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
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
Characterising inheritance patterns of whole genome DNA methylation. This project aims to characterise epigenetic diversity and inheritance patterns in whole genome sequencing data from a unique human population. The project will employ the well-characterised Norfolk Island genetic isolate, cost-effective whole genome bisulphite sequencing technologies and advanced bioinformatics pipelines and statistical models. It will involve cross-discipline collaboration between human geneticists, epigeneti ....Characterising inheritance patterns of whole genome DNA methylation. This project aims to characterise epigenetic diversity and inheritance patterns in whole genome sequencing data from a unique human population. The project will employ the well-characterised Norfolk Island genetic isolate, cost-effective whole genome bisulphite sequencing technologies and advanced bioinformatics pipelines and statistical models. It will involve cross-discipline collaboration between human geneticists, epigeneticists, statistical geneticists and bioinformaticians. This project will advance our understanding of the interaction of genetics and epigenetics and their relationship to diversity and inheritance in humans.Read moreRead less
The nature of standing genetic variation. This project aims to expand understanding of the genetic variation underlying phenotypic differences among individuals. The nature of genetic variation has broad consequences across biology, from the detection of causal genetic variants to the adaptation of natural populations. This project will take a novel experimental approach to test several long-standing assumptions about the effects of new mutations on individual traits and their joint pleiotropic ....The nature of standing genetic variation. This project aims to expand understanding of the genetic variation underlying phenotypic differences among individuals. The nature of genetic variation has broad consequences across biology, from the detection of causal genetic variants to the adaptation of natural populations. This project will take a novel experimental approach to test several long-standing assumptions about the effects of new mutations on individual traits and their joint pleiotropic effect on fitness. By expanding our understanding of how mutation, selection and drift interact, this project could provide significant improvements in our understanding of the genetic basis of phenotypes, and our ability to predict phenotypic evolution.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
The transgenerational effect of thermosensing in plants. This project aims to understand how thermosensing mechanisms in plants result in transgenerational change, and potentially adaptation to climate. Exploiting the recent discovery of the thermosensor phytochrome B, this project will decipher the molecular cascade which, either through long-distance communication or through persistence of an epigenetic state in the cell lineage, could lead to a trans generational memory in plants helping with ....The transgenerational effect of thermosensing in plants. This project aims to understand how thermosensing mechanisms in plants result in transgenerational change, and potentially adaptation to climate. Exploiting the recent discovery of the thermosensor phytochrome B, this project will decipher the molecular cascade which, either through long-distance communication or through persistence of an epigenetic state in the cell lineage, could lead to a trans generational memory in plants helping with climate adaptation. This project will unravel novel molecular mechanisms, which have the potential to pave the way for designing new climate-proofing solutions to cope with temperature uncertainty.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
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
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
Discovery Early Career Researcher Award - Grant ID: DE220101210
Funder
Australian Research Council
Funding Amount
$451,634.00
Summary
Deciphering molecular genetic mechanisms underlying chromatin interactions. This project aims to generate the high confidence map of enhancer-promoter links in 61 tissues and cells through robust integration of novel machine learning tools with genomic and epigenomic datasets. Understanding which key elements in the genome may be important to fine-tune gene expression is essential for understanding biological pathways. The expected outcomes include i) New tools to robustly identify true chromati ....Deciphering molecular genetic mechanisms underlying chromatin interactions. This project aims to generate the high confidence map of enhancer-promoter links in 61 tissues and cells through robust integration of novel machine learning tools with genomic and epigenomic datasets. Understanding which key elements in the genome may be important to fine-tune gene expression is essential for understanding biological pathways. The expected outcomes include i) New tools to robustly identify true chromatin pairs; ii) Comperehensive maps of regulatory interactomes in 61 tissues & cells, which will provide a roadmap for interpreting & prioritising noncoding variants.
This should provide significant benefit to Australia's capacity for cutting-edge genomics research through fundamental understanding of gene regulation mechanism.Read moreRead less