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• W1511590367 abstract "•SNPs determine genomic binding of adipose master regulator PPARγ in mice and humans•SNPs that impact PPARγ binding alter its motifs or those for cooperating factors•Variable PPARγ binding controls gene expression and anti-diabetic drug response•SNPs that alter PPARγ binding modulate human metabolic disease risk SNPs affecting disease risk often reside in non-coding genomic regions. Here, we show that SNPs are highly enriched at mouse strain-selective adipose tissue binding sites for PPARγ, a nuclear receptor for anti-diabetic drugs. Many such SNPs alter binding motifs for PPARγ or cooperating factors and functionally regulate nearby genes whose expression is strain selective and imbalanced in heterozygous F1 mice. Moreover, genetically determined binding of PPARγ accounts for mouse strain-specific transcriptional effects of TZD drugs, providing proof of concept for personalized medicine related to nuclear receptor genomic occupancy. In human fat, motif-altering SNPs cause differential PPARγ binding, provide a molecular mechanism for some expression quantitative trait loci, and are risk factors for dysmetabolic traits in genome-wide association studies. One PPARγ motif-altering SNP is associated with HDL levels and other metabolic syndrome parameters. Thus, natural genetic variation in PPARγ genomic occupancy determines individual disease risk and drug response. SNPs affecting disease risk often reside in non-coding genomic regions. Here, we show that SNPs are highly enriched at mouse strain-selective adipose tissue binding sites for PPARγ, a nuclear receptor for anti-diabetic drugs. Many such SNPs alter binding motifs for PPARγ or cooperating factors and functionally regulate nearby genes whose expression is strain selective and imbalanced in heterozygous F1 mice. Moreover, genetically determined binding of PPARγ accounts for mouse strain-specific transcriptional effects of TZD drugs, providing proof of concept for personalized medicine related to nuclear receptor genomic occupancy. In human fat, motif-altering SNPs cause differential PPARγ binding, provide a molecular mechanism for some expression quantitative trait loci, and are risk factors for dysmetabolic traits in genome-wide association studies. One PPARγ motif-altering SNP is associated with HDL levels and other metabolic syndrome parameters. Thus, natural genetic variation in PPARγ genomic occupancy determines individual disease risk and drug response. A major unanswered question is how most genetic variation causes phenotypic differences, as only a small fraction of single-nucleotide polymorphisms (SNPs) affect protein sequence (Shastry, 2002Shastry B.S. SNP alleles in human disease and evolution.J. Hum. Genet. 2002; 47: 561-566Crossref PubMed Scopus (276) Google Scholar). Current genome-wide association studies (GWAS) reveal a large gap between known causal genes and the observed heritability of common diseases and treatment outcomes (Sadee et al., 2014Sadee W. Hartmann K. Seweryn M. Pietrzak M. Handelman S.K. Rempala G.A. Missing heritability of common diseases and treatments outside the protein-coding exome.Hum. Genet. 2014; 133: 1199-1215Crossref PubMed Scopus (47) Google Scholar). Another limitation of GWAS is that each locus nominates a large group of SNPs in linkage disequilibrium, such that causal and neutral variants cannot easily be distinguished. Non-coding SNPs in regulatory regions may affect transcription factor (TF) binding and gene expression, thus contributing to complex phenotypes like disease association and response to drugs (Edwards et al., 2013Edwards S.L. Beesley J. French J.D. Dunning A.M. Beyond GWASs: illuminating the dark road from association to function.Am. J. Hum. Genet. 