An investigation into the evolution of hierarchy and its consequences for evolvability
An investigation into the evolution of hierarchy and its consequences for evolvability
This thesis is concerned with the evolution of hierarchical modules in a model of gene regulation, and the consequences thereof for evolvability. Developmental processes map genotypes to phenotypes, and translate random variation at the genetic level into biased, selectable variation at the phenotypic level. These developmental processes are themselves subject to evolution by natural selection and it might be the case that natural selection favours developmental architectures that facilitate phenotypic variation that is adaptive and enhances evolvability. One manner of developmental organisation that has inspired much interest is modular hierarchy. Such hierarchy - where one gene directs many others - has the potential to be very important to evolvability because it effectively rescales the variability of phenotypes, enabling natural selection to search combinations of modules rather than combinations of individual genes. However, the conditions where natural selection favours hierarchical organisation and the conditions where its consequences enable such rescaling are not well understood. Considering a developmental model based on a recurrent regulatory process, we describe conditions where natural selection favours the evolution of single-layer hierarchical modular structures, where independent ‘switch’ genes direct independent subsets of genes. We show that these structures increase evolvability by rescaling the genetic neighbourhood of phenotypes, from combinations of genes to combinations of modules, and that this makes high-fitness phenotypes more accessible to natural selection. This improved evolvability enables a micro-evolutionary process to better exploit a changing or static modular environment so long as sufficient long-term variation is maintained. We then investigate the underlying cause of the evolution of hierarchy. Interestingly, we find that the observable increase in evolvability (in particular, the ability to rescale the variability of phenotypes) is not required for natural selection to favour hierarchy in this model. Rather, hierarchy evolves due to a selective pressure for efficient phenotypic expression and because it is an efficient organisation for increasing the expression of many genes given limited regulatory connections. Thereby, we show that - in some cases - the causes and consequences of developmental hierarchy are not the same. That is, hierarchy evolves - and it increases evolvabilty - but increased evolvability need not be the reason it was favoured by selection.
University of Southampton
Nash, Frederick, James
063327dc-829e-4abf-a47d-71e9ff2a9b00
June 2022
Nash, Frederick, James
063327dc-829e-4abf-a47d-71e9ff2a9b00
Watson, Richard
ce199dfc-d5d4-4edf-bd7b-f9e224c96c75
Nash, Frederick, James
(2022)
An investigation into the evolution of hierarchy and its consequences for evolvability.
University of Southampton, Doctoral Thesis, 141pp.
Record type:
Thesis
(Doctoral)
Abstract
This thesis is concerned with the evolution of hierarchical modules in a model of gene regulation, and the consequences thereof for evolvability. Developmental processes map genotypes to phenotypes, and translate random variation at the genetic level into biased, selectable variation at the phenotypic level. These developmental processes are themselves subject to evolution by natural selection and it might be the case that natural selection favours developmental architectures that facilitate phenotypic variation that is adaptive and enhances evolvability. One manner of developmental organisation that has inspired much interest is modular hierarchy. Such hierarchy - where one gene directs many others - has the potential to be very important to evolvability because it effectively rescales the variability of phenotypes, enabling natural selection to search combinations of modules rather than combinations of individual genes. However, the conditions where natural selection favours hierarchical organisation and the conditions where its consequences enable such rescaling are not well understood. Considering a developmental model based on a recurrent regulatory process, we describe conditions where natural selection favours the evolution of single-layer hierarchical modular structures, where independent ‘switch’ genes direct independent subsets of genes. We show that these structures increase evolvability by rescaling the genetic neighbourhood of phenotypes, from combinations of genes to combinations of modules, and that this makes high-fitness phenotypes more accessible to natural selection. This improved evolvability enables a micro-evolutionary process to better exploit a changing or static modular environment so long as sufficient long-term variation is maintained. We then investigate the underlying cause of the evolution of hierarchy. Interestingly, we find that the observable increase in evolvability (in particular, the ability to rescale the variability of phenotypes) is not required for natural selection to favour hierarchy in this model. Rather, hierarchy evolves due to a selective pressure for efficient phenotypic expression and because it is an efficient organisation for increasing the expression of many genes given limited regulatory connections. Thereby, we show that - in some cases - the causes and consequences of developmental hierarchy are not the same. That is, hierarchy evolves - and it increases evolvabilty - but increased evolvability need not be the reason it was favoured by selection.
Text
F. Nash Final Thesis
- Version of Record
Text
Permission to deposit thesis
- Version of Record
Restricted to Repository staff only
More information
Published date: June 2022
Identifiers
Local EPrints ID: 467522
URI: http://eprints.soton.ac.uk/id/eprint/467522
PURE UUID: e93446e3-0e00-4603-a307-e127acdf5402
Catalogue record
Date deposited: 12 Jul 2022 16:37
Last modified: 17 Mar 2024 03:00
Export record
Contributors
Author:
Frederick, James Nash
Thesis advisor:
Richard Watson
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics