Learning mechanistic models of gene expression regulation from natural sequence variation

By Harmen Bussemaker, Columbia University

Apr 7, 2009

CNLS Conference room.

Our laboratory uses computation and quantitative modeling to understand the behavior of gene regulatory networks in terms of the underlying bio-molecular interactions. We focus on the function of transcription factors (TFs), which provide a crucial regulatory layer between signaling pathways and the genome. In this talk, we will describe how “hidden variables” related to the sequence specificity and condition-specific regulatory activity of TFs can be inferred through integrative analysis of functional genomics data of different type. We will also discuss a novel approach to mapping trans-acting sequence variation that infers segregant-specific TF activities, treat these as a quantitative trait, and then uses genetic linkage analysis to identify “aQTLs” harboring direct or indirect TF modulators.

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