Abstract
Epigenetic regulation is a key determinant of adipocyte fate, driving the differentiation toward white or thermogenic beige phenotypes in response to environmental cues. To dissect the mechanisms orchestrating this plasticity in human adipocytes, we conducted an integrative analysis of transcriptomic, epigenomic and enhancer connectome dynamics throughout white and beige adipogenesis. Using a machine learning approach, we show that the white transcriptional program is tightly linked to promoter-level modulation of H3K27ac and chromatin accessibility, whereas the beige-specific induction of mitochondrial genes is driven by promoter remodeling of H3K4me3, underscoring distinct epigenetic mechanisms for white or beige specification. Adipocyte beiging is accompanied by a targeted reorganization of the 3D genome, characterized by increased recruitment of short-range enhancers controlling thermogenesis genes, enriched for C/EBP transcription factor binding sites. Our findings highlight the multimodal regulation of the beige adipocyte fate, driven by the interplay of chromatin state transitions, enhancer rewiring, and transcription factor dynamics.
Similar content being viewed by others
Data availability
RNA-seq data, histone ChIPs, ATAC-seq and Hi-ChIP data generated for this study are available at NCBI GEO with accession number GSE293136. Re-analysis of MED1 datasets23 can be found at GEO under accession GSE256261. RNA-seq from paired white and brown fat biopsies were downloaded from GEO with accession GSE113764 and single nuclei RNAseq was sourced from the Single Cell Portal with accession SCP3116. Uncropped membranes are presented as Supplementary Figs. 10–12. The numerical data underlying the graphs is presented in Supplementary Data 6. All other data are available from the corresponding author on reasonable request.
Code availability
Code for data processing and analysis is available at Zenodo (https://doi.org/10.5281/zenodo.17625772)61.
References
Sharma, A. K., Khandelwal, R. & Wolfrum, C. Futile lipid cycling: from biochemistry to physiology. Nat. Metab. 6, 808–824 (2024).
Kajimura, S., Spiegelman, B. M. & Seale, P. Brown and beige fat: physiological roles beyond heat generation. Cell Metab. 22, 546–559 (2015).
Bartelt, A. & Heeren, J. Adipose tissue browning and metabolic health. Nat. Rev. Endocrinol. 10, 24–36 (2014).
Kajimura, S. The epigenetic regulation of adipose tissue plasticity. Proc. Natl. Acad. Sci. USA 118, e2102944118 (2021).
Roh, H. C. et al. Warming induces significant reprogramming of beige, but not brown, adipocyte cellular identity. Cell Metab. 27, 1121–1137 e1125 (2018).
Pan, D. et al. Jmjd3-mediated H3K27me3 dynamics orchestrate brown fat development and regulate white fat plasticity. Dev. Cell 35, 568–583 (2015).
Zha, L. et al. The histone demethylase UTX promotes brown adipocyte thermogenic program via coordinated regulation of H3K27 demethylation and acetylation. J. Biol. Chem. 290, 25151–25163 (2015).
Lehmann, J. M. et al. An antidiabetic thiazolidinedione is a high affinity ligand for peroxisome proliferator-activated receptor gamma (PPAR gamma). J. Biol. Chem. 270, 12953–12956 (1995).
Perdikari, A. et al. BATLAS: deconvoluting brown adipose tissue. Cell Rep. 25, 784–797.e784 (2018).
U Din, M. et al. Postprandial oxidative metabolism of human brown fat indicates thermogenesis. Cell Metab. 28, 207–216.e203 (2018).
Miranda, A. M. A. et al. Selective remodelling of the adipose niche in obesity and weight loss. Nature 644, 769–779 (2025).
Ke, G. L. et al. LightGBM: a highly efficient gradient boosting decision tree. Adv. Neural Inf. Process. Syst. 30, 3146–3154 (2017).
Lundberg, S. M. & Lee, S. I. A Unified approach to interpreting model predictions. Adv. Neural Inf. Process. Syst. 30, 4766–4777 (2017).
Juric, I. et al. MAPS: Model-based analysis of long-range chromatin interactions from PLAC-seq and HiChIP experiments. PLoS Comput Biol. 15, e1006982 (2019).
