Data Descriptor: High-coverage methylation data of a gene model before and after DNA damage and homologous repair Antonio Pezone 1,* , Giusi Russo 1,* , Alfonso Tramontano 1 , Ermanno Florio 1 , Giovanni Scala 1 , Rosaria Landi 1 , Candida Zuchegna 2 , Antonella Romano 2 , Lorenzo Chiariotti 1 , Mark T. Muller 3 , Max E. Gottesman 4 , Antonio Porcellini 2 & Enrico V. Avvedimento 1 Genome-wide methylation analysis is limited by its low coverage and the inability to detect single variants below 10%. Quantitative analysis provides accurate information on the extent of methylation of single CpG dinucleotide, but it does not measure the actual polymorphism of the methylation profiles of single molecules. To understand the polymorphism of DNA methylation and to decode the methylation signatures before and after DNA damage and repair, we have deep sequenced in bisulfite-treated DNA a reporter gene undergoing site-specific DNA damage and homologous repair. In this paper, we provide information on the data generation, the rationale for the experiments and the type of assays used, such as cytofluorimetry and immunoblot data derived during a previous work published in Scientific Reports, describing the methylation and expression changes of a model gene (GFP) before and after formation of a double-strand break and repair by homologous-recombination or non-homologous-end-joining. These data provide: 1) a reference for the analysis of methylation polymorphism at selected loci in complex cell populations; 2) a platform and the tools to compare transcription and methylation profiles. Design Type(s) DNA methylation profiling by high throughput sequencing design • epigenetic modification identification objective Measurement Type(s) DNA methylation profiling assay • DNA methylation • gene knockdown by shRNA transfection Technology Type(s) DNA sequencing • flow cytometry assay • western blot analysis Factor Type(s) epigenetic factor Sample Characteristic(s) HeLa cell 1 Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Istituto di Endocrinologia ed Oncologia Sperimentale del C.N.R., Università Federico II, Napoli 80131, Italy. 2 Dipartimento Biologia, Università Federico II, Napoli 80131, Italy. 3 Epigenetics Division, TopoGEN, Inc., 27960 CR319, Buena Vista, Colorado 81211, USA. 4 Institute of Cancer Research, Columbia University Medical Center, New York, New York 10032, USA. *These authors contributed equally to this work. Correspondence and requests for materials should be addressed to A.P. (email: antonio.porcellini@unina.it) or to E.V.A. (email: avvedim@unina.it). OPEN Received: 24 October 2016 Accepted: 27 February 2017 Published: 11 April 2017 www.nature.com/scientificdata SCIENTIFIC DATA | 4:170043 | DOI: 10.1038/sdata.2017.43 1