scholarly journals Integrated Analysis of Gene Expression Differences in Twins Discordant for Disease and Binary Phenotypes

2017 ◽  
Author(s):  
Sivateja Tangirala ◽  
Chirag J Patel

AbstractWhile both genes and environment contribute to phenotype, deciphering environmental contributions to phenotype is a challenge. Furthermore, elucidating how different phenotypes may share similar environmental etiologies also is challenging. One way to identify environmental influences is through a discordant monozygotic (MZ) twin study design. Here, we assessed differential gene expression in MZ discordant twin pairs (affected vs. non-affected) for seven phenotypes, including chronic fatigue syndrome, obesity, ulcerative colitis, major depressive disorder, intermittent allergic rhinitis, physical activity, and intelligence quotient, comparing the spectrum of genes differentially expressed across seven phenotypes individually. Second, we performed meta-analysis for each gene to identify commonalities and differences in gene expression signatures between the seven phenotypes. In our integrative analyses, we found that there may be a common gene expression signature (with small effect sizes) across the phenotypes; however, differences between phenotypes with respect to differentially expressed genes were more prominently featured. Therefore, defining common environmentally induced pathways in phenotypes remains elusive. We make our work accessible by providing a new database (DiscTwinExprDB: http://apps.chiragjpgroup.org/disctwinexprdb/) for investigators to study non-genotypic influence on gene expression.

2015 ◽  
Vol 309 (7) ◽  
pp. L677-L686 ◽  
Author(s):  
Georgios D. Vavougios ◽  
Evgeniy I. Solenov ◽  
Chrissi Hatzoglou ◽  
Galina S. Baturina ◽  
Liubov E. Katkova ◽  
...  

The aim of our study was to assess the differential gene expression of Parkinson protein 7 (PARK7) interactome in malignant pleural mesothelioma (MPM) using data mining techniques to identify novel candidate genes that may play a role in the pathogenicity of MPM. We constructed the PARK7 interactome using the ConsensusPathDB database. We then interrogated the Oncomine Cancer Microarray database using the Gordon Mesothelioma Study, for differential gene expression of the PARK7 interactome. In ConsensusPathDB, 38 protein interactors of PARK7 were identified. In the Gordon Mesothelioma Study, 34 of them were assessed out of which SUMO1, UBC3, KIAA0101, HDAC2, DAXX, RBBP4, BBS1, NONO, RBBP7, HTRA2, and STUB1 were significantly overexpressed whereas TRAF6 and MTA2 were significantly underexpressed in MPM patients ( network 2). Furthermore, Kaplan-Meier analysis revealed that MPM patients with high BBS1 expression had a median overall survival of 16.5 vs. 8.7 mo of those that had low expression. For validation purposes, we performed a meta-analysis in Oncomine database in five sarcoma datasets. Eight network 2 genes (KIAA0101, HDAC2, SUMO1, RBBP4, NONO, RBBP7, HTRA2, and MTA2) were significantly differentially expressed in an array of 18 different sarcoma types. Finally, Gene Ontology annotation enrichment analysis revealed significant roles of the PARK7 interactome in NuRD, CHD, and SWI/SNF protein complexes. In conclusion, we identified 13 novel genes differentially expressed in MPM, never reported before. Among them, BBS1 emerged as a novel predictor of overall survival in MPM. Finally, we identified that PARK7 interactome is involved in novel pathways pertinent in MPM disease.


2021 ◽  
Vol 22 (14) ◽  
pp. 7624
Author(s):  
Mohammad Saeed ◽  
Alejandro Ibáñez-Costa ◽  
Alejandra María Patiño-Trives ◽  
Laura Muñoz-Barrera ◽  
Eduardo Collantes Estévez ◽  
...  

