BCMO1 (Accession number GenBank: AJ271386), encoding the β-carotene 15, 15′-monooxygenase, a key enzyme in the conversion of β-carotene into colorless retinal, was a good functional candidate. Analysis of the abundance of BCMO1 mRNA in breast muscle of the HG x LG F2 population allowed for the identification of a strong cis eQTL. Moreover, reevaluation of the color QTL taking BCMO1 mRNA levels as a covariate indicated that BCMO1 mRNA levels entirely explained the variations in meat color. Two fully-linked single nucleotide polymorphisms (SNP) located within the proximal promoter of BCMO1 gene were identified. Haplotype substitution resulted in a marked difference in BCMO1 promoter activity in vitro. The association study in the F2 population revealed a three-fold difference in BCMO1 expression leading to a difference of 1 standard deviation in yellow color between the homozygous birds at this haplotype. This difference in meat yellow color was fully consistent with the difference in carotenoid content (i.e. lutein and zeaxanthin) evidenced between the two alternative haplotypes. A significant association between the haplotype, the level of BCMO1 expression and the yellow color of the meat was also recovered in an unrelated commercial broiler population. The mutation could be of economic importance for poultry production by making possible a gene-assisted selection for color, a determining aspect of meat quality. Moreover, this natural genetic diversity constitutes a new model for the study of β-carotene metabolism which may act upon diverse biological processes as precursor of the vitamin A.Classical quantitative trait loci (QTL) analysis and gene expression QTL (eQTL) were combined to identify the causal gene (or QTG) underlying a highly significant QTL controlling the variation of breast meat color in a F2 cross between divergent high-growth (HG) and low-growth (LG) chicken lines. Within this meat quality QTL,  GGA11 that affects color of breast meat  For more than half of a century, commercial poultry breeding programs have focused mainly on improvements of two major production traits, growth rate and feed efficiency, in meat-type (broiler) chickens. Furthermore, different experimental lines of chickens have been created to increase our understanding of genetic control over other important production traits, including meat quality. Our unique model is a population of meat-type chickens that was divergently selected for high (HG) or low growth (LG) rate, based on a difference in body weight (BW) at both 8 and 36 weeks of age GGA11. To refine the QTL location, three additional markers were developed and the QTL re-analyzed. As shown in vs. 69 cM), although the significance level was higher (F statistic of 95 vs. 63). In addition, the confidence interval of the QTL was reduced from 35 (13.3–21.9 Mb) to 17 cM (14.4–18.4 Mb). The origin of the high allele for BCo-Y was traced back to the LG line, which was consistent with the more intense yellow color of breast meat in this genotype. The QTL on GGA11 explained about 14% of the phenotypic variance in the BCo-Y trait in the HG x LG F2 population. Half-sib analysis showed that all F1 sires were heterozygous at this QTL, which suggested fixation of alternative alleles in the founder lines originally created from a mixing of several commercial breeds. Similar improvements in refinement of the QTL were obtained for the breast muscle redness (BCo-R), although the level of significance for this trait remained lower. The QTL region for the breast muscle redness trait (BCo-R) overlapped that for yellowness trait (BCo-Y). These observations suggested a strong impact of the GGA11 QTL on the variation of meat color observed between the HG and LG lines.At the step of initial mapping, the position of the meat color QTL was imprecise, due to the lack of microsatellite markers on the distal end of BCMO1, being located on GGA11 between 17.085 and 17.105 Mbp, the approximate location of the observed BCo-Y QTL  into two colorless retinal (pro-vitamin A) molecules BCMO1 mRNA levels in the breast muscle of HG and LG birds across six ages (1-11 wk). As reported in BCMO1 mRNA was consistently higher in the Pectoralis major muscle of HG chickens compared to LG chickens, regardless of age. This large difference in abundance of BCMO1 transcripts between LG and HG birds was evident with or without normalization to 18S ribosomal RNA levels. We then examined the relationship between variations of BCMO1 mRNA levels and the yellowness of breast meat (BCo-Y) in the segregating HG x LG F2 population. Breast muscle BCMO1 mRNA levels were quantified in one of the five F1 half-sib families (n = 134). A significant negative correlation (r =  −0.47) between BCMO1 mRNA levels and the BCo-Y measurements was observed. Subsequently, a QTL analysis was performed on GGA11 using BCMO1 mRNA levels as a quantitative trait. As shown in cis expression QTL (eQTL) was detected that was even more significant than the original BCo-Y QTL (vs. 14). The high allele for the eQTL (BCMO1 mRNA) was traced back to the HG line, indicating that higher expression of the BCMO1 gene is linked to lower meat yellowness in HG birds. The QTL analysis for the BCo-Y trait was also completed using breast muscle BCMO1 mRNA levels as a covariate. As illustrated by GGA11 disappeared after this correction. Collectively, these observations clearly show that the variation in the BCo-Y trait is linked to the variation of BCMO1 mRNA levels in breast muscle.Refinement of this meat quality QTL region reduced the number of positional candidate genes from about 140 in the initial mapping to 30 genes. The most obvious candidate gene was Co-Y QTL . FurtherBCMO1 gene to identify mutations underlying variations in BCMO1 transcript levels. The causal mutation was expected to be heterozygous in the five F1 sires, which were all heterozygous for BCo-Y QTL. Amplified fragments of the BCMO1 gene were sequenced in the five F1 sires from the HG x LG intercross, where a total of 23 SNP and 4 insertion/deletion polymorphisms were identified in the BCMO1 gene and its promoter. Six of the SNP observed in our population are publically available . Twenty-one new polymorphisms were observed (accession numbers ss325995734 to ss325995754). Six of the 23 SNP were heterozygous for all F1 sires: one semi-conservative SNP  was within exon 11, without any supposed effect on BCMO1 mRNA level, two SNP were within intron 8, one within intron 9 and, interestingly, two SNPs within the promoter region. Since the QTL controlled the BCMO1 gene expression and since the promoter is known as a region regulating expression, the last two SNPs positioned at −678 (SNP1) and −621 (SNP2) upstream of ATG (BCMO1 mRNA levels and meat color traits (BCo-Y and BCo-R) in the HG x LG F2 population. The two SNPs in the BCMO1 promoter were fully linked defining two AN57A and GN57G haplotypes. No recombinant AN57G or GN57A haplotype was observed in any of the F0, F1 or F2 birds. Genotyping of 35 F0 birds showed a difference in allele frequencies between the two lines. The GN57G haplotype was fixed in F0 LG birds (N = 20) while the AN57A haplotype was predominant in F0 HG birds (9 of 13 birds tested had the AN57A type). As shown in BCMO1 mRNA levels. Least square means (LSM) for mRNA levels were estimated at 1.17 (N = 63) and -0.48 (N = 101) in homozygous AN57A and GN57G birds, which corresponded to a 3 fold higher abundance of BCMO1 transcripts in the AN57A birds than in the GN57G birds. The two haplotypes acted additively, the heterozygous birds (AN57A/GN57G) showing intermediate mRNA levels . As shown by 57A, the heterozygous AN57A/GN57G, and the homozygous GN57G, respectively]. A lower but significant effect was found for the red color of the meat with a difference of 0.6 unit of BCo-R (∼0.75 S.D.) between extreme homozygous genotypes, the heterozygous genotype being intermediate .Next, we sequenced the promoter region and 11 exons of the m of ATG  were con57G (n = 11) than in AN57A (n = 9) with a ratio of 1.9 and 1.8 for lutein and zeaxanthin, respectively  and 0.4 unit of a* (p = 0.006) between the homozygous birds . The effect of the haplotype on BCMO1 expression was evaluated in a sample of 11 AN57A and 12 GN57G homozygous birds. BCMO1 mRNA levels were three-fold higher while BCo-Y values were significantly lower in AN57A compared to GN57G  and recombinant (GN57A and AN57G) haplotypes on the promoter activity was further investigated using a gene reporter strategy. As the AN57A, GN57A and AN57G haplotypes were obtained by mutagenesis of the GN57G haplotype, the gene expression variation can directly be associated to the two targeted SNPs. Chicken hepatoma cells (LMH) were transfected with a luciferase reporter construction containing a −734 to +97 fragment of the chicken BCMO1 promoter, corresponding to a unique sequence except for the two candidate SNPs. The AN57A construction was associated with a 3.7 fold higher luciferase activity than the GN57G construction , the identification of the underlying genes and mutations is still exceptional BCMO1 is the gene underlying the chicken meat color QTL on GGA11, through a cis eQTL controlling its expression. Two fully linked SNPs in the BCMO1 promoter defined two haplotypes (AN57A and GN57G) with respectively high and low promoter activity as proven in vivo and in vitro. Genomatix was used to check if the mutations could alter a transcription factor binding site. If no results were obtained for the first mutation, the second mutation alters a Vitamin D receptor (VDR), a DR5 binding site detected only with the A allele. However, we clearly demonstrated that both mutations are needed to modify the gene expression. This could be due either to a transcription factor binding site undetected in the first mutation region or most likely to an interaction between the two mutations, one hypothesis being that the first mutation alters the genome 3D structure and affects the fixation of transcription factors in this region. These variations are likely to impact on the biological activity of the BCMO1 enzyme as they lead to respectively low or high carotenoid content in breast meat. Of the major food quality attributes, color is the first critical one since it is the main visual factor involved in the consumer's choice BCMO1 polymorphism mainly affected the yellow color of breast meat, by altering the content of the yellow pigments lutein and zeaxanthin. These two carotenoids, although not considered as substrates of the BCMO1 enzyme BCMO1, as already described for related xanthophylls (canthaxanthin