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MRG15 orchestrates rhythmic epigenomic remodelling and controls hepatic lipid metabolism

Nature Metabolism volume 2, pages 447–460 (2020)Cite this article

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Abstract

The rhythmic regulation of transcriptional processes is intimately linked to lipid homeostasis, to anticipate daily changes in energy access. The Rev-erbα–HDAC3 complex was previously discovered to execute the rhythmic repression of lipid genes; however, the epigenetic switch that turns on these genes is less clear. Here, we show that genomic recruitment of MRG15, which is encoded by the mortality factor on chromosome 4 (MORF4)-related gene on chromosome 15, displays a significant diurnal rhythm and activates lipid genes in the mouse liver. RNA polymerase II (Pol II) recruitment and histone acetylation correspond to MRG15 binding, and the rhythm is impaired upon MRG15 depletion, establishing MRG15 as a key modulator in global rhythmic transcriptional regulation. MRG15 interacts with the nuclear receptor LRH-1, rather than with known core clock proteins, and is recruited to genomic loci near lipid genes via LRH-1. Blocking of MRG15 by CRISPR targeting or by the FDA-approved drug argatroban, which is an antagonist to MRG15, attenuates liver steatosis. This work highlights MRG15 as a targetable master regulator in the rhythmic regulation of hepatic lipid metabolism.

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Fig. 1: Rhythmic genomic recruitment of MRG15 in mouse liver.
Fig. 2: MRG15 regulates rhythmic RNA polymerase II recruitment in mouse liver.
Fig. 3: MRG15 regulates rhythmic histone acetylation and gene expression in mouse liver.
Fig. 4: LRH-1 mediates MRG15 recruitment to lipid regulatory genes.
Fig. 5: LRH-1 interacts with MRG15.
Fig. 6: Blocking of liver MRG15 by CRISPR targeting attenuates liver steatosis and improves metabolism.
Fig. 7: Treatment with the FDA-approved drug argatroban attenuates liver steatosis.
Fig. 8: Mechanistic model of the role of MRG15 in regulating liver lipid metabolism.

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Data availability

ChIP–seq and RNA-seq data have been deposited in the National Omics Data Encylopedia (http://www.biosino.org/node) under the accession code OEP000757.

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Acknowledgements

We thank K. Musunuru and Y. Chen for helpful discussions. We thank H. Feng and X.-F. Chen for assistance with data analysis, and Z.-G. Li for assistance with confocal analysis. This work was supported by grants from the National Key R&D Programme of China (2017YFA0102800 and 2017YFA0103700), the Strategic Priority Research Programme of the Chinese Academy of Sciences (XDA16030402), the National Natural Science Foundation of China (91957205, 31670829 and 31971063) and the China Postdoctoral Science Foundation (2019M661661).

Author information

Author notes

  1. These authors contributed equally: Yuda Wei, Cheng Tian, Yongxu Zhao.

Authors and Affiliations

  1. CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, P. R. China

    Yuda Wei, Cheng Tian, Yongxu Zhao, Xiaojian Liu, Shuang Li, Yanhao Chen, Yan Qiu, Zhuanghui Feng, Lanlan Chen, Tingting Zhou, Chengwu Feng, Yan Liu, Hao Ying & Qiurong Ding

  2. Shanghai Key Laboratory of Sleep Disordered Breathing, Department of Otolaryngology-Head and Neck Surgery, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, P. R. China

    Feng Liu

  3. Laboratory of RNA Epigenetics, Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai, P. R. China

    Xiaoguang Ren & Wenqiang Yu

  4. Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, P. R. China

    Qiurong Ding

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Contributions

Y.W., C.T., Y.Z. and Q.D. designed experiments. Y.W., C.T., Y.Z., X.L., F.L., S.L., Y.C., Y.Q., Z.F., L.C, T.Z., X.R., C.F. and Y.L. carried out experiments and analysed data. X.L. performed bioinformatics analysis. Y.W., C.T., Y.Z., F.L., W.Y., H.Y. and Q.D. wrote the manuscript. Q.D. supervised the project.

