Genetic diversity for nitrogen use efficiency in Arabidopsis thaliana.

Meyer RC, Gryczka C, Neitsch C, et al. Genetic diversity for nitrogen use efficiency in Arabidopsis thaliana. Planta. 2019;250(1):41-57.MAIN CONCLUSION: The plasticity of plant growth response to differing nitrate availability renders the identification of biomarkers difficult, but allows access to genetic factors as tools to modulate root systems to a wide range of soil conditions. Nitrogen availability is a major determinant of crop yield. While the application of fertiliser substantially increases the yield on poor soils, it also causes nitrate pollution of water resources and high costs for farmers. Increasing nitrogen use efficiency in crop plants is a necessary step to implement low-input agricultural systems. We exploited the genetic diversity present in the worldwide Arabidopsis thaliana population to study adaptive growth patterns and changes in gene expression associated with chronic low nitrate stress, to identify biomarkers associated with good plant performance under low nitrate availability. Arabidopsis accessions were grown on agar plates with limited and sufficient supply of nitrate to measure root system architecture as well as shoot and root fresh weight. Differential gene expression was determined using Affymetrix ATH1 arrays. We show that the response to differing nitrate availability is highly variable in Arabidopsis accessions. Analyses of vegetative shoot growth and root system architecture identified accession-specific reaction modes to cope with limited nitrate availability. Transcription and epigenetic factors were identified as important players in the adaption to limited nitrogen in a global gene expression analysis. Five nitrate-responsive genes emerged as possible biomarkers for NUE in Arabidopsis. The plasticity of plant growth in response to differing nitrate availability in the substrate renders the identification of morphological and molecular features as biomarkers difficult, but at the same time allows access to a multitude of genetic factors which can be used as tools to modulate and adjust root systems to a wide range of soil conditions

Genetic controls of short- and long-term stomatal CO2 responses in Arabidopsis thaliana

Background and Aims The stomatal conductance (g(s)) of most plant species decreases in response to elevated atmospheric CO2 concentration. This response could have a significant impact on plant water use in a future climate. However, the regulation of the CO2 induced stomatal closure response is not fully understood. Moreover, the potential genetic links between short-term (within minutes to hours) and long-term (within weeks to months) responses of g(s) to increased atmospheric CO2 have not been explored. Methods We used Arabidopsis thaliana recombinant inbred lines originating from accessions Col-0 (strong CO2 response) and C24 (weak CO2 response) to study short- and long-term controls of g(s) Quantitative trait locus (QTL) mapping was used to identify loci controlling short- and long-term g(s) responses to elevated CO2 as well as other stomata-related traits. Key Results Short- and long-term stomatal responses to elevated CO2 were significantly correlated. Both short-and long-term responses were associated with a QTL, at the end of chromosome 2. The location of this QTL was confirmed using near-isogonic lines and it was fine-mapped to a 410-kb region. The QTL did not correspond to any known gene involved in stomatal closure and had no effect on the responsiveness to abscisic acid. Additionally, we identified numerous other loci associated with stomatal regulation. Conclusions We identified and confirmed the effect of a strong QTL corresponding to a yet unknown regulator of stomatal closure in response to elevated CO2 concentration. The correlation between short- and long-term stomatal CO2 responses and the genetic link between these traits highlight the importance of understanding guard cell CO2 signalling to predict and manipulate plant water use in a world with increasing atmospheric CO2 concentration. This study demonstrates the power of using natural variation to unravel the genetic regulation of complex traits.Peer reviewe

Prediction of hybrid biomass in Arabidopsis thaliana by selected parental SNP and metabolic markers

A recombinant inbred line (RIL) population, derived from two Arabidopsis thaliana accessions, and the corresponding testcrosses with these two original accessions were used for the development and validation of machine learning models to predict the biomass of hybrids. Genetic and metabolic information of the RILs served as predictors. Feature selection reduced the number of variables (genetic and metabolic markers) in the models by more than 80% without impairing the predictive power. Thus, potential biomarkers have been revealed. Metabolites were shown to bear information on inherited macroscopic phenotypes. This proof of concept could be interesting for breeders. The example population exhibits substantial mid-parent biomass heterosis. The results of feature selection could therefore be used to shed light on the origin of heterosis. In this respect, mainly dominance effects were detected

Improved Heterosis Prediction by Combining Information on DNA- and Metabolic Markers