and astaxanthin) in fish BCMO1 polymorphism on red color was less marked, likely because redness may be influenced by other mechanisms such as muscle blood content at death. This last parameter depends on several factors such as genotype While several hundreds QTL have been reported in livestock species including chicken  and hypercarotenemia and hypovitaminosis A BCMO1 knock-out in mice had no evident effects on growth but revealed, as expected, a dramatic decrease of vitamin A level in several tissues BCMO1−/− mice, whereas no changes in serum glucose level were noticed. In response to dietary oil supplementation (30%), BCMO1−/− mice became heavier. In our chicken model, in addition to be of lower weight, LG chickens carrying the “deficient” BCMO1 promoter gene are leaner and exhibit higher plasma glucose but normal free fatty acid levels as compared to HG chickens BCMO1 mutant chickens with a common genetic background will be needed to precise the specific effects of that gene and to know whether chicken and mice respond differently to variations in BCMO1 activity.Several mutations have been found in the coding region of BCMO2 gene  which encodes β-carotene 9′, 10′-monooxygenase. These mutations prevent expression of the gene in the skin but not in liver. While BCMO1 and BCMO2 have close functions (the first monooxygenase being responsible for the centric cleavage of the β-carotene and the second for its eccentric cleavage), they are located on different chromosomes . Our findings open the way to future research on the specific or combined role of the two genes on color variation in chicken and in other species.The color of chicken skin, easily visible at the level of the shank, is also dependent upon dietary carotenoid levels and carotenoid metabolism. Interestingly, a recent study Chickens were bred at INRA, UE1295 Pôle d'Expérimentation Avicole de Tours, F-37380 Nouzilly in accordance with European Union Guidelines for animal care and under authorization 37-123 delivered to E. Le Bihan-Duval by the French Ministry of Agriculture. Animal procedure was approved by Departmental Direction of Veterinary Services of Indre-et-Loire.major muscle using a Miniscan Spectrocolorimeter. Color was measured by the CIELAB system, where L* represents lightness, a* redness and b* yellowness. Higher L*, a* and b* values correspond to paler, redder and more yellow meat, respectively.The HG and LG chicken lines have been divergently selected for BW for more than 20 generations GGA11 was originally developed with three polymorphic microsatellite markers  GGA11 was performed by adding three additional markers . These markers were already available Genomic DNA was extracted from whole blood and QTL mapping on Prior to QTL detection, the data were corrected for sex and hatch effects as estimated by PEST software BCMO1 gene was first measured in the Pectoralis major muscle of six HG and LG individuals slaughtered at 1, 3, 5, 7, 9 and 11 weeks of age. Then to test the association between SNP mutations and BCMO1 expression, BCMO1 mRNA levels were measured on 373 F2 birds from the HG x LG intercross, including all 134 offspring of the F1 sire family used for eQTL detection and additional 239 birds issued from the other F1 sire families. Methods used for preparation of RNA samples and quantitative real-time RT-PCR assay were described earlier BCMO1 sequence (143 bp spanning exon 1 and 2) was amplified using 5′-GCCAAGCCATCAAACCAGTG-3′ and 5′-AACAAAGAAGAGCATCCAGAGCC-3′ as reverse and forward primers, respectively. The mRNA levels were estimated based on the cycle threshold (CT) deviation of an unknown sample versus a control cDNA (consisting of a pool of chicken muscle cDNA) according to the equation proposed by Pfaffl The expression of BCMO1 exons and the putative promoter region from the chicken genome assembly (http://genome.ucsc.edu/index.html) using Lightcycler Probe Design 2 software (Roche) (See 2 and 0.2 mM dNTP on a GeneAmp® PCR System 9700 thermocycler (Applied Biosystems). The first 5-min denaturation was followed by 38 cycles of: denaturation at 94°C for 30 sec, annealing for 30 sec and elongation at 72°C for 30 sec, with a final elongation of 10 min at 72°C. After Exo/SAP-IT  purification, PCR products were sequenced on both strands using the same primers and a Big Dye Terminator V3.1 kit (Applied Biosystems) on an ABI 3100 DNA Analyzer (Applied Biosystems). All new polymorphisms have been deposited in dbSNP (http://www.ncbi.nlm.nih.gov/projects/SNP/).PCR primers were designed to amplify the 11 che) See . PCR amp2 and 0.2 mM dNTP on a GeneAmp® PCR System 9700 thermocycler (Applied Biosystems). The first 5-min denaturation was followed by 45 cycles, each of denaturation at 95°C for 20 sec, annealing at 58°C for 20 sec and elongation at 72°C for 20 sec, with a final elongation for 10 min at 72°C. After addition of 0.4 µM of allele-specific probe and 1X LC Green (Idaho Technology) to 8 µL of PCR products, the samples were heated to 95°C for 10 min and then progressively cooled to 60°C by 5°C increments and then to 40°C by 10°C increments, 10 sec for each step during, with a ramp rate of 2.2°C/sec, on a LightCycler 480 (Roche). Then the mix was heated to 95°C (0.02°C/sec). The fluorescence data were subsequently analyzed by LightCycler 480 Gene scanning software. SNP2 analysis was performed similarly, except probe and LightCycler Green were added to the PCR reaction mix, and the amplification and HRM analyses were realized on the LightCycler 480: the first 10-min denaturation was followed by 50 cycles, each of denaturation at 95°C for 1 s, annealing at 58°C for 1 sec and elongation at 72°C for 10 sec; then the PCR products were heated to 95°C for 1 sec, and the dissociation curve was obtained by cooling to 40°C and heating to 95°C at a ramp rate of 0.02°C/sec.Candidate mutations were screened by high-resolution melting curve (HRM) analysis . Birds from the two genotypes were chosen within the same sire family and exhibited significant differences in BCMO1 expression  and yellow breast meat color . Carotenoid concentrations were determined in Pectoralis major muscle by using Ultra Performance Liquid Chromatography (UPLC) equipped with a 150×2.1 mm Acquity UPLC HSS T3, 1.8 µm column and a 2996 PDA detector  according to an initial procedure used for plasma by Chauveau-Duriot et al. Muscle carotenoid contents were compared between homozygous birds from the F2 population (N = 9 and 11 for ANmajor muscle by using a Miniscan spectrocolorimeter. It was measured in the CIELAB trichromatic system by Lightness (L*), redness (a*) and yellowness (b*). All the sires and dams were genotyped as described previously. In a second step, genotyping was performed on the offspring of the heterozygous sires (N = 470). BCMO1 gene expression was measured in a sub-population of 11 AN57A and 12 GN57G homozygous male birds chosen within one batch of hatching.Birds originated from a slow-growing commercial line selected by a breeding company since 1994. A large pedigree population was constituted with 868 male and female birds issued from 10 sires and 100 dams. Birds were reared in three successive batches under similar conditions of free-range chickens with access to outdoor area after 6 weeks of age. At 12 weeks of age, birds were slaughtered after a 7 hours feed withdrawal. As for the experimental population, color was measured on the upper ventral side of the P. BCMO1 promoter with the GN57G haplotype was amplified by PCR from bases –734 to + 97 relative to the transcription start site from exon 1, using the following primers: BCMOF: 5′-AGCCTGTGATTTCCTCTGC-3′ and BCMO1R: 5′-TCGCTCTCCTGTGTCCTCTA-3′. First, this fragment was subcloned into PCR3.1 plasmid  by TA cloning procedure. The promoter insert of PCR3.1 plasmid was then cloned into pGL2 basic plasmid , upstream of the luciferase reporter gene, to create pGL2-BCMO1-Luc plasmid. Site-directed mutagenesis were performed with the QuikChange II Site-Directed Mutagenesis Kit (Stratagene) using the following mutagenic primers (only forward primers are shown), ACCATACTTTCGCAGAGG-3′5′-AATCCCCCTTCTTCTTAATTATTCCT and AGGAGAATGTAGAATAGTGCC-3′5′-GTGGTGGAATCAGATCACACGT (the mutated bases are in bold) to create the AN57A, AN57G and GN57A haplotypes.Chicken 2. For transactivation assay, transient transfections of LMH cells were performed in triplicate in 6 well plates using the FuGENE lipofection protocol . Each well was transfected with 200 ng of pGL2-BCMO1-Luc reporter plasmid and 20 ng of pCMV-bgal reference plasmid containing a bacterial β-galactosidase gene. After 24 h following transfection, the cells were washed once with phosphate buffered saline, and incubated with fresh medium. After 48 h following transfection, the cells were lysed . Cell lysates were stored at -80°C before analyses. After centrifugation 5 min at 12000 g, supernatants (10 µl) were incubated 5 s in the presence of 40 µl of luciferase assay buffer  including luciferin (470 µM). Luciferase activity was determined using a luminometer . The β-galactosidase activity was measured by hydrolysation of Ortho Nitro Phenyl Galactopyranoside  and used to normalize the luciferase activity.The chicken hepatocellular carcinoma cell line (LMH) was obtained from ATCC (cat # CRL-2117). LMH cells were grown in Waymouth's medium  supplemented with 10% foetal calf serum , 100 IU/ml penicillin , and 100 mg/ml streptomycin . The human hepatocellular carcinoma cells (HuH-7) were provided by the unit 6061-INSERM-France. HuH-7 cells were grown in William's medium , 10% FCS, 1.6 ml BSA 30%, 500 nM Hydroxy-Cholesterol , 1 µg/mL Insuline . All cultures were incubated at 37°C in a humidified atmosphere containing 5% COFigure S1Polymorphisms within the BCMO1 promoter sequence (-817 to +41 bp). All the SNPs found in at least one HG x LG F1 sire are italicized (light red font), while the two linked candidate SNP are in red bold font and underlined . The ATG codon is shown as a shaded box.(0.33 MB TIF)Click here for additional data file.Figure S2Melting curves obtained for SNP2 (GTG/AGG). The homozygous AN57A are characterized by a fluorescence peak at 63°C (blue line), the homozygous GN57G by a fluorescence peak at 68°C (red line) and the heterozygous by two fluorescence peaks at 63°C and 68°C (green line).(0.32 MB TIF)Click here for additional data file.Table S1Primers and PCR conditions used to amplify the BCMO1 promoter region and 11 exons.(0.04 MB DOC)Click here for additional data file.Table S2Primers and probes used to perform HRM curve analyses.(0.03 MB DOC)Click here for additional data file.


