Beyond pineal melatonin: sensing the seasons without the eye. The project will identify the causal connection between seasonal breeding in animals and a recently recognised brain biochemical pathway by applying experimental treatments mimicking seasonal environmental changes in a mutant and wild-type nematode worm model. Through experimentation we will identify useful biological targets that might be manipulated to enhance control of seasonal breeding in managed animals. With better control of r ....Beyond pineal melatonin: sensing the seasons without the eye. The project will identify the causal connection between seasonal breeding in animals and a recently recognised brain biochemical pathway by applying experimental treatments mimicking seasonal environmental changes in a mutant and wild-type nematode worm model. Through experimentation we will identify useful biological targets that might be manipulated to enhance control of seasonal breeding in managed animals. With better control of reproductive output in animals, farmers and managers can increase and/or decrease reproductive output as needed in managed species including livestock and vertebrate pests. This will enhance the use of precious land resources and minimize ecological damage from overbreeding.Read moreRead less
Who’s who in the plant gene world? As many more plant genomes are sequenced, the bottleneck is being able to interrogate and translate this data into applications for crop improvement. This project will develop and apply a population graph database, hosting genome data for the world’s major crops and their wild relatives, allowing the characterisation of gene diversity on an unparalleled scale. Analysis of this data will reveal the presence/absence and sequence diversity for classes of genes for ....Who’s who in the plant gene world? As many more plant genomes are sequenced, the bottleneck is being able to interrogate and translate this data into applications for crop improvement. This project will develop and apply a population graph database, hosting genome data for the world’s major crops and their wild relatives, allowing the characterisation of gene diversity on an unparalleled scale. Analysis of this data will reveal the presence/absence and sequence diversity for classes of genes for important agronomic traits including disease resistance, flowering time and legume nitrogen fixation which will enable plant breeders to identify and apply novel genes and allelic variants for use in breeding programmes, accelerating the production of improved crop varieties.Read moreRead less
The genomics of climate adaptation in eucalypts. This project aims to investigate validated, rapid and pragmatic solutions to managing plant and animal maladaptation caused by global environmental change. Using Australia’s iconic blue gum (Eucalyptus globulus), this project will test strategies for identifying the major climatic predictors of, and key genomic regions that underlie, adaptation to climate change. By integrating climate variables and genome sequences with field trial-derived trait ....The genomics of climate adaptation in eucalypts. This project aims to investigate validated, rapid and pragmatic solutions to managing plant and animal maladaptation caused by global environmental change. Using Australia’s iconic blue gum (Eucalyptus globulus), this project will test strategies for identifying the major climatic predictors of, and key genomic regions that underlie, adaptation to climate change. By integrating climate variables and genome sequences with field trial-derived trait and performance data from decades of research and thousands of trees, we will develop validated DNA-based tools for monitoring the rate of adaptation in our native forests and identifying climate-ready seed sources for environmental and industrial plantings.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
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