Multi-omics analysis of aggregative multicellularity

All organisms have to carefully regulate their gene expression, not least during development. mRNA levels are often used as proxy for protein output; however, this approach ignores post-transcriptional effects. In particular, mRNA-protein correlation remains elusive for organisms that exhibit aggregative rather than clonal multicellularity. We addressed this issue by generating a paired transcriptomics and proteomics time series during the transition from uni-to multicellular stage in the social ameba Dictyostelium discoideum. Our data reveals that mRNA and protein levels correlate highly during unicellular growth, but decrease when multicellular development is initiated. This accentuates that transcripts alone cannot accurately predict protein levels. The dataset provides a useful resource to study gene expression during aggregative multicellular development. Additionally, our study provides an example of how to analyze and visualize mRNA and protein levels, which should be broadly applicable to other organisms and conditions.