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Expression data from NDRG1 depleted SKBR3 cells

ABSTRACT: expression data from NDRG1 depleted SKBR3 cells

PROVIDER: PRJNA449286 | ENA |

REPOSITORIES: ENA

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expression data from NDRG1 depleted SKBR3 cells

Project description:SKBR3 cells expressing NDRG1 shRNA1 or vector control were harvested by trypsinization and total RNA was extracted. Silencing NDRG1 reduces cell proliferation rates, causing lipid metabolism dysfunction including increased fatty acid incorporation into neutral lipids and lipid droplets. global changes in transcriptome due to NDRG1 silencing were observed

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Expression data from SKBR3 cells

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RNA-sequencing of SKBR3 cells with and without NTN4 overexpression

Project description:Low NTN4 expression is correlated with breast cancer proliferation and metastasis, while the molecular mechanism of NTN4 has not been fully explored. Here, the breast cancer cells SKBR3 stably expressing dCas9-VP64 and MS-P65-HSG1 were generated by transducing a lentiviral plasmid containing lenti-dCAS-VP64-Blast (Addgene plasmid # 61425) and lenti-EF1a-MS2–p65–HSF1-2A-Hygro-WPRE (Addgene plasmid # 89308), followed by selection and maintained using 10 μg/mL of blasticidin and 200 μg/mL of hygromycin. SKBR3-dCas9-VP64-MPH cells were further transduced with a doxycycline (Dox)-induced expressing sgRNA targeting NTN4 promoter. The successfully transfected cells were selected and maintained with puromycin at a concentration of 0.5 μg/mL for SKBR3-dCas9-VP64-MPH. SKBR3-dCas9-VP64-MPH-AC-sgRNA cells were treated with or without 50 ng/μL Dox (three biological repeats for both groups) to induce NTN4 overexpressing. Total RNA was extracted using TRIzol according to the manufacturer’s instructions. The quality of RNA samples was examined by Agilent BioAnalyser 2100. The samples were subjected to RNA-sequencing analysis on the BGISEQ-500 system by Beijing Genomics Institute (BGI, China). The clean-tag reads were aligned to the reference genome and reference genes using HISAT2 and Bowtie2. The matched reads were calculated and then normalized using RSEM software. Differential gene expression was analyzed using DESeq2 and was carried out further to explore the mechanism of NTN4 in breast cancer.

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