Genetic dissection of the pluripotent proteome through multi-omics data integration

Genetic background is a major driver of the phenotypic variability observed across pluripotent stem cells (PSCs), and studies addressing it have relied on transcript abundance as the primary molecular readout of cell state. However, little is known about how proteins, the functional units in the cell, vary across genetically diverse PSCs and how this relates to variation in other measures of gene output. Here we present the first comprehensive genetic study characterizing the pluripotent proteome using 190 unique mouse embryonic stem cell lines derived from highly heterogeneous Diversity Outbred mice. Moreover, we integrated the proteome with chromatin accessibility and transcript abundance in 163 cell lines with matching genotypes using multi-omics factor analysis to distinguish shared and unique drivers of variability across molecular layers. Our findings highlight the power of multi-omics data integration in revealing the distal impacts of genetic variation. We show that limitations in mapping of individual molecular traits may be overcome by utilizing data integration to consolidate the influence of genetic signals shared across molecular traits and increase detection power.