CHSY1, we identified a candidate causal variant (rs9920291) overlapping an open chromatin region. Reporter assays demonstrated that rs9920291 shows allelic regulatory activity, and CRISPR/Cas9 targeting of human chondrocytes demonstrates that the region regulates CHSY1 expression. Thus, integrating biologically relevant epigenetic information  with genetic association results can identify biological mechanisms important for human growth.GWAS have identified hundreds of height-associated loci. However, determining causal mechanisms is challenging, especially since height-relevant tissues (e.g. growth plates) are difficult to study. To uncover mechanisms by which height GWAS variants function, we performed epigenetic profiling of murine femoral growth plates. The profiled open chromatin regions recapitulate known chondrocyte and skeletal biology, are enriched at height GWAS loci, particularly near differentially expressed growth plate genes, and enriched for binding motifs of transcription factors with roles in chondrocyte biology. At specific loci, our analyses identified compelling mechanisms for GWAS variants. For example, at  Humans vary considerably in height, a trait that is partly inherited from each individual's parents. Studies have identified hundreds of small changes in DNA that contribute to differences in human height. These small changes often swap out just one of the four letters that make up the DNA code. Some changes occur within genes, yet most occur in stretches of DNA that do not contain genes. These stretches of DNA likely control whether genes important for the growth of the skeleton are switched on or off.Cartilage cells, also known as chondrocytes, are important for height. These cells are found near the end of bones in the growth plates, where the bones grow during childhood and adolescence. The on and off switches for growth genes in chondrocytes are unknown. Identifying these genetic switches could help scientists understand how hundreds of small changes in DNA help determine how tall a person will be.Now, Guo, Liu, Willen et al. identify thousands of switches that turn on and off genes in chondrocytes. In their experiments, chondrocytes were removed from mouse bones and a type of genetic sequencing called ATAC-seq was used to identify the stretches of DNA that act as on/off switches for genes in these cells. Further analysis revealed that many of these same on/off switches occur in human chondrocytes too. Importantly, the experiments showed that many of the small changes in DNA that contribute to differences in human height are also found within these DNA switches.Guo, Liu, Willen et al. next tested how these switches and height-linked genes interact, and found, for example, that one switch acts to shut off the gene for a protein called chondroitin sulfate synthase 1. People with mutations in this gene can have unusually short stature. However, people with DNA changes in its nearby switch can be taller or shorter than average based on how the DNA influences the switch. More studies might help scientists understand the evolutionary significance of these DNA changes. They will also help determine if the genetic switches in chondrocytes contribute to diseases that affect the bones and joints, like bone cancer or arthritis. Human height, a main outcome of skeletal growth, is the product of many biological and environmental interactions spanning numerous cell and tissue types acting during pre- and post-natal development. The growth plate, located at the distal ends of long bones such as the femur, is among the most important tissues influencing height. In the growth plate, condensations of mesenchymal cells differentiate into chondrocytes in the process of endochondral ossification. Chondrocytes in the growth plate reside in longitudinally oriented columns divided in zones  each with important functions in allowing the bone to elongate and mature see . This prHeight has been studied for centuries as a model genetic trait, as it is easily measured and highly heritable  . Height Recently, genome-wide association studies (GWAS) have been used to study the genetics of height, as well as many other traits and disorders . This apHowever, as with all GWAS, moving from genetic associations to biological mechanisms at any individual locus can be challenging. There are two primary reasons for this difficulty. First, there is extensive linkage disequilibrium (LD) in the human genome, meaning that the genotypes at nearby genetic variants are often tightly correlated . The conAlthough the large number of associated variants offers advantages in making biological inferences for the set of associated variants as a whole , defininIn this study, we profile the epigenetic landscape of mouse growth plate chondrocytes using a new approach called ATAC-seq , 2013, wIn order to identify open chromatin regions involved in long bone development, we performed ATAC-seq , 2013 onSince a main goal was to understand the gene regulatory functions of variants influencing human height, we next mapped the locations of each mouse femur open chromatin region to the human genome . Our liftover resulted in 24,805 proximal femur peaks and 24,788 distal femur peaks, representing approximately 87.7% and 88.6% of sites identified in mouse, respectively. These sites that were capable of liftover to human likely reflect relatively conserved genes involved in vertebrate musculoskeletal development . The uniTo determine whether ATAC-seq peaks are enriched near gene sets/pathways with specific functions, we performed an enrichment analysis using Genomic Regions Enrichment of Annotations Tool (GREAT) , which iCol2a1, Fgfr1, and Pth1r   Ohba et. We founWe also wanted to determine if our ATAC-seq peaks reflect regulatory elements involved in human limb development and chondrocyte biology. First, we used a ChIP-seq dataset comprised of H3K27ac peaks found in E47 human limb buds  that are shared with mouse limb buds . We founOur ATAC-seq data were also able to identify 14 of 26 previously-discovered active regulatory elements residing near key cartilage genes detected at different time-points and using different assays e.g. see . This su2 >0.5 to the lead SNP based on the European subset of 1000 Genomes Phase 3  contained at least one variant that overlapped with an ATAC-seq peak. To test the significance of the observed overlap, we applied GoShifter , which performs a shuffling-based approach to evaluate the overlap between an epigenetic data set and GWAS data. We found strong enrichments for the ATAC-seq peak set and height GWAS data (p=0.0059) . We repeTo further demonstrate the specificity of our ATAC-seq peaks for capturing height GWAS signals, we repeated the GoShifter analysis by examining the enrichment of GWAS results for other complex traits/diseases at our ATAC-seq peaks. These other traits/diseases were chosen as they have no obvious connection to height and included age of menarche , body maAs a second approach to evaluate overlap between our ATAC-seq peak set and height GWAS data, we generated 1000 sets of random loci which were matched to the actual height GWAS loci based on factors including SNP density, minor allele frequency, number of proxy SNPs in the locus, and gene density  . For eacNotably, we observed that the actual number of SNPs that overlap an ATAC-seq peak for each set was higher than the number of represented loci. In total, there were 928 variants that overlapped with an ATAC-seq peak; these 928 variants were distributed across 317 loci . This fi2 >0.5 to the lead variant based on the European subset of 1000 Genomes Phase 3  and found that 46/688 loci (or ~6.7%) contained at least one GWAS variant that overlapped with an ATAC-seq peak and resided near a differentially expressed gene , transcription factors (e.g. RUNX2), extracellular matrix factors , among other factors involved in the growth plate in both humans and mice.Of the 46 loci in the ATAC-seq femur comparison that fall near genes differentially expressed in growth plates, 44 different genes have been identified as possibly being modulated by these putative regulatory variants  . These gWe next examined some of the most compelling loci from a genetic and mechanistic perspective. We filtered for loci where a height GWAS variant in the PICS 95% credible set overlapped an ATAC-seq peak, and was near a differentially expressed growth plate gene (±100 kb). In total, 59 variants distributed across 26 loci met these criteria. These 59 variants thus have strong evidence for being potentially causal variants and might be prioritized for downstream study .CHSY1 locus, four variants  met these criteria. Disruption of Chsy1 in mice and humans leads to severe skeletal phenotypes including long bone length reductions   and a 3’UTR SNP (rs11433), we demonstrate that rs9920291 displays allelic skew in expression  . In addiCHSY1, we performed CRISPR-Cas9 targeting of a 135 bp sequence spanning a conserved portion of the regulatory element containing rs9920291 (guides sg1 and sg4), or an 17 bp sequence immediately surrounding rs9920291 (guides sg6 and sg8). Either deletion led to a significant upregulation of CHSY1 expression in vitro in T/C-28a2 cells  at the h plates . We have activity. Thus, oAtf3 . First, we performed a de novo motif analysis on the union of distal and proximal femoral ATAC-seq peaks in mouse to identify enriched transcription-factor-binding motifs. We identified a number of highly enriched motifs relevant to chondrogenesis and other skeletal developmental processes, including Atf3 , Msx2 , will be important factors shaping height variation in humans.While our datasets capture aspects of general chondrocyte biology, we also found that ATAC-seq peaks acquired on femoral tissues show enrichment in human phenotypes related to the anatomy of femur. This finding points to a fine-grained, modularized control of skeletal element-specific biology. This is also supported by our independent identification of a number of previously published long bone growth plate chondrocyte enhancers in mice and humans, as well as the growing evidence that a number of important skeletal development genes, such as Bmp5 , Gdf6  locus. Human mutations in CHSY1 result in Temtamy preaxial brachydactyly syndrome, characterized by short stature, preaxial brachydactyly, and hyperphalangism of digits 1–3 , as well as a number of additional soft and hard tissue disorders. rs9920291 is in the fine-mapped credible set, resides in regulatory elements active in human adult chondrocytes and embryonic limb tissues, and displays evidence of binding by Sox9 in mouse chondrocytes. rs9920291 additionally modifies a critical nucleotide (C to T) and disrupts the experimentally determined in vitro binding motif of HOXD13, a homeodomain transcription factor that is expressed in chondrocytes  resides in the drocytes  and has drocytes . We perflidation .A number of other variants, listed in the browsable All experiments were performed following protocols approved by the Harvard University IACUC committee. Timed matings were established between FVB mice, and pregnant females were euthanized at E15.5 in order to acquire embryonic long bone growth plates. Embryos were dissected in PBS1X on ice under a dissection scope and the proximal and distal growth zones of the right and left femur were stripped clear of soft tissues. Each proximal or distal cartilaginous end was then micro-dissected from the bony diaphysis  and sepaBuenrostro et al., 2015Next, samples were subjected to PCR amplification and barcoding following Buenrostro et al., 2015http://homer.salk.edu/homer/motif/).Sequencing yielded approximately 400 million reads per lane and an average of 100 million per sample. Quality control statistics are presented in Raw sequencing fastq files and processed peak bed files have been deposited on NCBI GEO (GSE100585).http://great.stanford.edu/) were used. GREAT v3.0.0 was used.GREAT (Genomic Regions Enrichment of Annotations Tool)  identifiMouse chondrocyte data: ChIP-seq profiles Sox9 binding in mouse rib chondrocytes was obtained from http://egg2.wustl.edu/roadmap/web_portal/processed_data.html  (ENCSR000COE), liver male adult (8 weeks) (ENCSR000CNI), and lung male adult (8 weeks) (ENCSR000CNM). Processed NarrowPeak bed files were downloaded for each tissue and then lifted over to hg19 as described above.Mouse ENCODE data: DNA-seq data were downloaded from the mouse ENCODE project . All sam2 >0.5 to lead SNP).All intersection analyses of ATAC-seq peaks with GWAS loci, genes, or ChIP-seq peaks were performed using BEDTools v2.18  and custFor overlap of ChIP-seq datasets, any overlap (>=1 bp) was considered to represent the same feature. To evaluate the significance of overlap, a permutation-based procedure was implemented in the R package regioneR . We used2 >0.5 to the index SNP was used. A window size of 100 kb was used to find LD SNPs (‘window’ option). All other parameters were set to the software default. 