biostudies-arrayexpressSusanne MandrupMus musculushttps://www.ebi.ac.uk/biostudies/studies/E-GEOD-35262The liver X receptors (LXRs) are nuclear receptors that form permissive heterodimers with retinoid X receptor (RXR) and are important regulators of lipid metabolism in the liver. We have recently shown that RXR agonist-induced hypertriglyceridemia and hepatic steatosis in mice is dependent on LXR and correlates with an LXR-dependent hepatic induction of lipogenic genes. To further investigate the role of RXR and LXR in the regulation of hepatic gene expression, we have mapped the ligand-regulated genome-wide binding of these factors in mouse liver. We find that the RXR agonist bexarotene primarily increases the genomic binding of RXR, whereas the LXR agonist T0901317 greatly increases both LXR and RXR binding. Functional annotation of putative direct LXR target genes revealed a significant association with classical LXR-regulated pathways as well as PPAR signaling pathways, and subsequent ChIP-seq mapping of PPARM-NM-1 binding demonstrated binding of PPARM-NM-1 to 71-88% of the identified LXR:RXR binding sites. Sequence analysis of shared binding regions combined with sequential ChIP on selected sites indicate that LXR:RXR and PPARM-NM-1:RXR bind to degenerate response elements in a mutually exclusive manner. Together our findings suggest extensive and unexpected cross-talk between hepatic LXR and PPARM-NM-1 at the level of binding to shared genomic sites LXR, RXR, PPARalpha and RNA Polymerase II ChIP-seq on livers from female C57BL/6 wild-type and/or LXRM-NM-1/M-NM-2-deficient mice (13 weeks of age, n=1) treated by oral gavage once daily for 14 days with the RXR agonist bexarotene (100 mg/kg body weight [mpk], in 1% carboxymethylcellulose), the LXR agonist T0901317 (T09, 30 mpk) or vehicle alone.biostudies-arrayexpressSample Processing - Female C57BL/6 wild-type and LXRM-NM-1/M-NM-2-deficient mice (13 weeks of age) were treated by oral gavage once daily for 14 days with the RXR agonist bexarotene (100 mg/kg body weight [mpk], in 1% carboxymethylcellulose), the LXR agonist T0901317 (T09, 30 mpk) or vehicle alone.Nucleic Acid Extraction - Chromatin was prepared from snap frozen livers, homogenized in PBS and cross-linked in 1% formaldehyde (10 min, RT). Cross-linked material was added 1M glycine to a final concentration of 0.125 M and incubated for 10 min rotating at RT, pelleted by centrifugation at 400xg for 2 min at 4M-0C, washed 2x in cold PBS and resuspended in lysis buffer (1% triton, 0.1% SDS, 150 mM NaCl, 2 mM EDTA, 1 mM EGTA, 20 mM Tris, pH 8.0) (200 M-NM-<l/10 mg chromatin) before sonication according to the manufacturerM-bM-^@M-^Ys protocol using the Diagenode Bioruptor twin (2x20 cycles, 30 sec. on/off, max. level). Samples were centrifuged for 2 min at 10.000xg and supernatant used for subsequent chromatin IP performed according to standard protocol. ChIP-seq sample preparation for sequencing was performed according to the manufacturerM-bM-^@M-^Ys instructions (Illumina).OrganizationMINSEQE ScoreAssays and DataProcessed DataMAGE-TAB FilesFeature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: RNAPII_LXRdKO_Bexa_repl2.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: RNAPII_LXRdKO_T09_repl2.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: LXR_WT_T09.bed: mm9 LXR_WT_T09_peaks.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: RNAPII_WT_T09_repl2.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: LXR_WT_Control.bed: mm9 LXR_WT_Control_peaks.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: RNAPII_WT_Bexa_repl2.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: RXR_WT_T09.bed: mm9 RXR_WT_T09_peaks.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: RNAPII_LXRdKO_T09_repl1.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: RXR_dKO_T09.bed: mm9 RXR_dKO_T09_peaks.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: RXR_WT_Control.bed: mm9 RXR_WT_Control_peaks.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: RNAPII_WT_Control_repl1.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: RNAPII_WT_Bexa_repl1.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: RNAPII_LXRdKO_Control_repl2.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: PPARa_dKO.bed: mm9 PPARa_dKO_peaks.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: RXR_WT_Bexa.bed: mm9 RXR_WT_Bexa_peaks.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: RNAPII_LXRdKO_Control_repl1.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: RXR_dKO_Bexa.bed: mm9 RXR_dKO_Bexa_peaks.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: RXR_dKO_Control.bed: mm9 RXR_dKO_Control_peaks.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: PPARa_WT.bed: mm9 PPARa_WT_peaks.