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Organisms adopt a wide range of strategies to adapt to change. Gene silencing describes the ability of organisms to modulate the expression of susceptible genes at certain times at the transcriptional or the translational level. In all known eukaryotic organisms 21-nucleotide long short interfering RNAs (siRNAs) are the effector molecules of post-transcriptional gene silencing, while 24-nucleotide long siRNAs are involved in transcriptional gene silencing in plants. Mutant studies in Caenorhabditis elegans lead to the identification of the enzyme ERI (Enhancer of RNAinterference) with enhanced post-transcriptional gene silencing. Although the genes involved in growth vigor and growth rate are still unknown, it becomes clearer that the population of small RNAs plays a role in the very early phase of plant development. To pinpoint the link between growth and siRNAs, the expression of Arabidopsis uni-gene Enhancer of RNAi (ERI) homolog from C.elegans was modulated. Increased degradation of small RNAs was achieved by ectopic AtERI overexpression in planta. Based on global small RNA analysis, AtERI overexpression affects mainly the population of 21mers, excluding miRNAs. To identify target genes, AtERI gain-of-function mutants were analyzed, and differentially abundant small RNAs were identified. Plants with an elevated level of AtERI were bigger in all three light intensities analyzed, indicating an inhibitory function of particular small RNAs in plant growth, with differences in RGRs depending on developmental stage and light intensity. Understanding the role of these siRNAs could open new avenues for enhancing plant growth.

Detailed and standardized protocols for plant cultivation in environmentally controlled conditions are an essential prerequisite to conduct reproducible experiments with precisely defined treatments. Setting up appropriate and well defined experimental procedures is thus crucial for the generation of solid evidence and is thus indispensable for successful plant research. Non-invasive and high throughput (HT) phenotyping technologies offer the opportunity to monitor and quantify performance dynamics of several hundreds of plants at a time. Compared to small scale plant cultivations, HT systems have much higher demands, from a conceptual and a logistic point of view, on experimental design, as well as the actual plant cultivation conditions, and the image analysis and statistical methods for data evaluation. Furthermore, cultivation conditions need to be designed that elicit plant performance characteristics corresponding to those under natural conditions. This manuscript describes critical steps in the optimization of procedures for HT plant phenotyping systems. Starting with the model plant Arabidopsis, HT-compatible methods were tested, and optimized with regard to growth substrate, soil coverage, watering regime, experimental design (considering environmental inhomogeneities) in automated plant cultivation and imaging systems. As revealed by metabolite profiling, plant movement did not affect the plants’ physiological status. Based on these results, procedures for maize HT cultivation and monitoring were established. Variation of maize vegetative growth in the HT phenotyping system did match well with that observed in the field. The presented results outline important issues to be considered in the design of HT phenotyping experiments for model and crop plants. It thereby provides guidelines for the setup of HT experimental procedures, which are required for the generation of reliable and reproducible data of phenotypic variation for a broad range of applications.

There has been much excitement about the possibility that exposure to specific environments can induce an ecological memory in the form of whole-sale, genome-wide epigenetic changes that are maintained over many generations. In the model plant Arabidopsis thaliana, numerous heritable DNA methylation differences have been identified in greenhouse-grown isogenic lines, but it remains unknown how natural, highly variable environments affect the rate and spectrum of such changes. Here we present detailed methylome analyses in a geographically dispersed A. thaliana population that constitutes a collection of near-isogenic lines, diverged for at least a century from a common ancestor. Methylome variation largely reflected genetic distance, and was in many aspects similar to that of lines raised in uniform conditions. Thus, even when plants are grown in varying and diverse natural sites, genome-wide epigenetic variation accumulates mostly in a clock-like manner, and epigenetic divergence thus parallels the pattern of genome-wide DNA sequence divergence.

