|
| Status |
Public on May 18, 2024 |
| Title |
MDA-MB-231 cells, RCCs,rep1 |
| Sample type |
SRA |
| |
|
| Source name |
MDA-MB-231
|
| Organism |
Homo sapiens |
| Characteristics |
cell line: MDA-MB-231
cell type: triple-negative breast cancer (TNBC) cell line
genotype: WT
treatment: sorted PKH26lo cells
|
| Treatment protocol |
MDA-MB-231 cells were labeled with PKH26 and chased for 12 days. Cells with top 1% PKH26 retaining were sorted as slow-cycling cells (SCCs). Cells with moderate PKH26 intensity were sorted as rapid-cycling cells (RCCs).
|
| Growth protocol |
MDA-MB-231 cells were maintained in DMEM, high glucose supplemented with 10% fetal bovine serum (FBS) and antibiotics in humidified atmosphere with 5% CO2 at 37C
|
| Extracted molecule |
total RNA |
| Extraction protocol |
RNA was harvested using TRIzol (Invitrogen). 1.0 μg of total RNA was used for the construction of sequencing libraries.
Sequencing libraries were generated using NEBNext® UltraTM RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample.
|
| |
|
| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina HiSeq 2000 |
| |
|
| Description |
non_LRC1_1
|
| Data processing |
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 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.
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: Homo_sapiens_Ensemble_94
Supplementary files format and content: tab-delimted text file includes raw counts for each sample
Supplementary files format and content: tab-delimted text file includes RPKM counts for each sample
|
| |
|
| Submission date |
May 17, 2024 |
| Last update date |
May 18, 2024 |
| Contact name |
Yang Dong |
| E-mail(s) |
1810441@tongji.edu.cn
|
| Phone |
19542707574
|
| Organization name |
Tongji University
|
| Street address |
Shanghai
|
| City |
Shanghai |
| State/province |
上海 |
| ZIP/Postal code |
200120 |
| Country |
China |
| |
|
| Platform ID |
GPL11154 |
| Series (1) |
| GSE267759 |
AP-1 regulates heterogeneous cellular dormancy in TNBC II |
|
| Relations |
| BioSample |
SAMN41438108 |
| SRA |
SRX24593544 |
