Identifying the genes impacted by cell proliferation in proteomics and transcriptomics studies.

ABSTRACT: Hypothesis-free high-throughput profiling allows relative quantification of thousands of proteins or transcripts across samples and thereby identification of differentially expressed genes. It is used in many biological contexts to characterize differences between cell lines and tissues, identify drug mode of action or drivers of drug resistance, among others. Changes in gene expression can also be due to confounding factors that were not accounted for in the experimental plan, such as change in cell proliferation. We combined the analysis of 1,076 and 1,040 cell lines in five proteomics and three transcriptomics data sets to identify 157 genes that correlate with cell proliferation rates. These include actors in DNA replication and mitosis, and genes periodically expressed during the cell

SUBMITTER: Locard-Paulet M 

PROVIDER: S-EPMC9578628 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature