Brown fat dissipates energy as heat and protects against obesity. Here, we identified nuclear factor I-A (NFIA) as a transcriptional regulator of brown fat by a genome-wide open chromatin analysis of murine brown and white fat followed by motif analysis of brown-fat-specific open chromatin regions. NFIA and the master transcriptional regulator of adipogenesis, PPARγ, co-localize at the brown-fat-specific enhancers. Moreover, the binding of NFIA precedes and facilitates the binding of PPARγ, leading to increased chromatin accessibility and active transcription. Introduction of NFIA into myoblasts results in brown adipocyte differentiation. Conversely, the brown fat of NFIA-knockout mice displays impaired expression of the brown-fat-specific genes and reciprocal elevation of muscle genes. Finally, expression of NFIA and the brown-fat-specific genes is positively correlated in human brown fat. These results indicate that NFIA activates the cell-type-specific enhancers and facilitates the binding of PPARγ to control the brown fat gene program.

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  1. 1.

    & Brown adipose tissue: function and physiological significance. Physiol. Rev. 84, 277–359 (2004).

  2. 2.

    , & Unexpected evidence for active brown adipose tissue in adult humans. Am. J. Physiol. Endocrinol. Metab. 293, E444–E452 (2007).

  3. 3.

    et al. Cold-activated brown adipose tissue in healthy men. N. Engl. J. Med. 360, 1500–1508 (2009).

  4. 4.

    et al. Identification and importance of brown adipose tissue in adult humans. N. Engl. J. Med. 360, 1509–1517 (2009).

  5. 5.

    et al. Functional brown adipose tissue in healthy adults. N. Engl. J. Med. 360, 1518–1525 (2009).

  6. 6.

    et al. High incidence of metabolically active brown adipose effects of cold exposure and adiposity. Diabetes 58, 1526–1531 (2009).

  7. 7.

    et al. Cold acclimation recruits human brown fat and increases nonshivering thermogenesis. J. Clin. Invest. 123, 3395–3403 (2013).

  8. 8.

    et al. Short-term cold acclimation improves insulin sensitivity in patients with type 2 diabetes mellitus. Nat. Med. 21, 6–10 (2015).

  9. 9.

    et al. Activation of human brown adipose tissue by a β3-adrenergic receptor agonist. Cell Metab. 21, 33–38 (2015).

  10. 10.

    et al. PRDM16 controls a brown fat/skeletal muscle switch. Nature 454, 961–967 (2008).

  11. 11.

    et al. Transcriptional control of brown fat determination by PRDM16. Cell Metab. 6, 38–54 (2007).

  12. 12.

    et al. PRDM16 binds MED1 and controls chromatin architecture to determine a brown fat transcriptional program. Genes Dev. 29, 298–307 (2015).

  13. 13.

    , , & PPARγ agonists induce a white-to-brown fat conversion through stabilization of PRDM16 protein. Cell Metab. 15, 395–404 (2012).

  14. 14.

    et al. Genome-wide profiling of peroxisome proliferator-activated receptor γ in primary epididymal, inguinal, and brown adipocytes reveals depot-selective binding correlated with gene expression. Mol. Cell. Biol. 32, 3452–3463 (2012).

  15. 15.

    et al. EBF2 determines and maintains brown adipocyte identity. Cell Metab. 17, 562–574 (2013).

  16. 16.

    , , , & FAIRE (Formaldehyde-Assisted Isolation of Regulatory Elements) isolates active regulatory elements from human chromatin. Genome Res. 17, 877–885 (2007).

  17. 17.

    et al. Adipose subtype-selective recruitment of TLE3 or Prdm16 by PPARγ specifies lipid storage versus thermogenic gene programs. Cell Metab. 17, 423–435 (2013).

  18. 18.

    et al. Initiation of myoblast to brown fat switch by a PRDM16-C/EBP-β transcriptional complex. Nature 460, 1154–1158 (2009).

  19. 19.

    Roles of the NFI/CTF gene family in transcription and development. Development 249, 31–45 (2000).

  20. 20.

    , , , & Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213–1218 (2013).

  21. 21.

    et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589 (2010).

  22. 22.

    et al. Master transcription factors determine cell-type-specific responses to TGF-β signaling. Cell 147, 565–576 (2011).

