Folker Meyer Lab

Folker Meyer

University of Chicago
Computation Institute
Research Institute Suite 405
5640 South Ellis Avenue
Chicago, IL 60637

Argonne National Laboratory
9700 South Cass Avenue
Building 240
Argonne, IL 60439

Phone: (630) 252-3261

About the Lab

Dr. Meyer builds research software to study microbial communities.

His research interests include microbial ecology, distributed high performance computing and big data. He leads the MG-RAST project, providing what is currently the most widely used metagenomics and metatranscriptomics analysis platform with. MG-RAST has analyzed over 100,000 data sets analyzed in early 2014.

Dr. Meyer is the area lead for microbial community sciences in the Department of Energy (DOE) Systems Biology Knowledgebase project KBase.

In the past he has worked on the GenDB and RAST projects. He is a board member of the Genomics Standards Consortium and a founding member of the Earth Microbiome Project (EMP).

ResearchGate: Folker Meyer
Google scholar: Folker Meyer

Selected Papers

Kyrpides NC, et al. Genomic encyclopedia of bacteria and archaea: sequencing a myriad of type strains
PLoS Biol. 2014 Aug 5. eCollection 2014 Aug.
PMID: 2509381

Handley KM, et al. The complete genome sequence for putative H2 - and S-oxidizer Candidatus Sulfuricurvum sp., assembled de novo from an aquifer-derived metagenome
Environ Microbiol. 2014 Mar 14. [Epub ahead of print]
PMID: 24628880

Glass EM, et al. MIxS-BE: a MIxS extension defining a minimum information standard for sequence data from the built environment
ISME J. 2014 Jan 8. Epub 2013 Oct 24. No abstract available.
PMID: 24152717

Lab Members

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M
Folker Meyer

Folker Meyer

Argonne, Core Member, Sr. Fellow,
Computational Biologist, Mathematics and Computer Science Division, Argonne National Laboratories
Senior Fellow, Computation Institute, The University of Chicago
(630) 252-3261

Additional Lab Members

  • Jared Bischof, MSc
  • Dan Braithewaite, BSc
  • Mark D'Souza, PhD
  • Wolfgang Gerlach, PhD
  • Elizabeth Glass, PhD
  • Travis Harrison, MSc
  • Adina Chuang Howe, PhD
  • Kevin Keegan, PhD
  • Tobias Paczian, MSc
  • Will Trimble, PhD
  • Wei Tang, PhD
  • Andreas Wilke, MSc

Jack Gilbert Lab

Jack Gilbert

Argonne National Laboratory
9700 South Cass Avenue
Argonne, IL 60439

Phone: (630) 252-7489

About the Lab

My laboratory focuses on numerous key aspects of how bacteria assemble into distinct communities, the metabolic mechanisms that structure these assemblages, and whether these systems can be predictively modeled over time and space. We use next generation sequencing approaches to access phylogenetic and functional information embedded within the genes of bacteria that populate these communities.  Our goal is to use this information to reconstruct community interactions, and ultimately to build statistical models of the microbial ecosystem.  These models will help us visualize large-scale patterns, generate predictions of responses to changes in an environment, and to identify gaps in our sampling campaigns.

We are a very collaborative group. Currently, we are involved in the (1) Earth Microbiome Project, which is a systematic characterization of microbial life across the biomes of planet earth; (2) Home Microbiome Project, an ongoing study to determine the rate and direction of microbial interaction between people, their pets and their homes; (3) Chicago Waterways Metagenomic Initiative, which aims to map and model the dynamics of microbial metabolism in the Chicago River and surrounding canals; (4) The Gulf of Mexico Microbial Metabolic Modeling Initiative that will map and model the microbial dynamics of the Gulf of Mexico; (5) American Gut, which aims to characterize the microbial diversity of 20,000 humans over the next 2 years; (6) The Autism Microbiome Consortium, which is providing a nexus for research into the influence of microbial metabolism on the symptoms of Autism; (7) Microbial Assemblage Prediction, which involves developing microbial modeling tools capable of allowing global forecasting of microbial community structure and metabolic potential across planet earth.

Our group also leadS the Hospital Microbiome Project, which is characterizing the taxonomic composition of surface-, air-, water- and human associated microbial communities in the new Center for Care and Discovery hospital.  The aim is to determine the influence of human population demographics on the directionality in which the microbial communities evolve and the rate of colonization by potential pathogens.

