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dc.contributor.authorHe, Yuqi
dc.contributor.authorGong, Lei
dc.contributor.authorFang, Yaping
dc.contributor.authorZhan, Qi
dc.contributor.authorLiu, Hui-Xin
dc.contributor.authorLu, Yanliu
dc.contributor.authorGuo, Grace L.
dc.contributor.authorLehman-McKeeman, Lois
dc.contributor.authorFang, Jianwen
dc.contributor.authorWan, Yu-Jui Yvonne
dc.date.accessioned2014-04-18T14:40:42Z
dc.date.available2014-04-18T14:40:42Z
dc.date.issued2013-08-28
dc.identifier.citationHe, Yuqi, Lei Gong, Yaping Fang, Qi Zhan, Hui-Xin Liu, Yanliu Lu, Grace L Guo, Lois Lehman-McKeeman, Jianwen Fang, and Yu-Jui Yvonne Wan. 2013. “The Role of Retinoic Acid in Hepatic Lipid Homeostasis Defined by Genomic Binding and Transcriptome Profiling.” BMC Genomics 14 . http://dx.doi.org/10.1186/1471-2164-14-575
dc.identifier.urihttp://hdl.handle.net/1808/13556
dc.description.abstractBackground: The eyes and skin are obvious retinoid target organs. Vitamin A deficiency causes night blindness and retinoids are widely used to treat acne and psoriasis. However, more than 90% of total body retinol is stored in liver stellate cells. In addition, hepatocytes produce the largest amount of retinol binding protein and cellular retinoic acid binding protein to mobilize retinol from the hepatic storage pool and deliver retinol to its receptors, respectively. Furthermore, hepatocytes express the highest amount of retinoid x receptor alpha (RXRα) among all the cell types. Surprisingly, the function of endogenous retinoids in the liver has received very little attention. Results: Based on the data generated from chromatin immunoprecipitation followed by sequencing, the global DNA binding of transcription factors including retinoid x receptor α (RXRα) along with its partners i.e. retinoic acid receptor α (RARα), pregnane x receptor (PXR), liver x receptor (LXR), farnesoid x receptor (FXR), and peroxisome proliferator-activated receptor α (PPARα) has been established. Based on the binding, functional annotation illustrated the role of those receptors in regulating hepatic lipid homeostasis. To correlate the DNA binding data with gene expression data, the expression patterns of 576 genes that regulate lipid homeostasis were studied in wild type and liver RXRα-null mice treated with and without RA. The data showed that RA treatment and RXRα-deficiency had opposite effects in regulating lipid homeostasis. A subset of genes (114), which could clearly differentiate the effect of ligand treatment and receptor deficiency, were selected for further functional analysis. The expression data suggested that RA treatment could produce unsaturated fatty acids and induce triglyceride breakdown, bile acid secretion, lipolysis, and retinoids elimination. In contrast, RXRα deficiency might induce the synthesis of saturated fatty acids, triglyceride, cholesterol, bile acids, and retinoids. In addition, DNA binding data indicated extensive cross-talk among RARα, PXR, LXR, FXR, and PPARα in regulating those RA/RXRα-dependent gene expression levels. Moreover, RA reduced serum cholesterol, triglyceride, and bile acid levels in mice. Conclusions: We have characterized the role of hepatic RA for the first time. Hepatic RA mediated through RXRα and its partners regulates lipid homeostasis.
dc.publisherBioMed Central
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.rights.urihttp://creativecommons.org/licenses/by/2.0
dc.subjectNuclear Receptor
dc.subjectRetinoids X Receptor
dc.subjectRetinoic Acid Receptor
dc.subjectFarnesnoid X Receptor
dc.subjectPeroxisomal Proliferator-activated Receptor α
dc.subjectLiver X Receptor
dc.subjectPregnane X Receptor
dc.subjectChromatin Immunoprecipitation
dc.subjectSequencing
dc.subjectMicroarray
dc.titleThe role of retinoic acid in hepatic lipid homeostasis defined by genomic binding and transcriptome profiling
dc.typeArticle
kusw.kuauthorFang, Yaping
kusw.kudepartmentApplied Bioinformatics Laboratory
kusw.oastatusfullparticipation
dc.identifier.doi10.1186/1471-2164-14-575
kusw.oaversionScholarly/refereed, publisher version
kusw.oapolicyThis item meets KU Open Access policy criteria.
dc.rights.accessrightsopenAccess


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This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's license is described as: This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.