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Correlation guided Network Integration (CoNI) reveals novel genes affecting hepatic metabolism

ABSTRACT: Correlation guided Network Integration (CoNI) reveals novel genes affecting hepatic metabolism

PROVIDER: PRJNA573893 | ENA |

REPOSITORIES: ENA

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Correlation guided Network Integration (CoNI) reveals novel genes affecting hepatic metabolism

Project description:Obesity-induced ectopic fat disposition in the liver is a major risk factor in the pathogenesis of type 2 diabetes as it impairs hepatic insulin sensitivity, a crucial component of whole body glucose homeostasis; however molecular mechanisms remain largely elusive. Understanding the pathogenesis of fatty liver, including the identification of novel genetic regulators that are involved in the regulation of liver metabolism under excess energy supply, is crucial for the development and implementation of efficient prevention and treatment strategies. We here developed a new method to integrate metabolomics and transcriptomics data based on pairwise correlation analysis of metabolites coupled to partial correlation combining the metabolite correlations with the transcript expression profiles followed by the construction of undirected, weighted graphs.This Correlation based Network Integration (CoNI) approach was applied to liver metabolome and transcriptome datasets of lean and HFD-fed obese mice to unravel previously hidden local regulator genes (LRG). The selected candidate genes were validated by transcriptome-proteome correlation analysis, by association studies with liver lipid metabolism in humans and by analysis of cellular metabolite levels after siRNA knockdown. Overall, the new bioinformatic CoNI approach for Omics datasets allowed us to identify genes regulating metabolic networks in livers of obese mice that if solely analyzing the transcriptome dataset would have remained hidden.

2021-07-09 | GSE137923 | GEO

Correlation guided Network Integration (CoNI) reveals novel genes affecting hepatic metabolism.

Project description:ObjectiveTechnological advances have brought a steady increase in the availability of various types of omics data, from genomics to metabolomics. Integrating these multi-omics data is a chance and challenge for systems biology; yet, tools to fully tap their potential remain scarce.MethodsWe present here a fully unsupervised and versatile correlation-based method - termed Correlation guided Network Integration (CoNI) - to integrate multi-omics data into a hypergraph structure that allows for the identification of effective modulators of metabolism. Our approach yields single transcripts of potential relevance that map to specific, densely connected, metabolic subgraphs or pathways.ResultsBy applying our method on transcriptomics and metabolomics data from murine livers under standard Chow or high-fat diet, we identified eleven genes with potential regulatory effects on hepatic metabolism. Five candidates, including the hepatokine INHBE, were validated in human liver biopsies to correlate with diabetes-related traits such as overweight, hepatic fat content, and insulin resistance (HOMA-IR).ConclusionOur method's successful application to an independent omics dataset confirmed that the novel CoNI framework is a transferable, entirely data-driven, flexible, and versatile tool for multiple omics data integration and interpretation.

| S-EPMC8361260 | biostudies-literature

Targeted DNA integration in human cells without double-strand breaks using CRISPR RNA-guided transposases

Project description:Targeted DNA integration in human cells without double-strand breaks using CRISPR RNA-guided transposases

| PRJNA925176 | ENA

Chronic stress alters hepatic metabolism and thermodynamic respiratory efficiency affecting epigenetics in C57BL/6 mice

Project description:Chronic stress alters hepatic metabolism and thermodynamic respiratory efficiency affecting epigenetics in C57BL/6 mice

| PRJNA986046 | ENA

Generation of integration-free induced hepatocytes from mouse fibroblasts

Project description:Previous studies demonstrated that hepatocyte-specific transcription factors could directly convert fibroblasts into functional hepatocytes-like cells, namely induced hepatocytes (iHeps) using viral systems. However, viral integration into host genome causes insertional mutation and risk of tumorigenecity. we showed iHeps could be generated from MEFs using the integration-free system. They were expandable in vitro and showed hepatic features, similar to primary hepatocytes. iHeps_G4H1F3 transfected (Episomal vectors) and iHeps_G4H1F3 transduced (pMXs) were duplicate, respectively. MEFs and primary hepatocytes were used as negative and positive controls, respectively.

2015-03-27 | E-GEOD-67362 | biostudies-arrayexpress

Generation of integration-free induced hepatocytes from mouse fibroblasts

2015-03-27 | GSE67362 | GEO

Correlation Between RECIST, Morphologic Response by CT- Histopathologic Response in Hepatic Metastasis Secondary to Colorectal Cancer

Project description:The purpose of this study is to to evaluate the correlation of overall objective response according to RECIST v1.1. criteria evaluated by conventional imaging techniques, morphologic response by CT, and histopathologic response in patients with resectable hepatic metastasis secondary to colorectal cancer treated with bevacizumab in combination with XELOX.

| 2117357 | ecrin-mdr-crc

MALDI-imaging-guided transcriptomics

Project description:MALDI-imaging-guided Transcriptomics

| PRJEB69276 | ENA

HIV-1 integrase variants retarget viral integration and are associated with disease progression in a chronic infection cohort.

Project description:Distinct integration patterns of different retroviruses have puzzled virologists for over 20 years. The viral integrase (IN), as part of the intasome complex, docks onto the target DNA (tDNA) and catalyzes the insertion of the viral genome into the host chromatin. We identified retroviral IN amino acids directly contacting tDNA bases and affecting the local integration site sequence biases. These residues also determine the propensity of the virus to integrate into flexible tDNA sequences. Remarkably, natural polymorphisms INS119G and INR231G retarget viral integration away from gene dense regions, without affecting the interaction with the lentiviral tethering cofactor LEDGF/p75 (PSIP1). Precisely these variants were associated with rapid disease progression in a chronic HIV-1 subtype C infection cohort. These findings link integration site selection to virulence and viral evolution but also to the host immune response and antiretroviral therapy, since HIV-1 IN119 is under selection by HLA alleles and integrase inhibitors. LEDGF/p75 (PSIP1) ChIP-Seq using A300-848 antibody (recognizes p75 isoform) and input control in primary CD4+ T-cells

2015-01-26 | E-GEOD-61003 | biostudies-arrayexpress

Chronic stress alters hepatic metabolism and thermodynamic respiratory efficiency affecting epigenetics in C57BL/6 mice [MeDIP-seq]

Project description:Chronic stress alters hepatic metabolism and thermodynamic respiratory efficiency affecting epigenetics in C57BL/6 mice [MeDIP-seq]

| PRJNA986055 | ENA

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