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Common variable immunodeficiency (CVID), the most prevalent symptomatic primary immunodeficiency, displays impaired terminal B-cell differentiation and defective antibody responses. Incomplete genetic penetrance and ample phenotypic expressivity in CVID suggest the participation of additional pathogenic mechanisms. Monozygotic (MZ) twins discordant for CVID are uniquely valuable for studying the contribution of epigenetics to the disease. Here, we generate a single-cell epigenomics and transcriptomics census of naïve-to-memory B cell differentiation in a CVID-discordant MZ twin pair. Our analysis identifies DNA methylation, chromatin accessibility and transcriptional defects in memory B-cells mirroring defective cell-cell communication upon activation. These findings are validated in a cohort of CVID patients and healthy donors. Our findings provide a comprehensive multi-omics map of alterations in naïve-to-memory B-cell transition in CVID and indicate links between the epigenome and immune cell cross-talk. Our resource, publicly available at the Human Cell Atlas, gives insight into future diagnosis and treatments of CVID patients. ; This study was funded by: Spanish Ministry of Science and Innovation (grant number PID2020-117212RB-I00/AEI/10.13038/501100011033) (E.B.), Instituto de Salud Carlos III (ISCIII), Ref. AC18/00057, associated with i-PAD project (ERARE European Union program) (E.B.), Wellcome Sanger core funding (grant no. WT206194) (R.V.-T.), the Chan Zuckerberg Initiative (grant 2020-216799) (R.V.-T. and E.B.), an EMBO short-term fellowship (J.R.U.), Fondo de Investigación Sanitaria Instituto de Salud Carlos III (FIS PI16/01605) (L.P.-M.), the Spanish Ministry of Science, Innovation and Universities (SAF2017-89109-P; AEI/FEDER, UE) (H.H.), Instituto de Salud Carlos III, Ministry of Health (PI16/00759) and European Regional Development Fund-European Social Fund—FEDER-FSE) (C.R-G.), Grupo DISA (OA18/017) (C.R.-G.), the UK Biotechnology and Biological Sciences Research Council (BBS/E/B/000C0426) (G.K.) ...

Single-cell RNA sequencing is at the forefront of high-resolution phenotyping experiments for complex samples. Although this methodology requires specialized equipment and expertise, it is now widely applied in research. However, it is challenging to create broadly applicable experimental designs because each experiment requires the user to make informed decisions about sample preparation, RNA sequencing and data analysis. To facilitate this decision-making process, in this tutorial we summarize current methodological and analytical options, and discuss their suitability for a range of research scenarios. Specifically, we provide information about best practices for the separation of individual cells and provide an overview of current single-cell capture methods at different cellular resolutions and scales. Methods for the preparation of RNA sequencing libraries vary profoundly across applications, and we discuss features important for an informed selection process. An erroneous or biased analysis can lead to misinterpretations or obscure biologically important information. We provide a guide to the major data processing steps and options for meaningful data interpretation. These guidelines will serve as a reference to support users in building a single-cell experimental framework-from sample preparation to data interpretation-that is tailored to the underlying research context. ; H.H. is a Miguel Servet (CP14/00229) researcher funded by the Spanish Institute of Health Carlos III (ISCIII). This work received funding from the European Union's Horizon 2020 research and innovation program under Marie Skłodowska-Curie grant agreement no. H2020-MSCA-ITN-2015-675752 (SINGEK; A.L.) and the Ministerio de Ciencia, Innovación y Universidades (SAF2017-89109-P; AEI/FEDER, UE; H.H.). This project has been made possible in part by grant no. 2018-182827 (H.H.) from the Chan Zuckerberg Initiative DAF, an advised fund of the Silicon Valley Community Foundation

