ARC Centre of Excellence in Plant Cell Wall Biology. The ARC Centre for Plant Cell Wall Biology will define the regulatory mechanisms that control molecular, enzymic and cellular processes involved in the synthesis, deposition, re-modelling and depolymerisation of cell wall polysaccharides of cereals and grasses. Plant cell walls represent the world's largest renewable carbon resource, but the regulatory mechanisms responsible for their synthesis and assembly are not understood. Key distinguishi ....ARC Centre of Excellence in Plant Cell Wall Biology. The ARC Centre for Plant Cell Wall Biology will define the regulatory mechanisms that control molecular, enzymic and cellular processes involved in the synthesis, deposition, re-modelling and depolymerisation of cell wall polysaccharides of cereals and grasses. Plant cell walls represent the world's largest renewable carbon resource, but the regulatory mechanisms responsible for their synthesis and assembly are not understood. Key distinguishing features of the Centre will be the international, integrative, and multidisciplinary approach towards addressing major questions in plant biology, its strategy to leverage ARC funding, and its linkages with potential national and international end-users of the fundamental scientific discoveries.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