Ancestral Sequence Reconstruction is a technique used to statistically infer the
most likely ancestor of a set of evolutionarily related sequences, but research which relies
solely on protein data has the disadvantage of sequence information being lost upon
translation of a protein from its gene transcript, due to the redundancy inherent in the
genetic code. In this project, the amino acid sequences, and separately the corresponding
codon sequences, of 184 homologous Acetylcholine receptor protein sequences were
aligned, and phylogenetic analysis and ancestral sequence reconstruction was performed
based on both alignments to infer several ancestral sequences representing important
milestones in the evolutionary history of the homologous protein family. To further
extract meaningful information from the nucleotide sequences, positive selection analysis
was performed on the codon alignment using the Mixed Effects Model of Evolution
method, which estimates and compares between the rates of synonymous and non-
synonymous mutations across the alignment to detect the occurrence of positive selection
events throughout their evolution. The Mixed Effects Model of Evolution can infer
positive selection across both sites and evolutionary branches in a sequence alignment,
thus highlighting residues along the evolutionary trajectory of the proteins which may
have been functionally important in their evolution. Positive selection analysis detected
positive selection at a multitude of sites and branches, and by mapping signatures at
which selection is strongest with changes in the trajectory of ancestral states, several
important sites were chosen as likely to be most valuable for future experimental testing.
The implications of this study on the benefits of conducting ancestral sequence
reconstruction with protein and codon sequences are discussed.
| Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/45780 |
| Date | 03 January 2024 |
| Creators | Tehfe, Ali |
| Contributors | daCosta, Corrie John Bayley |
| Publisher | Université d'Ottawa / University of Ottawa |
| Source Sets | Université d’Ottawa |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
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