Data de publicació electrònica: 23-03-2021 ; Spatially resolved gene expression profiles are key to understand tissue organization and function. However, spatial transcriptomics (ST) profiling techniques lack single-cell resolution and require a combination with single-cell RNA sequencing (scRNA-seq) information to deconvolute the spatially indexed datasets. Leveraging the strengths of both data types, we developed SPOTlight, a computational tool that enables the integration of ST with scRNA-seq data to infer the location of cell types and states within a complex tissue. SPOTlight is centered around a seeded non-negative matrix factorization (NMF) regression, initialized using cell-type marker genes and non-negative least squares (NNLS) to subsequently deconvolute ST capture locations (spots). Simulating varying reference quantities and qualities, we confirmed high prediction accuracy also with shallowly sequenced or small-sized scRNA-seq reference datasets. SPOTlight deconvolution of the mouse brain correctly mapped subtle neuronal cell states of the cortical layers and the defined architecture of the hippocampus. In human pancreatic cancer, we successfully segmented patient sections and further fine-mapped normal and neoplastic cell states. Trained on an external single-cell pancreatic tumor references, we further charted the localization of clinical-relevant and tumor-specific immune cell states, an illustrative example of its flexible application spectrum and future potential in digital pathology. ; Funding: Ministerio de Ciencia, Innovación y Universidades [SAF2017-89109-P, AEI/FEDER to U.E.]; project (BCLLATLAS) that has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme [810287]; Chan Zuckerberg Initiative (in part); Spanish Ministry of Science and Innovation to the EMBL partnership, the Centro de Excelencia Severo Ochoa and the CERCA Programme/Generalitat de Catalunya; Spanish Ministry of Science and Innovation through the Instituto de Salud Carlos III, the Generalitat de Catalunya through Departament de Salut and Departament d'Empresa i Coneixement; Spanish Ministry of Science and Innovation with funds from the European Regional Development Fund (ERDF) corresponding to the 2014–2020 Smart Growth Operating Program. Funding for open access charge: Ministerio de Ciencia, Innovación y Universidades [SAF2017-89109-P, AEI/FEDER to U.E.]

Single-cell RNA sequencing (scRNA-seq) is the leading technique for characterizing the transcriptomes of individual cells in a sample. The latest protocols are scalable to thousands of cells and are being used to compile cell atlases of tissues, organs and organisms. However, the protocols differ substantially with respect to their RNA capture efficiency, bias, scale and costs, and their relative advantages for different applications are unclear. In the present study, we generated benchmark datasets to systematically evaluate protocols in terms of their power to comprehensively describe cell types and states. We performed a multicenter study comparing 13 commonly used scRNA-seq and single-nucleus RNA-seq protocols applied to a heterogeneous reference sample resource. Comparative analysis revealed marked differences in protocol performance. The protocols differed in library complexity and their ability to detect cell-type markers, impacting their predictive value and suitability for integration into reference cell atlases. These results provide guidance both for individual researchers and for consortium projects such as the Human Cell Atlas. ; This project has been made possible in part by grant no. 2018-182827 from the Chan Zuckerberg Initiative DAF, an advised fund of the Silicon Valley Community Foundation. H.H. is a Miguel Servet (CP14/00229) researcher funded by the Spanish Institute of Health Carlos III (ISCIII). C.M. is supported by an AECC postdoctoral fellowship. This work has received funding from the European Union's Horizon 2020 research and innovation program under Marie Skłodowska-Curie grant agreement no. H2020-MSCA-ITN-2015-675752 (Singek), and the Ministerio de Ciencia, Innovación y Universidades (SAF2017-89109-P; AEI/FEDER, UE). S. was supported by the German Research Foundation's (DFG's) (GR4980) Behrens-Weise-Foundation. C.Z. was supported by the European Molecular Biology Organization through the long-term fellowship ALTF 673-2017. The snRNA-seq data were generated with support from the National Institute of Allergy and Infectious Diseases (grant no. U24AI118672), I.N. was supported by JST CREST (grant no. JPMJCR16G3) , Japan. A.J., L.E.W., J.W.B. and W.E. were supported by funding from the DFG (EN 1093/2-1 and SFB1243 TP A14). This publication is part of a project (BCLLATLAS) that received funding from the European Research Council under the European Union's Horizon 2020 research and innovation program (grant agreement no. 810287). Core funding was from the ISCIII and the Generalitat de Catalunya

