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Sample GSM2552484

Query DataSets for GSM2552484

Status

Public on Mar 30, 2017

Title

T0.D.2670215

Sample type

SRA

Source name

Whole-blood

Organism

Homo sapiens

Characteristics

time point (weeks): T0
treatment: Duloxetine 60 mg
response: RES

Extracted molecule

total RNA

Extraction protocol

Peripheral blood samples were collected in PAXgene blood RNA tubes (PreAnalytix). PAXgene tubes were frozen using a sequential freezing process: tubes were stored at room temperature for 3hrs, transferred to 4°C overnight, followed by 6-8 hrs at -20°C, then final storage at -80°C. Total RNA (including the miRNA fraction) was isolated from whole-blood using the PAXgene Blood miRNA Kit (Qiagen, Canada), according to manufacturer’s instructions. RNA and miRNA yield and quality were determined using the Nanodrop 1000 (Thermo Scientific, USA) and Agilent 2100 Bioanalyzer (Agilent Technologies, USA).
All libraries were prepared using the Illumina TruSeq Small RNA protocol following the manufacturer's instructions with 12 cycles of PCR amplification after ligation of the 3' and 5' adapters, as described elsewhere5. Libraries were purified using biotinylated magnetic AMPure beads that allow for selection of specified cDNA products bound to streptavidin. A total of 50µl of amplified cDNA were mixed and purified twice with AMPure XP beads at a 1.8:1 ratio (beads:sample). This ratio allows for optimal selection of all products higher than 100nt. Library qualities were assessed using an Agilent 2100 Bioanalyzer High Sensitivity DNA chip, as well as qRT-PCR with the KAPA library quantification kit (Kapa Biosystems, USA). Samples were sequenced at the McGill University and Genome Quebec Innovation Centre (Montreal, Canada) using the HiSeq2500 Illumina sequencer with 50nt single-end reads.

Library strategy

miRNA-Seq

Library source

transcriptomic

Library selection

size fractionation

Instrument model

Illumina HiSeq 2500

Data processing

All sequencing data were processed using CASAVA 1.8+34 and extracted from FASTQ files. The Fastx_toolkit was used to trim the Illumina adapter sequences. Additional filtering based on defined cut-offs was applied in order to obtain high quality data. These filters included: 1) Phred quality (Q) mean scores higher than 30, 2) reads between 15-40nt in length, 3) adapter detection based on perfect-10nt match, and 4) removal of reads without detected adapter. Additionally, we used Bowtie 35 to align reads to the human genome (GRCh37)36 and ncPRO-seq37 in combination with miRBase (V20) to match them to known miRNA sequences38,39. We used a detection threshold of 10 counts per miRNA (present at least in 80% of libraries tested). A total of 281 miRNAs survived our criteria and were included in the analysis. All small RNA sequencing data was normalized with the Bioconductor – DESeq2 package using the Variance Stabilizing Transformation (VST) method40. To identify significant microRNAs based on differential expression changes across time, we used significance analysis of microarrays method, adapted for small RNA sequencing data (SAMSeq)41. SAMSeq was implemented using a two-class paired model which accounts for changes not only between groups, but also within subjects as there is a one-to-one pairing between subjects across time. We used the Benjamini–Hochberg, false discovery rate (FDR) correction for multiple testing set at 5%, which corrects for the proportion of miRNAs likely to have been identified by chance as being significant (adjusted P values < 0.05). We also tested for potential confounding effects of age, gender, race, and RNA integrity (RIN) but found no significant differences across groups or time.
Genome_build: Human genome (GRCh37)
Supplementary_files_format_and_content: Tab-delimited text file includes miRNA count values for each sample

Submission date

Mar 28, 2017

Last update date

May 15, 2019

Contact name

Juan Pablo Lopez

E-mail(s)

juan.lopez@mail.mcgill.ca

Phone

514 7616131

Organization name

McGill University