School of BioSciences - Theses
Permanent URI for this collection
Search Results
1 - 1 of 1
-
ItemGenomically informed gene drive modelling( 2022)CRISPR/Cas gene drives are a focus of genetic biocontrol for pest species. They have the potential to radically affect pest species, by making them more manageable or by eradicating them. However, it is not yet fully understood how the elements of a gene drive interact to guide the progression of a gene drive. We explored how we can design gene drives that are safer, either by being temporally limiting or spatially limiting, through a modelling framework. Our modelling included a range of variables, with the addition of genomic information to infer the homing efficiency of the gene drive. We showed that there was no single variable that differentiated between the outcomes of a gene drive. Granted some variables were more influential in determining the outcome than others. The degree of dominance of the selection coefficient was shown to be strongly influential on the equilibrium outcome. While the interaction between conversion efficiency and resistance was shown to strongly influence the Temporary outcome. Furthermore, we showed that internal dynamics of a gene drive can be regulated by the variables of the gene drive. This provided insight into where effort should be directed in gene drive design to achieve the intended outcome of a gene drive, as well as controlling the progression to that outcome. The inclusion of genomic data in CRISPR gene drive modelling allowed for localisation of the gene drive due to genetic variation alone. Finding loci in the genome where there were allele frequencies differences allowed us to model gene drives that were highly efficient in the target population and poorly efficient in off-target populations. This conversion efficiency differential allowed for sustained gene drive localisation in spite of migration and selection. Population suppression was explored in our modelling to better understand how we could create sustained localised suppression. We showed sustained population suppression was possible through incomplete distortion of the sex ratio of the progeny. A deterministic gene drive model was developed to solve for equilibrium points for a range of migration rates and selection coefficients. These equilibria can be used as thresholds for gene drive design and monitoring. This work aims to further develop our understanding of how gene drives are likely to progress when released. We focussed on characterising which aspects of a gene drive were most important in determining both their progression and outcome. The inclusion of genetic information in our modelling revealed a new avenue that can be exploited to achieve gene drive localisation. This modelling work will aid in the design process of gene drives to increase our confidence that gene drives will work as intended.