STS gene manifests with ichthyosis, but androgen synthesis and metabolism in STSD have not been studied in detail yet.Steroid sulfatase (STS) cleaves the sulfate moiety off steroid sulfates, including dehydroepiandrosterone (DHEA) sulfate (DHEAS), the inactive sulfate ester of the adrenal androgen precursor DHEA. Deficient DHEA sulfation, the opposite enzymatic reaction to that catalyzed by STS, results in androgen excess by increased conversion of DHEA to active androgens. STS deficiency (STSD) due to deletions or inactivating mutations in the X-linked STS gene by multiplex ligation-dependent probe amplification and Sanger sequencing.We carried out a cross-sectional study in 30 males with STSD  and 38 age-, sex-, and Tanner stage-matched healthy controls. Serum and 24-hour urine steroid metabolome analysis was performed by mass spectrometry and genetic analysis of the STS mutations in all patients, comprising 27 complete gene deletions, 1 intragenic deletion and 2 missense mutations. STSD patients had apparently normal pubertal development. Serum and 24-hour urinary DHEAS were increased in STSD, whereas serum DHEA and testosterone were decreased. However, total 24-hour urinary androgen excretion was similar to controls, with evidence of increased 5α-reductase activity in STSD. Prepubertal healthy controls showed a marked increase in the serum DHEA to DHEAS ratio that was absent in postpubertal controls and in STSD patients of any pubertal stage.Genetic analysis showed In STSD patients, an increased 5α-reductase activity appears to compensate for a reduced rate of androgen generation by enhancing peripheral androgen activation in affected patients. In healthy controls, we discovered a prepubertal surge in the serum DHEA to DHEAS ratio that was absent in STSD, indicative of physiologically up-regulated STS activity before puberty. This may represent a fine tuning mechanism for tissue-specific androgen activation preparing for the major changes in androgen production during puberty. “Steroid metabolome analysis reveals mild androgen deficiency and compensatorily increased 5alpha-reductase activity in steroid sulfatase (STS) deficiency and upregulation of STS activity in healthy boys before puberty.” Sulfation has been identified as a critical step in regulating the balance between conversion of the principal androgen precursor dehydroepiandrosterone (DHEA) to active androgens and its inactivation through sulfation to DHEA sulfate (DHEAS) . The latConsequently, it appears reasonable to assume that a defect in DHEA desulfation catalyzed by the enzyme steroid sulfatase (STS), may result in reduced sex steroid levels. STS also known as aryl sulfatase C, is a membrane-bound microsomal enzyme and member of a highly conserved family of aryl sulfatases. Members of that enzyme family catalyze the cleavage of the sulfate moiety from a variety of substrates, including conjugated steroids and other hormones, proteoglycans, posttranslationally modified proteins and aromatic compounds , which is part of the pseudoautosomal region escaping X-inactivation (STS gene cause STS deficiency (STSD) resulting in the skin condition X-linked ichthyosis (XLI), a common inborn error of metabolism with a reported prevalence of 1:1500 to 1:6000 males , steroid treatment during the preceding 12 months, including steroid inhalers, intake of other drugs known to alter steroid metabolism, and impairment of liver or kidney function due to concomitant disease or medication.The Warwickshire Research Ethics Committee provided approval of the study protocol. All participants provided written informed consent; in individuals under 18 years, additional assent from at least 1 parent was obtained. On the study day, participants arrived after an overnight fast at the clinical research facility. A clinical history was taken and participants underwent a physical examination, including a dermatological inspection and a detailed assessment of pubertal development including Tanner stages and testicular volume determined by referring to a Prader orchidometer. Anthropometric data  were recorded. Blood samples were obtained for measurement of serum steroid hormones and germline DNA extraction. All participants collected a 24-hour urine for evaluation of the steroid metabolome.STS gene deletions are the underlying abnormality in 90% of patients with XLI. Therefore, we used multiplex ligation-dependent probe amplification (MLPA) as the primary approach to genetic analysis. The MLPA assay was designed by MRC-Holland bv, comprising 11 probes specifically targeting the coding exons of the STS gene to identify partial or complete STS gene deletions. In addition, the assay also targets the coding exons of the neighboring KAL1 locus as well as the HDHD1 locus located centromeric and telomeric from STS, respectively. MLPA was performed using standard reaction conditions according to the manufacturer's protocol. In patients with no abnormalities on MLPA analysis, PCR amplification of the entire coding region of the STS gene (9 fragments), including intron/exon boundaries from genomic DNA, was performed . Direct sequencing was carried out using an ABI3730 sequencer (Applied Biosystems Inc), and sequencing analysis was carried out using the CLC Main Workbench software (CLC bio).Serum steroids were measured by liquid chromatography-tandem mass spectrometry (LC-MS/MS) employing a Waters Xevo mass spectrometer with Acquity uPLC system as described previously , 15. In DHEAS and cholesterol sulfate were extracted from serum in a method adapted form Chadwick et al . In brieSteroids were identified and quantified via comparison of retention time and 2 mass transitions (multiple reaction monitoring) to an authentic standard. Each steroid was quantified relative to a deuterated internal standard .Urinary steroid metabolite excretion analysis was carried out by quantitative gas chromatography-mass spectrometry (GC-MS) in selected-ion-monitoring analysis mode, as described previously . In brieP = .05 was assumed to be statistically significant. Data were expressed as median (±interquartile range [boxes] and ±10th–90th percentile [whiskers] ranges). The software GraphPad Prism was used for analysis.A nonparametric test (Mann-Whitney-Wilcoxon) was used to compare the 2 independent parameters from each cohort (control vs STSD). P = .42), height SDS , and BMI SDS .We recruited 30 patients with STSD and 38 healthy volunteers (controls). STSD patients and controls did not differ with regard to weight standard deviation score (SDS) . In 7 patients, an additional lymphocyte assay for STS activity had been performed, which had shown decreased activity. Only 3 of 30 patients had previously undergone genetic testing for confirmation of diagnosis.There was no history of consanguinity in the affected families. We recruited 4 pairs of siblings with STSD and 3 affected brothers from a single family.Eleven patients had additional conditions, mostly atopic disease such as mild asthma (n = 6), hay fever (n = 4), eczema (n = 1), or multiple allergies (n = 1); 1 patient had been diagnosed with attention deficit hyperactivity disorder.Thirteen STSD patients were clinically prepubertal with testicular volumes less than or equal to 4 mL and prepubertal Tanner stages. Five patients were peripubertal with testicular volumes between 4 and 14 mL; the remaining 12 STSD patients were postpubertal with testicular volumes more than 15 mL and physically fully developed secondary characteristics as assessed by Tanner stages .One STSD patient (age 6.7 y) was found to have a unilateral undescended testicle and was subsequently referred for surgical treatment by orchidopexy. No patient had delayed puberty as defined by pubertal onset after the age of 14 years; pubertal progression according to Tanner stages and testicular volumes were appropriate for age in all participants .For further analysis, subjects were allocated to 3 subgroups based on their pubertal progression as stated above: prepubertal STSD n = 13, controls n = 15; peripubertal STSD n = 5, controls n = 5; and postpubertal STSD n = 12, controls n = 19. Statistical analysis has been performed in all 3 subgroups , but forSTS gene in all patients. A total of 27 of 30 patients had a complete deletion of the STS gene and the adjacent HDHD1A gene. There was no evidence for deletion of further coding regions at the Xp22.31/32 locus; in particular, we did not identify KAL1 gene deletions in any of the included patients . One patient (P16) had a deletion of exon 7 only . In 2 brothers there were no abnormal findings in the MLPA analysis and subsequent Sanger sequencing of the STS gene revealed a hemizygous nonsynonymous missense mutation in exon 9  encoding for p.R454C, a cytosine to thymidine change at position g.114,414 resulting in the replacement of arginine to cysteine on the protein level. This mutation has previously been reported in a patient with XLI (Genetic analysis confirmed abnormalities within the with XLI .Serum DHEA was significantly lower in the pre- and postpubertal STSD subjects than in sex- and age-matched healthy controls , A and BOf note, the ratio of serum DHEA to DHEAS was significantly higher before puberty in healthy controls C. By conSerum testosterone was at age-appropriate low levels in all prepubertal subjects . After pHere, we have investigated androgen metabolism and generation and pubertal development in a large, genetically fully characterized cohort of patients with STSD/XLI. We found no gross abnormalities regarding pubertal progression and development in children and adolescents with STSD. Their steroid metabolome was indicative of mild androgen deficiency, with significantly lower circulating concentrations of DHEA and testosterone. However, these appear to be compensated for by enhanced tissue-specific androgen activation including increased net 5α-reductase activity observed in our cohort, resulting in total androgen metabolite excretion rates that did not differ significantly between STSD and healthy controls.STS gene in all patients. Complete deletions were detected in 27 of 30 patients, in keeping with previous reports describing deletions as the commonest mutation type in XLI/STSD with an incidence of 80%–90% (KAL1 gene resulting in Kallmann syndrome with anosmic hypogonadotropic hypogonadism were not present in this cohort. Similarly, other forms of contiguous gene deletion syndromes frequently described in patients with XLI (STS gene function. All our patients with complete STS deletions had a concurrent deletion of the HDHD1 gene upstream of the STS locus, which is a previously reported feature in most patients with complete STS deletions (HDHD1 encodes for a pseudouridine-5′-phosphatase involved in RNA metabolism, and its molecular function has been described in detail only recently (Hdhd1 knockout mouse has not yet been reported. One can speculate that HDHD1 contributes to some phenotypic features observed in patients with XLI; however, detailed genotype-phenotype studies are lacking partially due to insufficient genetic characterization of XLI patients of earlier cohorts. Preumont et al (STS gene. The one patient with an undescended testis in our cohort also had a HDHD1 deletion. However, at present there is no conclusive evidence for functional involvement of HDHD1 in testicular descent.We have genetically characterized the entire cohort and found abnormalities of the  80%–90% , 20. Impwith XLI , 22, wereletions , 24. HDHrecently . The impSTS gene. Although partial STS deletions have been reported in XLI (3H-DHEA assays with patient leukocytes demonstrated reduced STS activity (One patient in our cohort had a partial deletion of exon 7 of the d in XLI , 27, theactivity .Pubertal development and progression was not abnormal in this cohort of STSD patients; Tanner stages, testicular volumes and height SDS did not differ from controls. The onset of pubertal changes reported by the STSD patients in our cohort was between 11 and 11.5 years, which is considered to be within the normal range of pubertal onset in males , 29. HowPrevious studies on steroid production in STSD have mostly focused on cholesterol sulfate and DHEAS; the latter was not consistently reported as elevated, perhaps due to the different methodologies employed for steroid quantification . Our stuUrinary steroid metabolome analysis in our STSD cohort demonstrated normal overall androgen metabolite excretion despite lower concentrations of DHEA available for peripheral androgen inactivation. Our finding of enhanced 5α-reductase activity, which leads to increased activation of testosterone to 5α-dihydrostestosterone, suggests the presence of a compensatory mechanism counteracting a slightly lower androgen production rate. Increased 5α-reductase activity is frequently observed in androgen excess conditions like adult PCOS –33, but –Our study is the first to provide information on serum DHEA concentrations in STSD, which has not been measured in any of the previous studies  and the We also report, for the first time, a significantly increased ratio of serum DHEA over serum DHEAS in healthy prepubertal children that decreases steeply after puberty. This prepubertal increase in the DHEA to DHEAS ratio is absent in STSD patients, indicating that this previously unknown phenomenon is due to a prepubertal, physiological increase in STS activity. Little is known about normal physiological regulation of STS, with some evidence of cytokine-mediated changes in STS expression and activity , 37. In In summary, we have demonstrated by steroid metabolome analysis that the impact of STSD on androgen generation is small, resulting in only mild androgen deficiency that is apparently compensated for by up-regulation of peripheral androgen activation. This suggests that the sulfotransferase reaction inactivating DHEA to DHEAS is the predominant switch regulating the balance between DHEA activation and inactivation, with significant clinical implications , 2. We f


Bifidobacterium after soy consumption, and Bifidobacterium and Eubacterium were significantly greater in equol vs non-S-(-)equol producers. This is the first in vivo study using pyrosequencing to characterize significant differences in fecal community structure and composition in postmenopausal women after a week of soy diet-supplementation, and relate these changes to differences in soy isoflavones and isoflavone metabolites.Soy isoflavones and their metabolism by intestinal microbiota have gained attention because of potential health benefits, such as the alleviation of estrogen/hormone-related conditions in postmenopausal women, associated with some of these compounds. However, overall changes in gut bacterial community structure and composition in response to addition of soy isoflavones to diets and their association with excreted isoflavone metabolites in postmenopausal women has not been studied. The aim of this study was to determine fecal bacterial community changes in 17 postmenopausal women after a week of diet supplementation with soy bars containing isoflavones, and to determine correlations between microbial community changes and excreted isoflavone metabolites. Using DGGE profiles of PCR amplified 16S rRNA genes (V3 region) to compare microbial communities in fecal samples collected one week before and one week during soy supplementation revealed significant differences (ANOSIM p<0.03) before and after soy supplementation in all subjects. However, between subjects comparisons showed high inter-individual variation that resulted in clustering of profiles by subjects. Urinary excretion of isoflavone (daidzein) metabolites indicated four subjects were equol producers and all subjects produced O-desmethylangolensin (ODMA). Comparison of relative proportions of 16S rRNA genes from 454 pyrosequencing of the last fecal samples of each treatment session revealed significant increases in average proportions of NCT00244907Clinicaltrials.gov  Dietary consumption of soy isoflavones has been broadly studied for their potential health benefits Clostridium coccoides-Eubacterium rectale group Bifidobacterium, the Lactobacillus-Enterococcus group and Faecalibacterium prausnitzii occurred after a month of soy consumption Only a couple of studies have examined the effect of soy intervention on gut microbiota in postmenopausal women in vitro studies and in vivo animal studies Enterococcus faecium, Finegoldia magna, Lactobacillus mucosae, and Veillonella sp.) has been used to convert daidzein to S-(-)equol when mixed with feces of non-S-(-)equol producers Most gut microbiota capable of metabolizing soy products or soy isoflavones to metabolites have been found using in vivo response to soy consumption and bacterial populations contributing to variability in isoflavone metabolism, a more comprehensive approach is needed. The main aim of this study was to determine the effect of diet supplementation with soy on the fecal microbial community in postmenopausal women, and to determine the correlation between fecal bacterial populations with excreted soy isoflavone metabolites. A two-week experiment was conducted in which subjects in the first week were monitored for normal daily changes in fecal microbial community structure and the second week changes associated with the daily addition of soy bars to the diet using DGGE of 16S rRNA gene sequences (V3 region) amplified by PCR. Pyrosequences of the 16S rRNA gene (V3–V4 region) was used to compare bacterial community composition before and after diet supplementation with soy and to identify populations associated with metabolites produced after fermentation of isoflavones in postmenopausal women. Instead of targeting specific populations, which is a more limited approach, we chose to evaluate more comprehensively all populations that change with soy consumption to identify those that are associated with isoflavone metabolite production.To better understand differences in gut microbiota The protocol for this study and supporting checklist are available as supplemental materials; see The study period was comprised of two one-week sessions in which subjects were asked to avoid soy product consumption in their regular diet. During the first week individuals consumed their regular diets (designated no-soy samples) excluding soy products from their diet and in the second week they supplemented their regular diet daily with one Revival soy bar (160 mg of soy isoflavones and 1 g saponin) (designated soy samples). The timeframe used for the soy intervention is supported by work of others that have shown changes in gut microbial communities after a day of fat/fiber dietary interventions H. pomatia B-glucuronidase/sulfatase for the metabolites genistein, daidzein, dehydrodaidzein, glycitein, formononetin, biochanin A, coumestrol, O-desmethylangolensin (O-DMA), 6-hydroxy-ODMA and S-(-)equol. Metabolites were measured using reverse-phase HPLC in tandem with electrospray ionization mass spectrometry using a AB Sciex 4000 triple quadrupole mass spectrometer  as described previously Urine samples were collected and processed as described previously for isoflavone metabolite analysis During the study fecal samples were collected daily by subjects and kept on ice, for no more than 12 hours, until taken to Purdue University and stored at −20°C until processed. Each individual provided at least 13 samples during the course of the study. Fecal samples were thawed at 4°C overnight before processing. Each fecal sample was weighed, placed in a sterile stomacher bag and homogenized for approximately 2 minutes with two volumes of sterilized Milli-Q water per weight using a stomacher apparatus. Samples were aliquoted into sterile polypropylene tubes from the DNA extraction kit and stored at −20°C until DNA extraction.Total genomic DNA was extracted from each fecal homogenate (100 µL) using the Fast DNA Soil Spin kit  according to the manufacturer’s instructions. We have previously demonstrated that this kit yields maximum DNA from fecal samples due to the mechanical lysis process included as part of the protocol Fecal community structure was determined using PCR-DGGE. A ∼181 bp fragment from the V3 region of the 16S rRNA gene was amplified by PCR using the universal bacterial primers PRBA338F-GC and PRUN518R The 454 FLX system  was used to determine bacterial composition of the last fecal samples from each treatment session for each subject. The V4 region of the 16S rRNA gene was amplified by PCR using 10 picomoles of a 8-mer tagged forward primer 520-F and a set of four reverse primers 802-R http://qiime.sourceforge.net/) Sequences obtained from the 454 FLX pyrosequencing were analyzed using the QIIME pipeline  Wilcoxon signed-rank test was used to determine differences in the relative proportions of bacterial population obtained by pyrosequencing before and after soy diet supplementation. Mann-Whitney was used to determine differences in relative abundances of bacterial populations between S-(-)equol and non-S-(-)equol producers after supplementation with soy and differences in isoflavone metabolites that were excreted from S-(-)equol and non-S-(-)equol producers. Kendall tau rank correlation coefficients were calculated to identify significant correlations (p<0.05) between metabolites excreted and fecal bacterial populations determined by pyrosequencing. All these basic statistical tests were performed using software available in PAST 10 S-(-)equol:daidzein ratio of subjects 321, 325, 328 and 346 were greater than −1.75 making them S-(-)equol producers as defined by Setchell Metabolites from isoflavones were detected from urine samples in postmenopausal women after 4 days of supplementation with soy . The aglPearson’s correlations were found to be significantly different between concentrations of some isoflavones and isoflavone metabolites . PositivP<0.03) differences in bacterial community structure in all the subjects  sequences per sample and ranged from 4,900 to 16,250 sequences. All calculations and community comparisons were made using a subset of 4,900 sequences for each sample that were selected randomly after 10 iterations of rarefaction. More than 99% of the sequences were classified into the phyla Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria and Verrucomicrobia, for both no-soy