Date of Award

2023

Degree Type

Dissertation

Degree Name

Doctor of Philosophy in Biological and Environmental Sciences

First Advisor

Rachel Schwartz

Abstract

The remarkable biodiversity of the Earth fascinated natural scientists for centuries. Studying this biodiversity has been a major occupation of the life sciences because deciphering the underlying biological mechanisms of diversification provides fundamental knowledge for biological evolution. A significant body of evidence shows that today’s biodiversity originated from successive adaptive diversification periods (i.e.: evolutionary radiations) which are generally characterized by the rapid multiplication of lineages with a variety of adaptations and ecological roles. Some of the most well-known examples of evolutionary radiations include the striking wing pattern diversity of Heliconius butterflies, the great body form variety of Caribbean anole lizards, or the evolution of diverse beak phenotypes of Darwin’s finches in response to biotic and abiotic environmental conditions. Although these examples can be generalized as evolutionary radiations, the tempo and the mode of their diversification process across different taxa can vary greatly. Over the years, many theoretical and empirical approaches have been utilized to study this phenomenon including fossil records, lab studies, and phylogenetic methods. Phylogenetics is particularly found to be useful in studying species diversification processes because it provides significant information on past speciation and extinction events. Especially after the introduction of high-throughput-sequencing technologies, molecular phylogenetics methods revitalized systematic biology by allowing researchers to utilize extensive datasets to answer some of the long-standing challenging questions. However, using large amounts of molecular data also introduced new practical and theoretical challenges such as inconveniences in large data processing practices, computational complexity, and differing evolutionary histories of different genomic data types (e.g.: coding, non-coding, regulator, etc.) which frequently result in significant conflicts across findings. These conflicts often result in significant differences in biological conclusions for the taxa of interest. Therefore, there has been an ever-increasing need to develop and improve tools to utilize large amounts of molecular data efficiently. This is only possible by thoroughly investigating and understanding the relationship between the molecular data and the downstream phylogenetic diversification analyses. In this study, we aimed to investigate the relationship between the data and phylogenetic diversification analyses by using Aves (birds) radiation as an empirical case because birds are amongst the most well-studied organisms in phylogenetic research. Evidence decisively showed that birds underwent a rapid evolutionary diversification process right after the Cretaceous-Paleogene (K-Pg) extinction around ~65 MA years ago. However, there are still uncertainties around the relationship of some major bird orders due to this rapid evolutionary diversification of lineages, and this constitutes a useful case for studying the relationship between data and the phylogenetic analyses. In our study, we investigated the extent to which genomic data carry more phylogenetic information about past diversification patterns of birds and how this can be utilized to improve the phylogenetic diversification estimates and our understanding of underlying mechanisms of evolutionary diversification processes. We employed previously published whole-genome data from major bird orders and created novel sets of phylogenetic data from different regions of the genomes (coding, non-coding, regulatory). Overall, our results showed that regardless of the type, birds genomes contain insufficient levels of phylogenetic information to resolve controversial relationships in the bird phylogeny due to its rapid diversification history.

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Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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