Objectives: This study employed genetic and functional analyses using OASIS meta-analysis of multiple existing GWAS and gene-expression datasets to identify novel SLE genes. Methods: Four hundred and ten genes were mapped using SNIPPER to 30 SLE GWAS loci and investigated for expression in three SLE GEO-datasets and the Cordoba GSE50395-dataset. Blood eQTL for significant SNPs in SLE loci and STRING for functional pathways of differentially expressed genes were used. Confirmatory qPCR on SLE monocytes was performed. The entire 12p11 locus was investigated for genetic association using two additional GWAS. Expression of 150 genes at this locus was assessed. Based on this significance, qPCRs for DNM1L and KRAS were performed. Results: Fifty genes were differentially expressed in at least two SLE GEO-datasets, with all probes directionally aligned. DDX11, an RNA helicase involved in genome stability, was downregulated in both GEO and Cordoba datasets. The most significant SNP, rs3741869 in OASIS locus 12p11.21, containing DDX11, was a cis-eQTL regulating DDX11 expression. DDX11 was found repressed. The entire 12p11 locus showed three association peaks. Gene expression in GEO datasets identified DNM1L and KRAS, besides DDX11. Confirmatory qPCR validated DNM1L as an SLE susceptibility gene. DDX11, DNM1L and KRAS interact with each other and multiple known SLE genes including STAT1/STAT4 and major components of IFN-dependent gene expression, and are responsible for signal transduction of cytokines, hormones, and growth-factors, deregulation of which is involved in SLE-development. Conclusion: A genomic convergence approach with OASIS analysis of multiple GWAS and expression datasets identified DDX11 and DNM1L as novel SLE-genes, the expression of which is altered in monocytes from SLE patients. This study lays the foundation for understanding the pathogenic involvement of DDX11 and DNM1L in SLE by identifying them using a systems-biology approach, while the 12p11 locus harboring these genes was previously missed by four independent GWAS.


Blood ◽  
2011 ◽  
Vol 118 (26) ◽  
pp. 6849-6859 ◽  
Author(s):  
Kathryn T. Bieging ◽  
Kamonwan Fish ◽  
Subbarao Bondada ◽  
Richard Longnecker

AbstractThe link between EBV infection and Burkitt lymphoma (BL) is strong, but the mechanism underlying that link has been elusive. We have developed a mouse model for EBV-associated BL in which LMP2A, an EBV latency protein, and MYC are expressed in B cells. Our model has demonstrated the ability of LMP2A to accelerate tumor onset, increase spleen size, and bypass p53 inactivation. Here we describe the results of total gene expression analysis of tumor and pretumor B cells from our transgenic mouse model. Although we see many phenotypic differences and changes in gene expression in pretumor B cells, the transcriptional profiles of tumor cells from LMP2A/λ-MYC and λ-MYC mice are strikingly similar, with fewer than 20 genes differentially expressed. We evaluated the functional significance of one of the most interesting differentially expressed genes, Egr1, and found that it was not required for acceleration of tumor onset by LMP2A. Our studies demonstrate the remarkable ability of LMP2A to affect the pretumor B-cell phenotype and tumorigenesis without substantially altering gene expression in tumor cells.


Viruses ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 244 ◽  
Author(s):  
Antonio Victor Campos Coelho ◽  
Rossella Gratton ◽  
João Paulo Britto de Melo ◽  
José Leandro Andrade-Santos ◽  
Rafael Lima Guimarães ◽  
...  

HIV-1 infection elicits a complex dynamic of the expression various host genes. High throughput sequencing added an expressive amount of information regarding HIV-1 infections and pathogenesis. RNA sequencing (RNA-Seq) is currently the tool of choice to investigate gene expression in a several range of experimental setting. This study aims at performing a meta-analysis of RNA-Seq expression profiles in samples of HIV-1 infected CD4+ T cells compared to uninfected cells to assess consistently differentially expressed genes in the context of HIV-1 infection. We selected two studies (22 samples: 15 experimentally infected and 7 mock-infected). We found 208 differentially expressed genes in infected cells when compared to uninfected/mock-infected cells. This result had moderate overlap when compared to previous studies of HIV-1 infection transcriptomics, but we identified 64 genes already known to interact with HIV-1 according to the HIV-1 Human Interaction Database. A gene ontology (GO) analysis revealed enrichment of several pathways involved in immune response, cell adhesion, cell migration, inflammation, apoptosis, Wnt, Notch and ERK/MAPK signaling.


2016 ◽  
Vol 45 (1) ◽  
pp. e1-e1 ◽  
Author(s):  
Timothy E. Sweeney ◽  
Winston A. Haynes ◽  
Francesco Vallania ◽  
John P. Ioannidis ◽  
Purvesh Khatri

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