and soy samples. Other phyla present in percentages less than 0.001% included Cyanobacteria, Synergistetes, Tenericutes and TM7. Although primers used were theoretically specific for Bacteria some Archaea sequences were also amplified but were not included in downstream analysis due unknown coverage of this phylum by these primers.Bifidobacterium increased and Lactobacillus and unclassified Clostridiaceae decreased  in S-(-)equol producers whereas Roseburia was significantly lower.Taxonomic assignment of the sequences in all samples resulted in the identification of 65 genera, and an additional 47 taxa that were not classified to a known genus (designated “other” or “unclassified”) . Compariecreased . A compaecreased , in thisUsing rarefaction the same number of sequences from each sample was used in comparisons of community alpha and beta diversity measures. An average of 98.7% (range 97.7–99.4%) Good’s coverage was calculated for the rarefied dataset. Paired t-tests indicated there were no significant differences between subjects on the no-soy and soy diets based on the alpha diversity measures: Shannon diversity index (4.9±0.6 vs 4.6±0.9), richness indices ChaoI (432.8±110.8 vs 440.3±112.7) and observed species (305.4±79.0 vs 302.9±81.4), and phylogenetic diversity (PD) whole-tree measure (20.6±4.2 vs 20.8±4.8) between no-soy vs soy samples, respectively.Principal coordinate analysis (PCoA) of weighted Unifrac distances illustrated that communities of S-(-)equol producers clustered more together at the end of the soy diet that was not as evident before the soy diet when they were more intermixed . ResultsPeptoniphilus was negatively correlated with S-(-)equol and positively correlated with ODMA. Also notable was Bifidobacterium; it correlated negatively with dihydrodaidzein (−0.56) and was found to significantly increase in subjects after soy supplementation  was used to determine the relationship between the variation in bacterial community composition, and some subject traits that showed significant correlations. Host factors that significantly corresponded (p<0.05) with the microbial communities were being an S-(-)equol producer and the number of years the subject was post-menopause . Arrows Bifidobacterium, after soy consumption. Furthermore, correlations were found between isoflavones and isoflavone metabolites with proportions of a number of different bacterial genera, many were previously not reported to be associated with isoflavone fermentation. The increase in proportion of Bifidobacterium, a bacterium found by others to be involved in soy fermentation, provides support for the validity of these new findings Bifidobacterium with dihydrodaidzein suggests that it is involved in the fermentation of this metabolite to downstream metabolites. This study demonstrates that a week of a diet supplemented with soy is sufficient to significantly change the gut microbiome and these changes can be related to soy fermentation metabolites.After daily supplementation with a soy bar for one week the baseline fecal bacterial community structure and composition in postmenopausal women significantly changed. By using a community genetic fingerprinting method, PCR-DGGE, temporal changes were tracked and soy treatment differences were found to be significant. Based on the knowledge that community structure changed significantly, pyrosequencing of representative samples from the end of the soy and no-soy treatments were used to identify the bacterial genera contributing to these differences. There was a significant increase in the relative proportion of one genus, PCR-DGGE profiles indicated changes in bacterial community structure occurred from one to five days after beginning soy bar consumption, with the majority changing in the first couple of days. This illustrates subject variation in response to diet change but the effect is relatively rapid as seen in extreme changes in diet Bifidobacterium whose proportions increased with soy consumption, especially in S-(-)equol producers. Similar increases of Bifidobacterium in postmenopausal women after soy interventions have been previously reported Rothia that was in higher relative proportions in S-(-)equol versus non-S-(-)equol producers and was significantly correlated with equol production. This genus, also a member of the phylum Actinobacteria, has not been previously associated with S-(-)equol production. The proportions of this taxon are very low therefore more studies are needed in the future to determine its involvement in daidzein metabolism. Due to the high variability between subjects there is always a possibility that some of these correlations may be false positives.A potential bacterium that was selected by the soy diet was Collinsella, Dialister, Dorea, Finegoldia, Papillibacter. Peptoniphilus, Pseudoramibacter and Rothia. Correlations also identified a number of genera that have been previously reported to metabolize isoflavones in vitro: Adlercreutizia, Bifidobacterium, Clostridium, Corynebacterium, Lactococcus, Ruminococcus, and Slackia equol production in postmenopausal women in vivo metabolism of isoflavones and isoflavone metabolites in humans by these taxa has not been proven.Inherent variation between subjects in their gut microbiome and potential physiological redundancy of different bacterial taxa able to carry out isoflavone metabolism required additional analytical methods to explore associations between taxa and metabolites. Indeed, CCA indicated gut community composition corresponded with the number of years that subjects were post-menopause and was in the opposite orientation as alpha diversity measures, illustrating one potential source of gut microbiome variation among subjects. Correlation analyses identified a number of bacterial populations associated with isoflavone metabolism that have not been previously reported: Lower relative abundances in the phylum Bacteroidetes were observed in the subjects in this study when compared with other studies that included subjects within the same age range (less than 0.04% in comparison with ∼10%) in vivo response of GIT bacterial populations to one week of dietary soy supplementation in postmenopausal women. Previous studies examining the effect of soy on gut microbiota in postmenopausal women targeted only a few bacterial populations and monitored their changes. In this study using pyrosequencing positive correlations were found between bacterial taxa and production of soy isoflavone metabolites that have not been previously reported. Future studies in soy fermentation are needed to understand the specific role of these bacteria taxa. The validity of these findings was supported by increases in Bifidobacterium that have been reported in other studies. It negatively correlated with dihydrodaidzein and although not statistically significant its proportions correlated positively with excretion of S-(-)equol, suggesting a role in isoflavone metabolism in postmenopausal women. In addition, fecal bacterial communities from S-(-)equol and non-S-(-)equol producers were significantly different supporting the hypothesis that S-(-) equol production is dependent on intestinal bacterial community composition. Further studies are needed to determine the stability of changes in the gut microbiota in response to soy over longer periods of time and in the context different background diets, e.g., non-vegetarian versus vegetarian.This is the first report using pyrosequencing to determine the Table S1Primers used for fecal bacterial community analyses in postmenopausal women.(DOCX)Click here for additional data file.Table S2Correlations between isoflavones and isoflavone metabolite concentrations in urine samples from postmenopausal women after soy supplementation of diets.(DOCX)Click here for additional data file.Table S3Comparison of average proportion of genera in fecal samples of postmenopausal women after no-soy and soy supplementation of diets.(XLSX)Click here for additional data file.Table S4Correlations between average proportion of genera with isoflavones and isoflavone metabolites in fecal samples of postmenopausal women.(XLSX)Click here for additional data file.Checklist S1TREND Checklist.(PDF)Click here for additional data file.Protocol S1Trial Protocol.(PDF)Click here for additional data file.


Nucleic acids are potent inducers of the antiviral type I interferons (IFN) and therefore represent prototypic PAMPs in viral infections. Innate nucleic acids sensors patrol the cytoplasm for the presence of RNA and DNA but have only a limited capacity to discriminate between endogenous and exogenous nucleic acids. Therefore mechanisms evolved that prevent the accumulation of endogenously derived nucleic acids. In Aicardi-Goutières syndrome (AGS), which represents a rare monogenic variant of the prototypic autoimmune disease systemic lupus erythematosus, genetic defects of these mechanisms result in production of large amounts of type I IFN. SAMHD1 is an intracellular nuclease that degrades RNA and DNA and cleaves deoxynucleotides (dNTP) into nucleosides and inorganic triphosphate, mutation of which cause AGS. The nucleotide triphosphohydrolase also confers antiretroviral activity to SAMHD1, as dNTP degradation was shown to represent a major block to reverse transcription of retroviruses. How and why SAMHD1-deficent cells activate the type I IFN system is not known so far. Furthermore, a comprehensive analysis of the antiretroviral potential of mouse SAMHD1 is still lacking.We aim to identify essential pathways that mediate the spontaneous type I IFN response in SAMHD1 knockout mice.We generated SAMHD1 knock out mice and in parallel inactivated crucial molecules of the type I IFN systems in these mice. Activation of the type I IFN system was quantified by global transcriptome sequencing. Antiretroviral activity of murine SAMHD1 was assessed by infection of mutant mice with GFP-Reporter retroviruses.SAMHD1-deficient mice do not develop any signs of inflammation or systemic autoimmunity. However, they spontaneously produce IFNb that subsequently activates transcription of interferon-stimulated genes (ISG). This response was abolished in SAMHD1 IFNb and in SAMHD1 IFNAR1 double deficient mice. Surprisingly, additional inactivation of both, the intracellular RNA and DNA sensing machinery, by knocking out MAVS or STING in SAMHD1-deficient mice, respectively, suppressed the spontaneous IFN production. In vivo infection experiments showed that single deficiencies of IFNAR1 and SAMHD1 only slightly or moderately increased reverse transcription, respectively. Interestingly, in SAMHD1 IFNAR1 double deficient mice we found reverse transcription increased by an order of magnitude compared to wild type and the single deficient mice.In contrast to the situation in other AGS-mouse models, in SAMHD1-deficient mice both, a functional intracellular RNA and DNA sensing machinery are required to spontaneously activate the type IFN system. Understanding the mechanisms that establish the chronic IFN response in this model will be instrumental to elucidate whether there is a unifying concept underlying the pathogenesis of AGS.


