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 ; "Article signat per 11 autors/es: Romina Royo, Laura Magnano, Julio Delgado, Sara Ruiz-Gil, Josep Ll. Gelpí, Holger Heyn, Malcom A. Taylor, Tatjana Stankovic, Xose S. Puente, Ferran Nadeu & Elías Campo" ; Postprint (published version)
Interoperable metadata is key for the management of genomic information. We propose a flexible approach that we contribute to the standardization by ISO/IEC of a new format for efficient and secure compressed storage and transmission of genomic information ; This work is partly supported by the Spanish Government (GenCom, TEC2015-67774- C2-1-R and TEC2015-67774-2-R). We also thank the EGA team for their valuable comments. ; Peer Reviewed ; Postprint (author's final draft)
Interoperable metadata is key for the management of genomic information. We propose a flexible approach that we contribute to the standardization by ISO/IEC of a new format for efficient and secure compressed storage and transmission of genomic information ; This work is partly supported by the Spanish Government (GenCom, TEC2015-67774- C2-1-R and TEC2015-67774-2-R). We also thank the EGA team for their valuable comments. ; Peer Reviewed ; Postprint (author's final draft)
Genome-wide association studies (GWASs) identified hundreds of signals associated with type 2 diabetes (T2D). To gain insight into their underlying molecular mechanisms, we have created the translational human pancreatic islet genotype tissue-expression resource (TIGER), aggregating >500 human islet genomic datasets from five cohorts in the Horizon 2020 consortium T2DSystems. We impute genotypes using four reference panels and meta-analyze cohorts to improve the coverage of expression quantitative trait loci (eQTL) and develop a method to combine allele-specific expression across samples (cASE). We identify >1 million islet eQTLs, 53 of which colocalize with T2D signals. Among them, a low-frequency allele that reduces T2D risk by half increases CCND2 expression. We identify eight cASE colocalizations, among which we found a T2D-associated SLC30A8 variant. We make all data available through the TIGER portal (http://tiger.bsc.es), which represents a comprehensive human islet genomic data resource to elucidate how genetic variation affects islet function and translates into therapeutic insight and precision medicine for T2D. ; This work has been supported by the European Union's Horizon 2020 research and innovation program T2Dsystems under grant agreement no. 667191 . L.A. was supported by grant BES-2017-081635 of the Severo Ochoa Program, awarded by the Spanish government . I.M. was supported by the FJCI-2017-31878 Juan de la Cierva grant, awarded by the Spanish government . Work in the Cnop and Eizirik labs was further supported by the Fonds National de la Recherche Scientifique (FNRS), the Brussels Region Innoviris project DiaType , and the Walloon Region SPW-EER Win2Wal project BetaSource, Belgium . D.L.E. is supported by a grant from the Welbio–FNRS , Belgium. P.M., L.G., D.L.E., and M.C. are supported by the Innovative Medicines Initiative 2 Joint Undertaking Rhapsody , under grant agreement no. 115881 , which is supported by the European Union's Horizon 2020 research and innovation programme, EFPIA and the Swiss State Secretariat for Education' Research and Innovation (SERI) under contract number 16.0097 . J.M.M. is supported by American Diabetes Association Innovative and Clinical Translational Award 1-19-ICTS-068 . J.C. is supported by an Expanding Excellence in England Award from Research England . H.M., J.L.S.E., and L.E. are supported by the Swedish Strategic Research Foundation ( IRC15-0067 ). A.L.G. is a Wellcome Trust Senior Fellow in Basic Biomedical Science. This work was funded in Oxford and Stanford by the Wellcome Trust ( 095101 , 200837 , 106130 , and 203141 [all to A.L.G.]) and the NIH ( U01-DK105535 and U01-DK085545 [A.L.G.]). The research was funded by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC) (A.L.G.). I.M.-E. was supported by the EFDS/Novo Nordisk Rising Star Programme . Work in the Ferrer lab was supported by the Imperial College London Research Computing Service , the NIHR Imperial BRC , and the Centre for Genomic Regulation (CRG) genomics facility , and grants from Ministerio de Ciencia e Innovación ( BFU2014-54284-R and RTI2018-095666-B-I00 ), the Medical Research Council ( MR/L02036X/1 ), the Wellcome Trust Senior Investigator Award ( WT101033 ), and the European Research Council Advanced Grant ( 789055 ). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health. The technical support group from the Barcelona Supercomputing Center is gratefully acknowledged. Finally, we thank the entire Computational Genomics group at the BSC for their helpful discussions and valuable comments on the manuscript. We also acknowledge Cristian Opi and Laia Codó from the Barcelona Supercomputing Center for excellent website design and allocation of technical support and Isabelle Millard and Anyishaï Musuaya from the ULB Center for Diabetes Research for excellent technical and experimental support. ; Peer Reviewed ; "Article signat per 30 autors/es: Lorena Alonso, Anthony Piron, Ignasi Morán, Marta Guindo-Martínez, Sílvia Bonàs-Guarch, Goutham Atla, Irene Miguel-Escalada, Romina Royo, Montserrat Puiggròs, Xavier Garcia-Hurtado, Mara Suleiman, Lorella Marselli, Jonathan L.S. Esguerra, Jean-Valéry Turatsinze, Jason M. Torres, Vibe Nylander, Ji Chen, Lena Eliasson, Matthieu Defrance, Ramon Amela, MAGIC24, Hindrik Mulder, Anna L. Gloyn, Leif Groop, Piero Marchetti, Decio L. Eizirik, Jorge Ferrer, Josep M. Mercader, Miriam Cnop, David Torrents" ; Postprint (published version)
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)
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.
We present Nucleosome Dynamics, a suite of programs integrated into a virtual research environment and created to define nucleosome architecture and dynamics from noisy experimental data. The package allows both the definition of nucleosome architectures and the detection of changes in nucleosomal organization due to changes in cellular conditions. Results are displayed in the context of genomic information thanks to different visualizers and browsers, allowing the user a holistic, multidimensional view of the genome/transcriptome. The package shows good performance for both locating equilibrium nucleosome architecture and nucleosome dynamics and provides abundant useful information in several test cases, where experimental data on nucleosome position (and for some cases expression level) have been collected for cells under different external conditions (cell cycle phase, yeast metabolic cycle progression, changes in nutrients or difference in MNase digestion level). Nucleosome Dynamics is a free software and is provided under several distribution models. ; M.O. is an ICREA (Institució Catalana de Recerca i Estudis Avancats) academia researcher; Spanish Ministry of Science [RTI2018-096704-B-100]; Catalan Government [2017-SGR-134]; Instituto de Salud Carlos III–Instituto Nacional de Bioinformática, the European Union's Horizon 2020 research and innovation program, and the Biomolecular and Bioinformatics Resources Platform [ISCIII PT 17/0009/0007 co-funded by the Fondo Europeo de Desarrollo Regional FEDER; Grants Elixir-Excelerate: 676559 and BioExcel2: 823830; ERC:812850; MuG-676566]; MINECO Severo Ochoa Award of Excellence from the Government of Spain (awarded to IRB Barcelona). Funding for open access charge: Spanish Ministry of Science [RTI2018-096704-B-100]. ; Peer Reviewed ; Postprint (published version)
We present Nucleosome Dynamics, a suite of programs integrated into a virtual research environment and created to define nucleosome architecture and dynamics from noisy experimental data. The package allows both the definition of nucleosome architectures and the detection of changes in nucleosomal organization due to changes in cellular conditions. Results are displayed in the context of genomic information thanks to different visualizers and browsers, allowing the user a holistic, multidimensional view of the genome/transcriptome. The package shows good performance for both locating equilibrium nucleosome architecture and nucleosome dynamics and provides abundant useful information in several test cases, where experimental data on nucleosome position (and for some cases expression level) have been collected for cells under different external conditions (cell cycle phase, yeast metabolic cycle progression, changes in nutrients or difference in MNase digestion level). Nucleosome Dynamics is a free software and is provided under several distribution models. ; M.O. is an ICREA (Institució Catalana de Recerca i Estudis Avancats) academia researcher; Spanish Ministry of Science [RTI2018-096704-B-100]; Catalan Government [2017-SGR-134]; Instituto de Salud Carlos III–Instituto Nacional de Bioinformática, the European Union's Horizon 2020 research and innovation program, and the Biomolecular and Bioinformatics Resources Platform [ISCIII PT 17/0009/0007 co-funded by the Fondo Europeo de Desarrollo Regional FEDER; Grants Elixir-Excelerate: 676559 and BioExcel2: 823830; ERC:812850; MuG-676566]; MINECO Severo Ochoa Award of Excellence from the Government of Spain (awarded to IRB Barcelona). Funding for open access charge: Spanish Ministry of Science [RTI2018-096704-B-100].