100,000 permutations were run. GoShifter analyses for additional traits/diseases were performed in the same fashion.GoShifter v0.2 was used to evaluate the statistical enrichment of the overlap between height GWAS loci and ATAC-seq peaks (or other epigenetic peaks) . The Eur2 > 0.5 to the index SNP. Loci were matched using default criteria: MAF ± 5%, gene density ± 50%, distance to nearest gene ±50% and LD buddies ± 50%. SNPSNAP was able to generate matched gene sets for 676 out of the 697 loci from SNPSNAP  was usedA list of 427 differentially expressed mouse genes was downloaded from Using the set of 427 differentially expressed growth plate genes (see above), we identified 157 genes that were also genes for cis-eQTLs in whole blood (FDR < 0.05) as identified by The Genotype-Tissue Expression (GTEx) Project  was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. The data used for the analyses described in this manuscript were obtained from the GTEx Portal on 10/27/2017.ATAC-seq peak centers from proximal/distal tissues were aggregated and padded outwards to a fixed length of 200 bp (based on the distribution of ATAC-seq peak sizes). HOMER  de novo Lifted over human ATAC-seq peaks were then intersected with height GWAS variants from To assess enrichment of predicted transcription factor binding near variants intersecting ATAC-seq peaks, a set of hg19 DNA sequences was first constructed using 30 bp windows centered on each variant, generating an ATAC-intersected subset and whole GWAS superset. A utility from HOMER (findmotifs.pl) was then used to scan this sequence set using its provided vertebrate motif library to search for motif hits. Motifs from JASPAR 2016 were filtered (386 motifs) and counted within each of the two sets. Hypergeometric tests were performed for all motifs using Benjamini-Hochberg FDR correction .CRISPR-Cas9 PX458 vector was obtained from Addgene . pGL4.23 luciferase and pGL4.74 renilla vectors were acquired from Promega . Plasmids encoding HOXD13-FLAG and HOXD13-HA were generously gifted from Dr. Vincenzo Zappavigna (University of Modena and Reggio Emilia) .2 at 37°C in Dulbecco's Modified Eagle's Medium (DMEM), 10% fetal bovine serum (FBS), and 1% penicillin-streptomycin (P/S). Media was replaced every 2–3 days and the cells were sub-cultured every 5 days.Human embryonic kidney (HEK-293FT) cells were acquired from Dr. Pardis Sabeti (Harvard University and Broad Institute). T/C-28a2 human chondrocyte cells were acquired from Dr. Li Zeng (Tufts University) courtesy of Dr. Mary Goldring . Both cell lines were cultured at 5% COCHSY1 regulatory element or rs9920291 were designed using MIT CRISPR Tools (http://crispr.mit.edu), synthesized by Integrated DNA Technologies, Inc , and cloned into the PX458 vector following published protocols  with a modification efficiency of approximately 10% and smaller CHSY1 regulatory region around rs9920291  with a modification efficiency of approximately 8.5%. RNA was also extracted from control and CRISPR-Cas9 targeted T/C-28a2 cells. RNA was DNase-treated and converted to cDNA for qPCR (see below).After confirmation that sgRNAs worked in HEK-293FT cells, we performed in vitro deletion in the T/C-28a2 chondrocyte cell line . The samTotal RNA was extracted from HEK-293FT and T/C-28a2 cells and prepared using the Trizol Reagent  and Direct-zolTM RNA Miniprep kit (ZYMO). Three micrograms of total RNA were used to synthesize first-strand cDNA using SuperScript III First-Strand Synthesis System (Thermo Fisher Scientific). qRT-PCR analysis was then performed with specific primers and Applied Biosystems Power SYBR master mix (Thermo Fisher Scientific) with GAPDH as a reference gene. Primers used for qRT-PCR are listed in CHSY1 regulatory sequences into HEK-293FT and T/C-28a2 cells (see below), primers containing KpnI/HindIII linker sequences were used to amplify the putative regulatory element surrounding rs9920291.  at a Lipofectamine:DNA ratio of 4:1 according to manufacturer instructions. Luciferase activity was measured 48 hr after transfection using the 96-welll Dual-Glo Luciferase Assay System (Promega E2940) following manufacturer protocols on a SpectraMax L Microplate Reader  with a 1 min dark adapt, 5 s integration, and max range settings. For cell culture experiments, to compare expression between the reference and alternate allele CHSY1 constructs (HEK-293FT cells and T/C-28a2 chondrocytes were passaged using standard conditions (see above) prior to reporter gene transfection and HOXD13 over-expression experiments. Prior to transfection, cells were first cultured in DMEM with 10% FBS for 24 hr in 96-well dishes at a seeding density of 3 × 10nstructs , we perfhttp://hek293genome.org/v2/) that HEK-293FT cells were heterozygous at rs9920291, unlike T/C-28a2 cells which were homozygous for the reference C allele. Thus, only HEK-293FT cells could be used for allele-specific expression. Next, using the HEK-293 browser with follow-up verification using Sanger sequencing, we identified two heterozygous transcript variants (exon 3 coding variant [rs28364839] and 3’UTR variant [rs11433]).Both HEK-293FT cells and T/C-28a2 chondrocytes were screened using Sanger sequencing to identify genotype rs9920291. Sanger sequencing results confirmed preliminary findings using the HEK-293 browser . Samples were then run on a bioanalyzer to achieve RNA Integrity Numbers greater than 8. These RNA samples were then reverse transcribed using a SuperScript IV First Strand cDNA Synthesis Reaction kit  following manufacturer’s recommendations.For allelic skew analyses on untreated HEK-293FT samples, five independent biological replicates were grown and harvested. RNA was isolated separately from each sample using the Trizol Reagent  and the RNA Clean and ConcentratorCHSY1 (rs11433 and rs28364839), were validated by EpigenDx . Pyrosequencing for SNP genotyping  is a real-time sequencing-based DNA analysis that quantitatively determines the genotypes of single or multiple mutations in a single reaction. Briefly, 1 ng of sample cDNA was used for PCR amplification. PCR was performed using 10X PCR buffer  at 3.0 mM MgCl2, 200M of each dNTP, 0.2 µM each of the forward and reverse primers (available through EpigenDx), and 0.75 U of HotStar DNA polymerase (Qiagen Inc.), per 30 µl reaction. PCR cycling conditions were: 94°C 15 min; 45 cycles of 94°C 30 s; 60°C 30 s; 72°C 30 s; 72°C 5 min. One of the PCR primer pairs was biotinylated to convert the PCR product to single-stranded DNA sequencing templates using streptavidin beads and the PyroMark Q96 Vacuum Workstation. Ten microliters of the PCR products were bound to streptavidin beads and the single strand containing the biotinylated primer was isolated and combined with a specific sequencing primer (available through EpigenDx). The primed single stranded DNA was sequenced using the Pyrosequencing PSQ96 HS System (Qiagen Pyrosequencing) following the manufacturer’s instructions (Qiagen Pyrosequencing). The genotypes of each sample were analyzed using Q96 software AQ module (Qiagen Pyrosequencing). Pyrosequencing results for each CHSY1 exonic or 3’UTR SNP were used to calculate the allelic ratios in the heterozygous state.cDNA samples were then sent to EpigenDx for allelic skew analysis assay design and execution. SNPs in the coding regions of For regulatory element transfection experiments, CRISPR-Cas9 deletion experiments, and HOXD13 over-expression experiments, the means ± SEM of multiple independent measurements were calculated. The unpaired two-tailed Student’s t test was used to determine the significance of differences between means. P values smaller than 0.05  were considered to be statistical significant.CHYS1 we used UniProbe (http://the_brain.bwh.harvard.edu/uniprobe/browse.php) and identified the corresponding z-score for each 8-mer.To find upstream transcription factors (TF) predicted to bind at rs9920291 near UniProbe . UniProbUniProbe . For twoUniProbe . To idenhttp://genome.ucsc.edu/cgi-bin/hgVisigene), Eurexpress (http://www.eurexpress.org/ee/), Genepaint (http://www.genepaint.org/Frameset.html), and the Mouse Genome Informatics expression and phenotypic databases (http://www.informatics.jax.org). HOXD13 met the above criteria. HOXD13 had enrichment scores below the recommended UniProbe threshold of 0.4 for the REF sequence but much higher (above 0.4) for the ALT sequence, and this corresponded to a significant change in z-score  and three reviewers, one of whom is a member of our Board of Reviewing Editors.Thank you for submitting your article "Epigenetic profiling of growth plate chondrocytes sheds insight into regulatory genetic variation influencing height" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:All the reviewers were enthusiastic about your comprehensive generation of epigenetic data for the growth plate and the potential utilization for future studies on genetic regulatory regions. The ATAC-seq approach and the overlay of GWAS data will provide significant insights into murine and possibly human growth determinants.There were three major concerns that need to be addressed before a final decision can be made.First delineation of sex from the E15.5 murine chondrocytes and justification for the E15.5 time point are essential for understanding the framework for growth variants and for future studies by other investigators.Second, the manuscript still lacks a strong connection to chondrocyte biology as none of the links established by the data directly address (or explain) chondrocyte proliferation or hypertrophy and genes well known to regulate them positively or negatively .Third, although different genes have been identified as possibly being putative regulatory variants there are no experimental or computational evidence implicating the ATAC-seq peaks in regulating the nearby growth plate genes, nor altering transcriptional regulatory activity.These issues underlie a perception that, independent of your Nature Genetics paper, there is a lack in this manuscript of mechanistic evidence that the epigenomic profiles can be linked to functional correlates. For example, there is a suggestion that rs9920291 disrupted HOXD13 binding, but there is no evidence that HOXD13 actually binds this site at the endogenous locus. As computationally predicted TF motifs are prevalent in the genome, it is hard to assess whether this SNP/motif overlap is biologically meaningful. This requirement for a mechanistic/functional connection may require additional work.These major points will need to be addressed in the revision along with several other points imbedded in the three reviewers’ comments that have been included below in the comments, and should be considered carefully.Reviewer #1:In this paper, Capellini and colleagues utilize a novel method (ATAC-seq) to read the open chromatin regulatory landscape of growth plate chondrocytes in neonatal mice. They were then able to analyze height GWAS data in the context of femur growth to gain new insights into how height GWAS variants act at the growth plate. Briefly they showed that ATAC-seq datasets generated from mouse growth plate chondrocytes overlap with previously identified signals of chondrocyte biology in the mouse, as well as in humans. They identified locations of active regulatory enhancers and Sox9 binding sites as assessed using ChIP seq on mouse rib chondrocytes and provided datasets that overlap with evidence of regulatory control during chondrogenesis and human limb embryogenesis. Their work is a nice supplement to their Nature Genetics paper identifying an ancestral regulatory variant in 'Grow'1 enhancer in mouse limbs that also affects human chondrocyte biology. Finally, the authors detected a variant in the chondroitin sulfate synthase 1 gene which might influence binding of HOXD13, a trans acting regulator of chondrocyte growth.Strengths: There are several strengths to this paper: First the authors were able to provide very comprehensive data sets on the epigenetic landscape of mouse, and human chondrocytes, an important breakthrough in an otherwise very difficult organ to characterize. Second, they have provided evidence that these regions are critically important for growth of the chondrocyte and thus provide support from previous studies of candidate genes in chondrogenesis such as GDF5, 6, Bmp5 etc. that others have defined. Third they have been able to overlay height GWAS variants that are also significantly enriched in growth plate chondrocyte regulatory regions, particularly for those that are intergenic. Finally, this is state of the art technology in epigenetics; i.e. the use of ATAC methodology, importantly it requires fewer chondrocytes to peruse the chromatin landscape thus breaking new ground.Limitations: – there are some concerns that need to be fully addressed:1) The authors used E15.5 embryos from FVB mice to study the epigenetic regions for growth plate regulation. But inbred strains often exhibit numerous nucleotide variants; since C57BL6J mice are the most frequently utilized strain for in vitro and in vivo chondrocyte (and osteoblast) studies, have the authors determined whether the specific nucleotide sequence in the CHYS1 variant, rs9920291, is also present in B6 mouse chondrocytes?2) Sex is a major determinant of height particularly early in life and during puberty. The early influences of sex steroids likely begins during late embryonic development; i.e. after E11.5 when SRY is expressed in the males, but not females. It would be important to fully understand the epigenetic landscape in respect to sex differences