Root-Suppressed Phenotype of Tomato Rs Mutant is Seemingly Related to Expression of Root-Meristem-Specific Sulfotransferases
Authors: Kumari, A., Gupta, P., Santisree, P., Pamei, I., Valluri,, S., Sharma, K., Venkateswara Rao, K., Shukla, S., Nama, S., Sreelakshmi, Y., Sharma, R.
The study characterizes a radiation‑induced root‑suppressed (Rs) mutant in tomato that displays dwarfism and pleiotropic defects in leaves, flowers, and fruits. Metabolite profiling and rescue with H2S donors implicate disrupted sulfur metabolism, and whole‑genome sequencing identifies promoter mutations in two root‑meristem‑specific sulfotransferase genes as likely contributors to the root phenotype.
An ancient alkalinization factor informs Arabidopsis root development
Authors: Xhelilaj, K., von Arx, M., Biermann, D., Parvanov, A., Faiss, N., Monte, I., Klingelhuber, F., Zipfel, C., Timmermans, M., Oecking, C., Gronnier, J.
The study identifies members of the REMORIN protein family as inhibitors of plasma membrane H⁺‑ATPases, leading to extracellular pH alkalinization that modulates cell surface processes such as steroid hormone signaling and coordinates root developmental transitions in Arabidopsis thaliana. This inhibition represents an ancient mechanism predating root evolution, suggesting that extracellular pH patterning has shaped plant morphogenesis.
The authors compiled and standardized published data on Rubisco dark inhibition for 157 flowering plant species, categorizing them into four inhibition levels and analyzing phylogenetic trends. Their meta‑analysis reveals a complex, uneven distribution of inhibition across taxa, suggesting underlying chloroplast microenvironment drivers and providing a new resource for future photosynthesis improvement efforts.
PlantCV v4: Image analysis software for high-throughput plant phenotyping
Authors: Schuhl, H., Brown, K. E., Sheng, H., Bhatt, P. K., Gutierrez, J., Schneider, D., Casto, A. L., Acosta-Gamboa, L., Ballenger, J. G., Barbero, F., Braley, J., Brown, A. M., Chavez, L., Cunningham, S., Dilhara, M., Dimech, A. M., Duenwald, J. G., Fischer, A., Gordon, J. M., Hendrikse, C., Hernandez, G. L., Hodge, J. G., Huber, M., Hurr, B. M., Jarolmasjed, S., Medina Jimenez, K., Kenney, S., Konkel, G., Kutschera, A., Lama, S., Lohbihler, M., Lorence, A., Luebbert, C., Ly, N., Manching, H. K., Marrano, A., Meerdink, S., Miklave, N. M., Mudrageda, P., Murphy, K. M., Peery, J. D., Pierik, R., Polyd
PlantCV v4 is an open-source Python framework that simplifies image-based plant phenotyping by providing extensive tutorials and streamlined installation, enabling users with limited coding skills to automate trait extraction. The release adds support for fluorescence, thermal, and hyperspectral imaging and introduces a new subpackage for morphological measurements such as leaf angle, which is validated against manual data collection methods.
The study combined high-throughput image-based phenotyping with genome-wide association studies to uncover the genetic architecture of tolerance to the spittlebug Aeneolamia varia in 339 interspecific Urochloa hybrids. Six robust QTL were identified for plant damage traits, explaining up to 21.5% of variance, and candidate genes linked to hormone signaling, oxidative stress, and cell‑wall modification were highlighted, providing markers for breeding.
Evaluation of combined root exudate and rhizosphere microbiota sampling approaches to elucidate plant-soil-microbe interaction
Authors: Escudero-Martinez, C., Browne, E. Y., Schwalm, H., Santangeli, M., Brown, M., Brown, L., Roberts, D. M., Duff, A. M., Morris, J., Hedley, P. E., Thorpe, P., Abbott, J. C., Brennan, F., Bulgarelli, D., George, T. S., Oburger, E.
The study benchmarked several sampling approaches for simultaneous profiling of root exudates and rhizosphere microbiota in soil-grown barley, revealing consistent exudate chemistry across methods but variation in root morphology and nitrogen exudation. High‑throughput amplicon sequencing and quantitative PCR showed protocol‑specific impacts on microbial composition, yet most rhizosphere-enriched microbes were captured by all approaches. The authors conclude that different protocols provide comparable integrated data, though methodological differences must be aligned with experimental objectives.
Phenotypic scoring of Canola Blackleg severity using machine learning image analysis
Authors: Hu, Q., Anderson, S. N., Gardner, S., Ernst, T. W., Koscielny, C. B., Bahia, N. S., Johnson, C. G., Jarvis, A. C., Hynek, J., Coles, N., Falak, I., Charne, D. R., Ruidiaz, M. E., Linares, J. N., Mazis, A., Stanton, D. J.
The study introduces a deep‑learning based image analysis pipeline that scores blackleg disease severity from stem cross‑section images of canola species, achieving greater consistency than median expert raters while preserving comparable heritability of susceptibility traits. This standardized scoring method aims to improve selection of resistant varieties in breeding programs.
The study profiled root transcriptomes of Arabidopsis wild type and etr1 gain-of-function (etr1-3) and loss-of-function (etr1-7) mutants under ethylene or ACC treatment, identifying 4,522 ethylene‑responsive transcripts, including 553 that depend on ETR1 activity. ETR1‑dependent genes encompassed ethylene biosynthesis enzymes (ACO2, ACO3) and transcription factors, whose expression was further examined in an ein3eil1 background, revealing that both ETR1 and EIN3/EIL1 pathways regulate parts of the network controlling root hair proliferation and lateral root formation.
The study investigated how Arabidopsis thaliana SR protein kinases (AtSRPKs) regulate alternative RNA splicing by using chemical inhibitors of SRPK activity. Inhibition with SPHINX31 and SRPIN340 caused reduced root growth and loss of root hairs, accompanied by widespread changes in splicing and phosphorylation of genes linked to root development and other cellular processes. Multi‑omics analysis (transcriptomics and phosphoproteomics) revealed that AtSRPKs modulate diverse splicing factors and affect the splicing landscape of numerous pathways.
The study investigates the role of the Arabidopsis transcription factor AtMYB93 in sulfur (S) signaling and root development, revealing that AtMYB93 mutants exhibit altered expression of S transport and metabolism genes and increased shoot S levels, while tomato plants overexpressing SlMYB93 show reduced shoot S. Transcriptomic profiling, elemental analysis, and promoter activity assays indicate that AtMYB93 contributes to root responses to S deprivation, though functional redundancy masks clear phenotypic effects on lateral and adventitious root formation.