Female fertility is inversely correlated with maternal age due to a depletion of the oocyte pool and a reduction in oocyte developmental competence. Few studies have addressed the effect of maternal age on the human mature oocyte (MII) transcriptome, which is established during oocyte growth and maturation, however, the pathways involved remain unclear. Here, we characterize and compare the transcriptomes of a large cohort of fully grown germinal vesicle stage (GV) and in vitro matured (IVM-MII) oocytes from women of varying reproductive age. First, we identified two clusters of cells reflecting the oocyte maturation stage (GV and IVM-MII) with 4445 and 324 putative marker genes, respectively. Furthermore, we identified genes for which transcript representation either progressively increased or decreased with age. Our results indicate that the transcriptome is more affected by age in IVM-MII oocytes (1219 genes) than in GV oocytes (596 genes). In particular, we found that transcripts of genes involved in chromosome segregation and RNA splicing significantly increased representation with age, while genes related to mitochondrial activity showed a lower representation. Gene regulatory network analysis facilitated the identification of potential upstream master regulators of the genes involved in those biological functions. Our analysis suggests that advanced maternal age does not globally affect the oocyte transcriptome at GV or IVM-MII stages. Nonetheless, hundreds of genes displayed altered transcript representation, particularly in IVM-MII oocytes, which might contribute to the age-related quality decline in human oocytes. ; Work on this study in the laboratory of B.P. has been funded by the AXA research fund (AXA Chair in Risk prediction in age-related diseases), contributions from Clinica EUGIN (Identification of Epigenetic Effects of Ageing on Human Oocytes), the Spanish Ministry of Science, Innovation and Universities (BFU2017-88407-P), the Agencia Estatal de Investigación (AEI) (EUR2019-103817) and the Catalan Agència de Gestió d'Ajuts Universitaris i de Recerca (AGAUR, 2017 SGR 346). S.L. has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 754422. We acknowledge support of the Spanish Ministry of Science and Innovation through the Instituto de Salud Carlos III, to the EMBL partnership and to the Co-financing with funds from the European Regional Development Fund (FEDER) (Programa Operativo FEDER Plurirregional de España (POPE) 2014-2020). We also acknowledge support of the Centro de Excelencia Severo Ochoa and the Generalitat de Catalunya through the CERCA Programme, the Departament de Salut and Departament d'Empresa i Coneixement and through the Secretaria d'Universitats i Recerca for the Co-financing with FEDER funds (Programa Operatiu FEDER de Catalunya 2014-2020). Furthermore, this study has been supported by intramural funding of Clinica EUGIN to R.V.

The authors thank the Hematopathology Collection registered at the Biobank of Hospital Clínic—Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) as well as Sílvia Martín for the technical support. This study was supported by the "la Caixa" Foundation (CLLEvolution-LCF/PR/HR17/52150017, Health Research 2017 Program HR17-00221, to EC), the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (810287, BCLLatlas, to EC, and HH), CERCA Program/Generalitat de Catalunya, Generalitat de Catalunya Suport Grups de Recerca AGAUR 2017-SGR-1142 (to EC), CIBERONC (CB16/12/00225 to EC), Ministerio de Ciencia e Innovación PID2020-117185RB-I00 (to XSP), FEDER: European Regional Development Fund "Una manera de hacer Europa", and Fundación Asociación Española Contra el Cáncer FUNCAR-PRYGN211258SUÁR (to XSP). The authors thankfully acknowledge the computer resources at MareNostrum4 and the technical support provided by Barcelona Supercomputing Center (RES activity BCV-2018-3-0001). FN acknowledge research support from the American Association for Cancer Research (2021 AACR-Amgen Fellowship in Clinical/Translational Cancer Research, Grant Number 21-40-11-NADE), the European Hematology Association (EHA Junior Research Grant 2021, Grant Number RG-202012-00245), and the Lady Tata Memorial Trust (International Award for Research in Leukemia 2021–2022, Grant Number LADY_TATA_21_3223). EC is an Academia Researcher of the "Institució Catalana de Recerca i Estudis Avançats" (ICREA) of the Generalitat de Catalunya. This work was partially developed at the Centre Esther Koplowitz (CEK, Barcelona, Spain). ; Peer Reviewed ; Postprint (published version)

