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Sample GSM7865810

Query DataSets for GSM7865810

Status

Public on Nov 15, 2023

Title

P301L_2

Sample type

SRA

Source name

Primary cultured neurons

Organism

Mus musculus

Characteristics

cell type: Primary cultured neurons
genotype: WT
treatment: AAV-P301L

Extracted molecule

total RNA

Extraction protocol

RNA was harvested using Direct-zol RNA Microprep Kits
Messenger RNA was purified from total RNA using poly-T oligo-attached magnetic beads. After fragmentation, the first strand cDNA was synthesized using random hexamer primers, followed by the second strand cDNA synthesis using either dUTP for directional library or dTTP for non-directional library.

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

Illumina HiSeq 2500

Data processing

Quality control: Raw data (raw reads) of fastq format were firstly processed through fastp software. In this step, clean data (clean reads) were obtained by removing reads containing adapter, reads containing ploy-N and low quality reads from raw data. At the same time, Q20, Q30 and GC content the clean data were calculated. All the downstream analyses were based on the clean data with high quality.
Reads mapping to the reference genome: Reference genome and gene model annotation files were downloaded from genome website directly. Index of the reference genome was built using Hisat2 v2.0.5 and paired-end clean reads were aligned to the reference genome using Hisat2 v2.0.5. We selected Hisat2 as the mapping tool for that Hisat2 can generate a database of splice junctions based on the gene model annotation file and thus a better mapping result than other non-splice mapping tools.
Quantification of gene expression level: featureCounts v1.5.0-p3 was used to count the reads numbers mapped to each gene. And then FPKM of each gene was calculated based on the length of the gene and reads count mapped to this gene. FPKM, expected number of Fragments Per Kilobase of transcript sequence per Millions base pairs sequenced, considers the effect of sequencing depth and gene length for the reads count at the same time, and is currently the most commonly used method for estimating gene expression levels.
Assembly: mm10
Supplementary files format and content: Text files include average count number for each group

Submission date

Oct 25, 2023

Last update date

Nov 15, 2023

Contact name

Wei Cao

E-mail(s)

[email protected]

Organization name

The University of Texas Health Science Center at Houston

Street address

6431 Fannin Street