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 be challenging.
How are cells different?
A heatmap showing how many genes (of 100 tested) are differentially expressed between each pair of cells in the C. elegans lineage
Animal development requires cells to adopt very different morphologies and functions despite being derived from a common ancestor, the zygote, and despite containing identical DNA sequences. We use C. elegans to study developmental gene expression regulation because its transparency and invariant development allow automated quantitative analysis of gene expression by microscopy. The invariance of development means that every animal develops through an identical pattern of cell divisions and the pattern of cell divisions leading to a particular cell unambiguously predicts its fate. We can automatically trace the lineage in 3D movies of development by using custom software and quantitatively measure gene expression with cellular resolution over time. We have collected detailed wild-type expression patterns for over 100 transcription factors, and even this small number of genes can distinguish each cell in the embryo almost uniquely. We are currently developing tools to extend this information to the full genome.
Which targets are transcriptionally regulated?
A surprising result of genome-scale efforts to map transcription factor binding sites is that most factors bind to 100's or 1000's of sites in the genome. Several lines of evidence suggest that a large proportion of these sites are either nonfunctional or neutral, raising the question of how we can identify which sites are functionally important for regulation. We are coupling gain of function and loss of function experiments for transcription factors to high throughput gene expression methods to try to answer this question, with the ultimate goal of understanding which targets are regulated by which transcription factors in which cells.
How is temporal control established?
A heatmap showing the temporal expression across embryogenesis (x axis) for over 239 reporter embryos (y axis).
Many developmental events are temporally critical - if they occur at the wrong time the embryo will not survive. However we know surprisingly little about how temporal regulation is achieved. We are using temporally regulated reporter genes as molecular handles to allow us to identify these control mechanisms.
- What determines whether, when, and how much a given transcription factor impacts the expression of genes near its genomic binding sites?
- What combinatorial rules govern the interaction of multiple transcription factors?
- How are these factors combined into networks to ensure proper development in a multicellular organism?
Possible Rotation Projects
- Use quantitative microscopy to test predicted regulatory networks
- Develop computational tools to quantitatively measure localization to subcellular compartments
- Define combinatorial transcription factor targets by combining gain and loss of function genetics with genomic expression analysis
- Characterize sequences required for temporally correct expression patterns
- Determine how and why expression patterns are different in normal and stressful growth conditions
Walton, T, Preston, E, Nair, G, Zacharias, AL, Raj, A, Murray, JI: The bicoid class homeodomain factors ceh-36/OTX and unc-30/PITX cooperate in C. elegans embryonic progenitor cells to regulate robust development. PLOS Genetics 11(3), March 2015.
Churgin, MA, He, L, Murray, JI, Fang-Yen, c: Construction of a system for single-cell transgene induction in Caenorhabditis elegans using a pulsed infrared laser. Methods 68(3): 431-436, August 2014.
Araya CL, Kawli T, Kundaje A, Jiang L, Wu B, Vafeados D, Terrell R, Weissdepp P, Gevirtzman L, Mace D, Niu W, Boyle AP, Xie D, Ma L, Murray JI, Reinke V, Waterston RH, Snyder M: An integrative regulatory analysis of the C. elegans genome with temporal and spatial resolution. Nature 512(7515): 400-405, August 2014.
John Isaac Murray: A transmitotic memory of Wnt signaling and diversification of embryonic gene expression. SDB Mid-Atlantic Regional Meeting (Baltimore, MD) May 2014.
John Isaac Murray: Mining the C. elegans lineage for the developmental regulatory code. CSHL Conference on Systems Biology: Global Regulation of Gene Expression (Cold Spring Harbor, NY) Mar 2014.
Churgin MA, He L, Murray JI, Fang-Yen C.: Efficient Single-Cell Transgene Induction in Caenorhabditis elegans Using a Pulsed Infrared Laser. G3 3(10): 1827-32, October 2013.
Nair G, Walton T, Murray JI*, Raj A*: Gene transcription is coordinated with but not dependent on cell divisions during C. elegans embryonic fate specification. Development 140(16), August 2013.
Burdick, JT, Murray, JI: Deconvolution of gene expression from cell populations across the C. elegans lineage. BMC Bioinformatics 14(204), June 2013.
Richards, JL, Zacharias, AL, Walton, T, Burdick, JT, Murray, JI
: A quantitative model of normal C. elegans embryogenesis and its disruption after stress. Developmental Biology 374(1): 12-23, February 2013.
Murray JI, Bao Z: Automated Lineage and Expression Profiling in Live Caenorhabditis elegans Embryos. Cold Spring Harbor Protocols(8), August 2012.
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Last updated: 05/01/2015
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