2013; 93: 779-797Abstract Full Text Full Text PDF PubMed Scopus (497) Google Scholar). There are examples of regulatory variants causing Mendelian syndromes (De Gobbi et al., 2006De Gobbi M. Viprakasit V. Hughes J.R. Fisher C. Buckle V.J. Ayyub H. Gibbons R.J. Vernimmen D. Yoshinaga Y. de Jong P. et al.A regulatory SNP causes a human genetic disease by creating a new transcriptional promoter.Science. 2006; 312: 1215-1217Crossref PubMed Scopus (221) Google Scholar, Smemo et al., 2012Smemo S. Campos L.C. Moskowitz I.P. Krieger J.E. Pereira A.C. Nobrega M.A. Regulatory variation in a TBX5 enhancer leads to isolated congenital heart disease.Hum. Mol. Genet. 2012; 21: 3255-3263Crossref PubMed Scopus (128) Google Scholar), but such SNPs may be more likely to associate with complex non-Mendelian diseases in GWAS (Sakabe et al., 2012Sakabe N.J. Savic D. Nobrega M.A. Transcriptional enhancers in development and disease.Genome Biol. 2012; 13: 238Crossref PubMed Scopus (96) Google Scholar). Overall, putative causal GWAS SNPs cluster more in promoters and enhancers than in exons (Andersson et al., 2014Andersson R. Gebhard C. Miguel-Escalada I. Hoof I. Bornholdt J. Boyd M. Chen Y. Zhao X. Schmidl C. Suzuki T. et al.FANTOM ConsortiumAn atlas of active enhancers across human cell types and tissues.Nature. 2014; 507: 455-461Crossref PubMed Scopus (1530) Google Scholar), and a recent effort to computationally identify causal GWAS SNPs for autoimmune diseases found that ∼90% were non-coding, with ∼60% in distal immune cell enhancers (Farh et al., 2015Farh K.K.-H. Marson A. Zhu J. Kleinewietfeld M. Housley W.J. Beik S. Shoresh N. Whitton H. Ryan R.J.H. Shishkin A.A. et al.Genetic and epigenetic fine mapping of causal autoimmune disease variants.Nature. 2015; 518: 337-343Crossref PubMed Scopus (1153) Google Scholar). A few specific examples have emerged. The causal SNP for an LDL cholesterol and myocardial infarction locus is a regulatory variant altering hepatic SORT1 expression (Musunuru et al., 2010Musunuru K. Strong A. Frank-Kamenetsky M. Lee N.E. Ahfeldt T. Sachs K.V. Li X. Li H. Kuperwasser N. Ruda V.M. et al.From noncoding variant to phenotype via SORT1 at the 1p13 cholesterol locus.Nature. 2010; 466: 714-719Crossref PubMed Scopus (808) Google Scholar). Regulatory SNPs in distant enhancers for MYC result in associations with multiple cancers (Sur et al., 2013Sur I. Tuupanen S. Whitington T. Aaltonen L.A. Taipale J. Lessons from functional analysis of genome-wide association studies.Cancer Res. 2013; 73: 4180-4184Crossref PubMed Scopus (49) Google Scholar), and an intronic enhancer SNP in TCF7L2 may mediate type 2 diabetes (T2D) risk (Gaulton et al., 2010Gaulton K.J. Nammo T. Pasquali L. Simon J.M. Giresi P.G. Fogarty M.P. Panhuis T.M. Mieczkowski P. Secchi A. Bosco D. et al.A map of open chromatin in human pancreatic islets.Nat. Genet. 2010; 42: 255-259Crossref PubMed Scopus (415) Google Scholar). For the PPARG T2D locus, the causal SNP was thought to be a coding Pro12Ala polymorphism, yet recent evidence has implicated a tightly linked regulatory SNP (Claussnitzer et al., 2014Claussnitzer M. Dankel S.N. Klocke B. Grallert H. Glunk V. Berulava T. Lee H. Oskolkov N. Fadista J. Ehlers K. et al.DIAGRAM+ConsortiumLeveraging cross-species transcription factor binding site patterns: from diabetes risk loci to disease mechanisms.Cell. 2014; 156: 343-358Abstract Full Text Full Text PDF PubMed Scopus (93) Google Scholar). PPARγ provides an excellent system to study effects of regulatory variation on TF binding, gene expression, drug response, and phenotype. PPARγ is a nuclear receptor TF required for adipocyte development (Wang et al., 2013Wang