circHIPK3 nucleates IGF2BP2 and functions as a competing endogenous RNA.

Circular RNAs (circRNAs) represent a class of widespread endogenous RNAs that regulate gene expression and thereby influence cell biological decisions with implications for the pathogenesis of several diseases. Here, we disclose a novel gene-regulatory role of circHIPK3 by combining analyses of large genomics datasets and mechanistic cell biological follow-up experiments. Specifically, we use temporal depletion of circHIPK3 or specific RNA binding proteins (RBPs) and identify several perturbed genes by RNA sequencing analyses. Using expression-coupled motif analyses of mRNA expression data from various knockdown experiments, we identify an 11-mer motif within circHIPK3, which is also enriched in genes that become downregulated upon circHIPK3 depletion. By mining eCLIP datasets, we find that the 11-mer motif constitutes a strong binding site for IGF2BP2 and validate this circHIPK3-IGF2BP2 interaction experimentally using RNA-immunoprecipitation and competition assays in bladder cancer cell lines. Our results suggest that circHIPK3 and IGF2BP2 mRNA targets compete for binding. Since the identified 11-mer motif found in circHIPK3 is enriched in upregulated genes following IGF2BP2 knockdown, and since IGF2BP2 depletion conversely globally antagonizes the effect of circHIPK3 knockdown on target genes, our results suggest that circHIPK3 can sequester IGF2BP2 as a competing endogenous RNA (ceRNA), leading to target mRNA stabilization. As an example of a circHIPK3-regulated gene, we focus on the STAT3 mRNA as a specific substrate of IGF2BP2 and validate that manipulation of circHIPK3 regulates IGF2BP2-STAT3 mRNA binding and thereby STAT3 mRNA levels. However, absolute copy number quantifications demonstrate that IGF2BP2 outnumbers circHIPK3 by orders of magnitude, which is inconsistent with a simple 1:1 ceRNA hypothesis. Instead, we show that circHIPK3 can nucleate multiple copies of IGF2BP2, potentially via phase separation, to produce IGF2BP2 condensates. Finally, we show that circHIPK3 expression correlates with overall survival of patients with bladder cancer. Our results are consistent with a model where relatively few cellular circHIPK3 molecules function as inducers of IGF2BP2 condensation thereby regulating STAT3 and other key factors for cell proliferation and potentially cancer progression.

Sequence dependencies and mutation rates of localized mutational processes in cancer.

BACKGROUND: Cancer mutations accumulate through replication errors and DNA damage coupled with incomplete repair. Individual mutational processes often show nucleotide sequence and functional region preferences. As a result, some sequence contexts mutate at much higher rates than others, with additional variation found between functional regions. Mutational hotspots, with recurrent mutations across cancer samples, represent genomic positions with elevated mutation rates, often caused by highly localized mutational processes. METHODS: We count the 11-mer genomic sequences across the genome, and using the PCAWG set of 2583 pan-cancer whole genomes, we associate 11-mers with mutational signatures, hotspots of single nucleotide variants, and specific genomic regions. We evaluate the mutation rates of individual and combined sets of 11-mers and derive mutational sequence motifs. RESULTS: We show that hotspots generally identify highly mutable sequence contexts. Using these, we show that some mutational signatures are enriched in hotspot sequence contexts, corresponding to well-defined sequence preferences for the underlying localized mutational processes. This includes signature 17b (of unknown etiology) and signatures 62 (POLE deficiency), 7a (UV), and 72 (linked to lymphomas). In some cases, the mutation rate and sequence preference increase further when focusing on certain genomic regions, such as signature 62 in transcribed regions, where the mutation rate is increased up to 9-folds over cancer type and mutational signature average. CONCLUSIONS: We summarize our findings in a catalog of localized mutational processes, their sequence preferences, and their estimated mutation rates.

Epigenetic Silencing of LRP2 Is Associated with Dedifferentiation and Poor Survival in Multiple Solid Tumor Types.

