Research

The Centre for Plant Success uses an interdisciplinary approach to advance Australia’s capabilities in genomic prediction and genome editing, aiming to provide diverse outcomes with value to numerous disciplines including:

fundamental understanding of the physiological and genetic drivers of evolutionary adaptions in plant form and function across lineages;

new mathematical theory and software capable of accurately estimating plant phenotype or yield based on genotype, saving breeders time and money;

novel plant genomes, and genomic diversity that will help safeguard species—particularly crops—against climate change; and

innovative legal and social paradigms to protect complex and intangible IP and increase investment in Australia’s rapidly-growing biotech industries

Feeding the world requires a step change in plant breeding

Over the first 20 years of this century, plant breeders have had success in developing new varieties of food crops—specifically, rice, corn and wheat—that produce more food on the same amount of land. In that time, the rate of increase in crop productivity, or ‘genetic gain’, has averaged about 1% a year.

This trend may continue but 1% is not enough of a gain to feed the world’s growing population. Even without factoring in the projected changes in climate, including increasingly extreme weather events, the genetic gain needs to double.

To achieve this, we need a step change in plant breeding.

A FOOD DIVERSITY CRISIS

The focus on just rice, corn and wheat also comes with 2 downsides which have heralded a crisis in food diversity:

of the world’s calorie intake is from these 3 crops, with low-income countries hugely reliant on them. Because of a lack of food diversity, about 10% of people are undernourished and 21% of children under five years of age are stunted. Many obese people are undernourished, in both rich and poor countries.

of the world’s plant species are used for food. To date, it has been hard to extrapolate what we know from well-studied species to other species. A huge opportunity looms if we can understand what knowledge is transferable to poorly understood species such as sorghum, cassava, and horticultural crops.

The current limitations of plant breeding

Crossbreeding plants to introduce traits or genes from one variety to another has been largely based on observation and correlation. When selecting for a particular trait, breeders manipulate genes and wait to observe the results of their field trials. This can take years, especially in the case of trees.

The resulting cross may not produce the desired outcome with the plant failing to exhibit the desired trait or unintended consequences/trade-offs prove unacceptable.

Plant traits are almost always regulated by more than one gene (and their products) which interact with different parts of the plant system, and which also have external influences, such as the climate and the farmer’s management practices.

The reason for the poor success rate is that plant traits are almost always regulated by more than one gene (and their products) which interact with different parts of the plant system, and which also have external influences, such as the climate and the farmer’s management practices.

Knowing the entire genome of a species is useful only to a point—the sheer number of variables at play make it impossible to predict breeding success with any confidence, even in rice, corn and wheat.

For poorly understood plants, it is even more difficult for us to understand how plant traits are controlled. We need to learn what knowledge is transferable across the plant kingdom.

Increasing the odds of success in plant breeding

We believe that through biology, mathematics and responsible innovation, we can increase the odds of success in breeding, accelerate the breeding process, double the rate of genetic gain and transform the breeding industry.

And by learning what knowledge is transferable between species, we can broaden the knowledge of all species, thereby increasing the diversity of food crops and ultimately the nutrition in the diets of people all over the world.

Our research projects are integrated across six themes.

Projects

All projects are interdisciplinary, with Early-Mid Career Researchers working across projects with other Chief Investigator groups.

Lead Chief Investigator: Mark Cooper

Collaborating Chief Investigators: Graeme Hammer, David Jordan, Christine Beveridge, Kevin Burrage

Theme(s): Novel design principles, mathematics, and technologies; G-P modelling and prediction

The project is evaluating the potential to develop a wide range of informative link functions for application to genomic prediction of yield. The link functions are based on the hierarchical mechanistic functions for traits within crop growth models. The models under investigation are those available in APSIM. The hypothesis being tested is that by connecting components of the total genetic variation for yield to coefficients within the trait functions will enable enhanced modelling of a predictable fraction of the total trait-by-trait-by-environment interactions that influence crop yield outcomes and thus enable improvements in prediction accuracy at the grain yield level. The new link function framework is referred to as APSIM-GP. Improvements in yield prediction are evaluated in comparison to the traditional infinitesimal quantitative genetic models that directly connect gene effects or QTL effects to yield without using the APSIM-GP link function and therefore attempt yield prediction without supervised consideration of the intermediate trait-by-trait-by-environment interaction effects.

