Delivery of Cas9/sgRNA RNPs and DNA vectors designed to transiently express morphogenic regulatory genes or an antibiotic resistance gene enabled efficient recovery of gene edited onion lines. We developed a protocol for efficiently producing gene edited onion plants that does not depend on stable transformation. The process makes use of transient gene expression to enrich for gene editing among plants regenerated from immature embryos bombarded with ribonucleoprotein (RNP) complexes composed of CRISPR-associated protein 9 (Cas9) and single guide RNAs (sgRNAs). We used the Allium cepa Downy Mildew Resistant 6 (AcDMR6) gene as the target gene for our studies and produced a total of 47 onion plants with edited AcDMR6 alleles, including 13 homozygous plants, 12 biallelic plants, 7 heterozygous plants, and 15 chimeric plants. The most effective strategy for producing gene edited onion plants involved co-delivering plasmids encoding a hygromycin-resistance protein and plant developmental regulator genes along with the Cas9/sgRNA RNPs followed by transient Hygromycin selection for 48 h. Using this approach, up to 12

KEY MESSAGE:SpG Cas9 significantly expands the genome editing scope in carrot with NGN PAM recognition.

The formation of complex traits is the consequence of genotype and activities at multiple molecular levels. However, connecting genotypes and these activities to complex traits remains challenging. Here, we investigate whether integrating genomic, transcriptomic, and methylomic data can improve prediction for six Arabidopsis traits. We find that transcriptome- and methylome-based models have performances comparable to those of genome-based models. However, models built for flowering time using different omics data identify different benchmark genes. Nine additional genes identified as important for flowering time from our models are experimentally validated as regulating flowering. Gene contributions to flowering time prediction are accession-dependent and distinct genes contribute to trait prediction in different genotypes. Models integrating multi-omics data perform best and reveal known and additional gene interactions, extending knowledge about existing regulatory networks underlying flowering time determination. These results demonstrate the feasibility of revealing molecular mechanisms underlying complex traits through multi-omics data integration.

Main conclusion This review describes the potential use of two novel transformation methodologies, GRF-GIF and GRF-GIF-BBM, for improving the regeneration efficiency of genome-edited recalcitrant plants.

Hybrid cultivars are valuable in many crop species due to their high yield, uniformity, and other desirable traits. Doubled haploids, which have two identical sets of chromosomes, are valuable for hybrid breeding because they can be produced in one generation, in comparison to the multigenerational process typically used to produce inbred parents for hybrid production. One method to produce haploid plants is manipulation of centromeric histone H3 (CENH3). This method of producing haploids has so far been successful in Arabidopsis, maize (Zea mays), and wheat (Triticum aestivum). Here we describe modification of CENH3 in carrot (Daucus carota) to test for the ability of these modifications to induce uniparental genome elimination, which is the basis for haploid induction. Base editing was used to make cenh3 mutant plants with amino acid substitutions in the region of CENH3 encoding the histone fold domain. These cenh3 mutant plants were then outcrossed with CENH3 wild-type plants. Using PCR-based genotyping assays, we identified two candidates for genome elimination. One candidate was classified as a putative aneuploid plant in which chromosome 7 is in a single copy state. The other candidate was characterized as a putative tetraploid that was likely haploid during its genesis. Our results suggest that this putative tetraploid inherited all of its chromosomes from the CENH3 wild-type parent and that the genome of the cenh3 mutant plant was lost. This study provides evidence that modification of CENH3 in carrot has the potential to induce genome elimination and ploidy changes in carrot.

