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
Breaking the nexus: more biomass in cereal grain. Grain yield is controlled by complex, regulated genetic networks or quantitative trait loci (QTLs) derived from natural variations in many crop plants. Yield is a product of the three major parameters: panicle number, grain number and grain size, trade-offs are commonly observed between grain number and size. There is evidence to suggest it is possible to improve grain size without altering overall biomass. With the genomic and genetic resource t ....Breaking the nexus: more biomass in cereal grain. Grain yield is controlled by complex, regulated genetic networks or quantitative trait loci (QTLs) derived from natural variations in many crop plants. Yield is a product of the three major parameters: panicle number, grain number and grain size, trade-offs are commonly observed between grain number and size. There is evidence to suggest it is possible to improve grain size without altering overall biomass. With the genomic and genetic resource tools at hand. This project will elucidate the genetic architecture of grain size, and manipulate the key loci to generate more biomass in the grain, minimising or eliminating the adverse impact on seed number. This will maximise harvestable yield without imposing increased demand for water and nutrients.Read moreRead less
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