Genome-Wide Profiling of H3K56 Acetylation and Transcription Factor Binding Sites in Human Adipocytes

Lo, Kinyui Alice; Bauchmann, Mary K.; Baumann, Amy; Donahue, Christopher J.; Thiede, Mark A.; Hayes, Lisa S.; Etages, Shelley Ann G. des; Fraenkel, Ernest

doi:10.1371/journal.pone.0019778

Cited by 51 publications

(39 citation statements)

References 31 publications

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“…We currently include all available ENCODE transcription factor (TF) ChIP-seq, histone ChIP-seq, FAIRE, and DNase I hypersensitive site data (The ENCODE Project Consortium 2012). In addition, we have included transcription factor ChIP-seq data available from the NCBI Sequence Read Archive (Hollenhorst et al 2009;Jolma et al 2010;Verzi et al 2010;Wei et al 2010;Hu et al 2011;Lo et al 2011;Novershtern et al 2011;Palii et al 2011;Yu et al 2011). We also include a large collection of eQTL (Myers et al 2007;Stranger et al 2007;Schadt et al 2008;Veyrieras et al 2008;Dimas et al 2009;Gibbs et al 2010;Montgomery et al 2010;Pickrell et al 2010;Zeller et al 2010), dsQTL (Degner et al 2012, and ChIP-exo (Rhee and Pugh 2011) data.…”

Section: Data Sources For Regulomedbmentioning

confidence: 99%

Annotation of functional variation in personal genomes using RegulomeDB

et al. 2012

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As the sequencing of healthy and disease genomes becomes more commonplace, detailed annotation provides interpretation for individual variation responsible for normal and disease phenotypes. Current approaches focus on direct changes in protein coding genes, particularly nonsynonymous mutations that directly affect the gene product. However, most individual variation occurs outside of genes and, indeed, most markers generated from genome-wide association studies (GWAS) identify variants outside of coding segments. Identification of potential regulatory changes that perturb these sites will lead to a better localization of truly functional variants and interpretation of their effects. We have developed a novel approach and database, RegulomeDB, which guides interpretation of regulatory variants in the human genome. RegulomeDB includes high-throughput, experimental data sets from ENCODE and other sources, as well as computational predictions and manual annotations to identify putative regulatory potential and identify functional variants. These data sources are combined into a powerful tool that scores variants to help separate functional variants from a large pool and provides a small set of putative sites with testable hypotheses as to their function. We demonstrate the applicability of this tool to the annotation of noncoding variants from 69 full sequenced genomes as well as that of a personal genome, where thousands of functionally associated variants were identified. Moreover, we demonstrate a GWAS where the database is able to quickly identify the known associated functional variant and provide a hypothesis as to its function. Overall, we expect this approach and resource to be valuable for the annotation of human genome sequences. [Supplemental material is available for this article.]The increasing number of sequenced human genomes is providing a catalog of the large number of individual variations present in the human genome (The International HapMap Consortium 2005; The 1000 Genomes Project Consortium 2010). Many of these variants are expected to be responsible for normal and disease phenotypes. Similarly, large, genome-wide association studies (GWAS) continue to map diseases to associated genomic regions from large cohorts of individuals (Hindorff et al. 2012). Initial interpretation of results generated by both of these approaches has been limited to DNA regions that cause disruption of gene function through coding sequence changes typically identified using an application such as PolyPhen-2 (Adzhubei et al. 2010). However, ;95% of known variants within sequenced genomes and 88% of those variants from GWAS studies fall outside of coding regions and have been difficult to interpret ).Both large consortia and individual labs are generating a significant amount of regulatory information that is providing a better interpretation of the noncoding portions of the genome. The ENCODE Project, in particular, has mapped open chromatin and protein binding regions for large numbers of factors across many cell type...