Summary Revealing the contributions of genes to plant phenotype is frequently challenging because loss‐of‐function effects may be subtle or masked by varying degrees of genetic redundancy. Such effects can potentially be detected by measuring plant fitness, which reflects the cumulative effects of genetic changes over the lifetime of a plant. However, fitness is challenging to measure accurately, particularly in species with high fecundity and relatively small propagule sizes such as Arabidopsis thaliana. An image segmentation‐based method using the software ImageJ and an object detection‐based method using the Faster Region‐based Convolutional Neural Network (R‐CNN) algorithm were used for measuring two Arabidopsis fitness traits: seed and fruit counts. The segmentation‐based method was error‐prone (correlation between true and predicted seed counts, r2 = 0.849) because seeds touching each other were undercounted. By contrast, the object detection‐based algorithm yielded near perfect seed counts (r2 = 0.9996) and highly accurate fruit counts (r2 = 0.980). Comparing seed counts for wild‐type and 12 mutant lines revealed fitness effects for three genes; fruit counts revealed the same effects for two genes. Our study provides analysis pipelines and models to facilitate the investigation of Arabidopsis fitness traits and demonstrates the importance of examining fitness traits when studying gene functions.

We have developed and validated an efficient protocol for producing gene-edited carrot plants that do not result in the stable incorporation of foreign DNA in the edited plant’s genome. We report here a method for producing transgene-free, gene-edited carrot (Daucus carota subs. sativus) plants. With this approach, PEG-mediated transformation is used to transiently express a cytosine base editor and a guide RNA in protoplasts to induce targeted mutations in the carrot genome. These protoplasts are then cultured under conditions that lead to the production of somatic embryos which subsequently develop into carrot plants. For this study, we used the Centromere-Specific Histone H3 (CENH3) gene as a target for evaluating the efficiency with which regenerated, edited plants could be produced. After validating sgRNA performance and protoplast transformation efficiency using transient assays, we performed two independent editing experiments using sgRNAs targeting different locations within CENH3. In the first experiment, we analyzed 184 regenerated plants and found that 22 of them (11.9%) carried targeted mutations within CENH3, while in the second experiment, 28 out of 190 (14.7%) plants had mutations in CENH3. Of the 50 edited carrot lines that we analyzed, 43 were homozygous or bi-allelic for mutations in CENH3. No evidence of the base editor expression plasmid was found in the edited lines tested, indicating that this approach is able to produce transgene-free, gene-edited lines. The protocol that we describe provides an efficient method for easily generating large numbers of transgene-free, gene-edited carrot plants.

SummaryRevealing the contributions of genes to plant phenotype is frequently challenging because the effects of loss of gene function may be subtle or be masked by genetic redundancy. Such effects can potentially be detected by measuring plant fitness, which reflects the cumulative effects of genetic changes over the lifetime of a plant. However, fitness is challenging to measure accurately, particularly in species with high fecundity and relatively small propagule sizes such as Arabidopsis thaliana.An image segmentation-based (ImageJ) and a Faster Region Based Convolutional Neural Network (R-CNN) approach were used for measuring two Arabidopsis fitness traits: seed and fruit counts.Although straightforward to use, ImageJ was error-prone (correlation between true and predicted seed counts, r2=0.849) because seeds touching each other were undercounted. In contrast, Faster R-CNN yielded near perfect seed counts (r2=0.9996) and highly accurate fruit counts (r2=0.980).By examining seed counts, we were able to reveal fitness effects for genes that were previously reported to have no or condition-specific loss-of-function phenotypes.Our study provides models to facilitate the investigation of Arabidopsis fitness traits and demonstrates the importance of examining fitness traits in the study of gene functions.

Abstract Estimating the abundance of organisms is fundamental to the study and management of ecological systems. However, accurately and precisely estimating organism abundance is challenging, especially in aquatic systems where organisms are hidden underwater. Estimating the abundance of fish is critical for the management of fisheries which relies on accurate assessment of population status to maximize yield without overharvesting populations. Monitoring population status is particularly challenging for inland fisheries in which populations are distributed among many individual waterbodies. Environmental DNA (eDNA) may offer a cost‐effective way to rapidly estimate populations across a large number of systems if eDNA quantity correlates with the abundance of its source organisms. Here, we test the ability of quantities of eDNA recovered from surface water to estimate the abundance of walleye (Sander vitreus), a culturally and economically important sportfish, in lakes in northern Wisconsin (USA). We demonstrate a significant, positive relationship between traditional estimates of adult walleye populations (both number of individuals and biomass) and eDNA concentration (R2 = .81; n = 22). Our results highlight the utility of eDNA as a population monitoring tool that can help guide and inform inland fisheries management.

