<HashMap><database>biostudies-arrayexpress</database><scores/><additional><submitter>Michael Morgan</submitter><organism>Mus musculus</organism><software>Cellranger, emptyDrops</software><software>scran</software><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/E-MTAB-8737</full_dataset_link><description>TEC progenitors that express beta 5-t contribute to both the cortical and medullary TEC compartments. Our initial experiments across ageing thymi identified a population of potential progenitor TECs which expanded with age, and appears to be a progenitor population for mTEC. These lineage tracing experiments are designed to chart the altered differentiation and senescence of mTEC progenitors with age.</description><repository>biostudies-arrayexpress</repository><sample_protocol>Nucleic Acid Extraction - Equal cell numbers were pooled from each of the samples, and a total of 30000 cells were loaded per well onto a Chromium Single Cell B Chip (10x Genomics) coupled with the Chromium Single Cell 3ʹ GEM, Library &amp; Gel Bead Kit v3 and Chromium i7 Multiplex Kit (10x Genomics) for library preparation, according to the manufacturer’s instructions. In short, the cell suspension was mixed with the GEM Retrotranscription Master Mix and loaded onto well number 1 on the Chromium Chip B (10x Genomics). Wells 2 and 3 were loaded with the appropriate volumes of gel beads and partitioning oil, respectively, after which the Chromium Controller (10x Genomics) was used to generate nanoliter-scale Gel Beads-in-emulsion (GEMs) containing the single cells to be analysed. The fact that cell samples containing 6 different hashtag antibodies were pooled together allowed us to overload the 10x wells with 30000 cells per well, aiming for a recovery of approximately 12000 single cells (40%) per well, and being able to overcome the increase in doublet rate by subsequently eliminating any cell barcode containing more than one single hashtag sequence from further analysis. Incubation of the GEM suspension results in the simultaneous production of barcoded full-length cDNA from poly-adenylated mRNA as well as barcoded DNA from the cell surface protein-bound TotalSeqA antibodies inside of each individual GEM. Fragmentation of the GEMs allowed the recovery and clean-up of the pooled fractions using silane magnetic beads. Recovered DNA was then amplified, and cDNA products were separated from the Antibody-Derived Tags (ADT) and Hashtag oligonucleotides (HTO) by size selection.</sample_protocol><sample_protocol>Sample Collection - Single thymic epithelial cell suspensions were obtained by enzymatic digestion using Liberase, Papain and DNase in PBS. Prior to FAC-sorting, TEC were enriched for EpCAM-positivity using a magnetic cell separator, as described above. Enriched cells were subsequently stained for the indicated cell surface antigens EpCAM, Ly51, CD80, MHCII &amp; UEA1 in conjunction with TotalSeq-A oligonucleotide-conjugated antibodies against mouse MHCI and CD45 to allow barcoding and pooling of different TEC subpopulations and subsequently sorted into 4 subpopulations: ZsGreen+ cTEC, ZsGreen- cTEC, ZsGreen+ mTEC, and ZsGreen- mTEC. After sorting, the cell viability and concentration of each of the cell samples collected was measured using a Nexcelom Bioscience Cellometer K2 Fluorescent Viability Cell Counter.</sample_protocol><sample_protocol>Sequencing - Library quality was assessed using capillary electrophoresis on a Fragment Analyzer (AATI). The different libraries corresponding to each sample set were pooled as follows: 85% cDNA + 10% ADT + 5% HTO. Pooled libraries were sequenced on an Illumina NovaSeq 6000 using the NovaSeq 6000 S2 Reagent Kit (100 cycles) (Illumina).</sample_protocol><sample_protocol>Library Construction - The amplified full-length cDNA generated from polyadenylated mRNA were enzymatically fragmented and size selection was used to optimise amplicon size for the generation of 3’ libraries. Library construction was achieved by adding P5, P7, a sample index, and TruSeq Read 2 (read 2 primer sequence) via End Repair, A-tailing, Adaptor Ligation, and PCR. Separately, ADT and HTO library generation was achieved through the addition of P5, P7, a sample index, and TruSeq Read 2 (read 2 primer sequence) by PCR.