Genome-wide association study (GWAS) has identified more than 30 loci associated with type 2 diabetes (T2D) in Caucasians. However, genomic understanding of T2D in Asians, especially Han Chinese, is still limited.−17, OR 1.28) and C2CD4A/B  in Han Chinese.A two-stage GWAS was performed in Han Chinese from Mainland China. The discovery stage included 793 T2D cases and 806 healthy controls genotyped using Illumina Human 660- and 610-Quad BeadChips; and the replication stage included two independent case-control populations  genotyped using TaqMan assay. We validated the associations of KCNQ1 (rs163182, p = 2.085×10Our study represents the first GWAS of T2D with both discovery and replication sample sets recruited from Han Chinese men and women residing in Mainland China. We confirmed the associations of KCNQ1 and C2CD4A/B with T2D, with the latter for the first time being examined in Han Chinese. Arguably, eight more independent loci were replicated in our GWAS. Type 2 diabetes (T2D) is a complex disease hallmarked by insulin resistance and pancreatic beta-cell dysfunction Genetic analysis of T2D and related diseases (such as obesity and monogenic diabetes) and traits (such as fasting plasma glucose levels) has greatly improved our understanding of glucose homeostasis and energy balance in both physiological and pathological conditions, some of which has brought novel preventive and therapeutic options KCNQ1 with T2D was first independently identified by two GWASs in Japanese PTPRD) and serine racemase (SRR) genes Extending GWAS to populations of diverse descents is valuable, because different frequencies of genetic variants and patterns of linkage disequilibrium (LD) due to population backgrounds may strongly affect the power and potential of GWAS to discover and/or refine certain genetic loci associated with disease In the discovery stage, 998 T2D patients of Han Chinese descent recruited in Shanghai were genotyped using Illumina Human 660-Quad BeadChips. Our control population was derived from a glucose survey in a community in Shanghai and was genotyped using Illumina Human 660- and 610-Quad BeadChips. After stringent quality control, we obtained 561,694 SNPs that were common to both genotyping platforms with both average call rates of >99%. To ensure that case and control groups were genetically matched, in addition to close examination of their geographic origins, MDS was used to exclude population outliers, the result of which was further confirmed by PCA, which showed minimal evidence for population stratification . 474,515P ≤10−4) for genotyping in an independent case-control population from Shanghai (n = 2620)  as a fast-track replication analysis [P<0.10 , were located in the same locus in gene KCNQ1 as previously reported. The remaining SNP, rs3773159 , is likely to represent a novel susceptibility locus for T2D in the population.We selected the top 30 significantly associated SNPs representing 15 genomic regions in the discovery stage  and pooled analysis (Replication 1: 2660 cases and 2068 controls) showed a nominally significant association of rs3773159 with T2D (P<0.05 (NOTCH2), rs2943641 (IRS1), rs2120825 , rs734312 (WFS1), rs896854 (TP53INP1), rs10906115 (CDC123/CAMK1D), rs7901695 (TCF7L2), rs7903146 (TCF7L2), rs1552224 (CENTD2), rs1370176 (C2CD4A/B), rs1436953 (C2CD4A/B), rs7172432 (C2CD4A/B), and rs1436955 (C2CD4B). If we adopt a less stringent threshold of P<0.10, 4 more SNPs representing 3 genomic regions showed significant association with T2D in the discovery stage (HHEX), rs7923837 (HHEX), rs8050136 (FTO), and rs780094 (GCKR).We checked a total of 37 genomic loci previously reported to be associated with T2D P<0.05 : rs27938ry stage : rs11118C2CD4A/B on chromosome 15 – were exactly the lead SNPs in a three-stage GWAS recently reported involving a total of ∼19000 Japanese P = 0.1134, 0.03651, and 0.01884, respectively). Genotyping in the remaining 1602 cases and 506 controls of Replication 1 and pooled analysis (Replication 1) expectedly rendered these associations significant . rs163184, the SNP most significantly associated with T2D in KCNQ1 in our discovery stage, is also the lead SNP in two other independent studies KCNQ1 were associated with T2D in different populations, and our GWAS worked in identifying such variants.In Han Chinese population, our study validated previously known susceptibility loci of T2D, among which SNPs in KCNQ1, our study rediscovered several SNPs in additional susceptibility loci of T2D originally identified in populations of different ancestries, and SNPs in three such loci came to our notice. The first is C2CD4A/B in 15q21.3, which was quite recently reported by a GWAS of T2D involving about 8000 Japanese in their discovery stage GWASP = 3.264×10−4), but did not reach the cutoff P = 10−4, mainly due to our limited power because of small sample size. Two more SNPs reported, namely rs1370176 and rs1436953, were in the same locus and associated with T2D in our GWAS. We noticed that another recent work reported an association of rs1436955 with T2D in Han Chinese, which was indeed in the same locus; albeit in silico replication strategy might have prevented their further analysis C2CD4A/B locus are associated with T2D in Central Han Chinese population residing in Mainland China. Further studies are required to investigate whether such associations exist in Southern and Northern Han Chinese populations and identify the causal variants.Aside from variants in TP53INP1  and CENTD2 ; both of them were discovered in a large-scale meta-analysis comprising more than one hundred thousand individuals of European descent (DIAGRAM+). Our GWAS was likely to validate these two newly identified loci in the Han Chinese population, but further replication is required to examine their effects. Moreover, in light of the small sample size of our GWAS stage, these results support the notion that GWAS in Han Chinese has potential to identify novel risk loci of T2D.The other two loci are Our study represents the first GWAS with both discovery and replication sample sets recruited both Han Chinese men and women residing in Mainland China. Han Chinese is geographically and genetically heterogeneous and has subpopulation structures, which may have considerable effect on design and interpretation of GWAS KCNQ1showed the strongest association, and variants in C2CD4A/B were first replicated in Han Chinese residing in Mainland China.In conclusion, our genome-wide association study confirmed several T2D susceptibility loci previously identified in Caucasians and Japanese, among which variants in This study was approved by the Institutional Review Board of the Ruijin Hospital, Shanghai Jiao Tong University School of Medicine and was in accordance with the principle of the Helsinki Declaration II. The written informed consent was obtained from each participant.The GWAS genotyped 998 T2D patients recruited from outpatient departments of Ruijin Hospital, and 1002 healthy controls obtained from one glucose survey in Youyi community, Baoshan district, Shanghai P<10−7). SNPs on the X, Y and mitochondrial chromosomes and copy number variation (CNV) probes were also excluded from further analysis.Genomic DNA was extracted from peripheral blood by standard phenol/chloroform-based method. In the discovery stage, genotyping was conducted by using Illumina Human 660- and 610-Quad BeadChips at the Chinese National Human Genome Center at Shanghai. Genotyping was performed according to the Infinium HD protocol from Illumina. Quality control involved exclusion of SNPs with a call rate <90%, a minimum allele frequency <0.01, and/or a significant deviation from Hardy-Weinberg equilibrium (HWE) in the controls  on an ABI PRISM 7900HT Sequence Detection System following the manufacturer's protocol. In our study, the call rate ranged from 97.95% (rs3773159 in the Replication 1) to 99.33% (rs3773159 in Replication 2). There is no significant difference of SNP calling between the case and the control groups. The average consensus rate in the duplicate samples (n = 100) was 100%.Identification of cryptic relatedness among individuals in the discovery stage was based on pairwise identity by state using the PLINK 1.07 software Replication analysis was performed by first analyzing replication samples separately and then combining them with the discovery sample set Figure S1Multidimensional scaling analysis (MDS) plot. MDS plot by PLINK of the 793 cases and 806 controls shows no evident population stratification and outliers. Blue: control; pink: case.(TIF)Click here for additional data file.Figure S2Principal component analysis (PCA) plot. PCA plot by EIGENSTRAT of the 793 cases and 806 controls shows no evident population stratification and outliers. Green: control; red: case.(TIF)Click here for additional data file.Figure S3Quantile-quantile (Q-Q) plot for the trend test. (λ = 1.08). Q-Q plot for the Cochran-Armitage trend test for 474,515 SNPs in 793 cases and 806 controls. λ = 1.08 and minimal evidence of association due to population stratification was observed.(TIF)Click here for additional data file.Figure S4Manhattan plot for GWAS data. The x-axis represents chromosomal location of 474,515 SNPs examined and the y-axis represents –log10 of the P value of the Cochran-Armitage trend test under an additive model. A cutoff line was drawn at the significance threshold of 10−4.(TIF)Click here for additional data file.Table S1SNPs selected for fast-track replication. RAF(T2D) and RAF(NC), risk allele frequency in T2D cases and controls, respectively. OR, odds ratio for risk allele.(DOC)Click here for additional data file.Table S2SNPs in previously reported T2D loci. RAF(T2D) and RAF(NC), risk allele frequency in T2D cases and controls, respectively. OR, odds ratio for risk allele. *, P<0.05. **, P<0.10(DOC)Click here for additional data file.