In addition to these core projects, we also have over 35 ongoing collaborations with researchers from around the world and right here in Chicago.

Selected publications

Shogan BD, et al. Intestinal anastomotic injury alters spatially defined microbiome composition and function
Microbiome. 2014 Sep 15. eCollection 2014.
PMID: 25250176

Zaborin A, et al. Membership and Behavior of Ultra-Low-Diversity Pathogen Communities Present in the Gut of Humans during Prolonged Critical Illness
MBio. 2014 Sep 23. mBio.01361-14.
PMID: 25249279

Hawley ER, et al. Metagenomic analysis of microbial consortium from natural crude oil that seeps into the marine ecosystem offshore Southern California
Stand Genomic Sci. 2014 Jan 2. eCollection 2014 Jun 15.
PMID: 25197496

Rideout JR, et al. Subsampled open-reference clustering creates consistent, comprehensive OTU definitions and scales to billions of sequences
PeerJ. 2014 Aug 21. eCollection 2014.
PMID: 25177538

Lax S, et al. Longitudinal analysis of microbial interaction between humans and the indoor environment
Science. 2014 Aug 29. science.1254529.
PMID: 25170151

Kyrpides NC, et al. Genomic encyclopedia of bacteria and archaea: sequencing a myriad of type strains
PLoS Biol. 2014 Aug 5. eCollection 2014 Aug.
PMID: 25093819

Larsen PE, et al. Satellite remote sensing data can be used to model marine microbial metabolite turnover
ISME J. 2014 Jul 29. ismej.2014.107. [Epub ahead of print]
PMID: 25072414

Parfrey LW, et al. Communities of microbial eukaryotes in the mammalian gut within the context of environmental eukaryotic diversity
Front Microbiol. 2014 Jun 19. fmicb.2014.00298. eCollection 2014.
PMID: 24995004

Hawley ER, et al. Metagenomes from two microbial consortia associated with Santa Barbara seep oil
Mar Genomics. 2014 Jun 20. margen.2014.06.003. [Epub ahead of print]
PMID: 24958360

Winston ME, et al. Understanding cultivar-specificity and soil determinants of the cannabis microbiome
PLoS One. 2014 Jun 16. journal.pone.0099641. eCollection 2014.
PMID: 24932479

Mason OU, et al. Metagenomics reveals sediment microbial community response to Deepwater Horizon oil spill
ISME J. 2014 Jul. ismej.2013.254. Epub 2014 Jan 23.
PMID: 24451203

Lab Members

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M
Folker Meyer

Folker Meyer

Argonne, Core Member, Sr. Fellow,
Computational Biologist, Mathematics and Computer Science Division, Argonne National Laboratories
Senior Fellow, Computation Institute, The University of Chicago
(630) 252-3261

Additional Lab Members

Sean Gibbons sgibbons@uchicago.edu
Simon Lax simonlax24@gmail.com
Jarrad Marcell jhampton-marcell@anl.gov
Angel Frazier frazierangel43@gmail.com
Tifani Anton tweshoo@gmail.com
kim handley kmhandley@uchicago.edu
Nicole Scott nicolescott1@gmail.com
Chris Marshall chris.w.marshall@gmail.com
Naseer Sangwan nikki1018sangwan@gmail.com
Cesar Cardona cesarcardona@uchicago.edu
Pamela Weisenhorn weise088@umn.edu

News

Research Papers

Barbara Stranger Lab

Barbara Stranger

Institute for Genomics and Systems Biology
The University of Chicago
KCBD 10134
900 E. 57th St.
Chicago, IL 60637

Phone: 773-702-4301

About the Lab

The overriding research interest of the lab is trying to disentangle the relationship between genotype and phenotype, and to understand the forces shaping functional genetic variation in humans. We use a combination of experimental and computational approaches: We employ high-throughput functional genomics and genome-wide association analysis (GWAS) to identify variable regions of the genome with functional effects on the transcriptome and proteome, and to investigate the context-specificity of these patterns. At the same time, we examine the levels and patterns of genetic variation within and between human populations, and between human and other species to identify regions of the genome with patterns of variation suggestive of natural selection.