DNA methylation is an epigenetic modification involved in regulatory processes such as cell differentiation during development, X-chromosome inactivation, genomic imprinting and susceptibility to complex disease. However, the dynamics of DNA methylation changes between humans and their closest relatives are still poorly understood. We performed a comparative analysis of CpG methylation patterns between 9 humans and 23 primate samples including all species of great apes (chimpanzee, bonobo, gorilla and orangutan) using Illumina Methylation450 bead arrays. Our analysis identified ∼800 genes with significantly altered methylation patterns among the great apes, including ∼170 genes with a methylation pattern unique to human. Some of these are known to be involved in developmental and neurological features, suggesting that epigenetic changes have been frequent during recent human and primate evolution. We identified a significant positive relationship between the rate of coding variation and alterations of methylation at the promoter level, indicative of co-occurrence between evolution of protein sequence and gene regulation. In contrast, and supporting the idea that many phenotypic differences between humans and great apes are not due to amino acid differences, our analysis also identified 184 genes that are perfectly conserved at protein level between human and chimpanzee, yet show significant epigenetic differences between these two species. We conclude that epigenetic alterations are an important force during primate evolution and have been under-explored in evolutionary comparative genomics. © 2013 Hernando-Herraez et al. ; TMB is supported by the European Research Council (ERC Starting Grant, StG_20091118) and the Spanish Government (BFU2011-28549). AJS is supported by NIH grants 1R01DA033660, 1R01HG006696, and a grant from the Alzheimer's Association (2012ALZNIRG69983). IHH is supported by the European Social Fund, AGAUR (Generalitat de Catalunya, Spain) and the Spanish National Research Council (CSIC). We also thank the Spanish Government for the grant BFU2009-13409-C02-02 to AN and the Barcelona Zoo (Ajuntament de Barcelona) for an award to JPM. ; Peer Reviewed

During aging, stromal functions are thought to be impaired, but little is known whether this stems from changes of fibroblasts. Using population- and single-cell transcriptomics, as well as long-term lineage tracing, we studied whether murine dermal fibroblasts are altered during physiological aging under different dietary regimes that affect longevity. We show that the identity of old fibroblasts becomes undefined, with the fibroblast states present in young skin no longer clearly demarcated. In addition, old fibroblasts not only reduce the expression of genes involved in the formation of the extracellular matrix, but also gain adipogenic traits, paradoxically becoming more similar to neonatal pro-adipogenic fibroblasts. These alterations are sensitive to systemic metabolic changes: long-term caloric restriction reversibly prevents them, whereas a high-fat diet potentiates them. Our results therefore highlight loss of cell identity and the acquisition of adipogenic traits as a mechanism underlying cellular aging, which is influenced by systemic metabolism. ; M.C.S. was supported by a Boehringer Ingelheim Fonds International PhD fellowship. IRB Barcelona is the recipient of a Severo Ochoa Award of Excellence from MINECO (Government of Spain). H.H. is a Miguel Servet (CP14/00229) researcher funded by the Spanish Institute of Health Carlos III (ISCIII). This work has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sk1odowska-Curie grant agreement No. H2020-MSCA-ITN-2015-675752 (SINGEK)