The transcription readthrough phenotype was accompanied by a decrease in the density of RNAP II in the vicinity of the promoter region. With the exception of TFIIB and TFIIF, the recruitment of the general transcription factors onto the promoter, however, remained unaffected in the clp1 mutant. These results suggest that the CF1A complex affects the recruitment of RNAP II onto the promoter for reinitiation of transcription. Simultaneously, an increase in synthesis of promoter-initiated divergent antisense transcript was observed in the clp1 mutant, thereby implicating CF1A complex in providing directionality to the promoter-bound polymerase. Chromosome Conformation Capture (3C) analysis revealed a physical interaction of the promoter and terminator regions of a gene in the presence of a functional CF1A complex. Gene looping was completely abolished in the clp1 mutant. On the basis of these results, we propose that the CF1A-dependent recruitment of RNAP II onto the promoter for reinitiation and the regulation of directionality of promoter-associated transcription are accomplished through gene looping.The Cleavage Factor 1A (CF1A) complex, which is required for the termination of transcription in budding yeast, occupies the 3′ end of transcriptionally active genes. We recently demonstrated that CF1A subunits also crosslink to the 5′ end of genes during transcription. The presence of CF1A complex at the promoter suggested its possible involvement in the initiation/reinitiation of transcription. To check this possibility, we performed transcription run-on assay, RNAP II-density ChIP and strand-specific RT-PCR analysis in a mutant of CF1A subunit Clp1. As expected, RNAP II read through the termination signal in the temperature-sensitive mutant of  The termination of transcription requires two major multisubunit complexes in budding yeast. These termination complexes are localized at the 3′ end of genes. Recent studies have found the termination factors occupying the 5′ end of genes as well. In this study, we investigate the physiological role of a termination factor at the 5′ end of a gene. Our results show that the CF1 termination complex affects the recruitment of the transcription enzyme RNAP II onto the promoter for reinitiation of transcription. The complex also affects the directionality of transcription of the promoter-bound polymerase. We also found that the looped gene conformation was disrupted in the absence of a functional termination complex. The overall conclusion of these results is that the terminator-bound factors contact the 5′ end of genes due to gene looping, and affect both the recruitment of the polymerase at the promoter for reinitiation, and directionality of the promoter-initiated transcription. Thus, the role of termination factors is not restricted to the 3′ end of the gene, but they are also involved in promoter-associated transcription. The process of transcription can be divided into three principal steps; initiation, elongation and termination An increasing amount of biochemical, genetic and functional evidence suggest the existence of a network of complex interactions between initiation and termination factors. The general transcription factor TFIIB, for example, exhibits multiple genetic and physical interactions with the factors operating at the 3′ end of genes Like initiation factors, an array of termination factors also crosstalk with the 5′ end of genes. The foremost among them is Ssu72, which was discovered as a protein of unknown function that genetically interacts with TFIIB The presence of termination factors on the promoter region could influence the events taking place at the 5′ end of genes. One possible role of the termination factors at the 5′ end could be to regulate initiation or reinitiation of transcription. It was recently demonstrated that proper termination of transcription is required for efficient execution of the transcription cycle in mammalian cells clp1 mutant, these results strongly suggest a novel role for the CF1A complex in reinitiation of transcription. We further found a role for CF1A complex in the inhibition of promoter-initiated anti-sense transcription. Thus, CF1A complex may have an additional function in providing directionality to bivalent yeast promoters. The CF1A-dependent promoter-based events coincide with the gene assuming a looped conformation, thereby suggesting a possible role of gene looping in reinitiation of transcription in the sense direction.Here we demonstrate the role of CF1A complex in the promoter-associated transcription in budding yeast. In a mutant of Clp1 subunit of the CF1A complex, recruitment of the whole CF1A complex at the 3′ end of genes was compromised, leading to a termination defect. The termination defect coincided with a decrease in the recruitment of RNAP II on the promoter indicating a possible initiation defect. Since there was no significant decrease in the recruitment of the general transcription factors onto the 5′ end of a gene in the CF1A is a hexameric complex comprised of two subunits each of Rna14 and Rna15, and one subunit each of Pcf11 and Clp1 clp1-769-5INO1 and CHA1 in the mutant clp1 strain in cells grown at the permissive (25°C) and non-permissive (37°C) temperatures. We chose INO1 and CHA1 for our study because their regulation is relatively well understood and their transcriptional state can be regulated by simply changing the growth conditions. Furthermore, CHA1 is relatively isolated in the yeast genome and therefore is a good candidate to study upstream and downstream transcription by transcription run-on (TRO) assay. RT-PCR was carried out using primers A and B as shown in INO1 and CHA1 decreased by about 4–8 fold upon shifting the mutant cells to 37°C  analysis of cription . In the perature . No suchperature  or in thperature . Strand-INO1 and CHA1  CHA1 in wild type and clp1-769-5 mutant as described in CHA1 in the mutant strain at 37°C , NAH21 (Myc-tagged Rna14), NAH22 (Myc-tagged Pcf11) and NAH25 (Myc-tagged Rna15), which contained the Myc-tag at the carboxy-terminus of the indicated factor, were constructed by transforming the clp1-769-5 strain with the PCR product amplified from pFA6-13Myc-KanMX6. For TAP-tagging of the general transcription factors, first the temperature-sensitive clp1-769-5 strain was made −trp1 by replacing TRP1 with a KanMX cassette that was PCR amplified from pUG6. Next a TAP-tag was inserted at the carboxy-terminus of TFIIH subunit Ccl1 (NAH31), TFIIF subunit Tfg2 (NAH33) and TFIIE subunit Tfa2 (NAH32) by transforming the clp1-769-5-(trp1) strain with the TAP-cassette amplified from plasmid pBS1479.Yeast strains used in this study are listed in supplemental 600∼0.4. The dilution was done in the appropriate synthetic complete-drop out medium. Induction was done for 2 hrs at 25°C before shifting the cells to 37°C for another 2 hours for the deactivation step. Usually, this takes the cells to OD600 of about 0.7–0.8. At this stage, the cells are ready for processing for RT-PCR, 3C, ChIP, or TRO assays.Cultures were started by inoculating 5 ml of YP-dextrose medium with colonies from a freshly streaked plate, and grown at 25°C overnight with constant shaking. Next morning, overnight grown cultures were diluted  to an appropriate volume and grown to ODCHA1, WT and clp1-769-5 cells were grown in 100 ml of synthetic complete medium containing ammonium sulfate until A600 reached 0.4. Cells were centrifuged and resuspended in 100 ml of synthetic media containing serine and threonine (1 g/l each) and induced for 2 hours at 25°C. 50 ml of the cultures were centrifuged and resuspended in 50 ml of pre-warmed (37°C) serine and threonine containing medium and deactivation was done at 37°C for 120 minutes. The cell pellet obtained from 50 ml of liquid culture was washed with 10 ml cold TMN buffer  and resuspended in 940 µl of DEPC (Diethylpyrocarbonate)-treated cold water. To the cell suspension, 60 µl of 10% sarkosyl was added and incubation performed on ice for 25 min to permeabilize the cells. Permeabilized cells were recovered by a low-speed centrifugation  and directly used in the run on transcription assay. Elongation of transcripts initiated in vivo was resumed by resuspending cells in 120 µl of 2.5× reaction buffer , 45 µl of NTPs/RNase inhibitor mix , and 7 µl of [α-32P]-UTP . The reaction mix was incubated at 30°C for 2 minutes to allow transcript elongation. The reaction was stopped by adding 1 ml of cold TMN buffer and quickly spun at low speed. The recovered pellet was resuspended in 350 µl of Trizol. About 250 µl of acid-washed glass beads were added and the cells were lysed by vigorous shaking for 5 minutes on an agitator at room temperature. After lysis, tubes were spun for 5 minutes at 13800×g. To the recovered supernatant, 700 µl of Trizol and 200 µl of Chloroform were added and the samples were vigorously shaken on a vortexer, left on the bench for 5 minutes, and centrifuged at high speed for 10 minutes.Transcription run-on (TRO) assay was performed by the modification of protocols described in Birse et al., 1997 and Hirayoshi and Lis, 1999 To isolate RNA, the supernatant was extracted twice with phenol/chloroform (pH 4.2). Labeled