Current projects in the lab investigate genetic effects on transcriptome regulation in disease contexts that include cancer, immune-mediated diseases, neuropsychiatric diseases, and pre-eclampsia. We also have a project examining the role of genetic regulation of the transcriptome in pharmacogenomics phenotypes. In parallel, as part of the ImmVar Consortium, we are studying immune cells of healthy cohorts to obtain a baseline against which to compare disease regulatory networks in immune-mediated diseases. We are active members of the Analysis Working Group of the Genotype-Tissue Expression (GTEx) Consortium, and have received funding to generate proteomic data and to perform analyses associating genetic variation data with proteomic expression data within and between tissues of the GTEx cohort. These approaches complement disease-mapping studies and provide hypotheses for the mechanism of action of specific variants in creating disease phenotypes.

We recently integrated GWAS results with protein-protein interaction networks and transcriptome data to examine the relationship between genome evolution and inflammatory disease (Raj et al, 2013).  We identified 21 genome regions with a ‘signature’ for both inflammatory disease susceptibility and natural selection. Our study suggests that genetic variants selected through human evolution based on their ability to function in pathogen-protection mechanisms can - in our modern, more pathogen-free, environment – predispose to autoimmune disease.

In Li et al (2014), we combined GWASs and data from The Cancer Genome Atlas (TCGA) to gain insight into the mechanisms by which cancer risk alleles predispose to disease.  We performed expression quantitative trait locus (eQTL) analyses for mRNA and miRNA expression levels in five tumor types (breast, colon, kidney, lung and prostate), thus identifying the germline genetic determinants of tumor gene expression and microRNA expression. We next tested 149 known cancer risk loci for eQTL effects, observing that nearly 30% were significantly associated with at least one transcript. For each of the risk loci, our study suggested 1 to 81 candidate causal variants that may be prioritized for downstream functional analysis. In summary, our study provided a comprehensive landscape of the genetic determinants of gene expression in different tumor types and ranked the genes and loci for further functional assessment of known cancer risk loci.

The lab is also interested in projects that are less disease centric and would be categorized as basic genome science.  We are interested in investigating:  1) the evolution of paralogs in the human genome; 2) the influence of genetic variation, ancestry, age, sex, cell-type, epigenome, and tissue-type on transcriptional networks; 3) genetic and epigenetic roles in gene splicing and 4) population genomics of regulatory regions and variants. We are constantly re-tooling and developing new analytic methods and tools to most effectively and efficiently make use of large-scale genomics data.

Selected Publications

Raj T, et al. Polarization of the effects of autoimmune and neurodegenerative risk alleles in leukocytes
Science. 2014 May 2. science.1249547.
PMID: 24786080

Lee MN, et al. Common genetic variants modulate pathogen-sensing responses in human dendritic cells
Science. 2014 Mar 7. science.1246980.
PMID: 24604203

Ye CJ, et al. Intersection of population variation and autoimmunity genetics in human T cell activation
Science. 2014 Sep 12. science.1254665.
PMID: 25214635

Hu X, et al. Regulation of gene expression in autoimmune disease loci and the genetic basis of proliferation in CD4+ effector memory T cells
PLoS Genet. 2014 Jun 26. eCollection 2014 Jun.
PMID: 24968232

Li Q, et al. Expression QTL-based analyses reveal candidate causal genes and loci across five tumor types
Hum Mol Genet. 2014 Oct 1. Epub 2014 Jun 6.
PMID: 24907074

Lab Members

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M
Folker Meyer

Folker Meyer

Argonne, Core Member, Sr. Fellow,
Computational Biologist, Mathematics and Computer Science Division, Argonne National Laboratories
Senior Fellow, Computation Institute, The University of Chicago
(630) 252-3261

News

NIH Funding to Study the Effects of Gender on Complex Human Traits

IGSB core investigator Barbara Stranger received supplemental funding from NIH to explore the effects of gender on human traits. Her group will characterize these differences and determine what underlies them. This new funding will allow her lab to focus on how gender influences the relationship between genetic differences among individuals and variation in protein levels among individuals and across tissues, with an ultimate goal of understanding how this influences disease susceptibility. Her lab also received funding to specifically investigate the role of gender in pharmacogenomics phenotypes and neuropsychiatric phenotypes (with IGSB core member Andrey Rzhetsky). For more information, click here.

