Improving the efficiency of CRISPR gene editing in cells. Human red blood cells are well-characterised and the globin gene locus is a model system for the study of gene regulation. Gene editing technologies and delivery tools are evolving rapidly and the globin gene locus is the perfect model for gene editing optimisation. This collaboration between UNSW Sydney and CSL aims to bring together our combined expertise and new technologies to develop an optimal platform for genetic modification in a ....Improving the efficiency of CRISPR gene editing in cells. Human red blood cells are well-characterised and the globin gene locus is a model system for the study of gene regulation. Gene editing technologies and delivery tools are evolving rapidly and the globin gene locus is the perfect model for gene editing optimisation. This collaboration between UNSW Sydney and CSL aims to bring together our combined expertise and new technologies to develop an optimal platform for genetic modification in a red blood cell line. Simultaneously, this project aims to generate fundamental insights into mechanisms of human gene regulation. The technological and biological outcomes of this project will be of benefit for future gene editing applications.Read moreRead less
Prediction of phenotype for multiple traits from multi-omic data. This project aims to develop better methods for predicting traits in an individual based on their genome sequence. This method will be tested in agricultural animals and plants and in humans. The prediction formula is derived from a training dataset that has information on the traits and genome sequence of a sample of individuals. The prediction formula can then be applied to predict the trait in individuals where the trait is un ....Prediction of phenotype for multiple traits from multi-omic data. This project aims to develop better methods for predicting traits in an individual based on their genome sequence. This method will be tested in agricultural animals and plants and in humans. The prediction formula is derived from a training dataset that has information on the traits and genome sequence of a sample of individuals. The prediction formula can then be applied to predict the trait in individuals where the trait is unknown. This is useful for selecting the best parents for breeding in agriculture and for predicting the future phenotype of animals, crops and people. The proposed method uses data on very many traits to identify sequence variants that have a function and to predict the traits affected by each variant.Read moreRead less