Natural variation in Brachypodium distachyon responses to combined abiotic stresses.

The demand for agricultural production is becoming more challenging as climate change increases global temperature and the frequency of extreme weather events. This study examines the phenotypic variation of 149 accessions of Brachypodium distachyon under drought, heat, and the combination of stresses. Heat alone causes the largest amounts of tissue damage while the combination of stresses causes the largest decrease in biomass compared to other treatments. Notably, Bd21-0, the reference line for B. distachyon, did not have robust growth under stress conditions, especially the heat and combined drought and heat treatments. The climate of origin was significantly associated with B. distachyon responses to the assessed stress conditions. Additionally, a GWAS found loci associated with changes in plant height and the amount of damaged tissue under stress. Some of these SNPs were closely located to genes known to be involved in responses to abiotic stresses and point to potential causative loci in plant stress response. However, SNPs found to be significantly associated with a response to heat or drought individually are not also significantly associated with the combination of stresses. This, with the phenotypic data, suggests that the effects of these abiotic stresses are not simply additive, and the responses to the combined stresses differ from drought and heat alone.

The Relationship Between Acoustic and Kinematic Vowel Space Areas With and Without Normalization for Speakers With and Without Dysarthria.

PURPOSE: Few studies have reported on the vowel space area (VSA) in both acoustic and kinematic domains. This study examined acoustic and kinematic VSAs for speakers with and without dysarthria and evaluated effects of normalization on acoustic and kinematic VSAs and the relationship between these measures. METHOD: Vowel data from 12 speakers with and without dysarthria, presenting with a range of speech abilities, were examined. The speakers included four speakers with Parkinson's disease (PD), four speakers with brain injury (BI), and four neurotypical (NT) speakers. Speech acoustic and kinematic data were acquired simultaneously using electromagnetic articulography during a passage reading task. Raw and normalized VSAs calculated from corner vowels /i/, /æ/, /ɑ/, and /u/ were evaluated. Normalization was achieved through z score transformations to the acoustic and kinematic data. The effect of normalization on variability within and across groups was evaluated. Regression analysis was used across speakers to assess the association between acoustic and kinematic VSAs for both raw and normalized data. RESULTS: When evaluating the speakers as three different groups (i.e., PD, BI, and NT), normalization reduced the standard deviations within each group and changed the relative differences in average magnitude between groups. Regression analysis revealed a significant relationship between normalized, but not raw, acoustic and kinematic VSAs, after the exclusion of an outlier speaker. CONCLUSIONS: Normalization reduces the variability across speakers, within groups, and changes average magnitudes affecting speaker group comparisons. Normalization also influences the correlation between acoustic and kinematic measures. Further investigation of the impact of normalization techniques upon acoustic and kinematic measures is warranted. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.22669747.

Improving cassava bacterial blight resistance by editing the epigenome.

Pathogens rely on expression of host susceptibility (S) genes to promote infection and disease. As DNA methylation is an epigenetic modification that affects gene expression, blocking access to S genes through targeted methylation could increase disease resistance. Xanthomonas phaseoli pv. manihotis, the causal agent of cassava bacterial blight (CBB), uses transcription activator-like20 (TAL20) to induce expression of the S gene MeSWEET10a. In this work, we direct methylation to the TAL20 effector binding element within the MeSWEET10a promoter using a synthetic zinc-finger DNA binding domain fused to a component of the RNA-directed DNA methylation pathway. We demonstrate that this methylation prevents TAL20 binding, blocks transcriptional activation of MeSWEET10a in vivo and that these plants display decreased CBB symptoms while maintaining normal growth and development. This work therefore presents an epigenome editing approach useful for crop improvement.

Increased signal-to-noise ratios within experimental field trials by regressing spatially distributed soil properties as principal components.

Environmental variability poses a major challenge to any field study. Researchers attempt to mitigate this challenge through replication. Thus, the ability to detect experimental signals is determined by the degree of replication and the amount of environmental variation, noise, within the experimental system. A major source of noise in field studies comes from the natural heterogeneity of soil properties which create microtreatments throughout the field. In addition, the variation within different soil properties is often nonrandomly distributed across a field. We explore this challenge through a sorghum field trial dataset with accompanying plant, microbiome, and soil property data. Diverse sorghum genotypes and two watering regimes were applied in a split-plot design. We describe a process of identifying, estimating, and controlling for the effects of spatially distributed soil properties on plant traits and microbial communities using minimal degrees of freedom. Importantly, this process provides a method with which sources of environmental variation in field data can be identified and adjusted, improving our ability to resolve effects of interest and to quantify subtle phenotypes.