II(atsm) rescues nigral cell loss and improves dopamine metabolism in the MPTP model. The mechanism of action of CuII(atsm) needs to be further defined to understand how the compound promotes neuronal survival. Whole genome transcriptomic profiling has become a popular method to examine the relationship between gene expression and function. Substantia nigra samples from MPTP-lesioned mice were evaluated using whole transcriptome sequencing to investigate the genes altered upon CuII(atsm) treatment. We identified 143 genes affected by MPTP lesioning that are associated with biological processes related to brain and cognitive development, dopamine synthesis and perturbed synaptic neurotransmission. Upon CuII(atsm) treatment, the expression of 40 genes involved in promoting dopamine synthesis, calcium signaling and synaptic plasticity were restored which were validated by qRT-PCR. The study provides the first detailed whole transcriptomic analysis of pathways involved in MPTP-induced Parkinsonism. In addition, we identify key therapeutic pathways targeted by a potentially new class of neuroprotective agents which may provide therapeutic benefits for other neurodegenerative disorders.The administration of MPTP selectively targets the dopaminergic system resulting in Parkinsonism-like symptoms and is commonly used as a mice model of Parkinson’s disease. We previously demonstrated that the neuroprotective compound Cu Parkinson’s disease (PD) is characterised by the presence of Lewy bodies, increased synucleinopathy, dopamine reduction in the striatum and degeneration of dopaminergic neurons in the substantia nigra pars compacta (SNpc). The consequence of such disease leads to motor impairments, including tremor dyskinesia, rigidity, instability and tremors+) by glial monoamine oxidase B. MPP+ is a substrate of the dopamine transporter. MPP+ then enters the mitochondria and disrupts oxidative phosphorylation by inhibiting complex I of the mitochondrial electron transport chain and results in a mitochondrial-initiated mode of cell death78Th; tyrosine hydroxylase, Nd4; NADH dehydrogenase, subunit 4, Sncb; β-synuclein, Uchl1; ubiquitin carboxyl-terminal esterase L1, Hsp70; heat shock protein 70, Park2; E3 ubiquitin protein ligase, NFkB; nuclear factor kB and iNOS; inducible nitric oxide synthase) are found to be altered at various time-points during the course of MPTP lesioning10Neurotoxin models of PD are widely used and often require a pathological lesion that results in an approximate 50% decrease of dopaminergic neurones in the SNpc to produce the phenotypic features of late-stage PD. One of the most commonly used neurotoxin based animal models to study PD is the 1-methyl-1, 2, 3, 6-tetrahydropyidine (MPTP) induced mice model2345II(atsm)), which rescued PD-relevant phenotypes in multiple animal models including the MPTP mice modelTh and dopamine metabolismII(atsm) treatment was able to rescue nigral cell loss and improve dopamine metabolism in the MPTP model. The potential mechanism behind the neuroprotective affect of CuII(atsm) is the ability of this compound to inhibit peroxynitrate-mediated nitrative stress and consequently the formation of α-synuclein aggregates. It is possible that CuII(atsm) acts on other pathways to promote neuronal survival which needs to be investigated.Several studies have used the MPTP model to demonstrate the effectiveness of potential neuroprotective drugs for PD such as the iron chelator, M30, and others including ladostigil and TV-3326 (N-propargyl-3R-aminoindan-5yl)-ethyl methylcarbamate) which have been found to regulate a number of neuroprotective-adaptive mechanisms13II(atsm) treatment. This unbiased high-throughput approach enables the identification of genes relevant to PD that have not been previously associated with the disease and the cellular genes and pathways targeted by CuII(atsm). Furthermore, in addition to CuII(atsm), new targets could be identified to assist in the development of neuroprotective drugs that may exert their protective effect through their ability to modulate target gene expression. In our previous study, MPTP induced decreases in Snca, Th and Vmat2 (vesicular monoamine transporter 2) mRNA expression which recovered to normal levels upon treatment with CuII(atsm). Our previous study provides a rationale to identify all deregulated genes in MPTP-lesioned mice to understand the pathways targeted by this compound Until now, studies have employed the use of qRT-PCR and microarray technology to decipher the molecular mechanism behind potential therapeutics for PD within mice models. Here, we have employed an RNAseq whole transcriptomic sequencing approach to evaluate the SNpc from MPTP lesioned mice and the changes upon CuII(atsm) treatment. This study unveils a consistent pattern of expression changes in the transcriptome that correlates with injured or dying neurons under neurotoxic stress by acquiring either adaptive, compensatory or restoratory molecular responses.Here, we identified significantly altered gene expression in targets associated with perturbed synaptic neurotransmission, stress response, Mitogen-activated protein kinases (MAPK) signalling, cell adhesion, nervous system development and vascular smooth muscle contraction (VSMC) in MPTP-lesioned mice. Additional intrinsic signalling pathways in respect to activated calcium signalling, phosphatidylinositol 3′ –kinase—protein kinase B (PI3k-AKT) signalling, and neuronal junctions were also identified and were found to recover upon CuP < 0.05, Slc6a4 , Mapk13 , Oxt2  as well as upregulation of Pla2g5 , Clic6  and Kcne2   .II(atsm), including a group of unlesioned control mice treated with CuII(atsm), also underwent whole transcriptome profiling. Genes DE between MPTP-lesioned mice treated with CuII(atsm) compared to MPTP-lesioned mice  and MPTP lesioned mice  compared to the unlesioned sham control which are DE upon MPTP lesioning were also analysed. DE genes that changed in unlesioned mice treated upon CuII(atsm) mice compared to the sham controls are consequentially removed through this analysis (II(atsm) treatment in MPTP-lesioned mice  across the treatment groups are displayed in II(atsm) treatment, we selected 15 genes for validation using qRT-PCR (Ramp3 and Mt1 by no more than 0.25 fold change amongst the comparisons (Of the 37 genes DE in MPTP-lesioned mice which showed a degree of recovery upon Cu qRT-PCR . These g qRT-PCR . Genes tparisons .II(atsm) treatment underwent Gene Ontology (GO) enrichment and pathway analysis which categorised the set of genes into different functional and biological categories  altered in MPTP-lesioned mice and the 37 genes recovered upon Cutegories . Using ttegories . Biologitegories . Enrichmtegories . Genes wtegories . The anaII(atsm) treatment can be visualised in the circosdiagram in Adcy1 (adenylatecyclase 1), Mapk13 (p38 delta MAP kinase), Prkcd  and Ptk2b (PTK2 protein tyrosine kinase 2 beta). To understand the relationship of these genes, Adcy1, Mapk13, Prkcd and Ptk2b were used to identify direct and indirect relationships with the other 143 DE genes identified in MPTP-lesioned mice.The common regulatory pathways affected upon MPTP lesioning and those recovered upon CuII(atsm) treatment. The map contains 19 pathways, including enrichment pathways and 29 DE genes. Observations from the map uncovered that the DE genes were typically found at the extracellular and membrane regions that affected intrinsic signalling events. The combined approach allowed the identification of DE genes that have been directly or indirectly implicated in PD in this mice model including those targeted by CuII(atsm) (II(atsm) was found to target key regulatory genes such as Prkcd, Ptk2b, Th, Ramp3 and Calml  . Within nd Calml .II(atsm) seen in MPTP-lesioned mice was attributed to its peroxynitrite scavenging abilities thus decreasing protein nitration and retaining neuronal integrity. However, it is likely that CuII(atsm) also mediates other biological activities thus we performed whole transcriptome gene expression sequencing. Unlike microarray818II(atsm) may target in the SNpc. This study is also the first unbiased whole transcriptome analysis performed on MPTP-lesioned mice which covered 25, 902 genes. This study also addresses whether the MPTP lesioning represents similar aspects of PD in humans at the transcriptional level, and by doing so determine to what degree MPTP toxicity can predict translational targets in PD research. The deregulated genes we identify in the network collectively point towards dopamine synthesis impairment and perturbed synaptic neurotransmission, consistent with their involvement in PD.Current therapeutic strategies for PD largely involve dopamine replacement with L-Dopa (Levodopa) or dopamine receptor agonists (Cabasar and Ropinirole) which provide symptomatic relief. In the search for new neuroprotective drugs, various compounds have been shown to rescue PD phenotypes in MPTP-induced mice models1415Th, Ddc and Slc6a4 gene expression decreased which supports the destruction of dopaminergic neurons and loss of dopamine in injured neurons observed in the MPTP model system219Th expression has also been detected in microarray studies performed on MPTP-treated SNpc tissue17Ddc not only perturbs the normal biosynthesis of dopamine but also serotonin regulated by the Slc6a4 (SERT) gene. Slc6a4 is involved in serotonin uptake and synaptic vesicle trafficking making this transporter protein a potential neuroprotective target. For example, Dextromethorphan, a SERT inhibitor, was found to be neuroprotective for dopaminergic cells in the MPTP-diethyldithiocarbamate (DDC) model of ParkinsonismSlc6a118817In this study, the level of Shank3; SH3 and multiple ankyrin repeat domains 3 and Car12; carbonic anyhydrase 12) and calcium signalling  as identified through KEGG pathway analysis. Overall, calcium homeostasis is critical in neuronal cells and regulates many functions such as cell survival and promoting neuronal function and communicationIt has been reported that the MPTP neurotoxin also causes an increase in nitrosative stressIgsf5  and Cldn2 (claudin 2) were perceived to maintain cell polarity upon the loss of neurons after MPTP treatment. However, genes involved with focal adhesion and the extra cellular matrix (ECM), Col27a1 , Thbs3 (thrombospondin 3), Spp1 (secreted phosphoprotein 1) and Lama1  were downregulated, suggesting the existence of damaged neurons. Prior reports from Chang et al. highlighted that matrix metalloproteinase-3 (MMP-3), a proteinase that degrades ECM components, is released following damage to dopaminergic neurons and