More than 80% of human cancers originate in epithelial tissues. Loss of epithelial cell characteristics are hallmarks of tumor development. Receptor-mediated endocytosis is a key function of absorptive epithelial cells with importance for cellular and organismal homeostasis. LRP2 (megalin) is the largest known endocytic membrane receptor and is essential for endocytosis of various ligands in specialized epithelia, including the proximal tubules of the kidney, the thyroid gland, and breast glandular epithelium. However, the role and regulation of LRP2 in cancers that arise from these tissues has not been delineated. Here, we examined the expression of LRP2 across 33 cancer types in The Cancer Genome Atlas. As expected, the highest levels of LRP2 were found in cancer types that arise from LRP2-expressing absorptive epithelial cells. However, in a subset of tumors from these cancer types, we observed epigenetic silencing of LRP2. LRP2 expression showed a strong inverse correlation to methylation of a specific CpG site (cg02361027) in the first intron of the LRP2 gene. Interestingly, low expression of LRP2 was associated with poor patient outcome in clear cell renal cell carcinoma, papillary renal cell carcinoma, mesothelioma, papillary thyroid carcinoma, and invasive breast carcinoma. Furthermore, loss of LRP2 expression was associated with dedifferentiated histological and molecular subtypes of these cancers. These observations now motivate further studies on the functional role of LRP2 in tumors of epithelial origin and the potential use of LRP2 as a cancer biomarker.

The landscape and driver potential of site-specific hotspots across cancer genomes.

Large sets of whole cancer genomes make it possible to study mutation hotspots genome-wide. Here we detect, categorize, and characterize site-specific hotspots using 2279 whole cancer genomes from the Pan-Cancer Analysis of Whole Genomes project and provide a resource of annotated hotspots genome-wide. We investigate the excess of hotspots in both protein-coding and gene regulatory regions and develop measures of positive selection and functional impact for individual hotspots. Using cancer allele fractions, expression aberrations, mutational signatures, and a variety of genomic features, such as potential gain or loss of transcription factor binding sites, we annotate and prioritize all highly mutated hotspots. Genome-wide we find more high-frequency SNV and indel hotspots than expected given mutational background models. Protein-coding regions are generally enriched for SNV hotspots compared to other regions. Gene regulatory hotspots show enrichment of potential same-patient second-hit missense mutations, consistent with enrichment of hotspot driver mutations compared to singletons. For protein-coding regions, splice-sites, promoters, and enhancers, we see an excess of hotspots associated with cancer genes. Interestingly, missense hotspot mutations in tumor suppressors are associated with elevated expression, suggesting localized amino-acid changes with functional impact. For individual non-coding hotspots, only a small number show clear signs of positive selection, including known sites in the TERT promoter and the 5' UTR of TP53. Most of the new candidates have few mutations and limited driver evidence. However, a hotspot in an enhancer of the oncogene POU2AF1, which may create a transcription factor binding site, presents multiple lines of driver-consistent evidence.

miRNA activity inferred from single cell mRNA expression.

High throughput single-cell RNA sequencing (scRNAseq) can provide mRNA expression profiles for thousands of cells. However, miRNAs cannot currently be studied at the same scale. By exploiting that miRNAs bind well-defined sequence motifs and typically down-regulate target genes, we show that motif enrichment analysis can be used to derive miRNA activity estimates from scRNAseq data. Motif enrichment analyses have traditionally been used to derive binding motifs for regulatory factors, such as miRNAs or transcription factors, that have an effect on gene expression. Here we reverse its use. By starting from the miRNA seed site, we derive a measure of activity for miRNAs in single cells. We first establish the approach on a comprehensive set of bulk TCGA cancer samples (n = 9679), with paired mRNA and miRNA expression profiles, where many miRNAs show a strong correlation with measured expression. By downsampling we show that the method can be used to estimate miRNA activity in sparse data comparable to scRNAseq experiments. We then analyze a human and a mouse scRNAseq data set, and show that for several miRNA candidates, including liver specific miR-122 and muscle specific miR-1 and miR-133a, we obtain activity measures supported by the literature. The methods are implemented and made available in the miReact software. Our results demonstrate that miRNA activities can be estimated at the single cell level. This allows insights into the dynamics of miRNA activity across a range of fields where scRNAseq is applied.

Transcriptome-wide profiles of circular RNA and RNA-binding protein interactions reveal effects on circular RNA biogenesis and cancer pathway expression.

