Industrial Transformation Training Centres - Grant ID: IC220100035
Funder
Australian Research Council
Funding Amount
$4,958,927.00
Summary
ARC Training Centre for Hyphenated Analytical Separation Technologies . The toughest analytical science challenges typically require advanced analytical technologies to acquire the desired solutions. In the field of separation science this inevitably involves hyphenated separation technologies, specifically the combination of chromatography and mass spectrometry. Advancing this technology to its full capability requires the collaborative strength of academic, industry and end-user partnerships, ....ARC Training Centre for Hyphenated Analytical Separation Technologies . The toughest analytical science challenges typically require advanced analytical technologies to acquire the desired solutions. In the field of separation science this inevitably involves hyphenated separation technologies, specifically the combination of chromatography and mass spectrometry. Advancing this technology to its full capability requires the collaborative strength of academic, industry and end-user partnerships, providing the materials and inspiration for young researchers to apply novel hyphenated methods to complex environmental and industrial systems. This Centre will deliver fundamental developments in hyphenated technologies, new analytical capability, and applied outcomes across multiple end-user groups and interests. Read moreRead less
Mid-Career Industry Fellowships - Grant ID: IM230100154
Funder
Australian Research Council
Funding Amount
$1,049,904.00
Summary
Fungi Power: Designer Fungal Cell Factories for Advanced Biomanufacturing. This project aims to build an advanced biomanufacturing platform based on filamentous fungi in collaboration with industry. Using synthetic biology, the project expects to engineer superior fungal host strains customisable to the needs of the industry and to address their technological gaps. The expected outcomes include the development of cost-efficient and sustainable fungal-based bioprocesses for the companies to produ ....Fungi Power: Designer Fungal Cell Factories for Advanced Biomanufacturing. This project aims to build an advanced biomanufacturing platform based on filamentous fungi in collaboration with industry. Using synthetic biology, the project expects to engineer superior fungal host strains customisable to the needs of the industry and to address their technological gaps. The expected outcomes include the development of cost-efficient and sustainable fungal-based bioprocesses for the companies to produce products, such as fine chemicals, pharmaceutical actives and food ingredients. The project would provide significant benefits by enabling existing and emerging companies' commercial successes and competitiveness in global markets, creating new jobs and resulting in the growth of the bio-economy in Australia.Read moreRead less
Estimation of non-additive genetic variance for complex traits using genome-wide single nucleotide polymorphyisms and sequence data. Finding genes for traits of importance in agriculture, ecology and human health depends on understanding the genetic basis of these traits. This project will investigate whether variation in traits in humans, cattle and wild sheep are influenced by gene-gene interactions.
The genetic architecture and evolution of quantitative traits. Most important traits are controlled by many genes and by the environment, however there is little knowledge of how many genes are involved in these complex traits and what their effects are. This project will describe the number of genes and their effects for complex traits in humans and livestock and explain how these genes evolve.
Genetic architecture and evolution of complex traits across populations. Most human traits have a genetic component and display substantial diversity within and among populations. How natural selection changes and maintains genetic variation in human traits is a long-standing question in evolution that the proposed project aims to answer. Using innovative statistical methods and largest genomic “big” datasets ever across populations of different ancestral backgrounds, this project expects to gen ....Genetic architecture and evolution of complex traits across populations. Most human traits have a genetic component and display substantial diversity within and among populations. How natural selection changes and maintains genetic variation in human traits is a long-standing question in evolution that the proposed project aims to answer. Using innovative statistical methods and largest genomic “big” datasets ever across populations of different ancestral backgrounds, this project expects to generate new knowledge on the roles of natural selection in shaping the genetic variation in traits and identify key factors that drive the differentiation of human populations. These outcomes will significantly improve our understanding on the evolution of human traits and adaptation of populations to changing environments.Read moreRead less
Exposing the complex and flexible genetic basis to polygenic adaptation: integrating population and quantitative genomic approaches. Using leading-edge genomic approaches, the project will dissect the genetic basis to adaptation across an entire species range. The results will highlight the complex nature of adaptation to environmental change and will deliver new approaches to study it in natural populations.
The extent, causes and implications of pleiotropy among complex traits. The project seeks to understand how a DNA mutation can affect many characters or traits. Many traits are called complex because they are controlled by a very large number of genes, most of which have small effects. Complex traits include traits important in medicine (such as susceptibility to heart disease) and in agriculture (such as tenderness of meat). Because there are many genes affecting each trait, most genes have sma ....The extent, causes and implications of pleiotropy among complex traits. The project seeks to understand how a DNA mutation can affect many characters or traits. Many traits are called complex because they are controlled by a very large number of genes, most of which have small effects. Complex traits include traits important in medicine (such as susceptibility to heart disease) and in agriculture (such as tenderness of meat). Because there are many genes affecting each trait, most genes have small effects which makes them hard to identify. The fact that a mutation that has a small effect on a complex trait also has a larger effect on a less complex trait may help us to identify the mutation and use it in agriculture or medicine.Read moreRead less
Identification of causal variants for complex traits. The aim of this project is to identify causal variants for complex traits in cattle and humans. Although most important traits in agriculture, medicine and evolution are complex traits, very few of the genetic variants affecting these traits are known and this undermines our understanding of how genetic variants affect a trait and practical uses of this knowledge. Huge datasets of individuals with genome sequence and phenotypes and new statis ....Identification of causal variants for complex traits. The aim of this project is to identify causal variants for complex traits in cattle and humans. Although most important traits in agriculture, medicine and evolution are complex traits, very few of the genetic variants affecting these traits are known and this undermines our understanding of how genetic variants affect a trait and practical uses of this knowledge. Huge datasets of individuals with genome sequence and phenotypes and new statistical methods provide the opportunity to close this gap. The outcome will be identification of many genomic variants causing variation in complex traits. This will benefit scientific understanding of complex traits and the ability to predict traits for individuals from their genome sequence.Read moreRead less
The role of X-chromosome inactivation in quantitative trait variation. This project aims to develop methods and software that can be applied to genetic and genomic studies in animal breeding, wildlife protection, and humans. X-chromosome inactivation (XCI) is an important biological phenomenon but its effect on quantitative trait variation remains largely unknown. This project aims to develop novel statistical methods to estimate the X-linked genetic variance and the proportion that escapes XCI, ....The role of X-chromosome inactivation in quantitative trait variation. This project aims to develop methods and software that can be applied to genetic and genomic studies in animal breeding, wildlife protection, and humans. X-chromosome inactivation (XCI) is an important biological phenomenon but its effect on quantitative trait variation remains largely unknown. This project aims to develop novel statistical methods to estimate the X-linked genetic variance and the proportion that escapes XCI, and identify trait-associated genetic variants affected and not affected by XCI. The methods would then be applied to large datasets from genome-wide association studies for a large number of traits. Project outcomes may enable us to better understand the role of XCI in quantitative trait variation and gene expression in humans and animals.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