F. Mullican S.E. DiSpirito J.R. Peed L.C. Lazar M.A. Lipoatrophy and severe metabolic disturbance in mice with fat-specific deletion of PPARγ.Proc. Natl. Acad. Sci. USA. 2013; 110: 18656-18661Crossref PubMed Scopus (180) Google Scholar) that activates many adipocyte genes. PPARγ is genetically implicated in metabolic disease, both through the common SNP associated with T2D (Altshuler et al., 2000Altshuler D. Hirschhorn J.N. Klannemark M. Lindgren C.M. Vohl M.C. Nemesh J. Lane C.R. Schaffner S.F. Bolk S. Brewer C. et al.The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes.Nat. Genet. 2000; 26: 76-80Crossref PubMed Scopus (122) Google Scholar) and also through rare ligand binding domain mutations, causing an autosomal dominant syndrome of lipodystrophic insulin resistance (Barroso et al., 1999Barroso I. Gurnell M. Crowley V.E. Agostini M. Schwabe J.W. Soos M.A. Maslen G.L. Williams T.D. Lewis H. Schafer A.J. et al.Dominant negative mutations in human PPARgamma associated with severe insulin resistance, diabetes mellitus and hypertension.Nature. 1999; 402: 880-883Crossref PubMed Scopus (1158) Google Scholar). Since variants affecting the PPARγ TF itself have these consequences, then genetic variation in key PPARγ genomic binding sites may similarly have metabolic effects. PPARγ is also the target of anti-diabetic thiazolidinedione (TZD) drugs, which have a unique and powerful insulin-sensitizing effect, yet clinical use has declined due to concerns over side effects and adverse events (Soccio et al., 2014Soccio R.E. Chen E.R. Lazar M.A. Thiazolidinediones and the promise of insulin sensitization in type 2 diabetes.Cell Metab. 2014; 20: 573-591Abstract Full Text Full Text PDF PubMed Scopus (324) Google Scholar). Individuals differ in drug response, and ∼20%–30% of diabetic patients fail to respond to TZDs (Sears et al., 2009Sears D.D. Hsiao G. Hsiao A. Yu J.G. Courtney C.H. Ofrecio J.M. Chapman J. Subramaniam S. Mechanisms of human insulin resistance and thiazolidinedione-mediated insulin sensitization.Proc. Natl. Acad. Sci. USA. 2009; 106: 18745-18750Crossref PubMed Scopus (141) Google Scholar). Most pharmacogenomic studies focus on coding or non-coding variants affecting the drug target itself or drug-metabolizing enzymes and transporters (Mizzi et al., 2014Mizzi C. Peters B. Mitropoulou C. Mitropoulos K. Katsila T. Agarwal M.R. van Schaik R.H.N. Drmanac R. Borg J. Patrinos G.P. Personalized pharmacogenomics profiling using whole-genome sequencing.Pharmacogenomics. 2014; 15: 1223-1234Crossref PubMed Scopus (76) Google Scholar). However, regulatory variants may potentially alter downstream transcriptional effects of drugs, either indirectly after signal transduction from a cell surface receptor or directly in the case of DNA-binding nuclear receptors like PPARγ. Here, we set out to determine whether non-coding regulatory variation could affect PPARγ genomic occupancy and whether such SNP-dependent binding could affect gene expression, drug response, and metabolic phenotype. Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) was used to define genetically determined variation in PPARγ sites genome wide in white adipose tissue (WAT). In mice, sites with inbred strain-selective PPARγ genomic occupancy were highly enriched for SNPs, and in heterozygous F1 mice, these SNPs had allelic imbalance in PPARγ binding. These SNPs often altered TF motifs—not only motifs for PPARγ, but also motifs for other, cooperating TFs. Importantly, some strain-selective binding sites were functional regulating nearby gene expression in WAT, both basal and TZD stimulated. Similar studies were performed in human WAT, in whom SNPs also led to imbalanced PPARγ binding. Remarkably, these human SNPs were