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| Status |
Public on May 08, 2019 |
| Title |
Lung_HDM_CD44hi [GRA769A41] |
| Sample type |
SRA |
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| Source name |
Lung_HDM_CD44hi
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| Organism |
Mus musculus |
| Characteristics |
mouse model: House dust mite (HDM) allergy
mouse strain: C57BL/6/J
condition: Disease
infection protocol: Female C57BL/6/J mice (MRC NIMR) were sensitized with 10 mg HDM (Greer) and 2 mg Imject Alum (Thermo Scientific) in 200 ml PBS or Alum alone as control by i.p. injections on days 0 and 14, followed by i.t. challenge with 10 mg HDM in 20 ml of PBS or PBS on days 21 and 24 as described6. Whole blood and lung samples were collected from individual HDM and PBS control treated mice on day 25. For FACS sorting of T cells, pooled blood from 4-5 individual HDM or PBS treated mice was collected into heparin sodium (Wockhardt) at 10 to 30 international units per ml of blood. Peripheral blood mononuclear cells were isolated by density separation with Lympholyte®-Mammal (Cedarlane). Lung CD4+ T cells were enriched by positive selection (Miltenyi Biotech) from a corresponding pool of lungs. Blood and lung cells were stained with CD3 (145-2C11) APC, CD4 (RM4-5) eFluor450 and CD44 (IM7) PE (all from eBioscience) and CD3+CD4+, CD3+CD4+ CD44low and CD44high cells were sorted on MoFlo XDP (Beckman Coulter) and BD FACSAria™ Fusion (Beckton Dickinson) flow cytometers and 15,000 per population collected into TRI-Reagent LS (Sigma-Aldrich).
cell type: CD3+CD4+ CD44hi
mouse id: MS0855
tissue: Lung
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| Extracted molecule |
total RNA |
| Extraction protocol |
FACS sorted blood/lung cells were collected into TRI-Reagent LS (Sigma-Aldrich). Total RNA was extracted using the Purelink RNA microkit (Thermo Fisher).
Total RNA (30–500 pg) was used to prepare cDNA libraries using the NEBNext® Single Cell/Low Input RNA Library Prep Kit NEBNext® Multiplex Oligos for Illumina® #E6609 (New England BioLabs). Quality and integrity of the tagged libraries were initially assessed with the HT DNA HiSens Reagent kit (Perkin Elmer) using a LabChip GX bioanalyser (Caliper Life Sciences/Perkin Elmer). Tagged libraries were then sized and quantitated in duplicate (Agilent TapeStation system) using D1000 ScreenTape and reagents (Agilent). Libraries were normalised, pooled and then clustered using the HiSeq® 3000/4000 PE Cluster Kit (Illumina). The libraries were imaged and sequenced on an Illumina HiSeq 4000 sequencer using the HiSeq® 3000/4000 SBS kit (Illumina) at a minimum of 25 million paired-end reads (75 bp/100 bp) per sample.
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina HiSeq 4000 |
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| Description |
GRA769A41_S1_L001
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| Data processing |
Raw paired-end RNA-seq data was subjected to quality control using FastQC (Babraham Bioinformatics) and MultiQC. Trimmomatic v0.36 was used to remove the adapters and filter raw reads below 36 bases long, and leading and trailing bases below quality 25. The filtered reads were aligned to the Mus musculus genome Ensembl GRCm38 (release 86) using HISAT2 v2.0.4 with default settings and RF rna-strandedness, including unpaired reads, resulting from Trimmomatic, using option -U. The mapped and aligned reads were quantified to obtain the gene-level counts using HtSeq v0.6.1 with default settings and reverse strandedness. Raw counts were processed using the bioconductor package DESeq2 v1.12.4 in R v3.3.1, and normalised using the DESeq method to remove the library-specific artefacts. Variance stabilizing transformation was applied to obtain normalised log2 gene expression values. Further quality control was performed using principal component analysis, boxplots, histograms and density plots.
Raw_counts_HDM_sorted_CD4_Tcells.xlsx:Raw counts generated from paired-end RNA-seq fastq files, aligned using HISAT2 and quantified using HtSeq
DESeq_normalised_counts_HDM_sorted_CD4_Tcells.xlsx:Normalised counts generated using the DESeq method to remove the library-specific artefacts
DESeq_VSTlog2_normalised_values_HDM_sorted_CD4_Tcells.xlsx:Log2 expression values generated from normalised counts using variance stabilizing transformation in DESeq2
Genome_build: Mus musculus genome Ensembl GRCm38 (release 86)
Supplementary_files_format_and_content: Excel files containing raw counts, DESeq2 normalized counts, and DESeq2 log2 expression values
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| Submission date |
Sep 12, 2018 |
| Last update date |
May 08, 2019 |
| Contact name |
Akul Singhania |
| E-mail(s) |
akul.singhania@crick.ac.uk
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| Phone |
+442037963319
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| Organization name |
The Francis Crick Institute
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| Street address |
1 Midland Road
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| City |
London |
| ZIP/Postal code |
NW1 1AT |
| Country |
United Kingdom |
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| Platform ID |
GPL21103 |
| Series (2) |
| GSE119852 |
Global transcriptional profiling unveils the interferon network in blood and tissues across different diseases [RNA-seq_HDM_sorted_CD4_Tcells] |
| GSE119856 |
Global transcriptional profiling unveils the interferon network in blood and tissues across different diseases |
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| Relations |
| BioSample |
SAMN10037924 |
| SRA |
SRX4672950 |
| Supplementary data files not provided |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data are available on Series record |
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