Sahin, M. et al. HiC-DC+ enables systematic 3D interaction calls and differential analysis for Hi-C and HiChIP. Nat. Commun. 12, 3366 (2021).
Jin, F. et al. A high-resolution map of the three-dimensional chromatin interactome in human cells. Nature 503, 290–294 (2013).
Hazell Pickering, S., Abdelhalim, M., Collas, P. & Briand, N. Alternative isoform expression of key thermogenic genes in human beige adipocytes. Front Endocrinol. 15, 1395750 (2024).
Dekker, J. & Mirny, L. A. The chromosome folding problem and how cells solve it. Cell 187, 6424–6450 (2024).
Stadhouders, R., Filion, G. J. & Graf, T. Transcription factors and 3D genome conformation in cell-fate decisions. Nature 569, 345–354 (2019).
Chen, W. & Roeder, R. G. Mediator-dependent nuclear receptor function. Semin. Cell Dev. Biol. 22, 749–758 (2011).
Ito, K. et al. Critical roles of transcriptional coactivator MED1 in the formation and function of mouse adipose tissues. Genes Dev. 35, 729–748 (2021).
Kagey, M. H. et al. Mediator and cohesin connect gene expression and chromatin architecture. Nature 467, 430–435 (2010).
Loft, A. et al. Browning of human adipocytes requires KLF11 and reprogramming of PPARgamma superenhancers. Genes Dev. 29, 7–22 (2015).
Step, S. E. et al. Anti-diabetic rosiglitazone remodels the adipocyte transcriptome by redistributing transcription to PPARgamma-driven enhancers. Genes Dev. 28, 1018–1028 (2014).
Whyte, W. A. et al. Master transcription factors and mediator establish super-enhancers at key cell identity genes. Cell 153, 307–319 (2013).
Aronheim, A., Zandi, E., Hennemann, H., Elledge, S. J. & Karin, M. Isolation of an AP-1 repressor by a novel method for detecting protein-protein interactions. Mol. Cell Biol. 17, 3094–3102 (1997).
Cowell, I. G., Skinner, A. & Hurst, H. C. Transcriptional repression by a novel member of the bZIP family of transcription factors. Mol. Cell Biol. 12, 3070–3077 (1992).
Zhang, W. et al. Molecular cloning and characterization of NF-IL3A, a transcriptional activator of the human interleukin-3 promoter. Mol. Cell Biol. 15, 6055–6063 (1995).
Li, F., Liu, J., Jo, M. & Curry, T. E. Jr. A role for nuclear factor interleukin-3 (NFIL3), a critical transcriptional repressor, in down-regulation of periovulatory gene expression. Mol. Endocrinol. 25, 445–459 (2011).
MacGillavry, H. D. et al. Genome-wide gene expression and promoter binding analysis identifies NFIL3 as a repressor of C/EBP target genes in neuronal outgrowth. Mol. Cell Neurosci. 46, 460–468 (2011).
Reinisch, I. et al. Unveiling adipose populations linked to metabolic health in obesity. Cell Metab. 37, 640–655 (2024).
Hinte, L. C. et al. Adipose tissue retains an epigenetic memory of obesity after weight loss. Nature 636, 457–465 (2024).
Merlin, J. et al. Rosiglitazone and a beta(3)-adrenoceptor agonist are both required for functional browning of white adipocytes in culture. Front. Endocrinol. 9, 249 (2018).
Rosenwald, M., Perdikari, A., Rulicke, T. & Wolfrum, C. Bi-directional interconversion of brite and white adipocytes. Nat. Cell Biol. 15, 659–667 (2013).
Altshuler-Keylin, S. et al. Beige adipocyte maintenance is regulated by autophagy-induced mitochondrial clearance. Cell Metab. 24, 402–419 (2016).
Kajimura, S. et al. Initiation of myoblast to brown fat switch by a PRDM16-C/EBP-beta transcriptional complex. Nature 460, 1154–1158 (2009).
Barquissau, V. et al. White-to-brite conversion in human adipocytes promotes metabolic reprogramming towards fatty acid anabolic and catabolic pathways. Mol. Metab. 5, 352–365 (2016).
Pettersen, I. K. N. et al. Upregulated PDK4 expression is a sensitive marker of increased fatty acid oxidation. Mitochondrion 49, 97–110 (2019).
