PH.D. Defense: Sumaira Zaman

Title: New Approaches for Investigating Gene and Subgene Evolution and Inferring Viral Recombination   

Student: Sumaira Zaman

Major Advisor: Dr. Mukul Bansal

Associate Advisors: Dr. Ion Mandoiu, Dr. Sheida Nabavi

Date/Time: Thursday, April 6th, 2023, 1:00 pm

Location: HBL 1102 

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Abstract:

Existing computational approaches for studying gene family evolution generally assume that any relevant evolutionary events, such as gene duplication, gene loss, horizontal gene transfer, and sequence rearrangement, affect entire genes rather than parts of genes. However, it is well-understood that these events can occur at the subgene level. When present, such subgene level events, unless explicitly accounted for, can significantly affect even the most fundamental computational steps in the study of gene family evolution such as computing multiple sequence alignments and reconstructing gene trees. In this dissertation, we focus on systematically assessing the impact of two important subgene evolutionary events, partial gene transfer (PGT) and protein domain rearrangement, on the study of gene family evolution and on developing new algorithms for their improved handling. In addition, motivated by the COVID-19 pandemic, we propose a new computational protocol, called virDTL, for studying recombination in viruses.

As our first contribution, we systematically assess the impact of PGT on gene tree reconstruction in microbial gene families and develop a new computational approach, called trippd, to reliably identify gene families that have not been significantly affected by PGT. For our second contribution, we continue investigating sub-gene evolution in the form of domain shuffling in eukaryotes. We assess the impact of protein domain gain, loss, and rearrangement on traditional multiple sequence alignment and develop new computational approaches for mitigating the impact of such domain-level events on multiple sequence alignment and subsequent gene tree reconstruction. As our final contribution, we develop a new computational protocol, virDTL, that leverages the strengths of existing phylogenetic reconciliation algorithms used to study gene family evolution in microbes, while accounting for multiple sources of inference error and uncertainty, to infer recombination in viruses. We use virDTL to study the recombination history of Sarbecoviruses and shed light on the evolution of SARS-CoV-2.