Analysis of mutational signatures is becoming routine in cancer genomics, with implications for pathogenesis, classification, prognosis, and even treatment decisions. However, the field lacks a consensus on analysis and result interpretation. Using whole-genome sequencing of multiple myeloma (MM), chronic lymphocytic leukemia (CLL) and acute myeloid leukemia, we compare the performance of public signature analysis tools. We describe caveats and pitfalls of de novo signature extraction and fitting approaches, reporting on common inaccuracies: erroneous signature assignment, identification of localized hyper-mutational processes, overcalling of signatures. We provide reproducible solutions to solve these issues and use orthogonal approaches to validate our results. We show how a comprehensive mutational signature analysis may provide relevant biological insights, reporting evidence of c-AID activity among unmutated CLL cases or the absence of BRCA1/BRCA2-mediated homologous recombination deficiency in a MM cohort. Finally, we propose a general analysis framework to ensure production of accurate and reproducible mutational signature data. ; F.M. is supported by A.I.L. (Associazione Italiana Contro le Leucemie-Linfomi e Mieloma ONLUS), by S.I.E.S. (Società Italiana di Ematologia Sperimentale) and by the Memorial Sloan Kettering Cancer Center NCI Core Grant (P30 CA 008748). N.B. is funded by the University of Milan (project 22597-PSR2017_DIP_032) and by the European Research Council under the European Union's Horizon 2020 research and innovation program (grant agreement no. 817997). X.S.P. is supported by thr Ministerio de Economía y Competitividad Grant No. SAF2017–87811-R. F.N. is supported by a pre-doctoral fellowship of the MINECO (BES-2016–076372). This work was supported by the Instituto de Salud Carlos III (project PMP15/00007, F.N., E.C.), the "la Caixa" Foundation Grant No HR17-00221 (Health Research 2017 Program, F.N., E.C.), the Ministerio de Economía y Competitividad (MINECO) SAF2013-45836-R (E.C.) from. Plan Nacional de I + D + I, Generalitat de Catalunya Suport Grups de Recerca AGAUR 2017-SGR-1142 (E.C.) and the European Regional Development Fund "Una manera de hacer Europa". E.C. is supported by ICREA under the ICREA Academia program. A.D. is funded by a CRUK Pioneer Award C60100/A23433. S.N.Z. is funded by a CRUK Advanced Clinician Scientist Award (C60100/A23916) and a CRUK Grand Challenge Award (C60100/A25274). This work was supported by: Department of Veterans Affairs Merit Review Award I01BX001584-01 (N.C.M.), NIH grants P01-155258 (N.C.M., H.A.L., M.F., P.J.C., K.C.A.) and 5P50CA100707-13 (N.C.M., H.A.L., K.C.A).
