ENCODE ChIP-seq Data Research Articles

Long noncoding RNA LINP1: scaffolding non-homologous end joining.

Non-homologous end joining (NHEJ) is a principal pathway of DNA double-strand break (DSB) repair in mammalian cells,1 but is also involved in assembly of antigen receptor genes and telomere maintenance.2,3 Loss of NHEJ function can result in chromosome instability promoting malignant transformation, in particular when other cellular safeguards are compromised. Inherited NHEJ defects underlie radiosensitive severe combined immunodeficiency. NHEJ is initiated by binding of Ku70–Ku80 heterodimers to both ends of a DNA break, followed by recruitment of catalytic subunits of DNA-dependent protein kinase (DNA-PKcs) to form juxtaposed DNA-PK holoenzymes which join the ends in a synaptic complex. Cohesive blunt DNA ends can be joined directly by the XFL-XRCC4-DNA ligase IV complex, but in many cases DNA ends contain damaged bases or DNA backbone sugars that require processing before ligation. End processing may involve nucleases such as Artemis, DNA polymerases and polynucleotide kinase among other enzymes.4,5

Histone H4 lysine 20 acetylation is associated with gene repression in human cells.

Histone acetylation is generally associated with gene activation and chromatin decondensation. Recent mass spectrometry analysis has revealed that histone H4 lysine 20, a major methylation site, can also be acetylated. To understand the function of H4 lysine 20 acetylation (H4K20ac), we have developed a specific monoclonal antibody and performed ChIP-seq analysis using HeLa-S3 cells. H4K20ac was enriched around the transcription start sites (TSSs) of minimally expressed genes and in the gene body of expressed genes, in contrast to most histone acetylation being enriched around the TSSs of expressed genes. The distribution of H4K20ac showed little correlation with known histone modifications, including histone H3 methylations. A motif search in H4K20ac-enriched sequences, together with transcription factor binding profiles based on ENCODE ChIP-seq data, revealed that most transcription activators are excluded from H4K20ac-enriched genes and a transcription repressor NRSF/REST co-localized with H4K20ac. These results suggest that H4K20ac is a unique acetylation mark associated with gene repression.

Genome-wide Analysis Identifies Novel Loci Associated with Ovarian Cancer Outcomes: Findings from the Ovarian Cancer Association Consortium.

Chemotherapy resistance remains a major challenge in the treatment of ovarian cancer. We hypothesize that germline polymorphisms might be associated with clinical outcome. We analyzed approximately 2.8 million genotyped and imputed SNPs from the iCOGS experiment for progression-free survival (PFS) and overall survival (OS) in 2,901 European epithelial ovarian cancer (EOC) patients who underwent first-line treatment of cytoreductive surgery and chemotherapy regardless of regimen, and in a subset of 1,098 patients treated with ≥ 4 cycles of paclitaxel and carboplatin at standard doses. We evaluated the top SNPs in 4,434 EOC patients, including patients from The Cancer Genome Atlas. In addition, we conducted pathway analysis of all intragenic SNPs and tested their association with PFS and OS using gene set enrichment analysis. Five SNPs were significantly associated (P ≤ 1.0 × 10(-5)) with poorer outcomes in at least one of the four analyses, three of which, rs4910232 (11p15.3), rs2549714 (16q23), and rs6674079 (1q22), were located in long noncoding RNAs (lncRNAs) RP11-179A10.1, RP11-314O13.1, and RP11-284F21.8, respectively (P ≤ 7.1 × 10(-6)). ENCODE ChIP-seq data at 1q22 for normal ovary show evidence of histone modification around RP11-284F21.8, and rs6674079 is perfectly correlated with another SNP within the super-enhancer MEF2D, expression levels of which were reportedly associated with prognosis in another solid tumor. YAP1- and WWTR1 (TAZ)-stimulated gene expression and high-density lipoprotein (HDL)-mediated lipid transport pathways were associated with PFS and OS, respectively, in the cohort who had standard chemotherapy (pGSEA ≤ 6 × 10(-3)). We have identified SNPs in three lncRNAs that might be important targets for novel EOC therapies.