This model recapitulates an in vivo process in which AEC transition from one differentiated cell type to another during regeneration following lung injury. Interrogation of histone marks over time revealed enrichment of specific transcription factor binding motifs within regions of changing chromatin structure. Cross-referencing of these motifs with pathways showing transcriptional changes revealed known regulatory pathways of distal alveolar differentiation, such as the WNT and transforming growth factor beta (TGFB) pathways, and putative novel regulators of adult AEC differentiation including hepatocyte nuclear factor 4 alpha (HNF4A), and the retinoid X receptor (RXR) signaling pathways. Inhibition of the RXR pathway confirmed its functional relevance for alveolar differentiation. Our incorporation of epigenetic data allowed specific identification of transcription factors that are potential direct upstream regulators of the differentiation process, demonstrating the power of this approach. Integration of epigenomic data with transcriptomic profiling has broad application for the identification of regulatory pathways in other models of differentiation.Elucidation of the epigenetic basis for cell-type specific gene regulation is key to gaining a full understanding of how the distinct phenotypes of differentiated cells are achieved and maintained. Here we examined how epigenetic changes are integrated with transcriptional activation to determine cell phenotype during differentiation. We performed epigenomic profiling in conjunction with transcriptomic profiling using  Understanding the role of epigenetic control of gene expression is critical to the full description of biological processes, such as development and regeneration. Herein we utilize the differentiation of cells from the distal lung to gain insight into the correlation between the epigenetic landscape, molecular signaling events, and eventual changes in transcription and phenotype. We found that by integrating epigenetic profiling with whole genome transcriptomic data we were able to determine which molecular signaling events were activated and repressed during adult alveolar epithelial cell differentiation, and we identified epigenetic changes that contributed to these changes. Furthermore, we validated the role of one of these predicted but not previously identified pathways, retinoid X receptor signaling, in this process. Ac), found at promoters and enhancers of actively transcribed genes me3) confers repression through binding of the polycomb repressive complex (PRC1/2) and chromatin compaction Ac and H3K27me3 marks usually occur in distinct cell-type specific genomic regions. Many studies have examined the differentiation of stem cells into a variety of differentiated cell types, in processes that traverse large phenotypic (and presumably epigenetic) distances in vitro in a manner closely mimicking both normal maintenance and regeneration following lung injury Over the past two decades the relationship between gene expression and chromatin structure has been increasingly recognized in vitro when purified primary AT2 cells are plated under defined cell culture conditions The distal lung alveolar epithelium consists of two major cell types: cuboidal surfactant-producing AT2 cells and elongated type 1 (AT1) cells that facilitate gas exchange. AT2 cells are the implicated precursors of AT1 cells, and through differentiation restore function of damaged distal lung epithelium Differentiation of purified primary human AT2 cells into AT1-like cells represents a unique kinetic model system to study the process of epithelial cell differentiation without the caveats of cell line immortalization or mixed tissue analysis. Here, we simultaneously profiled the transcriptomic and epigenomic changes of differentiating human alveolar epithelial cells (AEC). Detailed integrated analysis facilitated identification of regulatory networks and participating transcription factors, pointing to roles for known and novel signaling pathways in distal lung epithelial differentiation. To our knowledge this is the first integrated analysis of human primary epithelial cell differentiation.SFTPC, upregulation of AQP5, and establishment of transepithelial resistance AT2 cells were isolated from the lungs of three non-smoker donors  and platRaw expression data across all samples had similar distributions , GEO accPDPN, CAV1, and AQP5) were also assessed using qRT-PCR and values were plotted for comparison alongside the top differentially expressed genes  excluding the technical duplicates and a moderated t-test was used to determine significance of changes in gene expression from D0 (AT2 cells) to D8 (AT1-like cells). 6755 probes (5651 genes) showed statistically significant changes in gene expression; 4196 upregulated probes (3500 genes) and 2559 downregulated probes (2171 genes) . These cAKT), protein kinase C (PRKC), and the RAS family RAB genes, implicated in endocytosis, while FBJ murine osteosarcoma viral gene homolog (FOS) was the center of interconnectivity in the top downregulated network  revealed that the top upregulated pathways were cell assembly and organization, cell movement, cell-cell signaling, tissue development, and lipid metabolism, all of which are consistent with AT2 cells differentiating into larger, flat AT1 cells, while the most downregulated pathways pertained to cell proliferation, cell death, inflammatory response, cell cycle and infectious processes . Signali network . Analysi network .−16). Separating significantly up- or downregulated genes yielded similar degrees of overlap  and the Model-based Analysis of ChIP-Seq (MACS) methods. Each analysis revealed thousands of enriched regions, with a significant fraction (20–40%) shared between D0 and D8 and the remainder of them specific to D0 or D8  , transcription factor 3 (TCF3 or E2A), TCF4 , and RXR. TFBSs strongly associated with repressive chromatin changes included those for forkhead box (FOX) proteins FOXA1 and FOXA2, TATA-box binding protein TBP, and CCAAT/enhancer-binding protein CEBP. Two example loci illustrate the location of particular motifs within differentially marked chromatin regions – an upregulated gene, frizzled family receptor 2 (FZD2), which shows spreading acetylation and loss of H3K27me3, is predicted to have an RXR site within activating chromatin marks (PGC), shows loss of acetylation but no gain of H3K27me3 and is predicted to have numerous FOXA1 sites within silenced regions (Ac and H3K27me3 from D0 to D8.Using subsets of the same batches of human AT2 cells (D0) and fully differentiated AT1-like cells (D8) used for expression analyses, we assessed alterations to the chromatin environment by chromatin immunoprecipitation followed by sequencing (ChIP-seq). Specifically, H3K9/14D0 or D8 . ChangesD0 or D8 . The traH3K27me3 . We thentive D8) , revealiin marks , while a regions . These tActivating chromatin changes were strongly associated with upregulated gene expression, while repressive chromatin changes were loosely associated with downregulated gene expression . 3011 5. Since wdirect transcriptional targets for each pathway, such as PGC, encoding an AT2-specific protease FZD2, encoding a WNT receptor and candidate target of RXR  revealed 34 predicted PPARA:RXR heterodimer binding sites   cells revealed that UVI-3003 inhibited ∼50% of Aqp5 promoter activity , thyroid hormone receptor (THR), the vitamin D receptor (VDR), farnesoid X receptor (NR1H4) and other nuclear receptors (NRs), as well as the family of peroxisome proliferator-activated receptors (PPARs) me3 mark . To testme3 mark  and signme3 mark . Rescue ng sites  and an an, Cav1) . Luciferactivity . ChIP ashenotype . Taken tin vitro from AT2 cells, exhibit many properties of AT1 cells in vivo, including morphology and expression of known phenotypic markers. Direct isolation of fragile AT1 cells from human lung is very challenging in vitro into AT1-like cells offers a tractable model system to study not only the transcriptomic and epigenomic differences between these two cell types, but also the kinetic mechanisms controlling epithelial cell differentiation. Transcriptomic analysis of differentiating primary human and rat AEC identified thousands of genes undergoing significantly altered expression, a large number of which overlap between the two species. ChIP-seq identified D0- and D8-specific acetylation (H3K9/14Ac) and methylation events (H3K27me3) and allowed identification of corresponding TFBSs enriched within AT2- or AT1-specific chromatin patterns. Interestingly, almost all of the TFBS enriched within D8-specific H3K9/14Ac regions were also enriched within D0-specific H3K27me3 regions, and conversely for D0-specific H3K9/14Ac and D8-specific H3K27me3. This near perfect concordance is unexpected since H3K27me3 is thought to represent only one of several silencing mechanisms active in development AT1-like cells, differentiated Ac and loss of H3K27me3, while downregulation was primarily associated with loss of H3K9/14Ac. Approximately half of the genes showing altered expression were not associated with either chromatin mark. This could be because marks were present but distant from the gene, or because other chromatin marks or regulatory mechanisms were involved in their up or downregulation. With application of ChIP-seq to the examination of other chromatin marks, remodeling complexes, and transcription factors, and the addition of information on nucleosome positioning, non-coding RNAs, microRNAs, chromatin conformation capture technologies, and DNA methylation, the current model system will lend itself well to a detailed understanding of the epigenomic basis for the differentiation of adult epithelial cells.Integrated analysis showed that upregulation of gene expression was associated with individual or combined gain of H3K9/14This study demonstrates how expression datasets and chromatin mapping are a potent combination to obtain an integrated picture of signaling pathway activity, transcription factors and their genomic targets. Transcriptional profiling can identify altered gene expression and corresponding regulatory pathways, but identifying transcription factors is difficult without knowing which genomic regions are implicated; epigenomic profiling can pinpoint the specific genomic regions where transcription factors and other regulatory proteins are likely to bind. Our approach revealed known regulators, such as TGFB, WNT, FOXA1 and FOXA2 Aqp5 promoter by UVI-3003, as well as the specific detection of RXR on the Aqp5 promoter in rAT1-like cells. Retinoic acid receptors (RARs) are one of the many potential binding partners with RXRs and numerous reports have implicated retinoic acid and/or RARs in lung development and injury in vitro as well as ChIP data showing increased promoter occupancy in AT1-like cells on day 8 support its functional role and illustrate the utility of our system and the potential of epigenomic/transcriptomic data integration to reveal novel regulators of biologic processes.As proof-of-principle, we investigated whether RXR signaling was required for the differentiation process of adult alveolar epithelium. Use of an RXR-specific inhibitor delayed differentiation as measured by inhibition of AT1-specific AQP5 expression and delayed TER. A role for RXR in normal AQP5 expression in AT1 cells is further supported by the inhibition of the in vitro differentiation can serve as a powerful tool for the mechanistic investigation of normal and aberrant epithelial cell differentiation.In summary, our analysis enabled identification of known and novel signaling pathways, gene regulatory networks and associated TFBS implicated in morphologic and phenotypic changes that occur during AEC differentiation. Full characterization of normal differentiation is critical to determine the precise mechanisms that are perturbed in disease. In the distal lung, this might shed light on the molecular basis of chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis. The analysis presented here shows that purified human primary epithelial cells undergoing Remnant human transplant lungs were obtained in compliance with Institutional Review Board-approved protocols for the use of human source material in research (HS-07-00660) and processed within 3 days of death. Rat AT2 cells were isolated in compliance with IACUC protocol #11360.SFTPC and AQP5 expression using RNA extracted with the Illustra TriplePrep Kit , and by measuring transepithelial