Body-axis organization in tetrapods: a model-system to disentangle the developmental origins of convergent evolution in deep time

Convergent evolution is a central concept in evolutionary theory but the underlying mechanism has been largely debated since On the Origin of Species. Previous hypotheses predict that developmental constraints make some morphologies more likely to arise than others and natural selection discards those of the lowest fitness. However, the quantification of the role and strength of natural selection and developmental constraint in shaping convergent phenotypes on macroevolutionary timescales is challenging because the information regarding performance and development is not directly available. Accordingly, current knowledge of how embryonic development and natural selection drive phenotypic evolution in vertebrates has been extended from studies performed at short temporal scales. We propose here the organization of the tetrapod body-axis as a model system to investigate the developmental origins of convergent evolution over hundreds of millions of years. The quantification of the primary developmental mechanisms driving body-axis organization (i.e. somitogenesis, homeotic effects and differential growth) can be inferred from vertebral counts, and recent techniques of three-dimensional computational biomechanics have the necessary potential to reveal organismal performance even in fossil forms. The combination of both approaches offers a novel and robust methodological framework to test competing hypotheses on the functional and developmental drivers of phenotypic evolution and evolutionary convergence.

Automated summary

Convergent evolution is a central concept in evolutionary theory, but the mechanisms underlying it have been debated. Research suggests that natural selection and developmental constraints play key roles in shaping convergent traits, but quantification over long periods is challenging. By studying the body-axis organization in tetrapods, researchers can infer primary developmental mechanisms and use computational biomechanics to reveal organismal performance, presenting a novel methodological framework.