Loregic: a method to characterize the cooperative logic of regulatory factors.

The topology of the gene-regulatory network has been extensively analyzed. Now, given the large amount of available functional genomic data, it is possible to go beyond this and systematically study regulatory circuits in terms of logic elements. To this end, we present Loregic, a computational method integrating gene expression and regulatory network data, to characterize the cooperativity of regulatory factors. Loregic uses all 16 possible two-input-one-output logic gates (e.g. AND or XOR) to describe triplets of two factors regulating a common target. We attempt to find the gate that best matches each triplet’s observed gene expression pattern across many conditions. We make Loregic available as a general-purpose tool (github.com/gersteinlab/loregic). We validate it with known yeast transcription-factor knockout experiments. Next, using human ENCODE ChIP-Seq and TCGA RNA-Seq data, we are able to demonstrate how Loregic characterizes complex circuits involving both proximally and distally regulating transcription factors (TFs) and also miRNAs. Furthermore, we show that MYC, a well-known oncogenic driving TF, can be modeled as acting independently from other TFs (e.g., using OR gates) but antagonistically with repressing miRNAs. Finally, we inter-relate Loregic’s gate logic with other aspects of regulation, such as indirect binding via protein-protein interactions, feed-forward loop motifs and global regulatory hierarchy.

Abstract 2318: The role of EZH2 as an epigenetic switch of the TGF-β/SMAD4 targets in regulating EMT in ovarian cancer

Abstract The TGF-β signaling regulates numerous cellular processes, including cell proliferation, cell differentiation, apoptosis, migration and cell fate. It was also demonstrated that TGF-β functions as a tumor suppressor in normal ovarian surface epithelium (OSE) cells but promotes tumor proliferation and epithelial-mesenchymal transition (EMT) during ovarian cancer progression. Nevertheless, the molecular mechanisms leading to this divert role of TGF-β signaling in ovarian cancer remains to be elucidated. Our previous studies demonstrated that several TGF-β/SMAD4 regulated targeted are epigenetically silenced by DNA methylation and histone modification including H3K27me3. We therefore hypothesized that the histone-lysine N-methyltransferase, EZH2 may act as an epigenetic switch to facilitate the TGF-β mediated EMT in ovarian cancer. In this study, we utilized our previously identified TGF-β responsive targets using combined ChIP-chip and expression arrays in an immortalized ovarian surface epithelial (IOSE) cell which showed TGF-β growth inhibition. Bioinformatics analysis using ENCODE ChiP-Seq data identified that several of these TGF-β targets are marked by EZH2. To investigate the effect of TGF-β signaling on the methylome of ovarian cancer, we performed MBDcap-Seq in SMAD4 knockdown CP70 cells. Our result showed that there are 99 and 73 TGF-β targets showing hyper- or hypo-methylation respectively after SMAD4 knockdown. Analysis of the gene functions on DAVID has uncovered that some of these hypermethylated genes are associated with EMT process and the TGF-β signaling pathway. On the other hand, the hypomethylated genes are associated with transcription repressor activity. We selected one of the hypermethylated target, LTBP2 which was previously found to be a tumor suppressor for further experiment. This gene was expressed in IOSE but down regulated in a panel of ovarian cancer cells showing overexpression of EZH2. Except for IOSE, promoter hypermethylation of LTBP2 was found in ovarian cancer cells as revealed by bisulphite pyrosequencing. In consistent with deep sequencing result, knock-down of SMAD4 further increased the promoter methylation in CP70 cells. Treatment of demethylation agent, 5azaDC partially restored its expression in these cancer cells. Interestingly, synergistic treatment of 5azaDC and EZH2 inhibitor, GSK343 resulted in a dramatic increase of LTBP2 expression in MCP3 and CP70 cells. Taken together, our result suggested that EZH2 may be involved in the epigenetic silencing of TGF-β/SMAD4-regulated tumor suppressors in ovarian cancer. The differential occupancy of EZH2 into these SMAD4 loci may act as an epigenetic switch to turn the function of TGF-β from a tumor suppressor into an EMT regulator. The therapeutic potential of targeting EZH2 in the inhibition of EMT in ovarian cancer deserves further investigation. Citation Format: Jora Meng-Ju Lin, Jacqueline Shay, Jian-Liang Chou, Pearlly S. Yan, Tim H.-M. Huang, Hung Cheng Lai, Michael W.y. Chan. The role of EZH2 as an epigenetic switch of the TGF-β/SMAD4 targets in regulating EMT in ovarian cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2318. doi:10.1158/1538-7445.AM2014-2318

