https://researchdata.se/en/catalogue Search results en The samples in the dataset are connected to a study focusing on establishment of a long-term stable three-dimensional (3D) model of human primary ovarian cells for toxicological research. These samples are collected from patients undergoing elective abdominal surgery. The cortex and medulla were separated and dissociated into single-cell suspension using mechanical and enzymatic methods, followed by culture in 2D and 3D systems. In total 75 samples are included in the dataset (36 samples from cortex and 39 from medulla). Among these samples, 29 tissue samples were used as reference in the comparison of 2D culture vs tissue and 3D culture vs tissue. 16 samples from 2D culture were used as the reference in the comparison of 3D vs 2D. The rest 30 samples were from 3D culture (Silk-Ovarioid). RNA extraction of tissues and 2D cultured cells was performed using RNeasy Mini Kit (Qiagen, Germany). Total RNA of Silk-Ovarioids samples was extracted using RNeasy Micro Kit (Qiagen, Germany). Only samples with RIN values > 9 were used for library preparation. Libraries were prepared using Illumina Stranded mRNA Prep Ligation protocol (Illumina, USA) using 10 ng RNA as input. Pooled libraries were sequenced on Illumina NovaSeq 6000 platform. Fastq files were mapped to human genome GRCh38 using STAR (version 2.7.10b). subread package (version 2.0.1) was used to align the bam files using featureCount function. After import the raw data matrix into Rstudio, technical replicates were collapsed using DESeq2 collapseReplicates function. GRCh38 (Homo_sapiens.GRCh38.108.chr.gtf) was used for mapping and alignment. The dataset consists of 150 files in fastq format, compressed with GNUzip (gzip), one file in txt format and one file in xlsx format. The total size of the dataset is approximately 400 GB. Tue, 15 Jul 2025 09:18:20 GMT https://researchdata.se/en/catalogue/dataset/2025-25 https://researchdata.se/en/catalogue/dataset/2025-25 Karolinska Institutet Valentina Di Nisio Tianyi Li Zhijie Xiao Kiriaki Papaikonomou Anastasios Damdimopoulos Ákos Végvári Filipa Lebre Ernesto Alfaro-Moreno Mikael Pedersen Terje Svingen Roman Zubarev Ganesh Acharya Pauliina Damdimopoulou Andres Salumets Most proteins at the plasma membrane are not uniformly distributed but localize to dynamic domains of nanoscale dimensions. To investigate their functional relevance, there is a need for methods that enable comprehensive analysis of the compositions and spatial organizations of membrane protein nanodomains in cell populations. Here we describe the development of a non-microscopy based method for ensemble analysis of membrane protein nanodomains. The method, termed NANOscale DEciphEring of membrane Protein nanodomains (NanoDeep), is based on the use of DNA nanoassemblies to translate membrane protein organization information into a DNA sequencing readout. Using NanoDeep, we characterised the nanoenvironments of Her2, a membrane receptor of critical relevance in cancer. Importantly, we were able to modulate by design the inventory of proteins analysed by NanoDeep. NanoDeep has the potential to provide new insights into the roles of the composition and spatial organization of protein nanoenvironments in the regulation of membrane protein function. The methodology is described in the preprint article (see publications list). The methodology for this dataset is available in the preprint (see publication list) Software for data collection: Biacore T200 System Control software, NextSeq control software Software for data analysis: BIAevaluation v3.0, GraphPad Prism v8.2.1, Fiji ImageJ v1.0, Illumina Sequencing Analysis Viewer software, Python v3.8.0. Thu, 24 Jun 2021 15:02:32 GMT https://researchdata.se/en/catalogue/dataset/2020-90-1 https://researchdata.se/en/catalogue/dataset/2020-90-1 Karolinska Institutet Elena Ambrosetti