in vivo. Hence, the embryos should have been typed for sex, and both male and female embryos should be examined to more fully understand the transcriptional regulation of chondrocyte differentiation.3) Can the authors justify why they did not follow up with functional studies on the CHYS1 variant rs9920291 which they identified as being a cis acting site for HOXD13.4) Reviewer #2:In this study, the authors have performed epigenetic profiling of active chromatin regions in E15.5 mouse embryo femurs to establish possible links with GWAS variants associated with human height previously described by other groups. The regions were found to positively associate with known genes regulating chondrocyte and skeletal biology, particularly those encoding growth plate transcription factors. These and other data lead the authors to conclude that integration of epigenetic information with genetic association data can identify mechanisms important for human height.The study comes from a research group with recognized expertise in genetics and genomics and for important contributions to the field. It also addresses human height that can be severely affected by congenital conditions, thus introducing an element of translational medicine relevance to the work. The extensive data combining epigenetic profiling using ATAT-seq with several bioinformatics and analytical tools provide a wealth of possible links with specific genes and transcriptome data sets from previous studies. Despite these positive assets, the study raises several concerns.While the study is technically strong, it is deficient in skeletal cell and developmental biology, raising questions about the major conclusions reached and specific relevance to human height.The growth plate is certainly the key structure determining long bone and vertebral elongation and thus, body height. It is clearly established that the rates of skeletal growth are determined by chondrocyte proliferation (minor contribution) and chondrocyte hypertrophy (major contribution) in the growth plate. It is also well established that different growth plates within the same organism at any given time "grow" at very different rates, such as proximal and distal growth plates in radius and ulna. None of the links established by the data presented here directly address (or explain) chondrocyte proliferation or hypertrophy and genes known to regulate them positively or negatively . The only links established are to general aspects of chondrocyte and skeletal biology, thus making it very difficult to understand how the links have anything to do with "height". The behavior of the growth plate is controlled by intrinsic mechanisms (see above) as well as systemic factors such as growth hormone. Again, none of the links related to this or other systemic cues.The authors made use of the proximal and distal portions of E15.5 mouse embryo femur and associated perichondrium as starting material for the epigenetic analysis. The tissues were digested into single cell suspension enzymatically before processing for ATAT-seq. There is no explanation of why this developmental stage was chosen and why both ends of the femur were considered. Also, the lengthy enzymatic digestion could have altered gene expression and chromatin configuration.To establish stronger links, the authors considered the most compelling GWAS variants overlapping ATAT-seq peaks, finding 59 variants distributed over 26 loci. The two examples mentioned are CHSY1 and HOXD13 neither of which has established roles in growth plate function. Indeed, most evidence indicates that HOXD13 regulates autopod skeletal patterning and morphogenesis, but not rates of growth.The authors make a strong case that the data can provide insights into the meaning and functional relevance of GWAS correlations, but I do not see how they provide any direct insights into what regulates human height. It may be worth considering an overall change in rationale for the study.Reviewer #3:The article by Guo et al. describes the epigenetic profiling of mouse growth plate chondrocytes to elucidate potential molecular mechanisms through which genetic variants contribute to human height. The authors perform ATAC-seq profiling to identify open chromatin regions from murine femoral growth plates and demonstrate that femur open chromatin are (i) enriched nearby skeletal development genes, and (ii) enriched for human height GWAS loci, above other epigenomic datasets available from mouse and human. While it has previously been shown that height GWAS loci are enriched nearby musculoskeletal genes . Given that r2>0.5 is not a strict LD threshold , is it still meaningful to report overlap statistics using the r2>0.5 set when the PICS 95% credible set is available?1) Substantially fewer GWAS loci overlap ATAC-seq peaks when using the fine-mapped 95% credible variants, instead of all SNPs with r2) The authors state "44 different genes have been identified as possibly being modulated by these putative regulatory variants". However, in the present manuscript the authors do not provide experimental or computational evidence implicating the ATAC-seq peaks in regulating the nearby growth plate genes, and provide limited evidence that any of these overlapping variants can alter transcriptional regulatory activity.3) Following point #2, and to support the authors' claim of identifying "prime targets for functional testing", it would be helpful to know how many GWAS SNP overlaps with femur open chromatin regions the authors believe to be biologically meaningful versus coincidence.4) Similar to point #2, it is premature to state "59 variants thus have strong evidence for being potentially causal variants". For the authors' example of the CHSY1 locus, while there are 4 SNPs in the PICS 95% set that overlap an ATAC-seq peak nearby CHSY1, 5) Subsection “Known and novel targets of human height variants in putative chondrocyte regulatory regions”, first paragraph: The authors suggest rs9920291 disrupts HOXD13 binding, but do not provide evidence that HOXD13 actually binds this site at the endogenous locus. As computationally predicted TF motifs are prevalent in the genome, it is hard to assess whether this SNP/motif overlap is biologically meaningful.6) Wood et al. (2014) found that height GWAS loci were more likely to be eQTLs (in blood) for genes expressed in cartilage. Did the authors examine whether the 468 credible SNPs overlapping femur open chromatin peaks are enriched for eQTL signals? This analysis may strengthen the authors' mechanistic claims. […] There were three major concerns that need to be addressed before a final decision can be made.First delineation of sex from the E15.5 murine chondrocytes and justification for the E15.5 time point are essential for understanding the framework for growth variants and for future studies by other investigators.We thank the Reviewing Editor for summarizing these two main concerns and address each below separately.While we agree that sex is a major determinant of height in humans particularly during puberty, our method of cell collection for ATAC-seq is not yet conducive to examining this aspect of biology. We have optimized our protocol to acquire large numbers of viable chondrocytes that have not been removed from their in vivocontext for extended periods of time.First, we perform our ATAC-seq on freshly acquired chondrocytes, extracted from the embryonic growth plates, and we must pool embryonic long bone ends across a litter to collect enough for each specific growth plate end . In the process, any significant delay in extraction can significantly impact chromatin state, as the cells are no longer fresh and instead are subjected to prolonged exposure to artificial media and in vitro conditions. Genotyping for sex constitutes a major delay in the process.Second, we perform our ATAC-seq on E15.5 embryos, a stage when sex differences are not readily apparent in the lengths of the skeletal elements . However, we intentionally chose E15.5 for a number of reasons (see next point below), most notably our ability to easily extract large numbers of viable chondrocytes from the limited extracellular matrix environment using a brief collagenase digestion step (<2 hours). Our current attempts to extract chondrocytes at much later stages  require at least 12 hours of collagenase digestion, but result in an increased ECM content that interferes with ATAC-seq and more importantly a significant increase in cell death (>25%), which results in low quality and biased ATAC-seq libraries. In addition, the prolonged duration of exposure to collagenase and artificial media in vitro that comes hand-in-hand with studying these later stages likely impacts chromatin profiles. In time, when chondrocyte extraction techniques improve, we plan to extract chondrocytes from single early post-natal mice, genotype each embryo for sex while we perform ATAC-seq, and explore sex-specific differences in growth plate chondrocyte chromatin biology.We chose E15.5 as a stage to explore chondrocyte growth plate biology for a number of reasons:First, growth plates at this stage show a very limited amount of extracellular matrix, which can interfere with the ATAC-seq protocol. For example, extensive extracellular matrix, characteristic of later fetal and post-natal stages, requires long periods of collagenase digestion  to isolate chondrocytes, which in turn has a significant impact on the nature of open chromatin profiles in the resultant extracted cell populations. Increased collagenase digestion also increases cell death which also influences chromatin state biology.Second, growth plates are readily dissected at E15.5 since soft tissues, such as tendon, ligament, and muscle, strip easily off the growth plate using simple mechanical force rather than enzymatic digestions that can alter chromatin state profiles. At later stages, increased enzymatic concentrations and processing times, as well as more mechanical force are necessary to strip soft tissues off of growth plates, and the effects of these treatments on ATAC-seq libraries remainproblematic and unclear.Third, growth plates at E15.5 display all major chondrocyte differentiated cell types  and at the same time lack evidence in and around the epiphysis of secondary ossification center formation. Thus, we when we extract at this stage, we are less concerned about introducing additional cell types .Fourth, we chose to separate both long bone ends because the growth plates of the proximal and distal femur mature at different stages and under different processes, with the former undergoing complex chondrogenesis and osteogenesis patterns not evident in the latter , and because proximal and distal growth plates show evidence of differential growth across a number of species, including humans. Thus, by separating growth plates, we are able to identify ATAC-seq peaks unique to each region and likely important for the marked distal femur elongation seen in humans.Second, the manuscript still lacks a strong connection to chondrocyte biology as none of the links established by the data directly address (or explain) chondrocyte proliferation or hypertrophy and genes well known to regulate them positively or negatively .Col2a1 (encoding a collagen subunit), Pth1r (parathyroid hormone receptor), and Fgfr1 (fibroblast growth factor)new . Our GREctor)new . We now Third, although different genes have been identified as possibly being putative regulatory variants there are no experimental or computational evidence implicating the ATAC-seq peaks in regulating the nearby growth plate genes, nor altering transcriptional regulatory activity.CHSY1 locus.We thank the reviewers for their suggestions of including experimental validation. To this end, we have included a variety of experiments aimed at validating our experimental predictions at the 1) First, using a luciferase reporter assay, we demonstrated that rs9920291 demonstrates allelic regulatory activity in the T/C-28a2 human chondrocyte cell line new .CHSY1 expression. We chose to use HEK-293FT because it is heterozygous “C/T” for rs9920291. We had genotyped several human chondrocyte cell lines, and unfortunately they were all homozygous “C” for this variant (new CHSY1 in human transformed fibroblasts (new 2) Using a human cell line (HEK-293FT), we demonstrate that there is allelic skew in iant new . This isasts new .CHSY1 expression, suggesting that rs9920291 marks a regulatory element with repressive activity (new 3) Next, we used two separate pairs of CRISPR guide RNAs to delete the region surrounding rs9920291 in the T/C-28a2 cell line. We deleted either a large 135 bp region, or a smaller 17 bp region. Deletion of either region enhances vity new .CHSY1 expression, providing evidence to support our computational predictions that HOXD13 may bind at the open chromatin region marked by rs9920291 and regulate CHSY1 expression (new 4) Finally, we demonstrate that overexpression of HOXD13 can increase sion new .GDF5 from our group) with experimental validation, again highlighting the novelty of our paper.Together, we believe these new results provide strong evidence that our approach can pinpoint plausible candidate causal GWAS variants. Additionally, to our knowledge, this is one of the few height