Integrating morphology, fossils and molecules to evaluate major evolutionary events

Lead Research Organisation: University of Manchester
Department Name: Earth Atmospheric and Env Sciences

Abstract

Recent advances have provided a wealth of molecular data with which to build phylogenies and study evolutionary processes. Morphology, however, remains fundamental for reconstructing how organisms have changed and evolved through time. Indeed, it is usually the only kind of data yielded by fossils. However, a large gap exists between genomic and phenomic data limiting our ability to use either to evaluate evolutionary hypotheses. For example, which aspects of morphology are in accordance with molecular data and can be used to reliably reconstruct major evolutionary events? Do genetic innovations such as gene and genome duplication events match morphological innovation, integration or radiation? This project aims to address these outstanding questions by collating and integrating genetic, morphological, and morphometric datasets from across the tree of life. The combined datasets will not only provide a tool kit with which to better reconstruct morphological phylogenies but also to better evaluate the nature and tempo of evolutionary processes.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
BB/M011208/1 01/10/2015 31/03/2024
1618732 Studentship BB/M011208/1 01/10/2015 31/12/2019
 
Description I have found that osteological morphological data in birds and reptiles are better at reconstructing evolutionary history as compared with soft characters such as plumage and scales. I found this by comparing the fit of these tho different data types against trees constructed with DNA data, a generally quite reliable form of data for building evolutionary trees. This is good for palaeontologists as they mostly deal with osteological data. I have also found that transitions in soft characters from one state to another typically occur younger on an evolutionary tree than hard characters, possible demonstrating faster evolutionary rates of these character types. This may have implication for different character types resolving at different levels of an evolutionary tree. Additionally, I have found that morphological data are more correlated within than between these partitions. Characters showing higher internal correlation additionally tend to share similar fit on molecular trees. I extended all these analyses to mammals, comparing dental and osteological data, similarly finding osteological data to be more consistent with molecular data, and that both data types are more correlated within than between partitions.
Exploitation Route Findings so far show that palaeontologists can be reasonably confident in their findings when placing fossil species in evolutionary trees, as compared with if they used soft characters. Additionally, differences between data types can be used to inform model based methods of phylogenetic inference. My work also sheds light on the nature and mode of phenotypic evolution.
Sectors Other