The Genomic Signal of Mass Extinction: Using Molecular Clocks to Study Recovery from the Cretaceous-Paleogene (K-Pg) Extinction

Is evolution primarily driven by the slow and steady action of everyday processes or do rare, extreme events play an important, even central role in driving evolution? Evidence from palaeontology and geochemistry suggests that the history of life has been shaped by mass extinctions- severe, global and rapid environmental changes that saw the rapid disappearance of 75% or more of all species on Earth. The best documented mass extinction is the Cretaceous-Paleogene (K-Pg) mass extinction 66 million years ago, when the Chicxulub asteroid impact drove not only the disappearance of the dinosaurs, but devastating extinctions among mammals (1), birds (2), lizards, and snakes (3).

Yet mass extinctions not only destroy diversity, but create it by opening up new niches, driving the rapid evolution and diversification of survivor species. Striking examples include the rapid evolution of mammals (1) birds (2) crocodylians (4) and lizards (3,5) in the aftermath of the K-Pg extinction. Particularly for mammals and birds, modern diversity is largely the result of rapid adaptive radiation following the K-Pg extinction. For many animals and plants, however, the effects of the K-Pg extinction on their diversification remains unknown due to the limitations of the fossil record. Yet we have another record of their evolution- the DNA of living species, which can be used to reconstruct their evolutionary history.

Following speciation, the DNA sequences of two species will become more and more different as they accumulate mutations. If we can model the rate at which their sequences change, we can use the difference between the sequences to determine when they split apart. This concept- the molecular clock- can be used to test the hypothesis that the Chicxulub impact and the K-Pg extinction drove diversification for a wide range of organisms- frogs and salamanders, butterflies and ants, grasses and daisies.

Using gene sequence data from the GenBank repository, we will generate molecular phylogenies, then use fossils to calibrate timetrees, testing whether the post-extinction interval from 66-55 Myr is associated with the origins of modern animal and plant diversity. Several developments- including (i) new Bayesian relaxed-clock models, (ii) a new calibration framework, and (iii) rigorous application of fossil calibrations- make this possible for the first time. In addition, we will also examine extinction biogeography- the hypothesis that post-extinction intervals are associated with elevated rates of dispersal, as the elimination of competitors and predators allows survivors to expand their ranges. This project will focus on a wide range of groups, including amphibians, teleosts, sharks, bivalves, and insects. The project is expected to produce significant papers to be published in international journals.

Our lab focuses on using the fossil record to study major evolutionary transitions, including the evolution of organisms and the evolution of new ecosystems. Current projects in the lab include the mass extinction of pterosaurs at the K-Pg boundary, and the radiation and biogeography of crocodilians and lizards in the early Cenozoic. The paleontology group at Bath is growing, with two faculty (Dr. Nick Longrich and Professor Matt Wills) being joined by a third member (Dr. Daniel Field) in early 2017, and we are part of the new Milner Centre for Evolution, a research centre focused on doing groundbreaking research focusing on major questions in evolutionary biology.

As part of our lab, the student will develop experience in molecular phylogenies, timetrees, and the use of phylogenies to infer evolutionary patterns. The student is expected to be able to work independently and collaboratively. Prior experience in paleontology and evolutionary biology are not necessary, but both research experience and a strong background in computers and computational approaches to research are required; experience with programs such as BEAST, MrBayes, and alignment is desirable.

Professor Davide Pisani of the University of Bristol will provide additional supervision for the project.