GWAS loci  The authors used E15.5 embryos from FVB mice to study the epigenetic regions for growth plate regulation. But inbred strains often exhibit numerous nucleotide variants; since C57BL6J mice are the most frequently utilized strain for in vitro and in vivo chondrocyte (and osteoblast) studies, have the authors determined whether the specific nucleotide sequence in the CHYS1 variant, rs9920291, is also present in B6 mouse chondrocytes?Thank you for raising this important point regarding mouse strains and the potential for there to be genetic and epigenetic differences across strains. We chose the FVB strain for this study given the consistently large number of embryos that the FVB strain produces, which allowed us to increase the number of mice from which we could collect difficult to extract tissue. We also wish to clarify that rs9920291 is a human variant that, to our knowledge, is not present in mouse. We note that the reference “C” allele is the ancestral allele that is present on the mouse sequence.2) Sex is a major determinant of height particularly early in life and during puberty. The early influences of sex steroids likely begins during late embryonic development; i.e. after E11.5 when SRY is expressed in the males, but not females. It would be important to fully understand the epigenetic landscape in respect to sex differences in vivo. Hence, the embryos should have been typed for sex, and both male and female embryos should be examined to more fully understand the transcriptional regulation of chondrocyte differentiation.Thank you for raising this important point regarding sex of the mice used for analyses. We have addressed this point in our response to the Editor’s first comment (see above).3) Can the authors justify why they did not follow up with functional studies on the CHYS1 variant rs9920291 which they identified as being a cis acting site for HOXD13.CHSY1. We describe the new experiments we have performed in our response to the Editor’s third comment (see above).As suggested by multiple reviewers, we have pursued functional studies of our candidate causal variant rs9920291 at 4) GDF5 experiment from our paper. Additionally, we have moved the epigenetic view of the GDF5 locus to the new We thank the reviewer for this comment. We wish to clarify that the lacZ reporter used in this paper is from a stable line, and thus different from the original Nature Genetics paper. Given that the results are very similar, we have decided to remove the Reviewer #2:[…] While the study is technically strong, it is deficient in skeletal cell and developmental biology, raising questions about the major conclusions reached and specific relevance to human height.Thank you for your careful review of our manuscript. We are pleased that you found our paper “technically strong” and with “positive assets”. Below, we address the criticisms that you raise. We hope that our revised manuscript and new experiments address these gaps and make our manuscript suitable for publication.The growth plate is certainly the key structure determining long bone and vertebral elongation and thus, body height. It is clearly established that the rates of skeletal growth are determined by chondrocyte proliferation (minor contribution) and chondrocyte hypertrophy (major contribution) in the growth plate. It is also well established that different growth plates within the same organism at any given time "grow" at very different rates, such as proximal and distal growth plates in radius and ulna. None of the links established by the data presented here directly address (or explain) chondrocyte proliferation or hypertrophy and genes known to regulate them positively or negatively . The only links established are to general aspects of chondrocyte and skeletal biology, thus making it very difficult to understand how the links have anything to do with "height". The behavior of the growth plate is controlled by intrinsic mechanisms (see above) as well as systemic factors such as growth hormone. Again, none of the links related to this or other systemic cues.Ihh, Pth1r, and Fgfr1. We believe that these revisions help more directly connect our data to chondrocyte biology.Thank you for raising these points about linking our epigenetic data with biological insights into chondrocyte and skeletal biology. In our revision, we have included several improvements to strengthen the connection between our ATAC-seq data and chondrocyte biology. First, we revised our GREAT analysis by removing ATAC-seq peaks that are also seen in the mouse brain. By doing so, we are limiting ourselves to more chondrocyte-specific regions. When repeating the GREAT analysis, we find many chondrocyte-relevant gene sets, such as “Cartilage condensation”, “Positive regulation of chondrocyte differentiation”, and “Chondrocyte proliferation”. Second, we have included an additional figure new  where weThe authors made use of the proximal and distal portions of E15.5 mouse embryo femur and associated perichondrium as starting material for the epigenetic analysis. The tissues were digested into single cell suspension enzymatically before processing for ATAT-seq. There is no explanation of why this developmental stage was chosen and why both ends of the femur were considered. Also, the lengthy enzymatic digestion could have altered gene expression and chromatin configuration.Thank you for raising this important point regarding our choice of using E15.5 embryos. We have addressed this point in our response to the Editor’s first comment (see above).To establish stronger links, the authors considered the most compelling GWAS variants overlapping ATAT-seq peaks, finding 59 variants distributed over 26 loci. The two examples mentioned are CHSY1 and HOXD13 neither of which has established roles in growth plate function. Indeed, most evidence indicates that HOXD13 regulates autopod skeletal patterning and morphogenesis, but not rates of growth.CHSY1 as one example relevant to both human height and human health, as it has previously published roles in chondrocyte biology and mutations in CHSY1 cause a variety of skeletal dysplasias (see main text). We identified HOXD13 as a potential transcriptional regulator of CHSY1 at the rs9920291 enhancer variantusing the UniProbe Database . While it is well-known that Hoxd13 plays important roles in autopod patterning, it is also expressed in growth plates  and has been known for some time  to be growth promoting factor . As Hox proteins act redundantly during limb bud development and growth plate function, deciphering the specific functions of Hoxd13 or its targets has been extremely difficult. However, our newly added data reveal that HOXD13 is expressed in chondrocytes and can increase CHSY1 expression when overexpressed in chondrocyte cell lines  may act to influence human height. Unfortunately, despite claiming the identification of "compelling mechanisms for GWAS variants" (Abstract), the authors do not provide sufficient experimental or computational evidence in support, except for rs4911178 that references data in Capellini et al. 2017 (PMID 28671685). In summary, the authors present an important epigenomic dataset that can act as a first step for future study of height GWAS SNPs, but do not provide "strong evidence"  for compelling mechanisms at any height GWAS loci beyond referencing their previously published paper.CHSY1 locus. We have also made many other changes and performed new experiments as suggested by the reviewer.We thank the reviewer for his/her careful review our paper and are pleased that the reviewer recognizes the value of our work. To strengthen our connections between ATAC-seq peaks at GWAS loci with biological mechanisms, we now provide extensive functional work at the 2>0.5 . Given that r2>0.5 is not a strict LD threshold , is it still meaningful to report overlap statistics using the r2>0.5 set when the PICS 95% credible set is available?1) Substantially fewer GWAS loci overlap ATAC-seq peaks when using the fine-mapped 95% credible variants, instead of all SNPs with r2>0.5 is not a universally agreed upon LD threshold. We have now included GoShifter analyses at several different r2thresholds ranging from 0.2 to 0.8 (new 2 cutoff of 0.5 demonstrated the strongest enrichment (p=0.0059).We thank the reviewer for raising these important points regarding proxy SNPs at GWAS loci. We agree with the reviewer that r 0.8 new . Among t2>0.5 in our new The reviewer makes an excellent point regarding whether we should just report PICS credible set overlaps. While the reviewer’s point is valid and well-taken, we have decided to be more inclusive in our approach and report both PICS overlaps and variants overlaps with r2) The authors state "44 different genes have been identified as possibly being modulated by these putative regulatory variants". However, in the present manuscript the authors do not provide experimental or computational evidence implicating the ATAC-seq peaks in regulating the nearby growth plate genes, and provide limited evidence that any of these overlapping variants can alter transcriptional regulatory activity.CHSY1 locus.Thank you for this comment. We now provide evidence that differentially expressed growth plate genes that are also eQTLs genes in whole blood are enriched at ATAC-seq peaks (see response to point #6). Additionally, as detailed in our response to the Editor’s third comment, we now provide extensive experimental evidence for rs9920291 as a causal variant at the 3) Following point #2, and to support the authors' claim of identifying "prime targets for functional testing", it would be helpful to know how many GWAS SNP overlaps with femur open chromatin regions the authors believe to be biologically meaningful versus coincidence.CHSY1 locus to demonstrate the value of our approach.We thank the reviewer for raising this important point. Unfortunately, without a “truth” set, it is difficult to evaluate what proportion of our nominated SNPs are likely to be biologically meaningful as opposed to coincidence. However, we do note that using both GoShifter and random matched GWAS loci, we detect very strong enrichments of our height GWAS SNPs at ATAC-seq loci, suggesting that a large proportion of our nominated SNPs are meaningful. We also point out the work of Ulirsch et al., Cell, 2016, which performed MPRA for red blood cell traits and demonstrated that a large proportion of variants nominated by similar approaches as used in our paper demonstrated functional activity in the MPRA assay. As an additional approach to demonstrate that our observed overlaps are not simply coincidence, we also performed GoShifter analyses for enrichments of GWAS associations of several traits  at our ATAC-seq peaks. For most of these additional traits, we did not detect significant associations (p>0.05) of enrichment new . Lastly,4) Similar to point #2, it is premature to state "59 variants thus have strong evidence for being potentially causal variants". For the authors' example of the CHSY1 locus, while there are 4 SNPs in the PICS 95% set that overlap an ATAC-seq peak nearby CHSY1, CHSY1, intersection with ATAC-seq data prioritized the 87 SNPs in the 95% credible set down to just four variants. In our revision, we now provide extensive functional evidence for rs9920291, providing further credence for our claim that our approach can nominate likely causal variants  Subsection “Known and novel targets of human height variants in putative chondrocyte regulatory regions”, first paragraph: The authors suggest rs9920291 disrupts HOXD13 binding, but do not provide evidence that HOXD13 actually binds this site at the endogenous locus. As computationally predicted TF motifs are prevalent in the genome, it is hard to assess whether this SNP/motif overlap is biologically meaningful.CHSY1 , there are limited ChIP-seq datasets in relevant tissues to assess whether HOXD13 truly binds at rs9920291, in part because of the known difficulty of generating and using HOXD13-specific antibodies for ChIP-seq. We have toned down the language in the manuscript regarding this HOXD13 connection . Additionally, we do now provide evidence that overexpression of HOXD13 increases expression of HSY1 new .6) Wood et al. (2014) found that height GWAS loci were more likely to be eQTLs (in blood) for genes expressed in cartilage. Did the authors examine whether the 468 credible SNPs overlapping femur open chromatin peaks are enriched for eQTL signals? This analysis may strengthen the authors' mechanistic claims.We thank the reviewer for this excellent suggestion. We have now included additional analyses, which confirm the observation in Wood et al., that height GWAS loci are more likely to be eQTLs in blood for genes expressed in cartilage. To do this, we used a set of eQTLs from whole blood from Westra et al., 2014 and subsetted for eQTLs genes that are differentially expressed in the growth plate. We then ran GoShifter on this set of corresponding eQTLs variants and indeed detected a significant enrichment when compared with our ATAC-seq peaks (p=0.0004). This is discussed in the third paragraph of the subsection “A subset of human height variants in femoral open chromatin regions reside near genes 261 differentially expressed in the growth plate”.