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: RNAPII_LXRdKO_Bexa_repl1.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: LXR_WT_Bexa.bed: mm9 LXR_WT_Bexa_peaks.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: RNAPII_WT_T09_repl1.bed: mm9Feature Extraction - Read were mapped to mm9 using ELAND using 0 or 1 mismatches. Non-unique reads were discarded, ie only one read per genomic position was kept. The mapped reads were normalized between samples by uniformly removing reads to obtain an identical number of mapped reads for each experiment. Peaks were called using FindPeaks 4 with the parameters -subpeaks 0.1 and -trim-peaks 0.3. All peaks with less than 10 overlapping reads were discarded. Genome Build: RNAPII_WT_Control_repl2.bed: mm9MetabolomicsUnknownTranscriptomicsGenomicsProteomicsThe liver X receptors (LXRs) are nuclear receptors that form permissive heterodimers with retinoid X receptor (RXR) and are important regulators of lipid metabolism in the liver. We have recently shown that RXR agonist-induced hypertriglyceridemia and hepatic steatosis in mice are dependent on LXRs and correlate with an LXR-dependent hepatic induction of lipogenic genes. To further investigate the roles of RXR and LXR in the regulation of hepatic gene expression, we have mapped the ligand-regulated genome-wide binding of these factors in mouse liver. We find that the RXR agonist bexarotene primarily increases the genomic binding of RXR, whereas the LXR agonist T0901317 greatly increases both LXR and RXR binding. Functional annotation of putative direct LXR target genes revealed a significant association with classical LXR-regulated pathways as well as peroxisome proliferator-activated receptor (PPAR) signaling pathways, and subsequent chromatin immunoprecipitation-sequencing (ChIP-seq) mapping of PPARα binding demonstrated binding of PPARα to 71 to 88% of the identified LXR-RXR binding sites. The combination of sequence analysis of shared binding regions and sequential ChIP on selected sites indicate that LXR-RXR and PPARα-RXR bind to degenerate response elements in a mutually exclusive manner. Together, our findings suggest extensive and unexpected cross talk between hepatic LXR and PPARα at the level of binding to shared genomic sites.ChIP-seqMus musculusGenome-wide profiling of liver X receptor, retinoid X receptor, and peroxisome proliferator-activated receptor M-NM-1 in mouse liver reveals extensive sharing of binding sites.Hilde NebbJan-M-CM-^Eke GustafssonSimon van HeeringenChristian BindesbM-CM-8llSandrine CaronKnut SteffensenMichael BoergesenBart StaelsSusanne MandrupBarbara GrossBoergesen M, Pedersen TM-CM-^E, Gross B, van Heeringen SJ, Hagenbeek D, BindesbM-CM-8ll C, Caron S, Lalloyer F, Steffensen KR, Nebb HI, Gustafsson JM-CM-^E, Stunnenberg HG, Staels B, Mandrup SHendrik StunnenbergDik HagenbeekFanny LalloyerfalseGenome-wide profiling of LXR, RXR and PPARM-NM-1 in mouse liver reveals extensive sharing of binding sitesThe liver X receptors (LXRs) are nuclear receptors that form permissive heterodimers with retinoid X receptor (RXR) and are important regulators of lipid metabolism in the liver. We have recently shown that RXR agonist-induced hypertriglyceridemia and hepatic steatosis in mice is dependent on LXR and correlates with an LXR-dependent hepatic induction of lipogenic genes. To further investigate the role of RXR and LXR in the regulation of hepatic gene expression, we have mapped the ligand-regulated genome-wide binding of these factors in mouse liver. We find that the RXR agonist bexarotene primarily increases the genomic binding of RXR, whereas the LXR agonist T0901317 greatly increases both LXR and RXR binding. Functional annotation of putative direct LXR target genes revealed a significant association with classical LXR-regulated pathways as well as PPAR signaling pathways, and subsequent ChIP-seq mapping of PPARM-NM-1 binding demonstrated binding of PPARM-NM-1 to 71-88% of the identified LXR:RXR binding sites. Sequence analysis of shared binding regions combined with sequential ChIP on selected sites indicate that LXR:RXR and PPARM-NM-1:RXR bind to degenerate response elements in a mutually exclusive manner. Together our findings suggest extensive and unexpected cross-talk between hepatic LXR and PPARM-NM-1 at the level of binding to shared genomic sites LXR, RXR, PPARalpha and RNA Polymerase II ChIP-seq on livers from female C57BL/6 wild-type and/or LXRM-NM-1/M-NM-2-deficient mice (13 weeks of age, n=1) treated by oral gavage once daily for 14 days with the RXR agonist bexarotene (100 mg/kg body weight [mpk], in 1% carboxymethylcellulose), the LXR agonist T0901317 (T09, 30 mpk) or vehicle alone.2012-01-31T00:00:00Z2023-08-19T16:55:21.125Z2021-10-05T22:24:22ZE-GEOD-35262GSE3526222158963SRP010657EFO_000269210.1128/MCB.06175-11