A comparison of ImageJ and machine learning based image analysis methods to measure cassava bacterial blight disease severity.

BACKGROUND: Methods to accurately quantify disease severity are fundamental to plant pathogen interaction studies. Commonly used methods include visual scoring of disease symptoms, tracking pathogen growth in planta over time, and various assays that detect plant defense responses. Several image-based methods for phenotyping of plant disease symptoms have also been developed. Each of these methods has different advantages and limitations which should be carefully considered when choosing an approach and interpreting the results. RESULTS: In this paper, we developed two image analysis methods and tested their ability to quantify different aspects of disease lesions in the cassava-Xanthomonas pathosystem. The first method uses ImageJ, an open-source platform widely used in the biological sciences. The second method is a few-shot support vector machine learning tool that uses a classifier file trained with five representative infected leaf images for lesion recognition. Cassava leaves were syringe infiltrated with wildtype Xanthomonas, a Xanthomonas mutant with decreased virulence, and mock treatments. Digital images of infected leaves were captured overtime using a Raspberry Pi camera. The image analysis methods were analyzed and compared for the ability to segment the lesion from the background and accurately capture and measure differences between the treatment types. CONCLUSIONS: Both image analysis methods presented in this paper allow for accurate segmentation of disease lesions from the non-infected plant. Specifically, at 4-, 6-, and 9-days post inoculation (DPI), both methods provided quantitative differences in disease symptoms between different treatment types. Thus, either method could be applied to extract information about disease severity. Strengths and weaknesses of each approach are discussed.

Systems-wide analysis revealed shared and unique responses to moderate and acute high temperatures in the green alga Chlamydomonas reinhardtii.

Different intensities of high temperatures affect the growth of photosynthetic cells in nature. To elucidate the underlying mechanisms, we cultivated the unicellular green alga Chlamydomonas reinhardtii under highly controlled photobioreactor conditions and revealed systems-wide shared and unique responses to 24-hour moderate (35°C) and acute (40°C) high temperatures and subsequent recovery at 25°C. We identified previously overlooked unique elements in response to moderate high temperature. Heat at 35°C transiently arrested the cell cycle followed by partial synchronization, up-regulated transcripts/proteins involved in gluconeogenesis/glyoxylate-cycle for carbon uptake and promoted growth. But 40°C disrupted cell division and growth. Both high temperatures induced photoprotection, while 40°C distorted thylakoid/pyrenoid ultrastructure, affected the carbon concentrating mechanism, and decreased photosynthetic efficiency. We demonstrated increased transcript/protein correlation during both heat treatments and hypothesize reduced post-transcriptional regulation during heat may help efficiently coordinate thermotolerance mechanisms. During recovery after both heat treatments, especially 40°C, transcripts/proteins related to DNA synthesis increased while those involved in photosynthetic light reactions decreased. We propose down-regulating photosynthetic light reactions during DNA replication benefits cell cycle resumption by reducing ROS production. Our results provide potential targets to increase thermotolerance in algae and crops.

Identification of beneficial and detrimental bacteria impacting sorghum responses to drought using multi-scale and multi-system microbiome comparisons.

Drought is a major abiotic stress limiting agricultural productivity. Previous field-level experiments have demonstrated that drought decreases microbiome diversity in the root and rhizosphere. How these changes ultimately affect plant health remains elusive. Toward this end, we combined reductionist, transitional and ecological approaches, applied to the staple cereal crop sorghum to identify key root-associated microbes that robustly affect drought-stressed plant phenotypes. Fifty-three Arabidopsis-associated bacteria were applied to sorghum seeds and their effect on root growth was monitored. Two Arthrobacter strains caused root growth inhibition (RGI) in Arabidopsis and sorghum. In the context of synthetic communities, Variovorax strains were able to protect plants from Arthrobacter-caused RGI. As a transitional system, high-throughput phenotyping was used to test the synthetic communities. During drought stress, plants colonized by Arthrobacter had reduced growth and leaf water content. Plants colonized by both Arthrobacter and Variovorax performed as well or better than control plants. In parallel, we performed a field trial wherein sorghum was evaluated across drought conditions. By incorporating data on soil properties into the microbiome analysis, we accounted for experimental noise with a novel method and were able to observe the negative correlation between the abundance of Arthrobacter and plant growth. Having validated this approach, we cross-referenced datasets from the high-throughput phenotyping and field experiments and report a list of bacteria with high confidence that positively associated with plant growth under drought stress. In conclusion, a three-tiered experimental system successfully spanned the lab-to-field gap and identified beneficial and deleterious bacterial strains for sorghum under drought.

