Proteome-wide copy-number estimation from transcriptomics

ABSTRACT: Protein copy numbers constrain systems-level properties of regulatory networks, but proportional proteomic data remain scarce compared to RNA-seq. We related mRNA to protein statistically using best-available data from quantitative proteomics-transcriptomics for 4366 genes in 369 cell lines. The approach starts with a protein's median copy number and hierarchically appends mRNA-protein and mRNA-mRNA dependencies to define an optimal gene-specific model linking mRNAs to protein. For dozens of cell lines and primary samples, these protein inferences from mRNA outmatch stringent null models, a count-based protein-abundance repository, empirical protein-to-mRNA ratios, and a proteogenomic DREAM challenge winner. The optimal mRNA-to-protein relationships capture biological processes along with

SUBMITTER: Dr Andrew, J. Sweatt 

PROVIDER: S-SCDT-10_1038-S44320-024-00064-3 | biostudies-other |

REPOSITORIES: biostudies-other