Seedling establishment is inhibited on media containing high levels (∼ 6%) of glucose or fructose. Genetic loci that overcome the inhibition of seedling growth on high sugar have been identified using natural variation analysis and mutant selection, providing insight into sugar signaling pathways. In this study, a quantitative trait locus (QTL) analysis was performed for seedling sensitivity to high sugar in a Col/C24 F2 population of Arabidopsis thaliana. A glucose and fructose-sensing QTL, GSQ11, was mapped through selective genotyping and confirmed in near-isogenic lines in both Col and C24 backgrounds. Allelism tests and transgenic complementation showed that GSQ11 lies within the ANAC060 gene. The Col ANAC060 allele confers sugar insensitivity and was dominant over the sugar-sensitive C24 allele. Genomic and mRNA analyses showed that a single-nucleotide polymorphism (SNP) in Col ANAC060 affects the splicing patterns of ANAC060 such that 20 additional nucleotides are present in the mRNA. The insertion created a stop codon, resulting in a truncated ANAC60 protein lacking the transmembrane domain (TMD) that is present in the C24 ANAC060 protein. The absence of the TMD results in the nuclear localization of ANAC060. The short version of the ANAC060 protein is found in ∼ 12% of natural Arabidopsis accessions. Glucose induces GSQ11/ANAC060 expression in a process that requires abscisic acid (ABA) signaling. Chromatin immunoprecipitation-qPCR and transient expression analysis showed that ABI4 directly binds to the GSQ11/ANAC060 promoter to activate transcription. Interestingly, Col ANAC060 reduced ABA sensitivity and Glc-induced ABA accumulation, and ABI4 expression was also reduced in Col ANAC060 lines. Thus, the sugar-ABA signaling cascade induces ANAC060 expression, but the truncated Col ANAC060 protein attenuates ABA induction and ABA signaling. This negative feedback from nuclear ANAC060 on ABA signaling results in sugar insensitivity.

To contribute to a further insight into heterosis we applied an integrative analysis to a systems biological network approach and a quantitative genetics analysis towards biomass heterosis in early Arabidopsis thaliana development. The study was performed on the parental accessions C24 and Col-0 and the reciprocal crosses. In an over-representation analysis it was tested if the overlap between the resulting gene lists of the two approaches is significantly larger than expected by chance. Top ranked genes in the results list of the systems biological analysis were significantly over-represented in the heterotic QTL candidate regions for either hybrid as well as regarding mid-parent and best-parent heterosis. This suggests that not only a few but rather several genes that influence biomass heterosis are located within each heterotic QTL region. Furthermore, the overlapping resulting genes of the two integrated approaches were particularly enriched in biomass related pathways. A chromosome-wise over-representation analysis gave rise to the hypothesis that chromosomes number 2 and 4 probably carry a majority of the genes involved in biomass heterosis in the early development of Arabidopsis thaliana.

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.

Plant roots elongate under mild nitrogen deficiency as part of a foraging response that facilitates nutrient uptake. Here the authors show that natural variation in this response among Arabidopsis accessions depends on the brassinosteroid (BR) signaling kinase BSK3, which can enhance BR sensitivity and root growth.

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.

Nitrogen (N) is a macronutrient determining crop yield. The application of N fertilisers can substantially increase the yield, but excess use also causes the nitrate pollution of water resources and increases production costs. Increasing N use efficiency (NUE) in crop plants is an important step to implement low-input agricultural systems. We used Arabidopsis thaliana as model system to investigate the natural genetic diversity in traits related to NUE. Natural variation was used to study adaptive growth patterns and changes in gene expression associated with limited nitrate availability. A genome-wide association study revealed an association of eight SNP markers on Chromosome 1 with shoot growth under limited N. The identified linkage disequilibrium (LD) interval includes the DNA sequences of three cysteine/histidine-rich C1 domain proteins in tandem orientation. These genes differ in promoter structure, methylation pattern and expression level among accessions, correlating with growth performance under N deficiency. Our results suggest the involvement of epigenetic regulation in the expression of NUE-related traits.