The phenomenon of convergent evolution fascinates scientists across disciplines. Classic examples of convergent traits, such as the camera-eyes in vertebrates and cephalopods or the wings of bats, birds and insects, remind us of the efficacy of evolution as well as the common environmental constraints shared by organisms. Yet, the extent to which convergent molecular processes drive structural convergence remains unclear. This study investigates if the number of possible ?molecular solutions? for a trait favored by natural selection is as limited as the number of structural solutions. By investigating gene expression profiles, this project addresses whether the pressure of natural selection influences genomic resourcefulness and causes the independent deployment of similar genetic pathways.
Convergent forms of bioluminescence have originated often across diverse forms of life, providing an excellent system for investigating convergent evolution. Within cephalopods, a form of bioluminescence reliant on a luminous symbiotic bacterium has evolved multiple times. This study investigates if the expression profiles for genes required for the specialized organ housing these bacteria are as similar as the profiles between organs that share an evolutionary history (eyes, brain, etc.). Results of this work have important consequences for our understanding of gene expression evolution and the evolution of animal-bacteria symbiosis.
The frequency with which similar phenotypic traits repeatedly arise during evolution (e.g, the camera eyes of cephalopods and vertebrates) suggests optimal and predictable solutions to common problems (e.g., visual acuity). Although convergent evolution has been studied with respect to particular candidate genes, no one previously examined the evolutionary history of all genes expressed in convergent traits. In this study, we've developed novel phylogenetic and quantitative approaches that allow us to report the first evidence that the evolution of convergent phenotypes is associated with the convergent expression of thousands of genes. More specifically, we demonstrated that specialized organs harboring luminous symbiotic bacteria have originated repeatedly during squid evolution and the show that global gene expression profiles underlying those organs are strikingly similar. We also developed a regression technique to model tissue transcriptomes, which allows us to show for the first time that the evolution of overall gene expression underlying traits may be predictable. Thus, we report the first evidence that congruent expression patterns of thousands of genes mirror the phenotypic evolution of a convergent trait. Gene expression is so similar that overall expression levels alone can predict organ identity, even in separately evolved traits of squid species separated by tens of millions of years. The striking similarity of expression of thousands of genes in distinct photophores indicates complex trait evolution may sometimes be more constrained and predictable than expected, either because of internal factors like a limited array of suitable genetic building blocks, or external factors, like natural selection favoring an optimum. This study leverages exciting advances in sequencing technology, cutting-edge genomic tools and an unorthodox non-model system in order to test a fascinating hypothesis concerning predictability in the evolution of a complex trait. These approaches and ensuing results have broad implications for workers in the fields of evolution, genetics, genomics/bioinformatics, symbiosis, invertebrate zoology, and evolutionary development. In particular, our results underscore the importance of evaluating whole expression profiles rather than candidate genes alone. We also discovered a number of new candidate genes putatively involved in light reception and innate immunity and animal-bacterial symbiosis, which have spawned new collaborations. The results of this project have lead to one submitted publication to date, an invited symposium at an international conference, and a thesis defense. Additional impact included mentoring of four STEM undergraduates from junior colleges and training of two high school students in molecular biology. Finally, in the course of processing and analyzing this massive dataset, we developed and published an online, open-access bioinformatics toolkit compatible with the Galaxy platform. These computational tools enable fast implementation of our workflows and ensure replicability and transparency of our data analysis.