IGSB Core Member Co-Authors Paper

Barbara Stranger and her lab led analyses of data published in the journal, Science. The report, “Polarization of the Effects of Autoimmune and Neurodegenerative Risk Alleles in Leukocytes,” demonstrates how genetic variations among healthy, young individuals can influence immune cell function. Many of those variants are also genetic risk factors for Alzheimer’s disease, diabetes, and multiple sclerosis later in life, offering new insight into disease pathology.

Immunity, inflammation and natural selection

Barbara Stranger and colleagues take a systems approach, integrating GWAS, eQTL and protein interaction data, to demonstrate that loci associated with inflammatory disease susceptibility are enriched for genomic signatures of recent evolutionary selection.  Their analyses suggest that natural selection for pathogen-defense mechanisms through human evolution may underlie modern susceptibility to inflammatory diseases.

Research Papers

Robert Grossman Lab

Robert Grossman

Institute for Genomics and Systems Biology
The University of Chicago
900 East 57th Street KCBD 10146
Chicago, IL 60637

Phone: 773-834-4669

About the Lab

Professor Grossman’s research group focuses on bioinformatics, data mining, cloud computing, data intensive computing, and related areas.  Current research projects include: Bionimbus (http://www.bionimbus.org) a cloud-based system for managing, analyzing and sharing genomic data and the Open Science Data Cloud (OSDC), a large-scale distributed cloud-based infrastructure for managing, analyzing, integrating and sharing scientific data.  The OSDC is operated by the Open Cloud Consortium (OCC), which is a not-for-profit supporting the cloud community by operating cloud infrastructure.  Professor Grossman is also interested in developing new algorithms for the large-scale analysis projects of genomic and phenotypic data.

 

Selected Papers

Slattery M, et al. Diverse patterns of genomic targeting by transcriptional regulators in Drosophila melanogaster
Genome Res. 2014 Jul. gr.168807.113.
PMID: 24985916

Kolker E, et al. Toward more transparent and reproducible omics studies through a common metadata checklist and data publications
OMICS. 2014 Jan. omi.2013.0149.
PMID: 24456465

Madzo J, et al. Hydroxymethylation at gene regulatory regions directs stem/early progenitor cell commitment during erythropoiesis
Cell Rep. 2014 Jan 16.celrep.2013.11.044. Epub 2013 Dec 27.
PMID: 24373966

Heath AP, et al. Bionimbus: a cloud for managing, analyzing and sharing large genomics datasets
J Am Med Inform Assoc. 2014 Jan 24. amiajnl-2013-002155. [Epub ahead of print]
PMID: 24464852

Lab Members

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M
Folker Meyer

Folker Meyer

Argonne, Core Member, Sr. Fellow,
Computational Biologist, Mathematics and Computer Science Division, Argonne National Laboratories
Senior Fellow, Computation Institute, The University of Chicago
(630) 252-3261

News

Big Data Versus the Big C

IGSB investigators Bob Grossman and Megan McNerney
are highlighted in an Outlook Cancer: Bioinformatics profile in the May 29, 2014 issue of Nature.

Open Science Data Cloud – Partnerships for International Research & Education

TRAVEL ABROAD WHILE RESEARCHING THE LATEST TECHNOLOGIES IN CLOUD COMPUTING WITH NSF FUNDED OSDC-PIRE FELLOWSHIP                                                             DEADLINE: April 30, 2014

The Open Science Data Cloud PIRE project provides international research and education experiences through training and study at universities and research institutes around the world with leading scientists in computing. Increase your expertise in managing and analyzing data.

Robert Grossman named a Federal 100 Award winner

The annual list, published by Federal Computer Week, recognizes government, industry and academic leaders who have played pivotal roles in the federal government IT community.

IGSB Core Faculty Robert Grossman appointed Chief Research Informatics Officer

Robert Grossman, PhD, assumed the role of chief research informatics officer and is currently overseeing a research group focused on bioinformatics, data mining, data intensive computing and related areas. Press Release

Research Papers

Michael Rust Lab

Michael Rust

Institute for Genomics and Systems Biology
The University of Chicago
900 East 57th Street
KCBD 10124
Chicago, IL 60637

Phone: (773)-834-1463

About the Lab

My lab is interested in understanding how the properties of living cells emerge from the stochastic reactions of molecular components. We use a mixture of biophysical, biochemical, genomic, mathematical modeling, and single-cell microscopy approaches to link the properties of molecules to the systems-level behavior of cells. Most of our attention is currently focused on an oscillatory protein network found in the cyanobacterium Synechococcus elongates that the organism uses to predict the time of day. Remarkably, the biological rhythms generated by this circadian clock can be reconstituted in a test tube using three purified protein components - KaiA, KaiB, KaiC - making this the best-defined biological oscillator currently known. It is possible to reconstitute metabolic input signaling to this minimal clock by varying ATP and ADP concentrations (Rust et al, 2011).  We are actively pursuing a quantitative understanding of the reactions that generate oscillations and the robustness properties of this minimal circadian clock. We are also working outward to expand the functions that can be studied in a purified context and include additional components from the in vivo clock system. We seek to tie the biochemical and biophysical properties of these components back to physiologically relevant conclusions for the organism by making quantitative measurements of growth rate and single-cell behavior, including experiments that are uniquely possible in microbial model systems.


We have recently shown that both robustness and adaptability of the clock are determined by the two enzymatic domains of KaiC (Phong et al, 2013).  One of the domains, CII, phosphorylates itself in response to input signals.  CI, a domain of previously unknown function, is insulated from input signals and sets a slow, constant timescale for the interaction between KaiC and the negative regulator KaiB. By building mathematical models of this system, we showed that this two-domain architecture is needed to get the combination of robust period and tunable phase in the circadian clock.  These models will help to illuminate the structures of the clock networks in humans and other organisms where input-sensitive and input-insensitive feedback loops may also be required for proper function.

Selected publications

Lin J, et al. Mixtures of opposing phosphorylations within hexamers precisely time feedback in the cyanobacterial circadian clock
Proc Natl Acad Sci U S A. 2014 Sep 16. pnas.1408692111. Epub 2014 Sep 2.
PMID: 25197081

Pattanayak GK, et al. Rhythms in energy storage control the ability of the cyanobacterial circadian clock to reset
Curr Biol. 2014 Aug 18. j.cub.2014.07.022. Epub 2014 Aug 7.
PMID: 25127221

Pattanayak G, et al. The cyanobacterial clock and metabolism
Curr Opin Microbiol. 2014 Apr. j.mib.2014.02.010. Epub 2014 Mar 22.
PMID: 24667330

Lab Members

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M
Folker Meyer

Folker Meyer

Argonne, Core Member, Sr. Fellow,
Computational Biologist, Mathematics and Computer Science Division, Argonne National Laboratories
Senior Fellow, Computation Institute, The University of Chicago
(630) 252-3261

News

IGSB Students Participate in iGEM Competition

IGSB students in Mike Rust's lab are collaborating on an International Genetically Engineered Machines (iGEM) project about synthetic biology. IGSB team members are using standardized biological parts provided by iGEM and molecular components they have devised to engineer E.coli mutator strains that can optimize the production of a desired metabolite using a novel technique in directed evolution. The team will go to the 2014 iGEM jamboree at MIT to present their research. Participating iGEM teams from around the world will also attend and demonstrate synthetic living systems with innovative functions and capabilities.

Mike Rust Honored by Being Named a Pew Scholar

IGSB Core Member, Mike Rust, was
honored today by being named a Pew
Scholar in the Biomedical Sciences by the
Pew Charitable Trusts. Pew Scholars are
selected by a national advisory committee.
They receive flexible funding over four
years to seed innovation at the start of
independent research careers.

The inner workings of the circadian clock

Michael Rust and colleagues reveal the biochemical mechanisms that allow the oscillations of the cyanobacterial biological clock to be tuned to changes in the environment while simultaneously maintaining a robust 24-hour period.

Research Papers

Dionysios Antonopoulos Lab

Dionysios Antonopoulos

Argonne National Laboratory
9700 S. Cass Avenue
Bldg 202, Room A-341
Argonne, IL 60439

Phone: (630) 252 3935

About the Lab

My laboratory specializes in microbial ecology and using metagenomic-enabled approaches to study communities of microorganisms in a variety of environments. We apply next-generation DNA sequencing technologies towards describing both the structure and function of microbial communities in these systems, taking advantage of the computational resources available at Argonne for handling the scale of data afforded by these technologies. I started my career as a microbiologist studying the cellulose-degrading capabilities of bacteria from production livestock, making extensive use of anaerobic cultivation buoyed by the then emerging area of comparative microbial genomics.  My interest in understanding mammalian gastrointestinal function has expanded to research in environmental systems (subsurface and topsoil systems) using metagenomics. Although the scales are vastly different between the two, similar approaches based in classical ecological theory can be used for both gastrointestinal and field research to circumnavigate the complex microbial communities underlying system function.

