Kris Gunsalus

Kris Gunsalus

Assistant Professor of Biology
Ph.D. 1997 (Section of Genetics and Development), Cornell University; B.A. 1984 (Chemistry and Biology), Cornell University.

Office Address:
New York University
Center for Genomics and Systems Biology
Department of Biology
1009 Silver Center
100 Washington Square East
New York, NY 10003-6688

Email:
Phone: (212) 998-8236
Fax: (212) 995-4015
List of Publications from Pubmed

Research

Our laboratory is interested in the integrative analysis of diverse functional genomics data to identify groups of genes that work in specific cellular and developmental processes. A major challenge in systems biology is how to extract meaningful biological insights from large heterogeneous data sets that probe different aspects of gene function. Several ongoing projects in the lab use integrative approaches to analyze and interpret large-scale datasets and to generate testable hypotheses on gene function in different biological systems. These projects all involve close collaborative interaction between experimental and computational scientists.

Molecular networks in C. elegans early embryogenesis
We have used an integrative approach to characterize gene networks that function in the very early C. elegans embryo, based on data from different kinds of functional genomics data that we and others have collected, such as protein-protein interactions, gene expression profiles, and phenotypic maps (Fig. 1). We are currently extending this work in collaboration with the laboratory of Dr. Fabio Piano to systematically define genetic interactions in C. elegans early embryogenesis. Genetic interactions tell us about logical relationships between different cellular components, and we are analyzing how these functional dependencies complement other functional data that we already have in hand. The long-term goal of this work is to develop a global map of the molecular architecture underlying early development in C. elegans.


Figure 1. C. elegans gene networks in early embryogenesis. (a) A composite view of around 30,000 functional linkages between 661 C. elegans genes with phenotypes in the early embryo, based on protein-protein interactions (Int), phenotypic similarity based on a signature of 45 early embryonic phenotypic characters (Ph), and gene co-expression in a compendium of gene expression data (Tr). (b) When the network is filtered for high-confidence functional links between genes (supported by two or more types of functional genomic data, e.g. phenotypic correlation and protein-protein interaction), a modular organization of molecular machinery is revealed, in which groups of highly interconnected genes are linked to each other via a small number of functional interactions. Adapted from Gunsalus et al., Nature 2005.


Genetic requirements for mouse early embryogenesis
We are collaborating with Dr. Nicole Noyes of the NYU School of Medicine to predict and analyze RNAi phenotypes in early mouse embryos using time-lapse microscopy. For this work, we are leveraging functional genomic data from several model organisms to identify candidate genes for RNAi that will help us define the spectrum of phenotypic defects that can occur in early mammalian embryos, similar to our previous work in C. elegans. One of the goals of this translational project is to develop a more sophisticated and non-invasive way to determine the developmental potential of human embryos for patients who seek reproductive assistance for infertility.

Post-transcriptional gene regulation in C. elegans
Regulation of mRNA localization, translation, and stability is increasingly recognized as in important layer in the regulation of gene activity in diverse biological systems. The modENCODE Consortium is an NIH/NHGRI initiative to identify and analyze functional elements in model organism genomes. As part of modENCODE, we are involved in the annotation of C. elegans 3’UTRs and functional sequence elements contained in these regions. The goal of this work is to identify and test putative post-transcriptional regulatory networks in development. This project is a collaboration with Fabio Piano (PI), John Kim (U. Michigan, Co-PI), and Nikolaus Rajewsky (Center for Medical Systems Biology, Max Delbruck Center, Berlin, Co-PI).

Interactive tools for functional genomic data
As part of these projects, we develop web-based tools and graphical interfaces to provide the research community at large with enhanced access to and mining capabilities for large-scale functional genomic data. To facilitate a systems-level view of gene networks, we have developed a web-based network visualization tool called "N-Browse" (http://www.gnetbrowse.org) that allows researchers to browse gene neighborhoods and heterogeneous functional relationships in a modular way based on these integrated data. We have also developed a web-accessible database of RNA interference (RNAi) phenotypes in C. elegans, "RNAiDB" (http://www.rnai.org), which we use both to distribute data from large-scale RNAi studies and as an online notebook for ongoing high-content phenotypic analysis. In conjunction, we are developing strategies to make phenotypic data more amenable to computational analysis and tools to mine these data.

Web Resources:

Job Opportunity:

Post-doctoral Positions(October 2009)
Multiple positions are available in the laboratories of Dr. Kris Gunsalus and Dr. Richard Bonneau in the NYU CGSB.

Gunsalus lab: Two post-doctoral positions are currently available as part of our modENCODE project that will focus on annotation and computational analysis of 3’UTR regions of mRNA transcripts, potential trans-acting factors such as miRNAs and proteins, and post-transcriptional regulatory networks. The work will include analysis of RNA-seq data from high-throughput sequencing platforms (including 454, Illumina, ABI SOLiD) and integration with other data (chromatin & histone marks, smRNA profiling, etc.).

Bonneau lab: Dr. Bonneau is part of a new NIH Physical Sciences Oncology Center spanning several experimental and computational groups that aims to reconstruct regulatory and signaling networks from systems biology datasets (including: proteomics, genotype, expression, protein modification and cell micro-environment) in human and mouse. We will develop novel methods for learning dynamical models of regulatory and signaling networks from these integrated datasets. For more information see: http://homepages.nyu.edu/~rb133/

The NYU CGSB is a dynamic environment with close interactions between experimental and computational labs located at the heart of Greenwich Village in New York City. Interested parties should provide a CV, a statement of research interests, and contacts for two references to kcgl [at] nyu [dot] edu and bonneau [at] cs [dot] nyu [dot] edu as a single PDF with the subject line:“Postdoctoral application: computational systems biology”. NYU is an equal opportunity employer.

Areas of Research/Interest

Developmental systems biology.

Fellowships/Honors

National Academies Education Fellow in the Life Sciences, NSF ADVANCE Fellows Award, W.M. Keck Foundation Fellowship in Biology

Publications