The KDM5 family is required for activation of pro-proliferative cell cycle genes during adipocyte differentiation.

The KDM5 family of histone demethylases removes the H3K4 tri-methylation (H3K4me3) mark frequently found at promoter regions of actively transcribed genes and is therefore generally considered to contribute to corepression. In this study, we show that knockdown (KD) of all expressed members of the KDM5 family in white and brown preadipocytes leads to deregulated gene expression and blocks differentiation to mature adipocytes. KDM5 KD leads to a considerable increase in H3K4me3 at promoter regions; however, these changes in H3K4me3 have a limited effect on gene expression per se. By contrast, genome-wide analyses demonstrate that KDM5A is strongly enriched at KDM5-activated promoters, which generally have high levels of H3K4me3 and are associated with highly expressed genes. We show that KDM5-activated genes include a large set of cell cycle regulators and that the KDM5s are necessary for mitotic clonal expansion in 3T3-L1 cells, indicating that KDM5 KD may interfere with differentiation in part by impairing proliferation. Notably, the demethylase activity of KDM5A is required for activation of at least a subset of pro-proliferative cell cycle genes. In conclusion, the KDM5 family acts as dual modulators of gene expression in preadipocytes and is required for early stage differentiation and activation of pro-proliferative cell cycle genes.

Rare variant association analysis in 51,256 type 2 diabetes cases and 370,487 controls informs the spectrum of pathogenicity of monogenic diabetes genes.

We meta-analyzed array data imputed with the TOPMed reference panel and whole-genome sequence (WGS) datasets and performed the largest, rare variant (minor allele frequency as low as 5×10-5) GWAS meta-analysis of type 2 diabetes (T2D) comprising 51,256 cases and 370,487 controls. We identified 52 novel variants at genome-wide significance (p<5 × 10-8), including 8 novel variants that were either rare or ancestry-specific. Among them, we identified a rare missense variant in HNF4A p.Arg114Trp (OR=8.2, 95% confidence interval [CI]=4.6-14.0, p = 1.08×10-13), previously reported as a variant implicated in Maturity Onset Diabetes of the Young (MODY) with incomplete penetrance. We demonstrated that the diabetes risk in carriers of this variant was modulated by a T2D common variant polygenic risk score (cvPRS) (carriers in the top PRS tertile [OR=18.3, 95%CI=7.2-46.9, p=1.2×10-9] vs carriers in the bottom PRS tertile [OR=2.6, 95% CI=0.97-7.09, p = 0.06]. Association results identified eight variants of intermediate penetrance (OR>5) in monogenic diabetes (MD), which in aggregate as a rare variant PRS were associated with T2D in an independent WGS dataset (OR=4.7, 95% CI=1.86-11.77], p = 0.001). Our data also provided support evidence for 21% of the variants reported in ClinVar in these MD genes as benign based on lack of association with T2D. Our work provides a framework for using rare variant imputation and WGS analyses in large-scale population-based association studies to identify large-effect rare variants and provide evidence for informing variant pathogenicity.

Lipolysis regulates major transcriptional programs in brown adipocytes.

ß-Adrenergic signaling is a core regulator of brown adipocyte function stimulating both lipolysis and transcription of thermogenic genes, thereby expanding the capacity for oxidative metabolism. We have used pharmacological inhibitors and a direct activator of lipolysis to acutely modulate the activity of lipases, thereby enabling us to uncover lipolysis-dependent signaling pathways downstream of ß-adrenergic signaling in cultured brown adipocytes. Here we show that induction of lipolysis leads to acute induction of several gene programs and is required for transcriptional regulation by ß-adrenergic signals. Using machine-learning algorithms to infer causal transcription factors, we show that PPARs are key mediators of lipolysis-induced activation of genes involved in lipid metabolism and thermogenesis. Importantly, however, lipolysis also activates the unfolded protein response and regulates the core circadian transcriptional machinery independently of PPARs. Our results demonstrate that lipolysis generates important metabolic signals that exert profound pleiotropic effects on transcription and function of cultured brown adipocytes.

Highly interconnected enhancer communities control lineage-determining genes in human mesenchymal stem cells.

Adipocyte differentiation is driven by waves of transcriptional regulators that reprogram the enhancer landscape and change the wiring of the promoter interactome. Here, we use high-throughput chromosome conformation enhancer capture to interrogate the role of enhancer-to-enhancer interactions during differentiation of human mesenchymal stem cells. We find that enhancers form an elaborate network that is dynamic during differentiation and coupled with changes in enhancer activity. Transcription factors (TFs) at baited enhancers amplify TF binding at target enhancers, a phenomenon we term cross-interaction stabilization of TFs. Moreover, highly interconnected enhancers (HICE) act as integration hubs orchestrating differentiation by the formation of three-dimensional enhancer communities, inside which, HICE, and other enhancers, converge on phenotypically important gene promoters. Collectively, these results indicate that enhancer interactions play a key role in the regulation of enhancer function, and that HICE are important for both signal integration and compartmentalization of the genome.

Osteogenesis depends on commissioning of a network of stem cell transcription factors that act as repressors of adipogenesis.

Mesenchymal (stromal) stem cells (MSCs) constitute populations of mesodermal multipotent cells involved in tissue regeneration and homeostasis in many different organs. Here we performed comprehensive characterization of the transcriptional and epigenomic changes associated with osteoblast and adipocyte differentiation of human MSCs. We demonstrate that adipogenesis is driven by considerable remodeling of the chromatin landscape and de novo activation of enhancers, whereas osteogenesis involves activation of preestablished enhancers. Using machine learning algorithms for in silico modeling of transcriptional regulation, we identify a large and diverse transcriptional network of pro-osteogenic and antiadipogenic transcription factors. Intriguingly, binding motifs for these factors overlap with SNPs related to bone and fat formation in humans, and knockdown of single members of this network is sufficient to modulate differentiation in both directions, thus indicating that lineage determination is a delicate balance between the activities of many different transcription factors.

Author Correction: Osteogenesis depends on commissioning of a network of stem cell transcription factors that act as repressors of adipogenesis.

In the version of this article initially published, in the graph keys in Fig. 1i, the colors indicating 'Ob' and 'Ad' were red and blue, respectively, but should have been blue and red, respectively; the shapes indicating 'MUS' and 'BM' were a triangle and a square, respectively, but should have been a square and a triangle, respectively. The errors have been corrected in the HTML and PDF versions of the article.