BACKGROUND: Circular RNAs (circRNAs) are stable, often highly expressed RNA transcripts with potential to modulate other regulatory RNAs. A few circRNAs have been shown to bind RNA-binding proteins (RBPs); however, little is known about the prevalence and distribution of these interactions in different biological contexts. METHODS: We conduct an extensive screen of circRNA-RBP interactions in the ENCODE cell lines HepG2 and K562. We profile circRNAs in deep-sequenced total RNA samples and analyze circRNA-RBP interactions using a large set of eCLIP data with binding sites of 150 RBPs. We validate interactions for select circRNAs and RBPs by performing RNA immunoprecipitation and functionally characterize our most interesting candidates by conducting knockdown studies followed by RNA-Seq. RESULTS: We generate a comprehensive catalog of circRNA-RBP interactions in HepG2 and K562 cells. We show that KHSRP binding sites are enriched in flanking introns of circRNAs and that KHSRP depletion affects circRNA biogenesis. We identify circRNAs that are highly covered by RBP binding sites and experimentally validate individual circRNA-RBP interactions. We show that circCDYL, a highly expressed circRNA with clinical and functional implications in bladder cancer, is almost completely covered with GRWD1 binding sites in HepG2 cells, and that circCDYL depletion counteracts the effect of GRWD1 depletion. Furthermore, we confirm interactions between circCDYL and RBPs in bladder cancer cells and demonstrate that circCDYL depletion affects hallmarks of cancer and perturbs the expression of key cancer genes, e.g., TP53. Finally, we show that elevated levels of circCDYL are associated with overall survival of bladder cancer patients. CONCLUSIONS: Our study demonstrates transcriptome-wide and cell-type-specific circRNA-RBP interactions that could play important regulatory roles in tumorigenesis.

Epigenetic and transcriptomic consequences of excess X-chromosome material in 47,XXX syndrome-A comparison with Turner syndrome and 46,XX females.

47,XXX (triple X) and Turner syndrome (45,X) are sex chromosomal abnormalities with detrimental effects on health with increased mortality and morbidity. In karyotypical normal females, X-chromosome inactivation balances gene expression between sexes and upregulation of the X chromosome in both sexes maintain stoichiometry with the autosomes. In 47,XXX and Turner syndrome a gene dosage imbalance may ensue from increased or decreased expression from the genes that escape X inactivation, as well as from incomplete X chromosome inactivation in 47,XXX. We aim to study genome-wide DNA-methylation and RNA-expression changes can explain phenotypic traits in 47,XXX syndrome. We compare DNA-methylation and RNA-expression data derived from white blood cells of seven women with 47,XXX syndrome, with data from seven female controls, as well as with seven women with Turner syndrome (45,X). To address these questions, we explored genome-wide DNA-methylation and transcriptome data in blood from seven females with 47,XXX syndrome, seven females with Turner syndrome, and seven karyotypically normal females (46,XX). Based on promoter methylation, we describe a demethylation of six X-chromosomal genes (AMOT, HTR2C, IL1RAPL2, STAG2, TCEANC, ZNF673), increased methylation for GEMIN8, and four differentially methylated autosomal regions related to four genes (SPEG, MUC4, SP6, and ZNF492). We illustrate how these changes seem compensated at the transcriptome level although several genes show differential exon usage. In conclusion, our results suggest an impact of the supernumerary X chromosome in 47,XXX syndrome on the methylation status of selected genes despite an overall comparable expression profile.

Passenger Mutations in More Than 2,500 Cancer Genomes: Overall Molecular Functional Impact and Consequences.

The dichotomous model of "drivers" and "passengers" in cancer posits that only a few mutations in a tumor strongly affect its progression, with the remaining ones being inconsequential. Here, we leveraged the comprehensive variant dataset from the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) project to demonstrate that-in addition to the dichotomy of high- and low-impact variants-there is a third group of medium-impact putative passengers. Moreover, we also found that molecular impact correlates with subclonal architecture (i.e., early versus late mutations), and different signatures encode for mutations with divergent impact. Furthermore, we adapted an additive-effects model from complex-trait studies to show that the aggregated effect of putative passengers, including undetected weak drivers, provides significant additional power (∼12% additive variance) for predicting cancerous phenotypes, beyond PCAWG-identified driver mutations. Finally, this framework allowed us to estimate the frequency of potential weak-driver mutations in PCAWG samples lacking any well-characterized driver alterations.

