Host-Pathogen Interactions: Circuits to Systems Symposium
Wednesday, Feb 20, 2019
8:30 am – 7:00 pm
Sanford Consortium, Roth Auditorium
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Career Development Seminar Series
Spring Quarter 2019
4:00 pm – 5:00 pm
UC San Diego, BRF2 Rm 1102
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Genetics, Bioinformatics and Systems Biology Colloquium
Thursdays, 12:00 pm – 1:00 pm
UC San Diego, Leichtag Building, Room 107
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Spatiotemporal Architecture of the Genome

Investigators: Chris Glass, Clodagh O’Shea, Trey Ideker, Bing Ren

A central challenge of molecular biology is to understand how transcriptional regulatory elements are selected from the genome thereby specifying cellular identity and cell-specific responses. The goal of this project is to use systems biology approaches and the maps-to-model paradigm to gain insights into general mechanisms responsible for the selection and function of cis-regulatory elements necessary for transcriptional responses to pathogens.

The SDCSB has previously made substantial progress in understanding how stress remodels transcriptional regulatory networks. The Ren laboratory adapted a high-throughput DNA sequencing method known as Hi-C to investigate how long range chromatin interactions regulate transcription, resulting in the striking finding that functional enhancer-gene interactions occur within megabase-sized topological domains (Jin et al., Nature 2013). The Glass laboratory used both genetic manipulations and natural genetic variations in mice to identify combinations of transcription factors that bind enhancers to affect a gene regulatory response during inflammation stress (Heinz et al., Nature 2013).  
 
 
 

 

In this project, we will map transcription factor binding sites, enhancer-promoter interactions and the 3D higher-order organization of the genome to develop models that predict how cells from different genotypes and tissues respond transcriptionally to pathogenic stimuli. Primary data sets derived from ChIP-Seq, GRO-Seq and conformation capture assays will be used to build context-dependent maps of cis-regulatory elements. We will then develop and apply novel analytical approaches to construct and test models for how enhancers and promoters are initially selected from the genome by combinations of sequence specific transcription factors, how these genomic regions subsequently acquire features of active enhancers, and how active enhancers ultimately communicate with target genes. DNA-DNA interaction networks will also be analyzed for their underlying hierarchical structure.

The Ideker lab recently developed an innovative new approach, called NeXO (Network-extracted ontologies), which identifies the complete hierarchical structure of modules embedded in a biological network and represents this hierarchy as an ontology (Dutkowski et al., Nat Biotechnol 2013). An improved version of this algorithm, called CliXO (Clique-extracted ontologies), can construct an ontology from any set of quantitative data between elements for which a pairwise similarity score can be defined (Kramer et al., Bioinformatics 2014). Hi-C experiments form such a data set, as an increasing number of reads connecting two genomic regions correlates with a closer position in 3D topological space in the nucleus. This in turn may correlate with functional similarity or cooperation, as we hypothesize that DNA elements in a single topological domain in 3D space are more likely to be functionally related. We are also devising methods to explore whether this chromatin-based ontology can be used to predict transcriptional activity.  
 

 

It is likely that viruses also target and subvert the 3D landscape of the host genome. Human adenovirus serotype Ad5 is a double stranded DNA virus that induces large-scale changes in cellular mRNA expression, epigenetic marks and nuclear morphology. The activation of viral gene promoters is exquisitely timed in concert with the systems-wide subversion of host transcription. We plan to map the host-viral genome interactions and transcriptional programs, which we predict will play a key role in determining viral tropism and replication.

 

Recent SDCSB Publications by these Investigators:

  1. Fonseca, GJ, Tao, J, Westin, EM, Duttke, SH, Spann, NJ, Strid, T et al.. Diverse motif ensembles specify non-redundant DNA binding activities of AP-1 family members in macrophages. Nat Commun. 2019;10 (1):414. doi: 10.1038/s41467-018-08236-0. PubMed PMID:30679424 PubMed Central PMC6345992.
  2. Hoeksema, MA, Glass, CK. Nature and nurture of tissue-specific macrophage phenotypes. Atherosclerosis. 2019;281 :159-167. doi: 10.1016/j.atherosclerosis.2018.10.005. PubMed PMID:30343819 PubMed Central PMC6399046.
  3. Eckhardt, M, Zhang, W, Gross, AM, Von Dollen, J, Johnson, JR, Franks-Skiba, KE et al.. Multiple Routes to Oncogenesis Are Promoted by the Human Papillomavirus-Host Protein Network. Cancer Discov. 2018;8 (11):1474-1489. doi: 10.1158/2159-8290.CD-17-1018. PubMed PMID:30209081 PubMed Central PMC6375299.
  4. Zhang, W, Ma, J, Ideker, T. Classifying tumors by supervised network propagation. Bioinformatics. 2018;34 (13):i484-i493. doi: 10.1093/bioinformatics/bty247. PubMed PMID:29949979 PubMed Central PMC6022559.
  5. Link, VM, Duttke, SH, Chun, HB, Holtman, IR, Westin, E, Hoeksema, MA et al.. Analysis of Genetically Diverse Macrophages Reveals Local and Domain-wide Mechanisms that Control Transcription Factor Binding and Function. Cell. 2018;173 (7):1796-1809.e17. doi: 10.1016/j.cell.2018.04.018. PubMed PMID:29779944 PubMed Central PMC6003872.
  6. Bui, N, Huang, JK, Bojorquez-Gomez, A, Licon, K, Sanchez, KS, Tang, SN et al.. Disruption of NSD1 in Head and Neck Cancer Promotes Favorable Chemotherapeutic Responses Linked to Hypomethylation. Mol. Cancer Ther. 2018;17 (7):1585-1594. doi: 10.1158/1535-7163.MCT-17-0937. PubMed PMID:29636367 PubMed Central PMC6030464.
  7. Muse, ED, Yu, S, Edillor, CR, Tao, J, Spann, NJ, Troutman, TD et al.. Cell-specific discrimination of desmosterol and desmosterol mimetics confers selective regulation of LXR and SREBP in macrophages. Proc. Natl. Acad. Sci. U.S.A. 2018;115 (20):E4680-E4689. doi: 10.1073/pnas.1714518115. PubMed PMID:29632203 PubMed Central PMC5960280.
  8. Zhang, W, Bojorquez-Gomez, A, Velez, DO, Xu, G, Sanchez, KS, Shen, JP et al.. A global transcriptional network connecting noncoding mutations to changes in tumor gene expression. Nat. Genet. 2018;50 (4):613-620. doi: 10.1038/s41588-018-0091-2. PubMed PMID:29610481 PubMed Central PMC5893414.
  9. Huang, JK, Carlin, DE, Yu, MK, Zhang, W, Kreisberg, JF, Tamayo, P et al.. Systematic Evaluation of Molecular Networks for Discovery of Disease Genes. Cell Syst. 2018;6 (4):484-495.e5. doi: 10.1016/j.cels.2018.03.001. PubMed PMID:29605183 PubMed Central PMC5920724.
  10. Preissl, S, Fang, R, Huang, H, Zhao, Y, Raviram, R, Gorkin, DU et al.. Single-nucleus analysis of accessible chromatin in developing mouse forebrain reveals cell-type-specific transcriptional regulation. Nat. Neurosci. 2018;21 (3):432-439. doi: 10.1038/s41593-018-0079-3. PubMed PMID:29434377 PubMed Central PMC5862073.
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