Development of genetic technology for rodent population suppression. Vertebrate pests cost Australia over $1 billion each year in agricultural losses and environmental damage and novel strategies are urgently required to tackle this massive challenge. Newly proposed “gene drives”, which might rapidly spread through populations, have enormous potential for the sustained management and even eradication of pests. Through innovative application of cutting-edge genome editing approaches, this proposa ....Development of genetic technology for rodent population suppression. Vertebrate pests cost Australia over $1 billion each year in agricultural losses and environmental damage and novel strategies are urgently required to tackle this massive challenge. Newly proposed “gene drives”, which might rapidly spread through populations, have enormous potential for the sustained management and even eradication of pests. Through innovative application of cutting-edge genome editing approaches, this proposal aims to develop gene drive technology in mice as a prototypical vertebrate pest species. We will also develop cutting-edge mathematical models of rodent gene drives to identify crucial parameters for efficacious employment and investigate potential for impact on non-target populations.Read moreRead less
Whole-genome multivariate reaction norm model for complex traits. This project aims to develop a multivariate whole-genome genotype-covariate correlation and interaction model that can be applied to a wide range of existing genome-wide association study (GWAS) datasets. Genotype-covariate correlation and interaction (GCCI) are fundamental in biology but there is no standard approach to disentangle interaction from correlation in the whole-genome analyses. This project will address the key featur ....Whole-genome multivariate reaction norm model for complex traits. This project aims to develop a multivariate whole-genome genotype-covariate correlation and interaction model that can be applied to a wide range of existing genome-wide association study (GWAS) datasets. Genotype-covariate correlation and interaction (GCCI) are fundamental in biology but there is no standard approach to disentangle interaction from correlation in the whole-genome analyses. This project will address the key feature in biology, which relates to dissecting the complex mechanism of association and interaction. The proposed statistical model implemented in a context of a novel design based on multiple GWAS data sets is a paradigm shifting-tool with applications to multiple industries.Read moreRead less