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Abstract Premise: The agar‐based culture of Arabidopsis seedlings is widely used for quantifying root traits. Shoot traits are generally overlooked in these studies, probably because the rosettes are often askew. A technique to assess the shoot surface area of seedlings grown inside agar culture dishes would facilitate simultaneous root and shoot phenotyping. Methods: We developed an image processing workflow in Python that estimates rosette area of Arabidopsis seedlings on agar culture dishes. We validated this method by comparing its output with other metrics of seedling growth. As part of a larger study on genetic variation in plant responses to nitrogen form and concentration, we measured the rosette areas from more than 2000 plate images. Results: The rosette area measured from plate images was strongly correlated with the rosette area measured from directly overhead and moderately correlated with seedling mass. Rosette area in the large image set was significantly influenced by genotype and nitrogen treatment. The broad‐sense heritability of leaf area measured using this method was 0.28. Discussion: These results indicated that this approach for estimating rosette area produces accurate shoot phenotype data. It can be used with image sets for which other methods of leaf area quantification prove unsuitable. 

The rhizosphere microbiome influences many aspects of plant fitness, including production of secondary compounds and defence against insect herbivores. Plants also modulate the composition of the microbial community in the rhizosphere via secretion of root exudates. We tested both the effect of the rhizosphere microbiome on plant traits, and host plant effects on rhizosphere microbes using recombinant inbred lines (RILs) ofBrassica rapathat differ in production of glucosinolates (GLS), secondary metabolites that contribute to defence against insect herbivores. First, we investigated the effect of genetic variation in GLS production on the composition of the rhizosphere microbiome. Using a Bayesian Dirichlet‐multinomial regression model (DMBVS), we identified both negative and positive associations between bacteria from six genera and the concentration of five GLS compounds produced in plant roots. Additionally, we tested the effects of microbial inoculation (an intact vs. disrupted soil microbiome) on GLS production and insect damage in these RILs. We found a significant microbial treatment × genotype interaction, in which total GLS was higher in the intact relative to the disrupted microbiome treatment in some RILs. However, despite differences in GLS production between microbial treatments, we observed no difference in insect damage between treatments. Together, these results provide evidence for a full feedback cycle of plant–microbe interactions mediated by GLS; that is, GLS compounds produced by the host plant “feed‐down” to influence rhizosphere microbial community and rhizosphere microbes “feed‐up” to influence GLS production.

 

Nitrogen is an essential element required for plant growth and productivity. Understanding the mechanisms and natural genetic variation underlying nitrogen use in plants will facilitate the engineering of plant nitrogen use to maximize crop productivity while minimizing environmental costs. To understand the scope of natural variation that may influence nitrogen use, we grew 1,135 Arabidopsis thaliana natural genotypes on two nitrogen sources, nitrate and ammonium, and measured both developmental and defense metabolite traits. By using different environments and focusing on multiple traits, we identified a wide array of different nitrogen responses. These responses are associated with numerous genes, most of which were not previously associated with nitrogen responses. Only a small portion of these genes appear to be shared between environments or traits, while most are predominantly specific to a developmental or defense trait under a specific nitrogen source. Finally, by using a large population, we were able to identify unique nitrogen responses, such as preferring ammonium or nitrate, which appear to be generated by combinations of loci rather than a few large-effect loci. This suggests that it may be possible to obtain novel phenotypes in complex nitrogen responses by manipulating sets of genes with small effects rather than solely focusing on large-effect single gene manipulations.

 

Plants produce diverse metabolites to cope with the challenges presented by complex and ever-changing environments. These challenges drive the diversification of specialized metabolites within and between plant species. However, we are just beginning to understand how frequently new alleles arise controlling specialized metabolite diversity and how the geographic distribution of these alleles may be structured by ecological and demographic pressures. Here we measure the variation in specialized metabolites across a population of 797 natural Arabidopsis thaliana accessions. We show a combination of geography, environmental parameters, demography, and different genetic processes all combine to influence the specific chemotypes and their distribution. This showed that causal loci in specialized metabolism contain frequent independently generated alleles with patterns suggesting potential within species convergence. This provides a new perspective about the complexity of the selective forces and mechanisms that shape the generation and distribution of allelic variation that may influence local adaptation. 

The receptor kinase FERONIA (FER) is a versatile regulator of plant growth and development, biotic and abiotic stress responses, and reproduction. To gain new insights into the molecular interplay of these processes and to identify new FER functions, we carried out quantitative transcriptome, proteome, and phosphoproteome profiling of Arabidopsis (Arabidopsis thaliana) wild-type and fer-4 loss-of-function mutant plants. Gene ontology terms for phytohormone signaling, abiotic stress, and biotic stress were significantly enriched among differentially expressed transcripts, differentially abundant proteins, and/or misphosphorylated proteins, in agreement with the known roles for FER in these processes. Analysis of multiomics data and subsequent experimental evidence revealed previously unknown functions for FER in endoplasmic reticulum (ER) body formation and glucosinolate biosynthesis. FER functions through the transcription factor NAI1 to mediate ER body formation. FER also negatively regulates indole glucosinolate biosynthesis, partially through NAI1. Furthermore, we found that a group of abscisic acid (ABA)-induced transcription factors is hypophosphorylated in the fer-4 mutant and demonstrated that FER acts through the transcription factor ABA INSENSITIVE5 (ABI5) to negatively regulate the ABA response during cotyledon greening. Our integrated omics study, therefore, reveals novel functions for FER and provides new insights into the underlying mechanisms of FER function.