IL2RA gene on transcriptional regulation. This polymorphism is associated with multiple autoimmune conditions . Analysis in silico suggested significant difference in the affinity of estrogen receptor (ER) binding site between alternative allelic variants, with stronger predicted affinity for the risk (G) allele. Electrophoretic mobility shift assay showed that purified human ERα bound only G variant of a 32-bp genomic sequence containing rs12722489. Chromatin immunoprecipitation demonstrated that endogenous human ERα interacted with rs12722489 genomic region in vivo and DNA pull-down assay confirmed differential allelic binding of amplified 189-bp genomic fragments containing rs12722489 with endogenous human ERα. In a luciferase reporter assay, a kilobase-long genomic segment containing G but not A allele of rs12722489 demonstrated enhancer properties in MT-2 cell line, an HTLV-1 transformed human cell line with a regulatory T cell phenotype.We studied functional effect of rs12722489 single nucleotide polymorphism located in the first intron of human  New technologies, modern computational capacities and collection of large study populations through international collaboration brought new hope for understanding the mechanisms of complex diseases with strong genetic component . Genome-State-of-the-art approach to finding candidate SNPs for functional studies includes successive filtering by several criteria: (i) localization in the vicinity of relevant genes; (ii) mapping to genomic regions with regulatory properties such as DNase I accessibility, evolutionary conservation, appropriate epigenetic signature, ChIP-Seq-confirmed binding of transcription factors; (iii) correlation of SNP haplotype with expression levels of candidate genes. However, such algorithm inevitably filters out many SNPs and may lead to under-recognition of actual causative polymorphisms.FTO locus SNPs and IRF3 expression  vis visIL2RAcsc.edu, ). It incpression .IL2RA expression [We tested our reporter constructs in two cell lines, Jurkat and MT-2. Jurkat is a T cell leukemia-derived cell line that retains its original T-helper properties with regard to surface antigen expression and inducibility of the IL-2/IL-2Rα positive feedback loop . MT-2 ispression .−9 to 10−6 M was added 24h later. Luciferase signal was assessed 18h after E2 addition. As a control for adequate estrogen induction and the presence of functional ER in MT-2 cells, part of the cells in each experiment were transfected with a highly estrogen-responsive control ERE-LUC vector which gave dose-dependent induction. In this experimental system, 1 kb (G) did not demonstrate enhancer properties in the absence of E2 whereas addition of estrogen at 10−9–10-6M resulted in up to 1.5-fold increase in luciferase signal. The A variant of the 1 kb sequence had no effect on luciferase expression regardless of the E2 presence in culture medium  [International Multiple Sclerosis Genetics Consortium initially reported rs12722489 as the strongest MS-associated SNP in the  in 2007 . Yet, th = 0.56) . Later s = 0.56) –38, whil = 0.56) , 40, and = 0.56) . Variant = 0.56)  although = 0.56) .Concurrently, strong association of rs12722489 with Crohn's disease was reported . InteresThus, different GWASs give confusing information on the significance of a given polymorphism and this makes complementary analytical tools for identification of candidate SNPs (such as transcription factor binding site prediction) even more important.Analysis using PERFECTOS-APE software showed that rs12722489 was located in a very conservative position of a putative ER binding site  and G toIL2RA gene encodes CD25 protein which represents α subunit of the high-affinity IL-2 receptor. The high affinity IL-2 receptor is best known for its role in T cell development and function. CD25 is constitutively expressed at high levels by CD4+ Foxp3+ Tregs and is induced on naïve and memory T cells upon antigen stimulation [The mulation . It can mulation , 14. Othmulation –54, actimulation  and actimulation , 57. Botmulation –60.IL2RA expression can have opposing outcomes in terms of disease susceptibility depending on the cell type, it is of great importance to reveal in which cell type a particular causative SNP plays its role. This would also be crucially important if gene therapy of autoimmune disorders ever reaches practical use in clinic.Since changes in IL2RA promoter activity in MT-2 but not in Jurkat cells and that this SNP affected luciferase expression only in the former cell type. This is in agreement with the observation that the majority of cell type-specific effects of common genetic variation on gene expression results from cell type-specific use of regulatory elements [Using luciferase reporter system we showed that the 1 kb genomic segment containing rs12722489 increased elements . DNA regS1 TableThe predictions overlapping between mono- and dinucleotide PWMs are marked in green(XLSX)Click here for additional data file.S1 FigThe promoter region indicated by a blue bar and the tracks considered in promoter region selection shown below.(TIF)Click here for additional data file.S2 FigJurkat cells were placed in steroid-free medium immediately after transfection with ERE-LUC plasmid and 17β-estradiol (E2) was added 24h later. Luciferase signal was assessed 18h after E2 addition. Data is represented as mean±SD.(TIF)Click here for additional data file.


CPT Iα1b and CPT Iα2a genes, we cloned the 2695-bp and 2631-bp regions of CPT Iα1b and CPT Iα2a promoters of grass carp (Ctenopharyngodon idella), respectively, and explored the structure and functional characteristics of these promoters. CPT Iα1b had two transcription start sites (TSSs), while CPT Iα2a had only one TSS. DNase I foot printing showed that the CPT Iα1b promoter was AT-rich and TATA-less, and mediated basal transcription through an initiator (INR)-independent mechanism. Bioinformatics analysis indicated that specificity protein 1 (Sp1) and nuclear factor Y (NF-Y) played potential important roles in driving basal expression of CPT Iα2a gene. In HepG2 and HEK293 cells, progressive deletion analysis indicated that several regions contained cis-elements controlling the transcription of the CPT Iα1b and CPT Iα2a genes. Moreover, some transcription factors, such as thyroid hormone receptor (TR), hepatocyte nuclear factor 4 (HNF4) and peroxisome proliferator-activated receptor (PPAR) family, were all identified on the CPT Iα1b and CPT Iα2a promoters. The TRα binding sites were only identified on CPT Iα1b promoter, while TRβ binding sites were only identified on CPT Iα2a promoter, suggesting that the transcription of CPT Iα1b and CPT Iα2a was regulated by a different mechanism. Site-mutation and electrophoretic mobility-shift assay (EMSA) revealed that fenofibrate-induced PPARα activation did not bind with predicted PPARα binding sites of CPT I promoters. Additionally, PPARα was not the only member of PPAR family regulating CPT I expression, and PPARγ also regulated the CPT I expression. All of these results provided new insights into the mechanisms for transcriptional regulation of CPT I genes in fish.Carnitine palmitoyltransferase I (CPT I) is a key enzyme involved in the regulation of lipid metabolism and fatty acid β-oxidation. To understand the transcriptional mechanism of  CPT I gene are useful for the understanding of the β-oxidation in fish. In mammals, three CPT I isoforms encoded by distinct genes have been discovered: a liver isoform (CPT Iα) [CPT Iβ) [CPT Ic) [CPT I isoforms have been cloned. For example, three α-copies and one β-copy of CPT I was obtained in yellow catfish Pelteobagrus fulvidraco [CPT I cDNA sequences  and a partial cDNA sequence (CPT Iα2b1b) were cloned in goby Synechogobius hasta [CPT Iα genes  and one CPT Iβ gene isoforms have successfully been cloned [CPT Iβ had a much lower IC50 and higher Km for carnitine than CPT Iα (from [CPT I gene and structure prediction as well as its enzyme kinetics are well documented in fish [CPT I gene received no attention.Lipids are the major sources of metabolic energy in fish . Body li(CPT Iα) , a muscl[CPT Iβ) , and a b[CPT Ic) . In fishlvidraco  and seveus hasta . In grasn cloned ,11. Althn cloned . For exan cloned  pointed Iα (from ). Lineag in fish ,11,13,14CPT I mRNA expression. At present, most studies on the mRNA expression and/or activity of CPT I isoforms in fish involve the response to either dietary or hormonal treatments [CPT I promoter, which helps to understand the regulatory mechanism of CPT I itself. At present, the promoter of the CPT Iα gene has been obtained only in mammals [CPT I promoters between fish and mammals.Considering the importance of CPT I in regulating fatty acid oxidation, it is very important and meaningful to explore the regulatory mechanism of eatments ,17,18,19 mammals ,21, but PPARα mRNA expression was positively correlated to CPT I mRNA expression [CPT Iα genes, respectively [PPARγ was positively correlated with CPT I expression, suggesting a potential regulation of PPARγ on CPT I expression. At present, although several evidences suggested that CPT Iα was a target gene for PPAR [Lipid metabolism is closely controlled by diverse regulatory systems involving many transcription factors. Peroxisome proliferator-activated receptors (PPARs), which belong to ligand-dependent transcription factors, regulate the expression of various genes involved in lipid metabolism ,23. Amonpression ,26. Furtectively ,28. PPARectively . In an eectively  found thfor PPAR ,28,29, aCtenopharyngodon idella) was an important herbivorous freshwater fish widely farmed all over the world because of its good taste and high market price. Its aquaculture yield amounted to 6 million metric tons in China in 2016. In some countries of European and Northern America, grass carp were used to control aquatic plants because of their aggressive feeding on vegetation [CPT Iα1b and CPT Iα2a promoters in grass carp. Their transcriptional regulation by peroxisome proliferators was also explored. These studies will provide new insights into the transcriptional regulatory mechanism of CPT I genes in fish.Grass carp , and explored their functional characteristics in fish.Studies indicated that, compared with other isoforms, mRNA levels of he liver ,11. TherCPT Iα1b promoter and 2631 bp of CPT Iα2a promoter were cloned and submitted to an online transcription factor database (MatInspector) for sequence analysis. RNA ligase-mediated rapid amplification of 5′ cDNA ends (RLM-5′RACE) was performed to identify the TSS of CPT Iα1b and CPT Iα2a promoters. This amplification generated two different TSSs of CPT Iα1b which approximately corresponded to the alternative 5′ splice variants of CPT Iα1b mRNA, and