Background: Hybrids represent a cornerstone in the success story of breeding programs. The fundamental principle underlying this success is the phenomenon of hybrid vigour, or heterosis. It describes an advantage of the offspring as compared to the two parental lines with respect to parameters such as growth and resistance against abiotic or biotic stress. Dominance, overdominance or epistasis based models are commonly used explanations. Conclusion/Significance: The heterosis level is clearly a function of the combination of the parents used for offspring production. This results in a major challenge for plant breeders, as usually several thousand combinations of parents have to be tested for identifying the best combinations. Thus, any approach to reliably predict heterosis levels based on properties of the parental lines would be highly beneficial for plant breeding. Methodology/Principal Findings: Recently, genetic data have been used to predict heterosis. Here we show that a combination of parental genetic and metabolic markers, identified via feature selection and minimum-description-length based regression methods, significantly improves the prediction of biomass heterosis in resulting offspring. These findings will help furthering our understanding of the molecular basis of heterosis, revealing, for instance, the presence of nonlinear genotype-phenotype relationships. In addition, we describe a possible approach for accelerated selection in plant breeding

Heterosis of Biomass Production in Arabidopsis. Establishment during Early Development

Heterosis has been widely used in agriculture to increase yield and to broaden adaptability of hybrid varieties and is applied to an increasing number of crop species. We performed a systematic survey of the extent and degree of heterosis for dry biomass in 63 Arabidopsis accessions crossed to three reference lines (Col-0, C24, and Nd). We detected a high heritability (69%) for biomass production in Arabidopsis. Among the 169 crosses analyzed, 29 exhibited significant mid-parent-heterosis for shoot biomass. Furthermore, we analyzed two divergent accessions, C24 and Col-0, the F(1) hybrids of which were shown to exhibit hybrid vigor, in more detail. In the combination Col-0/C24, heterosis for biomass was enhanced at higher light intensities; we found 51% to 66% mid-parent-heterosis at low and intermediate light intensities (60 and 120 μmol m(−2) s(−1)), and 161% at high light intensity (240 μmol m(−2) s(−1)). While at the low and intermediate light intensities relative growth rates of the hybrids were higher only in the early developmental phase (0–15 d after sowing [DAS]), at high light intensity the hybrids showed increased relative growth rates over the entire vegetative phase (until 25 DAS). An important finding was the early onset of heterosis for biomass; in the cross Col-0/C24, differences between parental and hybrid lines in leaf size and dry shoot mass could be detected as early as 10 DAS. The widespread occurrence of heterosis in the model plant Arabidopsis opens the possibility to investigate the genetic basis of this phenomenon using the tools of genetical genomics

Establishment of integrated protocols for automated high throughput kinetic chlorophyll fluorescence analyses

Abstract Background Automated plant phenotyping has been established as a powerful new tool in studying plant growth, development and response to various types of biotic or abiotic stressors. Respective facilities mainly apply non-invasive imaging based methods, which enable the continuous quantification of the dynamics of plant growth and physiology during developmental progression. However, especially for plants of larger size, integrative, automated and high throughput measurements of complex physiological parameters such as photosystem II efficiency determined through kinetic chlorophyll fluorescence analysis remain a challenge. Results We present the technical installations and the establishment of experimental procedures that allow the integrated high throughput imaging of all commonly determined PSII parameters for small and large plants using kinetic chlorophyll fluorescence imaging systems (FluorCam, PSI) integrated into automated phenotyping facilities (Scanalyzer, LemnaTec). Besides determination of the maximum PSII efficiency, we focused on implementation of high throughput amenable protocols recording PSII operating efficiency (ΦPSII). Using the presented setup, this parameter is shown to be reproducibly measured in differently sized plants despite the corresponding variation in distance between plants and light source that caused small differences in incident light intensity. Values of ΦPSII obtained with the automated chlorophyll fluorescence imaging setup correlated very well with conventionally determined data using a spot-measuring chlorophyll fluorometer. The established high throughput operating protocols enable the screening of up to 1080 small and 184 large plants per hour, respectively. The application of the implemented high throughput protocols is demonstrated in screening experiments performed with large Arabidopsis and maize populations assessing natural variation in PSII efficiency. Conclusions The incorporation of imaging systems suitable for kinetic chlorophyll fluorescence analysis leads to a substantial extension of the feature spectrum to be assessed in the presented high throughput automated plant phenotyping platforms, thus enabling the simultaneous assessment of plant architectural and biomass-related traits and their relations to physiological features such as PSII operating efficiency. The implemented high throughput protocols are applicable to a broad spectrum of model and crop plants of different sizes (up to 1.80 m height) and architectures. The deeper understanding of the relation of plant architecture, biomass formation and photosynthetic efficiency has a great potential with respect to crop and yield improvement strategies