enriched in WAT expression quantitative trait loci (eQTLs) as well as in regions linked to metabolic disease in GWAS. Thus, variable PPARγ occupancy due to SNPs determines nearby gene activation by PPARγ and its ligands, and these effects may underlie genetic differences in metabolic phenotypes and drug responses. ChIP-seq was performed in WAT from two inbred mouse strains, C57Bl/6J (B6) and 129S1/SvImJ (129), which differ in susceptibility to obesity and insulin resistance (Almind and Kahn, 2004Almind K. Kahn C.R. Genetic determinants of energy expenditure and insulin resistance in diet-induced obesity in mice.Diabetes. 2004; 53: 3274-3285Crossref PubMed Scopus (206) Google Scholar). Since highly polymorphic 129 sequencing reads may not align to the B6 reference genome, the SNP-sensitive alignment tool GSNAP (Wu and Nacu, 2010Wu T.D. Nacu S. Fast and SNP-tolerant detection of complex variants and splicing in short reads.Bioinformatics. 2010; 26: 873-881Crossref PubMed Scopus (1363) Google Scholar) was used to eliminate alignment bias and identify truly strain-selective binding (Figures S1A and S1B). Three independent ChiP-seq experiments were performed (Table S1), allowing identification of strain-selective sites at high confidence (3-fold strain difference in reads in at least two out of three experiments) and highest confidence (all three, Figure 1A). Average peak heights in F1 intercross progeny were intermediate between parents, while nonselective sites were equal in all three (Figure 1B), indicating that strain selectivity of adipose genomic PPARγ occupancy was genetically determined. Of note, while WAT PPARγ cistromes include contributions of other cell types that express PPARγ, such as resident macrophages, the great majority of sites overlapped with those in 3T3-L1 adipocytes, but not with previously reported macrophage-selective sites (Lefterova et al., 2010Lefterova M.I. Steger D.J. Zhuo D. Qatanani M. Mullican S.E. Tuteja G. Manduchi E. Grant G.R. Lazar M.A. Cell-specific determinants of peroxisome proliferator-activated receptor gamma function in adipocytes and macrophages.Mol. Cell. Biol. 2010; 30: 2078-2089Crossref PubMed Scopus (174) Google Scholar), thus likely representing adipocyte binding sites.Figure 1SNPs Genetically Determine Mouse Strain-Selective PPARγ SitesShow full caption(A) ChIP-seq in mouse WAT identified ∼35,000 PPARγ sites, and the heat map shows 2,226 B6 or 129 strain-selective sites in three independent experiments. High-confidence sites were 3-fold strain selective in two, while highest-confidence sites were in all three.(B) For the five PPARγ site classes, average binding profiles are shown for the two inbred strains (B6 red, 129 blue) and F1 progeny (green).(C) For the five classes, occurrence of one or more B6:129 SNPs in each site’s central 200 bp is shown, with enrichment of SNPs in strain-selective sites (∗p < 0.0001 versus non-selective sites by Chi-square test).(D) In F1 ChIP-seq, allelic imbalance was assayed in binding sites with SNPs (∗p < 0.0001 versus non-selective sites by Mann-Whitney test, two-tailed).See also Figure S1 and Table S1.View Large Image Figure ViewerDownload Hi-res image Download (PPT) (A) ChIP-seq in mouse WAT identified ∼35,000 PPARγ sites, and the heat map shows 2,226 B6 or 129 strain-selective sites in three independent experiments. High-confidence sites were 3-fold strain selective in two, while highest-confidence sites were in all three. (B) For the five PPARγ site classes, average binding profiles are shown for the two inbred strains (B6 red, 129 blue) and F1 progeny (green). (C) For the five classes, occurrence of one or more B6:129 SNPs in each site’s central 200 bp is shown, with enrichment of SNPs in strain-selective sites (∗p < 0.0001 versus non-selective sites by Chi-square test). (D) In F1 ChIP-seq, allelic imbalance was assayed in binding sites with SNPs (∗p < 0.0001 versus non-selective sites by Mann-Whitney test, two-tailed). See also Figure S1 and Table S1. The B6 and 129 genomes differ by ∼5.3 million SNPs (Keane et al., 2011Keane T.M. Goodstadt L. Danecek P. White M.A. Wong K. Yalcin B. Heger A. Agam A. Slater G. Goodson M. et al.Mouse genomic variation and its effect on phenotypes and gene regulation.Nature. 