  23. 23.

    et al. Disruption of the murine nuclear factor I-A gene (Nfia) results in perinatal lethality, hydrocephalus, and agenesis of the corpus callosum. Proc. Natl Acad. Sci. USA 96, 11946–11951 (1999).

  24. 24.

    & Brown and beige fat: development, function and therapeutic potential. Nat. Med. 19, 1252–1263 (2013).

  25. 25.

    et al. Activation of classical brown adipocytes in the adult human perirenal depot is highly correlated with PRDM16-EHMT1 complex expression. PLoS ONE 10, 1–13 (2015).

  26. 26.

    et al. A classical brown adipose tissue mRNA signature partly overlaps with brite in the supraclavicular region of adult humans. Cell Metab. 17, 798–805 (2013).

  27. 27.

    et al. Anatomical localization, gene expression profiling and functional characterization of adult human neck brown fat. Nat. Med. 19, 635–639 (2013).

  28. 28.

    , & Stimulation of adipogenesis in fibroblasts by PPAR γ2, a lipid-activated transcription factor. Cell 79, 1147–1156 (1994).

  29. 29.

    et al. Regulation of CSF1 promoter by the SWI/SNF-like BAF complex. Cell 106, 309–318 (2001).

  30. 30.

    & Pioneer transcription factors: establishing competence for gene expression. Genes Dev. 25, 2227–2241 (2011).

  31. 31.

    et al. Genetic variation determines PPARγ function and anti-diabetic drug response in vivo. Cell 162, 33–44 (2015).

  32. 32.

    et al. Large-scale identification of sequence variants influencing human transcription factor occupancy in vivo. Nat. Genet. 47, 1393–1401 (2015).

  33. 33.

    et al. Systematic dissection of genomic features determining transcription factor binding and enhancer function. Proc. Natl Acad. Sci. USA 114, E1291–E1300 (2017).

  34. 34.

    , & The genetics of transcription factor DNA binding variation. Cell 166, 538–554 (2016).

  35. 35.

    et al. Prdm16 is required for the maintenance of brown adipocyte identity and function in adult mice. Cell Metab. 19, 593–604 (2014).

  36. 36.

    et al. Ebf2 is a selective marker of brown and beige adipogenic precursor cells. Proc. Natl Acad. Sci. USA 111, 14466–14471 (2014).

  37. 37.

    , , , & Antagonism between the master regulators of differentiation ensures the discreteness and robustness of cell fates. Mol. Cell 54, 526–535 (2014).

  38. 38.

    , , & Identification of a potent adipocyte-specific enhancer: involvement of an NF-1-like factor. Genes Dev. 5, 428–437 (1991).

  39. 39.

    et al. Global mapping of cell type-specific open chromatin by FAIRE-seq reveals the regulatory role of the NFI family in adipocyte differentiation. PLoS Genet. 7, e1002311 (2011).

  40. 40.

    et al. Dissecting the brown adipogenic regulatory network using integrative genomics. Sci. Rep. 7, 42130 (2017).

  41. 41.

    et al. Nuclear factor I-C reciprocally regulates adipocyte and osteoblast differentiation via control of canonical Wnt signaling. FASEB J. 31, 1939–1952 (2017).

  42. 42.

    et al. Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity. Nature 541, 81–86 (2017).

  43. 43.

    , , & Differential roles of insulin receptor substrates in the anti-apoptotic function of insulin-like growth factor-1 and insulin. J. Biol. Chem. 277, 31601–31611 (2002).

  44. 44.

    , , , & EHMT1 controls brown adipose cell fate and thermogenesis through the PRDM16 complex. Nature 504, 163–167 (2013).

  45. 45.

    et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008).

  46. 46.

    et al. Cistrome: an integrative platform for transcriptional regulation studies. Genome Biol. 12, R83 (2011).

  47. 47.

    & Inferring direct DNA binding from ChIP-seq. Nucleic Acids Res. 40, 1–10 (2012).

  48. 48.

    et al. TRANSFAC: an integrated system for gene expression regulation. Nucleic Acids Res. 28, 316–319 (2000).

  49. 49.

    , & Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44–57 (2009).

  50. 50.

    , & Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

  51. 51.

    et al. GenePattern 2.0. Nat. Genet. 38, 500–501 (2006).

