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Abstract The karrikin (KAR) receptor and several related signaling components have been identified by forward genetic screening, but only a few studies have reported on upstream and downstream KAR signaling components and their roles in drought tolerance. Here, we characterized the functions of KAR UPREGULATED F-BOX 1 (KUF1) in drought tolerance using a reverse genetics approach in Arabidopsis (Arabidopsis thaliana). We observed that kuf1 mutant plants were more tolerant to drought stress than wild-type (WT) plants. To clarify the mechanisms by which KUF1 negatively regulates drought tolerance, we performed physiological, transcriptome, and morphological analyses. We found that kuf1 plants limited leaf water loss by reducing stomatal aperture and cuticular permeability. In addition, kuf1 plants showed increased sensitivity of stomatal closure, seed germination, primary root growth, and leaf senescence to abscisic acid (ABA). Genome-wide transcriptome comparisons of kuf1 and WT rosette leaves before and after dehydration showed that the differences in various drought tolerance-related traits were accompanied by differences in the expression of genes associated with stomatal closure (e.g. OPEN STOMATA 1), lipid and fatty acid metabolism (e.g. WAX ESTER SYNTHASE), and ABA responsiveness (e.g. ABA-RESPONSIVE ELEMENT 3). The kuf1 mutant plants had higher root/shoot ratios and root hair densities than WT plants, suggesting that they could absorb more water than WT plants. Together, these results demonstrate that KUF1 negatively regulates drought tolerance by modulating various physiological traits, morphological adjustments, and ABA responses and that the genetic manipulation of KUF1 in crops is a potential means of enhancing their drought tolerance.
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SMART: An open and affordable plant phenotyping system for leaf-specific color analysis of the Arabidopsis Rosette
Challenge : Most plant imaging systems focus predominantly on monitoring morphological traits. The challenge is to relate color information to measurements of physiological processes. Question: Can the color of individual leaves be measured and quantified over time to infer physiological information about the plant? Solution: We developed the open source and affordable plant phenotyping software pipeline for Arabidopsis thaliana. SMART (Speedy Measurement of Arabidopsis Rosette Traits) that integrates a new color analysis algorithm to measure leaf surface temperature, leaf wilting and zinc toxicity over time. Data Collection: We used public datasets to develop the algorithm [1] and validate morphological measurements. We also collected top-view images of the Arabidopsis rosette with the Open-Leaf
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- Award ID(s):
- 1845760
- PAR ID:
- 10438563
- Date Published:
- Journal Name:
- ASPB Meeting 2023 (Poster)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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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.more » « less
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SUMMARY The first draft of the Arabidopsis genome was released more than 20 years ago and despite intensive molecular research, more than 30% of Arabidopsis genes remained uncharacterized or without an assigned function. This is in part due to gene redundancy within gene families or the essential nature of genes, where their deletion results in lethality (i.e., thedark genome). High‐throughput plant phenotyping (HTPP) offers an automated and unbiased approach to characterize subtle or transient phenotypes resulting from gene redundancy or inducible gene silencing; however, access to commercial HTPP platforms remains limited. Here we describe the design and implementation ofOPEN leaf, an open‐source phenotyping system with cloud connectivity and remote bilateral communication to facilitate data collection, sharing and processing.OPEN leaf, coupled with our SMART imaging processing pipeline was able to consistently document and quantify dynamic changes at the whole rosette level and leaf‐specific resolution when plants experienced changes in nutrient availability. Our data also demonstrate that VIS sensors remain underutilized and can be used in high‐throughput screens to identify and characterize previously unidentified phenotypes in a leaf‐specific time‐dependent manner. Moreover, the modular and open‐source design ofOPEN leafallows seamless integration of additional sensors based on users and experimental needs.more » « less
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Abstract Trees are arguably the most diverse and complex macro-organisms on Earth. The equally diverse functions of trees directly impact fluxes of carbon, water and energy from the land surface. A number of recent studies have shed light on the substantial within-species variability across plant traits, including aspects of leaf morphology and plant allocation of photosynthates to leaf biomass. Yet, within-tree variability in leaf traits due to microclimatic variations, leaf hydraulic coordination across traits at different physiological scales and variations in leaf traits over a growing season remain poorly studied. This knowledge gap is stymieing the fundamental understanding of what drives trait variation and covariation from tissues to trees to landscapes. Here, we present an extensive dataset measuring within-tree heterogeneity in leaf traits in California’s blue oak (Quercus douglasii) across an edaphic gradient and over the course of a growing season at an oak–grass savanna in Southern CA, USA. We found a high level of within-tree crown leaf area:sapwood area variation that was not attributable to sample height or aspect. We also found a higher level of trait integration at the tree level, rather than branch level, suggesting that trees optimize water use at the organismal level. Despite the large variance in traits within a tree crown and across trees, we did not find strong evidence for adaptive plasticity or acclimation in leaf morphological traits (e.g., changes to phenotype which increased fitness) across temporal and spatial water availability gradients. Collectively, our results highlight strong variation in drought-related physiology, but limited evidence for adaptive trait plasticity over shorter time scales.more » « less
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Abstract Argonaute 1 (AGO1), the principal protein component of microRNA-mediated regulation, plays a key role in plant growth and development. AGO1 physically interacts with the chaperone HSP90, which buffers cryptic genetic variation in plants and animals. We sought to determine whether genetic perturbation of AGO1 in Arabidopsis thaliana would also reveal cryptic genetic variation, and if so, whether AGO1-dependent loci overlap with those dependent on HSP90. To address these questions, we introgressed a hypomorphic mutant allele of AGO1 into a set of mapping lines derived from the commonly used Arabidopsis strains Col-0 and Ler. Although we identified several cases in which AGO1 buffered genetic variation, none of the AGO1-dependent loci overlapped with those buffered by HSP90 for the traits assayed. We focused on 1 buffered locus where AGO1 perturbation uncoupled the traits days to flowering and rosette leaf number, which are otherwise closely correlated. Using a bulk segregant approach, we identified a nonfunctional Ler hua2 mutant allele as the causal AGO1-buffered polymorphism. Introduction of a nonfunctional hua2 allele into a Col-0 ago1 mutant background recapitulated the Ler-dependent ago1 phenotype, implying that coupling of these traits involves different molecular players in these closely related strains. Taken together, our findings demonstrate that even though AGO1 and HSP90 buffer genetic variation in the same traits, these robustness regulators interact epistatically with different genetic loci, suggesting that higher-order epistasis is uncommon. Plain Language Summary Argonaute 1 (AGO1), a key player in plant development, interacts with the chaperone HSP90, which buffers environmental and genetic variation. We found that AGO1 buffers environmental and genetic variation in the same traits; however, AGO1-dependent and HSP90-dependent loci do not overlap. Detailed analysis of a buffered locus found that a nonfunctional HUA2 allele decouples days to flowering and rosette leaf number in an AGO1-dependent manner, suggesting that the AGO1-dependent buffering acts at the network level.more » « less
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