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Transcriptome-based prediction of nitrogen use efficiency in Arabidopsis and maize - I

ABSTRACT: Transcriptome-based prediction of nitrogen use efficiency in Arabidopsis and maize - I

PROVIDER: PRJNA638728 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR11993700.fastq.gz	Fastqsanger.gz
	SRR11993800.fastq.gz	Fastqsanger.gz
	SRR11993701.fastq.gz	Fastqsanger.gz
	SRR11993801.fastq.gz	Fastqsanger.gz
	SRR11993702.fastq.gz	Fastqsanger.gz

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ZmNRT1.1B (ZmNPF6.6) determines nitrogen use efficiency via regulation of nitrate transport and assimilation in maize

Project description:Nitrate (NO3-) is crucial for optimal plant growth and development and often limits crop productivity at the low availability. In comparison with model plant Arabidopsis, the molecular mechanisms underlying NO3- acquisition and utilization remain largely unclear in maize. In particular, only a few genes have been exploited to improve nitrogen use efficiency (NUE). Here, we demonstrated that NO3--inducible ZmNRT1.1B (ZmNPF6.6) positively regulated NO3--dependent growth and NUE in maize. We showed that the tandem duplicated proteoform ZmNRT1.1C is irrelevant to maize seedling growth under nitrate supply, however, loss-of-function of ZmNRT1.1B significantly weakened plant growth under adequate NO3- supply in both hydroponic and field conditions. 15N-labeled NO3- absorption assay indicated that ZmNRT1.1B mediated high-affinity NO3--transport and root-to-shoot NO3- translocation. Furthermore, upon NO3- supply, ZmNRT1.1B promotes cytoplasmic-to-nuclear shuttling of ZmNLP3.1 (ZmNLP8), which co-regulates the expression of genes involved in NO3- response, cytokinin biosynthesis and carbon metabolism. Remarkably, overexpression of ZmNRT1.1B in modern maize hybrids improved grain yield under nitrogen (N) limiting fields. Taken together, our study revealed a crucial role of ZmNRT1.1B in high-affinity NO3- transport and signaling and offers valuable genetic resource for breeding nitrogen use efficient high-yield cultivars.

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Transcriptome-based prediction of nitrogen use efficiency in Arabidopsis and maize - I

Project description:Inferring phenotypic outcome from genomics features is the promise and challenge for basic and applied research. Functionally testing whether the feature(s) with predictive power can shed light on the underlying mechanism remains largely unexplored. We address these gaps by applying a machine learning approach to predict phenotypes based on transcriptome data. We validate the predictive models in silico using out-of-sample varieties and in planta by reverse genetics. Our study primarily focuses on a agronomic trait nitrogen use efficiency (NUE), but the described approach can be applied to any phenotype across biology, agriculture and medicine. We measure NUE and gene expression from natural and cultivated varieties of Arabidopsis and maize, respectively, under low and high N environments. We integrate transcriptomics across a model and a crop and demonstrate that identifying the evolutionarily conserved N-responsive differentially expressed genes is an efficient technique to reduce the feature dimensionality, which ultimately improves the predictive power of the gene-to-trait models learned. Furthermore, including a model organism with a comprehensive mutant collection has enabled the efficient validation of the role candidate genes with predictive power in NUE outcomes. Using the matched transcriptomic and phenotypic data from a model and crop species, we present an analysis pipeline to infer a complex trait from transcript abundance. This analysis pipeline can be applied to any other organisms to uncover novel genes underpinning physiological traits of interest.

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ZmNRT1.1B (ZmNPF6.6) determines nitrogen use efficiency via regulation of nitrate transport and assimilation in maize

Project description:ZmNRT1.1B (ZmNPF6.6) determines nitrogen use efficiency via regulation of nitrate transport and assimilation in maize

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Would reducing chlorophyll content result in a higher photosynthesis nitrogen use efficiency in crops?

Project description:Decreasing antenna size is regarded as a potential strategy to improve photosynthesis for higher yield potential. Reducing chlorophyll content has been used as a strategy to decrease antenna size. One of the commonly cited benefits of this strategy has been its ability to improve crop nitrogen use efficiency; however, field evidence for this so far is limited. Here we used a mutant, p35s-Ami-YGL1, which has a lower chlorophyll content and also lower antenna size, to study the impacts of modifying leaf chlorophyll content on tissue nitrogen content and nitrogen use efficiency of plants. We show that the nitrogen contents for different tissues, including the seed tissue, on a weight basis were increased in p35s-Ami-YGL1, together with a decrease in C: N. Concurrently, we found that tissue carbon content decreased, while the content of chlorophyll precursors increased. These results suggest that the observed increase in tissue nitrogen content in Ami-YGL1 does not reflect an increase in plant nitrogen absorption or use efficiency, rather it is a result of stunted carbon fixation capacity of plants. The observed increase in seed nitrogen content in Ami-YGL1 suggests a potential strategy to increase seed nitrogen content in crops.

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Would reducing chlorophyll content result in a higher photosynthesis nitrogen use efficiency in crops?

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Root gene expression profiles of two maize inbred lines (Lo5 and T250) in response to nitrate treatment

Project description:Among the mineral elements necessary for plant growth, nitrogen (N) is the macronutrient required in larger amounts. The optimization of N use efficiency (NUE) in maize could be obtained through both genetic improvement and agronomic practices in order to enhance production and reduce the negative impact of the N fertilizer use on the environment. Physiological characterizations of inbred lines with different NUE are available in maize.

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