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Sample GSM6041831

Query DataSets for GSM6041831

Status

Public on May 18, 2022

Title

Sheep granulosa cells low-glucose treatment group, LOW_3

Sample type

SRA

Source name

Granulosa cells

Organism

Ovis aries

Characteristics

cell type: Granulosa cells
treatment: Granulosa cells were cultured with glucose concentration of 8.4 mM
strain: thin-tailed Han

Treatment protocol

The GCs were allocated to six treatments and cultured in 6-well plates at a density of 1×106/well using DMEM/F12 medium supplemented with 10% FBS. All treatments were cultured without glucose and serum but containing streptomycin/penicillin mixture (1%) for 8 h; then, the treatments received various solutions of glucose and were cultured for an additional 24 h as follows: 0 mM (i.e., zero glucose), 2.1 mM (378.3 μg/ml), 4.2 mM (756.6 μg/ml), 8.4 mM (1513.2 μg/ml), 16.8 mM (3026.4 μg/ml), 33.6 mM (6052.8 μg/ml). These doses were designed to span the normal physiological ranges of follicles

Growth protocol

the GCs were seeded in cell culture plates (Thermo Fisher Scientific, USA) at a density of 1×105/well and cultured in Dulbecco’s Modified Eagle Medium (DMEM/F12, Gibco, USA) supplemented with 10% fetal bovine serum (FBS) (Gibco, Grand Island, NY, USA) and 1% streptomycin/penicillin mixture in a humidiﬁed atmosphere at 37 ℃ and 5% CO2 for 48 h with the medium changed every 24 h.

Extracted molecule

total RNA

Extraction protocol

Total RNA was extracted by Trizol method to construct a high-throughput sequencing library

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

HiSeq X Ten

Description

G1_3
Glucose regulates germ cell proliferation and differentiation
LOW_3

Data processing

Tophat2（http://tophat.cbcb.umd.edu；Trapnell C et al., 2009), Hisat2（http://ccb.jhu.edu/software/hisat2；Kim D et al., 2015), STAR（http://code.google.com/p/rna-star；Dobin A et al., 2013）
Raw data (raw reads) of fastq format were firstly processed through in-house perl scripts. 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.
Reference genome and gene model annotation files were downloaded from genome website directly. Index of the reference genome was built using STAR and paired-end clean reads were aligned to the reference genome using STAR (v2.5.1b). STAR used the method of Maximal Mappable Prefix(MMP) which can generate a precise mapping result for junction reads.
HTSeq v0.6.0 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.
Supplementary files format and content: count and FPKM

Submission date

Apr 12, 2022

Last update date

May 18, 2022

Contact name

Yong Wang

E-mail(s)

huyifeikeyan@sina.com

Phone

+8618730236550

Organization name

Hebei Agricultural University