Abstract 2221: A new promoter of Casp 8 in an esophageal squamous cell carcinoma susceptibility locus

Abstract Our previous Genome wide associationstudy (GWAS) of esophagealsquamous cell carcinoma (ESCC) identified a susceptibility locus on chromosome 2q33.1 encompassing CASP8 gene. Caspase 8 is an essential initiator in cell apoptosis and is associated with many diseases. CASP8 has varieties of transcripts, which might exert distinct functions. However, the transcriptional determinants, which control CASP8 gene expression remain poorly defined. The present study focused on revealing the mechanism behind the GWAS signal and finding clues for the complex regulation of CASP8.We observed a secondary promoter in CASP8 using a series of luciferase reporter assays, which locates 25kb far away from the previously described CASP8 promoter. The ENCODE ChIP-seq data shows the promoter features at the epigenetic level, including high H3K27Ac, H3K4M3 and low CpG methylation around the novel promoter region. Though people have known lots of transcription factors, little research focuses on which factors exert the transcription function for a certain promoteron earth. To explore the transcription factors that contribute to the secondary promoter of CASP8, we developed an effective strategy based on DNA-protein affinity purification and mass spectrometry. PURα was identified from the eluted protein products that the secondary promoter fragment could bind specific. We validated the mass spectrometry result through western blot analysis and immunoprecipitation assay and confirmed that PURα was involved in the transcription machine and might exert the function by forming a complex together with E2F-1 and Pol II. Remarkably, we observed that if knocking down the expression of PURα, the transcription activity decreased significantly. Although the physiologicrole of the CASP8 secondary promoter and its correspondent transcripts remain unclear, the current data suggest that it could explain the complexity of CASP8's transcription in some degree and expand the GWAS results to the function level. We believe these two promoters have thecapacity to play a role in the very different functions of caspase 8 isoforms. Note: This abstract was not presented at the meeting. Citation Format: Zhengwei Lin, Xiaohang Zhao, Yang Xu, Zhimin Guo, Nan Zhao, Yulin Sun. A new promoter of Casp 8 in an esophageal squamous cell carcinoma susceptibility locus. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2221. doi:10.1158/1538-7445.AM2014-2221

Large differences in global transcriptional regulatory programs of normal and tumor colon cells

BackgroundDysregulation of transcriptional programs leads to cell malfunctioning and can have an impact in cancer development. Our study aims to characterize global differences between transcriptional regulatory programs of normal and tumor cells of the colon.MethodsAffymetrix Human Genome U219 expression arrays were used to assess gene expression in 100 samples of colon tumor and their paired adjacent normal mucosa. Transcriptional networks were reconstructed using ARACNe algorithm using 1,000 bootstrap replicates consolidated into a consensus network. Networks were compared regarding topology parameters and identified well-connected clusters. Functional enrichment was performed with SIGORA method. ENCODE ChIP-Seq data curated in the hmChIP database was used for in silico validation of the most prominent transcription factors.ResultsThe normal network contained 1,177 transcription factors, 5,466 target genes and 61,226 transcriptional interactions. A large loss of transcriptional interactions in the tumor network was observed (11,585; 81% reduction), which also contained fewer transcription factors (621; 47% reduction) and target genes (2,190; 60% reduction) than the normal network. Gene silencing was not a main determinant of this loss of regulatory activity, since the average gene expression was essentially conserved. Also, 91 transcription factors increased their connectivity in the tumor network. These genes revealed a tumor-specific emergent transcriptional regulatory program with significant functional enrichment related to colorectal cancer pathway. In addition, the analysis of clusters again identified subnetworks in the tumors enriched for cancer related pathways (immune response, Wnt signaling, DNA replication, cell adherence, apoptosis, DNA repair, among others). Also multiple metabolism pathways show differential clustering between the tumor and normal network.ConclusionsThese findings will allow a better understanding of the transcriptional regulatory programs altered in colon cancer and could be an invaluable methodology to identify potential hubs with a relevant role in the field of cancer diagnosis, prognosis and therapy.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2407-14-708) contains supplementary material, which is available to authorized users.

