique
 s\, and on a spectrum of scales. Here I present three different models on 
 different scales. Using a combination of time-resolved expression data and
  \n\nBased on high-dimensional gene expression data\, we want to first ass
 ess differences in gene expression patterns between different developmenta
 l stages as well as within developmental stages. Conventional multivariate
  linear methods such as PCA fail at resolving important differences as eac
 h lineage has a unique gene expression pattern which changes gradually ove
 r time yielding different gene expressions both between different developm
 ental stages as well as heterogeneous distributions at a specific stage. W
 e therefore propose a novel framework based on Gaussian Process Latent Var
 iable Models for this analysis\, and apply it successfully to single-cell 
 qPCR expression data of 48 genes from mouse zygote to blastocyst.\n\nThe s
 econd model aims at describing fate decisions between mesodermal and endod
 ermal lineage. Initially based on expression data\, we identify a microRNA
 \, miR335\, as a developmentally regulated intronic host-gene miRNA during
  this process. We developed and validated a molecular mathematical model f
 or studying dynamic expression of miRNA335 and its targets Foxa2 and Sox17
 . The model provides an explanatory view on how miRNAs can form a spacio-t
 emporal gradient of gene expression. Taken together\, these results implic
 ate that miR335 fine tunes transcription factor gradients in the endoderm 
 and promotes mesoderm-lineage formation by targeting the endoderm-specific
 ation factors\, Foxa2 and Sox17. \n\nFinally on the microlevel\, we study 
 the stability and dynamics of a gene switch involved in lineage decisions 
 within a probabilistic framework under the assumption of monomeric transcr
 iption factor binding and separate mRNA and protein entities. Contrary to 
 the expectation from a deterministic description\, this switch shows rich 
 multi-stable dynamics. The stability of the regimes varies depending on th
 e number of mRNA and protein molecules. We predict that optimal stability 
 versus potential for robust differentiation is achieved at low copy number
 s of the associated mRNA species\, since the introduced intrinsic noise ca
 n more quickly lead to random transitions between the attractors of the sy
 stem\, thus allowing the potential for multiple robust differentiation sta
 tes. \n\nIn summary\, this talk aims at providing a multi-scale picture of
  how to infer and study dynamic models in stem cell differentiation.
LOCATION:Cancer Research UK Cambridge Research Institute\, Lecture Theatre
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