resistance. Rat AT2 cells were isolated as previously described Human lung tissue was processed as previously described Freshly isolated hAT2 cells were fixed with 4% paraformadehyde for 10 min at room temperature (RT), permeabilized with 0.3% Triton, and blocked with CAS blocking reagent  for 30 min at RT. Slides were incubated with rabbit anti-pro-SFTPC (Seven Hills #WRAB-SPC serum) or anti-PTPRC (Santa Cruz sc-25590) antibodies and diluted in CAS-block at 4°C overnight. Slides were washed in Tris-Buffered Saline & Tween 20 (TBST) and incubated with anti-rabbit-FITC fluorescent secondary antibody in CAS-block for 1 hr at RT. For vimentin staining, mouse anti-VIM (Sigma V2258) and biotinylated anti-mouse IgM (Vector # BA-2020) antibodies were used. Sections were viewed with a NIKON Eclipse microscope equipped with a QImaging Retica 200R charge-coupled-device camera . Images were processed with the NIS-Elements BR program (NIKON).www.ingenuity.com) or DAVID 1 µg of RNA was converted into cRNA using Illumina TotalPrep RNA amplification kit,  and used for Illumina HT-12v4 or RatRef-12 expression analysis at the Southern California Genotyping Consortium, University of California Los Angeles. BeadStudio was used to convert images to raw signal data. Using R (version 2.11.1), Variant Stabilization and Normalization (VSN) was performed using LUMI RNA was reverse transcribed using random hexamers and M-MLV reverse transcriptase per manufacturer's guidelines (Invitrogen), followed by qRT-PCR using SYBR green  with primers listed in Ac , H3K27me3 , POL2 , and RXR  were performed as previously described Gapdh promoter, POL2 was used as a positive control. For human ChIP-seq, positive control loci were the promoter regions of GAPDH and MUC4 for H3K9/14Ac and H3K27me3 respectively; ≥10-fold enrichment was considered successful. ChIP-seq libraries were constructed using the New England Biolabs library prep kit . ChIP products underwent Illumina GAII single-end sequencing; reads were aligned to the hg18 human genome build using the MAQ 0.7.1 aligner. All datasets are deposited in the public GEO database (GEO# GSE38571).Chromatin immunoprecipitations for H3K9/14All datasets are deposited in the public GEO database (GEO# GSE38571).http://cistrome.org/ap/) was performed using default parameters and input DNA for background normalization. SICER- and MACS-called peaks had a large degree of overlap, as measured by the correlation coefficient (Genome Graphs (http:/genome.ucsc.edu). A lack of correlation was observed between H3K9/14Ac and H3K27me3 (Genome Graphs.Integrative Genomics Viewer v1.5 (The Broad Institute) was used to visually inspect peak quality. SICER fficient , calculaH3K27me3  [66]–[70H3K27me3 . DifferePeaks were annotated to the nearest transcription start site (TSS) and motif analysis was performed with HOMER 6 rat AT2 (≥95% purity) cells were plated on 1.1-cm2 polycarbonate filters (Corning Costar #3401) and treated with either 7.5 µM UVI-3003  or DMSO vehicle control from the time of plating (D0) through completion of the study. Whole cell lysates were extracted in 2% SDS lysis buffer ).1×10Western blots were performed as previously described 4 cells per well on 24-well plates 1.5 days prior to transfection. Duplicate wells were transiently transfected with 500 ng rAqp5-luc containing the 4.3 kb rat Aqp5 promoter or pGL2 empty vector using Superfect (Qiagen). Three hours post-transfection, media was changed to contain 7.5 µM UVI-3003 or DMSO vehicle control. 48 hours post transfection, luciferase assays were performed as previously described Mouse lung epithelial cells (MLE-15) were plated at a density of 4×10Figure S12) for all 3 donor lungs. E) AT1-like hAEC differentiated and stained for tight junction protein. PI = propidium iodide, DNA stain (blue), TJP1 = tight junction protein 1 (orange).Quality control for human AT2 cell extraction and differentiation. A) Information on the three subjects from whom AEC were obtained, showing the color-coding used in (TIF)Click here for additional data file.Figure S2Raw human expression profiling. A) Density plot of raw sample distributions. B) Boxplot of raw sample intensity distributions. C) Raw ranked mean standard deviation of signal for all samples. D) Dendrogram of sample similarity based on top variant genes, those with standard deviation/mean >0.1. E) Distribution of raw p-values.(TIF)Click here for additional data file.Figure S3Preprocessed and normalized human expression profiling. A) Density plot of VSN background corrected and normalized sample distributions. B) Boxplot of VSN-corrected sample intensity distribution. C) Normalized ranked mean standard deviation of signal for all samples. D) Dendrogram of sample similarity based on top variant genes, those with standard deviation/mean >0.1. E) Principal component analysis of normalized sample data. Each bar represents a source of variation. Bar height indicates amount of variation. F) Distribution of p-values for normalized data (x-axis) and their rate of occurrence (y-axis).(TIF)Click here for additional data file.Figure S4Stability of human gene expression clusters. A) Heatmap clustering of top 2% of variant genes between samples, clustering using Ward's method. B) Heatmap clustering of top 10% of variant genes between samples, clustering using Ward's method. C) Silhouette plot using Euclidean distances. Clusters were defined from Heatmap at major branch points as D0 (cluster 1), D2 (cluster 2), and D4, 6, 8 (cluster 3).(TIFF)Click here for additional data file.Figure S5qRT-PCR of top up- and down-regulated genes. Graphs represent relative transcript abundance at each time point during differentiation. Fold change is expressed relative to transcript abundance at D0 (AT2 cells). 18S rRNA served as normalization control. Error bars represent standard error of the mean (SEM) from biological triplicates.(TIF)Click here for additional data file.Figure S6IPA up- and down-regulated networks of human gene expression data. A) IPA upregulated networks. Intensity of red color indicates degree of upregulation, dark red = highly upregulated, light red = modestly upregulated. Blue lines highlight AKT connections. B) IPA downregulated networks. Intensity of green color indicates degree of downregulation, dark green = heavily downregulated, light green = modestly downregulated. Blue lines highlight FOS (AP1) connections.(TIF)Click here for additional data file.Figure S710 BH-corrected p-value of significance for enrichment as compared to random sampling of the reference set of genes.DAVID pathways analysis of human gene expression data. Separation of the 3000 upregulated genes with greatest calculated significance (red bars) and all significantly downregulated genes (green bars). Data bars expressed as −log(TIF)Click here for additional data file.Figure S8Raw rat expression profiling. A) Density plot of raw sample distributions. B) Boxplot of raw sample intensity distributions. C) Raw ranked mean standard deviation of signal for all samples. D) Dendrogram of sample similarity based on top variant genes, those with standard deviation/mean >0.1. E) Distribution of raw p-values. F) Principal component analysis of sample distribution. Color indicates lung preparation by rat.(TIF)Click here for additional data file.Figure S9Preprocessed and normalized rat expression profiling. A) Density plot of VSN background-corrected and normalized sample distributions. B) Boxplot of VSN-corrected sample intensity distribution. C) Ranked mean standard deviation of signal for all normalized samples. D) Dendrogram of sample similarity based on top variant genes, those with standard deviation/mean >0.1. E) Distribution of p-values from normalized data (x-axis) and their rate of occurrence (y-axis). F) Principal component analysis of normalized sample data. Each bar represents a source of variation. Bar height indicates amount of variation.(TIF)Click here for additional data file.Figure S10Stability of rat gene expression clusters. A) Heatmap clustering of top 20% of variant genes between samples, clustering using Ward's method. B) Heatmap clustering of top 5% of variant genes between samples, clustering using Ward's method.(TIFF)Click here for additional data file.Figure S1110 of the BH-corrected p-value for enrichment of each pathway as compared to background. B) Top IPA network analysis of overlapping significant genes in human and rat expression. Red = upregulated in AT2 to AT1 cell differentiation, green = downregulated in AT2 to AT1 cell differentiation. Intensity of color is indicative of degree of fold change in expression.IPA network analysis of overlapping human and rat significant gene expression changes. A) IPA (left) and DAVID (right) of genes with significantly altered expression in both human and rat. Data bars expressed as −log(TIF)Click here for additional data file.Figure S1210 of the BH-corrected p-value for enrichment of each pathway as compared to background. B) Top IPA network of human-specific changes. Red = upregulated in AT2 to AT1 cell differentiation, green = downregulated in AT2 to AT1 cell differentiation. Intensity of color is indicative of degree of fold change in expression. Blue lines highlight HNF4A connections.IPA analysis of human-specific gene expression changes. A) IPA (left) and DAVID (right) of human-specific significant gene expression. Data bars expressed as −log(TIF)Click here for additional data file.Figure S1310 of the BH-corrected p-value for enrichment of each pathway as compared to background. B) Top IPA network of rat-specific changes. Red = upregulated in AT2 to AT1 cell differentiation, green = downregulated in AT2 to AT1 cell differentiation. Intensity of color is indicative of degree of fold change in expression. Blue lines highlight Tgfb1 connections.IPA analysis of rat-specific gene expression changes. A) IPA (left) and DAVID (right) of rat-specific significant gene expression. Data bars expressed as −log(TIF)Click here for additional data file.Figure S14Ac chromatin mark. (Middle) H3K9/14Ac peak overlap between chromatin from D0 and D8 (Venn diagram intersection). Left panel: D0-specific chromatin peaks, right panel: D8-specific chromatin peaks B) SICER and MACS peaks called for H3K27me3 chromatin mark. Peak overlap between chromatin from D0 and D8 is at Venn diagram intersection. Left panel: D0-specific chromatin peaks; right panel: D8-specific peaks. For both H3K9/14Ac and H3K27me3, chromatin-enriched DNA motifs are listed and the corresponding transcription factors which bind the recognition sequences in an AT2 (left panels) or AT1 cell-specific fashion (right panels).SICER and MACS called peaks and associated predicted TFBS using genomic background. A) SICER and MACS peaks called for H3K19/14(TIF)Click here for additional data file.Figure S15WNT signaling activated in AT2 to AT1 cell differentiation. A) Canonical WNT signaling pathway. Red = upregulated gene expression, green = downregulated gene expression. B) qRT-PCR of select WNT pathway members over course of AT2 to AT1 cell differentiation. 18S rRNA was used for normalization. Error expressed as SEM, n = 3 separate lung donors.(TIF)Click here for additional data file.Figure S162) = degree of correlation. Blue = H3K9/14Ac, red = H3K27me3, purple = input. B) Table demonstrating the degree of correlation between chromatin states between cell types and between differing histone marks. Blue = H3K9/14Ac, red = H3K27me3.Summary of ChIP-seq data. A) Summary of ChIPs, sequencing data, and peaks called. IP = immunoprecipitation target. R = correlation coefficient. R squared (R(TIF)Click here for additional data file.Figure S17Ac ChIP-seq peak calling. A) SICER peak calling of H3K9/14Ac in AT2 cells as a function of randomly chosen reads from parent H3Ac AT2 read file. B) SICER peak calling of H3K9/14Ac in AT1 cells as a function of randomly chosen reads from parent H3Ac AT1 read file. C) Merged overlap of peaks called as a function of number of reads included in H3K9/14Ac for both AT2 cells (dark blue) and AT1 cells (light blue).Read count has minimal effect on H3K9/14(TIF)Click here for additional data file.Table S1HOMER motif analysis of cell-specific TFBS. Each transcription factor (as recorded in HOMER known motifs database) and the associated p-value of enrichment for each day-specific chromatin mark.(XLS)Click here for additional data file.Table S2qRT-PCR primers used in this study.(DOC)Click here for additional data file.Table S3ChIP primers.(DOC)Click here for additional data file.