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Correspondence to Qiurong Ding.

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Extended data

Extended Data Fig. 1 Rhythmic genomic recruitment of exogenous MRG15 in mouse liver.

Adeno-associated virus 8 (AAV8) vectors either containing TBG-luciferase (AAV-Luci) or TBG-FLAG-Mrg15 (AAV-FLAG-MRG15) were administered via tail vein injection. Tissues were collected for analysis after virus injection for around 4 weeks. a, Western analysis of endogenous and FLAG-MRG15 levels in mouse liver tissues. Repeated twice with similar results. b, Average MRG15 signals from −5 kb to +5 kb surrounding the TSS and from −2 kb to +2 kb surrounding the gene bodies. c, Distribution of the MRG15 ZT22 binding sites in different genomic locations relative to known genes. d. ChIP–seq tracks of MRG15 signals at ZT10 and ZT22 in Acat2, Acly and Elovl5 gene loci, as indicated. e, Gene enrichment analysis of genes both bound by MRG15 as revealed in ChIP–seq analysis and displayed circadian rhythm at transcriptional levels (603 genes). Associated P values were determined according to the analysis in the GO database (Fisher’s exact P value).

Source data

Extended Data Fig. 2 Rhythmic genomic recruitment of endogenous MRG15 in mouse liver in Mrg15Flag-KI animals.

a, Scheme illustration of the generation of the Mrg15Flag-KI animals via knockin of a 3 × FLAG tag at the C-terminal of endogenous Mrg15 before the stop codon. b, Western analysis of the endogenous FLAG-MRG15 with both FLAG and MRG15 antibodies. Repeated twice with similar results. c, Relative MRG15 binding signals as assessed by ChIP–qPCR in animals at ZT10 and ZT22. n = 3 for Wild-type and 6 for Mrg15Flag-KI groups. d, The rhythm of MRG15 recruitment is reversed by daytime feeding. n = 3 for Wild-type, 4 for Mrg15Flag-KI ZT10 and 3 for Mrg15Flag-KI ZT22. Some of the values in the wild-type group are very low and were not detected by qPCR, therefore are not displayed. Data points were all from biologically independent samples (c, d). P values are shown for indicated comparisons by the two-tailed Mann–Whitney U tests. Values are mean ± s.e.m.

Source data

Extended Data Fig. 3 Liver-specific depletion of MRG15 via CRISPR technology.

a, Schematic illustration of the CRISPR–Cas9 KI mice and AAV constructs used to deplete genes in this study. b, In vivo bioluminescence imaging of AAV vectors (left) and endogenous liver MRG15 levels in animals administered AAV-Cre-2a-Luci (Control) or AAV-Cre-2a-Luci-Mrg15 sgRNA1 (Mrg15-sgRNA). Repeated twice with similar results.

Source data

Extended Data Fig. 4 MRG15 depletion in liver leads to reduced expression of lipid and cholesterol synthesis genes in NCD-fed animals.

Tissues were collected from animals under NCD after virus injection for 14 weeks for RNA-seq analysis. a, b, Representative genes downregulated in CRISPR-Mrg15 livers involved in triglyceride synthesis (a) and cholesterol synthesis (b). Values are indicated as log 2 [Fold change (CRISPR-Mrg15/Control)] in a and b. Genes that are direct targets of MRG15 as revealed in ChIP–seq analysis are labelled with an asterisk at upper right.

Extended Data Fig. 5 MRG15 binding sites show minimal overlap with binding loci of HDAC3, Rev-erbα or NCoR, at commonly bound genes.

Heatmap displaying localisation of ChIP signals relative to the TSS site (0 bp) near common target genes between MRG15 vs. HDAC3 a, MRG15 vs. Rev-erbα b, and MRG15 vs. NCoR c. The numbers of common target genes and overlapped peaks are indicated below, with common genes (peaks) showing in blue, and total bound genes (peaks) of HDAC3, Rev-erbα and NCoR are shown in black. Detailed information can also be found in Supplementary Table 1.