Lead Chief Investigator: Graeme Hammer

Collaborating Chief Investigators: Mark Cooper, Christine Beveridge

Theme(s): Novel design principles, mathematics, and technologies; G-P modelling and prediction

The project will utilise high performance computing to generate a simulated (synthetic) data set of predicted yield for sorghum breeding populations across a comprehensive sample of the target population of environments (E) in the production region of Australia using the APSIM-sorghum crop growth model (CGM), which will be adapted for the task. Populations will vary for key adaptive traits with genomic regions (G) assigned to influence model parameters generating those traits (e.g. maturity, leaf size). A range of crop management (M) approaches (e.g. plant density) will also be simulated. The resultant GxExM data base of phenotypic outcomes will be invaluable in contrasting utility of methods for whole genome prediction (WGP) in plant breeding.

Lead Chief Investigator: Christine Beveridge

Collaborating Chief Investigators: Mark Cooper, David Jordan, Graeme Hammer, Jim Weller

Theme(s): Discovering mechanisms and principles of biology

This project will discover genes underpinning branching and tillering in Arabidopsis, sorghum and garden pea. It uses quantitative genetics and developmental genetics as well as molecular physiology to describe the genetic architecture.

Lead Chief Investigator: David Jordan

Collaborating Chief Investigators: Mark Cooper, Barbara Holland

Theme(s): Novel design principles, mathematics, and technologies; Genetic basis of domestication and adaptation

Recent research suggests that changes in gene composition makes a major contribution to plant species adaptation to diverse environments. Investigating the variation in gene composition among closely related species with different adaptation and evolutionary histories provides important information about the functionality of gene families and their interactions in gene networks.

This project aims to build on the world’s first sorghum pan-genome, developed by our group, and expand this resource to include rice and maize, 2 importance crop species that share a close ancestry with sorghum. In addition to our own work on developing the sorghum pan-genome, pan-genomes of rice and maize are being developed by two independent groups to better capture gene content variation within each species. Additionally, CI Henry has generated de-novo sequences of 15+ Australian native sorghums which we will look to incorporate if feasible.

The proposed grass pan-genome will identify shared and unique genes among and within three important cereal crops. This will provide the Centre with a critical resource to identify genes and genetic networks underlying key agronomical traits and investigate their evolutionary trajectory. This in turn will facilitate the Centre’s goal of making significant advances in the emerging fields of evolutionary systems biology and predictive analytics to deliver novel strategies for improving ecosystem management, crop resilience and yield.

Lead Chief Investigator: Christine Beveridge

Collaborating Chief Investigators: Graeme Hammer, Kevin Burrage, Mark Cooper

Theme(s): Novel design principles, mathematics, and technologies; G-P modelling and prediction

Current methods of capturing complex networks for the purposes of validation and prediction, for any number of a range of purposes, are either highly detailed, such as differential equations models, or adapted for extremely large data sets with little detail on the interactions within the network. PSoup provides a solution where the interactions in the network are captured including networks that are too large to be successfully modelled with differential equations.

Lead Chief Investigator: Ian Wright

Collaborating Chief Investigators: Tim Brodribb, Peter Waterhouse, Mark Cooper, Graeme Hammer, Eloise Foo, Barbara Holland, Steven Smith

Theme(s): Discovering mechanisms and principles of biology; Comparative ecology and evolution of plant strategies

We are investigating adaptations to site climate (especially drought and heat) in four study systems: (i) Interspecific and evolutionary studies in Eucalyptus and allied genera; (ii) Interspecific studies in Australian Sorghum species; (iii) Intraspecific (among population) studies in kangaroo grass, Themeda triandra; and (iv) Intraspecific studies in Sorghum bicolor (among African and Indian landraces)

Lead Chief Investigator: Steve Smith

Collaborating Chief Investigators: Ian Wright, Eloise Foo, Tim Brodribb, Barbara Holland, Peter Waterhouse

Theme(s): Discovering mechanisms and principles of biology; Comparative ecology and evolution of plant strategies; Novel design principles, mathematics, and technologies; Genetic basis of domestication and adaptation

A major challenge is to understand how evolution and adaptation have shaped, and been shaped, by the content and organisation of plant genomes and how the expression of the information contained in the genomes leads to defined phenotypic outcomes. At the core is a thorough understanding of phylogeny which enables us to understand evolutionary pathways and the relatedness of different taxa to each other. Comparative genomic approaches and genetic analysis then enable us to identify genetic variation and to understand the genetic basis for particular traits and physiological responses.  These approaches will enable us to identify genes and genetic processes underlying evolution and adaptation of plants in nature, domestication and crop improvement. Transcriptome analysis plays a central role in deciphering genome expression mechanisms and identifying key genes and gene networks that lead to phenotypic responses. We have undertaken genome and transcriptome analysis in several taxa including Arabidopsis thaliana, Pisum sativum, Themeda triandra, Nicotiana benthamiana and numerous Eucalyptus species.

Lead Chief Investigator: Tim Brodribb

Collaborating Chief Investigators: Ian Wright

Theme(s): Discovering mechanisms and principles of biology

This project broadly aims to define the principal modes of adaptation to low rainfall in plant species. Using a wide range of species from ferns, conifers and angiosperms, and investigating both above and belowground tissues investigations will examine correlative evidence for trait adaptation to dry climate. Trait selection will be guided by novel research into the function of hydraulic systems under stress. Ultimately the goal is to identify core adaptations and to predict how their function enables success under water limited conditions.

Lead Chief Investigator: John Bowman

Collaborating Chief Investigators: Tim Brodribb, Christine Beveridge

Theme(s): Discovering mechanisms and principles of biology

Signalling between cells and organs directs the development of plants in response to changing environmental cues and much of this communication relies on hormone signalling networks. This project explores the evolution of hormone signalling networks, asking (1) how the signalling networks initially evolved, (2) how the networks have been co-opted during evolution into directing novel development and physiology and (3) how they can be manipulated to produce desired developmental outcomes. These objectives are derived from a comparative approach contrasting biology in the liverwort Marchantia polymorpha with that of flowering plants. While most focus has been on auxin, collaborative projects involve other plant hormones, abscisic acid (Brodribb) and the sugar trehelose (Beveridge).

Lead Chief Investigator: Christine Beveridge

Collaborating Chief Investigators: Jim Weller

Theme(s): Discovering mechanisms and principles of biology

Processes of flowering, branching, and meristem and apical arrest are all known to affect seed yield and yet are almost always studied in isolation. This project mostly in garden peas, seeks to understand:

  • How the flowering pathway affects branching
  • Whether suppression of growth at the apical meristem is regulated by a similar genetic network as the suppression of buds from growing into branches.

Lead Chief Investigator: Jim Weller

Theme(s): Discovering mechanisms and principles of biology; Genetic basis of domestication and adaptation

Understanding the genetic basis for changes associated with domestication of crops from their wild ancestors is essential to several emerging approaches in crop improvement, including modification of existing crops through strategic incorporation of specific wild alleles, and the engineered de novo domestication of new crops from wild species with valuable potential. This knowledge also provides key fundamental insights into the mechanisms and constraints of crop domestication and allows its historical reconstruction in time and space.

Legumes are an ancient and important group of crop species globally, and major export crops for Australia.. However, relative to other major grain crop groups such as cereals, they are significantly understudied, particularly the "temperate" species lentil, chickpea and pea. This project will use genetic, molecular and genomic approaches to characterise the genetic basis for key changes that accompanied and enabled their domestication, including a critical reduction in seed dispersal and dormancy, and alterations to phenology and architecture.  Surprisingly, despite recent rapid progress in characterisation of genomes and genetic diversity, there is virtually nothing currently known about the domestication genetics of these species.

Lead Chief Investigator: Robert Henry

Collaborating Chief Investigators: Peter Waterhouse

Theme(s): Genetic basis of domestication and adaptation

Domestication of new species provides a strategy to expand the range of species available to support food security. This may be especially important as climate change alters the relative performance of different plant species in agricultural production.

Lead Chief Investigator: Robert Henry

Theme(s): Genetic basis of domestication and adaptation

This project explores the relationships between wild and domesticated plants by genome analysis. Analysis of wild crop relatives allows the mining of useful genes that might be incorporated into domesticated crops. Key targets in the Australian flora are Oryza (rice) Sorghum, Millet (Echinochloa and Panicum), Macadamia, Citrus and Glycine (soybean) species. Genomics and transcriptomics will be used to explore the genetic basis of adaptation in nature and agriculture

Lead Chief Investigator: Eloise Foo

Collaborating Chief Investigators: Christine Beveridge, Tim Brodribb

Theme(s): Novel design principles, mathematics, and technologies

Plant hormones are key regulators of development, but our understanding of how they regulate complex organ development has been hampered by inability to spatially map their concentration in tissue.  The ARC LIEF-funded cyclic ion mobility quadrupole time-of-flight mass spectrometer linked to a DESI (Desorption Electrospray Ionisation) imaging platform at UTAS enables quantitative imaging of small to medium sized metabolites, including plant hormones, in plant tissue sections. Dr Karen Velandia and Prof Eloise Foo laboratory working with Dr David Nichols (CSL, UTAS) are developing technique to quantitatively map plant hormone like auxin, and other primary and secondary metabolites, within plant tissue sections at high resolution.

This will enable us to answer questions about how plant hormone control spatial development and growth (e.g. nodulation, mycorrhizal symbioses, axillary bud development and shoot branching) and response to the environment (e.g. drought response).

Lead Chief Investigator: Eloise Foo

Collaborating Chief Investigators: Tim Brodribb, Barbara Holland

Theme(s): Discovering mechanisms and principles of biology; Genetic basis of domestication and adaptation

This project examines the key genes and signals that control plants ability to form symbiotic relationships with nitrogen-fixing bacteria (in legumes, called nodulation) and phosphorous-acquiring arbuscular mycorrhizal symbioses (widespread in land plants). Our primary focus is on plant hormones and peptide signals that regulate the formation and extent of symbioses. This includes developing new techniques to monitor peptide hormone levels in planta.

We also examine how these symbioses impacts plant water hydraulics, an underexplored topic that has important implications for how plants trade-off nutrient acquisition and water.

Lead Chief Investigator: Peter Waterhouse

Collaborating Chief Investigators: Tim Brodribb

Theme(s): Discovering mechanisms and principles of biology; Novel design principles, mathematics, and technologies; Genetic basis of domestication and adaptation

The aim of the project is to keep pace with new advances and further develop gene and genome editing technologies to alter pathways (e.g. metabolic/defence/development) in plants. To do this we have first sought to understand two important pathways (Anthocyanin and Drought) in the native Australian species Nicotiana benthamiana, such that we can testbed our editing technologies. Our intention is to prove the concept by directing the controllers of one pathway to control components of the other. The first requirement was the assembly of reference quality chromosome-level genome sequences and full annotation for at least two ecotypes of N.benthamiana. Secondly, we needed to understand the subtleties of their specific drought responses (focusing mainly on wax biosynthesis for cuticle modification) and anthocyanin biosynthesis capacities of the ecotypes.  Thirdly, we have been, concurrently, developing efficient means to rewrite genome sequences.

