<HashMap><database>biostudies-arrayexpress</database><scores/><additional><submitter>Rui Guo</submitter><organism>Mus musculus</organism><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/E-MTAB-15514</full_dataset_link><description>Utilizing single-cell RNA sequencing, analyzed the impact of OGT deficiency on RNA metabolism across distinct germ cell populations and assessed the influence of O-GlcNAcylation loss on developmental trajectories within spermatogenic lineages.</description><repository>biostudies-arrayexpress</repository><sample_protocol>Sample Collection - Under sterile conditions, the freshly collected tissues  were washed twice with pre-cooled RPMI 1640 medium containing 0.04% BSA. The tissues were then mechanically dissociated into approximately 0.5 mm³ fragments using surgical scissors and transferred into freshly prepared enzymatic digestion solution. The digestion mixture contained RPMI 1640 (Conring, cat.no. 10-040-CVR), 0.04% BSA (MACS, cat.no. 1000076), and 0.2% collagenase II (Gibco, cat.no. 17101015). The samples were incubated at 37°C for 30-60 minutes with gentle inversion every 5-10 minutes.The digested cell suspension was filtered through a BD 40 μm cell strainer (Falcon, cat.no. 352340) 1-2 times. The filtrate was centrifuged at 300 × g for 5 minutes at 4°C. The cell pellet was resuspended in appropriate medium, mixed with an equal volume of red blood cell lysis buffer (Miltenyi, cat.no. 130-094-183), and incubated at 4°C for 10 minutes. After centrifugation at 300 × g for 5 minutes, the supernatant was discarded. The pellet was washed once with medium followed by another centrifugation at 300 × g for 5 minutes, and the final supernatant was removed.Finally，the cells were re-suspended with 1ml RPMI 1640 medium (Conring, cat.no.10-040-CVR) with 0.04% BSA added. Single-cell suspension concentration and cell viability were then evaluated by Luna-FL cell counter (Logos Biosystems，Korea) or Trypan Blue staining method.</sample_protocol><sample_protocol>Nucleic Acid Extraction - Cell suspensions were calibrated to 700–1,200 cells/μL and immediately loaded onto microfluidic chips for droplet generation. Subsequent reverse transcription, and cDNA amplification were executed following the manufacturer’s standardized workflow.</sample_protocol><sample_protocol>Library Construction - The freshly prepared single-cell suspension was adjusted to a concentration of 700–1200 cells/μl. Library preparation and loading were performed following the manufacturer’s protocol for the MobiCube High-throughput Single Cell 3 ′ Transcriptome Set V2.1 (cat.no.PN-S050200301).</sample_protocol><sample_protocol>Sequencing - The constructed libraries were sequenced on the Illumina Nova 6000 PE150  platform for high-throughput sequencing.</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>Data Transformation - Single-cell sequencing data processing commenced with alignment of FASTQ files to the GRCm39 reference genome via MobiVision v3.2, incorporating unique molecular identifier (UMI) deduplication for transcript quantification. The resultant UMI count matrix underwent quality control and computational analysis through Seurat v4.0.0, implementing a multi-parameter filtration strategy. A set of criteria were conducted: Cells were filtered by (1) &lt;200 detected genes/cell, (2) &lt;1,000 UMIs/cell, (3) Gene-to-transcript complexity ratio (log10[Genes/UMI]) &lt;0.7, (4) >10% mitochondrial content and (5) >5% hemoglobin gene expression. Potential multiplets were computationally identified using DoubletFinder v2.0.3. Normalization employed the LogNormalize method, scaling cellular transcripts to 10,000 UMIs/cell followed by natural logarithm transformation.</data_protocol><omics_type>Metabolomics</omics_type><omics_type>Unknown</omics_type><omics_type>Transcriptomics</omics_type><omics_type>Genomics</omics_type><omics_type>Proteomics</omics_type><instrument_platform>Illumina NovaSeq 6000</instrument_platform><instrument_platform>Illumina Nova 6000 PE150</instrument_platform><study_type>RNA-seq of coding RNA from single cells</study_type><species>Mus musculus</species><pubmed_authors>Rui Guo</pubmed_authors></additional><is_claimable>false</is_claimable><name>ScRNA-Sequencing of Postnatal day 12 (P12)​ tetstes in Ogt conditional knock out and Wild-Type mice</name><description>Utilizing single-cell RNA sequencing, analyzed the impact of OGT deficiency on RNA metabolism across distinct germ cell populations and assessed the influence of O-GlcNAcylation loss on developmental trajectories within spermatogenic lineages.</description><dates><release>2026-08-01T00:00:00Z</release><modification>2026-08-01T01:01:00.021Z</modification><creation>2025-08-29T05:00:41.152Z</creation></dates><accession>E-MTAB-15514</accession><cross_references><ENA>ERP179373</ENA><EFO>EFO_0002944</EFO><EFO>EFO_0004170</EFO><EFO>EFO_0005684</EFO><EFO>EFO_0005518</EFO><EFO>EFO_0003816</EFO><EFO>EFO_0004184</EFO></cross_references></HashMap>