|
|
GEO help: Mouse over screen elements for information. |
|
Status |
Public on Sep 23, 2022 |
Title |
03idBALBCmo2rp3 |
Sample type |
SRA |
|
|
Source name |
Lacrimal Gland
|
Organism |
Mus musculus |
Characteristics |
tissue: Lacrimal Gland strain: BALB/cJ age: 2 months Sex: male
|
Growth protocol |
Mice were fed ad libitum and kept under a 12-hour light/12-hour dark cycle
|
Extracted molecule |
total RNA |
Extraction protocol |
Each lacrimal gland was transferred into 2mL bead beating tubes (cat# 19-628, OMNI, Kennesaw GA) containing 700 µL of Qiazol lysis reagent (#79306, Qiagen). The lacrimal gland was disrupted using Bead Ruptor 4 (cat# 25-010, Omni) in two cycles: first at speed 5, for 40 sec and then at speed 5, for 30 sec. Between the two cycles, the tubes were placed on ice for 2 mins. RNA was isolated with the miRNeasy Mini kit (#217084, Qiagen) including a DNAse treatment step, according to the manufacturer’s instructions. The amount of total RNA was estimated by a Nanodrop ND-1000 spectrophotometer and checked for purity and integrity (RIN) in a Bioanalyzer-2100 device (Agilent Technologies, Inc., Santa Clara, CA). 800 ng of total RNA (RIN>8) from each sample was used to prepare RNAseq libraries using the NEBNext rRNA Depletion Kit (Human/Mouse/Rat) followed by the NEBNext Ultra II RNA Library Prep Kit for Illumina (9 cycles of PCR). Completed libraries had been sequenced (2 x 75 paired ends) using Illumina NextSeq500 to generate 50M reads for each sample.
|
|
|
Library strategy |
RNA-Seq |
Library source |
transcriptomic |
Library selection |
cDNA |
Instrument model |
Illumina NextSeq 500 |
|
|
Data processing |
Data was analyzed by ROSALIND® (https://rosalind.bio/), with a HyperScale architecture developed by ROSALIND, Inc. (San Diego, CA). Reads were trimmed using cutadapt Quality scores were assessed using FastQC Reads were aligned to the Mus musculus genome build GRCm38 using STAR Individual sample reads were quantified using HTseq Reads were normalized via Relative Log Expression (RLE) using DESeq2 R library Read Distribution percentages, violin plots, identity heatmaps, and sample MDS plots were generated as part of the QC step using RSeQC DEseq2 was also used to calculate fold changes and p-values and perform optional covariate correction. Clustering of genes for the final heatmap of differentially expressed genes was done using the PAM (Partitioning Around Medoids) method using the fpc R library Assembly: Mus musculus genome build GRCm38 Supplementary files format and content: Raw Count matrix are provided in .txt file Supplementary files format and content: Normalized Count matrix are provided in .txt file
|
|
|
Submission date |
Aug 02, 2022 |
Last update date |
Sep 23, 2022 |
Contact name |
Helen Makarenkova |
E-mail(s) |
hmakarenk@scripps.edu
|
Organization name |
The Scripps Research Institute
|
Department |
Molecular Medicine
|
Lab |
Makarenkova Lab
|
Street address |
10550 N Torrey Pines Rd, MB-218
|
City |
La Jolla |
State/province |
CA |
ZIP/Postal code |
92037 |
Country |
USA |
|
|
Platform ID |
GPL19057 |
Series (1) |
GSE210332 |
Whole transcriptomics analysis of lacrimal gland during chronic inflammation progression. |
|
Relations |
BioSample |
SAMN30104362 |
SRA |
SRX16772015 |
Supplementary data files not provided |
SRA Run Selector |
Raw data are available in SRA |
Processed data are available on Series record |
|
|
|
|
|