Comparative Analysis of Coding and Non-Coding Features within Insect Tolerance Loci in Wheat with Their Homologs in Cereal Genomes

Muslu, Tuğdem; Akpınar, Bala Anı; Biyiklioglu-Kaya, Sezgi; Yüce, Meral; Budak, Hikmet

doi:10.3390/ijms222212349

Cited by 9 publications

(6 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[ 5 , 6 ] The phenotype and kinetics of HR can, however, differ greatly depending on the host and causative agent. [ 7 ] HR assays are invaluable in the study of plant‐pathogen interactions, [ 8 , 9 ] defense responses, and associated signal transduction pathways. [ 10 ] HR assays are used not only for detecting the presence of HR, but also for precisely evaluating the intensity and timing of responses.…”

Section: Introductionmentioning

confidence: 99%

Parallel, Continuous Monitoring and Quantification of Programmed Cell Death in Plant Tissue

Collins,

Kurt,

Duggan

et al. 2024

Advanced Science

View full text Add to dashboard Cite

Accurate quantification of hypersensitive response (HR) programmed cell death is imperative for understanding plant defense mechanisms and developing disease‐resistant crop varieties. Here, a phenotyping platform for rapid, continuous‐time, and quantitative assessment of HR is demonstrated: Parallel Automated Spectroscopy Tool for Electrolyte Leakage (PASTEL). Compared to traditional HR assays, PASTEL significantly improves temporal resolution and has high sensitivity, facilitating detection of microscopic levels of cell death. Validation is performed by transiently expressing the effector protein AVRblb2 in transgenic Nicotiana benthamiana (expressing the corresponding resistance protein Rpi‐blb2) to reliably induce HR. Detection of cell death is achieved at microscopic intensities, where leaf tissue appears healthy to the naked eye one week after infiltration. PASTEL produces large amounts of frequency domain impedance data captured continuously. This data is used to develop supervised machine‐learning (ML) models for classification of HR. Input data (inclusive of the entire tested concentration range) is classified as HR‐positive or negative with 84.1% mean accuracy (F1 score = 0.75) at 1 h and with 87.8% mean accuracy (F1 score = 0.81) at 22 h. With PASTEL and the ML models produced in this work, it is possible to phenotype disease resistance in plants in hours instead of days to weeks.

show abstract

Section: Introductionmentioning

confidence: 99%

Parallel, Continuous Monitoring and Quantification of Programmed Cell Death in Plant Tissue

Collins,

Kurt,

Duggan

et al. 2024

Advanced Science

View full text Add to dashboard Cite

show abstract

“…The phenotype and kinetics of HR can, however, differ greatly depending on the host and causative agent. 7 HR assays are invaluable in the study of plant-pathogen interactions, 8,9 defense responses, and associated signal transduction pathways. 10 HR assays are used not only for detecting the presence of HR, but also for precisely evaluating the intensity and timing of responses.…”

Section: Introductionmentioning

confidence: 99%

Parallel, Continuous Monitoring and Quantification of Programmed Cell Death in Plant Tissue

Collins,

Kurt,

Duggan

et al. 2023

Preprint

View full text Add to dashboard Cite

The accurate quantification of hypersensitive response (HR) programmed cell death is imperative for understanding plant defense mechanisms and developing disease-resistant crop varieties. In this study, we report an accelerated phenotyping platform for the continuous-time, rapid and quantitative assessment of HR: Parallel Automated Spectroscopy Tool for Electrolyte Leakage (PASTEL). Compared to traditional HR assays, PASTEL significantly improves temporal resolution and has high sensitivity, facilitating the detection of microscopic levels of cell death. We validated PASTEL by transiently expressing the effector protein AVRblb2 in transgenic lines of the model plantNicotiana benthamiana(expressing the corresponding resistance protein Rpi-blb2) to reliably induce HR. We were able to detect cell death at microscopic intensities, where leaf tissue appeared healthy to the naked eye one week after infiltration. PASTEL produces large amounts of frequency domain impedance data captured continuously (sub-seconds to minutes). Using this data, we developed a supervised machine learning models for classification of HR. We were able to classify input data (inclusive of our entire tested concentration range) as HR-positive or negative with 84.1% mean accuracy (F1score = 0.75) at 1 hour and with 87.8% mean accuracy (F1score = 0.81) at 22 hours. With PASTEL and the ML models produced in this work, it is possible to phenotype disease resistance in plants in hours instead of days to weeks.

show abstract

“…Abiotic stressors, including heavy metals, nutrient deficiencies, extreme temperature, salinity/alkalinity, and drought, can negatively impact plant health and productivity [1]. In recent decades, there has been a notable global escalation in soil heavy metal pollution due to extensive industrial and anthropogenic activities.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, Cd inhibits the activities of key enzymes and the acquisition of essential nutrients, reducing both the quality and yield of crop plants [5,6]. Several methods have been proposed to remove heavy metal ions from soil [6,7], including phytoremediation, physical remediation, chemical remediation, and bioremediation [1][2][3][4]. Physical and chemical remediation methods provide quick remediation but are costly and cause secondary pollutants [2].…”

Section: Introductionmentioning

confidence: 99%

The SbbHLH041–SbEXPA11 Module Enhances Cadmium Accumulation and Rescues Biomass by Increasing Photosynthetic Efficiency in Sorghum

Wang,

Yu,

Zhu

et al. 2023

IJMS

View full text Add to dashboard Cite

In plants, expansin genes are responsive to heavy metal exposure. To study the bioremediary potential of this important gene family, we discovered a root-expressed expansin gene in sorghum, SbEXPA11, which is notably upregulated following cadmium (Cd) exposure. However, the mechanism underlying the Cd detoxification and accumulation mediated by SbEXPA11 in sorghum remains unclear. We overexpressed SbEXPA11 in sorghum and compared wild-type (WT) and SbEXPA11-overexpressing transgenic sorghum in terms of Cd accumulation and physiological indices following Cd. Compared with the WT, we found that SbEXPA11 mediates Cd tolerance by exerting reactive oxygen species (ROS)-scavenging effects through upregulating the expression of antioxidant enzymes. Moreover, the overexpression of SbEXPA11 rescued biomass production by increasing the photosynthetic efficiency of transgenic plants. In the pot experiment with a dosage of 10 mg/kg Cd, transgenic sorghum plants demonstrated higher efficacy in reducing the Cd content of the soil (8.62 mg/kg) compared to WT sorghum plants (9.51 mg/kg). Subsequent analysis revealed that the SbbHLH041 transcription factor has the ability to induce SbEXPA11 expression through interacting with the E-box located within the SbEXPA11 promoter. These findings suggest that the SbbHLH041–SbEXPA11 cascade module may be beneficial for the development of phytoremediary sorghum varieties.

show abstract

Comparative Analysis of Coding and Non-Coding Features within Insect Tolerance Loci in Wheat with Their Homologs in Cereal Genomes

Cited by 9 publications

References 52 publications

Parallel, Continuous Monitoring and Quantification of Programmed Cell Death in Plant Tissue

Parallel, Continuous Monitoring and Quantification of Programmed Cell Death in Plant Tissue

Parallel, Continuous Monitoring and Quantification of Programmed Cell Death in Plant Tissue

The SbbHLH041–SbEXPA11 Module Enhances Cadmium Accumulation and Rescues Biomass by Increasing Photosynthetic Efficiency in Sorghum

Contact Info

Product

Resources

About