<HashMap><database>biostudies-arrayexpress</database><scores/><additional><submitter>Jan Dobeš</submitter><organism>Mus musculus</organism><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/E-MTAB-15468</full_dataset_link><description>The goal of the experiment is to determine the impact of Claudin 1 deficiency on the gene expression of thymic type 1 dendritic cells.</description><repository>biostudies-arrayexpress</repository><sample_protocol>Sequencing - ibraries were sequenced with the NextSeq P2 XLEAP-SBS Reagent Kit on a NextSeq 2000 sequencer (Illumina). Pair-end: rd1=75bp, rd2=15bp.</sample_protocol><sample_protocol>Nucleic Acid Extraction - Complete mRNA was isolated based on polyA selection using Dynabeads mRNA direct purification kit.</sample_protocol><sample_protocol>Library Construction - Sequencing libraries were prepared using the MARS-seq protocol, as described previously (Jaitin, D. A. et al. Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types. Science 343, 776–779 (2014)).</sample_protocol><sample_protocol>Sample Collection - The Defa6-iCre R26-TdTomato mouse model, which exhibits restricted expression of the TdTomato fluorescent protein in medullary thymic epithelial cells, was used as the recipient for competitive bone marrow chimeras composed of Claudin-1–sufficient and Claudin-1–deficient donor cells. After six weeks, thymi were dissected and type 1 dendritic cells arising from Claudin-1–sufficient and Claudin-1–deficient bone marrow were isolated by flow cytometric sorting from one individual animal. Cells were directly sorted into lysis buffer.</sample_protocol><figure_sub>Organization</figure_sub><figure_sub>MINSEQE Score</figure_sub><figure_sub>Assays and Data</figure_sub><figure_sub>Processed Data</figure_sub><figure_sub>MAGE-TAB Files</figure_sub><data_protocol>Sequence Alignment - Reads were trimmed using cutadapt (DOI: 10.14806/ej.17.1.200).  Reads were mapped to genome using STAR (DOI: 10.1093/bioinformatics/bts635) v2.7.10a.  The pipeline quantifies the 3’ of RefSeq annotated genes (The 3’ region contains 1,000 bases upstream of the 3’ end and 100 bases downstream):  We used the 3’ end (1000bp) of the transcripts for counting the number of reads per gene. Counting (UMI counts) was done after marking duplicates (in-house script) using HTSeq-count (DOI: 10.1093/bioinformatics/btu638) v2.0.2 in union mode.  Further analysis is done for genes having minimum 5 read in at least one sample. The analysis was done using UTAP:  Kohen R, Barlev J, Hornung G, Stelzer G, Feldmesser E, Kogan K, Safran M, Leshkowitz D: UTAP: User-friendly Transcriptome Analysis Pipeline. BMC Bioinformatics 2019, 20(1):154.</data_protocol><data_protocol>Data Transformation - Normalization of the counts and differential expression analysis was performed using DESeq2 (DOI: 10.1186/s13059-014-0550-8) v1.36.0 with the parameters: betaPrior=True, cooksCutoff=FALSE, independentFiltering=FALSE. Raw P values were adjusted for multiple testing using the procedure of Benjamini and Hochberg (DOI: 10.1111/j.2517-6161.1995.tb02031.x).</data_protocol><omics_type>Unknown</omics_type><omics_type>Transcriptomics</omics_type><omics_type>Genomics</omics_type><omics_type>Proteomics</omics_type><instrument_platform>NextSeq 2000</instrument_platform><study_type>RNA-seq of coding RNA</study_type><species>Mus musculus</species><pubmed_authors>Jan Dobeš</pubmed_authors></additional><is_claimable>false</is_claimable><name>RNA-seq analysis of murine thymic type 1 dendritic cells from competitive bone marrow chimeras containing both claudin-1–deficient and claudin-1–sufficient cells</name><description>The goal of the experiment is to determine the impact of Claudin 1 deficiency on the gene expression of thymic type 1 dendritic cells.</description><dates><release>2025-08-08T00:00:00Z</release><modification>2025-08-08T15:47:57.771Z</modification><creation>2025-08-08T15:35:50.325Z</creation></dates><accession>E-MTAB-15468</accession><cross_references><ENA>ERP178572</ENA><Biostudies>E-MTAB-14319</Biostudies><EFO>EFO_0002944</EFO><EFO>EFO_0004170</EFO><EFO>EFO_0004917</EFO><EFO>EFO_0005518</EFO><EFO>EFO_0003816</EFO><EFO>EFO_0003738</EFO><EFO>EFO_0004184</EFO></cross_references></HashMap>