one TSS of CPT Iα2a without alternative 5′ variant. The first nucleotide of the CPT Iα1b gene, mapped to the most upstream position from the grass carp liver cDNA library, was arbitrarily designated as +1′ and the alternative 5′ splicing site was designated as +1 . Predicted TATA-box was located between 148 bp and 167 bp of the FAM-labeled fragment, and the electropherograms around this region presented similar peak patterns between control group  and DNase I digested group . In contrast, the region between 290 bp and 360 bp presented different peak patterns between control group and DNase I digested group, where the initiator (INR) was located. CPT Iα1b promoter from −581 bp to −236 bp containing alternative transcription start site (TSS2). Predicted TATA-box on this fragment was located between 327 bp and 343 bp of the FAM-labeled fragment, and the electropherograms on this region were similar between control group  and DNase I digested group . In contrast, the different peak patterns were discovered at the region between 285 bp and 310 bp, where the INR was located. Taken together, these indicated that the INR on the promoter was sufficient for the transcription initiation of CPT Iα1b gene.CPT Iα1b promoter, including two TATA-box (TBP) located from −160 bp to −176 bp and from −293 bp to −309 bp, and two initiator (INR) located at −2 bp to +10 bp (TSS1) and −333 bp to −343 bp (TSS2), were identified  were identified, located at −46 bp to −60 bp, −146 bp to −160 bp and −165 bp to −179 bp, respectively. Besides, two GGGCGG-box (Sp1), located at −13 bp to −29 bp and −127 bp to −143 bp, were also identified on the core promoter of CPT Iα2a  binding sites on the CPT Iα2a promoter, at the position −39 bp to −63 bp, −1103 bp to −1127 bp and −1331 bp to −1355 bp, respectively. In addition, we discovered one HNF4 binding site on the CPT Iα1b promoter, located at −2379 bp to −2403 bp, one HNF4 binding site on the CPT Iα2a promoter, located at the position −406 bp to −430 bp, and one HNF4α binding site on the CPT Iα2a promoter, located at the position −2587 bp to −2611 bp. Moreover, analysis using MatInspector database revealed two PPAR binding sites on the CPT Iα1b promoter and four PPAR binding sites on the CPT Iα2a promoter. Among these sites, one PPARα/RXR binding site located at the position −1814 bp to −1836 bp and one PPARγ binding site located at the position −1719 bp to −1741 bp were predicted on the CPT Iα1b promoter. Meanwhile, there were four important binding sites of transcriptional factors on the CPT Iα2a promoter, distributed at the position −1939 bp to −1961 bp (PPARα/RXR binding site), −1179 bp to −1201 bp (PPARγ binding site), −1104 bp to −1136 bp (PPARγ binding site) and −1044 bp to −1066 bp (PPARγ binding site).Several putative core promoter elements close to the TSS on the entified . MeanwhiCPT Iα2a . Some reCPT Iα1b and CPT Iα2a promoters was presented in CPT Iα1b promoter sequence from −2695 bp to −86 bp in HepG2 cells. Deletion of the region from −2276 bp to −2695 bp significantly increased the relative luciferase activity of the promoter. Subsequent deletion to −1716 bp significantly decreased the relative luciferase activity. Deletion of the sequence from −581 bp to −1716 bp showed no significant effect, whereas deletion of the sequence from −581 bp to −86 bp significantly decreased the relative luciferase activity. CPT Iα1b promoter in HEK293 cells. Deletion of the sequence from −2695 bp to −2276 bp significantly increased the relative luciferase activity, and the sequence deletion from −2276 bp to −1716 bp significantly reduced the activity. Subsequent deletion to −581 bp presented no significant effects on the relative luciferase activity. The sequence deletion from −581 bp to −86 bp significantly decreased the relative luciferase activity.Deletion analysis of CPT Iα2a promoter sequence from −2631 bp to −97 bp in HepG2 cells. The relative luciferase activity of CPT Iα2a promoter showed no significant difference from −2631 bp to −1646 bp. Deletion of the sequence from −1646 bp to −1304 bp significantly increased the relative luciferase activity. Subsequent deletion to −848 bp presented no significant effects on the relative luciferase activity. Deletion of the sequence of −848 bp to −428 bp and −428 bp to −97 bp significantly decreased the relative luciferase activity. CPT Iα2a promoter in HEK293 cells. Deletion of the sequence from −2631 bp to −1165 bp presented no significant effects on the relative luciferase activity. All of these sequence deletions from −1165 bp to −848 bp, −848 bp to −428 bp and −428 bp to −97 bp significantly decreased the luciferase activity.CPT Iα1b and CPT Iα2a genes in HepG2 cells  and be disrupted by a 100-fold excess of unlabeled wild-type, and restored by a point-mutant probe  were identified in grass carp (C. idella) [CPT Iα1b and CPT 1α2a were predominant in the liver. Therefore, CPT Iα1b and CPT 1α2a were considered as the liver isoform. To investigate their transcriptional regulatory mechanism, for the first time, we cloned the sequences of CPT Iα1b and CPT Iα2a promoters in fish, and explored their functional characteristics.The reaction catalyzed by CPT I is a rate-controlling step in the pathway of LCFA β-oxidation. Currently, five isoforms of  idella) ,11. MoreCPT Iα1b corresponding to the alternative 5′ splice variants of CPT Iα1b mRNA. Studies suggested that alternative TSSs usually occurred in the proximal promoter of genes lacking TATA and CCAAT boxes [CPT Iα) promoter was GC rich and TATA-less and had an alternative transcription initiation. However, our present study found some variations in TSSs of the CPT Iα1b promoter in grass carp. Grass carp CPT Iα1b promoter was AT-rich and contained two TATA elements without canonical CpG islands, but DNase I foot printing assay showed that both TATA elements were not protected from DNase I digestion, whereas the INR, which encompassed the TSS, was protected from DNase I digestion. These phenomena indicated that the basal transcription of the CPT Iα1b gene required the INR to position the basal transcription machinery. In agreement with our study, Smale and Kadonaga [CPT Iα1b gene might be mediated through an INR-independent mechanism. For CPT Iα2a gene, the present study indicated that the core promoter of grass carp CPT Iα2a was GC-rich and did not contain a TATA box.In the present study, we found two TSSs of AT boxes . BatarseAT boxes  pointed AT boxes  found thKadonaga  pointed CPT Iα gene [CPT Iα2a contained several Sp1 and NF-Y binding sites, whereas only one transcription initiation was identified on the promoter. Steffen et al. [CPT Iα gene. Sp1, a ubiquitously expressed prototypic C2H2-type zinc finger protein, can activate or repress transcription after physiological and pathological stimuli [CPT Iα2a promoter in a similar manner, indicating a similar transcription initiation for CPT Iα2a transcription. Taken together, our study indicated that transcription initiation of the CPT Iα1b and CPT Iα2a genes presented different mechanisms, suggesting that the expression of two genes from grass carp was induced by different transcriptional initiation.In agreement with rat  Iα gene , our stun et al.  pointed  stimuli ,37. Stud stimuli . Moreove stimuli ,39. In aCPT Iα1b and CPT Iα2a at the transcriptional level, we functionally characterized the CPT Iα1b and CPT Iα2a promoters of grass carp. The present study identified a cluster of TFBS, such as TR, HNF4 and PPAR family, on the grass carp CPT Iα1b and CPT Iα2a promoters. Similarly, Jackson-Hayes et al. [CPT Iα gene had a thyroid hormone response element (TRE) which was required for the thyroid hormone receptor (TR) binding. In the present study, several TREs were also observed on the grass carp CPT Iα1b and CPT Iα2a promoters. Interestingly, our study found that CPT Iα1b and CPT Iα2a promoters were bound by different isoforms of TRs. The two TREs on the CPT Iα1b promoter were only for TRα binding, and the three TREs on the CPT Iα2a promoter were only for TRβ binding. In fish, TRα and TRβ were expressed at different developmental stages, suggesting their functional differentiation [CPT Iα1b and CPT Iα2a genes were regulated through different mechanism in the liver.Identification of TFBSs is very important for deciphering the mechanisms of gene regulation . To betts et al.  showed tntiation . Additiontiation . Thus, tCPT Iα1b and CPT Iα2a genes. Furthermore, the regions of the CPT Iα1b and CPT Iα2a promoters presented different reporter activities in HepG2 and HEK293 cells. Obviously, the enhancing/decreasing reporter activity indicated the existence of potential positive/negative regulators on the regions, respectively. For the promoter of CPT Iα1b gene, we found that, compared to the region between −1716 and 1379 bp, the luciferase activity between the region from −2276 bp to −1716 bp significantly increased in HepG2 and HEK293 cells. Interestingly, we noticed that the −2067/−2091 TRα binding site, −1939/−1961 PPARα binding site and −1719/−1741 PPARγ binding site were located at the region from −2276 bp to −1716 bp, which was reported to correlated with CPT I expression in mammals [CPT Iα2a gene, we discovered that the luciferase activity increased from the TSS to −848 bp in HepG2 cells, whereas the activity increased from TSS to −1165 bp in HEK293 cells, indicating a different regulation at the region from −848 bp to −1165 bp between the two kinds of cell lines. In the meantime, we found the −1103/−1127 TRβ binding site, −1044/−1066 PPARγ binding site and −1104/−1126 PPARγ binding site were located in this region. Besides, the luciferase activity declined at the region from −1304 bp to −1646 bp in HepG2 cells, but not in HEK293 cells, and this region contained the −1331/−1355 TRβ binding site. Considering different TREs on CPT Iα1b and CPT Iα2a promoter, TR enhanced the promoter activity of corresponding genes and might play important roles in regulating the expression of CPT Iα2a in different tissues. Moreover, we also discovered that the luciferase activity declined in the region from −2695 bp to −2276 bp of CPT Iα1b and the region from −1304 bp to −1646 bp of CPT Iα2a promoter in HepG2 cells. Obviously, some negative regulators binding on these regions regulated CPT Iα1b and CPT Iα2a expression. In addition, studies suggested that the luciferase activity declined in the deletion region from more that −6000 bp to −1653 bp on the promoter of rat CPT Iα [CPT Iα1b and CPT Iα2a, suggesting that positive regulators existed on the upstream region of CPT Iα1b and CPT Iα2a promoters. Thus, it appears that the regulation of CPT Iα1b and CPT Iα2a transcription was more complicated in fish than mammals.In the present study, deletion analysis indicated