EZH2 are recurrent in germinal center B cell lymphomas, and the most common variants lead to altered EZH2 enzymatic activity and enhanced tri-methylation of histone H3 at lysine 27, a repressive chromatin modification. As an initial step toward screening patients for cancer genotype-directed therapy, we developed a screening assay for EZH2 codon 641 mutations amenable for testing formalin-fixed clinical specimens, based on the sensitive SNaPshot single nucleotide extension technology. We detected EZH2 mutations in 12/55 (22%) follicular lymphomas (FL), 5/35 (14%) diffuse large B cell lymphomas with a germinal center immunophenotype (GCB-DLBCL), and 2/11 (18%) high grade B cell lymphomas with concurrent rearrangements of BCL2 and MYC. No EZH2 mutations were detected in cases of Burkitt lymphoma (0/23). EZH2 mutations were frequently associated with the presence of BCL2 rearrangement (BCL2-R) in both the FL  and GCB-DLBCL groups , and across all lymphoma types excluding BL . We confirmed gain-of-function activity for all previously reported EZH2 codon 641 mutation variants. Our findings suggest that EZH2 mutations constitute an additional genetic “hit” in many BCL2-rearranged germinal center B cell lymphomas. Our work may be helpful in the selection of lymphoma patients for future trials of pharmacologic agents targeting EZH2 and EZH2-regulated pathways.Mutations at codon 641 of  IGH-BCL2 rearrangement, which leads to overexpression of the Bcl-2 oncoprotein, and is frequently present in follicular lymphoma and GCB-DLBCL, but not in other gene expression-defined subtypes of DLBCL. Human mature B cell lymphomas encompass a diverse spectrum of biologically and clinically distinct entities, many of which appear to recapitulate a specific stage of B cell development by morphologic, immunophenotypic and/or gene expression criteria. Follicular lymphoma (FL), Burkitt lymphoma (BL), and a gene expression-defined subset of diffuse large B cell lymphoma  all recapitulate biological features of normal germinal center B cells. EZH2 encodes the enzymatic subunit of the polycomb repressive complex 2 (PRC2), which mediates gene repression through trimethylation of histone H3 at lysine 27 (H3K27). Point mutations affecting codon 641 of EZH2 were recently described in a subset of GCB-DLBCL and FL, EZH2 were initially reported to result in enzymatic loss-of-function based on in vitro studies which used unmodified histone tails as a substrate for modification by recombinant PRC2 complexes, but the most common variants have subsequently been shown to possess increased activity in trimethylation of H3K27 in the mono- or di-methylated state. EZH2 have been implicated in the pathogenesis of several cancer types, including prostate, EZH2 is a mutant oncogene in germinal center-phenotype B cell lymphomas raises the possibility of targeting this pathway pharmacologically in the treatment of patients with these lymphomas. Important steps toward this goal include further delineation of the lymphoma types in which this mutation occurs, and development of assays amenable to detection of these mutations in routine clinical specimens.EZH2 codon 641 mutations in a large series of B cell lymphomas of germinal center origin, using a sensitive and specific single nucleotide extension method (SNaPshot) which has been validated for clinical tumor genotyping at our institution. We detect EZH2 mutations in a significant proportion of BCL2-rearranged follicular lymphomas, BCL2-rearranged diffuse large B cell lymphomas, and high-grade B cell lymphomas with concurrent BCL2 and MYC rearrangements , but not in BL. The data suggest that this mutation is not universally present in all germinal center-phenotype B cell lymphoma subtypes but appears to correlate with BCL2 status. Finally, we provide evidence that all previously reported EZH2 codon 641 mutation variants show the potential for enhanced H3K27 trimethylation activity.In this study, we report the results of testing for All research was conducted with the written approval of the Partners Healthcare Human Research Committee in accordance with the Ethical Principles and Guidelines for the Protection of Human Subjects of Research, generally known as the “Belmont Report.”MYC and BCL2 rearranged “double hit” lymphomas (DHL), and BL were identified from our pathology archives. All cases were diagnosed according to WHO 2008 criteria, and cases of uncertain classification were reviewed by a panel of expert hematopathologists . The follicular lymphoma cohort was enriched for cases of low morphologic grade and a Ki-67 proliferation index (PI) >30%, which prior work has suggested may represent a distinct poor prognosis subgroup. Cases of FL, GCB-DLBCL, Immunohistochemistry, including stains for CD10, Bcl-6, Mum-1, and Ki-67, was performed using protocols and antibodies validated for clinical use as described previously. Areas showing at least 40% malignant cells on hematoxylin and eosin (H&E) or immunohistochemically stained slides were selected for coring (1.5 mm) of the respective formalin-fixed, paraffin-embedded (FFPE) tissue blocks. Total nucleic acid (TNA) was purified using the FormaPure method , which was automated on a Beckman Biomek II liquid handler .EZH2 codon 641 in both the forward and reverse direction, a strategy that can detect all possible single point mutations leading to a missense substitution at that codon. Following initial validation we applied this assay to 124 cases of B cell lymphoma with a germinal center phenotype.Our institution routinely uses the SNaPshot multiplex single-nucleotide extension assay for clinical genotyping of tumor-associated point mutations. EZH2 codon 641 was PCR amplified from TNA using the forward primer 5′-AGTTAGTATATACAATGCCACCTG-3′ and reverse primer 5′- CTCTAGCATCTATTGCTGGC-3′, followed by a cleanup reaction with shrimp acid phosphatase and exonuclease 1 (USB). The SNaPshot single-nucleotide extension reaction was performed using SNaPshot Ready Reaction mix  and 4 multiplexed extension primers designed to interrogate the first two nucleotides of EZH2 codon 641 on both the coding and noncoding strands. Following a final shrimp acid phosphatase cleanup reaction, extension products were evaluated by capillary electrophoresis, using an Applied Biosystems 3500×L Genetic Analyzer. Extension primers used for initial screening of all samples were as follows:SNaPshot genotyping was performed in 96-well plates and is based on a one-tube protocol validated for clinical use in the Massachusetts General Hospital Diagnostic Molecular Pathology Laboratory. Genomic DNA containing 5′-ACTGACTGCAGAAAAATGAATTCATCTCAGAA-3′EZH2_c.1921F.v1: 5′-GACTGACTGACTGACTGACTGACTGACTGCAGAAAAATGAATTCATCTCAGAAT-3′EZH2_c.1922F.v1: 5′-GACTGACTGACTGACTGACTGACTGTGCCTTACCTCTCCACAGT-3′EZH2_c.1921R.v1: 5′-AGTGCCTTACCTCTCCACAG-3′EZH2c.1922R.v1: A final set of optimized extension primers was used to confirm all detected mutations:5′-CAGAAAAATGAATTCATCTCAGAA-3′EZH2_c.1921F.v2: 5′-AGTCAGTCAGTCAGAAAAATGAATTCATCTCAGAAT-3′EZH2_c.1922F.v2: 5′-AGTCAGTCAGTCAGTCAGTCAGTCAGGTGCCTTACCTCTCCACAGT-3′EZH2_c.1921R.v2: 5′-AGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTCAGTGCCTTACCTCTCCACAG-3′EZH2_c.1922R.v2: EZH2 coding sequence of RefSeq isoform C, NM_001203247.1, as explained subsequently.All transcript sequence references are to the BCL2 status were assessed for the presence of BCL2 rearrangement on 2–5 micron FFPE sections using the Vysis LSI BCL2 Dual Color Break Apart Rearrangement Probe . Cases were scored as BCL2-rearranged (BCL2-R) on the basis of detecting unambiguous probe separation or splitting in at least 15% of observed cells (50-cell count) as scored by two independent observers (M.N. and R.J.H.R.).All cases of unknown Statistical significance of differences in EZH2 mutation frequency between lymphoma groups was calculated by the two-tailed Fisher's exact test using GraphPad QuickCalcs . Statistical significance was defined as p<0.05.EZH2 coding sequence was PCR amplified from pooled human bone marrow cDNA (Clontech) using the primers 5′-GGGGACAAGTTTGTACAAAAAAGCAGGCTGCACCATGGACTACAAGGACGACGATGACAAAGGCCAGACTGGGAAG-3′ and 5′-GGGGACCACTTTGTACAAGAAAGCTGGGTTAAGGCAGCTGTTTCAGAGG-3′ which encode an N-terminal FLAG tag. PCR products were cloned into pDONR221 and confirmed by sequencing. A clone matching the coding sequence of EZH2 RefSeq isoform C was subcloned into pCDNA3.2/V5-DEST using the Gateway recombination system (Invitrogen). Codon 641 and 689 point mutations were generated in pENTRY vectors using the QuickChange Lightning kit (Stratagene) and were subcloned into pCDNA3.2/V5-DEST. SET domain-truncated EZH2 (EZH2ΔSET) was generated by PCR subcloning with the C-terminal primer 5′-GGGGACCACTTTGTACAAGAAAGCTGGGTTCATGCCAGCAATAGATGCTTTTT-3′ as previously described. The EZH2 vectors were transfected into sub-confluent NIH-3T3 murine fibroblasts with Fugene HD reagent (Roche) according to the manufacturer's instructions. Cells were harvested 72 hours later and conventional western blotting was performed on whole-cell extracts , or acid-extracted histones . Ponceau S was used to confirm transfer of equivalent total protein levels in all lanes prior to antibody binding. The antibodies used for western blot are as follows:Beta-actin – Abcam , Cat# ab8827 (rabbit)EZH2 – Active Motif , Cat# 39639 (rabbit)H3  – Abcam, Cat# ab1791 (rabbit)H3K9me3 – Abcam, Cat# ab8898 (rabbit)H3K27me1 – Active Motif, Cat# 39377 (rabbit)H3K27me2 – Abcam, Cat# ab24684 (rabbit)H3K27me3 – Millipore , Cat# 07-449 (rabbit)Published RNA-seq data for DLBCL cell lines Oci-Ly1, Oci-Ly7, and Oci-Ly19 (SRA accession SRP001599) EZH2 codon 641 mutations in 19/124 (15%) cases. All mutations were genotyped redundantly by the corresponding forward and reverse extension primers, and were detected in independent screening and confirmatory runs. Detected mutations included all of the four most common reported variants . There was no difference in EZH2 mutation frequency between the low-PI and high-PI subgroups of grade 1–2 FL  or between EZH2 mutation status and morphologic FL grade . Within the grade 3 FL group, 3 cases were graded as 3B, and none of these cases showed an EZH2 mutation. We also detected EZH2 mutations in the GCB-DLBCL  and DHL  groups, but not in any case of BL (0/23). Four of the five DLBCL EZH2 mutations belonged to a group of nine DLBCL cases that had concurrent diagnoses of grade 3 FL.The frequency of BCL2 rearrangements in all of our lymphoma cases that were not previously tested for this aberration. As expected, BCL2 rearrangements were detected in the majority of FL (78%) and in a smaller proportion of GCB-DLBCL (34%) , the DLBCL group , and across all lymphoma types excluding BL, which universally lacked both BCL2 rearrangements and EZH2 mutations  (We used FISH to screen for CL (34%) . We founp<0.003) .EZH2 mutations in a cellular context, we PCR cloned the EZH2 coding sequence from human bone marrow cDNA. Of the 7 independent clones we sequenced, all contained the exon 8–9 splice junction seen in EZH2 Refseq isoform C (NM_001203247), corresponding to the Y641 codon designation used in the initial description of the lymphoma mutation, EZH2 Refseq isoform A (NM_004456), which has been used as a reference transcript in some later work, resulting in designation of the same residue as Y646. EZH2 exon 8–9 splice junction support the splice junction found in isoform C, and not the junction