Genetic redundancy refers to a situation where an individual with a loss-of-function mutation in one gene (single mutant) does not show an apparent phenotype until one or more paralogs are also knocked out (double/higher-order mutant). Previous studies have identified some characteristics common among redundant gene pairs, but a predictive model of genetic redundancy incorporating a wide variety of features derived from accumulating omics and mutant phenotype data is yet to be established. In addition, the relative importance of these features for genetic redundancy remains largely unclear. Here, we establish machine learning models for predicting whether a gene pair is likely redundant or not in the model plant Arabidopsis thaliana based on six feature categories: functional annotations, evolutionary conservation including duplication patterns and mechanisms, epigenetic marks, protein properties including posttranslational modifications, gene expression, and gene network properties. The definition of redundancy, data transformations, feature subsets, and machine learning algorithms used significantly affected model performance based on holdout, testing phenotype data. Among the most important features in predicting gene pairs as redundant were having a paralog(s) from recent duplication events, annotation as a transcription factor, downregulation during stress conditions, and having similar expression patterns under stress conditions. We also explored the potential reasons underlying mispredictions and limitations of our studies. This genetic redundancy model sheds light on characteristics that may contribute to long-term maintenance of paralogs, and will ultimately allow for more targeted generation of functionally informative double mutants, advancing functional genomic studies.

In animals, endocytosis of a seven-transmembrane GPCR is mediated by arrestins to propagate or arrest cytoplasmic G protein-mediated signaling, depending on the bias of the receptor or ligand, which determines how much one transduction pathway is used compared to another. In Arabidopsis thaliana, GPCRs are not required for G protein-coupled signaling because the heterotrimeric G protein complex spontaneously exchanges nucleotide. Instead, the seven-transmembrane protein AtRGS1 modulates G protein signaling through ligand-dependent endocytosis, which initiates derepression of signaling without the involvement of canonical arrestins. Here, we found that endocytosis of AtRGS1 initiated from two separate pools of plasma membrane: sterol-dependent domains and a clathrin-accessible neighborhood, each with a select set of discriminators, activators, and candidate arrestin-like adaptors. Ligand identity (either the pathogen-associated molecular pattern flg22 or the sugar glucose) determined the origin of AtRGS1 endocytosis. Different trafficking origins and trajectories led to different cellular outcomes. Thus, in this system, compartmentation with its associated signalosome architecture drives biased signaling.

The versatility of mitogen-activated protein kinases (MAPKs) in translating exogenous and endogenous stimuli into appropriate cellular responses depends on its substrate specificity. In animals, several mechanisms have been proposed about how MAPKs maintain specificity to regulate distinct functional pathways. However, little is known of mechanisms that enable substrate selectivity in plant MAPKs. Small ubiquitin-like modifier (SUMO), a posttranslational modification system, plays an important role in plant development and defense by rapid reprogramming of cellular events. In this study we identified a functional SUMO interaction motif (SIM) in Arabidopsis MPK3 and MPK6 that reveals a mechanism for selective interaction of MPK3/6 with SUMO-conjugated WRKY33, during defense. We show that WRKY33 is rapidly SUMOylated in response to Botrytis cinerea infection and flg22 elicitor treatment. SUMOylation mediates WRKY33 phosphorylation by MPKs and consequent transcription factor activity. Disruption of either WRKY33 SUMO or MPK3/6 SIM sites attenuates their interaction and inactivates WRKY33-mediated defense. However, MPK3/6 SIM mutants show normal interaction with a non-SUMOylated form of another transcription factor, SPEECHLESS, unraveling a role for SUMOylation in differential substrate selectivity by MPKs. We reveal that the SUMO proteases, SUMO PROTEASE RELATED TO FERTILITY1 (SPF1) and SPF2 control WRKY33 SUMOylation and demonstrate a role for these SUMO proteases in defense. Our data reveal a mechanism by which MPK3/6 prioritize molecular pathways by differentially selecting substrates using the SUMO-SIM module during defense responses.

