Methods to infer dense genomic information from sparsely genotyped populations. Prediction of phenotype based on DNA polymorphisms or sequence has important applications such as prediction of disease risk in human medicine and prediction of genetic value in plant or animal breeding. This project will enhance precision and lower the cost of association studies leading to substantial increase in accuracy of such predictions. This will allow more effective genetic improvement, particularly of diff ....Methods to infer dense genomic information from sparsely genotyped populations. Prediction of phenotype based on DNA polymorphisms or sequence has important applications such as prediction of disease risk in human medicine and prediction of genetic value in plant or animal breeding. This project will enhance precision and lower the cost of association studies leading to substantial increase in accuracy of such predictions. This will allow more effective genetic improvement, particularly of difficult but important traits such as disease resistance, reduced green-house gas emissions and product quality. The same methods can be extended to improve genetic improvement in plants and better prediction of human disease risk. 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.
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
Complex trait analyses based on genome-wide approaches. This project aims to develop whole genome approaches that can improve the estimation and prediction power by using information from the dynamic genetic architecture of complex traits (i.e. the changes of genetic characteristics and effects when varying effective population size and genetic backgrounds). The project intends to deliver advanced statistical models, efficient algorithms and design by combining data from close relatives, populat ....Complex trait analyses based on genome-wide approaches. This project aims to develop whole genome approaches that can improve the estimation and prediction power by using information from the dynamic genetic architecture of complex traits (i.e. the changes of genetic characteristics and effects when varying effective population size and genetic backgrounds). The project intends to deliver advanced statistical models, efficient algorithms and design by combining data from close relatives, population samples or from different populations (e.g. multi-ethnicities or multi-breeds). The expected outcome is to better understand the dynamic architecture of complex traits and develop methods with improved power, precision and accuracy in genomic analyses.Read moreRead less
Expanding and resolving the earliest modern human divergence through DNA. This project aims to expand and resolve the earliest modern human divergence. Although it is clear modern humans emerged from Africa, there is no consensus on the timeline of modern human evolution. Archaeological evidence suggests two contenders: east and southern Africa. Genetic data supports the latter; the team’s own data shows that the southern African KhoeSan click-speaking forager peoples have the oldest extant huma ....Expanding and resolving the earliest modern human divergence through DNA. This project aims to expand and resolve the earliest modern human divergence. Although it is clear modern humans emerged from Africa, there is no consensus on the timeline of modern human evolution. Archaeological evidence suggests two contenders: east and southern Africa. Genetic data supports the latter; the team’s own data shows that the southern African KhoeSan click-speaking forager peoples have the oldest extant human lineages. This project will generate large mitochondrial genome and whole genome sequence data for KhoeSan lineages. This is expected to narrow the time of modern human emergence.Read moreRead less
Transforming The Diagnosis And Management Of Severe Neurocognitive Disorders Through Genomics
Funder
National Health and Medical Research Council
Funding Amount
$2,499,330.00
Summary
Neurocognitive disorders (NCD) are one of the most common genetic conditions in our society and it results with a need for ongoing permanent care for many affected people. Until recently, only 30% of people with NCD could be diagnosed but this has changed with the availability of genomic testing where all genes can be tested at once. The use of genomics in the CRE will lead to new NCD genes being identified and this information being translated into a clinical setting.
Preparing Australia For Genomic Medicine: A Proposal By The Australian Genomics Health Alliance
Funder
National Health and Medical Research Council
Funding Amount
$25,000,000.00
Summary
The sequencing of the human genome brings the possibility of more accurate identification of the underlying basis of many diseases. This technology has moved so rapidly, however, that clinical access has been limited. In this application, a national alliance of clinicians, researchers, health economists and policymakers will evaluate the case for clinical genomics across inherited disease and cancer, determine how best to deliver this to the patient and train a capable workforce.
Sequencing and assembling microbial community metagenomes in real-time. This project aims to assemble metagenomes directly from environmental samples using nanopore sequencing. Short-read approaches to metagenomics cannot assemble mixed genomes from an environmental sample, so focus on describing which species and genes are present. Long-read nanopore sequencing enables the assembly of full genomes of multiple species in a sample. Assembling complete genomes in important resources such as water ....Sequencing and assembling microbial community metagenomes in real-time. This project aims to assemble metagenomes directly from environmental samples using nanopore sequencing. Short-read approaches to metagenomics cannot assemble mixed genomes from an environmental sample, so focus on describing which species and genes are present. Long-read nanopore sequencing enables the assembly of full genomes of multiple species in a sample. Assembling complete genomes in important resources such as water and soil should lead to deeper understanding of the dynamics, variation and transfer of genetic material within these resources’ microbial communities, strategies to manage microbial diversity, and improved productivity and long-term sustainability for these resources.Read moreRead less