found in isoform A . In contrast, there was a marked increase in global H3K27me3 levels in cells transfected with each of the five lymphoma-associated mutants. There was no measurable difference in global levels of H3K27me2, H3K27me1, and H3K9me3 between the transfectants  BRAF V600E mutations). EZH2 mutations in a substantial proportion of germinal center lymphomas from routine FFPE clinical specimens. The absence of EZH2 mutations in BL highlights both the biological specificity of the EZH2 codon 641 mutation for certain lymphoma subtypes, and the technical specificity of our assay.Our findings confirm and extend prior work regarding the prevalence of EZH2 mutations in FL  compared to prior reports (7% EZH2 mutations in 4/13 cases (31%). EZH2 mutations in follicular lymphoma may be higher than originally reported. EZH2 mutations were not enriched in more proliferative subgroups of FL (low grade/high PI FL and grade 3 FL), suggesting that EZH2 mutations are not associated with known aggressive subtypes of FL. Larger studies with clinical follow-up will be required to determine whether this mutation carries independent prognostic significance in FL.In comparison to prior studies, we detected a relatively high rate of ports 7%  overall.EZH2 mutations in 14% of a cohort of 63 microarray-defined GCB-DLBCL. EZH2 mutations detected in the GCB-DLBCL cohort occurred in a subgroup of nine cases in which the diagnostic biopsy showed a large cell lymphoma with areas of both follicular and diffuse growth, resulting in concurrent diagnoses of DLBCL and grade 3 FL by current WHO criteria. de novo high-grade germinal center phenotype lymphomas with partial residual folliculotropism. This finding raises the possibility that EZH2-mutated DLBCL may have characteristic morphological and biological features, and merits further investigation.In contrast to the findings in FL, we detected mutations in a relatively low proportion of GCB-DLBCL (14%) compared to the original report (22%) EZH2 codon 641 mutation was first identified through whole-genome sequencing of a follicular lymphoma that lacked a t IGH-BCL2 rearrangement. EZH2 codon 641 mutations with rearrangements of BCL2. This implies that EZH2 mutations do not substitute for BCL2 rearrangement, but rather represent a functionally distinct oncogenic “hit” in germinal center B cell lymphomagenesis. Targeted inhibitors of BCL2 have been developed, with some advancing into clinical trials. The EZH2 mutations are rare or absent in this lymphoma type. We did detect EZH2 mutations in MYC and BCL2-rearranged “double hit” high grade B cell lymphomas, which often show morphologic, genetic, and immunophenotypic features intermediate between DLBCL and BL, and are associated with a poor prognosis EZH2 mutation status could also potentially contribute to this distinction.BL is a prototypical germinal center-derived lymphoma, but shows substantial biologic, pathogenic, and epidemiologic differences from FL and DLBCL. in-vivo enzyme kinetics, EZH2 mutations are thought to confer gain-of-function. However, the Y641C mutation has also been reported in an acute myeloid leukemia cell line, despite the fact that many reported EZH2 mutations in myeloid tumors are clearly inactivating. EZH2 mutations, and highlight the need for further functional investigation of these mutant proteins. While the H3K27me3 modification is known to have a repressive effect on gene expression, the precise genomic targets that are affected by the mutant protein during lymphomagenesis and confer selective advantage have not been identified.The results of our mutant EZH2 expression experiments indicate that the mutant protein conferred a gain-of-function phenotype as evidenced by increased generation of the H3K27me3 histone mark, the mechanism of which has been demonstrated by others. EZH2 with a coding sequence matching that of the original reported EZH2 coding sequence EZH2 Refseq isoform C (NM_001203247). Our results suggest that this is the predominant long splice form of EZH2 in lymphoma and other tissues, and for this reason we prefer to designate the EZH2 codon affected by recurrent mutations in B cell lymphoma as Y641, rather than Y646. Shorter EZH2 transcripts produced by variant splicing of exons 3 and 4 are also well supported by ESTs and other public data, and are of uncertain significance.For our transgenic work, we used a cDNA clone for EZH2 codon 641 mutations in FFPE tissue, and demonstrate frequent occurrence of these gain-of-function mutations in the full biological spectrum of BCL2-rearranged germinal center phenotype B cell lymphomas, but not in Burkitt lymphoma.In conclusion, we have developed a clinically applicable assay for sensitive detection of Figure S1EZH2 transcript splice variants in the DLBCL cell line Oci-Ly1. Alignment of RNA-seq data from the DLBCL cell line Oci-Ly-1 EZH2 exon 8 shows that the vast majority of transcripts contain the splice junction seen in EZH2 isoform C (NM-001203247), as marked by the black arrow. Only rare reads, marked with a red arrow, support the alternate splice site seen in EZH2 isoform A (NM_004456), which encodes an additional 5 amino acids. Findings in the DLBCL cell lines Oci-Ly7 and Oci-Ly19 (not shown) were similar.RNA-seq analysis of (TIF)Click here for additional data file.Figure S2EZH2 codon 641 mutants was not associated with differences in the global levels of histone marks H3K27me1, H3K27me2, and H3K9me3 compared to vector control, wild-type, or SET domain-inactivated EZH2.Western blot of EZH2 mutant overexpression in NIH-3T3 fibroblasts. Transgenic overexpression of lymphoma-associated (TIF)Click here for additional data file.


HLA-DRA mRNA expression, even in the absence of interferon-γ stimulation, as well as increased cell surface expression of MHC II. Together, these data add mechanistic insight to prior observations of increased EZH2 expression and decreased CIITA expression in multiple tumor types.One mechanism frequently utilized by tumor cells to escape immune system recognition and elimination is suppression of cell surface expression of Major Histocompatibility Class II (MHC II) molecules. Expression of MHC II is regulated primarily at the level of transcription by the Class II Transactivator, CIITA, and decreased CIITA expression is observed in multiple tumor types. We investigate here contributions of epigenetic modifications to transcriptional silencing of CIITA in variants of the human breast cancer cell line MDA MB 435. Significant increases in histone H3 lysine 27 trimethylation upon IFN-γ stimulation correlate with reductions in transcription factor recruitment to the interferon-γ inducible CIITA promoter, CIITApIV, and with significantly increased CIITApIV occupancy by the histone methyltransferase enhancer of zeste homolog 2 (EZH2). Most compelling is evidence that decreased expression of EZH2 in MDA MB 435 variants results in significant increases in CIITA and  As activated T cells are in turn responsible for driving adaptive immune responses, MHC II molecules play critical roles in regulating immune recognition of pathogens and tumors. Constitutive expression of MHC class II is limited to professional antigen presenting cells, but MHC II expression is induced in all nucleated cells by inflammatory cytokines, of which IFN-γ is the most potent + T cells are directly responsible for lysis of infected cells and tumor cells, recent studies have shown that peptide immunization in the presence of CD4+ T cells enhances CD8+ T cell responses + T cells are required for an effective anti-tumor immune response + T cells respond to tumor antigens presented via MHC II to induce an effective immune response and emphasize the importance of transcriptional regulation of MHC II genes in cancer cells.Major histocompatibility class II (MHC II) genes encode cell surface proteins responsible for presenting extracellularly derived peptides for activation of CD4HLA-DRA promoters, assembly of which is stabilized by the Class II transactivator, CIITA HLA-DRA proximal promoter utilized in this study, components of the basal transcriptional machinery, histone acetyltransferases (HATs), histone deacetylases (HDACs), chromatin remodeling complexes, and kinases that phosphorylate RNA pol II Tight regulation of MHC II transcription is necessary for proper initiation, stabilization, and termination of adaptive immune responses to infection and to tumors. MHC II genes are regulated by a multi-protein enhanceosome complex that binds the W-X-Y region of CIITA transcription is also tightly regulated in a cell specific manner from four distinct promoters HLA-DRA and CIITApIV genes HLA-DRA promoter exhibits low basal acetylation which allows for binding of the ubiquitously expressed components of the enhanceosome complex. Following cytokine stimulation, acetylation of histones (H) H3 and H4 significantly increases, allowing recruitment of CIITA and the basal transcription machinery and initiation of MHC II transcription Previous studies from our lab and others indicate that epigenetic modifications to chromatin play important roles in regulating transcription of Decreased expression of MHC II has been previously described in breast tumors 435-Lung 2 and 435-Brain 1 variants of the estrogen independent MDA MB 435 human breast cancer cell line were provided by Dr. Janet Price Antibodies recognizing IRF-1 and STAT-1 were from Santa Cruz . Antibodies recognizing histone H3, acetylated histone H3, histone H4, acetylated histone H4, and rabbit and mouse immunoglobulin G (IgG) isotype control antibodies were from Millipore . Antibodies recognizing histone 3 (trimethyl K27), histone 3 (acetyl K27), histone 3 (trimethyl K9), histone 3 (acetyl K18), CBP, and EZH2 antibodies were from Abcam . Antibody recognizing EZH2 was from Millipore ; antibody recognizing Tubulin was from Santa Cruz ; HRP conjugated mouse antibody was from Promega ; and HRP conjugated rabbit antibody was from Pierce .2O) with EDTA free protease inhibitor (Roche) and analyzed by western blot for knockdown efficiency and specificity.Short interfering RNA (siRNA) duplexes predesigned against human EZH2 (Qiagen) were used for transient knockdown of EZH2. Cells were transfected with 1 ug of EZH2 specific siRNA or All Star scrambled sequence control (Qiagen) using RNAiFect transfection reagent (Qiagen) according to the manufacturer's instructions and were treated with IFN-γ (500 U/ml) as indicated. Cells were lysed in NP-40 lysis buffer  as indicated, and were trypsinized, washed with PBS and resuspended in 100 µl of incubation buffer . 