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Gene loss during the transition to multicellularity

Jimenez-Marin, B.; Rakijas, J. B.; Tyagi, A.; Pandey, A.; Hanschen, E. R.; Anderson, J.; Heffel, M. G.; Platt, T. G.; Olson, B. J. S. C.

2021-02-17 evolutionary biology
10.1101/2021.02.16.431445 bioRxiv
Show abstract

Multicellular evolution is a major transition associated with momentous diversification of multiple lineages and increased developmental complexity. The volvocine algae comprise a valuable system for the study of this transition, as they span from unicellular to undifferentiated and differentiated multicellular morphologies despite their genomes being highly similar, suggesting multicellular evolution requires few genetic changes to undergo dramatic shifts in developmental complexity. Here, the evolutionary dynamics of six volvocine genomes were examined, where a gradual loss of genes was observed in parallel to the co-option of a few key genes. Protein complexes in the six species exhibited a high degree of novel interactions, suggesting that gene loss plays a role in evolutionary novelty. This finding was supported by gene network modeling, where gene loss outpaces gene gain in generating novel stable network states. These results suggest developmental complexity may be driven by gene loss, and not just by gene gain. Significance StatementIncreased developmental complexity is thought to evolve mainly through genetic innovation and co-option. Comparison of the genomes of the closely related volvocines revealed that despite large changes in developmental complexity their genomes are exhibiting significant gene loss. Further, a burst of gene loss is shown to occur at the transition to undifferentiated multicellularity by gene inactivation and decay. This likely results in changes to protein-protein interactions within the cell, suggesting evolutionary novelty does not always require gene gain. Using empirical and modelling approaches we demonstrate gene loss can more easily produce protein network novelty than gene gain. We propose that gene loss can be a driver of biological innovation, allowing for reconfiguration of gene networks and differential use of existing functional repertoires.

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