compromises the BBB after MPTP treatmentCellular communication through tight junctions, gap junctions, adherens junctions and focal adhesion molecules are essential in the nervous system for the transmission of nerve signals26Mapk13, Mef2c (Myocyte Enhancer Factor 2c) and Lef1 (lymphoid enhancer binding factor 1). PI3k-Akt signaling pathway is well-known for cell growth and survival. Activation of genes for Kitl (kit ligand), Prlr (prolactin receptor) and Vav3 (vav 3 oncogene) may mediate signals for reduction of apoptosis to avoid a major cascade of neuronal death in response to MPTP neurotoxicity. Other chemokine signalling genes identified were Prkcd and Pla2g5. Although these genes are enriched in the GO enrichment pathway related to vascular muscle, these genes also mediate membrane phospholipid synthesis. Studies have shown that phospholipase A2 show less activity in the SNpc of PD patients which may result in the inability to turnover phospholipids at the neuronal membrane upon oxidative stressPla2g5 as seen in MPTP-lesioned mice. Group 6 of the phospholipase A2  family has been well-characterised to be associated with PD in which single-nucleotide polymorphisms have been identified in PD patientsA major hallmark of PD is the malfunction of presynaptic signalling, however what occurs post-synaptically and intracellularly is less defined. It has been shown that chemokine signalling increases in MPTP-induced mice and activation of this pathway leads to cell adhesion, cell survival, neuronal polarity and synaptic transmission32Ttr (transthyretin) gene was found to be one of the most upregulated  genes in SNpc of MPTP-lesioned mice. Transthyretin has been shown to be indirectly associated with PD by its presence in serum and cerebrospinal fluid in Lewy body disordersFat2 , a cadherin protein found restricted to the nervous system in the brain, which initial studies have shown its involvement in the development of neuronsHoxc4, Hoxb3os, Hoxb3 and Hoxb5, FC > 1.2, P < 0.05) were also found to be significantly downregulated in MPTP mice. These represent a highly conserved family of transcription factors involved in neurogenesis such as neuronal differentiation and neuronal connectivity (reviewed inPitx3 (paired-like homeodomain transcription factor 3) has been shown to in involved in the development of dopamine neurons of the SNpcPitx2 (paired-like homeodomain transcription factor 2) was found to show a modest but significant fold change . The role of Hoxc4, Hoxb3os, Hoxb3 and Hoxb5 should be investigated further in the MPTP mice which may further support the possibility of regenerating neurones in the SNpc through new therapiesThe II(atsm) through understanding changes in gene regulation. Some of the restored genes include Ddc, Th, Calml, Kcne2, Sphk1, Ptk2b, Prkcd and Ramp3 which are associated with dopamine synthesis, synaptic neurotransmission and calcium signalling all required for coordination and smooth movement21920II(atsm) where an increase of TH and dopamine was confirmed by stereological counting of Nissl stained SNpc neurones and Western blottingCar12 which can also modulate neuronal excitability through mediating levels of H+ ions. H+ controls pH within and outside of neurones which is fundamental to neuronal development and synaptic plasticity+ in the brain requires the conductance of ionic channels and gap junctions to function which associated genes were found to be DE in MPTP-lesioned mice  and the majority restored upon CuII(atsm). This suggests that CuII(atsm) may not only promote the survival of dopaminergic neurones but has downstream effects to restore excitability within tissue by promoting the flow of ions through junctions of adjoining cells. Furthermore, CuII(atsm) treatment restored metallothionein 1 and 2 (Mt1 and Mt2) to unlesioned levels by up regulating their expression supporting reported neuroprotective effects of metallothionein (MT) observed in the literature4445Ttr was also restored in MPTP-lesioned mice treated with CuII(atsm). Using qRT-PCR, changes in Ttr expression were observed across various sections of the brain in adult unlesioned C57BL mice treated with M30Ttr before and after treatment may support its use as a potential biomarker for monitoring disease progressionThis is the first report revealing possible neuroprotective mechanisms of CuII(atsm) may serve as a promising neuroprotective drug to prevent the destruction of dopaminergic neurons and impairment of dopamine synthesis in PD. The validation of gene expression levels highly associated with PD such as Th, Ddc and solute carrier family genes suggests that the other differentially expressed genes identified in this study should be investigated further to uncover new insights into PD pathology and new potential treatments.The current transcriptomic data provides detailed signalling insights into potential drug targets where disease-modifying drugs can aim to restore dopamine metabolism, promote neurogenesis and re-establish normal homeostatic balance in the synaptic space and within neurons. Here, CuII(atsm) via oral gavage for 21 d. Pole test was performed after 19 d of treatment which was used to assess specific motor impairments related to basal ganglion pathology as described in our previous study2. Animals were killed by an overdose of sodium pentobarbitone , and perfused via the heart with cold 0.1 M PBS (Sigma-Aldrich), pH 7.4. The left brain hemisphere was dissected into regions and the SNpc was treated in RNAlater (Life Technologies) to preserve RNA for isolation. The study involved unlesioned (n = 6), MPTP-lesioned (n = 5) and MPTP-lesioned mice treated with CuII(atsm) (n = 7) including a unlesioned control treated with CuII(atsm) (n = 4). All methods conformed to the Australian National Health and Medical Research Council published code of practice for animal research, and experimentation was approved by a University of Melbourne Animal Ethics Committee. Sprague Dawley rats and C57BL/6 mice were purchased from Monash Animal Services.All studies and analysis were conducted in a blinded fashion to remove any bias associated with analysis. MPTP lesioning of C57BL/6 mice was performed as previously publishedPRJEB6957.Total RNA was isolated from SNpc section of all mice in the study using the miRNeasy kit (QIAGEN) according to manufacturer’s instructions. RNA integrity was assessed using the RNA Nano 6000 kit and run on the Agilent 2100 Bioanalyser (Agilent Technologies). mRNA was further isolated from total RNA using the NEBNext Poly(A) mRNA magnetic isolation module (New England BioLabs) according to manufacturer’s instructions and the yield and size distribution of mRNA was analysed using a RNA Nano 6000 chip. The mRNA samples were fragmented in preparation for cDNA synthesis and library construction using the NEBNext mRNA Library Prep Master Mix Set (New England BioLabs), whereby the manufacturer’s instructions were followed including ligating each sample with a unique index primer using the NEBNext Multiplex Oligos for Illumina (New England BioLabs). Library quality was assessed on an Agilent 2100 Bioanalyser using a DNA 1000 chip prior to sequencing on the Illumnia Hiseq 2500. Sequencing was performed at the Centre for Translational Pathology, Department of Pathology, University of Melbourne. Raw files can be downloaded at ENA, primary accession # https://www.vlsci.org.au/pipelines_and_protocols) developed by Life Sciences Computation Centre at the University of Melbourne was employed to process and align sequence reads generated from the libraries. The pipeline was based around Tuxedo protocol and R bioconductor packages. Briefly, sequence read quality was initially assessed in Illumina BaseSpace and parsed to FastQC for further evaluation. Only those reads with at least 80% of the base calls above Q30 were retained. The 3′ adapter sequence was removed from all reads using the suggested parameters in TrimmomaticMus musculus reference genome using TopHat version 2.0.8A basic differential expression analysis pipeline  and read counts were loaded into Seqmonk version 0.27.0 for visualisation (www.bioinformatics.babraham.ac.uk/projects/seqmonk). To determine fold change differences, the log of ratio of expression levels for each gene between conditions being tested was computed. Significantly DE genes were identified as those with a P value of <0.05 with Benjamini-Hochberg multiple testing correction at 5% FDR and a fold change to be a minimum of 1.2 fold change (log2). We consider this a reliable criteria which identifies significant genes of interest with notable differences in fold change which can be validated and reproduced by qRT-PCR using other biological replicates.The R package edgeR version 3.8.5II(atsm) treatment, DE genes , were queried using The Database for Annotation, Visualisation and Integrated Discovery (DAVID 6.7)® software . The pathways were then classified using the Kyoto Encyclopedia of Genes and Genomes databaseTo reveal GO biological processes, molecular functions and localisations between the altered genes in MPTP-lesioned mice treated with and without Cug in group i and replicate j; j; g and group i; g representing the variability. Pearson correlation coefficient was used to examine the relationship between different samples and the distribution was graphed in a scatter plot. To assess gene function and pathway, enrichment analysis was performed using the default parameters in DAVID and GeneGoMetaCore® through implementing Fisher’s exact test and adjusted for multiple testing using Benjamini-Hochberg FDR analysis to obtain significant results N is the total number of genes in the pathways; n is the number of gene interests; m is the number of gene samples in one pathway; k is the frequency of genes overlapped in all pathways.Preliminary quality control of sequencing reads was determined by the Phred scoring system. A Phred score of a base is: n = 6), MPTP-lesioned (n = 5), MPTP-lesioned CuII(atsm) (n = 7) and unlesioned CuII(atsm) (n = 4)) was run in triplicate to monitor technical variability and quality control. For data normalisation across samples, Hprt1 was used as an endogenous control gene. Normalisation of Ct values of each gene and determination of fold differences in gene expression  was calculated by the 2−∆∆Ct method. Data assist (Applied Biosystems) was used to analyse the data.For qRT-PCR, 1.5 μg of RNA was converted to cDNA  according to the manufacturers’ protocol. qRT-PCR  was performed using individual gene assays  and run on the VIIA™ 7 Real-Time PCR System (Life Technologies). Each biological replicate . Sci. Rep.6, 22398; doi: 10.1038/srep22398 (2016).


