rna-seq
Description
The MCF-7 cells in the logarithmic growth phase were cultured in high-glucose DMEM medium and low-glucose DMEM medium for 48 hours. The cells were collected and stored using TRIzol reagent. A series of experiments were conducted on the samples, including RNA extraction, RNA sample quality detection, library construction, library purification, library detection, library quantification, sequencing cluster generation, and computer sequencing. The direct manifestation of a gene expression level is its abundance on the gene level. The higher the gene abundance, the higher the gene expression level. Gene expression calculation uses the Htseq software (V 0.6.1), which uses the FPKM (Fragments Per Kilo bases per Million reads) (Mortazavi, 2008) method to calculate gene expression levels. The input data for gene differential expression is the read count data obtained from the analysis of gene expression levels, and the gene difference analysis is performed using the DESeq2 (V1.26.0) package of the Bioconductor software. The fold change is the difference change value from condition A to condition B. The changes in genes between the control group (high-glucose medium) and the low-glucose group were compared. Consistent to previous observations, AKT3, MCL1 and TOP2A genes, which are essential for breast cancer cell growth, were significantly downregulated under low-glucose treatment .The results showed that LRRC15 was highly expressed in the cells treated with low glucose.
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Steps to reproduce
The MCF-7 cells in the logarithmic growth phase were cultured in high-glucose DMEM medium and low-glucose DMEM medium for 48 hours. The cells were collected and stored using TRIzol reagent. A series of experiments were conducted on the samples, including RNA extraction, RNA sample quality detection, library construction, library purification, library detection, library quantification, sequencing cluster generation, and computer sequencing. The direct manifestation of a gene expression level is its abundance on the gene level. The higher the gene abundance, the higher the gene expression level. Gene expression calculation uses the Htseq software (V 0.6.1), which uses the FPKM (Fragments Per Kilo bases per Million reads) (Mortazavi, 2008) method to calculate gene expression levels. The input data for gene differential expression is the read count data obtained from the analysis of gene expression levels, and the gene difference analysis is performed using the DESeq2 (V1.26.0) package of the Bioconductor software. The fold change is the difference change value from condition A to condition B. The changes in genes between the control group (high-glucose medium) and the low-glucose group were compared.