Discovery Early Career Researcher Award - Grant ID: DE190100116
Funder
Australian Research Council
Funding Amount
$415,737.00
Summary
Cell types and cell states revealed by single-cell regulatory networks. This project aims to use single-cell gene regulation networks to predict cell types. Computational approaches are needed to recapitulate how the over 37 trillion cells program the shared genome sequence in a human body to create astoundingly diverse forms and functions. This project integrates millions of high-resolution single-cell gene expression profiles with large-scale population regulatory data to systematically recons ....Cell types and cell states revealed by single-cell regulatory networks. This project aims to use single-cell gene regulation networks to predict cell types. Computational approaches are needed to recapitulate how the over 37 trillion cells program the shared genome sequence in a human body to create astoundingly diverse forms and functions. This project integrates millions of high-resolution single-cell gene expression profiles with large-scale population regulatory data to systematically reconstruct gene regulatory networks. These networks are the molecular basis for understanding human cells. This projects outcomes intend to include the first reference single-cell regulatory database and novel methods and software to predict individual cells. This project will contribute to advancing Australia's capabilities in single-cell, precision medicine, and big biological data analysis leading to significant scientific, societal and commercial benefits.Read moreRead less
The Stemformatics gene expression compendium: development of multivariate statistical approaches for cross platform analyses. Scientific data is gathered in many different forms, but there are significant gaps in our ability to analyse multiple datasets when generated on different pieces of equipment. This project will study three typical research questions in stem cell biology to develop new analytical approaches to help solve this major data gap.
Genetic variation of single cell transcriptional heterogeneity in HiPSCs. This project aims to investigate whether induced pluripotent stem cells (iPSC) can be used to study the functions of genetic variants associated with human phenotypes and cell fate decisions. The project will utilise technology to produce single cell RNA sequence data for 100,000s of cells. By sequencing individual cells, the genetic control of cellular heterogeneity both within and between cells can be identified, and in ....Genetic variation of single cell transcriptional heterogeneity in HiPSCs. This project aims to investigate whether induced pluripotent stem cells (iPSC) can be used to study the functions of genetic variants associated with human phenotypes and cell fate decisions. The project will utilise technology to produce single cell RNA sequence data for 100,000s of cells. By sequencing individual cells, the genetic control of cellular heterogeneity both within and between cells can be identified, and in doing so, will provide significant benefit by revealing the potential for iPSC to be used for functional translation of human genomics.Read moreRead less
Decoding miRNA regulated genetic circuits. This project will aim to develop a much better understanding of how the process of making proteins from genes is regulated, and will develop scientific software capable of predicting how a cell will respond to changes in this regulation. The results will have widespread use, including assistance in deciding the best treatments for genetic diseases.
Developing bioinformatics methods for single cell transcriptomics. This project aims to develop novel bioinformatics methods for single cell transcriptomic data that seek to model variability in cell populations. The project expects to generate new approaches using Bayesian statistics that will act as high-end enablers of discovery in transcriptional regulatory processes. Through an interdisciplinary combination of experimental and computational research, insights into fundamental biological pro ....Developing bioinformatics methods for single cell transcriptomics. This project aims to develop novel bioinformatics methods for single cell transcriptomic data that seek to model variability in cell populations. The project expects to generate new approaches using Bayesian statistics that will act as high-end enablers of discovery in transcriptional regulatory processes. Through an interdisciplinary combination of experimental and computational research, insights into fundamental biological processes will be elucidated, specifically the robustness of cellular systems. Expected outcomes include a suite of novel tools that will push the boundaries of current bioinformatics solutions with potential to deliver significant benefits to every domain of biological science, particularly tissue engineering and synthetic biology.Read moreRead less
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
Discovery Early Career Researcher Award - Grant ID: DE150101117
Funder
Australian Research Council
Funding Amount
$327,000.00
Summary