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We are grateful to S. Mandrup for her suggestion about our study. We thank K. Shiina and K. Tatsuno for their help in library preparation for high-throughput sequencing, S. Fukuda and T. Umehara for their help in computational analysis, K. Ueki, S. Kajimura and C. Villanueva for providing cells and plasmids, K. Nakashima for his suggestion regarding NFIA-KO mice, and T. Sugiyama, T. Kubota and N. Kubota for their help in animal experiments. We also thank T. Wada for his technical assistance. This work is funded by an AMED-CREST research grant from the Japan Agency for Medical Research and Development (AMED) to T.Y.; by a grant-in-aid for scientific research (B) from the Japan Society for the Promotion of Science (JSPS), grant number 25293209 to H.W.; by a grant-in-aid for JSPS fellows from JSPS, grant number 15J02835 to Y.Hiraike; and by a junior scientist development grant from the Japan Diabetes Society to Y.Hiraike. Y.Hiraike has been supported by a research fellowship from JSPS. The Centre of Inflammation and Metabolism (CIM) and the Centre for Physical Activity Research (CFAS), Department of Infectious Diseases, Rigshospitalet is supported by a grant from TrygFonden. CIM/CFAS is a member of DD2—the Danish Center for Strategic Research in Type 2 Diabetes (the Danish Council for Strategic Research, grant no. 09-067009 and 09-075724). T.J.L. has been supported by a research grant from the Danish Diabetes Academy supported by the Novo Nordisk Foundation. The Novo Nordisk Foundation Center for Basic Metabolic Research is supported by an unconditional grant from the Novo Nordisk Foundation to University of Copenhagen.

Author information

Author notes

    • Yuta Hiraike
    •  & Hironori Waki

    These authors contributed equally to this work.


  1. Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan

    • Yuta Hiraike
    • , Hironori Waki
    • , Jing Yu
    • , Masahiro Nakamura
    • , Kana Miyake
    • , Ken Suzuki
    • , Hirofumi Kobayashi
    • , Wei Sun
    • , Tomohisa Aoyama
    • , Yusuke Hirota
    • , Toshimasa Yamauchi
    •  & Takashi Kadowaki
  2. Department of Molecular Science on Diabetes, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan

    • Hironori Waki
  3. Department of Molecular and Internal Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima 734-8551, Japan

    • Gaku Nagano
    • , Haruya Ohno
    • , Kenji Oki
    •  & Masayasu Yoneda
  4. Genome Science Division, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 153-8904, Japan

    • Ryo Nakaki
    • , Shogo Yamamoto
    • , Shuichi Tsutsumi
    •  & Hiroyuki Aburatani
  5. Department of Orthopedic Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts 02215, USA

    • Andrew P. White
  6. Section on Integrative Physiology and Metabolism, Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts 02215, USA

    • Yu-Hua Tseng
  7. Translational Physiology Section, Diabetes, Endocrinology, and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, Maryland 20892, USA

    • Aaron M. Cypess
  8. The Centre of Inflammation and Metabolism and the Centre for Physical Activity Research, Department of Infectious Diseases, Rigshospitalet, University of Copenhagen, DK-2100 Copenhagen, Denmark

    • Therese J. Larsen
    • , Naja Z. Jespersen
    •  & Camilla Scheele
  9. Danish Diabetes Academy, Odense University Hospital, DK-5000 Odense C, Denmark

    • Therese J. Larsen
  10. Novo Nordisk Foundation Center for Basic Metabolic Research, Section for Metabolic Receptology, University of Copenhagen, 2200 Copenhagen, Denmark

    • Naja Z. Jespersen
  11. Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, 2200 Copenhagen, Denmark

    • Camilla Scheele


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Y.Hiraike and H.W. designed the study. Y.Hiraike., H.W., J.Y., K.M., H.K., W.S., Y.Hirota and T.A. performed experiments. M.N., R.N., K.S., S.Y., S.T., Y.Hiraike and H.W. performed computational analysis. G.N., H.O., K.O. and M.Y. performed analysis of human perirenal BAT. A.P.W., Y.-H.T. and A.M.C. performed analysis of human neck BAT and WAT. T.J.L., N.Z.J. and C.S. performed analysis of human brown and white adipocytes. Y.Hiraike and H.W. wrote the manuscript. H.A., T.Y. and T.K. supervised all aspects of this work.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Hironori Waki or Hiroyuki Aburatani or Toshimasa Yamauchi or Takashi Kadowaki.

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