Discovery Early Career Researcher Award - Grant ID: DE200100425
Funder
Australian Research Council
Funding Amount
$409,364.00
Summary
Genetic and Molecular Consequences of Non-Random Mating in Humans. This project aims to develop and apply novel statistical methods to quantify the effects on a large number of complex traits of two forms of non-random mating in humans, that is inbreeding and assortative mating. The innovation in this proposal lies in integrating multi-level phenotypes with next-generation sequencing data collected in more than half a million study participants. Expected outcomes of this research include advance ....Genetic and Molecular Consequences of Non-Random Mating in Humans. This project aims to develop and apply novel statistical methods to quantify the effects on a large number of complex traits of two forms of non-random mating in humans, that is inbreeding and assortative mating. The innovation in this proposal lies in integrating multi-level phenotypes with next-generation sequencing data collected in more than half a million study participants. Expected outcomes of this research include advanced analytical methods to perform this integration and dissection of the biological consequences of non-random mating in humans at an unprecedented phenotypically detailed scale. The benefit of this project will be to identify new drivers of mate choice that can contribute to economic, health and social inequalities. Read moreRead less
Genomic Control of Human Complex Trait Variation. This project aims to address knowledge gaps in our understanding of the genetic and environmental control of complex human trait variation. This project will use innovative approaches that combine molecular genomic information with data from large biobank sized cohorts to generate new knowledge of the mechanisms underlying ancestral and sex differences in humans. Expected outcomes include the development of novel methods for the integrative analy ....Genomic Control of Human Complex Trait Variation. This project aims to address knowledge gaps in our understanding of the genetic and environmental control of complex human trait variation. This project will use innovative approaches that combine molecular genomic information with data from large biobank sized cohorts to generate new knowledge of the mechanisms underlying ancestral and sex differences in humans. Expected outcomes include the development of novel methods for the integrative analysis of genomic data and building Australia’s capacity in a highly demanded field, ensuring the capability to realise the translation of this knowledge to positively impact society and human well-being.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE130100614
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Novel statistical algorithms and methods to quantify and partition pleiotropy between complex traits in populations. A fundamental question in biology is how common genetic effects are shared between traits or groups. For example, is cognition or human behaviour genetically identical across genders or across human population groups? This project will address these questions using multiple independent genome-wide association studies.
Phenotypic profiling from DNA using genetic and epigenetic information. The project intends to quantify how much information about a person can be inferred from a DNA sample. A DNA sample contains epigenomic information additional to the genome sequence. This information can reflect age and the past and present lifestyle of the individual whose sample it is. The project aims to quantify the accuracy of lifestyle and phenotypic prediction from DNA. Existing genome-wide genotype and methylation ar ....Phenotypic profiling from DNA using genetic and epigenetic information. The project intends to quantify how much information about a person can be inferred from a DNA sample. A DNA sample contains epigenomic information additional to the genome sequence. This information can reflect age and the past and present lifestyle of the individual whose sample it is. The project aims to quantify the accuracy of lifestyle and phenotypic prediction from DNA. Existing genome-wide genotype and methylation array data from thousands of blood samples from human subjects will be statistically analysed to develop and validate predictors for chronological age, smoking, caffeine use, pesticide exposure, diet and body mass index. Potential applications of epigenomic prediction are widespread, ranging from forensics to ecology.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL180100072
Funder
Australian Research Council
Funding Amount
$3,460,832.00
Summary
Causes and consequence of human trait variation. This project aims to exploit the availability of Big Data from the genomics revolution to understand the relationship between the genome, the environment and complex human traits. New statistical methods and user-friendly software tools will be developed and applied to datasets on millions of individuals to generate new knowledge on human life history variation and healthy ageing. This project will position Australia to benefit from rapid advances ....Causes and consequence of human trait variation. This project aims to exploit the availability of Big Data from the genomics revolution to understand the relationship between the genome, the environment and complex human traits. New statistical methods and user-friendly software tools will be developed and applied to datasets on millions of individuals to generate new knowledge on human life history variation and healthy ageing. This project will position Australia to benefit from rapid advances in genomic technologies, to build and sustain critical capacity in statistical genetics, and better understand the causes and consequence of individual differences in human traits from genetic and environmental factors across the entire human lifespan.Read moreRead less
TraitCapture: Genomic modelling for plant phenomics under environmental stress. This project aims to develop software to integrate new hyper-spectral and 3D growth models of plant phenomics with population genomics to identify heritable developmental traits across varied environments. Genome wide association studies aim to then be used to identify causal genes. Functional structural plant models incorporating genetic variation will be used to predict growth under simulated stress environments. ....TraitCapture: Genomic modelling for plant phenomics under environmental stress. This project aims to develop software to integrate new hyper-spectral and 3D growth models of plant phenomics with population genomics to identify heritable developmental traits across varied environments. Genome wide association studies aim to then be used to identify causal genes. Functional structural plant models incorporating genetic variation will be used to predict growth under simulated stress environments. The research team unites international industry, the Australian Plant Phenomics Facility, and university statistical geneticists. TraitCapture software will use open standards applicable to both controlled and field environments enabling plant breeders to pre-select adaptive traits to increase crop productivity under environmental stress.Read moreRead less
Establishing novel breeding methods for canola improvement. It is imperative to ensure reliable food production in the coming years of climate change and increasing population. Genomics offers the greatest potential to increase food production. This project will apply genomic selection methods to accelerate canola oilseed breeding to ensure continued increases in production of this important food and national export.
Fertility crisis: harnessing the genomic tension behind pollen fertility in sorghum. Hybrid sorghum varieties yield more grain than inbred varieties but the production seed for farmers can be difficult. This project will identify the genes responsible for a trait that makes hybrid seed production possible and this knowledge will help raise sorghum yields in Australian and in some of the world’s poorest countries.