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.
Mapping recombination blocks in Brassica. DNA technology provides new ways to study genomes. Understanding how the genome behaves during plant breeding will help design strategies for the breeding and selection of improved crop plants.
The role of Roquin in microRNA function and decay. The aim of this study is to understand how microRNAs (newly discovered genetic components that control cell growth and survival) function and are regulated. The expected discoveries will help understand how common cancers including breast cancer and autoimmune diseases emerge, and will help develop cutting edge genetic technologies.
Discovery Early Career Researcher Award - Grant ID: DE130101450
Funder
Australian Research Council
Funding Amount
$374,300.00
Summary
The molecular basis of division of labour in the beehive. This study will dissect the genes and gene networks underpinning behaviour using cutting edge molecular and computational techniques. As a model, this project will study the division of labour in a social insect, the honeybee.
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
How novel ribosomal RNA gene repeat variants drive cellular function. The hundreds of ribosomal RNA gene repeat copies are a remarkable part of our genomes, as they encode the machinery responsible for all cellular protein synthesis and shape the structure of the nucleus. However, due to their high degree of sequence similarity, they still have not been assembled into the human genome reference. This project will resolve this impasse and furthermore uncover the functional impacts of a newly iden ....How novel ribosomal RNA gene repeat variants drive cellular function. The hundreds of ribosomal RNA gene repeat copies are a remarkable part of our genomes, as they encode the machinery responsible for all cellular protein synthesis and shape the structure of the nucleus. However, due to their high degree of sequence similarity, they still have not been assembled into the human genome reference. This project will resolve this impasse and furthermore uncover the functional impacts of a newly identified molecular diversity in the ribosomal RNA gene repeats. Outcomes include new paradigms for how the ribosomal RNA gene repeats drive protein synthesis and genome structure, and a blueprint to develop novel genomics applications for human health, biotechnology, and agriculture.Read moreRead less
HEN1 is a regulator of piRNA metabolism, transcriptional regulation and mammalian male fertility. This project is to define the biochemistry of a previously uncharacterized protein in male fertility using a unique mouse model and innovative DNA and protein technologies. This project will define a novel, and essential, pathway for male fertility and may ultimately have relevance to the maintenance of health or improving fertility.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE120100025
Funder
Australian Research Council
Funding Amount
$380,000.00
Summary
A high-throughput screening and sequencing facility for single cell genomics. Genomics has revolutionised biology, but for most microorganisms this revolution has not arrived because very few can be grown in pure culture. The single cell genomics facility will address this major bottleneck by allowing as little as a single cell in a clinical or environmental setting to be sequenced thereby accelerating new discoveries and outcomes.
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