In collaboration with colleagues at the University of Chicago these approaches were used to understand the role that diet plays in promoting complex immune disorders such as inflammatory bowel diseases (IBD). This study, which appeared in the journal Nature, provides new insights into why some people are more likely than others to develop IBD (Devkota et al, 2012). Working with a mouse model, we traced both the shift in the microbial community structure and the corresponding host immune response to a diet high in saturated (milk-derived) fats. To dissolve such fats, the liver produces a form of bile rich in sulfur. When the bile reaches the intestines, a microbe called Bilophila wadsworthia – the name means “bile loving” – blooms. Such blooms can trigger the immune system in people with a genetic predisposition. Moreover, the byproducts of this microbe’s interaction with bile can amplify the effect, making the bowel more permeable and unleashing an unregulated immune response in individuals at high risk for diseases such as IBD.

Selected publications

Evans CC, et al. Exercise prevents weight gain and alters the gut microbiota in a mouse model of high fat diet-induced obesity
PLoS One. 2014 Mar 26. journal.pone.0092193. eCollection 2014.
PMID: 24670791

Handley KM, et al. The complete genome sequence for putative H2 - and S-oxidizer Candidatus Sulfuricurvum sp., assembled de novo from an aquifer-derived metagenome
Environ Microbiol. 2014 Mar 14. [Epub ahead of print]
PMID: 24628880

Huse SM, et al. Comparison of brush and biopsy sampling methods of the ileal pouch for assessment of mucosa-associated microbiota of human subjects
Microbiome. 2014 Feb 14. 2049-2618-2-5.
PMID: 24529162

Lab Members

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M
Folker Meyer

Folker Meyer

Argonne, Core Member, Sr. Fellow,
Computational Biologist, Mathematics and Computer Science Division, Argonne National Laboratories
Senior Fellow, Computation Institute, The University of Chicago
(630) 252-3261

News

Why a diet rich in saturated fat can trigger bowel disorders

Dionysios Antonopoulos, an assistant biologist (microbiologist) in the Institute for Genomics and Systems Biology at Argonne National Laboratory, is co-author (with Suzanne Devkota, Bana Jabri, Eugene Chang, and others at the University of Chicago) of a new study on the role that diet plays in promoting complex immune disorders such as inflammatory bowel disease (IBD).

Research Papers

Andrey Rzhetsky Lab

Andrey Rzhetsky

Institute for Genomics and Systems Biology
The University of Chicago
900 East 57th Street
KCBD
Chicago, IL

Phone: (773) 834-7367 Fax: (773) 834-2877

About the Lab

Our group is engaged in a series of computational projects that involve mathematical modeling and analysis of disparate data sets, such as electronic medical records, scientific texts, and high-throughput experimental data.  The overarching goal of such analyses is formulating and testing hypotheses regarding interplay of genetic and environmental mechanisms of human disease.  Formulation and testing of models requires dynamic collaboration with a range of experts in disease phenotype, genetics, statistical modeling, epidemiology, and sociology of science.  We also closely collaborate with groups producing high-throughput data on data interrogation and experimental validation of computational predictions.

We are currently developing approaches for large-scale modeling and analyses of a time-series of phenotypic and environmental records, as represented in patient record databases.  In parallel, we are developing models to analyze gene association and genetic linkage data in a molecular network context, explicitly allowing for multigenic models.  We will implement joint probabilistic models of groups of disease phenotypes, accounting for their dependence on genetic variation, the proximity of genes in molecular networks, and environmental events.  Our aim is to integrate these multi-level models to jointly analyze genomic, clinical and textual data, so as to obtain insights into genetic and environmental factors that, in combination, determine disease phenotypes.

Selected publications

Blair DR, et al. Quantifying the Impact and Extent of Undocumented Biomedical Synonymy
PLoS Comput Biol. 2014 Sep 25. journal.pcbi.1003799. eCollection 2014 Sep.
PMID: 25255227

Liu CC, et al. DiseaseConnect: a comprehensive web server for mechanism-based disease-disease connections
Nucleic Acids Res. 2014 Jul. Epub 2014 Jun 3.
PMID: 24895436

Rzhetsky A, et al. Environmental and state-level regulatory factors affect the incidence of autism and intellectual disability
PLoS Comput Biol. 2014 Mar 13. journal.pcbi.1003518. eCollection 2014 Mar.
PMID: 24625521

Lab Members

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M
Folker Meyer

Folker Meyer

Argonne, Core Member, Sr. Fellow,
Computational Biologist, Mathematics and Computer Science Division, Argonne National Laboratories
Senior Fellow, Computation Institute, The University of Chicago
(630) 252-3261

News

New data-mining effort launched to study mental disorders

The Sylvio O. Conte Center, a multi-institutional effort based at the University of Chicago, will combine the statistical power of pre-existing genetics, pharmacogenomics, text-mining and clinical record databases to confront diseases that have so far frustrated researchers.Press Release

Research Papers

Kevin White Lab

Kevin White

James and Karen Frank Professor
Department of Human Genetics
Director, Institute for Genomics and Systems Biology
The University of Chicago

The Institute for Genomics and Systems Biology
The University of Chicago
900 East 57th Street
KCBD 10100A
Chicago, IL 60637

Phone: (773) 834-0074

About the Lab

The White lab studies the coordinated action of networks of genes that control developmental, disease and evolutionary processes. We have particular focus on discovery of genetic factors that contribute to cancer development and progression, and on building genome-wide models of transcriptional networks. We use an integrated approach that makes use of genome and transcriptome sequencing, large-scale protein-protein and protein-DNA interaction analyses, measurement of chromatin state, systematic RNAi and CRISPR mutational analysis, and high throughput functional analyses of genomic regulatory elements. By applying our methods to both closely and distantly related species, we are investigating how conserved molecular networks control basic developmental processes and how variation in molecular networks translates into variation in organismal phenotypes. We are also particularly interested in the transcriptional networks controlled by nuclear receptor proteins in development and disease. For example, we have produced genome-wide maps of the entire repertoire of nuclear receptors expressed in breast cancer cells, and this has led to the discovery of previously untargeted nuclear receptors that are promising drug candidates. We then test such candidates in mouse models, and we are attempting to ‘reverse engineer’ the nuclear receptor regulatory networks in breast cancer using a combination of genome-scale data generation, computational techniques and genomic engineering of cell lines and mice. We also have recently built novel algorithms for discovering tumor drivers and tumor risk factors from large-scale sequencing data, such as those available from The Cancer Genome Atlas. In those projects we have identified significantly co-occurring mutations and tested for genetic interactions in cell lines and in patient survival data, we have identified dozens of novel fusion genes and then synthesized them for testing in cell and mouse models, and we have systematically identified germline variants that may contribute to cancer risk and tested their functional roles using CRISPR engineered cell models.  Another focus of the lab is studying genetic regulatory programs that are highly conserved between fly and human. This has led to discoveries such as a role for the protein SPOP in both Drosophila embryogenesis and human kidney cancer, and to the identification of conserved targets of natural selection during adaptation to hypoxia (low oxygen) in both flies and humans. Related to this comparative work is our lab’s contributions to the ENCODE and modENCODE projects, where we have been systematically comparing the binding patterns of transcription factors genome-wide in flies, worms and humans. Our lab also contributes to the NIH GTEx and psychENCODE projects through our investigations of the relationship between genomic variation and variation in transcript and protein expression. Finally, we have recently embarked on an ambitious project in pancreatic cancer to co-analyze large numbers of tumor genomes, tens of thousands of electronic medical records, and literature databases to build predictive models of which patients might respond to which treatments. This work is facilitated by the use of patient-derived xenograft models, as well as mouse models developed using the CRISPR Cas9 system. Our goal is to develop algorithmic approaches to rapidly assess a tumor’s genomic and physiological state, then test drugs in mouse models that ultimately can be moved into patients.

