Murray Lab

Research

The goal of the Murray lab is to understand how genomes encode diverse gene expression patterns and cellular phenotypes. While the genetic code provides a basis for predicting the phenotypic consequences of coding sequence changes, we don’t have an equivalent framework for regulatory sequences. The regulatory code is clearly more complex than the genetic code because it uses combinatorial protein-DNA binding rather than base pairing to achieve specificity. Because there are many regulatory proteins and DNA binding sites, unraveling the importance of each interaction will require a large amount of experimental data. We hope to generate these data by combining high resolution microscopy with genomics methods to identify functional targets of transcription factors during animal development.

Development is an amazing process, considering that it requires cells to adopt very different morphologies and functions despite being derived from a common ancestor, the zygote, and despite containing the same DNA sequences. We use the nematode C. elegans as a model because its transparency and invariant development allow automated quantitative analysis of gene expression by microscopy. Invariant development means that every animal develops through an identical pattern of cell divisions and the pattern of cell divisions unambiguously predicts each cell's fate. We use custom software to automatically trace the lineage in 3D movies collected by confocal microscopy and quantitatively measure expression dynamics with cellular resolution. We have collected detailed wild-type expression patterns for over 100 transcription factors and have begun assaying their regulation by using mutants and RNAi.

Our ongoing work focuses on three questions related to developmental genomics. 1) What determines whether, when, and how much a given transcription factor impacts the expression of genes or its genomic binding sites? 2) What combinatorial rules govern the interaction of multiple transcription factors? 3) How are these factors combined into networks to control development in a multicellular organism?