Barbara Stranger Lab
Institute for Genomics and Systems Biology
The University of Chicago
900 E. 57th St.
Chicago, IL 60637
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 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 and epigenetic effects on transcriptome regulation in disease contexts that include cancer, asthma and pre-eclampsia. In parallel, we are studying immune cells of healthy cohorts to obtain a baseline against which to compare disease regulatory networks in immune-mediated diseases. 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 (2013), we combined GWASs and data from The Cancer Genome Atlas (TCGA) to gain insight into the mechanisms by which breast cancer risk alleles predispose to disease. Expression quantitative trait locus (eQTL) analyses of 15 breast cancer risk loci demonstrated that three risk variants regulate expression of the estrogen receptor (ESR1) and the oncogenes MYC and KLF4, and have downstream effects on transcript levels of many genes. The methods applied in this comprehensive study are being applied to additional cancer types.
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.
Li Q, Seo JH, Stranger B, McKenna A, Pe’er I, Laframboise T, Brown M, Tyekucheva S, Freedman ML. Integrative eQTL-based analyses reveal the biology of breast cancer risk loci. Cell. 2013 Jan 31;152(3):633-41. doi: 10.1016/j.cell.2012.12.034.
Cui J, Stahl EA, Saevarsdottir S, Miceli C, Diogo D, Trynka G, Raj T, Mirkov MU, Canhao H, Ikari K, Terao C, Okada Y, Wedrén S, Askling J, Yamanaka H, Momohara S, Taniguchi A, Ohmura K, Matsuda F, Mimori T, Gupta N, Kuchroo M, Morgan AW, Isaacs JD, Wilson AG, Hyrich KL, Herenius M, Doorenspleet ME, Tak PP, Crusius JB, van der Horst-Bruinsma IE, Wolbink GJ, van Riel PL, van de Laar M, Guchelaar HJ, Shadick NA, Allaart CF, Huizinga TW, Toes RE, Kimberly RP, Bridges SL Jr, Criswell LA, Moreland LW, Fonseca JE, de Vries N, Stranger BE, De Jager PL, Raychaudhuri S, Weinblatt ME, Gregersen PK, Mariette X, Barton A, Padyukov L, Coenen MJ, Karlson EW, Plenge RM. Genome-Wide Association Study and Gene Expression Analysis Identifies CD84 as a Predictor of Response to Etanercept Therapy in Rheumatoid Arthritis. PLoS Genet. 2013 Mar;9(3):e1003394. doi: 10.1371/journal.pgen.1003394.
Raj T, Kuchroo M, Replogle JM, Raychaudhuri S, Stranger BE, De Jager PL. Common risk alleles for inflammatory diseases are targets of recent positive selection.
Am J Hum Genet. 2013 Apr 4;92(4):517-29. doi: 10.1016/j.ajhg.2013.03.001.
Trynka G, Sandor C, Han B, Xu H, Stranger BE, Liu XS, Raychaudhuri S. Chromatin marks identify critical cell types for fine mapping complex trait variants. Nat Genet. 2013 Feb;45(2):124-30. doi: 10.1038/ng.2504.
Stranger BE, De Jager PL.Coordinating GWAS results with gene expression in a systems immunologic paradigm in autoimmunity.
Curr Opin Immunol. 2012 Oct;24(5):544-51. doi: 10.1016/j.coi.2012.09.002.
Stranger BE, Montgomery SB, Dimas AS, Parts L, Stegle O, Ingle CE, Sekowska M, Smith GD, Evans D, Gutierrez-Arcelus M, Price A, Raj T, Nisbett J, Nica AC, Beazley C, Durbin R, Deloukas P, Dermitzakis ET. Patterns of cis regulatory variation in diverse human populations. PLoS Genet. 2012;8(4):e1002639. doi: 10.1371/journal.pgen.1002639.
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.
- Candidate causal regulatory effects by integration of expression QTLs with complex trait genetic ass
- Chromatin marks identify critical cell types
- Chromatin marks identify critical cell types for fine mapping complex trait variants
- Common regulatory variation impacts gene expression in a cell type-dependent manner
- Common risk alleles for inflammatory diseases are targets of recent positive selection
- Coordinating GWAS results with gene expression in a systems immunologic paradigm in autoimmunity
- Extensive genetic diversity and substructuring among zebrafish strains revealed through copy number
- Gene expression levels are a target of recent natural selection in the human genome.
- Genome-Wide Association Study and Gene Expression Analysis Identifies CD84 as a Predictor
- Independent and population-specific association of risk variants at the IRGM locus with Crohn’s di
- Integrative eQTL-Based Analyses Reveal the Biology of Breast Cancer Risk Loci
- Modifier effects between regulatory and protein-coding variation
- Patterns of cis regulatory variation in diverse human populations
- Progress and promise of genome-wide association studies for human complex trait genetics
- Relative impact of nucleotide and copy number variation on gene expression phenotypes.
- Sex-biased genetic effects on gene regulation in humans
- Systems and genome-wide approaches unite to provide a route to personalized medicine.