Publication:
Modelling how genetic diversity interacts with other genes, and with species diversity

dc.contributor.advisor Sherwin, William en_US
dc.contributor.advisor Tanaka, Mark en_US
dc.contributor.advisor Murray, John en_US
dc.contributor.advisor Goldys, Beniamin en_US
dc.contributor.author Byrnes, Juliet en_US
dc.date.accessioned 2022-03-15T08:53:02Z
dc.date.available 2022-03-15T08:53:02Z
dc.date.issued 2021 en_US
dc.description.abstract This PhD thesis moves beyond conservation genetics/molecular ecology’s traditional consideration of genetic loci acting in isolation from other genetic loci, in a species that is acting in isolation from other species. I use modelling to explore these interactions, and produce some surprising results with implications for evolutionary biology and for conservation management. The first chapter presents a meta-analysis and simulations of recombination with epistatic selection – where a combination of alleles at different loci produces a fitness effect neither could produce alone. Epistasis is ubiquitous in nature, but difficult to detect. Additionally, mathematical models of recombination and epistatic interactions are typically intractable or contradictory. Consequently, epistatic interactions are often ignored. The main conclusion of the first chapter is that in Drosophila melanogaster, and in some models, lethal combinations of alleles at different loci tend to have a low recombination rate and thus break up less easily, though beneficial combinations show a different pattern. The second and third chapters use modelling to study correlations between species diversity and genetic diversity (SGDCs). If strong positive SGDCs are common, it may be possible to use one diversity measure in the place of another. Conversely, if strong negative SGDCs are common, conservation measures which target one diversity will negatively impact the other. There are theoretical arguments in support of positive and negative SGDCs, but little formal algebraic theory. Moreover, despite many SGDC studies, the results are equivocal. The second chapter shows that SGDCs which measure diversity using richness tend to be positive due to the construction of the SGDC as well as sampling bias but that assemblages with the same SGDCs can evolve very differently. Therefore, SGDCs may not be meaningful. However, many SGDC researchers use measures other than richness which weight rare variants differently from common ones. Therefore, the third chapter shows that the choice of weighting can seriously bias the interpretation of SGDC studies. In summary, this thesis lays the groundwork for a version of molecular ecology based upon a more thorough and accurate assessment of interactions of genes with one another, and with other species. en_US
dc.identifier.uri http://hdl.handle.net/1959.4/71174
dc.language English
dc.language.iso EN en_US
dc.publisher UNSW, Sydney en_US
dc.rights CC BY-NC-ND 3.0 en_US
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/3.0/au/ en_US
dc.subject.other Molecular ecology en_US
dc.subject.other Genetic diversity en_US
dc.subject.other Species diversity en_US
dc.subject.other Recombination en_US
dc.title Modelling how genetic diversity interacts with other genes, and with species diversity en_US
dc.type Thesis en_US
dcterms.accessRights open access
dcterms.rightsHolder Byrnes, Juliet
dspace.entity.type Publication en_US
unsw.accessRights.uri https://purl.org/coar/access_right/c_abf2
unsw.date.embargo 2023-10-25 en_US
unsw.description.embargoNote Embargoed until 2023-10-25
unsw.identifier.doi https://doi.org/10.26190/unsworks/2378
unsw.relation.faculty Science
unsw.relation.originalPublicationAffiliation Byrnes, Juliet, School of Biological, Earth & Environmental Sciences, Science, UNSW en_US
unsw.relation.originalPublicationAffiliation Sherwin, William, School of Biological, Earth & Environmental Sciences, Science, UNSW en_US
unsw.relation.originalPublicationAffiliation Tanaka, Mark, School of Biotechnology & Biomolecular Sciences, Science, UNSW en_US
unsw.relation.originalPublicationAffiliation Murray, John, School of Mathematics and Statistics, UNSW en_US
unsw.relation.originalPublicationAffiliation Goldys, Beniamin, School of Mathematics and Statistics, UNSW en_US
unsw.relation.school School of Biological, Earth & Environmental Sciences *
unsw.thesis.degreetype PhD Doctorate en_US
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