The functional impact of new genes acquired through retrotransposition. Novel copies of genes often arise through retrotransposition of processed messenger RNAs. Many thousands of gene copies have arisen over evolutionary time and some of these have retained functionality while diverging from the parental gene leading to new paralogs under different regulatory regimes. Through analysis of whole-genome sequence data, we are now able to identify very recent gene copies that are not present in the ....The functional impact of new genes acquired through retrotransposition. Novel copies of genes often arise through retrotransposition of processed messenger RNAs. Many thousands of gene copies have arisen over evolutionary time and some of these have retained functionality while diverging from the parental gene leading to new paralogs under different regulatory regimes. Through analysis of whole-genome sequence data, we are now able to identify very recent gene copies that are not present in the reference genomes for various species, giving us the opportunity to explore the effects of new copies on the regulation of the original gene and the surrounding genomic environment into which the new copy is inserted. This project aims to address these important open questions through computational and biochemical approaches.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE190100008
Funder
Australian Research Council
Funding Amount
$387,103.00
Summary
Exploring the evolution and ecology of non-photosynthetic Cyanobacteria. This project aims to contribute and expand our rudimentary understanding of non-photosynthetic Cyanobacteria by obtaining representative genome sequences using metagenomics. The dogma that all Cyanobacteria are photosynthetic has recently been challenged by the discovery of non-photosynthetic lineages. This project expects to obtain representative genome sequences using metagenomics to predict surface structures. The expect ....Exploring the evolution and ecology of non-photosynthetic Cyanobacteria. This project aims to contribute and expand our rudimentary understanding of non-photosynthetic Cyanobacteria by obtaining representative genome sequences using metagenomics. The dogma that all Cyanobacteria are photosynthetic has recently been challenged by the discovery of non-photosynthetic lineages. This project expects to obtain representative genome sequences using metagenomics to predict surface structures. The expected outcomes from this project includes providing insights into the function and evolution of non-photosynthetic Cyanobacteria and their viruses, and pure or enriched cultures to enable future studies.Read moreRead less
Reconstructing proteins to explain and engineer biological diversity. The aim of this project is to develop computational methods to construct entirely new proteins. Computational reconstruction of enzymes that have been extinct for over 400 million years has revealed remarkable opportunities for biotechnological innovation. The intended outcomes are to develop bioinformatics methods to broaden the scope of ancestral protein reconstruction to include protein super-families, to establish what spe ....Reconstructing proteins to explain and engineer biological diversity. The aim of this project is to develop computational methods to construct entirely new proteins. Computational reconstruction of enzymes that have been extinct for over 400 million years has revealed remarkable opportunities for biotechnological innovation. The intended outcomes are to develop bioinformatics methods to broaden the scope of ancestral protein reconstruction to include protein super-families, to establish what specific changes led to the evolutionary success of a protein, and to re-run evolution to generate proteins that perform in conditions suitable for industrial and agricultural applications, in particular the production of hydroxylated fatty acids for bioplastics. By examining proteins from many life forms, the project plans to develop a novel bioinformatics strategy to understand their evolution and engineer new proteins for use in production of chemical commodities.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE190101078
Funder
Australian Research Council
Funding Amount
$374,433.00
Summary
Functional role of a novel DNA modification in the adult brain. This project aims to understand how neuronal DNA is modified upon learning and how this impacts memory formation. The project will investigate the combination of different genome-wide sequencing approaches and molecular and cell biological assays to provide new insight into the functional role of a novel DNA modification, N6-methyl-2'-deoxyadenosine in the adult brain. This projects expects to have a major impact on many fields, inc ....Functional role of a novel DNA modification in the adult brain. This project aims to understand how neuronal DNA is modified upon learning and how this impacts memory formation. The project will investigate the combination of different genome-wide sequencing approaches and molecular and cell biological assays to provide new insight into the functional role of a novel DNA modification, N6-methyl-2'-deoxyadenosine in the adult brain. This projects expects to have a major impact on many fields, including neuroscience, evolutionary biology, and genetics, by helping to shape a new way of thinking about gene-environment interactionsRead moreRead less