Development of cloning technology for the Australian Pig Industry. Cloning has the potential to be the most efficient of the reproductive technologies developed for increasing genetic improvement in livestock. Currently up to 5% of cloned embryos develop to term in the pig. This is higher than that reported for cattle and sheep. Moreover the use of this technology in the pig does not appear not to result in the same sorts of problems and losses seen around the time of birth in these species ....Development of cloning technology for the Australian Pig Industry. Cloning has the potential to be the most efficient of the reproductive technologies developed for increasing genetic improvement in livestock. Currently up to 5% of cloned embryos develop to term in the pig. This is higher than that reported for cattle and sheep. Moreover the use of this technology in the pig does not appear not to result in the same sorts of problems and losses seen around the time of birth in these species i.e. the majority of cloned pigs appear normal and are healthy at birth. However before cloning can be used commercially, current efficiencies need to be increased approx two fold for this to be economically viable. The aim of the present study is to improve the efficiency of our current cloning protocol and develop associated technologies such as embryo freezing to facilitate commercialisation. This will ensure that the Australian Pig Industry remains competitive at a pivotal time in its development.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120100390
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Characterisation of collagenous lectins and their roles in ovine infectious diseases. Specific proteins involved in immunity against infections will be studied in sheep to enhance their immune response against specific infections, such as ovine Johne's disease and footrot. This may lead to selective breeding of sheep that are more resistant to disease, minimising production losses and use of medications.
Estimating genotype-environment interaction using genomic information. This project aims to develop statistical methods that can explore genotype–environment interaction at the genomic level using genome-wide single nucleotide polymorphisms or sequence data. It plans to estimate how the effects of genetic variants change with changing environmental conditions and how overall genetic variance changes due to changing effects in specific gene regions. It plans to deliver statistical models and meth ....Estimating genotype-environment interaction using genomic information. This project aims to develop statistical methods that can explore genotype–environment interaction at the genomic level using genome-wide single nucleotide polymorphisms or sequence data. It plans to estimate how the effects of genetic variants change with changing environmental conditions and how overall genetic variance changes due to changing effects in specific gene regions. It plans to deliver statistical models and methods and an efficient algorithm implemented in software, which would broadly benefit the field of complex trait genetics. Methods to estimate genotype–environment interaction effects at the genomic level would help elucidate complex biological systems, including human genetic response to changing environmental factors and the potential adaptation of animals to changing environmental conditions.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
Complex trait analyses based on genome-wide approaches. This project aims to develop whole genome approaches that can improve the estimation and prediction power by using information from the dynamic genetic architecture of complex traits (i.e. the changes of genetic characteristics and effects when varying effective population size and genetic backgrounds). The project intends to deliver advanced statistical models, efficient algorithms and design by combining data from close relatives, populat ....Complex trait analyses based on genome-wide approaches. This project aims to develop whole genome approaches that can improve the estimation and prediction power by using information from the dynamic genetic architecture of complex traits (i.e. the changes of genetic characteristics and effects when varying effective population size and genetic backgrounds). The project intends to deliver advanced statistical models, efficient algorithms and design by combining data from close relatives, population samples or from different populations (e.g. multi-ethnicities or multi-breeds). The expected outcome is to better understand the dynamic architecture of complex traits and develop methods with improved power, precision and accuracy in genomic analyses.Read moreRead less