Analyses of non-coding somatic drivers in 2,658 cancer whole genomes.

The discovery of drivers of cancer has traditionally focused on protein-coding genes1-4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.

Regmex: a statistical tool for exploring motifs in ranked sequence lists from genomics experiments.

BACKGROUND: Motif analysis methods have long been central for studying biological function of nucleotide sequences. Functional genomics experiments extend their potential. They typically generate sequence lists ranked by an experimentally acquired functional property such as gene expression or protein binding affinity. Current motif discovery tools suffer from limitations in searching large motif spaces, and thus more complex motifs may not be included. There is thus a need for motif analysis methods that are tailored for analyzing specific complex motifs motivated by biological questions and hypotheses rather than acting as a screen based motif finding tool. METHODS: We present Regmex (REGular expression Motif EXplorer), which offers several methods to identify overrepresented motifs in ranked lists of sequences. Regmex uses regular expressions to define motifs or families of motifs and embedded Markov models to calculate exact p-values for motif observations in sequences. Biases in motif distributions across ranked sequence lists are evaluated using random walks, Brownian bridges, or modified rank based statistics. A modular setup and fast analytic p value evaluations make Regmex applicable to diverse and potentially large-scale motif analysis problems. RESULTS: We demonstrate use cases of combined motifs on simulated data and on expression data from micro RNA transfection experiments. We confirm previously obtained results and demonstrate the usability of Regmex to test a specific hypothesis about the relative location of microRNA seed sites and U-rich motifs. We further compare the tool with an existing motif discovery tool and show increased sensitivity. CONCLUSIONS: Regmex is a useful and flexible tool to analyze motif hypotheses that relates to large data sets in functional genomics. The method is available as an R package (https://github.com/muhligs/regmex).

DNA hypermethylation and differential gene expression associated with Klinefelter syndrome.

Klinefelter syndrome (KS) has a prevalence ranging from 85 to 250 per 100.000 newborn boys making it the most frequent sex chromosome aneuploidy in the general population. The molecular basis for the phenotypic traits and morbidity in KS are not clarified. We performed genome-wide DNA methylation profiling of leucocytes from peripheral blood samples from 67 KS patients, 67 male controls and 33 female controls, in addition to genome-wide RNA-sequencing profiling in a subset of 9 KS patients, 9 control males and 13 female controls. Characterization of the methylome as well as the transcriptome of both coding and non-coding genes identified a unique epigenetic and genetic landscape of both autosomal chromosomes as well as the X chromosome in KS. A subset of genes show significant correlation between methylation values and expression values. Gene set enrichment analysis of differentially methylated positions yielded terms associated with well-known comorbidities seen in KS. In addition, differentially expressed genes revealed enrichment for genes involved in the immune system, wnt-signaling pathway and neuron development. Based on our data we point towards new candidate genes, which may be implicated in the phenotype and further point towards non-coding genes, which may be involved in X chromosome inactivation in KS.

APD-Containing Cyclolipodepsipeptides Target Mitochondrial Function in Hypoxic Cancer Cells.

The natural product family of macrocyclic lipodepsipeptides containing the 4-amido-2,4-pentadienoate functionality possesses intriguing cytotoxic selectivity toward hypoxic cancer cells. These subpopulations of cancer cells display increased metastatic potential and resistance to chemo- and radiotherapy. In this paper, we present studies on the mechanism of action of these natural products in hypoxic cancer cells and show that this involves rapid and hypoxia-selective collapse of mitochondrial integrity and function. These events drive a regulated cell death process that potentially could function as a powerful tool in the fight against chemo- and radiotherapy-resistant cancer cells. Toward that end, we demonstrate activity in two different mouse tumor models.

A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data.

