Browsing by Author "Kazemi Mehrabadi, Mobina"
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- ItemOpen AccessDetectability of Non-Equilibrium Molecular Evolution Caused by Fitness Shift and Drift(2022-05-17) Kazemi Mehrabadi, Mobina; de Koning, Jason; Long, Quan; Anderson, DavidOne of the key interests of computational molecular evolution is the inference of the strength and direction of natural selection in protein-coding genes. The non-synonymous to synonymous rate ratio (dN/dS) is widely used to evaluate the effect of natural selection on genes, lineages, and sites. When dN/dS is inferred to be greater than one along a particular branch and at a specific site, this is often taken as evidence of episodic positive selection and adaptive change in function. Despite the simplicity and widespread use of dN /dS approaches, they are funda- mentally unable to differentiate between fit and unfit states, and the stationary distributions in all widely-used approaches are (unrealistically) identical across sites. To address these short- comings, the mutation-selection framework, which is a class of codon substitution models that allows a mechanistic relationship between fitness and sequence has been proposed. Recently, due to developments in Markov-Chain Monte Carlo (MCMC) methods and penalized maximum likelihood approaches, computationally tractable models have been implemented that enable in- ference under site-heterogeneous mutation-selection models, though substantial computational barriers to using such methods on large datasets persist.Here, in my thesis, I introduce time-heterogeneous mutation-selection models as an ideal representation of how episodic adaptation occurs. Using these models, I study how true dN /dS changes over time following a wide variety of fitness shifts (when the fitness profile at a site is completely replaced with a new fitness profile) and fitness drift scenarios (when the fitness of the two most favorable states is swapped). Both simulation and direct (simulation-free) analysis are used to characterize non-equilibrium molecular evolution under time-heterogeneous mutation- selection models of codon substitution. Additionally, I evaluate the performance of existing branch-site type methods to distinguish fitness shift from a relaxation of constraints at a small number of sites. In general, I find that the more different the starting and ending fitness profiles are, the more reliably an adaptive burst is produced, which is potentially detectable using dN /dS approaches. Although all existing methods we considered in the simulation performed poorly and have very low power to detect fitness shifts, I find that covariate information that helps inform which sites might be targets of positive selection can rescue high power of dN/dS type methods to detect modest to strong fitness shifts.Our desire in this project has been to improve our understanding of non-equilibrium molecular evolution under mechanistic models of adaptive change in function and to illuminate how well relatively simple statistical approaches perform in inference tasks. I hope this body of work will broaden the horizon for more realistic, mechanistic, and tractable models of non-equilibrium molecular evolution.