Drosophila, development of the compound eye is orchestrated by a network of highly conserved transcriptional regulators known as the retinal determination (RD) network. The retinal determination gene eyes absent (eya) is expressed in most cells within the developing eye field, from undifferentiated retinal progenitors to photoreceptor cells whose differentiation begins at the morphogenetic furrow (MF). Loss of eya expression leads to an early block in retinal development, making it impossible to study the role of eya expression during later steps of retinal differentiation. We have identified two new regulatory regions that control eya expression during retinal development. These two enhancers are necessary to maintain eya expression anterior to the MF (eya-IAM) and in photoreceptors (eya-PSE), respectively. We find that deleting these enhancers affects developmental events anterior to the MF as well as retinal differentiation posterior to the MF. In line with previous results, we find that reducing eya expression anterior to the MF affects several early steps during early retinal differentiation, including cell cycle arrest and expression of the proneural gene ato. Consistent with previous observations that suggest a role for eya in cell proliferation during early development we find that deletion of eya-IAM leads to a marked reduction in the size of the adult retinal field. On the other hand, deletion of eya-PSE leads to defects in cone and pigment cell development. In addition we find that eya expression is necessary to activate expression of the cone cell marker Cut and to regulate levels of the Hedgehog pathway effector Ci. In summary, our study uncovers novel aspects of eya-mediated regulation of eye development. The genetic tools generated in this study will allow for a detailed study of how the RD network regulates key steps in eye formation.In  Drosophila eye imaginal disc consists of pluripotent cells that are committed to a retinal fate and express high levels of eyeless (ey), a critical regulator of eye development. These pluripotent retinal progenitors begin differentiation along a moving boundary called the morphogenetic furrow (MF) at the posterior margin of the early third instar eye imaginal disc atonal (ato), which encodes a basic helix-loop-helix (bHLH) transcription factor (TF) necessary for the onset of photoreceptor differentiation ato expression resolves into regularly spaced single cells, which differentiate into R8 photoreceptors, the founding cell of each ommatidium (unit eye). The remaining cell types of the adult eye are progressively recruited and differentiate around each founding R8 photoreceptor The early eyes absent (eya) is a conserved transcription co-factor expressed in a broad band anterior to the MF and in all cells posterior to the MF eya such as 1eya and 2eya lead to eye specific loss of eya expression and gives rise to adult flies without eyes, suggesting that eya is necessary for eye development 1eya and 2eya imaginal discs express ey suggesting that the retinal progenitors lacking eya expression are committed to the eye lineage eya expression do not execute any further steps of eye development ato expression eya mutant tissue, retinal progenitors overproliferate and grow out of the plane of the eye disc; these cells eventually undergo apoptosis eya expression, the role eya may play in differentiating photoreceptors has been difficult to study. One way to bypass this early block and to identify the role of eya during later steps in retinal developmental is to generate single-celled eya mutant clones posterior to the MF. Although this approach has suggested a requirement for eya function in differentiating photoreceptors, it use is limited by the minimal clone size possible The RD network member eya and so causes G1 arrest of proliferating retinal progenitors anterior to the MF eya during photoreceptor morphogenesis posterior to the MF is lacking. We have addressed this gap by the design and implementation of an eya genomic rescue construct that allows normal early (anterior) expression but blocks eya expression posterior to the MF, such that retinal differentiation is properly initiated but downstream developmental events are affected.Previous studies suggest that Eya functions at least in part through forming a transcriptional regulatory complex with the homeodomain transcription factor Sine oculis (So), which directly activates expression of several regulators of retinal development eya, eya-IAM (Immediately Anterior to the MF) and eya-PSE (Photoreceptor Specific Expression). Reporter analysis of these regulatory regions using destabilized GFP (dGFP) suggests that eya-IAM is expressed in retinal progenitors immediately anterior to the MF, while eya-PSE is expressed in differentiating photoreceptors posterior to the MF in the third instar eye imaginal disc. We have analyzed the role of these elements in regulating eya expression during retinal development by deleting them in a previously characterized eya genomic rescue construct. As predicted, our analysis of GRΔIAMeya and GRΔPSEeya animals supports a role for eya during G1 arrest of retinal progenitors anterior to the MF as well as expression of the proneural gene ato. Our analysis also suggests a novel role for eya in the development of cone and pigment cells.In this report we describe two new regulatory regions of eya genomic region. The enhancer fragments were then subcloned into a plasmid carrying destabilized GFP (dGFP) as a reporter and an attB site for site-specific integration eya-IAM fragment was generated using IAM-F 5′ AGAGAATTCCAAACACCTGGCATTATCGCTTCATCTCGG and IAM-R 5′AGCGGATCCAGTTTCGTCTCCTCTTTTGCTGCCTCTTTG, the eya-PSE enhancer was generated using PSE-F 5'-ATTGAATTCGTCCAGAGTGGTGGTGGTGA and PSE R 5'-GATCTCGAGGTACGATTTGTGCGTGCG. These primers also indicate the limits of deletion. The resulting construct was integrated into the P{CaryP}attP2 site (abbreviated P2), which is located at 3L∶11,063,638, using φC31 integrase. Site-specific integration was confirmed by PCR with attB/attP primers Enhancer fragments were amplified from a BAC carrying the eya genomic rescue (GReya) constructs carrying deletions of eya-IAM and eya-PSE enhancers were generated using recombineering as previously described P2, the same site used for the wild-type GReyaattB/attP primers. We performed PCR on genomic DNA from the transgenic flies to verify the deletions.The eya enhancers in eye development, we crossed the mutant GReya constructs into the following mutant backgrounds: 2eya homozygotes, which specifically lack Eya expression in the eye disc cliIID/Df(2L)BSC354. eyacliIIDeya is a null allele caused by a premature stop codon that causes recessive embryonic lethality Df(2L)BSC354 (hereafter referred to as Df(eya) removes the entire eya locus cliIID/Df (eya)eya lacks all endogenous eya function. The ΔIAMeya and ΔPSEeya clones were generated by crossing cliIID, FRT 40/CyO; eyaGRΔIAM/TM6B,Tb1eya or cliIID, FRT 40/CyO; eyaGRΔPSE/TM6B,Tb1eya respectively with hsflp; P{w[+mC] = arm-LacZ}, FRT40/CyO animals. The RNAi stocks w; UAS-soRNAi (transformant ID104386) and w; UAS-eyaRNAi (transformant ID 108071) from VDRC were used All crosses were performed on standard cornmeal agar at 25°C. Heat shocks were performed at 37°C as described in Anderson et.al., 2012. To test the function of the Primary antibodies used were mouse anti-Eya (1∶200), anti-Cyclin B (1∶200), Anti-Ci (1∶200), anti-Cut(1∶100), rat anti-Elav (1∶500) , guinea pig anti-Sens (1∶2000), guinea pig anti-Ato , Rabbit anti-β-Gal  and chick anti-GFP . All secondary antibodies were made in goat and used at a final dilution of 1∶500; Cy3 and Cy5 labeled secondary antibodies were obtained from Jackson ImmunoResearch, the Alexa Fluor 488 (used at 1∶500) and Phalloidin Alexa Fluor 594 (used at 1∶500) was obtained from life technologies. Images were taken with a Zeiss LSM 510 confocal microscope and processed with ImageJ and Adobe Photoshop software. Immunohistochemistry on third instar eye discs and imaging of the adult eye were conducted as described previously eya mutant 2eya harbors a 322 bp deletion approximately 500 bp upstream of the eya transcription start site eya expression in the eye imaginal disc, suggesting a necessary role for this region for eya expression during eye development. A previous report using LacZ reporter constructs suggests that the 322 bp region can recapitulate the basic pattern of eya expression anterior to the MF in the early larval eye disc eya expression pattern during retinal development. Therefore, to identify the regulatory elements needed for complete retinal expression of eya we generated a large reporter construct, F4-dGFP that contains ∼9 kb of DNA upstream of the eya transcriptional start site (TSS), including the previously identified 322 bp enhancer (F4-dGFP recapitulates the complete endogenous eya expression pattern in the developing eye disc (F4-dGFP expression appears as a posterior to anterior gradient mimicking the endogenous eya gradient (data not shown). Posterior to the MF in third instar eye disc, F4 drives dGFP expression in differentiating photoreceptors and still maintains dGFP expression in retinal progenitors anterior to the MF  and eya-PSE (Photoreceptor Specific Enhancer), based on their ability to drive dGFP expression in undifferentiated and differentiating retinal cells, respectively . eya-PSE driven dGFP expression is completely absent from second instar and early third larval instar eye discs (data not shown). eya-PSE driven dGFP co-localizes with Eya staining in photoreceptors posterior to the MF eya animals , as well as cliIIDeya clones rescued by a single copy of GRΔIAMeya (henceforth referred to as ΔIAMeya clones). As expected (assuming there are no other redundant enhancers), Eya expression immediately anterior to the MF in ΔIAMeya eye discs is significantly lower compared to control animals (ΔIAMeya clones show a complete loss of Eya expression anterior to the MF as compared to neighboring control tissue (ΔIAMeya eye discs and in ΔIAMeya anterior clones that do not span the MF (data not shown). Thus, consistent with the eya-IAM-dGFP reporter expression pattern, deletion of eya-IAM results in reduced eya expression in retinal progenitors anterior to the MF. In addition, ΔIAMeya clones posterior to the MF also show a reduction in the levels of Eya  escapers do reach adulthood and eclose. Such ΔPSEeya escapers are unable to locomote normally and rapidly fall into the fly food and die. However, ΔPSEeya escapers do show strong eye defects, including a glazed appearance and occasional melanotic tissue on the eye surface. These defects are more severe toward the posterior margin of the eye as compared to the anterior region . In contrast to ΔPSEeya whole mutant escaper animals, ΔPSEeya clones show a clear reduction in the levels of Eya expression posterior to the MF . As seen in ΔPSEeya clones anterior to the MF also show a reduction in the levels of Eya expression, although not as severe as that seen in ΔIAMeyaclones  and analyzing Cut expression as marker for cone cell development. We used GMR-Gal4 to drive so-RNAi and eya-RNAi in all cells posterior to the MF. Knockdown of so or eya was confirmed by antibody staining  in the MF. Retinal progenitors in the MF stabilize the active form of Ci (CiAct) that activates transcription of Hh responsive genes such as dpp. However, Ci is actively degraded in all the cells posterior to the MF eya expression would lead to higher levels of CiAct. We analyzed expression of Ci in ΔPSEeya clones using an antibody that recognizes both the full length and activated forms of Ci eya expression leads to elevated expression of Ci both anterior as well as posterior to the MF (eya may play a role in Ci degradation both anterior and posterior to the MF.Previous studies have suggested that ectopic expression of Hedgehog (Hh), as well as the Hh nuclear effector Cubitus interruptus (Ci), can cause an increase in the number of pigment cells in the o the MF , suggesteya receives regulatory input from several signaling pathways in the eye, as well as RD network members such as Ey eya-IAM and eya-PSE, we mutated putative binding sites of potential regulators within these enhancers, including Ey and Mad binding sites