10 µg Phycoerythrin (PE)-labeled anti-human HLA-DR  or PE mouse IgG2a κ isotype control antibody (Biolegend) was added and the cell suspension was rotated at 4°C for 45 minutes. Following antibody incubation, cells were washed with PBS and fixed with 2% paraformaldehyde. MHC II cell surface expression was measured by FACS-Canto  and analyzed using FlowJo. All samples were analyzed using 10,000 events per sample.Cells were plated at a density of 7×105, transfected with 1 µg EZH2 specific or control siRNA (Qiagen), and twenty four hours post transfection, stimulated with IFN-γ (500 U/ml) as indicated. Following the stimulation cells were trypsinized, washed with PBS and 10% of the cell volume was lysed with 1% Nonidet P-40 lysis buffer and was analyzed by western blot for knockdown efficiency and specificity. The remaining cell volume was resuspended in 100 µl of incubation buffer and labeled as above.Cells were plated at a density of 7×105 cells and were stimulated as indicated with IFN-γ (500 U/ml). Cells were harvested and were subjected to RNA extraction with 1 ml of Trizol reagent (Invitrogen) as previously described HLA-DRA, and GAPDH TTCATGCAACACCCAACACT, EZH2 antisene GAGAGCAGCAGCAAACTCCT, and EZH2 probe FAM-TTACCAGCATTTGGAGGGAG-TAMRA. Values generated from Q-PCR reactions were calculated on the basis of standard curves generated.Cells were plated at a density of 8×105 cells, transfected with EZH2 specific or control siRNA, and twenty four hours later were stimulated as indicated with IFN-γ (500 U/ml). Cells were harvested and 10% of the cell volume was lysed with 1% Nonidet P-40 lysis buffer and subjected SDS PAGE. RNA was extracted and analyzed from the remaining fraction of cell volume as above.Cells were plated at a density of 8×106, stimulated with IFN-γ as indicated (500 U/ml), and were crosslinked with 1% formaldehyde for 10 minutes at room temperature. Crosslinking was stopped by the addition of 0.125 M glycine for five minutes at room temperature. Cells were lysed in SDS lysis buffer and were sonicated at constant pulse to generate an average of 500–750 bp sheared DNA. Sonicated lysates were precleared with salmon-sperm coated agarose beads (Upstate) and half of the lysate was immunoprecipitated with 5 µg of indicated antibody overnight at 4°C. The remaining half of the lysate was immunoprecipitated with isotype control antibody (Upstate). Following a two hour immunoprecipitation with 50 µl of salmon-sperm coated agarose beads, samples were washed for 3 minutes at 4°C with each of the following buffers: low salt buffer, high salt buffer, LiCl, and 1×TE and were eluted with SDS elution buffer HLA-DRA promoter and the IRF-E-GAS box of CIITApIV ChIP assays were performed as previously described 6 cells and were stimulated as indicated with 500 U/ml IFN-γ. Cells were harvested and washed with PBS, resuspended in 10 ml of PBS (pH 8.0) containing 1 mM MgCl2 and 1 µM of Disuccinimidyl Glutarate (DSG) and were incubated at room temperature for 45 minutes as described above Cells were plated at a density of 2.5×105, transfected with 1 µg EZH2 specific or control siRNA (Qiagen), and stimulated as indicated with IFN-γ (500 U/ml). 10% of the cell volume was lysed with 1% Nonidet P-40 lysis buffer and was analyzed by western blot for knockdown efficiency and specificity. The remaining cell volume was crosslinked, lysed in SDS lysis buffer, and subjected to sonication and ChIP assay as above.ChIP siRNA assays were performed as previously described 5, trypsinized, washed with PBS and re-suspended in 5 mL of PBS. Bisulfite treatment of DNA was performed using the EZ DNA methylation kit  according to the manufacturer's instructions. Hot start touchdown PCR was performed in 1× PCR buffer, 0.25 mM dNTP, 0.5 µM forward and reverse primer, and 1.0 U Taq polymerase. Primers specific for CIITApIV CpG island region 2 MDA MB 435 breast cancer cells or HeLa cells were plated at a density of 7×10HLA-DRA mRNA levels in MDA MB 435 cells  analyses. Lysates were immunoprecipitated with antibody against acetylated H3  and of histone H3 lysine 27 (H3K27me3) at the La cells –D. TogetHLA-DRA promoter in MDA MB 435 cells and in HeLa cells, we performed ChIP assays with antibodies recognizing H3K27ac. Levels of H3K27ac on HLA-DRA increase significantly with cytokine stimulation in each of the three variants of MDA MB 435 cells with levels comparable to H3K27ac in HeLa cells (HLA-DRA promoter is opened and available upon IFN-γ stimulation.Acetylation of H3K27 (H3K27ac) is catalyzed by CBP and is associated with multiple active mammalian genes. To determine levels of H3K27ac on the La cells ; furtherHLA-DRA promoter is essential for transcriptional activation of HLA-DRA genes. Four different promoters have been described to regulate transcription of CIITA, each being characterized by a different first exon CIITA expression and subsequent binding to the Our observations of significant decreases in CIITApIV transcripts between MDA MB 435 variants  led us tTo determine CIITApIV levels of H3 lysine 9 and lysine 27 methylation and levels of lysine 27 acetylation in MDA MB 435 cell variants, ChIP experiments were performed using antibodies against H3K9me3, H3K27me3, and H3K27ac. Q-PCR analysis indicated elevated basal levels of H3K9me3 at CIITApIV that significantly decrease upon stimulation with IFN-γ in the MDA MB 435 variants and in HeLa cells . Basal lTo determine if epigenetic alterations at CIITApIV are sequence specific, ChIP assays were performed to detect levels of H3K27me3, H3K9me3, H3K27ac, and H3K18ac at the GAPDH promoter . Low levThe transcription factors STAT-1 and IRF-1 are both required for CIITApIV transcription in response to IFN-γ stimulation An open chromatin confirmation is required for the initiation of transcription. Data in HLA-DRA  are chromatin remodeling enzymes that add one, two, or three methyl groups to lysine residues on histones HLA-DRA  and to CHLA-DRA  in unstimulation . Strikinmulation . By compmulation  are simi MDA MB 435, 435-Brain 1, 435-Lung 2 cells, HeLa cells, and MCF 10A cells were stimulated with IFN-γ as indicated. Post stimulation cells were trypsinized, washed, and incubated with PE-labeled mouse control IgG. Following antibody incubation, cells were fixed and PE cell surface staining was measured by FACS-Canto. Results shown are representative of three independent experiments. (B) Cells were stimulated as indicated and were subjected to ChIP assay as above. Lysates were IP with isotype control antibodies or antibodies against indicated histone modification; associated DNA was isolated and analyzed via Q-PCR using primers spanning the GAPDH proximal promoter. Values shown represent mean ± SEM of two independent experiments. Average control IP values were 350±200(TIF)Click here for additional data file.Figure S2IFN-γ induced levels of H3K18ac, H3K27ac, CBP, H3K9me3, and H3K27me3 at the HLA-DRA promoter in HeLa cells and MDA MB 435 variants. (A–E) ChIP assays were carried out in HeLa cells, MDA MB 435 breast cancer cells, 435-Brain 1 cells, and 435-Lung2 cells stimulated as indicated with IFN-γ as described above. DNA was isolated and analyzed via Q-PCR using primers spanning the W-X-Y box of the HLA-DRA promoter. Values represent mean ± SEM of two independent experiments for HeLa and four independent experiments for MDA MB 435 variants. Average control IP values were 0.9±0.7(TIF)Click here for additional data file.Figure S3Levels of H3 and H4 remain unchanged in HeLa cells and in MDA MB 435 variants stimulated with IFN-γ. (A and B) Cells were stimulated as indicated with IFN-γ. Following stimulation lysates were subjected to ChIP analyses and IP with control antibody or with antibody against histones H3 (A) or H4 (B). DNA was analyzed via Q-PCR with primers and probes spanning the CIITApIV IRF-E-GAS. IP values shown represent mean ± SEM of two independent experiments. Control IP values for (A) and (B) were 1.8±0.7 (C) IRF-1, STAT-1, pSTAT-1, EZH2 and CBP protein expression. MDA MB 435 variants were stimulated with IFN-γ, harvested and subjected to Western Blot analysis of indicated proteins. Results shown are representative of three independent experiments.(TIF)Click here for additional data file.Figure S4Cell surface expression of MHC II in MDA MB 435, 435-Brain1, and 435-Lung2 cells treated with EZH2 siRNA. Cells were plated, treated with control siRNA or with EZH2 specific siRNA, and were stimulated with IFN-γ for 36 hours. Following stimulation, cells were trypsinized, washed, and incubated with PE-labeled anti-human HLA-DRA antibody. Following antibody incubation, cells were fixed and PE cell surface staining was measured by FACS-Canto. Results shown are representative of three independent experiments.(TIF)Click here for additional data file.


We characterized 7 highly pathogenic avian influenza A(H5N1) viruses isolated from poultry in China during 2009–2012 and found that they belong to clade 2.3.4 but do not fit within the 3 defined subclades. Antigenic drift in subtype H5N1 variants may reduce the efficacy of vaccines designed to control these viruses in poultry. Infection with the Asian lineage of highly pathogenic avian influenza (HPAI) A(H5N1) virus (prototype strain A/goose/Guangdong/1/96 [Gs/GD]) has resulted in substantial losses in the poultry industry and poses a threat to public health worldwide. According to the World Health Organization (WHO)/World Organisation for Animal Health (OIE)/Food and Agriculture Organization of the United Nations (FAO) H5N1 Evolution Working Group, 10 distinct clades of these viruses (0–9) were initially designated in 2008 to characterize the phylodynamics of the hemagglutinin (HA) gene of the Gs/GD-like viruses circulating during 1996–2007  at a wholesale live-bird market (LBM) in Yangzhou, Jiangsu Province, in eastern China. Birds offered for retail sale in the LBM were mainly from local farms in Jiangsu and the neighboring provinces in eastern China; some were transported from regions in southern or northern China. Virus isolation and identification were conducted as described .To characterize these 7 isolates, we sequenced the HA genes to determine clade distribution. In the reconstructed phylogenetic tree  using re>60 at the clade-defining node in which sequences monophyletically arose from a common ancestor but also with average between-clade and within-clade nucleotide divergences of >1.5% and <1.5%, respectively. Apart from subclades 2.3.4.1, 2.3.4.2, and 2.3.4.3, we found 3 additional monophyletic categories—the A/peregrine falcon/Hong Kong/810/2009-like viruses, the HPAI subtype H5N5–like reassortants, and the HPAI subtype H5N2/H5N8–like reassortants—that grouped clearly within the tree  showed limited reaction to Re-5 and A/chicken/eastern China/AH/2012. Moreover, antigenic variation also existed among the 6 A/peregrine falcon/Hong Kong/810/2009-like viruses, as highlighted by the HI assay using k0602 antiserum  and 10% (1/10 birds in the k0603 group) of the challenged chickens survived, reflecting poor protection by the Re-4/Re-5 vaccine. In addition, shed virus was detected in tracheal and cloacal swabs from most of the tested chickens on 3 and 5 days postchallenge. By contrast, the rk0602-vaccinated chickens all survived the challenge, and no virus was recovered from tracheal and cloacal samples  and A/chicken/Shandong/k0603/2010 (k0603) viruses to evaluate the bivalent inactivated reassortant H5N1/PR8 vaccine Re-4/Re-5 (the HA and NA genes of Re-4 are from a clade 7 virus A/chicken/Shanxi/2/2006). This vaccine has been extensively used to control the prevalence of clade 2.3.4 and clade 7 viruses in China since 2008 . The bir samples .The location of the 7 HPAI A(H5N1) virus variants in the HA gene tree  suggestsIn China, 1 of the 6 countries to which subtype H5N1 virus is endemic  viruses. The results of cross-HI assays  and vacc