Lead Chief Investigator: Brad Sherman

Collaborating Chief Investigators: Robert Henry

Theme(s): Responsible Innovation

Properties of Food aims to analyse and explore important and heritage food crops within their local and cultural context and how intellectual property and associated property-based regimes have shaped the legal, cultural and social status of selected, significant global crops. The project will cover a range of topics chosen to highlight key legal events. These will include:

  • Macadamia
  • Gnali Nut & taro
  • Plumpi nut
  • Cereal Crops: Wheat, sorghum & maize
  • Rice
  • Sonoran Wheat

Lead Chief Investigator: Mark Cooper

Collaborating Chief Investigators: Diane Donovan

Theme(s): Discovering mechanisms and principles of biology; Novel design principles, mathematics, and technologies; Genetic basis of domestication and adaptation

Applying the framework of the Diversity Prediction Theorem this project is investigating how to design ensemble-based predictions that combine the complementary strengths of different prediction models based on the diversity of the genomic information included in the models to predict trait values at the total genotype value (TGV) and breeding value (BV) levels. TGV and BV are key quantitative genetic concepts for prediction the trait performance of individuals (TGV) and the potential of individuals to create new individuals over breeding program cycles (BV). Current ensemble-based modelling investigations are evaluating ensembles that combine traditional parametric models of quantitative genetics together with the non-parametric network inspired models available from Machine Learning (ML) and Artificial Intelligence (AI).

Lead Chief Investigator: Diane Donovan

Collaborating Chief Investigators: Christine Beveridge, Kevin Burrage, Daniel Ortiz-Barrientos

Theme(s): Novel design principles, mathematics, and technologies

This project aims to develop innovative mathematical tools that use network and graph theory to better understand gene function and how it changes over time, across environments, and among different species. By creating methods that remain reliable under varying conditions – such as evolutionary changes or environmental stress – we aim to gain deeper insights into how living systems adapt and operate.

The research will build on existing knowledge to construct robust, quantitative models of genetic networks. These approaches will connect studies of native plants and crops from diverse environments, providing a unified framework for comparing biological systems. Ultimately, this work could inform new strategies for advancing agriculture, preserving biodiversity, and managing natural ecosystems.

Lead Chief Investigator: Christine Beveridge

Collaborating Chief Investigators: Graeme Hammer, Mark Cooper, Jim Weller, David Jordan

Theme(s): Discovering mechanisms and principles of biology

Branches and tillers need to be reproductive in order to contribute to seed yield. In sorghum and other plants, including Arabidopsis, branches/tillers often form but do not reach a reproductive phase or do not bear seeds. This branch arrest may be terms cessation of growth. Cessation of growth also occurs in the main shoot after reproduction and is regulated by a relatively well-established network. This project will reveal components of the network controlling cessation of branch growth by exploring the role of candidate genes and signals and through identifying genes regulated during the arrest process.

Lead Chief Investigator: Daniel Ortiz-Barrientos

Collaborating Chief Investigators: Diane Donovan, Barbara Holland, Kevin Burrage

Theme(s): Discovering mechanisms and principles of biology; Comparative ecology and evolution of plant strategies; Novel design principles, mathematics, and technologies; Genetic basis of domestication and adaptation

The adaptive outcomes of populations depend on the alignment of the genetic architectures underpinning traits under selection with the direction of selection. Understanding the nature of this link is key to predicting population responses to climate change, yields from potential crosses in agriculture, and improving the efficacy of personalised medicine. In this project, we use a variety of computational and mathematical tools to uncover the genetic architecture of adaptation. Using evolutionary genetic simulations, we explore the effects of genetic interactions driven by gene regulatory networks on producing constraints to adaptation. We analyse the effects of such networks on quantitative genetic parameters such as additive genetic variance and responses to selection. With similar simulations we also investigate the nature of organismal complexity on genetic variance and the interface between complexity, genetic architecture, and adaptation. We also explore a geometric treatment of quantitative genetics theory to further understand how the alignment of genetic variance and selection can vary in nature and agriculture. We also have developed a pipeline to make genomic imputation accessible for non-model organisms, and are using machine learning models to detect regions of the genome that are under parallel natural selection.

Lead Chief Investigator: Daniel Ortiz-Barrientos

Collaborating Chief Investigators: Barbara Holland

Theme(s): Discovering mechanisms and principles of biology; Genetic basis of domestication and adaptation

In this project, we are uncovering the genetic basis of adaptation by using 1) a system of parallel evolution, where similar selective pressures have driven the evolution of similar forms across independent lineages, and 2) a highly recombined population, enabling us to breakdown trait and genetic correlations and pinpoint the precise genetic basis of adaptation. We are investigating how natural selection shapes complex traits, whether it consistently produces the same solutions when faced with similar challenges, and ultimately whether evolutionary outcomes are predictable.