Selected Papers

Rhee DY, et al. Transcription Factor Networks in Drosophila melanogaster
Cell Rep. 2014 Sep 17. [Epub ahead of print]
PMID: 25242320

Boyle AP, et al. Comparative analysis of regulatory information and circuits across distant species
Nature. 2014 Aug 28
PMID: 25164757

Hause RJ, et al. Identification and validation of genetic variants that influence transcription factor and cell signaling protein levels
Am J Hum Genet. 2014 Aug 7. Epub 2014 Jul 31.
PMID: 25087611

Seiwert TY, et al. Integrative and comparative genomic analysis of HPV-positive and HPV-negative head and neck squamous cell carcinomas
Clin Cancer Res. 2014 Jul 23. [Epub ahead of print]
PMID: 25056374

Oh H, et al. Yorkie promotes transcription by recruiting a histone methyltransferase complex
Cell Rep. 2014 Jul 24. Epub 2014 Jul 10.
PMID: 25017066


Slattery M, et al. Diverse patterns of genomic targeting by transcriptional regulators in Drosophila melanogaster
Genome Res. 2014 Jul
PMID: 24985916


Arthur RK, et al. Evolution of H3K27me3-marked chromatin is linked to gene expression evolution and to patterns of gene duplication and diversification
Genome Res. 2014 Jul
PMID: 24985914


McNerney ME, et al. The spectrum of somatic mutations in high-risk acute myeloid leukaemia with -7/del(7q)
Br J Haematol. 2014 Aug. Epub 2014 Jun 13.
PMID: 24931631


VanderWeele DJ, et al. Low-grade prostate cancer diverges early from high grade and metastatic disease
Cancer Sci. 2014 Aug
PMID: 24890684

Lab Members

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M
Folker Meyer

Folker Meyer

Argonne, Core Member, Sr. Fellow,
Computational Biologist, Mathematics and Computer Science Division, Argonne National Laboratories
Senior Fellow, Computation Institute, The University of Chicago
(630) 252-3261

News

Audrey Fu Awarded K99 NIH Grant

IGSB Research Professional, Dr. Audrey Fu, was awarded a K99 NIH grant to support a research project entitled: Causal Inference of Gene Regulatory Networks with Application to Breast Cancer. The aim is to develop statistical models and computational methods for the inference of causal gene regulatory networks. The project will investigate how genetic variation acting on biological networks influences development and progression of diseases, using subtypes of breast cancer as a disease model.

IGSB Summer High School Student Accepted to Attend UChicago

Madison Olmsted, from Rio Americano High School in Sacramento, California, participated in a Research in Biological Sciences, Part 2 (RIBS-2) program in Kevin White’s lab last summer. 

Hormones and Microbes Interact to Modify Autoimmune Disease Progression

IGSB/CBC Postdoctoral Fellow Aly Khan co-authored a study on a previously unknown interaction between gut bacteria and gender bias in autoimmune diseases. The study proposes a novel two-signal model, in which hormones and microbes together influence the incidence and severity of autoimmune diseases. The results were published in Cell Immunity and are highlighted in a featured article in the issue.

Bionimbus Protected Data Cloud eliminates need for massive storage infrastructure

Bionimbus, an advanced cloud-based computing environment, helped Megan McNerney discover tumor suppressor gene, CUX1, is frequently inactivated in acute myeloid leukemia. The principal investigator for Bionimbus is Robert Grossman.

Gifts to boost University of Chicago as hub for biomedical ‘big data’

Two major gifts will build momentum behind the University of Chicago’s leadership in biomedical computation by assembling experts in the field and furnishing them with the tools to use “big data” to understand and treat disease.  Kevin White and Robert Grossman will lead the Pancreatic Cancer Genomic Medicine Initiative, which aims to improve care for patients with this disease using genomic and physiological data.

Tracing adaptive evolution of regulatory elements in the fly genome

Kevin White and colleagues determine the binding sites of the insulator protein CTCF in four Drosophila species whose divergence spans 25 million years in evolutionary time.  Their findings provide evidence for positive selection shaping the evolution of these regulatory sites and through them, the genes they control.

Aashish Jha was recently selected to receive a predoctoral fellowship from the University of Chicago

IGSB graduate student, Aashish Jha, in Kevin White?s lab, was recently selected to receive a predoctoral fellowship from the University of Chicago?s Center for Systems Biology of Oxygen Sensing.  An Institutional Training Grant, “Training in O2 Biology in Health & Disease,” will support his research training. This award is based on Aashish Jha?s academic record, scienti?c performance in the lab, and relevance of his thesis project to the ?eld of oxygen biology.

Research Papers