Mitogen-activated protein kinases (MAPKs) are key regulators of numerous biological processes in plants. To better understand the mechanisms by which these kinases function, high resolution measurement of MAPK activation kinetics in different biological contexts would be beneficial. One method to measure MAPK activation in plants is via fluorescence-based genetically-encoded biosensors, which can provide real-time readouts of the temporal and spatial dynamics of kinase activation in living tissue. Although fluorescent biosensors have been widely used to study MAPK dynamics in animal cells, there is currently only one MAPK biosensor that has been described for use in plants. To facilitate creation of additional plant-specific MAPK fluorescent biosensors, we report the development of two new tools: an in vitro assay for efficiently characterizing MAPK docking domains and a translocation-based kinase biosensor for use in plants. The implementation of these two methods has allowed us to expand the available pool of plant MAPK biosensors, while also providing a means to generate more specific and selective MAPK biosensors in the future. Biosensors developed using these methods have the potential to enhance our understanding of the roles MAPKs play in diverse plant signaling networks affecting growth, development, and stress response.

Sucrose-non-fermenting-1-related protein kinase-2s (SnRK2s) are critical for plant abiotic stress responses, including abscisic acid (ABA) signaling. Here, we develop a genetically encoded reporter for SnRK2 kinase activity. This sensor, named SNACS, shows an increase in the ratio of yellow to cyan fluorescence emission by OST1/SnRK2.6-mediated phosphorylation of a defined serine residue in SNACS. ABA rapidly increases FRET efficiency in N. benthamiana leaf cells and Arabidopsis guard cells. Interestingly, protein kinase inhibition decreases FRET efficiency in guard cells, providing direct experimental evidence that basal SnRK2 activity prevails in guard cells. Moreover, in contrast to ABA, the stomatal closing stimuli, elevated CO2 and MeJA, did not increase SNACS FRET ratios. These findings and gas exchange analyses of quintuple/sextuple ABA receptor mutants show that stomatal CO2 signaling requires basal ABA and SnRK2 signaling, but not SnRK2 activation. A recent model that CO2 signaling is mediated by PYL4/PYL5 ABA-receptors could not be supported here in two independent labs. We report a potent approach for real-time live-cell investigations of stress signaling.

ABSTRACT Genetic redundancy refers to a situation where an individual with a loss-of-function mutation in one gene (single mutant) does not show an apparent phenotype until one or more paralogs are also knocked out (double/higher-order mutant). Previous studies have identified some characteristics common among redundant gene pairs, but a predictive model of genetic redundancy incorporating a wide variety of features has not yet been established. In addition, the relative importance of these characteristics for genetic redundancy remains unclear. Here, we establish machine learning models for predicting whether a gene pair is likely redundant or not in the model plant Arabidopsis thaliana . Benchmark gene pairs were classified based on six feature categories: functional annotations, evolutionary conservation including duplication patterns and mechanisms, epigenetic marks, protein properties including post-translational modifications, gene expression, and gene network properties. The definition of redundancy, data transformations, feature subsets, and machine learning algorithms used affected model performance significantly. Among the most important features in predicting gene pairs as redundant were having a paralog(s) from recent duplication events, annotation as a transcription factor, downregulation during stress conditions, and having similar expression patterns under stress conditions. Predictions were then tested using phenotype data withheld from model building and validated using well-characterized, redundant and nonredundant gene pairs. This genetic redundancy model sheds light on characteristics that may contribute to long-term maintenance of paralogs that are seemingly functionally redundant, and will ultimately allow for more targeted generation of functionally informative double mutants, advancing functional genomic studies.

Biased signaling occurs when different ligands that are directed at the same receptor launch different cellular outcomes. Because of their pharmacological importance, we know the most about biased ligands and little is known about other mechanisms to achieve signaling bias. In the canonical animal G protein system, endocytosis of a 7-transmembrane GPCR is mediated by arrestins to propagate or arrest cytoplasmic signaling depending on the bias. In Arabidopsis, GPCRs are not required for G protein coupled signaling because the heterotrimeric G protein complex spontaneously exchanges nucleotide. Instead, the prototype 7-transmembrane Regulator of G Signaling 1 protein AtRGS1 modulates G signaling and through ligand-dependent endocytosis, de-repression of signaling is initiated but canonical arrestins are not involved. Endocytosis initiates from two separate pools of plasma membrane: sterol-dependent domains, possibly lipid rafts, and a clathrin-accessible neighborhood, each with a select set of discriminators, activators, and newly-discovered arrestin-like adaptors. Different trafficking origins and trajectories lead to different cellular outcomes. Thus, compartmentation with its attendant signalosome architecture is a previously unknown mechanism to drive biased signaling.