Heat stress changes mineral nutrient concentrations in Chenopodium quinoa seed.

Quinoa is a popular seed crop, often consumed for its high nutritional quality. We studied how heat stress in the roots or the shoots of quinoa plants affected the concentrations of 20 elements (aluminum, arsenic, boron, calcium, cadmium, cobalt, copper, iron, potassium, magnesium, manganese, molybdenum, sodium, nickel, phosphorous, rubidium, sulfur, selenium, strontium, and zinc) in quinoa seed. Elemental concentrations in quinoa seed were significantly changed after an 11-day heat treatment during anthesis. The type of panicle (main, secondary, and tertiary) sampled and the type of heat treatment (root only, shoot only, or whole plants) significantly affected elemental profiles in quinoa seed. Plants were also divided into five sections from top to bottom to assess the effect of panicle position on seed elemental profiles. Plant section had an effect on the concentrations of arsenic, iron, and sodium under control conditions and on copper with heat treatment. Overall, the time of panicle development in relation to the time of heat exposure had the largest effect on seed elemental concentrations. Interestingly, the quinoa plants were exposed to heat only during anthesis of the main panicle, but the elemental concentrations of seeds produced after heat treatment ended were still significantly changed, indicating that heat stress has long-lasting effects on quinoa plants. These findings demonstrate how the nutritional quality of quinoa seeds can be changed significantly even by relatively short heat spells.

Current status and impending progress for cassava structural genomics.

KEY MESSAGE: We demystify recent advances in genome assemblies for the heterozygous staple crop cassava (Manihot esculenta), and highlight key cassava genomic resources. Cassava, Manihot esculenta Crantz, is a crop of societal and agricultural importance in tropical regions around the world. Genomics provides a platform for accelerated improvement of cassava's nutritional and agronomic traits, as well as for illuminating aspects of cassava's history including its path towards domestication. The highly heterozygous nature of the cassava genome is widely recognized. However, the full extent and context of this heterozygosity has been difficult to reveal because of technological limitations within genome sequencing. Only recently, with several new long-read sequencing technologies coming online, has the genomics community been able to tackle some similarly difficult genomes. In light of these recent advances, we provide this review to document the current status of the cassava genome and genomic resources and provide a perspective on what to look forward to in the coming years.

Large structural variations in the haplotype-resolved African cassava genome.

Cassava (Manihot esculenta Crantz, 2n = 36) is a global food security crop. It has a highly heterozygous genome, high genetic load, and genotype-dependent asynchronous flowering. It is typically propagated by stem cuttings and any genetic variation between haplotypes, including large structural variations, is preserved by such clonal propagation. Traditional genome assembly approaches generate a collapsed haplotype representation of the genome. In highly heterozygous plants, this results in artifacts and an oversimplification of heterozygous regions. We used a combination of Pacific Biosciences (PacBio), Illumina, and Hi-C to resolve each haplotype of the genome of a farmer-preferred cassava line, TME7 (Oko-iyawo). PacBio reads were assembled using the FALCON suite. Phase switch errors were corrected using FALCON-Phase and Hi-C read data. The ultralong-range information from Hi-C sequencing was also used for scaffolding. Comparison of the two phases revealed >5000 large haplotype-specific structural variants affecting over 8 Mb, including insertions and deletions spanning thousands of base pairs. The potential of these variants to affect allele-specific expression was further explored. RNA-sequencing data from 11 different tissue types were mapped against the scaffolded haploid assembly and gene expression data are incorporated into our existing easy-to-use web-based interface to facilitate use by the broader plant science community. These two assemblies provide an excellent means to study the effects of heterozygosity, haplotype-specific structural variation, gene hemizygosity, and allele-specific gene expression contributing to important agricultural traits and further our understanding of the genetics and domestication of cassava.

High light and temperature reduce photosynthetic efficiency through different mechanisms in the C4 model Setaria viridis.

