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Projects

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Environment

NZ river landscape
Environmental Metagenomics

Led by Kim Handley, University of Auckland

A powerful way of studying microorganisms is by direct sampling of their collective genomes from the environment. This helps determine the role of organisms and their impact on environmental health. This project will generate a high quality database of mixed genomes from DNA collected from a stream to determine its health and genetic potential. The aim is to develop national capabilities and contribute to improved environmental monitoring approaches using genomics.

Te Nohonga Kaitiaki

Led by Maui Hudson, University of Waikato

This project will develop guidelines for genomic research with taonga species that align with cultural expectations of appropriate ethical behaviour. This will support Genomics Aotearoa researchers to work appropriately with Māori / Iwi communities in the generation, storage and use of genome sequences for taonga species and indigenous biota.

See also High Quality Genomes (below).

Primary Production

High Quality Genomes

Led by David Chagné, Plant & Food Research, and Thomas Buckley, Manaaki Whenua - Landcare Research

High quality genome (sets of DNA) sequences of organisms that are important to New Zealand are needed for conservation purposes and breeding within our primary industries. Assembling high quality genomes is a challenge as many genomes are large, variable or very complex. This project will develop the capability and distribute the tools needed to routinely generate high quality genome assemblies. These tools will accelerate protection of our threatened species and improve knowledge for primary production species.

blueberry

Photo: Copyright © The New Zealand Institute for Plant and Food Research Limited. All rights reserved for the picture (created by Minna Pesonen)

Better Breeding Values

Led by Dorian Garrick, Massey University, and Michael Lee, University of Otago

Primary industries rely on genetic improvement to maintain sustainability and increase efficiency and profitability, in order to remain competitive and mitigate risk. This project will develop next-generation tools and approaches to help manage the complexity of using genomic data to predict breeding values.

Health

Aotearoa New Zealand Genomic Variome

Led by Phil Wilcox and Stephen Robertson, University of Otago

To use genomic medical diagnosis effectively and equitably, we need to understand genomic variation in New Zealand’s unique and increasingly diverse population. The aim of this project is to assemble genomic resources that catalogue genetic variants present in the genomes of individuals in our communities. This will support disease diagnosis and research into healthcare conditions relevant and important to Māori and Pacific people.

Genomic Translational Oncology

Led by Cristin Print, University of Auckland

Genomic translational oncology is developing rapidly around the world, changing our understanding of cancer biology and approaches to treatment. This project will adopt overseas learnings in the use of genomics to assist people with cancer, while being mindful of New Zealand differences and opportunities. The aim is to develop a cohesive set of protocols and methods, and upskill clinical and research leaders, to enable the progressive induction of translational genomics into New Zealand’s oncology practice and cancer research.

Cell-Free Genomics

Led by Parry Guilford and Mik Black, University of Otago

Plasma genomics has the potential to enhance our ability to diagnose and treat cancer and other non-communicable diseases. Cell-free plasma samples are easily accessible from patients, and there may be effective ways to use such samples to monitor patient responses to cancer therapy, and eventually screen for multiple types of cancer. This project will develop pipelines for data analysis, quality control and clinical reporting of plasma genomic data, leading to the more rapid implementation of plasma genomics into clinical practice.

Culture-Independent Genomic Typing of Bacterial Pathogens

Led by Jenny Draper, ESR

Once a disease-causing microorganism is identified in a particular patient, food or environmental sample, it takes further clinical laboratory work to determine the “typing” data that describes the organism’s characteristics, such as what antibiotics it is resistant to or where it came from. This project will develop a metagenomics-based test to determine the typing information for a specific pathogen directly from the clinical sample. This will allow use of faster diagnostic tests without compromising the ability to monitor infectious diseases.

Epigenome-Wide Association Study Technology

Led by Greg Jones, University of Otago

Linking disease association with genetic, epigenetic or environmental factors may help better understand the health conditions of people taking part in New Zealand’s well-characterised cohort studies. However, New Zealand researchers need new pipelines and tools to do this. This project aims to streamline the analysis of population-level epigenetic datasets, in particular focusing on developing and establishing Epigenome-wide Association Study methods across several national research groups.

Clinical Genomics

Led by Stephen Robertson, University of Otago

This pilot project offers laboratory scientists the opportunity to analyse genomic datasets from patients with real clinical problems who present to genetic services, with the ability to deliver results back to patients. The initiative targets members of disadvantaged communities to ensure equitable access to the latest technologies. This work aims to further develop New Zealand’s capability to implement genomically informed healthcare in collaboration with clinicians and diagnostic laboratories.

Bioinformatics

Bioinformatics Capability

Led by Mik Black and Peter Dearden, University of Otago, Kim Handley, University of Auckland, Rudiger Brauning, AgResearch, and Jenny Draper, ESR

This project co-ordinates the bioinformatics aspects of Genomics Aotearoa projects. The focus is on establishing and providing underpinning computational / bioinformatics infrastructure and training.