Although single base-pair resolution DNA methylation landscapes for embryonic and different somatic cell types provided important insights into epigenetic dynamics and cell-type specificity, such comprehensive profiling is incomplete across human cancer types. This prompted us to perform genome-wide DNA methylation profiling of 22 samples derived from normal tissues and associated neoplasms, including primary tumors and cancer cell lines. Unlike their invariant normal counterparts, cancer samples exhibited highly variable CpG methylation levels in a large proportion of the genome, involving progressive changes during tumor evolution. The whole-genome sequencing results from selected samples were replicated in a large cohort of 1112 primary tumors of various cancer types using genome-scale DNA methylation analysis. Specifically, we determined DNA hypermethylation of promoters and enhancers regulating tumor-suppressor genes, with potential cancer-driving effects. DNA hypermethylation events showed evidence of positive selection, mutual exclusivity and tissue specificity, suggesting their active participation in neoplastic transformation. Our data highlight the extensive changes in DNA methylation that occur in cancer onset, progression and dissemination. ; This work was supported by Institute of Health Carlos III ISCIII Project no. PI11/00321, Spanish Cancer Research Network (RTICC) no. RD12/0036/0039; European Development Regional Fund, 'A way to achieve Europe' ERDF (SAF2014-55000-R), Sandra Ibarra Foundation; Olga Torres Foundation; Cellex Foundation; AGAUR 2014SGR633 grant; Health and Science Departments of the Catalan government (Generalitat de Catalunya) and European Community's Seventh Framework Program (FP7/2007-2013), grant HEALTH-F5-2011-282510 – BLUEPRINT. HH is a Miguel Servet (CP14/00229) ISCII researcher.

Adult hematopoietic stem cells (HSCs) are rare multipotent cells in bone marrow that are responsible for generating all blood cell types. HSCs are a heterogeneous group of cells with high plasticity, in part, conferred by epigenetic mechanisms. PHF19, a subunit of the Polycomb repressive complex 2 (PRC2), is preferentially expressed in mouse hematopoietic precursors. Here, we now show that, in stark contrast to results published for other PRC2 subunits, genetic depletion of Phf19 increases HSC identity and quiescence. While proliferation of HSCs is normally triggered by forced mobilization, defects in differentiation impede long-term correct blood production, eventually leading to aberrant hematopoiesis. At molecular level, PHF19 deletion triggers a redistribution of the histone repressive mark H3K27me3, which notably accumulates at blood lineage-specific genes. Our results provide novel insights into how epigenetic mechanisms determine HSC identity, control differentiation, and are key for proper hematopoiesis. ; The work in the Di Croce laboratory is supported by grants from the Spanish of Economy, Industry, and Competitiveness (MEIC) (BFU2016-75008-P), "Fundación Vencer El Cancer" (VEC), the European Regional Development Fund (FEDER), Fundació "La Marató de TV3," and from AGAUR. The laboratory of A.B. is supported by SAF2016-75613-R from the Ministerio de Ciencia, Innovación y Universidades. H.H. is a Miguel Servet (CP14/00229) researcher funded by the Spanish Institute of Health Carlos III (ISCIII) and received funding from the European Union's Horizon 2020 research and innovation programme (MSCA-ITN-2015-675752) and the Ministerio de Ciencia, Innovación y Universidades (SAF2017-89109-P; AEI/FEDER, UE). P.V. was supported by "Fundación Científica de la Asociación Española Contra el Cáncer."

The tumor immune microenvironment is a main contributor to cancer progression and a promising therapeutic target for oncology. However, immune microenvironments vary profoundly between patients, and biomarkers for prognosis and treatment response lack precision. A comprehensive compendium of tumor immune cells is required to pinpoint predictive cellular states and their spatial localization. We generated a single-cell tumor immune atlas, jointly analyzing published data sets of >500,000 cells from 217 patients and 13 cancer types, providing the basis for a patient stratification based on immune cell compositions. Projecting immune cells from external tumors onto the atlas facilitated an automated cell annotation system. To enable in situ mapping of immune populations for digital pathology, we applied SPOTlight, combining single-cell and spatial transcriptomics data and identifying colocalization patterns of immune, stromal, and cancer cells in tumor sections. We expect the tumor immune cell atlas, together with our versatile toolbox for precision oncology, to advance currently applied stratification approaches for prognosis and immunotherapy. ; This publication is part of a project (BCLLATLAS) that has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 810287). This work has received funding from the Ministerio de Ciencia, Innovación y Universidades (SAF2017-89109-P; AEI/FEDER, UE) and the Fundació La Marató de TV3 (201903-30-31-32).We further acknowledge funding from the St. Vincent's Clinic Foundation (V.T.C.) and the National Health and Medical Research Council Investigator Grant (APP1175781, J.E.P.), the Fundación Asociación Española contra el Cáncer (AECC), FERO (EDM), Ramón Areces Foundation, Cellex Foundation, BBVA (CAIMI), the ISCIII, FIS (PI16/01278), Juan de la Cierva formación fellowship (C.R.-P.) and Sara Borrell fellowship (E.P.-R.). Core funding is from the ISCIII and the Generalitat de Catalunya. We acknowledge support of the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) to the EMBL partnership, the Centro de Excelencia Severo Ochoa, the CERCA Programme / Generalitat de Catalunya, the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) through the nstituto de Salud Carlos III and the Generalitat de Catalunya through Departament de Salut and Departament d'Empresa i Coneixement. We also acknowledge the cofinancing by the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) with funds from the European Regional Development Fund (ERDF) corresponding to the 2014–2020 Smart Growth Operating Program

