REV-ERBalpha influences stability and nuclear localization of the glucocorticoid receptor

We report here that REV-ERBalpha influences nuclear localization of the glucocorticoid receptor and vice versa. As a consequence these two nuclear receptors influence each others transcriptome. REV-ERBalpha (Nr1d1) is a nuclear receptor that is part of the circadian clock mechanism and regulates metabolism and inflammatory processes. The glucocorticoid receptor (GR, Nr3c1) influences similar processes, but is not part of the circadian clock mechanism although glucocorticoid signaling affects resetting of the circadian clock in peripheral tissues. Because of their similar impact on physiological processes we studied the interplay between these two nuclear receptors. We found that REV-ERBalpha competes with GR for binding to HSP90, a chaperone responsible for the activation of substrate proteins to ensure survival of a cell. This competition affected stability and nuclear localization of GR, thereby affecting GR target gene expression such as I kappa beta and alcohol dehydrogenase1 (Adh1). Our findings highlight an important interplay between two nuclear receptors that influence each others transcriptional potential indicating that the transcriptional landscape is strongly dependent on dynamic processes at the protein level. In this dataset, we isolated livers at Zeitgeber time (ZT) 8 and ZT20 of wild type and Rev-erb alpha knock-out animals. Liver samples were immediately flash frozen in liquid N2 and stored at 80°C. RNA was extracted using NucleoSpin RNA (Machery-Nagel, Duren, Germany) according to the instructions of the manufacturer. Quality of the RNA samples was analysed with a spectrophotometer, agarose gel electrophoresis and reverse transcription-PCR. Library construction starting from the poly(A)-tail and multiplexing was performed according to the instructions of the manufacturer (Illumina). The samples were organized as follows: Three replicas (1-WT, 2-WT, 3-WT) correspond to genotype WT at ZT8. Three replicas (4-Rev, 5-Rev, 6-Rev) correspond to genotype Rev-/- at ZT8. Three replicas (7-WT, 8-WT, 9-WT) correspond to genotype WT at ZT20. Three replicas (10-Rev, 11-Rev, 12-Rev) correspond to genotypeRev-/- at ZT20. For the experiment, complementary DNA (cDNA) libraries were barcoded using Illumina primers and loaded onto one lane of an IlluminaHS2000 machine. cDNA libraries were diluted and loaded onto each lane. The samples were sequenced for a maximum sequencing length of 75 bp. Sequences were aligned to the mouse genome (UCSC version mm10 database). Numbers of the sequences obtained for each library can be found in Supplementary Table 3. Sequences (fastq format) were mapped with Tophat (Trapnell, C. 2009), uniquely mapped sequences from the output files (bam format) were then used for further analysis, percentage of the mapping obtained for each sample can be found in Supplementary Table 3. For all files the reads were counted with HTSeq-count using the following criteria: samtools view sample.bam | htseq-count -m union -a 10 -s no -i gene_name Mus_Musculus.gtf > sample_counts.txt Tests for differential expression between the samples were performed in R software (R Core Team, 2014 http://www.R-project.org/) using the DESeq2 package (Version 1.6.3) (Love, M. 2014). A threshold on the corrected P value was used to call for differentially expressed genes (P.adjust<0.05).本研究报道，REV-ERBα（REV-ERBalpha）可调控糖皮质激素受体（glucocorticoid receptor, GR）的核定位，反之亦然。因此，这两种核受体可相互调控对方的转录组。REV-ERBα（Nr1d1）是一种核受体，参与生物钟调控机制，并可调控代谢与炎症过程。糖皮质激素受体（GR, Nr3c1）可调控类似的生理过程，但并不参与生物钟调控机制，尽管糖皮质激素信号可影响外周组织的生物钟重置。鉴于二者对生理过程的调控作用相似，本研究探究了这两种核受体之间的相互作用。本研究发现，REV-ERBα可与GR竞争性结合HSP90——一种负责激活底物蛋白以维持细胞存活的分子伴侣。这种竞争会影响GR的稳定性与核定位，进而调控GR靶基因的表达，例如IκB（I kappa beta）与乙醇脱氢酶1（alcohol dehydrogenase1, Adh1）。本研究结果揭示了两种可相互调控转录潜能的核受体之间的重要相互作用，表明转录组景观在很大程度上依赖于蛋白质层面的动态调控过程。本数据集采集了野生型（wild type, WT）与Rev-erbα敲除（Rev-erb alpha knock-out, Rev-/-）小鼠在授时因子时间（Zeitgeber time, ZT）8与ZT20时的肝脏组织。肝脏样本经液氮快速速冻后，于-80℃条件下保存。总RNA提取采用NucleoSpin RNA试剂盒（Machery-Nagel公司，德国迪伦），严格遵循产品说明书操作。采用分光光度法、琼脂糖凝胶电泳与逆转录PCR对RNA样本的质量进行检测。以poly(A)尾为起点构建文库并进行多重标记的流程，严格按照Illumina公司的产品说明书执行。样本分组如下：3个生物学重复样本（1-WT、2-WT、3-WT）对应ZT8时的野生型样本；3个生物学重复样本（4-Rev、5-Rev、6-Rev）对应ZT8时的Rev-/-样本；3个生物学重复样本（7-WT、8-WT、9-WT）对应ZT20时的野生型样本；3个生物学重复样本（10-Rev、11-Rev、12-Rev）对应ZT20时的Rev-/-样本。实验中，采用Illumina引物对互补DNA（complementary DNA, cDNA）文库进行条形码标记，随后将文库加载至Illumina HS2000测序仪的一个测序通道中。将cDNA文库稀释后加载至各测序通道，设置测序读长上限为75 bp进行测序。将测序序列比对至小鼠基因组（UCSC数据库mm10版本）。各文库的测序序列总数详见补充表3。采用Tophat工具（Trapnell等, 2009）对fastq格式的序列进行比对，提取输出文件中唯一比对的bam格式序列用于后续分析；各样本的比对率详见补充表3。采用HTSeq-count工具对所有文件的reads进行计数，具体命令如下：samtools view sample.bam | htseq-count -m union -a 10 -s no -i gene_name Mus_Musculus.gtf > sample_counts.txt。采用R软件（R开发核心团队, 2014, http://www.R-project.org/）中的DESeq2包（版本1.6.3）（Love等, 2014）进行样本间的差异表达分析。以校正后P值（P.adjust<0.05）作为差异表达基因的筛选阈值。