So, J. et al. Chronic cAMP activation induces adipocyte browning through discordant biphasic remodeling of transcriptome and chromatin accessibility. Mol. Metab. 66, 101619 (2022).
Acharya, A., Rishi, V., Moll, J. & Vinson, C. Experimental identification of homodimerizing B-ZIP families in Homo sapiens. J. Struct. Biol. 155, 130–139 (2006).
Chen, S., Lei, M., Liu, K. & Min, J. Structural basis for specific DNA sequence recognition by the transcription factor NFIL3. J. Biol. Chem. 300, 105776 (2024).
Reed, K. S. M. et al. Temporal analysis suggests a reciprocal relationship between 3D chromatin structure and transcription. Cell Rep. 41, 111567 (2022).
Chen, S., Zhou, Y., Chen, Y. & Gu, J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34, i884–i890 (2018).
Kim, D., Paggi, J. M., Park, C., Bennett, C. & Salzberg, S. L. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat. Biotechnol. 37, 907–915 (2019).
Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).
Robinson, M. D. & Oshlack, A. A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol. 11, R25 (2010).
Law, C. W., Chen, Y., Shi, W. & Smyth, G. K. voom: Precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol. 15, R29 (2014).
Racle, J., de Jonge, K., Baumgaertner, P., Speiser, D. E. & Gfeller, D. Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data. Elife 6, e26476 (2017).
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008).
Lund, E., Oldenburg, A. R. & Collas, P. Enriched domain detector: a program for detection of wide genomic enrichment domains robust against local variations. Nucleic Acids Res. 42, e92 (2014).
Ramírez, F., Dündar, F., Diehl, S., Grüning, B. A. & Manke, T. deepTools: a flexible platform for exploring deep-sequencing data. Nucl. Acids Res. 42, W187–W191 (2014).
Robinson, J. T. et al. Integrative genomics viewer. Nat. Biotechnol. 29, 24–26 (2011).
Tu, S. et al. MAnorm2 for quantitatively comparing groups of ChIP-seq samples. Genome Res. 31, 131–145 (2021).
Ernst, J. & Kellis, M. Chromatin-state discovery and genome annotation with ChromHMM. Nat. Protoc. 12, 2478–2492 (2017).
Corces, M. R. et al. An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues. Nat. Methods 14, 959–962 (2017).
Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
Bentsen, M. et al. ATAC-seq footprinting unravels kinetics of transcription factor binding during zygotic genome activation. Nat. Commun. 11, 4267 (2020).
Castro-Mondragon, J. A. et al. JASPAR 2022: the 9th release of the open-access database of transcription factor binding profiles. Nucleic Acids Res. 50, D165–D173 (2022).
Ronningen, T. et al. Prepatterning of differentiation-driven nuclear lamin A/C-associated chromatin domains by GlcNAcylated histone H2B. Genome Res. 25, 1825–1835 (2015).
Hazell Pickering, S. sarahhp/beige_3d_epigenome: Hazell Pickering et al. 2025 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.17625772 (2025).
Acknowledgements
We acknowledge the Norwegian Sequencing Centre (Oslo University Hospital) for professional sequencing services. We thank Patrizia Nothnagel for assistance with Seahorse experiment. This work was funded by the University of Oslo, South-East Health Norway grant 40202 to P.C., Research Council of Norway grant 313508 to P.C., and Nansen fund 17368 to N.B.
Author information
Authors and Affiliations
Contributions
S.H.P. and M.A. analyzed data. N.M.G., A.L.S., and J.M.Ø. generated datasets. M.Z. advised on machine learning and statistics. N.B. and S.H.P. made figures. N.B. and P.C. designed the study. N.B. supervised the work. N.B., S.H.P., and P.C. wrote the manuscript. All authors approved the final version of the paper.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Communications Biology thanks Martin Jastroch, Michael Rossiter and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Dr. Nilanjan Banerjee and Dr Rosie Bunton-Stasyshyn. [A peer review file is available].
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Hazell Pickering, S., Galigniana, N.M., Abdelhalim, M. et al. Multimodal epigenetic and enhancer network remodeling shape the transcriptional landscape of human beige adipocytes. Commun Biol (2026). https://doi.org/10.1038/s42003-025-09469-8
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s42003-025-09469-8