Robust protocols and automation now enable large-scale single-cell RNA and ATAC sequencing experiments and their application on biobank and clinical cohorts. However, technical biases introduced during sample acquisition can hinder solid, reproducible results, and a systematic benchmarking is required before entering large-scale data production. Here, we report the existence and extent of gene expression and chromatin accessibility artifacts introduced during sampling and identify experimental and computational solutions for their prevention. ; HH is a Miguel Servet (CP14/00229) researcher funded by the Spanish Institute of Health Carlos III (ISCIII). CM and MK are supported by AECC postdoctoral fellowships. This work has received funding from the Ministerio de Ciencia, Innovación y Universidades (SAF2017-89109-P; AEI/FEDER, UE). This study was further funded by the Spanish Ministry of Economy and Competitiveness (grant number: IPT-010000-2010- 36, cofunded by the European Regional Development Fund). Core funding is from the ISCIII and the Generalitat de Catalunya. We acknowledge support of the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) to the EMBL partnership, the Centro de Excelencia Severo Ochoa, the CERCA Programme/Generalitat de Catalunya, the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) through the Instituto de Salud Carlos III and the Generalitat de Catalunya through Departament de Salut and Departament d'Empresa i Coneixement. We also acknowledge the Co-financing by the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) with funds from the European Regional Development Fund (ERDF) corresponding to the 2014–2020 Smart Growth Operating Program. We acknowledge the Generalitat de Catalunya Suport Grups de Recerca AGAUR 2017-SGR-736 (to JIMS) and 2017-SGR-1142 (to EC), and CIBERONC (CB16/12/00225 and CB16/12/00334). EC is an ICREA Academia Researcher. This project received support from the European Commission under the projects DocTIS (H2020, SEP-210574908). This publication is part of a project (BCLLATLAS) that has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement No 810287)

