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Sample GSM3405415

Query DataSets for GSM3405415

Status

Public on Apr 30, 2019

Title

UF-dFBS-1

Sample type

SRA

Source name

Ultrafiltrated EV-depleted fetal bovine serum extracellular vesicles

Organism

Bos taurus

Characteristics

sample type: EV
medium: Ultrafiltrated EV-depleted fetal bovine serum
supplier: Sigma-Aldrich

Extracted molecule

total RNA

Extraction protocol

Two supernatant removal steps were used on 3 ml of culture media to get rid of the un-precipitated material. EV lysis and RNA isolation was performed on 500 µl of media using exoRNeasy Serum/Plasma Maxi Kit (QIAGEN).
Library preparation was done using the QIAseq miRNA Library Kit (QIAGEN). Out of 12µl of isolated RNA, 5µl was converted into microRNA NGS libraries. Adapters containing 12nt-long unique molecular indices (UMIs) were ligated to the RNA. Then RNA was converted to cDNA. The cDNA was amplified using PCR (22 cycles) and during the PCR indices were added. After PCR the samples were purified. Library preparation quality control was performed using either Bioanalyzer 2100 (Agilent) or TapeStation 4200 (Agilent). Based on the quality of the inserts and the concentration measurements the libraries were pooled in equimolar ratios. The library pools were quantified using the qPCR ExiSEQ LNA™ Quant kit (Exiqon). The library pools were then sequenced on a NextSeq500 sequencing instrument according to the manufacturer instructions using 1x75bp reads.

Library strategy

ncRNA-Seq

Library source

transcriptomic

Library selection

size fractionation

Instrument model

Illumina NextSeq 500

Description

miRNA_raw.txt
smRNA_raw.txt
miRNA_spikein_normalized.txt
smRNA_spikein_normalized.txt

Data processing

Raw data was demultiplexed and FASTQ files for each sample were generated using the bcl2fastq software (Illumina inc.).
To correct PCR bias with UMI information, raw reads were processed as follows: First, cutadapt 1.11 was used on each raw read with the adapter sequence to acquire information about the presence of adapter. Only reads that fulfilled the following criteria were kept: 1) read contained adapters, 2) read had at least 16nt insert sequence length, and 3) read had at least 10nt-long UMI sequence. Second, insert sequences with incomplete UMI sequence were extracted as partial-UMI reads. Third, all unique insert+UMI combinations were identified from reads with full-length UMI and collapsed into a single read. Fourth, collapsed full-length UMI reads and partial-UMI reads were combined.
After UMI-correction, reads were trimmed using cutadapt output and an in-house script.
Reads were mapped using Bowtie 2 (2.2.2) as follows: First, reads mapped to spike-ins or outmapped (mapped to adapter sequences, polyA and polyC homopolymers, or abundant ribosomal or mitochondrial RNA sequences) were filtered out. Perfect match to the reference sequence was required. Second, reads were aligned to mature sequences of miRBase 20, requiring perfect matches. Third, unmapped reads were mapped to either to human GRCh37 or bovine UMD3 reference genome, allowing one mismatch in the first 32 bases of the read. Reads aligned to known miRNA loci in the genome were combined with the miRBase-mapped reads and reads aligned to smallRNA reqions in the Exiqon smallRNA database were classified as smallRNA. Reads mapping to the reference genome outside the miRNA or smallRNA regions were classified as genome-mapped. No indels were allowed in any of the mapping steps.
Read counts were normalized using the external spike-ins (UniSp100-UniSp151) that were present in three relative concentrations of 0.1 (low), 1 (moderate) and 5 (high), reflecting the expected range of miRNAs in the samples. Linear functions with intercept fixed at zero were fitted to the spike-in concentration versus observed counts in each sample. The linear fit was used calculate an estimated relative concentration for each RNA.
Genome_build: GRCh37
Supplementary_files_format_and_content: .txt files contain results of mapping to miRBase 20 and GRCh37 reference genome. miRNA_raw.txt: miRNA raw counts for all samples, smRNA_raw.txt: other smRNA raw counts for all samples, miRNA_spikein_normalized.txt: spike-in normalized miRNA counts for all samples, smRNA_spikein_normalized.txt: spike-in normalized counts for other smRNA for all samples.

Submission date

Sep 27, 2018

Last update date

Apr 30, 2019

Contact name

Sippy Kaur

E-mail(s)

sippy.kaur@helsinki.fi

Organization name

University of Helsinki

Department

Oral and Maxillofacial Diseases