Analysis of mutational signatures is becoming routine in cancer genomics, with implications for pathogenesis, classification, prognosis, and even treatment decisions. However, the field lacks a consensus on analysis and result interpretation. Using whole-genome sequencing of multiple myeloma (MM), chronic lymphocytic leukemia (CLL) and acute myeloid leukemia, we compare the performance of public signature analysis tools. We describe caveats and pitfalls of de novo signature extraction and fitting approaches, reporting on common inaccuracies: erroneous signature assignment, identification of localized hyper-mutational processes, overcalling of signatures. We provide reproducible solutions to solve these issues and use orthogonal approaches to validate our results. We show how a comprehensive mutational signature analysis may provide relevant biological insights, reporting evidence of c-AID activity among unmutated CLL cases or the absence of BRCA1/BRCA2-mediated homologous recombination deficiency in a MM cohort. Finally, we propose a general analysis framework to ensure production of accurate and reproducible mutational signature data. ; F.M. is supported by A.I.L. (Associazione Italiana Contro le Leucemie-Linfomi e Mieloma ONLUS), by S.I.E.S. (Società Italiana di Ematologia Sperimentale) and by the Memorial Sloan Kettering Cancer Center NCI Core Grant (P30 CA 008748). N.B. is funded by the University of Milan (project 22597-PSR2017_DIP_032) and by the European Research Council under the European Union's Horizon 2020 research and innovation program (grant agreement no. 817997). X.S.P. is supported by thr Ministerio de Economía y Competitividad Grant No. SAF2017–87811-R. F.N. is supported by a pre-doctoral fellowship of the MINECO (BES-2016–076372). This work was supported by the Instituto de Salud Carlos III (project PMP15/00007, F.N., E.C.), the "la Caixa" Foundation Grant No HR17-00221 (Health Research 2017 Program, F.N., E.C.), the Ministerio de Economía y Competitividad (MINECO) SAF2013-45836-R (E.C.) from. Plan Nacional de I + D + I, Generalitat de Catalunya Suport Grups de Recerca AGAUR 2017-SGR-1142 (E.C.) and the European Regional Development Fund "Una manera de hacer Europa". E.C. is supported by ICREA under the ICREA Academia program. A.D. is funded by a CRUK Pioneer Award C60100/A23433. S.N.Z. is funded by a CRUK Advanced Clinician Scientist Award (C60100/A23916) and a CRUK Grand Challenge Award (C60100/A25274). This work was supported by: Department of Veterans Affairs Merit Review Award I01BX001584-01 (N.C.M.), NIH grants P01-155258 (N.C.M., H.A.L., M.F., P.J.C., K.C.A.) and 5P50CA100707-13 (N.C.M., H.A.L., K.C.A). We thank Michael R. Stratton for discussions and help in data interpretation. ; Peer Reviewed ; Postprint (author's final draft)
Analysis of mutational signatures is becoming routine in cancer genomics, with implications for pathogenesis, classification, prognosis, and even treatment decisions. However, the field lacks a consensus on analysis and result interpretation. Using whole-genome sequencing of multiple myeloma (MM), chronic lymphocytic leukemia (CLL) and acute myeloid leukemia, we compare the performance of public signature analysis tools. We describe caveats and pitfalls of de novo signature extraction and fitting approaches, reporting on common inaccuracies: erroneous signature assignment, identification of localized hyper-mutational processes, overcalling of signatures. We provide reproducible solutions to solve these issues and use orthogonal approaches to validate our results. We show how a comprehensive mutational signature analysis may provide relevant biological insights, reporting evidence of c-AID activity among unmutated CLL cases or the absence of BRCA1/BRCA2-mediated homologous recombination deficiency in a MM cohort. Finally, we propose a general analysis framework to ensure production of accurate and reproducible mutational signature data. ; F.M. is supported by A.I.L. (Associazione Italiana Contro le Leucemie-Linfomi e Mieloma ONLUS), by S.I.E.S. (Società Italiana di Ematologia Sperimentale) and by the Memorial Sloan Kettering Cancer Center NCI Core Grant (P30 CA 008748). N.B. is funded by the University of Milan (project 22597-PSR2017_DIP_032) and by the European Research Council under the European Union's Horizon 2020 research and innovation program (grant agreement no. 817997). X.S.P. is supported by thr Ministerio de Economía y Competitividad Grant No. SAF2017–87811-R. F.N. is supported by a pre-doctoral fellowship of the MINECO (BES-2016–076372). This work was supported by the Instituto de Salud Carlos III (project PMP15/00007, F.N., E.C.), the "la Caixa" Foundation Grant No HR17-00221 (Health Research 2017 Program, F.N., E.C.), the Ministerio de Economía y Competitividad (MINECO) SAF2013-45836-R (E.C.) from. Plan Nacional de I + D + I, Generalitat de Catalunya Suport Grups de Recerca AGAUR 2017-SGR-1142 (E.C.) and the European Regional Development Fund "Una manera de hacer Europa". E.C. is supported by ICREA under the ICREA Academia program. A.D. is funded by a CRUK Pioneer Award C60100/A23433. S.N.Z. is funded by a CRUK Advanced Clinician Scientist Award (C60100/A23916) and a CRUK Grand Challenge Award (C60100/A25274). This work was supported by: Department of Veterans Affairs Merit Review Award I01BX001584-01 (N.C.M.), NIH grants P01-155258 (N.C.M., H.A.L., M.F., P.J.C., K.C.A.) and 5P50CA100707-13 (N.C.M., H.A.L., K.C.A). We thank Michael R. Stratton for discussions and help in data interpretation. ; Peer Reviewed ; Postprint (author's final draft)
Analysis of mutational signatures is becoming routine in cancer genomics, with implications for pathogenesis, classification, prognosis, and even treatment decisions. However, the field lacks a consensus on analysis and result interpretation. Using whole-genome sequencing of multiple myeloma (MM), chronic lymphocytic leukemia (CLL) and acute myeloid leukemia, we compare the performance of public signature analysis tools. We describe caveats and pitfalls of de novo signature extraction and fitting approaches, reporting on common inaccuracies: erroneous signature assignment, identification of localized hyper-mutational processes, overcalling of signatures. We provide reproducible solutions to solve these issues and use orthogonal approaches to validate our results. We show how a comprehensive mutational signature analysis may provide relevant biological insights, reporting evidence of c-AID activity among unmutated CLL cases or the absence of BRCA1/BRCA2-mediated homologous recombination deficiency in a MM cohort. Finally, we propose a general analysis framework to ensure production of accurate and reproducible mutational signature data. ; F.M. is supported by A.I.L. (Associazione Italiana Contro le Leucemie-Linfomi e Mieloma ONLUS), by S.I.E.S. (Società Italiana di Ematologia Sperimentale) and by the Memorial Sloan Kettering Cancer Center NCI Core Grant (P30 CA 008748). N.B. is funded by the University of Milan (project 22597-PSR2017_DIP_032) and by the European Research Council under the European Union's Horizon 2020 research and innovation program (grant agreement no. 817997). X.S.P. is supported by thr Ministerio de Economía y Competitividad Grant No. SAF2017–87811-R. F.N. is supported by a pre-doctoral fellowship of the MINECO (BES-2016–076372). This work was supported by the Instituto de Salud Carlos III (project PMP15/00007, F.N., E.C.), the "la Caixa" Foundation Grant No HR17-00221 (Health Research 2017 Program, F.N., E.C.), the Ministerio de Economía y Competitividad (MINECO) SAF2013-45836-R (E.C.) from. Plan Nacional de I + D + I, Generalitat de Catalunya Suport Grups de Recerca AGAUR 2017-SGR-1142 (E.C.) and the European Regional Development Fund "Una manera de hacer Europa". E.C. is supported by ICREA under the ICREA Academia program. A.D. is funded by a CRUK Pioneer Award C60100/A23433. S.N.Z. is funded by a CRUK Advanced Clinician Scientist Award (C60100/A23916) and a CRUK Grand Challenge Award (C60100/A25274). This work was supported by: Department of Veterans Affairs Merit Review Award I01BX001584-01 (N.C.M.), NIH grants P01-155258 (N.C.M., H.A.L., M.F., P.J.C., K.C.A.) and 5P50CA100707-13 (N.C.M., H.A.L., K.C.A). We thank Michael R. Stratton for discussions and help in data interpretation.
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)
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)
