Abstract

In life-science research isogenic B-lymphoblastoid cell lines (LCLs) are widely known and preferred for their genetic stability – they are often used for studying mutations for example, where genetic stability is crucial. We have shown previously that phenotypic variability can be observed in isogenic B-lymphoblastoid cell lines. Isogenic LCLs present well-defined phenotypic differences on various levels, for example on the gene expression level or the chromatin level. Based on our investigations, the phenotypic variability of the isogenic LCLs is accompanied by certain genetic variation too. We have developed a compendium of LCL datasets that present the phenotypic and genetic variability of five isogenic LCLs from a multiomic perspective. In this paper, we present additional datasets generated with Next Generation Sequencing techniques to provide genomic and transcriptomic profiles (WGS, RNA-seq, single cell RNA-seq), protein-DNA interactions (ChIP-seq), together with mass spectrometry and flow cytometry datasets to monitor the changes in the proteome. We are sharing these datasets with the scientific community according to the FAIR principles for further investigations.

Details

Title
Extensive proteome and functional genomic profiling of variability between genetically identical human B-lymphoblastoid cells
Author
Laczik, Miklós 1 ; Erdős, Edina 1 ; Ozgyin, Lilla 1 ; Hevessy, Zsuzsanna 2 ; Csősz, Éva 3   VIAFID ORCID Logo  ; Kalló, Gergő 3 ; Nagy, Tibor 4   VIAFID ORCID Logo  ; Barta, Endre 4 ; Póliska, Szilárd 1 ; Szatmári, István 5   VIAFID ORCID Logo  ; Bálint, Bálint László 6   VIAFID ORCID Logo 

 University of Debrecen, Genomic Medicine and Bioinformatic Core Facility, Department of Biochemistry and Molecular Biology, Faculty of Medicine, Debrecen, Hungary (GRID:grid.7122.6) (ISNI:0000 0001 1088 8582) 
 University of Debrecen, Department of Laboratory Medicine, Faculty of Medicine, Debrecen, Hungary (GRID:grid.7122.6) (ISNI:0000 0001 1088 8582) 
 University of Debrecen, Proteomics Core Facility, Department of Biochemistry and Molecular Biology, Faculty of Medicine, Debrecen, Hungary (GRID:grid.7122.6) (ISNI:0000 0001 1088 8582) 
 University of Debrecen, Genomic Medicine and Bioinformatic Core Facility, Department of Biochemistry and Molecular Biology, Faculty of Medicine, Debrecen, Hungary (GRID:grid.7122.6) (ISNI:0000 0001 1088 8582); Hungarian University of Agriculture and Life Sciences, Department of Genetics and Genomics, Institute of Genetics and Biotechnology, Gödöllő, Hungary (GRID:grid.129553.9) (ISNI:0000 0001 1015 7851) 
 University of Debrecen, Genomic Medicine and Bioinformatic Core Facility, Department of Biochemistry and Molecular Biology, Faculty of Medicine, Debrecen, Hungary (GRID:grid.7122.6) (ISNI:0000 0001 1088 8582); University of Debrecen, Faculty of Pharmacy, Debrecen, Hungary (GRID:grid.7122.6) (ISNI:0000 0001 1088 8582) 
 University of Debrecen, Genomic Medicine and Bioinformatic Core Facility, Department of Biochemistry and Molecular Biology, Faculty of Medicine, Debrecen, Hungary (GRID:grid.7122.6) (ISNI:0000 0001 1088 8582); Department of Bioinformatics, Semmelweis University, Budapest, Hungary (GRID:grid.11804.3c) (ISNI:0000 0001 0942 9821) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20524463
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2748911913
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.