The evolution of large organismal size is fundamentally important for multicellularity, creating new ecological niches and opportunities for the evolution of increased biological complexity. Yet little is known about how large size evolves, particularly in nascent multicellular organisms that lack genetically-regulated multicellular development. Here we examine the interplay between biological and biophysical drivers of macroscopic multicellularity using long-term experimental evolution. Over 600 daily transfers (~3,000 generations), multicellular snowflake yeast evolved macroscopic size, becoming ~2·104 times larger (~mm scale) and 104-fold more biophysically tough, while remaining clonal. They accomplished this through sustained biophysical adaptation, evolving increasingly elongate cells that initially reduced the strain of cellular packing, then facilitated branch entanglement so that groups of cells stay together even after many cellular bonds fracture. Four out of five replicate populations show evidence of predominantly adaptive evolution, with mutations becoming significantly enriched in genes affecting cell shape and cell-cell bonds. Taken together, this work shows how selection acting on the emergent properties of simple multicellular groups can drive sustained biophysical adaptation, an early step in the evolution of increasingly complex multicellular organisms.

We analyze patterns of gene presence and absence in a maximum likelihood framework with rate parameters for gene gain and loss. Standard methods allow independent gains and losses in different parts of a tree. While losses of the same gene are likely to be frequent, multiple gains need to be considered carefully. A gene gain could occur by horizontal transfer or by origin of a gene within the lineage being studied. If a gene is gained more than once, then at least one of these gains must be a horizontal transfer. A key parameter is the ratio of gain to loss rates, a/v We consider the limiting case known as the infinitely many genes model, where a/v tends to zero and a gene cannot be gained more than once. The infinitely many genes model is used as a null model in comparison to models that allow multiple gains. Using genome data from cyanobacteria and archaea, it is found that the likelihood is significantly improved by allowing for multiple gains, but the average a/v is very small. The fraction of genes whose presence/absence pattern is best explained by multiple gains is only 15% in the cyanobacteria and 20% and 39% in two data sets of archaea. The distribution of rates of gene loss is very broad, which explains why many genes follow a treelike pattern of vertical inheritance, despite the presence of a significant minority of genes that undergo horizontal transfer.

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The prevalence of multicellular organisms is due in part to their ability to form complex structures. How cells pack in these structures is a fundamental biophysical issue, underlying their functional properties. However, much remains unknown about how cell packing geometries arise, and how they are affected by random noise during growth - especially absent developmental programs. Here, we quantify the statistics of cellular neighborhoods of two different multicellular eukaryotes: lab-evolved ‘snowflake’ yeast and the green alga Volvox carteri. We find that despite large differences in cellular organization, the free space associated with individual cells in both organisms closely fits a modified gamma distribution, consistent with maximum entropy predictions originally developed for granular materials. This ‘entropic’ cellular packing ensures a degree of predictability despite noise, facilitating parent-offspring fidelity even in the absence of developmental regulation. Together with simulations of diverse growth morphologies, these results suggest that gamma-distributed cell neighborhood sizes are a general feature of multicellularity, arising from conserved statistics of cellular packing.