C4 plants frequently experience high light and high temperature conditions in the field, which reduce growth and yield. However, the mechanisms underlying these stress responses in C4 plants have been under-explored, especially the coordination between mesophyll (M) and bundle sheath (BS) cells. We investigated how the C4 model plant Setaria viridis responded to a four-hour high light or high temperature treatment at photosynthetic, transcriptomic, and ultrastructural levels. Although we observed a comparable reduction of photosynthetic efficiency in high light or high temperature treated leaves, detailed analysis of multi-level responses revealed important differences in key pathways and M/BS specificity responding to high light and high temperature. We provide a systematic analysis of high light and high temperature responses in S. viridis, reveal different acclimation strategies to these two stresses in C4 plants, discover unique light/temperature responses in C4 plants in comparison to C3 plants, and identify potential targets to improve abiotic stress tolerance in C4 crops.

ER71/ETV2 Promotes Hair Regeneration from Chemotherapeutic Drug-Induced Hair Loss by Enhancing Angiogenesis.

Chemotherapy-induced alopecia and hair loss can be stressful in patients with cancer. The hair grows back, but sometimes the hair tends to stay thin. Therefore, understanding mechanisms regulating hair regeneration may improve the management of chemotherapy-induced alopecia. Previous studies have revealed that chemotherapeutic agents induce a hair follicle vascular injury. As hair growth is associated with micro-vessel regeneration, we postulated that the stimulation of angiogenesis might enhance hair regeneration. In particular, mice treated with 5-fluorouracil (5-FU) showed delayed anagen initiation and reduced capillary density when compared with untreated controls, suggesting that the retardation of anagen initiation by 5-FU treatment may be attributed to the loss of perifollicular micro-vessels. We investigated whether the ETS transcription factor ETV2 (aka ER71), critical for vascular development and regeneration, can promote angiogenesis and hair regrowth in a 5-FU-induced alopecia mouse model. Tie2-Cre; Etv2 conditional knockout (CKO) mice, which lack Etv2 in endothelial cells, presented similar hair regrowth rates as the control mice after depilation. Following 5-FU treatment, Tie2-Cre; Etv2 CKO mice revealed a significant reduction in capillary density, anagen induction, and hair restoration when compared with controls. Mice receiving lentiviral Etv2 injection after 5-FU treatment showed significantly improved anagen induction and hair regrowth. Two-photon laser scanning microscopy revealed that enforced Etv2 expression restored normal vessel morphology after 5-FU mediated vessel injury. Our data suggest that vessel regeneration strategies may improve hair regrowth after chemotherapeutic treatment.

Escalation in the host-pathogen arms race: A host resistance response corresponds to a heightened bacterial virulence response.

The zig-zag model of host-pathogen interaction describes the relative strength of defense response across a spectrum of pathogen-induced plant phenotypes. A stronger defense response results in increased resistance. Here, we investigate the strength of pathogen virulence during disease and place these findings in the context of the zig-zag model. Xanthomonas vasicola pv. holcicola (Xvh) causes sorghum bacterial leaf streak. Despite being widespread, this disease has not been described in detail at the molecular level. We divided diverse sorghum genotypes into three groups based on disease symptoms: water-soaked lesions, red lesions, and resistance. Bacterial growth assays confirmed that these three phenotypes represent a range of resistance and susceptibility. To simultaneously reveal defense and virulence responses across the spectrum of disease phenotypes, we performed dual RNA-seq on Xvh-infected sorghum. Consistent with the zig-zag model, the expression of plant defense-related genes was strongest in the resistance interaction. Surprisingly, bacterial virulence genes related to the type III secretion system (T3SS) and type III effectors (T3Es) were also most highly expressed in the resistance interaction. This expression pattern was observed at multiple time points within the sorghum-Xvh pathosystem. Further, a similar expression pattern was observed in Arabidopsis infected with Pseudomonas syringae for effector-triggered immunity via AvrRps4 but not AvrRpt2. Specific metabolites were able to repress the Xvh virulence response in vitro and in planta suggesting a possible signaling mechanism. Taken together, these findings reveal multiple permutations of the continually evolving host-pathogen arms race from the perspective of host defense and pathogen virulence responses.

CelltrackR: An R package for fast and flexible analysis of immune cell migration data.

