Reproducibility enhancement and differential expression of non predefined functional gene sets in human genome

Silva, Samoel Renan Mello da; Perrone, Gabriel C.; Dinis, J.; Almeida, Rita Maria Cunha de

doi:10.1186/1471-2164-15-1181

Cited by 13 publications

(15 citation statements)

References 35 publications

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“…We obtained microarray data for genome-wide gene expression for all cell lines in triplicate. We then analyzed the resulting data using three different, complementary methods: single gene expression analysis using QIAGEN’s Ingenuity Pathway Analysis (IPA QIAGEN Redwood City), Gene Set Enrichment Analysis (GSEA) [26], and the transcriptogram method [22, 23, 27]. …”

Section: Resultsmentioning

confidence: 99%

“…The de Almeida laboratory developed transcriptogram whole-genome gene expression data analysis to identify perturbed molecular networks and pathways more sensitively than conventional gene-chip analysis methods [22–24]. Transcriptogram analysis orders genes into a list using a Monte Carlo simulation that minimizes the distance within the list between associated gene products, so proximity in the list correlates with the degree of co-participation in biological processes.…”

Section: Introductionmentioning

confidence: 99%

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Transcriptome analysis reveals manifold mechanisms of cyst development in ADPKD

et al. 2016

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BackgroundAutosomal dominant polycystic kidney disease (ADPKD) causes progressive loss of renal function in adults as a consequence of the accumulation of cysts. ADPKD is the most common genetic cause of end-stage renal disease. Mutations in polycystin-1 occur in 87% of cases of ADPKD and mutations in polycystin-2 are found in 12% of ADPKD patients. The complexity of ADPKD has hampered efforts to identify the mechanisms underlying its pathogenesis. No current FDA (Federal Drug Administration)-approved therapies ameliorate ADPKD progression.ResultsWe used the de Almeida laboratory’s sensitive new transcriptogram method for whole-genome gene expression data analysis to analyze microarray data from cell lines developed from cell isolates of normal kidney and of both non-cystic nephrons and cysts from the kidney of a patient with ADPKD. We compared results obtained using standard Ingenuity Volcano plot analysis, Gene Set Enrichment Analysis (GSEA) and transcriptogram analysis. Transcriptogram analysis confirmed the findings of Ingenuity, GSEA, and published analysis of ADPKD kidney data and also identified multiple new expression changes in KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways related to cell growth, cell death, genetic information processing, nucleotide metabolism, signal transduction, immune response, response to stimulus, cellular processes, ion homeostasis and transport and cofactors, vitamins, amino acids, energy, carbohydrates, drugs, lipids, and glycans. Transcriptogram analysis also provides significance metrics which allow us to prioritize further study of these pathways.ConclusionsTranscriptogram analysis identifies novel pathways altered in ADPKD, providing new avenues to identify both ADPKD’s mechanisms of pathogenesis and pharmaceutical targets to ameliorate the progression of the disease.Electronic supplementary materialThe online version of this article (doi:10.1186/s40246-016-0095-x) contains supplementary material, which is available to authorized users.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Transcriptome analysis reveals manifold mechanisms of cyst development in ADPKD

et al. 2016

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“…230,231 Still, identifying the optimal genetic background and understanding how expression of sets of genes over time drives (or allows) accommodation to occur will require a more incisive analysis, probably both GWAS and dynamic gene expression. 232,233 The more proximal consideration, however, is that pigs, like humans, undoubtedly vary greatly in the levels of baseline and induced resistance to immune and inflammatory injury. Differences in genetic background thus may confound efforts to compare efficacy of therapeutic regimens or genetic manipulations of xenografts from distinct sources.…”

Section: Baseline and Induced Resistance To Injury (Accommodation)mentioning

confidence: 99%

Xenotransplantation: Progress Along Paths Uncertain from Models to Application

2018

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For more than a century, transplantation of tissues and organs from animals into man, xenotransplantation, has been viewed as a potential way to treat disease. Ironically, interest in xenotransplantation was fueled especially by successful application of allotransplantation, that is, transplantation of human tissue and organs, as a treatment for a variety of diseases, especially organ failure because scarcity of human tissues limited allotransplantation to a fraction of those who could benefit. In principle, use of animals such as pigs as a source of transplants would allow transplantation to exert a vastly greater impact than allotransplantation on medicine and public health. However, biological barriers to xenotransplantation, including immunity of the recipient, incompatibility of biological systems, and transmission of novel infectious agents, are believed to exceed the barriers to allotransplantation and presently to hinder clinical applications. One way potentially to address the barriers to xenotransplantation is by genetic engineering animal sources. The last 2 decades have brought progressive advances in approaches that can be applied to genetic modification of large animals. Application of these approaches to genetic engineering of pigs has contributed to dramatic improvement in the outcome of experimental xenografts in nonhuman primates and have encouraged the development of a new type of xenograft, a reverse xenograft, in which human stem cells are introduced into pigs under conditions that support differentiation and expansion into functional tissues and potentially organs. These advances make it appropriate to consider the potential limitation of genetic engineering and of current models for advancing the clinical applications of xenotransplantation and reverse xenotransplantation.

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“…Transcriptograms provide a high-level visualization of significant changes in gene expression and have proved useful in identifying relationships between pathways in fungi [8,9], plants [10,11], and humans [12,13,7]. The Transcriptogramer software tool is freely available for download at https://lief.if.ufrgs.br/pub/biosoftwarestranscriptogramer/ and has a Bioconductor application [14].…”

Section: Introductionmentioning

confidence: 99%

Transcriptogram analysis reveals relationship between viral titer and gene sets responses during Corona-virus infection

Almeida

Thomas

Glazier

2020

Preprint

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To understand the difference between benign and severe outcomes after Coronavirus infection, we urgently need ways to clarify and quantify the time course of tissue and immune responses. Here we re-analyze 72-hour time-series microarrays generated in 2013 by Sims and collaborators for SARS-CoV-1 in vitro infection of a human lung epithelial cell line. Using a Transcriptogram-based top-down approach, we identified three major, differentially-expressed gene sets comprising 219 mainly immune-response-related genes. We identified timescales for alterations in mitochondrial activity, signaling and transcription regulation of the innate and adaptive immune systems and their relationship to viral titer. At the individual-gene level, EGR3 was significantly upregulated in infected cells. Similar activation in T-cells and fibroblasts in infected lung could explain the T-cell anergy and eventual fibrosis seen in SARS-CoV-1 infection. The methods can be applied to RNA data sets for SARS-CoV-2 to investigate the origin of differential responses in different tissue types, or due to immune or preexisting conditions or to compare cell culture, organoid culture, animal models and human-derived samples.

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Reproducibility enhancement and differential expression of non predefined functional gene sets in human genome

Cited by 13 publications

References 35 publications

Transcriptome analysis reveals manifold mechanisms of cyst development in ADPKD

Transcriptome analysis reveals manifold mechanisms of cyst development in ADPKD

Xenotransplantation: Progress Along Paths Uncertain from Models to Application

Transcriptogram analysis reveals relationship between viral titer and gene sets responses during Corona-virus infection

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