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Sample GSM2033120

Query DataSets for GSM2033120

Status

Public on Jul 07, 2017

Title

Scramble antagomiR-transfected CD34+-ECs, Replicate 1

Sample type

SRA

Source name

Endothelial cell

Organism

Homo sapiens

Characteristics

passage number: Passage 5
transfection: Scramble antagomiR
cell type: CD34+ endothelial cells

Treatment protocol

CD34+ endothelial cells differentiated from umbilical cord blood hematopoietic stem cells (CD34+) were treated with 50 nM antagomiR-17 (transfection group, AmiR; Dharmacon) or scrambled antagomiR (control group; Ambion) using Lipofectamine RNAiMAx (Life Technologies) for 48 h.

Growth protocol

Human CD34+ endothelial cells were expanded in 1% (w/v) gelatin-coated T75 flasks (BD Falcon) in EGM-2 medium (Lonza). The cultures were incubated at 37 ºC in a humidified incubator with 5% CO2 and medium was refreshed every other day.

Extracted molecule

total RNA

Extraction protocol

Total RNA was isolated using the miRVanaTM miRNA isolation kit from Ambion (Cat# AM1560) according to the manufacturer’s instructions. RNA sample quality control was performed by Exiqon (Vedbaek, Denmark).
Library quality control and quantification were performed by Exiqon (Vedbaek, Denmark). The library preparation was done using TruSeq® Stranded mRNA Sample preparation kit (Illumina inc). The starting material (500 ng) of total RNA was mRNA enriched using the oligodT bead system (manufacturer). The isolated mRNA was subsequently fragmented using enzymatic fragmentation. Then first strand synthesis and second strand synthesis were performed and the double stranded cDNA was purified (AMPure XP, Beckman Coulter). The cDNA was end repaired, 3’ adenylated and Illumina sequencing adaptors ligated onto the fragments ends, and the library was purified (AMPure XP). The mRNA stranded libraries were pre-amplified with PCR and purified (AMPure XP). The libraries size distribution was validated and quality inspected on a Bioanalyzer high sensitivity DNA chip (Agilent Technologies). High quality libraries were quantified using qPCR, the concentration normalized and the samples pooled according to the project specification (number of reads). The library pool(s) were re-quantified with qPCR and optimal concentration of the library pool used to generate the clusters on the surface of a flowcell before sequencing on Nextseq500 instrument using High Output sequencing kit (50 cycles) according to the manufacturer instructions (Illumina Inc.).

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

Illumina NextSeq 500

Data processing

The data analysis pipeline is based on the Tuxedo software package, which is a combination of open-source software and implements peer-reviewed statistical methods. In addition, specialized software developed internally at Exiqon was exployed to interpret and improve the readability of the final results.
The components of NGS RNA seq analysis pipeline include Bowtie2 (v. 2.2.2), Tophat (v2.0.11) and Cufflinks (v2.2.1) and are described in detail below.
Tophat is a fast splice junction mapper for RNA-Seq reads. It aligns the sequencing reads to the reference genome using the sequence aligner Bowtie2. Tophat also uses the sequence alignments to identify splice junctions for both known and novel transcripts.
Cufflinks takes the alignment results from Tophat to assemble the aligned sequences into transcripts, constructing a map or a snapshot of the transcriptome. To guide the assembly process, an existing transcript annotation is used. In addition, fragment bias correction which seeks to correct for sequence bias during library preparation (see Kasper et al., 2010 and Adam et al., 2011) was performed. The Cufflinks assembles aligned reads into different transcript isoforms based on exon usage and also determines the transcriptional start sites (TSSs).
When comparing groups, Cuffdiff is used to calculate the FPKM (number of fragments per kilobase per million mapped fragments) and test for differential expression and regulation among the assembled transcripts across the submitted samples using the Cufflinks output. Cuffdiff can be used to test differential expression at different levels, from CDS and gene specific, down to the isoform and TSS transcript level. For more information on the Cuffdiff module, see Trapnell et al., (2013).
As a final step, CummeRbund, which is an open source R package, will be used in combination with in-house custom software for post processing of Cufflinks and Cuffdiff results.
genome build: hsa hg 19 (Gencode v11) genome build from Ensembl has been used for annotation.
Supplementary_files_format_and_content: Differential Expression (cuffdiff_data): Result files created by Cuffdiff (see http://cole-trapnell-lab.github.io/cufflinks/cuffdiff)

Submission date

Jan 08, 2016

Last update date

May 15, 2019

Contact name

Sezin Aday

E-mail(s)

sezin_aday@yahoo.com

Organization name

University of Pennsylvania

Street address

210 South 33rd Street, Skirkanich Hall