Multi-level exploration of biological nitrification inhibition in rice for improved sustainability of crop production
Lead Research Organisation:
University of Aberdeen
Department Name: Inst of Biological and Environmental Sci
Abstract
Context of the research
Agricultural output is currently dependent on the use of synthetic nitrogen fertilisers. However, while the use of nitrogen fertilisers is essential to meet food security targets, the current efficiency of nitrogen fertilisers can be low, with up to 50% of applied nitrogen lost to the environment. Most of this loss happens through microbial-based nitrification and nitrate leaching. Reducing these processes is essential to improving agricultural sustainability.
Soil nitrification can be inhibited through both chemical (synthetic) and biological (plant-based) processes, and the latter being termed Biological Nitrification Inhibition (BNI). A range of crops and grasses perform allelopathic BNI through secretion of specific root exudate compounds, which inhibit ammonia oxidising archaea and ammonia oxidising bacteria nitrifiers by blocking either the ammonia monooxygenase or hydroxylamine oxidoreductase, or through other pathways. Plant BNI efficiency was first demonstrated in some tropical pasture grasses. Since then, it has been shown in a wide range of plants, including heavily cultivated crops such as rice.
While a small number of rice root BNI compounds have been identified, these are from a limited number of genotypes, and while genotypic variation for BNI efficiency has been determined in rice, the genetic basis of this variation is unknown. Additionally, the potential impact of breeding for high BNI efficient genotypes has not been explored.
Research aims
The overall aim of this multi-disciplinary proposal is to investigate biological nitrification inhibition (BNI) efficiency in rice, by understanding the nature of natural variation in BNI efficiency of both domesticated and wild rice. This will be conducted through genetic mapping and functional genomics (to identify key genes involved in increasing BNI efficiency), characterising BNI compounds produced by rice, evaluating the impact of variation in BNI on soil microbial communities and processes and the use of modelling to evaluate the impact of increasing BNI efficiency in rice on nitrous oxide emissions from soil.
Research Objectives
1) Characterise how BNI efficiency changes during the growing season and how cultivation water management decisions impact rice BNI efficiency.
2) Identify genomic loci and genes for natural variation for BNI efficiency in domesticated rice (Oryza sativa).
3) Evaluate BNI efficiency of wild rice accessions to identify if BNI efficiency is greater in wild rice relatives, identify accessions with BNI traits to be used in breeding, and to conduct GWA mapping with the O. rufipogon species.
4) Identify BNI compounds and their influence on microbial communities.
5) Scale up the observed impacts to model the impact of BNI efficiency on N2O emissions at the country level
Potential applications and benefits
Genotypes with high BNI efficiency have the potential to slow down the nitrification of ammonium (NH4+) to nitrate (NO3-). As plants can utilise both NH4+ and NO3- as a nitrogen source, reducing the nitrification will not reduce nitrogen availability for plants. However, NO3- can easily leach into groundwater as it is much more mobile in the soil environment than NH4+. Additionally aerobic nitrification generates N2O through various processes, and under the right conditions nitrifiers can also convert NO3- into N2O via the denitrification process, with N2O being a potent greenhouse gas. Therefore, if plants could be bred with increased BNI efficiency there is the potential to decrease NO3- leaching, reduce N2O emissions from soil, and reduce the amount of nitrogen fertiliser used (as it will be available in the soils longer for the plants).
The use of systems modelling to evaluate the impact of high BNI efficient genotypes on greenhouse gas emissions, will promote for the prioritisation of breeding for high BNI efficiency targeting specific climatic, edaphic and management scenarios.
Agricultural output is currently dependent on the use of synthetic nitrogen fertilisers. However, while the use of nitrogen fertilisers is essential to meet food security targets, the current efficiency of nitrogen fertilisers can be low, with up to 50% of applied nitrogen lost to the environment. Most of this loss happens through microbial-based nitrification and nitrate leaching. Reducing these processes is essential to improving agricultural sustainability.
Soil nitrification can be inhibited through both chemical (synthetic) and biological (plant-based) processes, and the latter being termed Biological Nitrification Inhibition (BNI). A range of crops and grasses perform allelopathic BNI through secretion of specific root exudate compounds, which inhibit ammonia oxidising archaea and ammonia oxidising bacteria nitrifiers by blocking either the ammonia monooxygenase or hydroxylamine oxidoreductase, or through other pathways. Plant BNI efficiency was first demonstrated in some tropical pasture grasses. Since then, it has been shown in a wide range of plants, including heavily cultivated crops such as rice.
While a small number of rice root BNI compounds have been identified, these are from a limited number of genotypes, and while genotypic variation for BNI efficiency has been determined in rice, the genetic basis of this variation is unknown. Additionally, the potential impact of breeding for high BNI efficient genotypes has not been explored.