that several regions of the promoters contained a potential cis-active element(s) which enhanced/decreased transcriptional activities of the grass carp  mammals ,45,46. Ft CPT Iα . HoweverCPT I was one of the target genes of PPARα [CPT Iα1b and CPT Iα2a promoters were induced by fenofibrate, PPARα agonist. However, site-directed mutagenesis and EMSA analysis indicated that CPT Iα1b and CPT Iα2a were not regulated through those predicted PPARα binding sites. Accordingly, the reporter activities were up-regulated by fenofibrate, indicating that other potential PPARα binding sites or other related factors existed on the promoter. For instance, studies suggested that PPARα-induced activation of CPT Iα gene was enhanced in a ligand-dependent manner by PGC-1 [CPT Iα1b and CPT Iα2a by fenofibrate may involve several nuclear factors and/or other promoter regions of the gene.PPARs are key transcriptional factors which mediate the regulation of many enzymes related with lipid metabolism . Studiesof PPARα ,45. In oby PGC-1 , and PGCby PGC-1 . Additioby PGC-1 ,40. TakeCPT I was regulated by PPARγ. Pioglitazone, the agonist of PPARγ [CPT Iα2a promoter, and site-mutation on the −1044/−1066 PPARγ binding site reduced the activity. Moreover, EMSA assay confirmed that the sequence at −1044 bp to −1066 bp was a functional binding locus. Similarly, Gilde et al. [CPT I promoter. Patsouris et al. [CPT Iα2a promoter, and pioglitazone-induced activation of PPARγ could up-regulate the activity of CPT Iα2a promoter. These evidences indicated that PPARγ probably played an important role in regulating CPT Iα2a transcription and compensated for PPARα-induced expression of lipolytic genes in fish.PPARγ is one of transcriptional factors which plays important roles in lipogenesis. The present study indicated that transcription of grass carp of PPARγ , could ie et al.  found ths et al.  reporteds et al. ,52. Stans et al.  found thCPT Iα1b and 2631-bp CPT Iα2a promoters in grass carp had been cloned and characterized. The promoters of CPT Iα1b and CPT Iα2a genes showed the different structures in their core regions. Several putative TFBSs had been predicted in their promoter regions. Analysis of 5′ deletion mutants presented the regulatory characteristics of CPT Iα1b and CPT Iα2a promoters. Fenofibrate activated the activities of CPT Iα1b and CPT Iα2a promoters. PPARγ played an important role in regulating CPT I expression. The present study provided new insights into the regulatory mechanisms of liver isoforms of CPT I genes in fish.In summary, the 2695-bp Juvenile grass carp was obtained from Hubei Honghu Fisheries Farm . HepG2 and HEK293 cell lines were obtained from the Cell Resource Center in Fishery College of Huazhong Agricultural University. We ensured that the experiments were performed in accordance with the experimental protocols of Huazhong Agricultural University (HZAU) and approved by the ethics committee of HZAU .CPT Iα1b and CPT Iα2a genes were determined using the GeneRacer Kit , according to the manufacturer’s instructions. Briefly, total RNA was isolated from the liver tissue using TRIzol Reagent (Invitrogen), and then the 5′-ready cDNA libraries were prepared using reverse transcription kit (Invitrogen). Nested PCR was performed using a commercial nested 5′ primer (Invitrogen) in combination with a reverse gene-specific primer complementary to CPT Iα1b and CPT Iα2a genes. The PCR reactions were performed using TaKaRa PrimeSTAR® HS DNA Polymerase kit  under the following PCR conditions: pre-incubation at 94 °C for 3 min, 30 cycles of 94 °C for 15 s, 60 °C for 30 s and 72 °C for 1 min. Amplified PCR products were gel-purified and subcloned into pMD19-T for sequencing .The TSSs of CPT Iα1b and CPT Iα2a promoters. Genomic DNA was extracted from grass carp tail fins using a commercial kit . For amplification of the CPT Iα1b and CPT Iα2a promoter sequences, specific primers with overlapping sequence were designed and listed in ® HS DNA Polymerase kit (TaKaRa) as mentioned above. All plasmids were sequenced in a commercial company (Tsingke).Based on the published draft genome of grass carp , we clonCPT Iα1b and CPT Iα2a genes in grass carp, putative TFBSs were predicted by MatInspector online (http://www.genomatix.de/). Nucleotide sequences of CPT Iα1b and CPT Iα2a promoters were compared with DNA sequences present in the GenBank database (http://www.ncbi.nlm.nih.gov/genbank/) and the UCSC Genome Browser (http://genome.ucsc.edu/).For sequence analysis of promoters of CPT Iα1b promoter, which contained two TSSs , were PCR amplified and cloned into pMD-19T vector (TaKaRa). Then, the amplicons were used as the template for further preparation of fluorescent 6-carboxy-fluorescein (FAM)-labeled probes with M13F and M13R-FAM to label the coding strand. After agarose gel electrophoresis, the FAM-labeled probes were purified by Gel Extraction Kit  and quantified with NanoDrop 2000 . 10 µg of proteins extracted from HepG2 cell lines were incubated with 500 ng of probes in the same binding buffer based on Zianni et al. [DNase I foot printing assays were performed based on the method of Zianni et al. . In briei et al. . DNase Iv/v) heat-inactivated FBS (Invitrogen) and 2 mM l-glutamine in a humidified atmosphere with 5% CO2 at 37 °C. Prior to the transient transfection, HepG2 or HEK293 cells were seeded in 24-well cell culture plate at a density of 1.2 × 105 and cultured for 24 h to reach 70–80% convergence. Plasmids were transiently transfected into HepG2 or HEK293 cells using Lipofectamine™ 2000 (Invitrogen) following the manufacture’s protocol. All reporter plasmids were used in equimolar amounts in Opti-MEM (Invitrogen), and they were co-transfected with 35 ng pRL-TK as the control. After 4 h, the transfection medium was replaced by 10% FBS-DMEM. Then, with 24-h incubation, cells were harvested to assay the relative luciferase activity by Dual-Luciferase Reporter Assay System (Promega). The relative luciferase activity was presented as the ratio of firefly luciferase to renilla luciferase. Results were normalized to the control reporter pGl3-Basic. All experiments were performed in triplicates and measured at least three times.HepG2 and HEK293 cells were cultured in DMEM medium supplemented with 10% . pGl3-CPTIα1b-2276, pGl3-CPTIα2a-2041 and pGl3-CPTIα2a-1304 were used as templates. The mutagenesis primers were listed in TM 2000 following the manufacture’s protocol. After 4 h, the transfection medium was replaced by 10% FBS-DMEM with 50 μM fenofibrate or 10 μM pioglitazone. After 24-h incubation, cells were harvested to assay the luciferase activity according to the procedure above.To identify the corresponding PPAR binding sites on the grass carp EMSA was performed to confirm the functional PPAR binding sites of the promoters. Proteins for EMSA were extracted from HepG2 cell lines. Nuclear and cytoplasmic extracts were prepared based on the methods of Read et al. . Proteint test. Difference was considered significant at p < 0.05. All statistical analyses were performed using the SPSS10.0 for Windows .Results were presented as mean ± SEM (standard errors of means) in at least three independent biological experiments. Prior to statistical analysis, all data were tested for normality of distribution using the Kolmogornov-Smirnov test. Differences between wild types and drug-treated groups were compared using the Student’s


GCKR) have been reported for lipid and glucose metabolism traits and the risk of T2D. We investigated the regulatory function of an intronic locus at GCKR represented by the lead single nucleotide polymorphism (SNP) rs780094.Genome-wide association studies (GWAS) have identified more than 100 genetic loci associated with type 2 diabetes (T2D). However, the underlying biological mechanisms for many of these associations remain unknown. GWAS signals close to the glucokinase regulatory protein gene (GCKR intronic locus formed by the high linkage disequilibrium rs780094(C/T), rs780095(G/A), and rs780096(G/C) SNPs. Characterization of the transcriptional activity of this region was assessed by luciferase reporter assays in HepG2 cells and mouse primary hepatocytes. ChIP-qPCR was used to determine the levels of haplotype specific transcription factor binding and histone marks. A CRISPR-dCas9 transcriptional activator system and qPCR were used to activate the locus and measure GCKR expression, respectively. Differential haplotype expression was measured from human liver biopsies.We used ENCODE project histone modification and transcription factor binding data to determine the regulatory features of a GCKR in HepG2 cells, confirming that GCKR is the direct target gene of the enhancer. Finally, we confirmed that the CGG haplotype exhibits higher levels of transcription in human liver.The ENCODE data suggest the existence of a liver-specific intragenic enhancer at the locus represented by s780094. We observed that FOXA2 increased the transcriptional activity of this region in a haplotype specific way . In addition, the CGG haplotype showed higher binding to FOXA2 and higher levels of the H3K27Ac histone mark. The epigenetic activation of this locus increased the expression of endogenous GCKR expression. Differential haplotype regulation suggests the existence of cis regulatory effects that may contribute to the associated traits at this locus.Our results demonstrate the existence of a liver-specific FOXA2-regulated transcriptional enhancer at an intronic T2D locus represented by rs780094, rs780095, and rs780096 SNPs that increases The online version of this article (doi:10.1186/s13073-017-0453-x) contains supplementary material, which is available to authorized users. Type 2 diabetes T2D; MIM 125853) develops as a consequence of complex interactions between genetic and environmental/lifestyle factors. Genome-wide association studies (GWAS) have identified more than 100 common single nucleotide polymorphisms (SNPs) associated with T2D and glycemic traits [25853 devGCKR; MIM 613463) encodes for glucokinase regulatory protein , the main allosteric inhibitor of glucokinase , and is a T2D-associated locus. GKRP inhibits GCK by a direct effect on enzyme kinetics or by sequestering GCK in the nucleus, where GCK is unable to facilitate glycolysis [The glucokinase regulatory protein gene (GCKR lies in a large region of linkage disequilibrium (LD) on chromosome 2, spanning about 417 kb, 16 genes, and several correlated variants [GCKR rather than to other genes in the LD block [variants . GeneticLD block . These sLD block . Functio2 = 0.94) overlap in their phenotypical associations [GCKR transcription. Another two SNPs, rs780095 and rs780096, are in high LD (r2 = 0.86) and are located very close  to rs780094. Therefore, it is likely