Person:
Platig, John

Profile Picture

Email Address

AA Acceptance Date

Birth Date

Research Projects

Organizational Units

Job Title

Last Name

Platig

First Name

John

Name

Platig, John
Author's Publications: search.filters.isAuthorOfPublication.b6d3cceb-8d8e-4664-bd9b-f6d0e476971d

Search Results

Now showing 1 - 4 of 4
  • Thumbnail Image
    Publication
    Regulatory network changes between cell lines and their tissues of origin
    (BioMed Central, 2017) Lopes-Ramos, Camila; Paulson, Joseph; Chen, Cho-Yi; Kuijjer, Marieke; Fagny, Maud; Platig, John; Sonawane, Abhijeet; Demeo, Dawn; Quackenbush, John; Glass, Kimberly
    Background: Cell lines are an indispensable tool in biomedical research and often used as surrogates for tissues. Although there are recognized important cellular and transcriptomic differences between cell lines and tissues, a systematic overview of the differences between the regulatory processes of a cell line and those of its tissue of origin has not been conducted. The RNA-Seq data generated by the GTEx project is the first available data resource in which it is possible to perform a large-scale transcriptional and regulatory network analysis comparing cell lines with their tissues of origin. Results: We compared 127 paired Epstein-Barr virus transformed lymphoblastoid cell lines (LCLs) and whole blood samples, and 244 paired primary fibroblast cell lines and skin samples. While gene expression analysis confirms that these cell lines carry the expression signatures of their primary tissues, albeit at reduced levels, network analysis indicates that expression changes are the cumulative result of many previously unreported alterations in transcription factor (TF) regulation. More specifically, cell cycle genes are over-expressed in cell lines compared to primary tissues, and this alteration in expression is a result of less repressive TF targeting. We confirmed these regulatory changes for four TFs, including SMAD5, using independent ChIP-seq data from ENCODE. Conclusions: Our results provide novel insights into the regulatory mechanisms controlling the expression differences between cell lines and tissues. The strong changes in TF regulation that we observe suggest that network changes, in addition to transcriptional levels, should be considered when using cell lines as models for tissues. Electronic supplementary material The online version of this article (10.1186/s12864-017-4111-x) contains supplementary material, which is available to authorized users.
  • Thumbnail Image
    Publication
    Bipartite Community Structure of eQTLs
    (Public Library of Science, 2016) Platig, John; Castaldi, Peter; Demeo, Dawn; Quackenbush, John
    Genome Wide Association Studies (GWAS) and expression quantitative trait locus (eQTL) analyses have identified genetic associations with a wide range of human phenotypes. However, many of these variants have weak effects and understanding their combined effect remains a challenge. One hypothesis is that multiple SNPs interact in complex networks to influence functional processes that ultimately lead to complex phenotypes, including disease states. Here we present CONDOR, a method that represents both cis- and trans-acting SNPs and the genes with which they are associated as a bipartite graph and then uses the modular structure of that graph to place SNPs into a functional context. In applying CONDOR to eQTLs in chronic obstructive pulmonary disease (COPD), we found the global network “hub” SNPs were devoid of disease associations through GWAS. However, the network was organized into 52 communities of SNPs and genes, many of which were enriched for genes in specific functional classes. We identified local hubs within each community (“core SNPs”) and these were enriched for GWAS SNPs for COPD and many other diseases. These results speak to our intuition: rather than single SNPs influencing single genes, we see groups of SNPs associated with the expression of families of functionally related genes and that disease SNPs are associated with the perturbation of those functions. These methods are not limited in their application to COPD and can be used in the analysis of a wide variety of disease processes and other phenotypic traits.
  • Thumbnail Image
    Publication
    Multisystem Analysis of Mycobacterium tuberculosis Reveals Kinase-Dependent Remodeling of the Pathogen-Environment Interface
    (American Society for Microbiology, 2018) Carette, Xavier; Platig, John; Young, David C.; Helmel, Michaela; Young, Albert T.; Wang, Zhe; Potluri, Lakshmi-Prasad; Moody, Cameron Stuver; Zeng, Jumei; Prisic, Sladjana; Paulson, Joseph; Muntel, Jan; Madduri, Ashoka V. R.; Velarde, Jorge; Mayfield, Jacob A.; Locher, Christopher; Wang, Tiansheng; Quackenbush, John; Rhee, Kyu Y.; Moody, David; Steen, Hanno; Husson, Robert
    ABSTRACT Tuberculosis is the leading killer among infectious diseases worldwide. Increasing multidrug resistance has prompted new approaches for tuberculosis drug development, including targeted inhibition of virulence determinants and of signaling cascades that control many downstream pathways. We used a multisystem approach to determine the effects of a potent small-molecule inhibitor of the essential Mycobacterium tuberculosis Ser/Thr protein kinases PknA and PknB. We observed differential levels of phosphorylation of many proteins and extensive changes in levels of gene expression, protein abundance, cell wall lipids, and intracellular metabolites. The patterns of these changes indicate regulation by PknA and PknB of several pathways required for cell growth, including ATP synthesis, DNA synthesis, and translation. These data also highlight effects on pathways for remodeling of the mycobacterial cell envelope via control of peptidoglycan turnover, lipid content, a SigE-mediated envelope stress response, transmembrane transport systems, and protein secretion systems. Integrated analysis of phosphoproteins, transcripts, proteins, and lipids identified an unexpected pathway whereby threonine phosphorylation of the essential response regulator MtrA decreases its DNA binding activity. Inhibition of this phosphorylation is linked to decreased expression of genes for peptidoglycan turnover, and of genes for mycolyl transferases, with concomitant changes in mycolates and glycolipids in the cell envelope. These findings reveal novel roles for PknA and PknB in regulating multiple essential cell functions and confirm that these kinases are potentially valuable targets for new antituberculosis drugs. In addition, the data from these linked multisystems provide a valuable resource for future targeted investigations into the pathways regulated by these kinases in the M. tuberculosis cell.
  • Thumbnail Image
    Publication
    Tissue-aware RNA-Seq processing and normalization for heterogeneous and sparse data
    (BioMed Central, 2017) Paulson, Joseph; Chen, Cho-Yi; Lopes-Ramos, Camila; Kuijjer, Marieke; Platig, John; Sonawane, Abhijeet; Fagny, Maud; Glass, Kimberly; Quackenbush, John
    Background: Although ultrahigh-throughput RNA-Sequencing has become the dominant technology for genome-wide transcriptional profiling, the vast majority of RNA-Seq studies typically profile only tens of samples, and most analytical pipelines are optimized for these smaller studies. However, projects are generating ever-larger data sets comprising RNA-Seq data from hundreds or thousands of samples, often collected at multiple centers and from diverse tissues. These complex data sets present significant analytical challenges due to batch and tissue effects, but provide the opportunity to revisit the assumptions and methods that we use to preprocess, normalize, and filter RNA-Seq data – critical first steps for any subsequent analysis. Results: We find that analysis of large RNA-Seq data sets requires both careful quality control and the need to account for sparsity due to the heterogeneity intrinsic in multi-group studies. We developed Yet Another RNA Normalization software pipeline (YARN), that includes quality control and preprocessing, gene filtering, and normalization steps designed to facilitate downstream analysis of large, heterogeneous RNA-Seq data sets and we demonstrate its use with data from the Genotype-Tissue Expression (GTEx) project. Conclusions: An R package instantiating YARN is available at http://bioconductor.org/packages/yarn. Electronic supplementary material The online version of this article (10.1186/s12859-017-1847-x) contains supplementary material, which is available to authorized users.