Using venoms to map critical and evolutionary conserved vulnerabilities. We have developed and applied new functional genomic approaches to study venom evolution. Using CRISPR screening, we find that unrelated venoms act on cells by exploiting the same vulnerabilities. By functionally mapping these vulnerabilities for all venom classes, we can begin to develop universal venom antidotes. Conversely, much of what we know about venom mechanisms comes from a small percentage of the biodiversity with ....Using venoms to map critical and evolutionary conserved vulnerabilities. We have developed and applied new functional genomic approaches to study venom evolution. Using CRISPR screening, we find that unrelated venoms act on cells by exploiting the same vulnerabilities. By functionally mapping these vulnerabilities for all venom classes, we can begin to develop universal venom antidotes. Conversely, much of what we know about venom mechanisms comes from a small percentage of the biodiversity within a venom, and we have developed genomic tools to study the venom “dark matter”. This work will lead to the full molecular characterisation of venom biodiversity, and new venom components will be useful for research or as novel medicines.Read moreRead less
Improving access to phylogenomic resources for under-resourced species: a new look at existing tools. This project will have an impact on our understanding of how to most effectively use existing genomic resources to benefit a wider range of species and to better design new genomic resources. By doing so, improved access to genomic resources will be provided to species that currently have few options.
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
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
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
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.