RNA was precipitated by adding 0.1 volumes of 10 M LiCl, 0.1 volumes of yeast tRNA (80 mg/ml) and 2.5 volumes of 100% ethanol. The mix was incubated at −20°C for 20 minutes followed by centrifugation at maximum speed for 15 minutes. The RNA pellet was resuspended in 60 µl of DEPC-treated water and denatured by adding 5 µl of 2 M NaOH followed by incubation on ice for 5 minutes. The NaOH was then neutralized by adding 12 µl of sodium acetate/acetic acid mix  and boiling the contents for 5 minutes.CHA1 gene, including the upstream and downstream regions, were obtained by PCR amplification (See BIO-RAD), according to manufacturer's instructions. Adsorbed DNA was crosslinked to the membrane by baking at 80°C in a vacuum oven for 30 minutes. The membrane was then prehybridized with 10 ml of hybridization solution  at 55°C for at least 30 minutes. The denatured RNA in hybridization solution from the step described above was added to the prehybridized membrane. Labeled RNA was allowed to hybridize to the probe for 18–24 hours at 55°C in a rotator. After hybridization, the membrane was washed twice with 20 ml of a solution containing 0.1% SDS and 1XSSC for 7 minutes at 55°C, and twice with 20 ml of a solution containing 0.1% SDS and 0.1XSSC for 7 minutes at 55°C. After drying, the membrane was exposed to X-ray film overnight in an autoradiography cassette and the films were developed in a Kodak M35A X-OMAT system. All TRO signals were quantified using the GEL LOGIC 200 (KODAK) system and normalized with respect to the 18S control.In parallel, DNA probes of about 200–300 bp each in length, spanning the desired regions of the ChIP was performed as described in Crosslinking, cell lysis and isolation of chromatin was done as described in 2, 0.5% tergitol, 0.5% sodium deoxycholate and 1 mM EDTA) and TE buffer. All the washing steps were performed at room temperature. The beads were resuspended in 250 µl of ChIP elution buffer ; incubated at 65°C for 20 minutes; briefly spun; and the supernatant was collected and incubated with 10 µg of DNase-free RNase for 15 minutes at 37°C. 20 µg proteinase K and 2.5 µl 10% SDS were added and the crosslinks were reversed by overnight incubation at 65°C. Samples were extracted with phenol-chloroform at least two times followed by ethanol precipitation of DNA using glycogen as a carrier. The DNA pellet was resuspended in 50 µl TE and used as template for PCR. Chromatin immunoprecipitated DNA was PCR amplified (30 cycles) by appropriate primer pairs, and subjected to quantification and statistical analysis as described below. Each experiment was repeated with at least two independently grown cultures.The beads were washed successively with 1 ml each of FA-lysis buffer (two times), FA-lysis buffer containing 500 mM NaCl (two times), ChIP wash buffer . After restriction digestion, the reaction volume was diluted by 7.5 fold to minimize intermolecular ligation in the next step. Ligation reactions were performed at room temperature for 90 minutes. The crosslinks were reversed by incubating at 65°C overnight. DNA was extracted with phenol-chloroform followed by ethanol precipitation. 300 ng of DNA was used as template in the PCR using the P1-T1 divergent primer pair as indicated in 3C experiments were performed exactly as described previously Isolation of total RNA and transcription analysis was performed by RT-PCR using oligo-dT primer at the reverse transcription step as described previously . The RT-PCR primers are shown in supplemental Strand-specific RT-PCR was performed to distinguish between sense and anti-sense transcripts. Total RNA for this procedure was extracted using Trizol reagent. The cell pellet was resuspended in 500 µl of Trizol. Acid-washed glass beads (about 250 µl) were added to the cell suspension. Cells were lysed by vigorous shaking for 10 minutes on an agitator at 4°C. Whole cell lysate was recovered by puncturing the bottom of the tube with a 22-guage needle, placing it on the top of a 15 ml pre-chilled centrifuge tube and centrifuging at 300×g for 2 minutes. The filtrate was transferred into a chilled 1.5 ml microfuge tube and 500 µl more Trizol reagent was added. After adding 200 µl of chloroform, tubes were vigorously agitated and left on the bench for 5 minutes. The tubes were then centrifuged at high speed for 10 minutes. The supernatant was extracted two times with an equal volume of phenol/chloroform (pH 4.3), followed by an extraction with chloroform only. RNA was precipitated using 0.1 volumes 10 M LiCl and 3 volumes cold ethanol in the presence of glycogen as a carrier. The precipitated RNA was collected by centrifugation at 14220×g on a table-top centrifuge for 15 minutes. The air-dried RNA pellet was resuspended in 50 µl of DEPC-treated water and the concentration was estimated using a spectrophotometer.CHA1 as shown in s, Bs, Cs and Ds were used to reverse-transcribe sense mRNA, while Aas, Bas and Cas primers were used for reverse transcription of anti-sense transcripts. This was followed by PCR amplification of cDNA for regions W, X, Y and Z using primer pairs Aas-Bs, Aas-As, Bas-Cs and Cas-Ds respectively. A minus-RT control (without reverse transcriptase) was always performed to ensure that the strand-specific RT-PCR signal was not due to contaminating DNA in the RNA preparation. RT-PCR results were normalized with respect to the 18S rRNA control that is transcribed by RNAP I and requires a different set of transcription factors.Strand specific RT-PCR was now performed as described in The quantification was performed as described in Figure S1tsclp1 mutant at the non-permissive temperature. tsclp1 mutant cells were grown at 25°C and then shifted to 37°C for 2 hours. Following cell lysis, Myc-tagged TFIIB or CF1A subunits were immunoprecipitated using anti-Myc antibodies from the cells grown at 25°C and 37°C. Equal amounts of protein were used in the immunoprecipitation. Immunoprecipitated proteins were fractionated on SDS-polyacrylamide gels and Western blot analysis was performed. (A) Western blot analysis for the cells grown at 25°C. (B) Western blot analysis for the cells grown at 37°C. Clp1 could not be detected in the cell lysate following the temperature shift to 37°C, while only a marginal change in the amounts of TFIIB and other CF1A subunits was observed in the mutant cells.The amounts of the general transcription factor TFIIB and CF1A subunits Pcf11, Rna14, Rna15 are not altered in the (TIF)Click here for additional data file.Figure S2INO1 and CHA1 genes is adversely affected in the tsclp1 mutant at elevated temperature.  Schematic depictions of INO1 and CHA1 indicating the position of ChIP primer pairs.  ChIP analysis showing crosslinking of the CF1A subunits Rna14, Pcf11 and Rna15 to the 5′ and 3′ end of INO1 and CHA1 in the clp1 mutant at 25°C and 37°C.The recruitment of the CF1A subunits onto the (TIF)Click here for additional data file.Figure S3INO1 and CHA1 genes remains unaffected in the wild type cells at elevated temperature.  Schematic depictions of INO1 and CHA1 indicating the position of ChIP primer pairs.  ChIP analysis showing crosslinking of the CF1A subunits Rna14, Pcf11 and Rna15 to the 5′ and 3′ end of INO1 and CHA1 in the clp1 mutant at 25°C and 37°C.The recruitment of the CF1A subunits onto the (TIF)Click here for additional data file.Figure S4INO1 and CHA1. (A) and (D) Schematic depictions of INO1 and CHA1 showing the positions of ChIP primer pairs. (B) and (E) ChIP analysis showing cross-linking of Clp1 to different regions of INO1 and CHA1 following 120 minutes of induction. (C) and (F) Quantification of the data shown in B and E respectively. Error bars indicate one unit of standard deviation.Clp1 is recruited to the promoter and the terminator regions of transcriptionally active (TIF)Click here for additional data file.Figure S5INO1 and CHA1 showing the positions of ChIP primer pairs.  ChIP analysis showing polymerase density in different regions of INO1 and CHA1 in the wild type cells at the permissive  and non-permissive  temperatures. (C and F) Quantification of data shown in B and E respectively. The input signals represent DNA prior to immunoprecipitation. The results shown are an average of at least eight independent PCRs from four separate immunoprecipitations from two independently grown cultures. Error bars indicate one unit of standard deviation. IP = immunoprecipitate.RNAP II density in the promoter region remains unaffected in wild type cells at the elevated temperature.  Schematic depictions of (TIF)Click here for additional data file.Figure S6INO1 and CHA1 remains unaffected in the wild type cells at the elevated temperature.  Schematic depictions of INO1 and CHA1 indicating the position of ChIP primer pairs.  ChIP analysis showing crosslinking of the general transcription factors TFIID, TFIIB, TFIIF, TFIIE and TFIIH to different regions of INO1 and CHA1 in the wild type cells at 25°C and 37°C.The recruitment of the general transcription factors at the promoter of (TIF)Click here for additional data file.Table S1List of strains used in this study.(PDF)Click here for additional data file.Table S2List of all the PCR primers used in this study.(PDF)Click here for additional data file.