Visualization of cell migration via time-lapse microscopy has greatly advanced our understanding of the immune system. However, subtle differences in migration dynamics are easily obscured by biases and imaging artifacts. While several analysis methods have been suggested to address these issues, an integrated tool implementing them is currently lacking. Here, we present celltrackR, an R package containing a diverse set of state-of-the-art analysis methods for (immune) cell tracks. CelltrackR supports the complete pipeline for track analysis by providing methods for data management, quality control, extracting and visualizing migration statistics, clustering tracks, and simulating cell migration. CelltrackR supports the analysis of both 2D and 3D cell tracks. CelltrackR is an open-source package released under the GPL-2 license, and is freely available on both GitHub and CRAN. Although the package was designed specifically for immune cell migration data, many of its methods will also be of use in other research areas dealing with moving objects.

Antiviral ARGONAUTEs Against Turnip Crinkle Virus Revealed by Image-Based Trait Analysis.

RNA-based silencing functions as an important antiviral immunity mechanism in plants. Plant viruses evolved to encode viral suppressors of RNA silencing (VSRs) that interfere with the function of key components in the silencing pathway. As effectors in the RNA silencing pathway, ARGONAUTE (AGO) proteins are targeted by some VSRs, such as that encoded by Turnip crinkle virus (TCV). A VSR-deficient TCV mutant was used to identify AGO proteins with antiviral activities during infection. A quantitative phenotyping protocol using an image-based color trait analysis pipeline on the PlantCV platform, with temporal red, green, and blue imaging and a computational segmentation algorithm, was used to measure plant disease after TCV inoculation. This process captured and analyzed growth and leaf color of Arabidopsis (Arabidopsis thaliana) plants in response to virus infection over time. By combining this quantitative phenotypic data with molecular assays to detect local and systemic virus accumulation, AGO2, AGO3, and AGO7 were shown to play antiviral roles during TCV infection. In leaves, AGO2 and AGO7 functioned as prominent nonadditive, anti-TCV effectors, whereas AGO3 played a minor role. Other AGOs were required to protect inflorescence tissues against TCV. Overall, these results indicate that distinct AGO proteins have specialized, modular roles in antiviral defense across different tissues, and demonstrate the effectiveness of image-based phenotyping to quantify disease progression.

An automated, high-throughput method for standardizing image color profiles to improve image-based plant phenotyping.

High-throughput phenotyping has emerged as a powerful method for studying plant biology. Large image-based datasets are generated and analyzed with automated image analysis pipelines. A major challenge associated with these analyses is variation in image quality that can inadvertently bias results. Images are made up of tuples of data called pixels, which consist of R, G, and B values, arranged in a grid. Many factors, for example image brightness, can influence the quality of the image that is captured. These factors alter the values of the pixels within images and consequently can bias the data and downstream analyses. Here, we provide an automated method to adjust an image-based dataset so that brightness, contrast, and color profile is standardized. The correction method is a collection of linear models that adjusts pixel tuples based on a reference panel of colors. We apply this technique to a set of images taken in a high-throughput imaging facility and successfully detect variance within the image dataset. In this case, variation resulted from temperature-dependent light intensity throughout the experiment. Using this correction method, we were able to standardize images throughout the dataset, and we show that this correction enhanced our ability to accurately quantify morphological measurements within each image. We implement this technique in a high-throughput pipeline available with this paper, and it is also implemented in PlantCV.

A Kinematic Analysis of Coarticulation Effects on Schwa.

PURPOSE: This study investigated coarticulatory effects on schwa. The purpose was to establish a viable phonetic environment and analysis for future studies of coarticulation, particularly in motor speech disorders. METHOD: Seven female adults read 2 phrases containing 4 target words in a CVC structure embedded in the carrier phrases, "Put a CVC here" and "Get CVC a puppy." A 3D electromagnetic articulography system was used to track lingual movements during schwa production. Two indices of coarticulation were employed: (a) tongue position difference between the temporal midpoint (grand mean of each speaker) and the onset/offset of schwa immediately following or preceding a transconsonantal vowel and (b) tongue position differences between the grand mean of each speaker and each utterance repetition, both measured at the temporal midpoint of the schwa. RESULTS: Both measures indicated that schwa is significantly influenced by transconsonantal corner vowels. The magnitude of coarticulation effects on schwa varied among the 4 corner vowels in the order of /i/>/ɑ/ = /æ/>/u/. CONCLUSION: Findings support the use of schwa in future studies when examining coarticulatory effects in people with and without motor speech disorders. Some methodological issues such as selection of measurement points and speech stimuli are also discussed.