Extended Data Fig. 6 LRH-1 and MRG15 co-regulate lipid synthesis genes.

a, Venn diagram indicating overlapping genes in Lrh1−/− and CRISPR-Mrg15 livers (left); and gene enrichment analysis of overlapped genes downregulated in Lrh1−/− and CRISPR-Mrg15 livers (120 genes). b, Venn diagram indicating overlapping genes in LRH-1 K289R and CRISPR-Mrg15 livers (left); and gene enrichment analysis of overlapped genes upregulated in LRH-1 K289R livers and downregulated in CRISPR-Mrg15 livers (161 genes). Associated P values were determined according to the analysis in the GO database (Fisher’s exact P value) for a and b. c, Representative commonly regulating lipid synthesis genes between Lrh1−/− and CRISPR-Mrg15 livers, and LRH-1 K289R and CRISPR-Mrg15 livers.

Extended Data Fig. 7 mRNA expression levels of Mrg15 and Lrh-1 at ZT10 and ZT22.

Relative mRNA expression of Mrg15 and Lrh-1 in liver at ZT10 and ZT22. n = 5 biologically independent samples. P values are shown for indicated comparisons by the two-tailed Mann–Whitney U tests. Values are mean ± s.e.m.

Source data

Extended Data Fig. 8 Liver depletion of MRG15 leads to reduced expression of lipid and cholesterol synthesis genes, and inflammatory genes in HFD animals.

Tissues were collected from animals under HFD after virus injection for 14 weeks for RNA-seq analysis. a, b, c, Representative genes downregulated in CRISPR-Mrg15 livers involved in triglyceride synthesis (a), cholesterol synthesis (b) and inflammatory response (c). Values are indicated as log 2 [Fold change (CRISPR-Mrg15/Control)] in a, b and c. Genes that are direct targets of MRG15 as revealed in ChIP–seq analysis in a and b are labelled with an asterisk at upper right. d, Gene enrichment analysis of downregulated genes in CRISPR-Mrg15 livers identified by RNA-seq (622 genes using a cut-off of P < 0.05). Associated P values were determined according to the analysis in the GO database (Fisher’s exact P value). e, Relative mRNA expression of representative lipid genes in liver in control and Mrg15-sgRNA treated animals under HFD. n = 9 biologically independent samples. P values are shown for indicated comparisons by the two-tailed Mann–Whitney U tests. Values are mean ± s.e.m.

Source data

Extended Data Fig. 9 CRISPR-Mrg15-sgRNA2 mice have improved metabolism.

a, Mrg15 targeting sequences of two sgRNAs. b, Western analysis of endogenous MRG15 levels after CRISPR treatment. Repeated twice with similar results. c, Body weight. d, Nuclear magnetic resonance analysis of fat mass. e, Nuclear magnetic resonance analysis of lean mass. Start, before virus injection. End, 19 weeks after virus injection. n = 10 (a-e). f, Blood triglyceride levels and total cholesterol levels (1 month: n = 11 and 13; 2 months: n = 13 and 15). g, GTT and ITT of animals after virus injection for 9–10 weeks. n = 11 for Control and 13 for Mrg15-sgRNA 2. h, Western analysis of endogenous MRG15 and LRH-1 levels after CRISPR treatment. Repeated twice with similar results. Data points were all from biologically independent samples (c-g). P values are shown for indicated comparisons by the two-tailed Mann–Whitney U tests (f) or were determined by multiple t-tests with fewer assumptions (do not assume consistent s.d.) for GTT and ITT analyses (g). Values are mean ± s.e.m.

Source data

Extended Data Fig. 10 MRG15 regulates expression of several core clock genes.

Relative mRNA levels of core clock genes in animal livers over a 24-h cycle. n = 4 biologically independent samples. Values are mean ± s.e.m.

Source data

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Wei, Y., Tian, C., Zhao, Y. et al. MRG15 orchestrates rhythmic epigenomic remodelling and controls hepatic lipid metabolism. Nat Metab 2, 447–460 (2020). https://doi.org/10.1038/s42255-020-0203-z

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