The mammalian transcription factors CLOCK and BMAL1 are essential components of the molecular clock that coordinate behavior and metabolism with the solar cycle. Genetic or environmental perturbation of circadian cycles contributes to metabolic disorders including type 2 diabetes. To study the impact of the cell-autonomous clock on pancreatic β-cell function, we examined islets from mice with either intact or disrupted BMAL1 expression both throughout life and limited to adulthood. We found pronounced oscillation of insulin secretion that was synchronized with the expression of genes encoding secretory machinery and signaling factors that regulate insulin release. CLOCK/BMAL1 co-localized with the pancreatic transcription factor PDX1 within active enhancers distinct from those controlling rhythmic metabolic gene networks in liver. β-cell clock ablation in adult mice caused severe glucose intolerance. Thus cell-type specific enhancers underlie the circadian control of peripheral metabolism throughout life and may help explain its deregulation in diabetes.

Much has been learned about transcriptional cascades and networks from large-scale systems analyses of high-throughput data sets. However, analysis methods that optimize statistical power through simultaneous evaluation of thousands of ChIP-seq peaks or differentially expressed genes possess substantial limitations in their ability to uncover mechanistic principles of transcriptional control. By examining nascent transcript RNA-seq, ChIP-seq, and binding motif data sets from lipid A-stimulated macrophages with increased attention to the quantitative distribution of signals, we identified unexpected relationships between the in vivo binding properties of inducible transcription factors, motif strength, and transcription. Furthermore, rather than emphasizing common features of large clusters of co-regulated genes, our results highlight the extent to which unique mechanisms regulate individual genes with key biological functions. Our findings demonstrate the mechanistic value of stringent interrogation of well-defined sets of genes as a complement to broader systems analyses of transcriptional cascades and networks.

Transcription is tightly regulated to maintain energy homeostasis during periods of feeding or fasting, but the molecular factors that control these alternating gene programs are incompletely understood. Here, we find that the B cell lymphoma 6 (BCL6) repressor is enriched in the fed state and converges genome-wide with PPARα to potently suppress the induction of fasting transcription. Deletion of hepatocyte Bcl6 enhances lipid catabolism and ameliorates high-fat-diet-induced steatosis. In Ppara-null mice, hepatocyte Bcl6 ablation restores enhancer activity at PPARα-dependent genes and overcomes defective fasting-induced fatty acid oxidation and lipid accumulation. Together, these findings identify BCL6 as a negative regulator of oxidative metabolism and reveal that alternating recruitment of repressive and activating transcription factors to shared cis-regulatory regions dictates hepatic lipid handling.

Mitochondrial dysfunction is increasingly recognized as a critical determinant of both hereditary and acquired kidney diseases. However, it remains poorly understood how mitochondrial metabolism is regulated to support normal kidney function and how its dysregulation contributes to kidney disease. Here, we show that the nuclear receptor estrogen-related receptor gamma (ERRγ) and hepatocyte nuclear factor 1 beta (HNF1β) link renal mitochondrial and reabsorptive functions through coordinated epigenomic programs. ERRγ directly regulates mitochondrial metabolism but cooperatively controls renal reabsorption via convergent binding with HNF1β. Deletion of ERRγ in renal epithelial cells (RECs), in which it is highly and specifically expressed, results in severe renal energetic and reabsorptive dysfunction and progressive renal failure that recapitulates phenotypes of animals and patients with HNF1β loss-of-function gene mutations. Moreover, ERRγ expression positively correlates with renal function and is decreased in patients with chronic kidney disease (CKD). REC-ERRγ KO mice share highly overlapping renal transcriptional signatures with human patients with CKD. Together these findings reveal a role for ERRγ in directing independent and HNF1β-integrated programs for energy production and use essential for normal renal function and the prevention of kidney disease.

Skeletal muscles consist of fibers of differing metabolic activities and contractility, which become remodeled in response to chronic exercise, but the epigenomic basis for muscle identity and adaptation remains poorly understood. Here, we used chromatin immunoprecipitation sequencing of dimethylated histone 3 lysine 4 and acetylated histone 3 lysine 27 as well as transposase-accessible chromatin profiling to dissect cis-regulatory networks across muscle groups. We demonstrate that in vivo enhancers specify muscles in accordance with myofiber composition, show little resemblance to cultured myotube enhancers, and identify glycolytic and oxidative muscle-specific regulators. Moreover, we find that voluntary wheel running and muscle-specific peroxisome proliferator–activated receptor gamma coactivator-1 alpha (Pgc1a) transgenic (mTg) overexpression, which stimulate endurance performance in mice, result in markedly different changes to the epigenome. Exercise predominantly leads to enhancer hypoacetylation, whereas mTg causes hyperacetylation at different sites. Integrative analysis of regulatory regions and gene expression revealed that exercise and mTg are each associated with myocyte enhancer factor (MEF) 2 and estrogen-related receptor (ERR) signaling and transcription of genes promoting oxidative metabolism. However, exercise was additionally associated with regulation by retinoid X receptor (RXR), jun proto-oncogene (JUN), sine oculis homeobox factor (SIX), and other factors. Overall, our work defines the unique enhancer repertoires of skeletal muscles in vivo and reveals that divergent exercise-induced or PGC1α-driven epigenomic programs direct partially convergent transcriptional networks.