</sample_protocol><sample_protocol>Sample Treatment - One-week old ﻿3xtgβ5t mice were treated with a single i.p. injection of 0.004mg of Doxycycline (Sigma) diluted in Hank’s Balanced Salt Solution (Life Technologies), whereas older mice (four-week and sixteen-week old) were treated with ﻿two i.p. injections of Doxycycline (2mg, each) on two consecutive days during which they were also exposed to drinking water supplemented with the drug ﻿(2 mg/mL in sucrose (5% w/v)).</sample_protocol><figure_sub>Organization</figure_sub><figure_sub>MINSEQE Score</figure_sub><figure_sub>Assays and Data</figure_sub><figure_sub>MAGE-TAB Files</figure_sub><data_protocol>Data Transformation - Poor quality cells barcodes were removed based on high mitochondrial content, defined within each sample as twice the median absolute deviation from the median mitochondrial fraction. Cell barcodes with low coverage (&lt; 1000 UMIs detected) were also removed prior to normalisation. Finally, deconvolution-estimated size factors were calculated to normalise across single cells, then log10 transformed with a pseudocount (+1), as implemented in scran (Lun et al., 2016a).</data_protocol><data_protocol>Sequence Alignment - Multiplexed 10X scRNA-seq libraries were aligned, deduplicated and quantified using Cellranger v3.1.0. Gene expression matrices of genes x cells were generated separately for each sample (i.e. 10X Chromium chip well), as well as those for hashtag oligo (HTO) and antibody (ADT) libraries. Cells were called using emptyDrops, with a background UMI threshold of 100 [Lun et al]. Experimental samples, i.e. replicates and ZsGreen-fractions, were demultiplexed using the assigned HTO for the respective sample [Stoeckius et al]. Specifically, within each sample, the HTO fragment counts were normalised across cells barcodes for all relevant HTOs using counts per million (CPM). These CPMs were used to cluster cell barcodes using k-means with the expected number of singlet clusters, i.e. unique HTOs in the respective sample. To estimate a background null distribution for each HTO within a sample, we then selected the k-means partition with the highest average CPM for the HTO and excluded these cells, along with the top 0.5% of cells with the highest counts for the respective HTO. We then fit a negative binomial distribution to the HTO counts for the remaining cells to estimate a threshold (q) at the 99th quantile. All cell barcodes with counts ≥ q were assigned this HTO. This procedure was repeated for each HTO within a sample. Cell barcodes that were assigned to a single HTO were called as ‘Singlets’, whilst cell barcodes assigned to > 1 HTO were called as ‘Multiplets’. Finally, cell barcodes with insufficient coverage across HTOs were called as ‘Dropouts’ (Supplementary Figure 9a). Only ‘Singlets’ were retained for normalisation and downstream analyses.</data_protocol><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><study_type>RNA-seq of coding RNA from single cells</study_type><species>Mus musculus</species><pubmed_authors>Michael Morgan</pubmed_authors></additional><is_claimable>false</is_claimable><name>Charting the age-altered thymic epithelial cell differentiation by lineage tracing from a beta 5-t expressing TEC progenitor</name><description>TEC progenitors that express beta 5-t contribute to both the cortical and medullary TEC compartments. Our initial experiments across ageing thymi identified a population of potential progenitor TECs which expanded with age, and appears to be a progenitor population for mTEC. These lineage tracing experiments are designed to chart the altered differentiation and senescence of mTEC progenitors with age.</description><dates><release>2020-09-14T00:00:00Z</release><modification>2022-02-03T06:55:45.93Z</modification><creation>2022-02-03T06:55:45.93Z</creation></dates><accession>E-MTAB-8737</accession><cross_references><ENA>ERP119803</ENA><Biostudies>E-MTAB-8560</Biostudies><EFO>EFO_0002944</EFO><EFO>EFO_0004170</EFO><EFO>EFO_0005684</EFO><EFO>EFO_0004917</EFO><EFO>EFO_0005518</EFO><EFO>EFO_0003816</EFO><EFO>EFO_0004184</EFO><EFO>EFO_0003969</EFO></cross_references></HashMap>