Polycomb Repressive Complex 2 (PRC2) is an essential regulator of gene expression that maintains genes in a repressed state by marking chromatin with trimethylated Histone H3 lysine 27 (H3K27me3). In Arabidopsis, loss of PRC2 function leads to pleiotropic effects on growth and development thought to be due to ectopic expression of seed and embryo-specific genes. While there is some understanding of the mechanisms by which specific genes are targeted by PRC2 in animal systems, it is still not clear how PRC2 is recruited to specific regions of plant genomes.We used ChIP-seq to determine the genome-wide distribution of hemagglutinin (HA)-tagged FERTLIZATION INDEPENDENT ENDOSPERM (FIE-HA), the Extra Sex Combs homolog protein present in all Arabidopsis PRC2 complexes. We found that the FIE-HA binding sites co-locate with a subset of the H3K27me3 sites in the genome and that the associated genes were more likely to be de-repressed in mutants of PRC2 components. The FIE-HA binding sites are enriched for three sequence motifs including a putative GAGA factor binding site that is also found in Drosophila Polycomb Response Elements (PREs).Our results suggest that PRC2 binding sites in plant genomes share some sequence features with Drosophila PREs. However, unlike Drosophila PREs which are located in promoters and devoid of H3K27me3, Arabidopsis FIE binding sites tend to be in gene coding regions and co-localize with H3K27me3. The Polycomb group (PcG) proteins are found across the higher eukaryotes and are essential for normal development. PcG proteins were first identified in Drosophila where they are required to maintain repression of homeotic genes  and haveclf swn double mutants and FIE RNAi plants leads to strong developmental defects, especially in organ identity [Plants have clear homologs of the four core protein components of PRC2, often with multiple genes encoding each component . In Arabidentity ,11. Wholidentity -17. The identity ,16 consiidentity . This inA major unanswered question in understanding Polycomb repression in plants is how specific loci are targeted by the Polycomb complexes. Polycomb recruitment has been best characterised in Drosophila where regions of H3K27me3 are associated with sequence elements termed Polycomb Response Elements (PREs) . DrosophHOXD cluster that confer PcG-dependent repression in reporter gene systems [cis, such as the Xist and Kcnq1ot1 lncRNAs that are involved in PcG recruitment in X chromosome inactivation and imprinting respectively [trans, such as the HOTAIR lncRNA which is produced from the HOXC cluster and acts as a scaffold to recruit PRC2 to the unlinked HOXD locus [In mammalian systems, PREs are less well characterised with the best examples being a 3 kb region from the mouse MafB gene and a 1.8 kb region from the human  systems ,20. Bothectively ,22, or iXD locus ,24.LEAFY COTYLEDON 2 (LEC2) gene which is required for PcG repression and confers repression and H3K27me3 deposition on a transgene [LEC2 promoter also contains a GAGA element that is bound by Arabidopsis GAGA factors in vitro. Mutation studies suggest that this GAGA element has an activator or enhancer function and is not required for H3K27me3 deposition [BREVIPEDICELLUS (BP) gene. The ASYMMETRIC LEAVES 1 (AS1)–AS2 complex binds to defined sequences in the BP promoter to silence its expression [BP locus is marked by H3K27me3 which requires the AS1-AS2 complex. The AS1-AS2 complex interacts with PRC2 components and the AS1-AS2 binding site from the BP promoter is sufficient to confer Polycomb repression on a GUS transgene. These properties are consistent with the AS1-AS2 binding site in BP functioning as a PRE at which AS1-AS2 recruits PRC2 [At present less is known of the mechanisms by which genes are targeted by the PcG system in plants. There is some evidence for the presence of PRE-like sequences in plants. A 50 bp element (RLE) has been identified from the promoter of the Arabidopsis ransgene . The LECposition . A seconpression . The BP FLC gene which encodes a MADS box repressor of flowering [FLC expression is repressed by vernalisation (extended cold) and this repression is maintained in a PRC2-dependent manner following return to warm growing conditions [FLC which are bound by the PRC component CLF, are required to maintain FLC repression in the cold [FLC repression.Some evidence for lncRNAs being involved in Polycomb recruitment in plants comes from the lowering ,29. FLC nditions ,30. Non-the cold , suggestTo further explore the mechanisms of PcG recruitment in plants we carried out a ChIP-seq experiment to determine the genome-wide distribution of FIE, the single ESC homolog in Arabidopsis which should therefore be present in all PRC2 complexes. By comparing the FIE binding sites with genome-wide H3K27me3 distribution we found over seven hundred high confidence FIE binding sites. The FIE binding sites were predominantly within gene bodies and were enriched for three sequence motifs including putative GAGA factor binding sites.fie-11 mutant in the C24 ecotype [LEC2 and BP genes. This identified 1298 peaks in the FIE-HA data and 5148 peaks in the H3K27me3 data using a q score of 10-10. This q score was selected from a range that was tested on the basis that it identified the largest number of peaks from the ChIP samples with minimal false positive peaks from the input datasets  analysis on the two datasets Figure , to deteclf-7 swn-28 double mutant [FIE[clf-7 swn-28 and siFIE compared to wildtype  on the basis that the known interaction sites of PRE-binding proteins in Drosophila are of approximately this length. This identified four motifs in the FIE-HA+H3K27me3 peaks Figure a. We alsWe have carried out a ChIP-seq analysis to identify binding sites for the PRC2 component FIE across the Arabidopsis genome. In comparison to the numbers of H3K27me3 sites (5148) we identified fewer high confidence sites of FIE binding (723). As PRC2, and therefore FIE, is required to deposit and maintain H3K27me3, a similar numbers of peaks is expected in both experiments. The discrepancy could have some biological significance or be a technical artefact. A technical difference could be simply a consequence of the two ChIP experiments using different antibodies and targeting proteins that interact with chromatin in different ways. Histone H3 is an intrinsic part of the nucleosome structure while FIE is part of a protein complex that interacts with chromatin. Although the FIE-HA sample was cross-linked prior to immunoprecipitation, the indirect nature of the interaction between FIE and the DNA that is assayed by ChIP may make it harder to detect FIE binding regions compared to H3K27me3 regions.Drosophila[Biological explanations for the low number of FIE-HA peaks compared to H3K27me3 peaks could be that there are differences in the number of PRC2 binding sites, the strength of PRC2 binding or the amount of time that PRC2 is present at a given locus. There is support for this last possibility from FRAP (Fluorescence Recovery After Photobleaching) studies in rosophila which surosophila where H3A search for sequence motifs in the high confidence FIE binding sites identified four short conserved motifs. One of these was identified as being similar to the GAGA factor binding site which is a component of Drosophila PREs. The GAGA factor binds to many Drosophila PREs, but is also found in active promoters  and is sLEC2 promoter [BP promoter does not have any associated FIE-HA binding in our high-confidence dataset, although there is evidence of FIE-HA binding across the BP gene body . The swn-7 clf-28 mutant is sterile and was selected from the progeny of swn-7 clf-28/+ plants.All plants were grown on MS agar plates in a 16 h light: 8 h dark photoperiod under fluorescent lights at 22°C for 12 days. Whole seedlings were harvested for ChIP experiments or RNA extraction. T1 siFIE plants (in Col ecotype) were selected on plates supplemented with kanamycin (50 mgLNative chromatin immunoprecipitation (N-ChIP) was performed as described previously  with minMaterial for FIE-HA ChIP was cross-linked with formaldehyde and ChIP carried out as previously described ,43 on mohttp://biokanga.sourceforge.net/), allowing 2 mismatches at any position. Peaks were identified using the log2 ratio of signal density between two samples to determine enriched regions as candidates, followed by significance analysis on the read density from candidate peaks [x was the normalised number of the extended reads located within a 10 bp window along a chromosome for sample x; a log2 ratio was then calculated on the corresponding Sx as log2R = log2(Streatment/Scontrol). Adjacent windows that have a log2R above a threshold (the threshold was 3-fold enrichment when compared with input) were merged to form candidate peaks and peaks that have been separated less than 200 bp were further merged. Finally a significance test was performed using the PeakSeq algorithm [-10 was selected on the basis of maximizing the number of predicted peaks in the immunoprecipitated sample and minimizing the numbers of peaks identified in the control input DNA samples.The numbers of sequence reads obtained for each sample are detailed in Additional file te peaks . Brieflylgorithm  where a GO enrichment analysis was performed using the BINGO 2.44 plug-in  in CytosMEME software (version 4.9.0)  was applhttp://www.invitrogen.com/) and at least triplicate reactions were amplified using 7900HT Fast Real-Time PCR System  with SYBR green. The primers used are listed in Additional file RNA was extracted from approximately 100 mg of seedlings using the RNeasy Plant Mini Kit (Qiagen) according to the manufacturer’s instructions. For quantitative RT-PCR, DNase-treated RNA was reverse transcribed using an oligo dT primer and Superscript III reverse transcriptase  representing 30,361 genes, each with 2 target probes as annotated by TAIR version 6. DNAstar software was used for analysis; gene lists with higher than 2 fold de-regulation at 95% confidence compared to wild type were exported to Excel files for comparison.http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48857). The raw sequence data has been deposited into the NCBI Short Read Archive, accession number SRP027413.The Nimblegen array date in this publication have been deposited in NCBI’s Gene Expression Omnibus  and are qPCR: quantitative polymerase chain reaction.The authors declared that they have no competing interests.WD, DB, WP, ED and CH participated in the design of the study, WD, DB, MR and CH carried out experiments, WD, DB, HY, JT and CH analysed data, WD and CH drafted the manuscript. All authors have read and approved the final manuscript.Summarises the identification of peaks from the FIE-HA and H3K27me3 datasets.Click here for fileLists all H3K27me3 ChIP-seq peaks. Click here for fileLists all FIE-HA ChIP-seq peaks.Click here for fileLists FIE-HA peaks coincident with H3K27me3 peaks.Click here for fileShows phenotypes of weak, intermediate and strong T1 siFIE plants in C24.Click here for fileclf-7 swn-28 plants.Lists of up- and down-regulated genes from microarray analysis of siFIE and Click here for fileShows RT-qPCR verification of microarray data.Click here for fileclf swn and siFIE.Shows GO analysis of genes up-regulated in siFIE or Click here for fileShows GO analysis of genes up-regulated in siFIE or clf swn and siFIE that have FIE + H3K27me3 ChIP-seq peaks.Click here for fileShows GO analysis of genes up-regulated in siFIE, clf swn or both that have H3K27me3 only ChIP-seq peaks.Click here for fileShows additional MEME analyses to those shown in Figure Click here for fileShows TOMTOM analyses of motifs 2 to 4.Click here for fileLists oligonucleotide sequences used in this study.Click here for file