© 2019 The Author(s). ; Mammalian gametogenesis involves dramatic and tightly regulated chromatin remodeling, whose regulatory pathways remain largely unexplored. Here, we generate a comprehensive high-resolution structural and functional atlas of mouse spermatogenesis by combining in situ chromosome conformation capture sequencing (Hi-C), RNA sequencing (RNA-seq), and chromatin immunoprecipitation sequencing (ChIP-seq) of CCCTC-binding factor (CTCF) and meiotic cohesins, coupled with confocal and super-resolution microscopy. Spermatogonia presents well-defined compartment patterns and topological domains. However, chromosome occupancy and compartmentalization are highly re-arranged during prophase I, with cohesins bound to active promoters in DNA loops out of the chromosomal axes. Compartment patterns re-emerge in round spermatids, where cohesin occupancy correlates with transcriptional activity of key developmental genes. The compact sperm genome contains compartments with actively transcribed genes but no fine-scale topological domains, concomitant with the presence of protamines. Overall, we demonstrate how genome-wide cohesin occupancy and transcriptional activity is associated with three-dimensional (3D) remodeling during spermatogenesis, ultimately reprogramming the genome for the next generation. ; This work was supported by the Ministry of Economy and Competitiveness ( BFU2017-89408-R to A.M.P.; BFU2013-47736-P and BFU2017-85926-P to M.A.M.-R.; and CGL2014-54317-P and CGL2017-83802-P to A.R.-H.) and the Agència de Gestió d'Ajuts Universitaris i de Recerca (AGAUR) ( DI2015 to A.R.-H. and R.A.C., as well as SGR468 to M.A.M-R.). Work at CRG, BIST, and UPF was in part funded by the Spanish Ministry of Economy and Competitiveness , 'Centro de Excelencia Severo Ochoa 2013-2017' (SEV-2012-0208), and 'Centro de Excelencia María de Maeztu 2016-2019.' CIC-IBMCC is supported by the Programa de Apoyo a Planes Estratégicos de Investigación de Estructuras de Investigación de Excelencia , co-funded by Junta de Castilla y León ( CSI239P18 ) and the European Regional Development Fund ( CLC–2017–01 ). C.V. is supported by a FPI predoctoral fellowship from the Ministry of Economy and Competitiveness ( BES-2015-072924 ). A.P.-G. is supported by a 'Doctorats Industrials' predoctoral fellowship ( AGAUR ). H.H. is a Miguel Servet ( CP14/00229 ) researcher funded by the Spanish Institute of Health Carlos III (ISCIII), the Agencia Estatal de Investigación (AEI), and FEDER ( SAF2017-89109-P ). C.M. is an Asociación Española Contra el Cáncer (AECC) postdoctoral fellow. M.A.M.-R. acknowledges support by the European Research Council under the 7th Framework Program FP7/2007-2013 (ERC grant agreement 609989 ) and the European Union's Horizon 2020 Research and Innovation Programme (grant agreement 676556 ). A.M.P. and A.R.-H. also acknowledge support from MeioNet ( BFU2015-71786-REDT ).

Background One of the hallmarks of cancer is the disruption of gene expression patterns. Many molecular lesions contribute to this phenotype, and the importance of aberrant DNA methylation profiles is increasingly recognized. Much of the research effort in this area has examined proximal promoter regions and epigenetic alterations at other loci are not well characterized. Results Using whole genome bisulfite sequencing to examine uncharted regions of the epigenome, we identify a type of far-reaching DNA methylation alteration in cancer cells of the distal regulatory sequences described as super-enhancers. Human tumors undergo a shift in super-enhancer DNA methylation profiles that is associated with the transcriptional silencing or the overactivation of the corresponding target genes. Intriguingly, we observe locally active fractions of super-enhancers detectable through hypomethylated regions that suggest spatial variability within the large enhancer clusters. Functionally, the DNA methylomes obtained suggest that transcription factors contribute to this local activity of super-enhancers and that trans-acting factors modulate DNA methylation profiles with impact on transforming processes during carcinogenesis. Conclusions We develop an extensive catalogue of human DNA methylomes at base resolution to better understand the regulatory functions of DNA methylation beyond those of proximal promoter gene regions. CpG methylation status in normal cells points to locally active regulatory sites at super-enhancers, which are targeted by specific aberrant DNA methylation events in cancer, with putative effects on the expression of downstream genes. ; The research leading to these results received funding from: the European Research Council (ERC), grant EPINORC, under agreement number 268626; MICINN Projects–SAF2011-22803 and BFU2011-28549; Ministerio de Economía y Competitividad (MINECO), co-financed by the European Development Regional Fund, 'A way to achieve Europe' ERDF, under grant number SAF2014-55000-R; the Cellex Foundation; AGAUR Catalan Government Project #2009SGR1315; the Institute of Health Carlos III (ISCIII), under the Spanish Cancer Research Network (RTICC) number RD12/0036/0039, the Integrated Project of Excellence number PIE13/00022 (ONCOPROFILE) and the research grant PI11/00321; the Sandra Ibarra Foundation, under IV ghd Grants for breast cancer research; the Olga Torres Foundation; the European Community's Seventh Framework Programme (FP7/2007-2013), grant HEALTH-F5-2011-282510 – BLUEPRINT, and the Health and Science Departments of the Generalitat de Catalunya. H.H. is a Miguel Servet (CP14/00229) researcher funded by the Spanish Institute of Health Carlos III (ISCIII). D.T. and M.E. are ICREA Research Professors. ; Peer Reviewed ; Postprint (author's final draft)