IRegulon: from a gene list to a gene regulatory network using large motif and track collections.

Identifying master regulators of biological processes and mapping their downstream gene networks are key challenges in systems biology. We developed a computational method, called iRegulon, to reverse-engineer the transcriptional regulatory network underlying a co-expressed gene set using cis-regulatory sequence analysis. iRegulon implements a genome-wide ranking-and-recovery approach to detect enriched transcription factor motifs and their optimal sets of direct targets. We increase the accuracy of network inference by using very large motif collections of up to ten thousand position weight matrices collected from various species, and linking these to candidate human TFs via a motif2TF procedure. We validate iRegulon on gene sets derived from ENCODE ChIP-seq data with increasing levels of noise, and we compare iRegulon with existing motif discovery methods. Next, we use iRegulon on more challenging types of gene lists, including microRNA target sets, protein-protein interaction networks, and genetic perturbation data. In particular, we over-activate p53 in breast cancer cells, followed by RNA-seq and ChIP-seq, and could identify an extensive up-regulated network controlled directly by p53. Similarly we map a repressive network with no indication of direct p53 regulation but rather an indirect effect via E2F and NFY. Finally, we generalize our computational framework to include regulatory tracks such as ChIP-seq data and show how motif and track discovery can be combined to map functional regulatory interactions among co-expressed genes. iRegulon is available as a Cytoscape plugin from http://iregulon.aertslab.org.

ChIP-Enrich: gene set enrichment testing for ChIP-seq data.

Gene set enrichment testing can enhance the biological interpretation of ChIP-seq data. Here, we develop a method, ChIP-Enrich, for this analysis which empirically adjusts for gene locus length (the length of the gene body and its surrounding non-coding sequence). Adjustment for gene locus length is necessary because it is often positively associated with the presence of one or more peaks and because many biologically defined gene sets have an excess of genes with longer or shorter gene locus lengths. Unlike alternative methods, ChIP-Enrich can account for the wide range of gene locus length-to-peak presence relationships (observed in ENCODE ChIP-seq data sets). We show that ChIP-Enrich has a well-calibrated type I error rate using permuted ENCODE ChIP-seq data sets; in contrast, two commonly used gene set enrichment methods, Fisher's exact test and the binomial test implemented in Genomic Regions Enrichment of Annotations Tool (GREAT), can have highly inflated type I error rates and biases in ranking. We identify DNA-binding proteins, including CTCF, JunD and glucocorticoid receptor α (GRα), that show different enrichment patterns for peaks closer to versus further from transcription start sites. We also identify known and potential new biological functions of GRα. ChIP-Enrich is available as a web interface (http://chip-enrich.med.umich.edu) and Bioconductor package.

Identification of a secondary promoter of CASP8 and its related transcription factor PURα.

Caspase-8 (CASP8) is an essential initiator of apoptosis and is associated with many diseases in humans including esophageal squamous cell carcinoma. CASP8 produces a variety of transcripts, which might perform distinct functions. However, the cis and trans transcriptional determinants that control CASP8 expression remain poorly defined. Using a series of luciferase reporter assays, we identified a novel secondary promoter of CASP8 within chr2: 202,122,236 to 202,123,227 and 25 kb downstream of the previously described CASP8 promoter. ENCODE ChIP-seq data for this novel promoter region revealed several epigenetic features, including high levels of histone H3 lysine 27 acetylation and lysine 4 methylation, as well as low levels of CpG island methylation. We developed a mass spectrometry based strategy to identify transcription factors that contribute to the function of the secondary promoter. We found that the transcription activator protein PURα is specifically involved in the transcriptional activation of the secondary promoter and may exert its function by forming a complex with E2F-1 and RNA polymerase II. PURα can bind to both DNA and RNA, and functions in the initiation of DNA replication, regulation of transcription. We observed that knockdown of PURα expression decreased the transcriptional activity of the secondary promoter and mRNA expression of CASP8 isoform G. Although the physiologic roles of this secondary promoter remain unclear, our data may help explain the complexity of CASP8 transcription and suggest that the various caspase 8 isoforms may have distinct regulations and functions.