The liver X receptors (LXRs) are oxysterol sensing nuclear receptors with multiple effects on metabolism and immune cells. However, the complete genome-wide cistrome of LXR in cells of human origin has not yet been provided.De novo analysis of LXR binding sequences identified a DR4-type element as the major motif. On mRNA level T09 up-regulated 1258 genes and repressed 455 genes. Our results show that LXR actions are focused on 112 genomic regions that contain up to 11 T09 target genes per region under the control of highly stringent LXR binding sites with individual constellations for each region. We could confirm that LXR controls lipid metabolism and transport and observed a strong association with apoptosis-related functions.We performed ChIP-seq in phorbol myristate acetate-differentiated THP-1 cells (macrophage-type) after stimulation with the potent synthetic LXR ligand T0901317 (T09). Microarray gene expression analysis was performed in the same cellular model. We identified 1357 genome-wide LXR locations (FDR < 1%), of which 526 were observed after T09 treatment. This first report on genome-wide binding of LXR in a human cell line provides new insights into the transcriptional network of LXR and its target genes with their link to physiological processes, such as apoptosis.http://www.ncbi.nlm.nih.gov/geo under accession number GSE28319.The gene expression microarray and sequence data have been submitted collectively to the NCBI Gene Expression Omnibus  NR1H3 and NR1H2) are transcription factors that act as sensors for oxidized cholesterol (oxysterols) [ABCA1) and ABCG1, while in parallel the receptor transrepresses inflammatory genes, such as inducible nitric oxide synthase, interleukin 1β and monocyte chemotactic protein-1 [The nuclear receptors liver X receptor (LXR) α and β (encoded by the genes sterols) . Interessterols) -7. In marotein-1 -11.50 of about 50 nM [De novo motif analysis identified DR4-type REs as the most highly enriched binding sequence, but only 6.3% of the LXR peaks contained such a DR4-type RE. Also motifs for the transcription factors PU.1 and AP-1 were co-enriched [Oxysterols and intermediates of the biosynthetic cholesterol pathway have been identified as the natural ligands for LXR, while T0901317 (T09) is a potent synthetic LXR agonist with an ECut 50 nM ,13. LXRsut 50 nM . These Dut 50 nM -17. Receut 50 nM  and in mut 50 nM . In the enriched .The ability of LXRs to integrate lipid metabolism and immune functions places them in an ideal position to tailor macrophage responses. Therefore, we performed a genome-wide analysis of T09-induced LXR binding in macrophage-type phorbol myristate acetate (PMA)-differentiated THP-1 human monocytic leukemia cells by ChIP-Seq using a highly specific anti-LXR antibody. In total we identified 1357 chromosomal LXR binding locations, of which 526 were observed after the T09 treatment. At the mRNA level the ligand induced 1258 genes and repressed 455 genes. We studied the LXR cistrome and identified LXR-enriched genomic regions as well as individual LXR target genes. Binding of LXR is focused on 112 genomic regions with individual constellations of binding sites and target genes. We could confirm that LXR controls functions related to lipid metabolism and observed a strong link to apoptosis. Therefore, this first report on genome-wide binding of LXR in a human cell line provides new insights into LXR target genes and their link to physiological processes, such as apoptosis.Figure S1), where the antibody recognizes both LXRα and LXRβ protein in liver from wild type mice. LXRα is not recognized in LXRα-/- mice, LXRβ is not recognized in LXRβ-/- mice and both LXR bands disappear in the LXRαβ-/- mice. Furthermore, the antibody recognizes both human LXRα and LXRβ when they are overexpressed in HeLa cells. This indicates that the antibody is specific to both mouse and human LXRα and LXRβ.THP-1 human monocytic leukemia cells were treated for 3 days with PMA to induce a human macrophage-type model and subsequently treated for 60 min with the potent synthetic LXR agonist T09 or vehicle DMSO. ChIP assays were performed using an antibody specific for LXRα and β (and non-specific IgG as negative control). The LXR antibody was successfully used in regular ChIP assays ,21 and aTable S1 for all binding locations). Since the use of a single criterion for the selection of a representative peak set could be restrictive for the further analysis, we considered three criteria, each with different stringency.Purified chromatin samples were sequenced using a Solexa GAII platform. In order to detect genomic LXR binding locations, we used Bowtie software  for the -10 showed a higher number of peaks in the ligand-treated sample (151 peaks) than in the vehicle-treated sample (137 peaks), suggesting that the ligand slightly induces LXR binding among the high confidence binding locations. Interestingly, the peaks of both T09- and vehicle-treated samples were enriched to exon and intron regions, but ligand treatment clearly increased the density of LXR binding close to the transcription start site (TSS) . Due to these very stringent criteria the total number of peaks is not very high (202 peak locations), but they have proportionally higher overlap between T09- and vehicle-treated samples (42.6%) than the two following criteria showing overlaps of only 28.1% and 19.4%.The first high stringency criterion with false discovery rate (FDR) < 1%, fold enrichment (FE) > 4 and raw P-value < 10 sample 17 peaks, The second stringency level using a single criterion of a FDR < 1% increased the number of LXR binding sites in the T09-treated sample to 526 peaks and even more (1212 peaks) in the vehicle-treated sample. In total, this represents 1357 LXR binding locations. Loosening the stringency to FDR < 5% further increases the total number of LXR binding locations in the vehicle-treated sample (6903 peaks) compared to the ligand treatment (2817 peaks). In general, ligand treatment seems to increase the number of high confidence peaks and to decrease the number of lower confidence peaks suggesting that liganded LXR is focusing on a fewer number of genomic binding sites of possibly increased importance.de novo motif detection tool MEME [5. This motif has a MEME score of E = 1.4 × 10-12 and the TOMTOM tool indicated its high similarity to two DR4-type LXR consensus matrices reported in the Transfac database (M00766 with E = 4.95 × 10-10 and M00647 with E = 1.60 × 10-8)  Figure . As a made novo derived DR4-type RE or its version with spacer positions 7 and 8 set equal to any nucleotide (see Methods for details) can be found in 7.4% (39 of 526 peaks) of the T09-treated peak set and in 7.2% (87 of 1212) of the vehicle-treated peak set with similarity P < 10-4. When the similarity threshold was reduced to P < 10-3 the number of DR4-type REs could be increased to 42.6% and 41.3% in T09- and vehicle-treated samples, respectively (data not shown). Due to relatively low percentage of DR4-type REs, we screened the high stringency LXR peak sequences for the nuclear receptor half-site motif RGKTCA in a DR 0-6, everted repeat (ER) 0-12 and inverted repeat (IR) 0-6 arrangement. This resulted in enrichment for DR1-, DR4- and IR1-type REs in the T09-treated sample and DR4- and ER9-type REs in the vehicle-treated sample . Direct LXR-RXR heterodimer binding to DR1- and ER9-type REs has not yet been found, but it had been reported on an IR1-type RE [Further analysis of all 1357 peak sequences with FDR < 1% using the matrix screening function of the regulatory sequence analysis tools (RSAT) web server  showed t-type RE .-4): EWSR1-FLI1 (15.4%), KLF4 (13.7%), RREB1 (13.7%), SP1 (13.1%) and the DR1-type RE PPARG:RXR (12.0%). In the vehicle-treated sample these were EWSR1-FLI1 (17.6%), MYF (11.8%), SP1 (11.8%), RREB1 (11.7%) and SPIB (10.9%). Among the top motifs SPIB represents a purine-rich ETS-type motif, which is also recognized by the transcription factor PU.1, previously found in the LXR ChIP-Seq analysis from the murine macrophage cell line RAW264.7 [PPARG gene was also detected as up-regulated with a FC = 1.4 in our microarray at 4 h, we decided to search peaks with FDR < 1% for motifs PPARG::RXRA (DR1-type PPRE based on ChIP-Seq performed in mouse with identifier MA0065.2) and PPARG , available in JASPAR. These covered together 16.5% (87 of 526) of the T09-treated and 14.3% (173 of 1212) of the vehicle-treated peak set with a similarity P < 10-4. Interestingly, most of the peaks containing a PPARγ binding motif did not contain any DR4-type RE motif (79 of 87 peaks (90.8%) in the T09-treated and 162 of 173 peaks (93.6%) in the vehicle-treated peak set). These results indicate that some of the LXR peaks observed in ChIP-Seq data could be explained by an indirect DNA binding of LXR via other transcription factors, such as PPARγ, or by cooperative direct DNA binding of LXR together with some of the mentioned transcription factors.Screening of the LXR peak sequences with all 459 non-redundant JASPAR database matrices , without DR4-type LXR RE among them, resulted in the following five most frequent motifs in the T09-treated sample  of the LXR binding locations in the high stringency set Figure  represenABCA1  showing P assays . Moreoveeq study . All fiv T cells ) that arde novo motif in the peak areas was a DR4-type RE, but matrix screening also identified binding sites for other transcription factors, such as PPARγ. The example of the ABCA1 locus indicates that our ChIP-Seq data can fully explain the LXR regulation of a T09 target gene.In summary, depending on chosen stringency criteria we detected in a human macrophage-type cell line between 202 and 8139 genomic LXR binding sites. The only identified Table S2). The response already after 4 h suggests that these genes are primary LXR target genes.Next we studied the genome-wide clustering of LXR binding sites and the location of target genes within the clustered chromosomal regions with enrichment of binding locations. We stimulated macrophage-type PMA-treated THP-1 cells for 4 h with T09 or vehicle (DMSO), extracted total RNA and analyzed it on Illumina Human HT-12 v3 Expression BeadChip gene expression microarrays. Statistical analysis detected 1713 regulated genes (P < 0.01), out of which 1258 were up and 455 down-regulated  of the differentially expressed (DE) genes, which emphasizes high peaks or extremely differentially expressed genes. Subsequent analysis of the window density data using segmentation  to detect the exact borders of the peak-enriched regions resulted in the indicated 112 distinct genomic areas. Regions with ≥ 2 peaks and ≥ 3 T09-regulated genes are highlighted in red and listed in Table Table S3).The genome-wide organization of the high stringency