in eya-IAM, as well as So and several putative ETS binding sites in eya-PSE. Mad is the downstream effector of the Dpp pathway, which has been shown to activate Eya expression in the eye eya-IAM expression was altered in 1-2, smo3Mad double mutant clones that cannot respond to Dpp or Hh signaling in order to rule out indirect regulation by Dpp and Hh pathways. Consistent with the mutant binding site data, eya-IAM expression was unaltered in the 1-2, smo3Mad double mutant clones.eya-IAM driven dGFP expression. However previous reports show loss of Eya expression in ey mutant eye discs eya-IAM is regulated by Ey through a non-canonical site or indirectly via other transcription factors. To this end, we reduced levels of Ey anterior to the MF using ey-RNAi driven by h10-Gal4hairyey knockdown animals , dGFP expression anterior to the MF is markedly reduced . Loss of rdx function results in elevated expression of CiAct posterior to the MF rdx in the degradation of CiAct. An rdx-lacZ reporter suggests that rdx may be expressed in all cells posterior to the MF rdx expression is not completely understood. It has been suggested that the EGFR pathway may play a role in regulation of rdx, although whether this activation is direct or indirect is not known eya expression maybe necessary for degradation of CiAct. Given that eya expression posterior to the MF is regulated by the EGFR pathway rdx is expressed in the same cell that express eya, it is possible that Eya could mediate degradation of Ci via rdx activation. Consistent with this hypothesis, we found that rdx is enriched for So-binding (the binding partner of Eya) sites in third instar eye discs Act posterior to the MF. Previous work from our laboratory has shown that the proteolytically cleaved form of Ci – CiRep blocks activation of eya expression In absence of the Hh signal, Ci - the nuclear effector of the Hh pathway - is proteolytically cleaved to a transcriptional repressor form called CiΔPSEeya escapers and the ΔPSEeya clones suggests a role for eya expression in cone and pigment cell development. Previous reports suggest that upregulation of Ci posterior to the MF can lead to excess pigment cells ΔPSEeya clones suggests that elevated Ci levels may contribute to excess pigment cells. However, reduced levels of eya posterior to the MF also cause defects in cone cell development. Signals from cone cells play an important role in specification of the primary pigment cell, thus raising the possibility that loss of cone cells may contribute to defective pigment cell development eya regulates cone and pigment cell development.Our analysis of the rare cis regulatory regions of eya that are needed to maintain eya expression immediately anterior and posterior to the MF. We have shown that these enhancers are necessary and sufficient for proper regulation of eya expression during retinal development. Clonal analysis using eya genomic rescue constructs bearing deletions of these enhancers has shown for the first time that loss of eya results in a delay in G1 arrest of retinal progenitors anterior to the MF and a delay in the expression of the proneural protein ato. In addition, our results identify a potential role for eya in cone and pigment cell differentiation and timely degradation of Ci posterior to the MF.In summary, we have identified two new Figure S1A-C. dGFP expression in larval eye discs driven by the 322 bp enhancer at 60 hr and 74 hr AEL (A and C) and the eya-IAM enhancer in a 60 hr eye disc (B). Eye discs were stained for dGFP  and endogenous Eya (red in C). D-E Ocelli of cliIID/CyOeya; GRΔIAMeya (C) and cliIID/Df(eya)eya; GRΔIAMeya (D) animals. Yellow arrowheads indicate the positions of ocelli. F-G Eya expression in third instar eye discs (white in E and F) in 2/CyOeya; GRΔIAMeya (E), and 2/Df(eya)eya; GRΔIAMeya (F). H-J. Adult eye phenotypes of cliIID/CyOeya; GRΔIAMeya (H), cliIID/CyOeya; GRΔPSEeya (I) and 2/Df(eya)eya; GRΔIAMeya (J) animals.(TIF)Click here for additional data file.Figure S2F4-dGFP completely recapitulates the endogenous Eya expression pattern in mid-late third instar eye imaginal discs (A-A′″). dGFP expression (white in A and green in A''') completely overlaps with the endogenous Eya expression (white in A′ and magenta in A''') and the neuronal differentiation marker Elav (white in A″ and red in A'''). Overlap of all three markers is shown in A'''. The F4-dGFP eye disc shown here is the same as the one shown in ΔPSEeya clone is not significantly altered. Eya expression is reduced (white in B′). Merge is shown in B′″. The clones shown here are the same as those shown in C-F. Theeya-PSE enhancer is active in differentiating photoreceptors posterior to the MF. Top panels (C-F) show third instar eye discs from transgenic larva carrying eya-PSE-dGFP. Eye discs were stained for dGFP (C and C′), Elav (D and D′), and Actin (E and E′). The bottom panels show orthogonal views of the same disc. The dotted yellow line in panel D indicates the position of the orthogonal sections.(TIF)Click here for additional data file.Figure S3A-H. RNAi knockdown of so and eya. Third instar eye discs of soRNAi/GMR-Gal4 (A-D) and eya-RNAi//GMR-Gal4 (E-H) stained for So (A and F), Eya (B and E), and Elav (C and G). Although So and Eya expression are clearly reduced in response to their respective RNAi constructs, no obvious change in ELAV expression is observed in either case.(TIF)Click here for additional data file.


Increasing evidence suggests that interactions between regulatory genomic elements play an important role in regulating gene expression. We generated a genome-wide interaction map of regulatory elements in human cells  using Chromatin Interaction Analysis by Paired-End Tag sequencing (ChIA-PET) experiments targeting six broadly distributed factors. Bound regions covered 80% of DNase I hypersensitive sites including 99.7% of TSS and 98% of enhancers. Correlating this map with ChIP-seq and RNA-seq data sets revealed cohesin, CTCF, and ZNF143 as key components of three-dimensional chromatin structure and revealed how the distal chromatin state affects gene transcription. Comparison of interactions between cell types revealed that enhancer–promoter interactions were highly cell-type-specific. Construction and comparison of distal and proximal regulatory networks revealed stark differences in structure and biological function. Proximal binding events are enriched at genes with housekeeping functions, while distal binding events interact with genes involved in dynamic biological processes including response to stimulus. This study reveals new mechanistic and functional insights into regulatory region organization in the nucleus. Since the sequencing of the human genome in 2001, great progress has been made in mapping the location of genes and other regulatory genomic elements. Systematic mapping of transcription factor binding sites and open chromatin regions have uncovered complex regulatory networks revealing mechanisms of gene regulation . HoweverNumerous genomic technologies have evolved to interrogate 3D interactions, each with its own benefits and disadvantages. Virtually all of the experimental methods use cross-linking of chromatin, cleavage of DNA, and proximity ligation of interacting segments to create chimeric fragments of DNA. In the first iteration of this method, chromatin conformation capture (3C), these chimeric fragments were detected via PCR and electrophoresis . In receDespite these advances, many questions regarding the nature of 3D chromatin interactions remain elusive: What factors and combinations of factors are involved in establishing and maintaining long-distance interactions? How do the chromatin states of distal interacting loci effect gene expression? How are these interactions used to regulate different biological functions? Answering these questions requires both a comprehensive map of interactions between regulatory elements and detailed maps of transcription factor (TF) binding, histone modification, and gene expression in the investigated cells.To address these questions, we conducted ChIA-PET experiments targeting six chromosomal proteins/modifications broadly associated with transcriptional regulation in a well-characterized myelogenous leukemia human cell line (K562). The interrogated regions cover the vast majority of open chromatin regions and provide a genome-wide map of long-range interactions between regulatory elements. Through extensive integration with hundreds of available genomic data sets, we characterized the proteins involved in 3D chromosomal organization, the functional impact of interactions, and the general characteristics of distal regulatory networks. To address the function and specificity of these interactions, we also conducted ChIA-PET experiments targeting RAD21 in a well-characterized human lymphoblastoid cell line (LCL) and compared it with RAD21 anchored interactions in K562 cells.Z-score by comparing the interaction frequency to the local mean and standard deviation of interaction frequencies from the rewired data set. Z-scores are calculated for both observed and rewired data sets, which allows interactions to be filtered to a user-defined false discovery rate (FDR). At an FDR of 10% we identified a total of 29,366 confident long-range interactions from the six factors/proteins . The median size of the interacting loci was 3603 bp, while the median distance between two interacting loci was 120,367 bp . Specific information for each data set and each factor can be found in Supplemental Tables S2 and S3.In order to detect regulatory interactions on a global scale, we conducted ChIA-PET in K562 cells using antibodies targeting six broadly distributed DNA binding proteins and histone marks (hereinafter referred to simply as “factors”). The factors include marks of enhancers, promoters, and active regulatory elements  as well as POLR2A and a component of the cohesin complex (RAD21). At least two biological replicate experiments were performed and interactions were scored and filtered using a novel ChIA-PET processing method . This method determines both binding sites and interaction frequencies between any two bound loci. Due to a physical connection through the DNA molecule itself, random interactions occur at a rate that correlates with genomic distance . To accoTo better understand the nature of each interaction, we compared our ChIA-PET results to the extensive list of elements defined by ChIA-PET interactions are highly consistent with interactions determined by both Hi-C and 5C . Genome-P < 0.001) . Within these regions 62.5% of ChIA-PET interactions were also identified by 5C. This overlap is significantly higher than expected (19.2%) based on permutation testing (< 0.001) . Compari< 0.001) . This imComparison of the types of interactions that comprised each data set revealed the similarities and differences between each TF . For exaGiven the agreement between previous interaction studies and the comprehensiveness of the coverage we conclude that our data set represents a genome-wide map of long-range interactions between regulatory elements in K562 cells.To determine which TFs participate in long-range interactions, we intersected our data with binding regions of 102 TFs determined via ChIP-seq by Z-scores relative to interactions where RAD21 was not bound at either end or bound at only one end   . Taken tP ≤ 0.01, Fisher’s exact test with Bonferroni correction) for interactions are shown. RAD21 and CTCF and SMC3 were present at very high percentages in virtually all of the neurons that were enriched for interactions. ZNF143 were in most but not all such neurons. These results underscore the central role of these four factors in establishment or maintenance of (3D) chromatin structure. Several other small clusters are evident including neurons with high percentages of enhancer-related TFs such as EP300 and TEAD4. Another cluster of neurons enriched in interactions is characterized by the presence of AP-1 family (FOS and JUN) proteins which are known as early response transcription factors and are involved in cell proliferation, differentiation, and survival as well as other important cellular events  and that HOT regions had a strong preference to interact with other HOT regions  (Many of the neurons