Targeting Folate Metabolism In Acute Myelogenous Leukemia

There is increasing evidence that deranged metabolism is an important mechanism of cancer pathogenesis. We conducted multiple genomic analyses of publicly available acute myelogenous leukemia (AML) data sets that revealed a critical role for one carbon and nucleotide metabolism, particularly mitochondrial, in a subset of AML samples. One carbon metabolism is a complex series of pathways involving several amino acids, the synthesis of purines, thymidylate, S-adenosylmethionine, and the support of cellular methylation reactions. SHMT2, MTHFD2, and MTHFD1L are the major enzymes functional in the one carbon folate pathway in the mitochondria. MTHFD2 is a NAD-dependent, mitochondrial methylenetetrahydrofolate dehydrogenase and cyclohydrolase, derived from a similar trifunctional cytoplasmic protein. In the mitochondria, the formyltetrahydrofolate synthetase activity is performed by MTHFD1L. We noted that these enzymes are downregulated with suppression of MYC. Gene set enrichment analysis (GSEA) of cell lines treated with JQ1, a small molecule BET bromodomain inhibitor which suppresses MYC, showed a significant enrichment in genes of the one carbon pool by folate KEGG pathway. We show that treatment of AML cells with JQ1 causes a decrease in MTHFD2 and MTHFD1L levels. This is recapitulated with knockdown of MYC with four shRNAs in multiple AML cell lines. Analysis of ENCODE ChIP-Seq data revealed MYC binding at SHMT2, MTHFD2 and MTHFD1L promoters, which we confirmed with ChIP-qPCR in human AML cell lines. Moreover, Independent component analysis (ICA) of primary AML samples in The Cancer Genome Atlas (TCGA) showed a significant correlation between high MTHFD2 and high MYC expression and a metabolic gene expression signature.MTHFD2 is differentially expressed in transformed and non-differentiated cells, and is thus an attractive drug target given its limited expression in normal tissues. Knockdown of MTHFD2 with four shRNAs in five AML cell lines caused a decrease in cell proliferation as measured by BrdU incorporation and a decrease in colony formation in methylcellulose. MTHFD2 knockdown also induced myeloid differentiation, as measured by Cd11b expression, morphologic changes and induction of a previously validated AML differentiation gene expression signature. AML cells transduced with MTHFD2-directed shRNAs demonstrated attenuated growth in an orthotopic mouse model of AML at day 15 post-injection. We next deployed a doxycycline inducible shRNA system to demonstrate that shRNAs directed against MTHFD2 cause a decrease in AML burden in mice with established disease as measured by bioluminescence with an increase in survival. Metabolite profiling is currently underway to further elucidate the metabolic consequences of MTHFD2 loss in AML.In summary, in silico analyses of primary patient AML data sets revealed a subset of AML samples enriched for a metabolic gene expression signature. We demonstrate that MYC is a regulator of the one carbon folate pathway, modulating expression of SHMT2, MTHFD2 and MTHFD1L. In vitro and in vivo data strongly supports a critical role for MTHFD2 in AML pathogenesis and its potential as a new target for AML therapy. Disclosures:No relevant conflicts of interest to declare.