Lead Chief Investigator: Daniel Ortiz-Barrientos

Collaborating Chief Investigators: David Jordan

Theme(s): Discovering mechanisms and principles of biology; Genetic basis of domestication and adaptation

This project will construct the Senecio pangenome, which will consist of multiple ecotypes that have adapted to a range of harsh environments across Australia. The pangenome will enable us to explore how gene families evolve during adaptation, how structural arrangements (duplications deletions, copy number variation, translocations and inversions) impact adaptation, and how repeatable is the structure and content of genomes across replicate populations.

Lead Chief Investigator: Ian Wright

Collaborating Chief Investigators: Tim Brodribb, Barbara Holland

Theme(s): Discovering mechanisms and principles of biology

Drawing on datasets and deep knowledge on drought response being generated across the Centre we will integrate physiological data and phylogenetic information into an extinction risk assessment protocol. Extrapolating networks and associated mathematical models from collated data sets is expected to enhance this prediction capability.

Lead Chief Investigator: Eloise Foo

Collaborating Chief Investigators: David Jordan, Ian Wright

Theme(s): Discovering mechanisms and principles of biology; Genetic basis of domestication and adaptation

Symbioses with nutrient acquiring symbioses are key adaptations in land plants and have also been under the influence of domestication and artificial selection. This project uses key grass species (Kangaroo grass, wheat, barley and sorghum) to explore how adaptation and/or domestication has shaped arbuscular mycorrhizal symbioses with these species.

The kangaroo grass project is part of a larger strategic focus of CoE that includes genomic sequencing, comparative transcriptomics and examining traits that adapt K.grass to specific environments (Ian Wright WSU and others). One part of this project examines how K.grass diversity drives partner selection of mycorrhizal fungi across Australian soil types.

The sorghum project is undertaken in collaboration with Prof David Jordan and Prof Emma Mace at UQ. It uses prior knowledge of key genes regulating mycorrhizal symbioses to identify racial diversity linked to adaptation to nutrient levels in soil. These genetic screens identify target genotypes to examine the impact on mycorrhizal colonisaiton and function and could underpin selection of elite genotypes that gain optimal benefit from mycorrhizae.

The wheat and barley project is undertaken in collaboration with AI Greg Rebetzke and examines the impact of selection for dwarf habit on below ground interactions, primarily mycorrhizal symbioses. This has important implications for selection of new elite dwarf lines that have optimal mycorrhizal symbioses.

Lead Chief Investigator: Tim Brodribb

Theme(s): Novel design principles, mathematics, and technologies

The aim of this project is to develop technology to sense and record leaf water potential, and to formulate analysis tools to process dynamic records from experimental or field situations. Ultimately the goal is to record and analyse water potential kinetics that will enable plant stress to be sensed and used to characterise species or genotypes in terms of response to climatic/soil water limitation. A plan for commercialization, if appropriate will also be pursued.

Lead Chief Investigator: Barbara Holland

Collaborating Chief Investigators: Daniel Ortiz-Barrientos

Theme(s): Discovering mechanisms and principles of biology; Comparative ecology and evolution of plant strategies

Shared evolutionary history implies a covariance structure for the evolution of traits across species. At the same time, genetics and the environment also constrain the extent to which different traits covary. This project aims to develop mathematical tools that will allow us to tease out the relative contributions.

 

In addition to being a source of covariance that we need to account for, phylogeny can help us by identifying “natural experiments”. Specifically, knowledge of phylogeny allows us to identify repeated independent transitions in both traits and environments. For example, in eucalyptus there have been numerous phylogenetically independent transitions from wet to arid environments. This replication gives a chance to ask (a) if the Anna Karenina principle applies – that is, are all arid adapted eucalyptus species adapted in the same way?; and (b) if so, do the same genetic mechanisms underly repeated phenotypic shifts?

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