set of 202 LXR binding locations Figure  and of tr = 0.55) and slightly with the density of differentially expressed genes (r = 0.32), but the number of LXR peaks in the 112 hotspots does not correlate with the proportion of DE genes in these regions nor with the density of DE genes in these regions . In a more detailed view, we correlated each of the 112 hotspot regions with the number of measured up-regulated  and ETF1 (eukaryotic translation termination factor 1) is shown in higher resolution , TRMT112 (tRNA methyltransferase 11-2 homolog) and PRDX5 (peroxiredoxin 5) is shown in higher resolution  and distal (± 0.1 to ± 1 Mb) regions of peak summits Figure . For theTable S2) and those that show an adjusted P <0.001 for differential expression and a proximal T09-induced LXR binding site are summarized in Table NACA , flanked by the PTGES3 (prostaglandin E synthase 3) and PRIM1 , which together form the core of region R61 , located in region R55  and the down-regulated (SLC3A2) genes appear to follow the same mechanism of a T09-induced LXR binding. In addition, we made a comparison with the LXR locations found previously in mouse macrophages [Table S2). Among all 1713 differentially expressed human genes only 7.9% (136 of 1713) showed LXR binding in the corresponding mouse region. Furthermore, among the 1063 selected target genes only 9.9% (105 of 1063) contained an LXR peak in the corresponding genomic region in mouse macrophages. Finally, from the human genes with proximal LXR peaks , NR1H3, SCD (stearoyl-CoA desaturase) and TATDN2 (TatD DNase domain containing 2) and the three down-regulated genes CNNM4 (cyclin M4), HARS (histidyl-tRNA synthetase) and PUF60 (poly-U binding splicing factor 60 KDa) have LXR binding location with a motif highly similar (P < 10-6) to a DR4-type RE. The ABCA1 gene is one of the best-known LXR target genes and contains even three DR4-type REs within its regulatory region , NR1H3 and SCD and the novel targets PPARG, SMPDL3A, ADM (adrenomedullin) and ACSL3 (acyl-CoA synthetase long-chain family member 3) . After 4 h of ligand treatment all nine genes were significantly up-regulated by both LXR ligands.Next we compared altered expression of LXR target genes to the occurrence of DR4-type REs within the proximal LXR peaks Figure . Althougn Figure . AnotherS Figure . Using qIn summary, 1063 of the 1713 T09 responding genes are probable direct targets of LXR, since 77% of them have at least one LXR binding site within 100 kb of their TSS and the further 23% show at least one LXR peak within 1 Mb distance. Interestingly, highly regulated LXR target genes have a higher probability to contain a DR4-type REs within the LXR peak associated with these genes.Table S4). Among these, 71 genes are related to regulation of programmed cell death (rank 42) and 73 genes to regulation of apoptosis (rank 53). Interestingly, the immune-related terms are not enriched significantly, as the best ranking immune-related term "somatic diversification of immune receptors via germline recombination" is only related to five LXR target genes with FDR = 57.3%. We also analyzed separately a more specific gene list, a subset of 1063 genes, with P < 0.001 for differential expression , Reactome and CGAP tissue EST expression for the 1063 true LXR target genes. In order to ease the later inspection of results, we limited the number of genes used in the clustering analysis to the 150 most up-regulated and the 76 most down-regulated, preserving the same ratio as between all 706 and 357 up- and down-regulated LXR target genes. For the annotations, we used all that were enriched with FDR < 50%, corresponding to the raw P ≤ 0.036 in the GO enrichment analysis. We were able to use this loose criterion and obtain adequate data, because the clustering is robust to false positive annotations. The genes and associated annotations were clustered and visualized in parallel using the heatmap.2 function available in the R-package gplots . AgglomeTaken together, functional annotation analysis of the 1063 true LXR target genes using GO, KEGG, Reactome and CGAP tissue EST expression databases resulted in eight clusters, in which the functions apoptosis and lipid transport are found, but no link to immune functions were observed.This study provides the first genome-wide view of LXR binding patterns in a human cell line using ChIP-Seq assays. We performed this study in PMA-differentiated THP-1 cells, a macrophage-type cellular system, which increases our understanding not only of the well-known role of LXR in lipid metabolism and transport, but also the receptor's assumed role in innate immunity and other physiological processes.ABCA1.The highly stringent analysis of the ChIP-Seq peaks obtained from PMA-treated THP-1 cells after a 60 min stimulation with the synthetic LXR ligand T09 or its vehicle DMSO yielded a surprisingly low number of 202 genome-wide binding locations of the receptor. However, from the 151 LXR sites observed in the presence of T09, 57% (86) are also bound in the absence of ligand. This supports the canonical model for nuclear receptor binding being valid for most members of the superfamily . AccordiA lower stringency in the detection of LXR ChIP-Seq peaks increased the number of sites substantially, to a total of 1357 (FDR < 1%) or even 8139 (FDR < 5%). However, with this increase of putative LXR binding sites the percentage of overlapping sites reduced to 28.1 and 19.4%, respectively, while the percentage of apparent binding sites in the absence of ligand increased to 61.2 and 65.4%, respectively. We assume that most of the latter sites are not genomic locations from which LXR initiates gene activation, but rather unspecific contact points of the genome with no functional impact. However, the tendency that ligand stimulation reduces the number of sites to less than half (from 1212 to 526 and from 6903 to 2817) suggests that in its ligand-activated state LXR makes a more focused selection of genomic targets.in vitro studies, is the only high affinity DNA binding site for LXR-RXR heterodimers. This fits with the observations of the two presently published mouse LXR ChIP-Seq studies, where only 6.3% [in vitro assays  or LXR is not directly contacting DNA, but sits "piggyback" on another DNA-binding transcription factor. Interestingly, in our T09 microarray the PPARG gene is 1.4-fold up-regulated, a value that was also confirmed by qPCR with two different LXR ligands. In parallel, we found for 16.5% of all LXR peaks in the T09-treated sample a PPARγ binding site. This suggests that PPARγ may be involved in the regulation of a subset of the LXR target genes. Boergesen et al. reported very recently that in mouse liver many genomic binding sites of LXR are also bound by PPARα, which is the predominant PPAR subtype in liver [et al. also found a higher percentage of DR1-type REs below their LXR ChIP-Seq peaks than DR4-type REs, but in sum this can explain only less than 25% of all LXR locations. Therefore, they assume that both LXR and PPAR are far more promiscuous in the recognition of their binding sites as suggested by in vitro studies.Surprisingly, only 7.3% of the LXR peak summit sequences contain a DR4-type RE, which, based on nly 6.3%  or up tonly 6.3%  of the Lnly 6.3% . Althougnly 6.3% , we founnly 6.3% ,43. Thesin liver . They suABCA1, ABCG1, NR1H3 and SCD. Moreover, in a reasonable number of gene regulatory scenarios two or more genomic LXR binding sites seem to work together in the regulation of a gene cluster  or individual genes . These multiple RE arrangements confirm observations from single gene analyses with other nuclear receptors, such as the VDR [Nevertheless, we found DR4-type REs as functional LXR binding sites in a number of prominent and highly ligand-responsive LXR target genes, such as  the VDR -46.More important than the actual number of individual LXR binding sites may be their spatial clustering along the genome. We identified 112 genomic regions of an average size of 1.7 Mb that contain clusters of highly stringent LXR binding sites and up to 11 T09 target genes. In total we identified 432 T09 target genes within these genomic LXR hotspots. Although each of these regions displays a rather individual arrangement of LXR binding sites in relation to up- and down-regulated genes, they seem to represent the core of the genome-wide activities of LXR. However, 13 of the 112 regions do not have any T09 target gene, suggesting that these stringent LXR locations may have effects on more distant target genes.In total our microarray analysis of the 4 h T09-stimulated human macrophage-type cells lists 1713 genes, 73% of which are up-regulated, i.e. more than double as many genes are up-regulated than down-regulated. Out of these T09 target genes, 432 (25%) are found within the 112 genomic LXR hotspots, 814 genes (48%) have an LXR binding site within 100 kb distance from the respective gene's TSS and for a further 249 genes (15%) an LXR location within 1 Mb of the TSS could be identified. This rate is similar to other reports comparing ChIP-Seq and microarray results . NeverthABCA1, ABCG1, MYLIP, NR1H3 and SCD, but we identified also a number of previously unknown, novel LXR targets. The most up-regulated LXR target gene, NACA, encodes for the nascent polypeptide associated complex alpha protein, which is associated to translation and protein folding related processes and when depleted is responsible of triggering endoplasmic reticulum stress-driven apoptosis in hypoxic cells [PTGES3 gene, which is co-located with the NACA gene, encodes for the co-chaperone protein prostaglandin E synthase 3 and is required together with the primary chaperone proteins for proper folding and functioning of the glucocorticoid receptor and other steroid receptors [SLC3A2, is related to various processes, for instance in the migration of leukocytes from blood to the central nervous system [SMPDL3A gene is an interesting new LXR target, but it has not yet been well characterized as there is only one report linking SMPDL3A to bladder tumorigenesis [Our study confirmed a number of known primary LXR target genes, such as ic cells . The PTGeceptors . The moss system , but alss system . Also thigenesis .LXR actions have been related to a number of autoimmune diseases, such as multiple sclerosis ,53, rheuWe present here the first genome-wide view on LXR locations in a human macrophage-type cellular system. The core action of LXR is focused on 112 genomic hotspots that contain 432 target genes. In total 1063 of the 1713 LXR target genes can be explained by a direct action of LXR, many of which have not been reported before. These genes are related to lipid metabolism and transport and to apoptosis, but not directly to immune functions.2 incubator. For differentiation into macrophage-type cells the THP-1 cells were incubated for 3 days with 20 nM PMA. Prior to stimulation with 1 μM of the synthetic LXR ligands T09 or GW (both from Sigma-Aldrich) or vehicle (dimethyl sulfoxide (DMSO), final concentration 0.1%) the medium was replaced by RPMI 1640 supplemented with 5% lipid-depleted fetal calf serum, 2 mM L-glutamine, 0.1 mg/ml streptomycin and 100 U/ml penicillin and 20 nM PMA.THP-1 human monocytic leukemia cells were grown in RPMI 1640 