2011; 477: 289-294Crossref PubMed Scopus (1058) Google Scholar), and strain-selective sites were highly enriched for occurrence of SNPs (Figure 1C). Notably, SNPs falling in B6- or 129-selective sites showed PPARγ binding allelic imbalance in F1 WAT favoring the allele with better parental binding, whereas SNPs in non-selective sites showed equal representation of both alleles (Figure 1D). F1 imbalance shows that cis-acting elements determine PPARγ occupancy, as selectivity is evident even when two alleles are in the same nucleus. To further validate cis-acting PPARγ site SNPs, ChIP-seq was performed in 3T3-L1 adipocytes, a cell line derived from outbred NIH Swiss albino mice (Todaro and Green, 1963Todaro G.J. Green H. Quantitative studies of the growth of mouse embryo cells in culture and their development into established lines.J. Cell Biol. 1963; 17: 299-313Crossref PubMed Scopus (2003) Google Scholar) and thus heterozygous at many loci. In these cells, PPARγ bound at ∼9,000 sites of B6:129 SNPs, and importantly, at least 18% were heterozygous (Figure S1C). At heterozygous sites where PPARγ binding was strain selective in B6 versus 129 WAT, the predicted allelic imbalance in binding was observed in 3T3-L1 adipocytes (Figure S1D). This is similar to F1 mice and confirms the powerful effect of cis-acting SNPs on PPARγ genomic binding. PPARγ binds DNA at direct repeat 1 (DR1) motifs both in vitro (Tontonoz et al., 1994Tontonoz P. Hu E. Graves R.A. Budavari A.I. Spiegelman B.M. mPPAR gamma 2: tissue-specific regulator of an adipocyte enhancer.Genes Dev. 1994; 8: 1224-1234Crossref PubMed Scopus (1996) Google Scholar) and in 3T3-L1 adipocytes (Lefterova et al., 2008Lefterova M.I. Zhang Y. Steger D.J. Schupp M. Schug J. Cristancho A. Feng D. Zhuo D. Stoeckert Jr., C.J. Liu X.S. Lazar M.A. PPARgamma and C/EBP factors orchestrate adipocyte biology via adjacent binding on a genome-wide scale.Genes Dev. 2008; 22: 2941-2952Crossref PubMed Scopus (613) Google Scholar, Nielsen et al., 2008Nielsen R. Pedersen T.A. Hagenbeek D. Moulos P. Siersbaek R. Megens E. Denissov S. Børgesen M. Francoijs K.-J. Mandrup S. Stunnenberg H.G. Genome-wide profiling of PPARgamma:RXR and RNA polymerase II occupancy reveals temporal activation of distinct metabolic pathways and changes in RXR dimer composition during adipogenesis.Genes Dev. 2008; 22: 2953-2967Crossref PubMed Scopus (436) Google Scholar), and this was the top motif found in WAT PPARγ sites (Figure 2A). To test whether DR1-altering SNPs cause strain-selective binding, all polymorphic DR1 motifs in PPARγ binding regions were identified and assigned motif scores, such that the B6:129 score ratio indicated strain difference in consensus motif agreement. SNPs with large effects on PPARγ/DR1 motifs (ratio >16) were highly likely to show selective binding in the strain with the stronger motif and were unlikely to be selective for the opposite strain (Figure 2B). This discrimination was apparent even when SNPs had medium (8- to 16-fold) or small (2- to 8-fold) motif effects but effectively lost when SNPs had minimal effects (<2-fold). While this analysis used thresholds for motif effects and binding difference, the same pattern emerged in a quantitative