that these variants overlap in their functional roles and thus their haplotype combinations may influence the metabolic susceptibility.Despite the functional evidence that the rs1260326 variant impacts on both the kinetics and cellular localization of GKRP, the high LD in the region warrants the investigation of other variants which could contribute to molecular mechanisms associated with multiple traits. One such variant is an intronic SNP, rs780094, which was originally identified to be associated with fasting serum triacyglycerol, insulinemia, and the risk of T2D [GCKR expression and that GCKR is a direct target of this regulatory region. In addition, we show an association between haplotype expression and the levels of free fatty acids (FFAs) in human liver biopsies. Our results suggest a novel mechanism for the regulation of GCKR expression that could have a combined effect with the P446L variant on the phenotypical associations at the GCKR locus.In the present study we demonstrate that the locus containing rs780094 functions as a transcriptional enhancer that is activated by the Forkhead box protein A2  transcription factor (TF) in a haplotype specific fashion. We show that epigenetic activation of the enhancer induces 6 cells/ml in the appropriate vessel depending on the assay performed. For insulin stimulation in ChiP-qPCR experiments, the cells were serum-starved overnight and insulin  was added for 15 min before crosslinking. The cells were transfected using Lipofectamine 3000 (ThermoFisher) according to the manufacturer’s indications. The transfection conditions were optimized before conducting the over-expression experiments.HepG2 cells  were cultured in Dulbecco’s modified Eagle medium  supplemented with 10% fetal bovine serum . Cells were seeded at 0.2–0.3 × 103, 10 mM HEPES, 0.5 mM EDTA in HBSS; pH adjusted to 7.4) followed by 35 ml of perfusion solution . Both the pre-perfusion and the perfusion solutions were pre-warmed to 37 °C and circulated through an oxygen atmosphere and a 37 °C water bath before reaching the liver at 3 ml/min. After the perfusion, the liver was removed and placed on a petri dish containing a sufficient amount of plating medium  and torn into pieces with sharp forceps to extract the cells. The cell suspension was filtrated through a cell strainer  and centrifuged at 50 × g for 2 min. Cells were seeded at 0.5 × 106 cells/ ml on collagen-coated 96-well plates. Five hours after plating, medium was changed to maintenance medium (seeding medium without FBS), and the following day cells were transfected with Targefect F1 plus Virofect enhancer transfection reagents (Targeting Systems) according to the manufacturer’s indications. DNA constructs were expressed for 24 h in basal William’s E medium with 20 ng/ml dexamethasone without or with 100 nM of insulin. All animal experiments in this study were approved by the National Experimental Animal Board of Finland.Mouse primary hepatocytes (MPHs) were prepared from 7–9-week-old C57BL male mice livers as previously described . BrieflyRenilla reniformis) and plasmids expressing human FOXA2, FOXA1, RXRA, or MAFK or the control vector pCMV6-XL5 without TF insert  . The luciferase activity was measured 48 h post-transfection using the Dual-Glo Luciferase Assay System (Promega) in the Cytation 3 Multi-Mode Reader (BioTek). MPH were transfected with 60 ng of plasmid DNA and 24 h post-transfection luciferase activity was measured with the Dual Luciferase Assay System (Promega) in a Fluostar OPTIMA plate reader (BMG LABTECH). In all cases, the firefly luciferase activity was normalized to the Renilla signal and reported as proportions relative to the control vector. In HepG2 cells, we performed five or six independent experiments with three or more technical replicates  was extracted using the PureLink genomic DNA Mini Kit (Invitrogen). A 3-kb region from gDNA was amplified by PCR with Phusion High-Fidelity DNA polymerase (ThermoFisher) and specific primers  were downloaded from the ENCODE database under accession numbers GSM733743, GSM803499, GSM803461, GSM803403, GSM803452, GSM935610, GSM803432, GSM733693, GSM935610, and GSM935305. The allele-specific ChIP-Seq data were visually quantified from bam files using the IGV , 15. TheddCt method to calculate the haplotype-specific enrichment for both input and immunoprecipitated chromatin over an intronic region of GRB10  for which no TF binding or H3K27Ac histone marks have been reported. Fold enrichment was determined by dividing the enrichment of the immunoprecipitated chromatin by the enrichment of the respective input. FOXA2 and H3K27Ac ChIP-qPCR experiments were performed in triplicate .ChIP experiments were performed in HepG2 cells with minor changes from a previously published protocol . BrieflyGCKR expression we used a CRISPR-dCas9-derived transcriptional activator system [GCKR mRNA and RPLP0 mRNA  expression were measured by qPCR using specific TaqMan gene expression assays (ThermoFisher) in a 7500 Real-Time PCR System (Applied Biosystems). The relative gene expression was calculated using the relative ddCt-quantification. Four independent experiments were performed .To determine the direct effect of the enhancer on r system , 18. Thir system , and ther system  and two ddCt method and the relative expression between the haplotypes was calculated. The haplotype expressions were compared using a Mann–Whitney U test, and the associations between haplotype expression and metabolic traits were assessed by a Spearman’s rank correlation test with Bonferroni correction.A total of 304 severely obese individuals participated in the ongoing KOBS study . All subPlasma glucose, insulin, serum lipids and lipoproteins , and FFAs were measured from fasting venous blood samples. Plasma glucose was measured by enzymatic hexokinase photometric assay . Plasma insulin was determined by immunoassay . An oral glucose tolerance test (OGTT) was performed after a 12-h fasting period. Serum FFAs were assayed with an enzymatic colorimetric method . Glucose, insulin, and FFA levels were determined at 0, 30, and 120 min with an OGTT.t-test to compare the haplotypes in the same treatment, and one-way ANOVA to compare the haplotypes between the different treatments (insulin versus no insulin). Basal H3K27Ac and FOXA2 ChIP-qPCR data . No comparison between the haplotypes was performed for gR1 + VPR. The haplotype expression data from human liver biopsies  and located very close to each other  and rs780093 (r2 = 0.98), which, however, reside outside the potential enhancer. Moreover, only the region containing rs780094, rs780095, and rs780096 has been found to bind TFs. Position weight matrix (PWM) modeling for rs780094, rs780095, and rs780096 [We investigated the chromatin features of the region containing rs780094, rs780095, and rs780096 by exploring the ENCODE Project data for histone modifications and TF binding . These Sher Fig. . The dather Fig. , in lineher Fig. . In additer Fig. . An adjater Fig. . Accordirs780096  showed tTo investigate the transcriptional activity of the region defined by rs780094, rs780095, and rs780096 and its relationship to the TFs, we performed luciferase reporter assays in HepG2 cells and MPHs. We cloned two DNA inserts representing the two most common haplotypes formed by these variants in the METSIM study  CGG/TAC. The seqp = 0.0003). Similarly, FOXA2 also increased the transcriptional activity of the 3-kb region in a haplotype-specific way , while no luciferase activity was observed in cotransfection with the pCMV6-XL5 vector . This may indicate insufficiency of the endogenous TF pool to activate the luciferase constructs transfected in excess to the cells, rather than a lack of enhancer activity. To test this, we co-transfected the 638-bp constructs with either the empty vector pCMV6-XL5 or plasmids expressing the TFs that bind to this region according to the ENCODE project data . When co-transfected with pCMV6-XL5, none of the haplotypes increased luciferase activity compared to the control vector pGL4.10-TK . As expected, insulin reduced FOXA2-dependent transcriptional activity similarly for both haplotypes .Although MAFK alone was not sufficient to activate reported gene expression  is not sufficient to discriminate whether the differential binding is allele-specific only for rs780094, thus limiting our analysis to the haplotypes. In line with the active histone marks H3K4me1/2, the CGG haplotype also exhibited 1.4-fold higher enrichment of H3K27Ac  activator system to this locus [GCKR transcription by 1.4-fold, compared to a control gRNA plasmid without targeting gRNA (VPR + gEm)  study [p = 2.92 × 10−4; Fig. p = 4.24 × 10−5, n = 44; women 12%, p = 0.051, n = 88; Fig. p = 0.001) but only a non-significant trend was observed in individuals with T2D   in individuals with NGT  study  . The pioneering function of FOXA2 may explain the role of this TF in activating the enhancer. Namely, FOXA2 has the ability to interact directly with the core histones to open condensed chromatin and facilitate the binding of other TFs that would otherwise not be able to access their binding sites [GCKR transcription is activated in the fed state by high glucose via ChREBP [GCKR transcription through a FOXA2-activated enhancer in a haplotype-specific way, which may also be contributed to by other TFs , supporting a co-regulatory role of MAFK . Like FOGCKR expression. Moreover, although the differences between the haplotypes were in the same direction, these were of higher magnitude and reached significance only in male subjects, which may have important functional relevance at the population level. Interestingly, the differences in haplotype expression followed the same trend in individuals with NGT and T2D. To our knowledge, changes in GCKR expression in T2D have not been reported. Therefore, our data suggest that the genotype may have a stronger effect on GCKR expression than the glycemic status. The effect of GCKR levels on the diabetic phenotype has been suggested by a study in which overexpression of GKRP in diabetic mice improved glucose homeostasis and increased insulin sensitivity [We also showed that the CGG haplotype exhibited higher expression compared to the TAC haplotype in human liver biopsy samples, providing evidence for a haplotype-specific effect on sitivity . FurtherGCKR transcription may alter the GCK/GKRP ratio, affect GCK activity, and impact glucose metabolism Additional file 2:Datasets. (XLSX 178 kb)Additional file 3:Histone modifications at rs780094 from different tissues (data from Roadmap Epigenomics Project). (XLSX 17 kb)Additional file 4:Raw sequencing data from HepG2, first read. (ZIP 436 kb)Additional file 5:Raw sequencing data from HepG2, second read. (ZIP 470 kb)