Acute Deletion of the Glucocorticoid Receptor in Hepatocytes Disrupts Postprandial Lipid Metabolism in Male Mice

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Abstract

Hepatic lipid metabolism is highly dynamic, and disruption of several circadian transcriptional regulators results in hepatic steatosis. This includes genetic disruption of the glucocorticoid receptor (GR) as the liver develops. To address the functional role of GR in the adult liver, we used an acute hepatocyte-specific GR knockout model to study temporal hepatic lipid metabolism governed by GR at several preprandial and postprandial circadian timepoints. Lipidomics analysis revealed significant temporal lipid metabolism, where GR disruption results in impaired regulation of specific triglycerides, nonesterified fatty acids, and sphingolipids. This correlates with increased number and size of lipid droplets and mildly reduced mitochondrial respiration, most noticeably in the postprandial phase. Proteomics and transcriptomics analyses suggest that dysregulated lipid metabolism originates from pronounced induced expression of enzymes involved in fatty acid synthesis, β-oxidation, and sphingolipid metabolism. Integration of GR cistromic data suggests that induced gene expression is a result of regulatory actions secondary to direct GR effects on gene transcription.

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Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Michael Love, Wolfgang Huber, Simon Anders (2014)

In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.

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clusterProfiler 4.0: A universal enrichment tool for interpreting omics data

Tianzhi Wu, Erqiang Hu, Shuangbin Xu … (2021)

Summary Functional enrichment analysis is pivotal for interpreting high-throughput omics data in life science. It is crucial for this type of tool to use the latest annotation databases for as many organisms as possible. To meet these requirements, we present here an updated version of our popular Bioconductor package, clusterProfiler 4.0. This package has been enhanced considerably compared with its original version published 9 years ago. The new version provides a universal interface for functional enrichment analysis in thousands of organisms based on internally supported ontologies and pathways as well as annotation data provided by users or derived from online databases. It also extends the dplyr and ggplot2 packages to offer tidy interfaces for data operation and visualization. Other new features include gene set enrichment analysis and comparison of enrichment results from multiple gene lists. We anticipate that clusterProfiler 4.0 will be applied to a wide range of scenarios across diverse organisms.

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MetaboAnalyst 5.0: narrowing the gap between raw spectra and functional insights

Zhiqiang Pang, Jasmine Chong, Guangyan Zhou … (2021)

Since its first release over a decade ago, the MetaboAnalyst web-based platform has become widely used for comprehensive metabolomics data analysis and interpretation. Here we introduce MetaboAnalyst version 5.0, aiming to narrow the gap from raw data to functional insights for global metabolomics based on high-resolution mass spectrometry (HRMS). Three modules have been developed to help achieve this goal, including: (i) a LC–MS Spectra Processing module which offers an easy-to-use pipeline that can perform automated parameter optimization and resumable analysis to significantly lower the barriers to LC-MS1 spectra processing; (ii) a Functional Analysis module which expands the previous MS Peaks to Pathways module to allow users to intuitively select any peak groups of interest and evaluate their enrichment of potential functions as defined by metabolic pathways and metabolite sets; (iii) a Functional Meta-Analysis module to combine multiple global metabolomics datasets obtained under complementary conditions or from similar studies to arrive at comprehensive functional insights. There are many other new functions including weighted joint-pathway analysis, data-driven network analysis, batch effect correction, merging technical replicates, improved compound name matching, etc. The web interface, graphics and underlying codebase have also been refactored to improve performance and user experience. At the end of an analysis session, users can now easily switch to other compatible modules for a more streamlined data analysis. MetaboAnalyst 5.0 is freely available at https://www.metaboanalyst.ca . Graphical Abstract From raw data to statistical and functional insights using MetaboAnalyst 5.0.