Human infection with a novel avian-origin influenza A (H7N9) virus occurred continuously in China during the first half of 2013, with high infectivity and pathogenicity to humans. In this study, we investigated the origin of internal genes of the novel H7N9 virus and analyzed the relationship between internal genes and infectivity of the virus.We tested the environmental specimens using real-time RT-PCR assays and isolated five H9N2 viruses from specimens that were positive for both H7 and H9. Results of recombination and phylogeny analysis, performed based on the entire sequences of 221 influenza viruses, showed that one of the Zhejiang avian H9N2 isolates, A/environment/Zhejiang/16/2013, shared the highest identities on the internal genes with the novel H7N9 virus A/Anhui/1/2013, ranging from 98.98% to 100%. Zhejiang avian H9N2 isolates were all reassortant viruses, by acquiring NS gene from A/chicken/Dawang/1/2011-like viruses and other five internal genes from A/brambling/Beijing/16/2012-like viruses. Compared to A/Anhui/1/2013 (H7N9), the homology on the NS gene was 99.16% with A/chicken/Dawang/1/2011, whereas only 94.27-97.61% with A/bramnling/Beijing/16/2012-like viruses. Analysis on the relationship between internal genes and the infectivity of novel H7N9 viruses were performed by comparing amino acid sequences with the HPAI H5N1 viruses, the H9N2 and the earlier H7N9 avian influenza viruses. There were nine amino acids on the internal genes found to be possibly associated with the infectivity of the novel H7N9 viruses. These findings indicate that the internal genes, sharing the highest similarities with A/environment/Zhejiang/16/2013-like (H9N2) viruses, may affect the infectivity of the novel H7N9 viruses. This stDifferent subtypes of avian influenza viruses (AIVs) possess different virulence and infectivity. Except for domestic poultry and wild birds, some AIVs including subtype H5, H7 and H9 had been detected from humans . Only inIn contrast to H5N1, subtype H9 AIVs were generally considered to be low pathogenicity viruses causing mild disease among domestic poultry and wild birds -16. HumaInfections with earlier H7N9 AIVs were rarely reported in China or sporadically happened in a couple of countries ,30. No HIn this study, we monitored the environmental specimens collected from live poultry markets and isolated five avian H9N2 viruses from both H7 and H9 positive specimens. Meanwhile, the origin of the internal genes of the novel H7N9 virus was systematically illustrated by analyzing the entire sequences of 221 influenza viruses using RDP3 software. Phylogeny analysis and homological comparison were performed to determine the reassortment events. In addition, the specific amino acids possibly related to the high infectivity of the novel H7N9 viruses were analyzed by comparing the genome sequences with the HPAI H5N1 viruses, the H9N2 and the earlier H7N9 AIVs. After the outbreaks of human infection with the novel H7N9 virus in Zhejiang province, China in 2013, we tested the environmental specimens collected from live poultry markets using real-time RT-PCR. Within the 82 environmental specimens collected from six cities, 33 (40.24%) were found to be positive for H7, 15 (18.29%) positive for H5 and 39 (47.56%) positive for H9. There were 23 (28.05%) found to be positive for both H7 and H9. Of the specimens positive for both H7 and H9, five AIVs were isolated, including A/environment/Zhejiang/09/2013 (ZJ09), A/environment/Zhejiang/13/2013 (ZJ13), A/environment/Zhejiang/14/2013 (ZJ14), A/environment/Zhejiang/15/2013 (ZJ15) and A/environment/Zhejiang/16/2013 (ZJ16), in which two specimens were from Hangzhou city and three from Huzhou city. Ct values of the clinical specimens of the five isolates ranged from 10 to 14 for H9, and 17 to 35 for H7. After the virus isolates were obtained from allantoic liquids, the whole genome of the isolates were sequenced and aligned in Blast of NCBI. The results showed that the sequences of each gene shared the highest similarities with H9N2 AIVs strains, and thus the five Zhejiang isolates were identified as avian influenza A (H9N2) viruses. The details of five Zhejiang H9N2 AIVs are shown in A retrospective analysis on surveillance data for the AIVs in Zhejiang province between 2011 and 2012 was performed as well. In total 784 environmental specimens were tested by real-time RT-PCR assay to detect H5, H7 and H9 AIVs in 2011, in which 13 (1.66%) were positive for avian H5, 34 (4.34%) were positive for H9 and three (0.38%) were positive for both H5 and H9. No H7 positive specimens were detected. In 2012, 709 specimens were tested, with 26 (3.67%) positive for H5 and 47 (6.63%) positive for H9. The detection of H7 was not performed. The evolutionary process of the novel H7N9 virus analyzed by RDP3 software showed that the six internal genes of the novel H7N9 viruses shared the highest similarities with ZJ16 (H9N2)-like viruses . SignifiComparisons on the nucleotide sequences amongst A/Anhui/1/2013 (AH1) (H7N9), ZJ16 (H9N2), BJ16-like viruses and A/chicken/Dawang/1/2011 are summarized in Phylogenetic trees drawn on the basis of the amino acid sequences were used to confirm the reassortment events. The PB2 gene phylogenetic tree  showed tIn this study, the specific amino acids possibly related to the high infectivity of the novel H7N9 viruses were analyzed based on the criteria illustrated in  In accordance with Since March 2013, a severe and fatal respiratory disease, characterized by high fever and severe low respiratory symptoms, has occurred continuously in China, mainly in Zhejiang and Jiangsu province, as well as Shanghai city . The ChiThe novel H7N9 virus has infected 46 individuals resulting in eight deaths within one month in Zhejiang province, China. Except for the laboratory diagnosis of the cases, the environmental specimens collected from live poultry markets were monitored for H5, H7 and H9 AIVs in order to assess whether the novel H7N9 virus has infected the domestic poultry and circulated in the external environment. Interestingly, 23 specimens were detected to be positive for both H7 and H9 during this surveillance, however, the Ct value of H9  obtained from real-time RT-PCR assay were significant lower than that of H7  and all the isolates obtained from the double-positive specimens were identified as H9N2 AIVs, which indicated the co-infection of H7 and H9 has existed in Zhejiang province, and that domestic poultry, especially chicken, has a close relationship with the reassortment between the novel H7N9 and avian H9N2 viruses.Based on the previous study, A/brambling/Beijing/16/2012 (BJ16), a H9N2 strain isolated from brambling in Beijing in 2012, were identified as the donor of the internal genes of the novel H7N9 virus [ Human infection with the HPAI H5N1 virus was first reported in Hong Kong in 1997, resulting in 18 cases with six deaths from May 1997 to February 1998 . The patIn this study, several subtypes of AIVs, including HPAI H5N1, avian H9N2 and earlier H7N9 viruses, were included to analyze the possible reason for the high infectivity of the novel H7N9 virus. These three subtypes of AIVs were all of avian origin and have been identified to cause human infections. The differences and similarities of amino acid sequences among the three subtypes of AVIs may result in different infectivity to humans. In this study, the HPAI H5N1, the H9N2 AIVs and the novel H7N9 viruses are characterized as high infectivity, therefore the identical amino acids shared amongst these three groups were selected as the high infectivity related sites, as shown in Even though the novel H7N9 virus is highly infective and pathogenic to humans, it is generally low pathogenic to poultry ,29. Ther Ethics committee of Zhejiang provincial Center for Disease Control and Prevention (CDC) approved this study. In order to control the outbreak of infection with the novel H7N9 virus, staff in municipal CDC took responsibility for disinfection of live poultry markets. To assess the disinfectant effect, the environmental specimens were collected before and after the disinfection. All the specimens used in this study were collected from environment before disinfection. st April to 2nd May in 2013. Those specimens found to be positive for both H7 and H9 AIVs were inoculated to the allantoic sac of 9-to-11-day-old specific pathogen-free (SPF) embryonated chicken eggs for 48 hours at 35°C to propagate the virus. In total 82 environmental specimens were screened for subtype H5, H7 and H9 AIVs using one-step real-time reverse-transcriptase polymerase chain reaction (rRT-PCR) assays. The primer pairs and probes of the real-time RT-PCR assays were designed and provided by the Chinese national influenza centre (CNIC). The environmental specimens, including swabs of chicken cage, chicken manure and sewage of slaughter poultry, were collected from the live poultry markets in Zhejiang province, China during 1 RNA was extracted from the harvested allantoic liquids using the QIAamp Viral RNA Mini Kit (Qiagen). The whole genomes of five avian H9N2 viruses were performed by second generation sequencing in Applied Biosystems (ABI). The obtained sequences of each gene were aligned in BLAST of NCBI. The complete sequences of five Zhejiang isolates were submitted to GenBank by Zhejiang provincial centre for disease control and prevention (CDC). The entire sequences of a total of 221 influenza viruses were used to perform the recombination analysis. The 221 viruses consisted of (1) five avian H9N2 viruses isolated from environmental specimens in Zhejiang province in 2013, (2) five novel H7N9 viruses, including A/Anhui/1/2013 (AH1), A/Shanghai/1/2013 (SH1), A/Shanghai/2/2013 (SH2), A/Hangzhou/1/2013 (HZ1) and A/Zhejiang/DTID-ZJU01/2013 (ZJU01) ,35, (3) A multiple sequence alignment was performed by the ClustalW program and the amino acid mutations were analyzed with the Highlight model using MEGA software (Version 5.0). Phylogenetic trees were drawn with the Neighbor-joining method of the MEGA software (Version 5.0) by means of bootstrap analysis with 1000 replications. Reassortment events on the six internal genes of the novel H7N9 viruses were searched by the RDP, GENECONV and MaxChi suites within the Recombination Detection Program (RDP3) software, according to the instruction and previous studies . The hig Phylogenetic trees were generated based on the amino acid sequences of 39 influenza viruses by means of the Neighbor-joining (NJ) method of the MEGA software (Version 5.0), with the bootstrap analysis of 1000 replications. The 39 viruses contained 19 of avian H9N2 viruses isolated during 1997 to 2012, five HPAI H5N1 viruses isolated in Hong Kong and mainland China, four avian H7N9 viruses isolated worldwide during 2006 to 2011, five novel H7N9 viruses isolated in 2013, five avian H9N2 virus isolated from Zhejiang province in 2013, as well as one avian H7N9 virus A/chicken/Zhejiang/DTID-ZJU01/2013, which was isolated from chicken in Zhejiang province in 2013 The multiple sequence alignments based on the amino acid sequences of the HPAI H5N1 viruses, the H9N2 and the earlier H7N9 AIVs, as well as the novel H7N9 viruses were performed by using BioEdit software. Except for the novel H7N9 viruses, all the amino acid sequences were downloaded from GenBank. The GenBank accession numbers of the AIVs used for the comparison were shown in We classified all the AIVs used in this comparison into four groups based on their different infectivity described in the previous studies ,19,21–30The comparative method and selection principle of the specific amino acids associated with high infectivity of the novel H7N9 virus is illustrated in Table S1Genbank accession numbers of amino acid sequences for the AIVs used in this study.(DOC)Click here for additional data file.