Research aims
The overall aim of this multi-disciplinary proposal is to investigate biological nitrification inhibition (BNI) efficiency in rice, by understanding the nature of natural variation in BNI efficiency of both domesticated and wild rice. This will be conducted through genetic mapping and functional genomics (to identify key genes involved in increasing BNI efficiency), characterising BNI compounds produced by rice, evaluating the impact of variation in BNI on soil microbial communities and processes and the use of modelling to evaluate the impact of increasing BNI efficiency in rice on nitrous oxide emissions from soil.
Research Objectives
1) Characterise how BNI efficiency changes during the growing season and how cultivation water management decisions impact rice BNI efficiency.
2) Identify genomic loci and genes for natural variation for BNI efficiency in domesticated rice (Oryza sativa).
3) Evaluate BNI efficiency of wild rice accessions to identify if BNI efficiency is greater in wild rice relatives, identify accessions with BNI traits to be used in breeding, and to conduct GWA mapping with the O. rufipogon species.
4) Identify BNI compounds and their influence on microbial communities.
5) Scale up the observed impacts to model the impact of BNI efficiency on N2O emissions at the country level
Potential applications and benefits
Genotypes with high BNI efficiency have the potential to slow down the nitrification of ammonium (NH4+) to nitrate (NO3-). As plants can utilise both NH4+ and NO3- as a nitrogen source, reducing the nitrification will not reduce nitrogen availability for plants. However, NO3- can easily leach into groundwater as it is much more mobile in the soil environment than NH4+. Additionally aerobic nitrification generates N2O through various processes, and under the right conditions nitrifiers can also convert NO3- into N2O via the denitrification process, with N2O being a potent greenhouse gas. Therefore, if plants could be bred with increased BNI efficiency there is the potential to decrease NO3- leaching, reduce N2O emissions from soil, and reduce the amount of nitrogen fertiliser used (as it will be available in the soils longer for the plants).
The use of systems modelling to evaluate the impact of high BNI efficient genotypes on greenhouse gas emissions, will promote for the prioritisation of breeding for high BNI efficiency targeting specific climatic, edaphic and management scenarios.
Technical Summary
Characterise how BNI efficiency changes during the growing season and how water management decisions impact rice BNI efficiency. This will involve screening rice genotypes that are known to have variation in BNI efficiency. Nitrification will be measured by nitrate accumulation over time, and nitrifier growth will be quantified by measuring the AOA and AOB abundance over time using a qPCR approach.
Identify genomic loci and genes for natural variation in BNI efficiency in domesticated rice using the RDP1 and BAAP populations. After BNI screening, GWA mapping will be conducted via the PIQUE pipeline utilising EMMA-X. Candidate genes will be identified based on proposed gene function. To validate these genes, knockout mutants will be evaluated for BNI efficiency, or if no mutants are available, we will use CRISPR/cas9 to create gene knockouts.
Evaluate BNI efficiency in wild rice species. Using a previously established association population of the wild rice O. rufipogon, we will conduct GWA mapping to identify novel loci for BNI efficiency. 20 accessions of three other wild species will also be screened for BNI.
Identify BNIs and their influence on microbial communities. The metabolic profile of selected rice cultivars will result in the identification of BNI compounds using LC-MS approaches. The BNI compounds will be tested separately and in combination for their BNI efficiency on nitrifier cultures. We will determine the impact of genotypes with high BNI efficiency on soil microbial communities using sequencing of amoA and 16S rRNA genes, and on nitrous oxide emissions from soil by collecting gas samples and analysing them using GC.
Scale up the observed impacts to model the impact of BNI efficiency on N2O emissions at the country level. We will model, using ECOSSE, the impact of growing high BNI efficient genotypes, at the field scale and country scale, on greenhouse gas emissions, therefore determining the likely benefit of increased BNI efficiency.
Identify genomic loci and genes for natural variation in BNI efficiency in domesticated rice using the RDP1 and BAAP populations. After BNI screening, GWA mapping will be conducted via the PIQUE pipeline utilising EMMA-X. Candidate genes will be identified based on proposed gene function. To validate these genes, knockout mutants will be evaluated for BNI efficiency, or if no mutants are available, we will use CRISPR/cas9 to create gene knockouts.
Evaluate BNI efficiency in wild rice species. Using a previously established association population of the wild rice O. rufipogon, we will conduct GWA mapping to identify novel loci for BNI efficiency. 20 accessions of three other wild species will also be screened for BNI.
Identify BNIs and their influence on microbial communities. The metabolic profile of selected rice cultivars will result in the identification of BNI compounds using LC-MS approaches. The BNI compounds will be tested separately and in combination for their BNI efficiency on nitrifier cultures. We will determine the impact of genotypes with high BNI efficiency on soil microbial communities using sequencing of amoA and 16S rRNA genes, and on nitrous oxide emissions from soil by collecting gas samples and analysing them using GC.
Scale up the observed impacts to model the impact of BNI efficiency on N2O emissions at the country level. We will model, using ECOSSE, the impact of growing high BNI efficient genotypes, at the field scale and country scale, on greenhouse gas emissions, therefore determining the likely benefit of increased BNI efficiency.
