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Sample GSM3058946

Query DataSets for GSM3058946

Status

Public on May 10, 2018

Title

Corneal tissue Con_S7

Sample type

SRA

Source name

Corneal tissue S7

Organism

Homo sapiens

Characteristics

individual: Control, myopia patient
tissue: Corneal tissue
batch: 2
Sex: Male

Extracted molecule

total RNA

Extraction protocol

RNeasy mini kit (Qiagen) was used to extract the RNA from tissues, following the manufacturer’s instruction with minor modifications. Briefly, RNALater was carefully removed from Eppendorf tubes containing tissues, and 300 μL of RLT containing 2-mercaptoethanol in a 100:1 ratio was added to each tube and the tubes were vortexed until the tissues were dissolved. Equal portions of 70% ethanol (300 μL) were added to each tube, vortexed, and centrifuged at 12,000xg for 20s at room temperature (RT). The cartridge was washed wash buffer I (700 μL) at 12,000g for 20s followed by two more wash with wash buffer II (500 μL) at 12,000g for 15s. The cartridge was dried at 12,000xg for 1min at RT and 30μL of RNase-Free water was added to center of the cartridge and incubated at RT for 2min. Purified RNA was eluted by centrifuging at 20,000xg for 2min at RT and then stored at -80 °C for further use.
mRNA libraries were prepared at the Ramaciotti Centre for Genomics (UNSW University of New South Wales, Australia). The Illumina TruSeq Stranded mRNA Prep Kit was used. AllRNA-Seq libraries were sequenced using the Illumina NextSeq 500. R1.fastq and R2.fastq files were produced for each sample.

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

Illumina NextSeq 500

Description

counts_table.txt
Con_S7

Data processing

RNA samples were prepared using the TruSeq Stranded Total RNA Library Prep Kit (Illumina,USA) according to the manufacturer’s instructions. One μg of total RNA was used as input to the Ribozero rRNA-depletion step of the assay. The adapter-ligated cDNA was enriched using 12 cycles of PCR. The libraries were sequenced on a NextSeq500 (Illumina) using a 75bp paired end read high output v2 run. This produced between 27 M and 60 M paired end reads per sample
The samples were processed in 2 batches each with the same number of KC (n=5 per batch) and control subjects (n=5 per batch). We mapped the 75 nucleotide reads to the human genome (GRCh38) using TopHat2 (v 2.0.4) 56, calling the Bowtie aligner (v 2-2.0.0-beta7) 57, allowing up to 2 bp mismatches per read (default position)
HTSeq-count (Python package HTSeq, python v 2.7.3) was used to generate counts of reads uniquely mapped to known and annotated genes using the Ensembl annotation file GRCh38.79.gtf (mode=union, –t = exon, –i = gene_name). The number of uniquely mapped reads varied between 41-50 million per sample in the first batch and 18-32 million per sample in the second batch
The count table of uniquely mapped reads was then used and differential expression was tested using the Bioconductor packages, edgeR (v3.16.0) and DESeq2 (v1.14.0).
Genome_build: Ensembl Home sapiens genome (GRCh38)
Supplementary_files_format_and_content: Tab-delimited text file with read count for each sample.

Submission date

Mar 21, 2018

Last update date

May 10, 2018

Contact name

Susan Corley

E-mail(s)

s.corley@unsw.edu.au

Phone

+61 02 9385 8853

Organization name

UNSW