BRCA1/2, CHEK2 and RAD51C is common practice for individuals from high-risk families. However, test results may be ambiguous due to the presence of unclassified variants (UCV) in the concurrent absence of clearly cancer-predisposing mutations. Especially the presence of intronic or exonic variants within these genes that possibly affect proper pre-mRNA processing poses a challenge as their functional implications are not immediately apparent. Therefore, it appears necessary to characterize potential splicing UCV and to develop appropriate classification tools. We investigated 30 distinct BRCA1 variants, both intronic and exonic, regarding their spliceogenic potential by commonly used in silico prediction algorithms  along with in vitro transcript analyses. A total of 25 variants were identified spliceogenic, either causing/enhancing exon skipping or activation of cryptic splice sites, or both. Except from a single intronic variant causing minor effects on BRCA1 pre-mRNA processing in our analyses, 23 out of 24 intronic variants were correctly predicted by MaxEntScan, while HSF was less accurate in this cohort. Among the 6 exonic variants analyzed, 4 severely impair correct pre-mRNA processing, while the remaining two have partial effects. In contrast to the intronic alterations investigated, only half of the spliceogenic exonic variants were correctly predicted by HSF and/or MaxEntScan. These data support the idea that exonic splicing mutations are commonly disease-causing and concurrently prone to escape in silico prediction, hence necessitating experimental in vitro splicing analysis.Screening for pathogenic mutations in breast and ovarian cancer genes such as  BRCA1 and BRCA2BRCA1/2 mutations were detected in approximately 24% of the families (as of May 2012), a considerable amount of BRCA1/2 variants were identified that are of unknown biological and clinical relevance, so called unclassified variants (UCV), including missense changes, small in-frame insertions or deletions, and potential splice site alterations. UCV are particularly problematic for cancer risk estimation and clinical management, as their functional implications are not immediately apparent BRCA1/2 pre-mRNA processing is challenging as it frequently requires experimental validation. Numerous BRCA1/2 splicing mutations have been identified by using either mRNA derived from mutation carriers or by employing BRCA1/2 minigene constructs BRCA1/2 pre-mRNA processing remain elusive.Between 1997 and 2012, more than 13.000 families fulfilling the criteria for hereditary breast and ovarian cancer were tested for mutations affecting the major susceptibility genes BRCA1 have been reported so far BRCA1/2 splicing mutations, both intronic and exonic, appears to be required. The pathogenic potential of putative splicing mutations is routinely estimated using in silico prediction analyses such as the maximum entropy model (MaxEntScan) BRCA1 variants on pre-mRNA processing by employing bioinformatic prediction tools and experimental analysis of mRNA derived from carriers. Among the 24 intronic and 6 exonic variants analyzed, a total of 25 variants, including 4 missense mutations and 2 silent alterations were identified spliceogenic, either cause/enhance exon skipping or activation of cryptic splice sites, or both. Interestingly, 23 out of 24 intronic variants were correctly predicted by combined bioinformatic analyses, while 3 out of 6 exonic variants clearly escaped in silico detection. In summary, these data contribute to the recent knowledge of BRCA1 splicing mutations and further highlight the importance of experimental splicing analysis particularly for exonic BRCA1 variants and the need for improved bioinformatic prediction of exonic variants that affect the splicing machinery.Today, there is ample evidence that disease-causing splicing mutations are more prevalent than previously expected. An often-cited estimate of 15% reflects only mutations that are known to affect the splice sites Probands were recruited at the German consortium of hereditary breast and ovarian cancer (GC-HBOC) centres in Cologne, Dresden, Kiel or Munich. Genomic DNA was isolated from venous blood samples using the salting out method BRCA1 pre-mRNA processing. Total RNA was isolated from peripheral blood leukocytes using TRIzol Reagent . RNA concentrations were determined using a NanoDrop ND-1000 spectrophotometer . Reverse transcription was carried out by employing the Transcriptor High Fidelity cDNA Synthesis Kit  using 500 ng of total RNA and oligo (dT)18 primers. Subsequent PCR were performed using the Qiagen Multiplex PCR Kit , template-specific primers (Reverse transcription PCR (RT-PCR) was performed to determine effects of intronic and exonic sequence variants on  primers , and one−ΔΔCt) was used to calculate the relative expression levels of each amplicon. For real-time quantification of target gene expression, one-step real-time PCR was performed using the QuantiTect SYBR Green RT–PCR Kit  on an Applied Biosystems StepOne Plus Real-Time PCR System . Each 20 µl RT–PCR mix contained 10 ng total RNA (4 ng/µl), 2 µl of the primer dilution, 10 µl Quanti-Tect SYBR Green RT-Master Mix and 0.2 µl QuantiTect RT Mix. One-step RT–PCR reactions were carried out in 96-well optical reaction plates, covered with Optical Adhesive Covers . Cycling conditions were as follows: 50°C for 30 min (reverse transcription step), 95°C for 15 min and 40 cycles of 94°C for 15 s, 60°C for 30 s and 72°C for 35 s. Real-time RT–PCR was conducted four times for each amplicon and each RNA sample. The comparative method of relative quantification (2http://www.umd.be/HSF/). For HSF, a ΔCV of 10% or more is considered significant based on empirical studies of known splicing mutations BRCA1. For comparison with the BIC website in the main text the description according to BIC is given. Genomic variation frequencies are given according to the 1000 Genomes (http://www.1000genomes.org), the Exome Variant Server  the Breast Cancer Information Core  databases and BRCA2006, the internal databases of the German Consortium of Hereditary Breast and Ovarian Cancer (GC-HBOC).For splice site prediction, we employed the maximum entropy model (MaxEntScan) BRCA1 variants (derived from 14 independent cases) located within invariant donor or acceptor dinucleotides, all of which are predicted to be damaging according to both, HSF and MaxEntScan analyses  or completely lack exon 5 (BRCA1- Δex5) IVS4-1G>C markedly increases skipping of exon 5  have been reported to enhance the usage of an upstream cryptic splice site, resulting in a 3′ 22 bp deletion of exon 5 on mRNA level (BRCA1-Δ22ntex5) IVS5+1G>C variant IVS17-2A>G  and is considered damaging IVS16+3G>C and five more variants  likely impair existing splice sites according to HSF and/or MaxEntScan, while the remaining variants appear to be neutral or below the respective thresholds  are predicted to impair the splice donor site of intron 16. As expected, retention of intronic sequences was also observed in each case  . To validate this finding, we performed quantitative real-time analyses to evaluate the effects of IVS4-18T>G on BRCA1 exon 5 exclusion. While BRCA1- Δex5 represents a rare isoform in controls, the occurrence of IVS4-18T>G increases exon 5 exclusion reaching levels of significance compared with control samples . All 6 variants locate in the close vicinity (≤3 nt) to the respective exon borders. Only 3/6 variants, 4304G>A,Q1395Q, 4794G>A,E1559K and 5193G>C,D1692H4304G>A,Q1395Q, affecting the last nucleotide of exon 12, causes exon 12 exclusion . The remaining variant 710C>T,C197CBRCA1 710C>T,C197C710C>T,C197C increases the abundance of BRCA1 transcripts lacking exon 9 and exons 9 and 10 about 2fold, reaching levels of significance compared with each control sample . For 787A>G,K223R, direct sequencing of wild-type sized RT-PCR products following gel extraction revealed a heterozygous A/G signal at position 787, indicating that the 787A>G transition impairs correct BRCA1 pre-mRNA splicing in an incomplete manner and thus, mutant BRCA1 proteins carrying the K223R amino acid substitution may be expressed. In contrast, transcripts carrying the 4304G>A,Q1395Q, 4794G>A,E1559K; 5193G>C,D1692H or 5527G>C,G1803A variants were not detected.Exonic alterations potentially affect splicing and thus, we analyzed the impact of 6 distinct exonic variants on ocessing . While 3xclusion  D. 4794G exon 15  E. 5193Gcontrols  G. Notewxclusion  B. 5527Gl sample . IncludiBRCA1/2, CHEK2RAD51Cin silico prediction and functionally analyzed using either mRNA derived from mutation carriers or by employing minigene constructs in silico prediction as demonstrated in this study. Moreover, when predicted deleterious, it frequently remains elusive whether deleterious variants cause exon skipping and/or activate cryptic splice sites which may be located distant to the wild-type sites, hence not covered by the prediction algorithms.Screening for pathogenic variants in breast and ovarian cancer genes BRCA1 variants regarding their spliceogenic potential using in silico  along with in vitro mRNA analyses. Among those, all 12 variants located within the canonical splice sites were predicted damaging, which was in-line with our in vitro mRNA analyses. A total of 6 out of 12 intronic variants outside the canonical splice sites were predicted damaging by HSF and/or MaxEntScan, which was also confirmed. Among the 6 remaining intronic variants predicted neutral, we demonstrate IVS4-18T>G to marginally impair proper processing of BRCA1 pre-mRNA as it causes an approximately three-fold increased abundance of BRCA1 transcripts lacking exon 5. IVS4-18T>G is listed 4 times in patient databases  and was not found on control chromosomes according to the EVS database. Even though the rare variant IVS4-18T>G only moderately augments the relative amount of BRCA1- Δex5 mRNA species  to the respective exon border, one silent and two missense alterations indeed were predicted damaging and cause substantial splice defects. The remaining variants  were below the respective HSF and MaxEntScan thresholds. Interestingly, 787A>G,K223R as well as 710C>T,C197C and 5527G>C,G1803A clearly escaped in silico prediction. 5527G>C,G1803A, which affects the second nucleotide of exon 23, causes skipping of that exon  while 787A>G,K223R impairs exon 10 recognition. Noteworthy, the latter variant disrupts BRCA1 pre-mRNA processing in an incomplete manner and thus, BRCA1 proteins carrying the possibly damaging K223R amino acid substitution are likely to be translated . The remaining, silent variant predicted neutral  causes a two fold increased abundance of the naturally occurring, rare isoforms BRCA1-Δ9 and BRCA1-Δ9/10 compared to controls . The degree of likelihood of pathogenicity of each variant remains elusive and requires further investigation, including multifactorial likelihood analysis and other approaches in silico prediction algorithms used in this study, 23 out of 24 intronic variants were predicted correctly by combined in silico analysis . Noteworthy, the MaxEntScan prediction performance clearly exceeds that of HSF in our cohort. Besides IVS4-18T>G, the remaining 23 out of 24 intronic variants were properly predicted by MaxEntScan, while 4 intronic variants experimentally proven damaging , 10 (B), 11 (C), 12 (D), 15 (E), 16 (F), 17 (G), 18 (H), 20 (I), 21 (J), 22  and 23 (M). The topmost band in lane IVS2-1G>C (A) and the middle bands in lanes IVS9-2A>C (B), IVS21-1G>T (K) and IVS22+2delT (K) could not be identified as additional BRCA1 isoforms by direct sequencing and thus appear to be unspecific (data not shown). RT-PCR signals suggested to be unspecific are marked with red asterisks. In case of the variants IVS16+4A>G (F), IVS18+1G>C (H), IVS21-1G>T (K) and IVS22+2delT (K), mRNA samples derived from two or three mutation carriers were analyzed, which are unrelated in case of IVS18+1G>C. The variant IVS9-2A>C (B) IVS20-14C>G (J), classified as neutral RT-PCR analyses of (PPT)Click here for additional data file.Table S1Classification, frequencies and in silico characterization of analyzed variants.A: BRCA1 mutations within invariant splice sites; B: Intronic BRCA1 variants outside invariant splice sites; C: Exonic BRCA1 variants; BIC, EVS and 1000 Genomes entries are as of 02/23/2012. BRCA2006 data of the GC-HBOC are as of 04/10/2012. EVS data refers to variation frequencies in the European/American population (rs numbers are given only when frequency data is available). Valuation of variants by the BIC steering committee is given in brackets, when available . The consensus values (CVs) for wildtype and mutant splice sites provided by HSF analysis are shown. For HSF prediction, a ΔCV of 10% or more is considered significant. For MaxEntScan analysis, a cutoff value of 20% has been suggested. Differences considered significant are shown in bold./ = no difference between for wildtype and mutant splice sites according to HSF or MaxEntScan.(DOC)Click here for additional data file.Table S2Oligonucleotides used for non-quantitative RT-PCR (A) and quantitative real-time RT-PCR analyses (B).(DOC)Click here for additional data file.