scatterplot analysis correlating binding ratio versus motif ratio (Figure S2A). This approach relies on natural B6:129 genetic variation at PPARγ motifs but can be extended to other variants. For instance, 3T3-L1 PPARγ sites have 936 heterozygous SNPs that are non-polymorphic between B6 and 129, and when these SNPs altered PPARγ/DR1 motifs, there was the predicted allelic imbalance in PPARγ occupancy (Figure S2B).Figure S2PPARγ Binding Is Altered by SNPs Affecting Motifs for PPARγ or Other TFs, Related to Figure 2Show full caption(A) 579 WAT PPARγ binding sites had DR1 motifs with B6:129 SNPs, and the strain difference in PPARγ binding (mean log2 fold change in three ChIP-seq experiments) was correlated with allelic difference in motif agreement (log2 motif score ratio, linear regression r2 = 0.29, and p < 0.0001 for a non-zero slope). (B) 3T3-L1 adipocyte PPARγ sites showed heterozygousity at other SNPs that did not differ between B6 and 129 mice. If these SNPs had more than minimal effects on PPARγ DR1 motifs, they showed 2-fold imbalanced PPARγ occupancy favoring the allele with the stronger motif. (C) Identification of each location in the consensus 16bp PPARγ DR1 motif logo, consisting of two nuclear receptor AGGTCA half sites separated by a 1bp spacer, and three conserved 5′ bases. For each designated motif location, B6:129 SNP alleles gave different agreement with the consensus as reflected by the mean motif ratio for all such SNPs. Graphs D-H show how many such binding sites showed 50% selectivity for the strain with the stronger (green) or weaker (orange) motif allele, versus non-selectivity (gray). (D) Two examples in which motif differences strongly predict binding selectivity. (E) At the spacer between the two half sites, A and G appear almost equally in the consensus motif, yet A:G SNPs clearly favor the A allele, though G is favored over C and T. (F) At the first position of each half site, A:G SNPs show better binding to A despite similar motif agreement. (G) At the 5′ flanking -1 and -3 positions, SNP alleles strongly affect binding. (H) Same graph for those motifs with B6:129 SNPs at more than one location in the same 16bp DR1 motif.View Large Image Figure ViewerDownload Hi-res image Download (PPT) (A) 579 WAT PPARγ binding sites had DR1 motifs with B6:129 SNPs, and the strain difference in PPARγ binding (mean log2 fold change in three ChIP-seq experiments) was correlated with allelic difference in motif agreement (log2 motif score ratio, linear regression r2 = 0.29, and p < 0.0001 for a non-zero slope). (B) 3T3-L1 adipocyte PPARγ sites showed heterozygousity at other SNPs that did not differ between B6 and 129 mice. If these SNPs had more than minimal effects on PPARγ DR1 motifs, they showed 2-fold imbalanced PPARγ occupancy favoring the allele with the stronger motif. (C) Identification of each location in the consensus 16bp PPARγ DR1 motif logo, consisting of two nuclear receptor AGGTCA half sites separated by a 1bp spacer, and three conserved 5′ bases. For each designated motif location, B6:129 SNP alleles gave different agreement with the consensus as reflected by the mean motif ratio for all such SNPs. Graphs D-H show how many such binding sites showed 50% selectivity for the strain with the stronger (green) or weaker (orange) motif allele, versus non-selectivity (gray). (D) Two examples in which motif differences strongly predict binding selectivity. (E) At the spacer between the two half sites, A and G appear almost equally in the consensus motif, yet A:G SNPs clearly favor the A allele, though G is favored over C and T. (F) At the first position of each half site, A:G SNPs show better binding to A despite similar motif agreement. (G) At the 5′ flanking -1 and -3 positions, SNP alleles strongly affect binding. (H) Same graph for those motifs with B6:129 SNPs at more than one location in the same 16bp DR1 motif. Individual nucleotide substitutions at each position of the DR1 motif (Figure S2C) were interrogated for PPARγ occupancy effects. Overall, this strongly validated the motif ratio approach, though there were informative exceptions where SNPs at some locations had large occupancy effects despite apparently small motif effects (Figures S2D–S2F). This reinforces a key point about consensus ChIP-seq motifs: they reflect nucleotide frequencies at motifs actually bound by the TF but may not necessarily represent the strongest binding version of the motif. Also, in addition to the core DR1 motif, three upstream bases also determined PPARγ occupancy (Figure S2G), confirming in vivo the importance of 5′ flanking sequence as reported in prior in vitro studies (Juge-Aubry et al., 1997Juge-Aubry C. Pernin A. Favez T. Burger A.G. Wahli W. Meier C.A. Desvergne B. DNA binding properties of peroxisome proliferator-activated receptor subtypes on various natural peroxisome proliferator response elements. Importance of the 5′-flanking region.J. Biol. Chem. 1997; 272: 25252-25259Crossref PubMed Scopus (321) Google Scholar) and the X-ray crystal structure (Chandra et al., 2008Chandra V. Huang P. Hamuro Y. Raghuram S. Wang Y. Burris T.P. Rastinejad F. Structure of the intact PPAR-gamma-RXR- nuclear receptor complex on DNA.Nature. 2008; 456: 350-356Crossref PubMed Scopus (591) Google Scholar). Finally, the most drastic effects on DR1 motifs and PPARγ binding occurred when multiple SNPs altered the same motif (Figure S2H). PPARγ often binds DNA in close proximity to C/EBP TFs, and the two facilitate each other’s binding by assisted loading (Madsen et al., 2014Madsen M.S. Siersbæk R. Boergesen M. Nielsen R. Mandrup S. Peroxisome proliferator-activated receptor γ and C/EBPα synergistically activate key metabolic adipocyte genes by assisted loading.Mol. Cell. Biol. 2014; 34: 939-954Crossref PubMed Scopus (145) Google Scholar). Consistent with other reported PPARγ cistromes (Lefterova et al., 2008Lefterova M.I. Zhang Y. Steger D.J. Schupp M. Schug J. Cristancho A. Feng D. Zhuo D. Stoeckert Jr., C.J. Liu X.S. Lazar M.A. PPARgamma and C/EBP factors orchestrate adipocyte biology via adjacent binding on a genome-wide scale.Genes Dev. 2008; 22: 2941-2952Crossref PubMed Scopus (613) Google Scholar, Nielsen et al., 2008Nielsen R. Pedersen T.A. Hagenbeek D. Moulos P. Siersbaek R. Megens E. Denissov S. Børgesen M. Francoijs K.-J. Mandrup S. Stunnenberg H.G. Genome-wide profiling of PPARgamma:RXR and RNA polymerase II occupancy reveals temporal activation of distinct metabolic pathways and changes in RXR dimer composition during adipogenesis.Genes Dev. 2008; 22: 2953-2967Crossref PubMed Scopus (436) Google Scholar), at WAT PPARγ sites, the top non-DR1 motif was for C/EBP (Figure 2A). As with DR1, SNPs with large C/EBP motif effects caused the predicted strain selectivity in PPARγ occupancy (Figure 2C). In addition to PPARγ and C/EBP, a motif for the nuclear factor I (NFI) family was also enriched at PPARγ binding sites, consistent with previous reports (Rajakumari et al., 2013Rajakumari S. Wu J. Ishibashi J. Lim H.-W. Giang A.-H. Won K.-J. Reed R.R. Seale P. EBF2 determines and maintains brown adipocyte identity.Cell Metab. 2013; 17: 562-574Abstract Full Text Full Text PDF PubMed Scopus (247) Google Scholar). SNPs with large NFI motif effects also gave strain selectivity in PPARγ binding (Figure 2D), indicating that an NFI TF can modulate PPARγ genomic binding in vivo. Thus, in addition to the well-known PPARγ-cooperating factor C/EBP, this SNP-based method can also suggest functional relevance for novel candidate TFs. The next highest motif found in PPARγ sites was a glucocorticoid receptor (GR) motif, and SNPs altering this inverted repeat 3 (IR3) motif affected PPARγ occupancy (Figure 2E). The effect of IR3 motifs was independent, as an IR3 motif SNP never also affected an overlapping DR1. GR plays a major role in adipocyte biology (Steger et al., 2010Steger D.J. Grant G.R. Schupp M. Tomaru T. Lefterova M.I. Schug J. Manduchi E. Stoeckert Jr., C.J. Lazar M.A. Propagation of adipogenic signals through an epigenomic transition state.Genes Dev. 2010; 24: 1035-1044Crossref PubMed Scopus (198) Google Scholar). GR ChIP-seq performed in WAT from B6 and 129 mice revealed strain-selective GR binding (Figure S3A) at sites highly enriched for SNPs (Figure S3B), and SNPs in GR motifs had predicted effects on GR occupancy (Figure S3C). Moreover, the majority of PPARγ binding sites in WAT are also occupied by GR, and hundreds of sites had high-confidence strain-selective binding of both factors (Figure S3D). Many had motif-altering SNPs in PPARγ, GR, or C/EBP motifs, and all three types of SNPs could mediate strain-selective binding of both PPARγ and GR (Figures S3E and S3F). Therefore, SNPs altering PPARγ motifs not only affect PPARγ occupancy, but also binding of other TFs like GR. Conversely, PPARγ binding can be altered by SNPs in PPARγ motifs as well as motifs for other TFs, showing the powerful effect of motif SNPs on cooperative binding of multiple TFs. Selective sites with SNPs but not identifiable motifs (Figure S3G), may be due to SNPs affecting degenerate or non-consensus motifs for these TFs or other TF motifs, yet many strain-selective sites are non-polymorphic over 200 bp. Such unexplained strain-selective sites, with or without SNPs, may result from long-range interactions with other sites in the same locus, and this is consistent with the observed clustering of both B6- and 129-selective binding sites near other sites selective for the same strain (Figure S3H). The great majority of PPARγ sites, including the genetically determined sites defined here, reside outside of promoters >5 kb from transcription start sites (TSSs). The function of sites as enhancers correlates with occupancy of cofactors such as Med1 and p300, as well as with transcription of enhancer RNA (eRNA) identified by global run-on sequencing (GRO-seq) (Hah et al., 2013Hah N. Murakami S. Nagari A. Danko C.G. Kraus W.L. Enhancer transcripts mark active estrogen receptor binding sites.Genome Res. 2013; 23: 1210-1223Crossref PubMed Scopus (332) Google Scholar, Step et al., 2014Step S.E. Lim H.-W. Marinis J.M. Prokesch A. Steger D.J. You S.-H. Won K.-J. Lazar M.A. Anti-diabetic rosiglitazone remodels the adipocyte transcriptome by redistributing transcription to PPARγ-driven enhancers.Genes Dev. 2014; 28: 1018-1028Crossref PubMed Scopus (78) Google Scholar). GRO-seq was performed in WAT from B6 mice, and eRNA was quantified at PPARγ sites. High eRNA transcription in B6 WAT was present at ∼18% of B6-selective sites, a significant 3-fold enrichment versus the 129-selective sites with little PPARγ binding in B6 mice, the majority of which had no detectable eRNA transcription (Figure 3A). Thus, strain-selective PPARγ binding in WAT correlated with functional enhancer activity defined by eRNA transcription. Moreover, ChIP-seq for coactivators in 3T3-L1 adipocyte" @default.
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• W1511590367 date "2015-07-01" @default.
• W1511590367 modified "2023-10-17" @default.
• W1511590367 title "Genetic Variation Determines PPARγ Function and Anti-diabetic Drug Response In Vivo" @default.
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