in this plot were characterized by cobinding of many TFs . These nct test) . Taken tPhysical interaction of gene promoters with distal regulatory elements represents an important mechanism of gene regulation. Understanding these interactions requires both mapping the interactions between promoters and distal regulatory elements and assessing their functional significance. Our genome-wide map of regulatory interactions intersected with a broad range of other data sets acquired on K562 cells and other well-characterized cell lines allows us to achieve a detailed understanding of the functional impact of long-range interactions at a level not previously achieved.We first investigated the effect that chromatin state of a distal interacting region had on gene expression . We obseP < 0.05, Fisher’s exact test) (Previous studies have shown that enhancers are highly cell-type-specific compared to other types of regulatory elements . Since oct test) . InteresP = 0.00079, Fisher’s exact test with Benjamini-Hochberg correction). This suggests an expanded role for enhancer–promoter interactions in regulatory networks as they may regulate not only these TFs but also the downstream targets of these TFs. We investigate the role of distal interactions in regulatory networks in greater detail later in this work (vide infra). Many of the TFs whose promoters are involved in interactions with enhancers regulate blood and immune-related functions including hematopoietically expressed homeobox protein (HHEX), nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha (NFKBIA), and interferon, gamma-inducible protein 16 (IFI16)  terms were enriched in genes whose promoters interacted with enhancers. Interestingly, genes corresponding to “transcription factor activity” were highly enriched  .P < 0.01, Wilcoxon signed rank test), indicating that these interactions likely play a regulatory role and are specific to certain cell types. We next compared the percentage of TSS that interacted with each type of distal regulatory element. As shown in P < 0.01, Fisher’s exact test). While enhancers have been known to be the most variable regulatory type, this is the first time a global genomic analysis has demonstrated that enhancer–promoter interactions are more variable than any other type of promoter centered interaction.In order to determine how interactions differed between cell types, we conducted ChIA-PET experiments targeting RAD21 in the well-characterized human LCL GM12878. We then determined differential interactions between the two cell lines while controlling for differences in RAD21 binding . At an FDR of 0.05 we found 1133 differential interactions, 685 and 448 interactions specific to either GM12878 or K562, respectively . Genes wAnother mechanism of transcriptional regulation may involve the compartmentalization of DNA into large domains of active or inactive chromatin . It has been previously shown that boundaries of megabase scale topological domains demarcate transitions from active to inactive chromatin and that CTCF is enriched at these boundaries . In addiGroup 1 is characterized by short interactions, active marks in the anchor regions, and enrichment for TSS–TSS and E–TSS interaction types . This grThese analyses allowed us to create models for each group of interactions . Group 1In total, these findings suggest that long-range chromatin interactions may function in at least two ways to regulate gene expression: (1) by bringing together promoters and distal regulatory elements and (2) by creating large structural domains that harbor functionally related genes that share gene expression patterns.Having established both the quality and functional relevance of these long-range interactions we next constructed and characterized the K562 distal regulatory network using the wealth of binding data in these cells. Comparison of the distal regulatory network to the proximal regulatory network revealed substantial differences in TF-target relationships, hierarchical structure, and network motif usage. Integration of the regulatory information from both networks into a single combined regulatory network provides a comprehensive view of regulatory TF binding in K562 cells.We first compared proximal and distal targets for each of the TFs for which ENCODE TF binding data was available . A totalNext, TF networks were organized into three-tiered hierarchical networks as described by Gerstein and colleagues . The col2 ratio of proximal vs. distal P-value and plotted the ratio as a heatmap . While some TFs, including TAF7 and EZH2, only exhibited proximal enrichment for GO terms, others showed both proximal and distal enrichment. Interestingly, for many such TFs the processes regulated via proximal binding were completely different from those regulated via distal binding. For example, GATA2 regulates “biosynthetic process” and “cell cycle” via proximal binding but “cell differentiation” and “developmental process” via distal binding. Thus, at least some TFs likely mediate different biological processes via proximal vs. distal binding. CTCF and RAD21 tend to regulate the same biological processes via direct and indirect binding, which again highlights their occupancy at both ends of most detected interactions.Combining multiple ChIA-PET data sets, we generated a genome-wide map of interactions between regulatory elements in human cells. Distance-dependent interaction scoring and filtering accurately identified long-range interactions, as confirmed by intersection with previous Hi-C and 5C studies. Analysis of these data sets provided novel insights into 3D chromatin structure, transcriptional regulation, and network wiring, and gives rise to a number of new models of gene regulation.One of the most striking trends observed in this study regards the strong enrichment of CTCF, cohesin, and ZNF143 at interacting loci. These results agree with a study by Comparing the results from these six data sets can help guide future experiments. While each data set revealed factor-specific interactions, the majority of interactions were found in more than one data set . The RAD21 data set revealed more than twice as many interactions as any of the other data sets. Moreover, all data sets revealed strong enrichment of CTCF and cohesin proteins in their anchor regions.HOT regions were enriched at interacting loci and tended to interact with other HOT regions. This finding supports the transcription factory model in which promoters of actively transcribed genes occupy distinct nuclear subcompartments. The strong enrichment for cohesin, CTCF, and ZNF143 at all interacting loci including HOT regions implicates these factors as possible regulators or facilitators of transcription factories.We demonstrated that the chromatin state at distal regulatory regions correlates significantly with gene expression. In addition to bringing together two functional elements, long-range interactions appear to form large loops that coincide with functionally coordinated domains of active and inactive chromatin. While this characteristic is shared with TADs, these loops tend to be substantially smaller and may represent subTAD structures. Further work is required to determine whether these looping events are a cause or result of chromatin boundaries; however, a recent study by Finally, we compared network wiring and architecture between proximal and distal regulatory networks and found substantial differences in TF-target relationships and network hierarchy that were consistent across cell lines. GO analysis revealed that many cell-type-specific and dynamic processes were regulated more by distal than proximal binding of TFs, while more routine biological processes tended to be regulated via proximal binding of TFs. We also show that certain TFs regulate distinct processes via proximal or distal binding.During the preparation of this work, a related study appeared that mapped interactions at high resolution with Hi-C using very deep sequencing . Their sAll ChIA-PET experiments were conducted for this study and are not previously published. K562 (ATCC# CCL-243) cells were grown under standard culture conditions and harvested at log phase. The cells were cross-linked by 1.5 mM EGS for 20 min followed by adding 1% formaldehyde at room temperature for 10 min on a plate rotator and then neutralized with 0.2 M glycine. After a two-step of cell lysis and nuclear lysis with RIPA buffer, chromatin was sheared by BioRuptor 300 to an average size of 500 bp. Sheared chromatin was subjected to overnight Immunoprecipitation by the addition of 50 mg of antibodies. The antibodies used in this study were POLR2A monoclonal antibody 8WG16 , rabbit polyclonal H3K4me1 , rabbit polyclonal H3K4me2 , rabbit polyclonal H3K4me3 (Abcam ab8580), rabbit polyclonal H3K27ac , and rabbit polyclonal RAD21 . Antibodies were coated to the beads using protein G magnetic beads for 2 h and then washed three times to remove nonspecific binding.Immunoprecipitated chromatin fragments were subjected to ChIA-PET library construction following the protocol as previously described . BrieflyZ-scores and allow for FDR estimation. Interactions between any two binding sites were scored and filtered such that no more than 10% of called interactions corresponded to the DMR data set. See Supplemental Information for more details.Paired-end reads were processed to remove linker sequences and aligned to the human genome (hg19) using Bowtie . AlignedDHSs for K562 were intersected with “combined” chromatin state calls via integration of both ChromHMM and Segway outputs as determined by We intersected our interactions with TADs determined by In order to determine overlap with 5C interactions, we intersected our results with those from P-value was ≤0.01, the log2(observed/expected) was greater than 0.35, and if the TF was present in at least 35% of interacting regions. TFs were annotated as weakly enriched if the P-value was ≤0.01 but did not meet the other criteria. If the P-value of enrichment was > 0.01 the enrichment was categorized as “none.”To test for enrichment of TFs at interacting loci, we first intersected CPBS with TF binding sites as determined by ChIP-seq acquired by Self-organizing maps (SOM) were constructed for each of the six ChIA-PET data sets using the R package “kohonen” . The pacP < 0.01) and filtered to include only those with fold enrichment greater than two. For generation of the heatmap in SOMs were made individually for each of the six data sets. Neurons enriched for interactions were determined by Fisher’s exact test with Benjamini-Hochberg correction . Genes were considered cell K562-specific if they were detected with > 10 RPKM in K562 and ≤ 10 RPKM in all other cell lines. Genes were considered broadly expressed if they were detected at > 10 RPKM in all 12 cell lines. Genes were annotated based upon which types of regulatory elements were present at the distal end of an interaction. Categories are not exclusive as gene promoters can interact with multiple different types of regulatory elements. Correlation between cell-type-specific gene expression and interaction with each distal chromatin state was determined using Fisher’s exact test (P < 0.05).Gene expression data for 12 cell lines were downloaded from the ENCODE website  in bam format. Intrachromosomal interactions from all six ChIA-PET data sets were combined. Thirty equally sized genomic bins were generated around each interaction; 10 bins in between the two interacting sites and 10 on either side of the loop. Reads were counted for each histone mark in each bin. Bins were normalized across marks and across interactions as previously described . Edges were constructed from TFs to genes whose promoters to which they were bound. Promoters were determined by extending 5 kb in both directions from the TSS as defined by GENCODE V7 annotations.Proximal regulatory networks were constructed using TF biding peaks for 102 factors in K562 cells downloaded from the ENCODE website  under accession number GSE59395 and to the ENCODE Data Coordination Center (https://www.encodeproject.org/datasets/) under accession number ENCSR727WCB.The ChIA-PET data from this study have been submitted to the NCBI Gene Expression Omnibus  member of Personalis. He is also on the SAB of Genapsys.