Transcriptome-wide analysis reveals sequence selection to avoid mRNA aggregation in E. coli
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The stability of RNA base pairing and its limited four-letter code create an intrinsic potential for promiscuous RNA-RNA interactions. In vitro , such interactions drive RNA to self-assemble into aggregates. This raises a fundamental unanswered question: within a confined cellular volume at physiological mRNA abundances, how much aggregation would arise from sequence-encoded chemistry alone? Here, we establish this baseline with large-scale kinetic simulations of the E. coli transcriptome. Our simulations reveal that sequence-encoded base-pairing energetics is sufficient to generate a dynamic network of large aggregates, organized by long, multivalent mRNA hubs. Strikingly, evolutionary analysis shows that native E. coli sequences exhibit clear signatures of selection to counteract this propensity: they fold more stably, minimize unstructured regions, and form weaker intermolecular contacts than dinucleotide-preserving controls. These findings demonstrate that maintaining transcriptome solubility has been a significant, previously unrecognized constraint shaping genome evolution, and provide a new lens to interpret cellular RNA management.
Significance Statement
RNA molecules are not inert carriers of genetic information: their chemistry can drive collective behaviors in cells. We developed a first-principles computational framework to quantify how much the transcriptome would aggregate if governed solely by sequence-encoded interactions in a cellular volume. Our simulations reveal that hybridization energies are sufficient to drive extensive mRNA aggregation into dynamic networks, with long transcripts acting as multivalent hubs— paralleling the organization of stress granules. Complementary evolutionary analyses show that native mRNAs bear signatures of selection against aggregation, favoring intramolecular folding to limit promiscuous intermolecular binding. These findings illuminate how RNA physical chemistry has constrained genome evolution and provide a new lens to interpret RNA behavior inside the cell.