supplemented with 10% fetal calf serum, 2 mM L-glutamine, 0.1 mg/ml streptomycin and 100 U/ml penicillin and the cells were kept at 37°C in a humidified 95% air/5% CO3, 0.5 M NaCl, pH 8.3 buffer were coupled on a N-hydroxysuccinimide activated matrix column and the immunized rabbit serum was added to the column, which was washed according to standard procedure. Elution of anti-LXR antibody was performed in 10 cycles and all fractions were pooled.Rat LXRα and LXRβ proteins were purified as previously described . Rabbits2 flasks, each 2 × 107 cells, density of 1 × 106 cells/ml) were treated for 60 min with 1 μM T09 or vehicle (DMSO). Then nuclear proteins were cross-linked to DNA by adding formaldehyde directly to the medium to a final concentration of 1% following incubation for 10 min at room temperature on a rocking platform. Cross-linking was stopped by adding glycine to a final concentration of 0.15 M and incubating at room temperature for 10 min on a rocking platform. The cells were collected by centrifugation and washed twice with ice cold PBS . Nuclear extraction was performed by adding 500 μl PIPES buffer , incubating for 10 min on ice and removing cytoplasmic components by centrifugation. Nuclear pellets were dissolved in 500 μl SDS lysis buffer  and incubated 10 min on ice. Lysates were sonicated at high power with 22 × 30 s pulses in a Bioruptor  to result in DNA fragments of 100 to 600 bp. Cellular debris were removed by centrifugation. Aliquots of 100 μl of the lysate were diluted 1:10 in ChIP dilution buffer  and 2 μg of anti-LXR antibody [3) for 15 min at room temperature with rotation. The supernatants were combined and the immune complexes were reverse cross-linked overnight at 65°C in the presence of proteinase K (Fermentas) in a final concentration of 0.1 mg/ml. DNA was extracted with the ChIP DNA Clean & Concentrator Kit  according to manufacturer's instructions and eluted in 40 μl nuclease-free H2O. The ChIP templates were sequenced using a Solexa Gene Analyzer II platform (Illumina) at 36 bp read length using standard manufacturer protocols at the Genomics Core Facility in Heidelberg, Germany.PMA-differentiated THP-1 cells  within their parental MACS peak.Some of our following in-house bioinformatics tools were already described recently ,63. Alig 1.3.7.1  was used program  with arg-3 reported by the MACS program) in one sample can have FDR < 5%, FDR < 1% or high stringency peak sets, when the overlapping peak in the other sample fulfills the criterion. Since many genomic positions cannot be uniquely assigned to the selected 10 types of genomic elements used in the analysis of peak distributions therein, in the genomic element analysis a prioritization scheme was employed, where the peaks were uniquely overlapped to the elements in a step-wise exclusive scheme, starting from coding elements (UTRs and coding exons), and then moving to introns and outward from the gene.Further data analyses were conducted using an in-house R pipeline containing tools for identifying peaks overlapping in two samples, the analysis of genomic distribution of peaks and the integration of peak and gene expression datasets. In the analysis of overlapping peaks, we require that the narrower of the two overlapping peaks shares at least 30% overlap with the broader peak. Under these conditions also any weaker peak . The reactions were performed using 4 pmol of reverse and forward primers, 4 μl cDNA template and FastStart SYBR Green Master (Roche) in a total volume of 10 μl. In the PCR reaction the DNA templates were pre-denaturated at for 10 min at 95°C, followed by amplification steps cycles of 20 s denaturation at 95°C, 15 s annealing at primer specific temperatures , 15 s elongation at 72°C and a final elongation for 10 min at 72°C. PCR product quality was monitored using post-PCR melt curve analysis. Fold inductions were calculated using the formula 2-(ΔΔCt), where ΔΔCt is ΔCt(stimulus)-ΔCt(solvent), ΔCt is Ct(target gene)-Ct(contol gene) and the Ct is the cycle, at which the threshold is crossed. Relative expression levels of the target genes were normalized to the internal control gene RPLP0.Total RNA was extracted using High Pure RNA Isolation kit (Roche). cDNA synthesis was performed using Transcriptor First Strand cDNA Synthesis Kit (Roche), using 1 μg of total RNA as a template and 50 pmol oligo(dT)Total RNA was checked for RNA integrity using a Biorad Experion automated electrophoresis system . None of the RNA samples showed any sign of degradation. Triplicate samples were analyzed with HumanHT-12 v3 Expression BeadChips from Illumina  at the Finnish Microarray Centre . Raw data are available at GEO under accession GSE28319. Analyses of microarray data were performed using R statistical software version 2.11  with assK [K starting from 1 ending to the number of analyzed data points. The results were further used for the "segselect" function, which uses an adaptive model selection [K. A result optimal in terms of this model selection was chosen as representative for each chromosome. The resulting chromosomal regions were selected for containing at least one LXR binding location within the high stringency set of peaks resulting in 112 separate regions. The region borders were widened 100 kb upstream of the 5'-border and 100 kb downstream of the 3'-border of each region to cover putative target genes in these regions.For the analysis of spatial clusters of LXR binding locations we first performed a density analysis of genomic coordinates of LXR peak summit locations in T09- and vehicle-treated samples and the starting coordinates of up- and down-regulated genes. This was made using the standard R function "density" with a 1 Mb size for the sliding window with 0.5 Mb steps over each chromosome using the default Gaussian window kernel function. The density values resulting from each of these windows were weighted using FE values for LXR binding locations or logarithmic FCs between T09- and vehicle-treated samples for the locations of regulated genes. In order to detect the exact borders of the LXR hotspot regions, we performed a subsequent clustering of the density data representing the LXR binding locations by using methods developed originally for the analysis of array CGH data implemented in R package SegClust ,72. Firselection  between ABC: ATP-binding cassette transporter; ACLS3: acyl-CoA synthetase long-chain family member 3; ADM: adrenomedullin; ChIP: chromatin immunoprecipitation; CNNM4: cyclin M4; DE: differentially expressed; DMSO: dimethyl sulfoxide; DR4: direct repeat spaced by 4 nucleotides; EGR1: early growth response protein; ER: everted repeat; ETF1: eukaryotic translation termination factor 1; EWSR1: Ewing sarcoma breakpoint region 1; FDR: false discovery rate; FLI1: friend leukemia virus integration 1; FE: fold enrichment; GPR137: G protein-coupled receptor 137; GO: gene ontology; GW: GW3965; HARS: histidyl-tRNA synthetase; IgG: immunoglobulin gamma; IR: inverted repeat; KLF4: krüppel-like factor 4; LXR: liver X receptor; MYF: myogenic factor; MYLIP: myosin regulatory light chain interact; NACA: nascent polypeptide-associated complex alpha subunit; NR1H3: LXRα; PMA: phorbol myristate acetate; PPAR: peroxisome proliferator-activated receptor; PRDX5: peroxiredoxin 5, PRIM1, primase, DNA, polypeptide 1; PTGES3: prostaglandin E synthase 3; PUF60: poly-U binding splicing factor 60 KDa; PWM: position weight matrix; qPCR: quantitative real-time PCR; RE: response element; RPLP0: ribosomal protein large P0; RREB1: Ras-responsive element-binding protein 1; RSAT: regulatory sequence analysis tools; RXR: retinoid X receptor; SCD: stearoyl-CoA desaturase; SCL3A2: solute carrier family 3A2; SMPDL3A: sphingomyelin phosphodiesterase: acid-like 3A; SP1: Sp1 transcription factor; SPIB: Spi-B transcription factor; T09: T0901317; TATDN2: TatD DNase domain containing 2; TRMT112: tRNA methyltransferase 11-2 homolog; TSS: transcription start site; VDR: vitamin D receptor.PP, LW-S and CC designed the project, LW-S, JD and JR performed the experiments, PP, AW-B and SH analyzed the data, ET and KRS provided material and participated in the discussion and PP and CC wrote the manuscript. All authors read and approved the final manuscript.Figure S1. Validation of LXR antibody. Protein extracts from livers of WT, LXRα-/-, LXRβ-/- and LXRαβ-/- mice [A) or from HeLa cells, which were transfected with the empty pSG5 expression vector as control and pSG5 expressing human LXRα or LXRβ, respectively, using FuGENE 6 transfection reagent (Roche) (B), were separated on 8% sodium dodecyl sulfate (SDS) polyacrylamide gels. Western blotting using anti-LXR antibody was then performed using standard procedures.-/- mice  (A) or fClick here for fileTable S1. LXR binding locations in a human macrophage-type cell line. Columns indicate the chromosome, start and end locations of ChIP-Seq peaks, peak length and summit, P-values from Poisson distribution, FE in comparison to IgG, FDR value and information on which sample peak was detected (T09- or vehicle-treated). Information regarding to any peak present in both samples is presented in two separate rows.Click here for fileFigure S2. Distribution of genomic LXR binding sites to genomic elements. A Distribution of LXR binding locations from the high stringent set of peaks to different genomic elements. Unique peaks represent binding locations present only in one of the two samples , everted repeats (ERs) and inverted repeats (IRs). Search has been made with RSAT DNA-pattern tool [ern tool  using RGClick here for fileTable S2. Differentially expressed genes in a human macrophage-type cell line. Columns indicate the chromosome, start of the T09 target gene, log2 expression after T09- and vehicle-treatment, adjusted P-value for gene expression difference, gene name and FC. The detected LXR binding locations within proximal (± 100 kb) and distal (± 1 Mb) area from the respective gene TSS are displayed on the right side of the table.Click here for fileTable S3. Detailed information on all 112 LXR hotspots. Numbers of peaks and genes are indicated similarly as in Table Click here for fileFigure S4. Enrichment statistics of LXR binding locations. The number of LXR peaks in one of the 112 hotspot regions , the number of DE genes with adjusted P < 0.01 (B), the proportion of DE genes (C) and the density of DE genes (D).Click here for fileFigure S5. LXR target gene validation. PMA-differentiated THP-1 cells were treated for 4 h with vehicle (DMSO), 1 μM GW3965 (GW) or 1 μM T0901317 (T09), total RNA was extracted and qPCR was performed with primers specific for selected genes. The data were normalized to the expression of the housekeeping gene RPLP0 and fold inductions were calculated in reference to vehicle control. Columns indicate the means of four independent cell treatments and the bars represent standard deviations. Student's t-test was performed to determine the significance of the stimulation in reference to vehicle-treated control .Click here for fileTable S4. Enrichment analysis for all LXR target genes. The analysis was performed using the DAVID tool [VID tool  for all Click here for fileTable S5. qPCR primers used in the validation of gene expression microarray results of select genes.Click here for file