GEO Accession viewer

NCBI > GEO > Accession Display

Not logged in | Login

GEO help: Mouse over screen elements for information.

Sample GSM2796092

Query DataSets for GSM2796092

Status

Public on Sep 29, 2017

Title

WT_distal_aorta_1

Sample type

SRA

Source name

distal aorta

Organism

Mus musculus

Characteristics

strain: 129S6
genotype/variation: wildtype
tissue: distal aorta
age: 2 months

Growth protocol

Proximal and distal aortic tissue samples were collected from 3 wildtype and 3 Notch1.129S6+/- mice at 2 months of age.

Extracted molecule

total RNA

Extraction protocol

RNA was isolated using a combination of Trizol and Total RNA Purification Kit (Norgen Biotek). Twelve (12) total RNA samples from mouse aorta tissues (n=3 of each group), were submitted to ORB for mRNA-Sequencing. The RNA was digested with RNase free DNase I (Epicentre; Part # D9905K) and re-purified on RNeasy MinElute columns (Qiagen; Part #: 74204) using an alternative high-ethanol binding condition to preserve Low Molecular Weight (LMW) RNAs. The newly prepared digested total RNA samples were then quantified by Quant-iT RiboGreen RNA fluorometric assay (Thermo Fisher Scientific; Part # R11491) and assessed for quality by Agilent2100 Bioanalyzer RNA 6000 Pico Assay (Agilent Technologies; Part # 5067-1513).
Amplified cDNA was prepared from a total of 10 nanograms (ng) of the digested total RNA samples using the NuGen Ovation RNA-Seq System v2 (NuGen: Part # 7102-A01) and fragmented using NEBNext dsDNA Fragmentase (NEB: Part # M0348L). Template DNA molecules suitable for cluster generation were then prepared from the fragmented cDNA using the Illumina TruSeq DNA Nano HT Library Preparation Kit (Illumina Inc.: Part # FC-121-4003). The quality and size distribution of the amplified cDNA libraries were determined by chip-based capillary electrophoresis using an Agilent 2100 Bioanalyzer DNA 1000 Chip assay (Agilent Technologies: Part # 5067-1504). The libraries were then quantified using the KAPA Library Quantification Kit (Kapa Biosystems; Boston MA). The libraries were pooled at equimolar concentrations and diluted prior to loading onto the flow cell of the Illumina cBot cluster station. The libraries were extended and bridge amplified to create sequence clusters using the Illumina HiSeq PE Cluster Kit v4 and sequenced on an Illumina HiSeq Flow Cell v4 with 50-bp paired-end reads plus dual index read using the Illumina HiSeq SBS Kit v4. Real time image analysis and base calling were performed on the HiSeq2500 using the HiSeq Sequencing Control Software version 2.2.68.

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

Illumina HiSeq 2500

Description

SL151325

Data processing

The raw FASTQ files were split into files containing 4,000,000 reads and checked for quality using FASTX toolbox
Based on the quality results, the reads were filtered (removing sequences that did not pass Illumina’s quality filter) and trimmed (3 nucleotides at the left end of R1 and 3 nucleotides off the left end of R2).
Sequence alignment to the mm10 mouse reference genome was performed using TopHat v2.1.0 with fr-unstranded as the library type. The mate-inner-distance and mate-std-dev settings were determined for each sample by non-gapped alignment of a portion of the reads to the mouse mRNA reference using Bowtie2. All other TopHat settings were left as default.
Exon- and gene-level read counts were calculated using the easyRNASeq function of the easyRNASeq R package version 2.4.7 running on R version 3.2.2. For gene-level read counts, the summarization method used was geneModels. For annotation, an RDA file was generated from the Ensembl Mouse Release 83 gene transfer format (GTF) file using the annotation file generation function of easyRNASeq.
Gene-level read counts were adjusted for library size and gene length by calculating the reads per kilobase transcript length per million mapped reads (RPKM). A reliable quantification threshold (RQT) was calculated for each sample according to the formula RQT = (50 / 2) / (total mapped reads / 1,000,000), which would be equal to an RPKM equivalent of 50 reads assuming an average gene length of 2 kb. The RPKM values were filtered to retain a list of genes whose RPKM values were above RQT in one or more samples. To avoid reporting large fold changes due to random variation of counts from low abundance mRNA, RPKM values equivalent to a count of <= 10 reads per gene were replaced with the average RPKM value equivalent to 10 reads/gene across all the samples in the experiment.
A 2-way ANOVA was performed on the log2 RPKM data for the 21,954 detectable mouse genes to examine the effect of Genotype (Wildtype and Notch1+/-) and Location (Proximal and Distal) as well as their interaction on gene expression. Tukey honestly significant difference tests were performed to determine the effect of genotype within each location and the effect of location within each genotype. No Tukey test was run if the average log2 RPKM value for both groups in the pairwise comparison was less than RQT. ANOVA and Tukey p values across all genes were adjusted to control the false discovery rate (FDR). Differentially expressed genes were defined as those having a Tukey P value < 0.05 and an expression fold change ≥ 1.5. All statistical analysis was performed using R version 3.2.2 statistical computing software.
Genome_build: mm10
Supplementary_files_format_and_content: The processed data file is an xlsx format, and contains the differential gene expression information, and includes information on the Gene ID, Related pubmed links, description, Tukey P values, Tukey FDR values, fold changes, and RPKM for each gene for each sample. Within this file, there is also the correlation matrix as a tab, thresholds as a tab, and sample info as a tab.

Submission date

Sep 28, 2017

Last update date

May 15, 2019

Contact name

Vidu Garg

E-mail(s)

vidu.garg@nationwidechildrens.org

Phone

614-355-5710

Organization name

Research Institute at Nationwide Children's Hospital