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
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
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