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Section: Data Sources For Regulomedbmentioning

confidence: 99%

Annotation of functional variation in personal genomes using RegulomeDB

et al. 2012

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“…Decreased acetylation was more specifically detected at H3K14 and H3K56 (Fig 4G,H). Acetylation at this latter position is associated with transcriptional activation in both yeast [23][24][25] and mammalian cells [26][27][28] and possibly linked to H3S57 phosphorylation during transcriptional elongation [29].…”

Section: Embo Reportsmentioning

confidence: 99%

DYRK1A phoshorylates histone H3 to differentially regulate the binding of HP1 isoforms and antagonize HP1‐mediated transcriptional repression

et al. 2014

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Heterochromatin protein 1 (HP1) proteins are chromatin-bound transcriptional regulators. While their chromodomain binds histone H3 methylated on lysine 9, their chromoshadow domain associates with the H3 histone fold in a region involved in chromatin remodeling. Here, we show that phosphorylation at histone H3 threonine 45 and serine 57 within this latter region differentially affects binding of the three mammalian HP1 isoforms HP1a, HP1b and HP1c. Both phosphorylation events are dependent on the activity of the DYRK1A kinase that antagonizes HP1-mediated transcriptional repression and participates in abnormal activation of cytokine genes in Downs syndrome-associated megakaryoblastic leukemia.

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“…ChIP was performed as described (28,29) with modifications. Five micrograms of specific or control antibody (HNF4-α, sc-8971; rabbit IgG, sc-2027) was incubated with preblocked Dyanbead Protein A (100.02D; Invitrogen) overnight.…”

Section: Hnf4amentioning

confidence: 99%

Adiponectin regulates expression of hepatic genes critical for glucose and lipid metabolism

Liu

Yuan

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

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The effects of adiponectin on hepatic glucose and lipid metabolism at transcriptional level are largely unknown. We profiled hepatic gene expression in adiponectin knockout (KO) and wild-type (WT) mice by RNA sequencing. Compared with WT mice, adiponectin KO mice fed a chow diet exhibited decreased mRNA expression of ratelimiting enzymes in several important glucose and lipid metabolic pathways, including glycolysis, tricarboxylic acid cycle, fatty-acid activation and synthesis, triglyceride synthesis, and cholesterol synthesis. In addition, binding of the transcription factor Hnf4a to DNAs encoding several key metabolic enzymes was reduced in KO mice, suggesting that adiponectin might regulate hepatic gene expression via Hnf4a. Phenotypically, adiponectin KO mice possessed smaller epididymal fat pads and showed reduced body weight compared with WT mice. When fed a high-fat diet, adiponectin KO mice showed significantly reduced lipid accumulation in the liver. These lipogenic defects are consistent with the down-regulation of lipogenic genes in the KO mice.hepatic metabolism | lipogenesis | transcriptional regulation A dipose tissue regulates energy homeostasis by secreting cytokines known as adipokines. Adiponectin, the most abundant adipokine in the serum, modulates lipid and glucose metabolism, including promotion of fatty acid oxidation and glucose utilization and repression of hepatic gluconeogenesis (1, 2). Several lines of adiponectin knockout (KO) or transgenic (Tg) mice have been generated in different laboratories (3, 4). Although the phenotypes reported are variable in some aspects, these mouse models all demonstrate that adiponectin deficiency predisposed mice to high-fat-diet (HFD)-induced insulin resistance (3-5). It was proposed that adiponectin is required to maintain a basal tone of insulin responsiveness (5). However, the way in which the basal tone of insulin responsiveness is established and how adiponectin maintains insulin sensitivity remain largely unknown.Adiponectin is present in plasma at extremely high concentrations (2-10 μg/mL), in contrast to that of insulin, glucagon, and leptin, which are found at orders-of-magnitude smaller concentrations. Moreover, most metabolic hormones are released into the blood in a regulated pulsatile fashion (6); this process allows the insulin's actions to respond to nutritional signals following meals or for glucagon to increase hepatic glucose output during hypoglycemia. In contrast, the blood levels of adiponectin are strikingly constant, making adiponectin a less-sensitive regulator in response to the acute changes in glucose and lipid levels following food intake or deprivation. We therefore hypothesize that adiponectin primarily regulates glucose and lipid metabolism at transcriptional levels besides its well described role that involves AMP-activated protein kinase (AMPK).To test this hypothesis, we profiled hepatic gene expression in both wild-type (WT) and adiponectin KO mice fed a standard chow diet by high-throughput RNA sequencing (RNA-Seq). ...

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Genome-Wide Profiling of H3K56 Acetylation and Transcription Factor Binding Sites in Human Adipocytes

Cited by 51 publications

References 31 publications

Annotation of functional variation in personal genomes using RegulomeDB

Annotation of functional variation in personal genomes using RegulomeDB

DYRK1A phoshorylates histone H3 to differentially regulate the binding of HP1 isoforms and antagonize HP1‐mediated transcriptional repression

Adiponectin regulates expression of hepatic genes critical for glucose and lipid metabolism

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