BACKGROUND: Detailed modelling of the neutral mutational process in cancer cells is crucial for identifying driver mutations and understanding the mutational mechanisms that act during cancer development. The neutral mutational process is very complex: whole-genome analyses have revealed that the mutation rate differs between cancer types, between patients and along the genome depending on the genetic and epigenetic context. Therefore, methods that predict the number of different types of mutations in regions or specific genomic elements must consider local genomic explanatory variables. A major drawback of most methods is the need to average the explanatory variables across the entire region or genomic element. This procedure is particularly problematic if the explanatory variable varies dramatically in the element under consideration. RESULTS: To take into account the fine scale of the explanatory variables, we model the probabilities of different types of mutations for each position in the genome by multinomial logistic regression. We analyse 505 cancer genomes from 14 different cancer types and compare the performance in predicting mutation rate for both regional based models and site-specific models. We show that for 1000 randomly selected genomic positions, the site-specific model predicts the mutation rate much better than regional based models. We use a forward selection procedure to identify the most important explanatory variables. The procedure identifies site-specific conservation (phyloP), replication timing, and expression level as the best predictors for the mutation rate. Finally, our model confirms and quantifies certain well-known mutational signatures. CONCLUSION: We find that our site-specific multinomial regression model outperforms the regional based models. The possibility of including genomic variables on different scales and patient specific variables makes it a versatile framework for studying different mutational mechanisms. Our model can serve as the neutral null model for the mutational process; regions that deviate from the null model are candidates for elements that drive cancer development.

Pan-cancer screen for mutations in non-coding elements with conservation and cancer specificity reveals correlations with expression and survival.

Cancer develops by accumulation of somatic driver mutations, which impact cellular function. Mutations in non-coding regulatory regions can now be studied genome-wide and further characterized by correlation with gene expression and clinical outcome to identify driver candidates. Using a new two-stage procedure, called ncDriver, we first screened 507 ICGC whole-genomes from 10 cancer types for non-coding elements, in which mutations are both recurrent and have elevated conservation or cancer specificity. This identified 160 significant non-coding elements, including the TERT promoter, a well-known non-coding driver element, as well as elements associated with known cancer genes and regulatory genes (e.g., PAX5, TOX3, PCF11, MAPRE3). However, in some significant elements, mutations appear to stem from localized mutational processes rather than recurrent positive selection in some cases. To further characterize the driver potential of the identified elements and shortlist candidates, we identified elements where presence of mutations correlated significantly with expression levels (e.g., TERT and CDH10) and survival (e.g., CDH9 and CDH10) in an independent set of 505 TCGA whole-genome samples. In a larger pan-cancer set of 4128 TCGA exomes with expression profiling, we identified mutational correlation with expression for additional elements (e.g., near GATA3, CDC6, ZNF217, and CTCF transcription factor binding sites). Survival analysis further pointed to MIR122, a known marker of poor prognosis in liver cancer. In conclusion, the screen for significant mutation patterns coupled with correlative mutational analysis identified new individual driver candidates and suggest that some non-coding mutations recurrently affect expression and play a role in cancer development.

Circular RNA expression is abundant and correlated to aggressiveness in early-stage bladder cancer.

The functions and biomarker potential of circular RNAs (circRNAs) in various cancer types are a rising field of study, as emerging evidence relates circRNAs to tumorigenesis. Here, we profiled the expression of circRNAs in 457 tumors from patients with non-muscle-invasive bladder cancer (NMIBC). We show that a set of highly expressed circRNAs have conserved core splice sites, are associated with Alu repeats, and enriched with Synonymous Constraint Elements as well as microRNA target sites. We identified 113 abundant circRNAs that are differentially expressed between high and low-risk tumor subtypes. Analysis of progression-free survival revealed 13 circRNAs, among them circHIPK3 and circCDYL, where expression correlated with progression independently of the linear transcript and the host gene. In summary, our results demonstrate that abundant circRNAs possess multiple biological features, distinguishing them from low-expressed circRNAs and non-circularized exons, and suggest that circRNAs might serve as a new class of prognostic biomarkers in NMIBC.

Non-coding cancer driver candidates identified with a sample- and position-specific model of the somatic mutation rate.

Non-coding mutations may drive cancer development. Statistical detection of non-coding driver regions is challenged by a varying mutation rate and uncertainty of functional impact. Here, we develop a statistically founded non-coding driver-detection method, ncdDetect, which includes sample-specific mutational signatures, long-range mutation rate variation, and position-specific impact measures. Using ncdDetect, we screened non-coding regulatory regions of protein-coding genes across a pan-cancer set of whole-genomes (n = 505), which top-ranked known drivers and identified new candidates. For individual candidates, presence of non-coding mutations associates with altered expression or decreased patient survival across an independent pan-cancer sample set (n = 5454). This includes an antigen-presenting gene (CD1A), where 5'UTR mutations correlate significantly with decreased survival in melanoma. Additionally, mutations in a base-excision-repair gene (SMUG1) correlate with a C-to-T mutational-signature. Overall, we find that a rich model of mutational heterogeneity facilitates non-coding driver identification and integrative analysis points to candidates of potential clinical relevance.

