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

Area of Science:

• Stem Cell Biology
• Genomics
• Proteomics

Background:

• Phenotypic variability in pluripotent stem cells (PSCs) is influenced by genetic background.
• Transcript abundance is typically used to study PSC states.
• Limited understanding of proteome variability and its genetic underpinnings in PSCs.

Purpose of the Study:

• To perform a comprehensive proteogenomics analysis of genetically diverse mouse embryonic stem cell (mESC) lines.
• To identify molecular drivers of quantitative variation in pluripotency-associated pathways.
• To reveal post-transcriptional mechanisms and genetic interactions influencing the pluripotent proteome.

Main Methods:

• Proteogenomics analysis of 190 genetically diverse mESC lines.
• Integration of proteomic, transcriptomic, and chromatin accessibility data.
• Quantitative trait locus (QTL) mapping to identify genetic drivers.

Main Results:

• Significant quantitative variability in the proteome across mESC lines.
• Identification of pluripotency pathways differentially activated at the protein level, not evident from transcriptomics alone.
• Co-variation across molecular layers (protein, RNA, chromatin) and identification of shared/unique drivers of variation.
• Localization of genetic drivers to specific genomic hotspots.

Conclusions:

• Post-transcriptional regulation plays a crucial role in pluripotent proteome variability.
• Genetic interactions and hotspots significantly influence multi-omic signatures in mESCs.
• Provides a regulatory map for mESCs, facilitating future mechanistic studies of stem cell variability.