Detection of Regulatory SNPs in Human Genome Using ChIP-seq ENCODE Data

A vast amount of SNPs derived from genome-wide association studies are represented by non-coding ones, therefore exacerbating the need for effective identification of regulatory SNPs (rSNPs) among them. However, this task remains challenging since the regulatory part of the human genome is annotated much poorly as opposed to coding regions. Here we describe an approach aggregating the whole set of ENCODE ChIP-seq data in order to search for rSNPs, and provide the experimental evidence of its efficiency. Its algorithm is based on the assumption that the enrichment of a genomic region with transcription factor binding loci (ChIP-seq peaks) indicates its regulatory function, and thereby SNPs located in this region are more likely to influence transcription regulation. To ensure that the approach preferably selects functionally meaningful SNPs, we performed enrichment analysis of several human SNP datasets associated with phenotypic manifestations. It was shown that all samples are significantly enriched with SNPs falling into the regions of multiple ChIP-seq peaks as compared with the randomly selected SNPs. For experimental verification, 40 SNPs falling into overlapping regions of at least 7 TF binding loci were selected from OMIM. The effect of SNPs on the binding of the DNA fragments containing them to the nuclear proteins from four human cell lines (HepG2, HeLaS3, HCT-116, and K562) has been tested by EMSA. A radical change in the binding pattern has been observed for 29 SNPs, besides, 6 more SNPs also demonstrated less pronounced changes. Taken together, the results demonstrate the effective way to search for potential rSNPs with the aid of ChIP-seq data provided by ENCODE project.

Genome-Wide Signatures of Transcription Factor Activity: Connecting Transcription Factors, Disease, and Small Molecules

Identifying transcription factors (TF) involved in producing a genome-wide transcriptional profile is an essential step in building mechanistic model that can explain observed gene expression data. We developed a statistical framework for constructing genome-wide signatures of TF activity, and for using such signatures in the analysis of gene expression data produced by complex transcriptional regulatory programs. Our framework integrates ChIP-seq data and appropriately matched gene expression profiles to identify True REGulatory (TREG) TF-gene interactions. It provides genome-wide quantification of the likelihood of regulatory TF-gene interaction that can be used to either identify regulated genes, or as genome-wide signature of TF activity. To effectively use ChIP-seq data, we introduce a novel statistical model that integrates information from all binding “peaks” within 2 Mb window around a gene's transcription start site (TSS), and provides gene-level binding scores and probabilities of regulatory interaction. In the second step we integrate these binding scores and regulatory probabilities with gene expression data to assess the likelihood of True REGulatory (TREG) TF-gene interactions. We demonstrate the advantages of TREG framework in identifying genes regulated by two TFs with widely different distribution of functional binding events (ERα and E2f1). We also show that TREG signatures of TF activity vastly improve our ability to detect involvement of ERα in producing complex diseases-related transcriptional profiles. Through a large study of disease-related transcriptional signatures and transcriptional signatures of drug activity, we demonstrate that increase in statistical power associated with the use of TREG signatures makes the crucial difference in identifying key targets for treatment, and drugs to use for treatment. All methods are implemented in an open-source R package treg. The package also contains all data used in the analysis including 494 TREG binding profiles based on ENCODE ChIP-seq data. The treg package can be downloaded at http://GenomicsPortals.org.

A probabilistic approach to learn chromatin architecture and accurate inference of the NF-κB/RelA regulatory network using ChIP-Seq

Using nuclear factor-κB (NF-κB) ChIP-Seq data, we present a framework for iterative learning of regulatory networks. For every possible transcription factor-binding site (TFBS)-putatively regulated gene pair, the relative distance and orientation are calculated to learn which TFBSs are most likely to regulate a given gene. Weighted TFBS contributions to putative gene regulation are integrated to derive an NF-κB gene network. A de novo motif enrichment analysis uncovers secondary TFBSs (AP1, SP1) at characteristic distances from NF-κB/RelA TFBSs. Comparison with experimental ENCODE ChIP-Seq data indicates that experimental TFBSs highly correlate with predicted sites. We observe that RelA-SP1-enriched promoters have distinct expression profiles from that of RelA-AP1 and are enriched in introns, CpG islands and DNase accessible sites. Sixteen novel NF-κB/RelA-regulated genes and TFBSs were experimentally validated, including TANK, a negative feedback gene whose expression is NF-κB/RelA dependent and requires a functional interaction with the AP1 TFBSs. Our probabilistic method yields more accurate NF-κB/RelA-regulated networks than a traditional, distance-based approach, confirmed by both analysis of gene expression and increased informativity of Genome Ontology annotations. Our analysis provides new insights into how co-occurring TFBSs and local chromatin context orchestrate activation of NF-κB/RelA sub-pathways differing in biological function and temporal expression patterns.

Genetic and Functional Investigation of Germline JAK2 Alleles That Predispose to Myeloproliferative Neoplasms

Abstract 124A somatic activating mutation in the pseudokinase domain of JAK2 (JAK2V617F) is found in the majority of patients with myeloproliferative neoplams (MPN). Using a genome-wide approach, we and others identified a germline haplotype in the JAK2 locus (rs10974944) that predisposes to the development of JAK2V617F-positive MPN. Importantly, this haplotype is associated with in cis acquisition of the somatic JAK2 mutation. An extended linkage disequilibrium block of 300kb is observed at this locus and others have reported an association between single nucleotide polymorphisms (SNPs) within this haplotype and risk of inflammatory bowel disease consistent with increased JAK-STAT signaling in patients who carry this risk haplotype. The mechanism by which this germline locus contributes to MPN pathogenesis has not been delineated. We hypothesized that the identified allele heightens the risk of developing MPN by either a) increasing the mutational rate at the JAK2 locus, or b) imparting a selective advantage on cells that acquire the somatic mutation through increased JAK2 expression.To address the mutational hypothesis, we performed targeted, high coverage, next-generation sequencing of the entire haplotype and of the entire JAK2 locus in 12 patients homozygous for the risk allele, and in 12 patients without the risk allele. Importantly we did not note an increased rate of somatic mutations (coding or noncoding) in patients homozygous for the risk haplotype. In addition, we expanded our GWAS to include 200 additional cases genotyped using the Illumina 1,000,000 SNP genotyping array. The number of SNPs did not significantly differ between the risk haplotype and non-risk haplotype, further suggesting that there is no increase in mutability attributable to the risk genotype. By constructing a phylogenetic tree, we found that the risk haplotype is ancestral to modern humans and demonstrates evidence of ancestral positive selection, although there was no evidence of recent selection at this locus. Taken together these data suggest that the JAK2 MPN risk hapolotype does not increase the mutational rate at this locus.We next investigated whether the risk allele affects JAK2 expression in hematopoietic cells. We compared the relative abundance of an exonic SNP within the haplotype using matched genomic DNA and cDNA from 8 MPN patients heterozygous for the risk allele. In each case we found that the risk allele was more highly expressed in cDNA compared to the non-risk allele despite similar allelic ratios in genomic DNA. The results suggest an increase in allele-specific expression of JAK2 associated with the JAK2 risk haplotype. We annotated all germline variants in cis with the JAK2 risk haplotype using next generation sequencing data of the entire JAK2 haplotype from MPN patients and from the 1000 Genomes project. We then used Encode ChIP-seq data and the ConSite web-based transcription factor binding prediction model to identify SNPs within the JAK2 haplotype that affect transcription factor binding. We identified a SNP within the JAK2 promoter region, rs1887428, as a potential causative allele because it is significantly associated with MPN (p=9.11E-11) and c-Fos/c-Jun is predicted to preferentially bind to the risk allele. In order to determine if this preferential transcription factor binding leads to a haplotype-specific increase in expression of JAK2, we performed luciferase assays in cells expressing reporter constructs with the two different alleles at rs1887428. Importantly, this demonstrated increased transcriptional activity in cells containing the risk allele at rs1887428, suggesting that enhanced transcription factor binding at rs1887428 may lead to increased JAK2 expression and confer a selective advantage on cells containing the risk haplotype. The effects of allelic variation at rs1887428 on JAK2 expression in hematopoietic cells will be presented.Taken together, our data suggests that the JAK2 MPN risk haplotype contributes to MPN pathogenesis through allele-specific transcription factor binding and JAK2 expression, which increases the selective advantage of JAK2 mutations arising on the risk haplotype. This study provides insight into how predisposing loci increase the predisposition to MPN and to other hematopoietic malignancies. Disclosures:No relevant conflicts of interest to declare.