The catalytic activity of mitogen-activated protein kinases (MAPKs) is dynamically modified in plants. Since MAPKs have been shown to play important roles in a wide range of signaling pathways, the ability to monitor MAPK activity in living plant cells would be valuable. Here, we report the development of a genetically encoded MAPK activity sensor for use in Arabidopsis thaliana. The sensor is composed of yellow and blue fluorescent proteins, a phosphopeptide binding domain, a MAPK substrate domain and a flexible linker. Using in vitro testing, we demonstrated that phosphorylation causes an increase in the Förster resonance energy transfer (FRET) efficiency of the sensor. The FRET efficiency can therefore serve as a readout of kinase activity. We also produced transgenic Arabidopsis lines expressing this sensor of MAPK activity (SOMA) and performed live-cell imaging experiments using detached cotyledons. Treatment with NaCl, the synthetic flagellin peptide flg22 and chitin all led to rapid gains in FRET efficiency. Control lines expressing a version of SOMA in which the phosphosite was mutated to an alanine did not show any substantial changes in FRET. We also expressed the sensor in a conditional loss-of-function double-mutant line for the Arabidopsis MAPK genes MPK3 and MPK6. These experiments demonstrated that MPK3/6 are necessary for the NaCl-induced FRET gain of the sensor, while other MAPKs are probably contributing to the chitin and flg22-induced increases in FRET. Taken together, our results suggest that SOMA is able to dynamically report MAPK activity in living plant cells.

In light of the ongoing spread and adverse impacts of invasive species, there is an urgent need to develop more effective monitoring and management strategies. Such efforts are constrained by our limited capacity to efficiently detect invasive species. Here, we present the case of Bythotrephes longimanus (spiny water flea) invasion into Wisconsin lakes. Detecting Bythotrephes has proven to be challenging due to its capacity to persist at low densities and its highly seasonal population dynamics. We use Bythotrephes to explore detection using three monitoring methods: zooplankton net tows, environmental DNA (eDNA), and sampling of Bythotrephes tail spine subfossils in sediments. Detection probabilities were highly seasonal for both the net tow and eDNA sampling methods—though detections occurred one to two weeks earlier in net tows—and seasonal targeting substantially improved detection by both methods. Conversely, Bythotrephes spine subfossils were found in all 10 lakes with confirmed Bythotrephes populations and in all five samples taken from each lake, except for a single lake where four of the five samples had subfossils. This method was insensitive to seasonally varying population densities as sediments integrate over variation in population densities. In this case, detection and abundance estimation were well covered by sediments and zooplankton nets, respectively, and eDNA provided little additional benefit to surveillance. Our work highlights the importance of choosing methods that address both species life history and monitoring objectives when designing surveillance programs.

Mitogen activated protein kinase (MAPK) cascades play an important role in many aspects of plant growth, development, and environmental response. Because of their central role in many important processes, MAPKs have been extensively studied using biochemical and genetic approaches. This work has allowed for the identification of the MAPK genes and proteins involved in a number of different signaling pathways. Less well developed, however, is our understanding of how MAPK cascades and their corresponding signaling pathways are organized at subcellular levels. In this review, we will provide an overview of plant MAPK signaling, including a discussion of what is known about cellular mechanisms for achieving signaling specificity. Then we will explore what is currently known about the subcellular localization of MAPK proteins in resting conditions and after pathway activation. Finally, we will discuss a number of new experimental methods that have not been widely deployed in plants that have the potential to provide a deeper understanding of the spatial and temporal dynamics of MAPK signaling.