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The endoplasmic reticulum (ER) of cancer cells needs to adapt to the enhanced proteotoxic stress associated with the accumulation of unfolded, misfolded and transformation-associated proteins. One way by which tumors thrive in the context of ER stress is by promoting ER-Associated Degradation (ERAD), although the mechanisms are poorly understood. Here, we show that the Small p97/VCP Interacting Protein (SVIP), an endogenous inhibitor of ERAD, undergoes DNA hypermethylation-associated silencing in tumorigenesis to achieve this goal. SVIP exhibits tumor suppressor features and its recovery is associated with increased ER stress and growth inhibition. Proteomic and metabolomic analyses show that cancer cells with epigenetic loss of SVIP are depleted in mitochondrial enzymes and oxidative respiration activity. This phenotype is reverted upon SVIP restoration. The dependence of SVIP hypermethylated cancer cells on aerobic glycolysis and glucose was also associated with sensitivity to an inhibitor of the glucose transporter GLUT1. This could be relevant to the management of tumors carrying SVIP epigenetic loss, because these occur in high-risk patients who manifest poor clinical outcomes. Overall, our study provides insights into how epigenetics helps deal with ER stress and how SVIP epigenetic loss in cancer may be amenable to therapies that target glucose transporters. ; This work was supported by the Health Department PERIS project number SLT/002/16/00374 and AGAUR project numbers 2017SGR1080, 2014SGR633, 2017SGR1033, and 2009SGR1315 of the Catalan Government (Generalitat de Catalunya); the Spanish Institute of Health Carlos III (ISCIII) project number DTS16/00153 and Ministerio de Economía y Competitividad (MINECO) project numbers SAF2014-55000-R, BFU2014-57466-P, SAF2017-89673-R, and SAF2015-70270-REDT co-financed by the European Development Regional Fund, A way to achieve Europe ERDF; the Cellex Foundation; and "la Caixa" Bank Foundation (LCF/PR/PR15/11100003). MC acknowledges the prize "ICREA Academia" for excellence in research, funded by ICREA foundation. We thank the Scientific and Technological Centre (CCiTUB) of the University of Barcelona for technical support with cell cytometry and sorting. We also thank the Regenerative Medicine Center (CMRB) Electron Microscopy and Histology facility.

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

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

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 ).

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).