Profiling of long non-coding RNAs identifies LINC00958 and LINC01296 as candidate oncogenes in bladder cancer.

Aberrant expression of long non-coding RNAs (lncRNAs) has been regarded as a critical component in bladder cancer (BC) and lncRNAs have been associated with BC development and progression although their overall expression and functional significance is still unclear. The aim of our study was to identify novel lncRNAs with a functional role in BC carcinogenesis. RNA-sequencing was used to identify aberrantly expressed lncRNAs in 8 normal and 72 BC samples. We identified 89 lncRNAs that were significantly dys-regulated in BC. Five lncRNAs; LINC00958, LINC01296, LINC00355, LNC-CMC1-1 and LNC-ALX1-2 were selected for further analyses. Silencing of LINC00958 or LINC01296 in vitro reduced both cell viability and migration. Knock-down of LINC00958 also affected invasion and resistance to anoikis. These cellular effects could be linked to direct/indirect regulation of protein coding mRNAs involved in cell death/survival, proliferation and cellular movement. Finally, we showed that LINC00958 binds proteins involved in regulation and initiation of translation and in post-transcriptional modification of RNA, including Metadherin, which has previously been associated with BC. Our analyses identified novel lncRNAs in BC that likely act as oncogenic drivers contributing to an aggressive cancerous phenotype likely through interaction with proteins involved in initiation of translation and/or post-transcriptional modification of RNA.

SNHG5 promotes colorectal cancer cell survival by counteracting STAU1-mediated mRNA destabilization.

We currently have limited knowledge of the involvement of long non-coding RNAs (lncRNAs) in normal cellular processes and pathologies. Here, we identify and characterize SNHG5 as a stable cytoplasmic lncRNA with up-regulated expression in colorectal cancer. Depletion of SNHG5 induces cell cycle arrest and apoptosis in vitro and limits tumour outgrowth in vivo, whereas SNHG5 overexpression counteracts oxaliplatin-induced apoptosis. Using an unbiased approach, we identify 121 transcript sites interacting with SNHG5 in the cytoplasm. Importantly, knockdown of key SNHG5 target transcripts, including SPATS2, induces apoptosis and thus mimics the effect seen following SNHG5 depletion. Mechanistically, we suggest that SNHG5 stabilizes the target transcripts by blocking their degradation by STAU1. Accordingly, depletion of STAU1 rescues the apoptosis induced after SNHG5 knockdown. Hence, we characterize SNHG5 as a lncRNA promoting tumour cell survival in colorectal cancer and delineate a novel mechanism in which a cytoplasmic lncRNA functions through blocking the action of STAU1.

Widespread DNA hypomethylation and differential gene expression in Turner syndrome.

Adults with 45,X monosomy (Turner syndrome) reflect a surviving minority since more than 99% of fetuses with 45,X monosomy die in utero. In adulthood 45,X monosomy is associated with increased morbidity and mortality, although strikingly heterogeneous with some individuals left untouched while others suffer from cardiovascular disease, autoimmune disease and infertility. The present study investigates the leukocyte DNAmethylation profile by using the 450K-Illumina Infinium assay and the leukocyte RNA-expression profile in 45,X monosomy compared with karyotypically normal female and male controls. We present results illustrating that genome wide X-chromosome RNA-expression profile, autosomal DNA-methylation profile, and the X-chromosome methylation profile clearly distinguish Turner syndrome from controls. Our results reveal genome wide hypomethylation with most differentially methylated positions showing a medium level of methylation. Contrary to previous studies, applying a single loci specific analysis at well-defined DNA loci, our results indicate that the hypomethylation extend to repetitive elements. We describe novel candidate genes that could be involved in comorbidity in TS and explain congenital urinary malformations (PRKX), premature ovarian failure (KDM6A), and aortic aneurysm formation (ZFYVE9 and TIMP1).