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.
The study profiled the maize (Zea mays) endosperm transcriptome for the first four days after pollination using laser-capture microdissection, revealing temporal co‑expression modules including a fertilization‑activated subset. Network analyses linked MYB‑related transcription factors to basal endosperm transfer layer (BETL) differentiation and E2F transcription factors, together with TOR‑dependent sugar sensing, to early endosperm proliferation and kernel size variation.
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 used a bottom‑up thermodynamic modelling framework to investigate how plants decode calcium signals, starting from Ca2+ binding to EF‑hand proteins and extending to higher‑order decoding modules. They identified six universal Ca2+-decoding modules that can explain variations in calcium sensitivity among kinases and provide a theoretical basis for interpreting calcium signal amplitude and frequency in plant cells.
The study reveals that each individual plant possesses a statistically unique leaf appearance that can be discriminated using convolutional neural network (CNN) based deep learning, enabling a "plant face" recognition concept. Applications demonstrated include distinguishing leaves from the same species/cultivar, analyzing leaflet positional patterns on compound leaves, assessing bilateral symmetry, and detecting morphological differences linked to stem chirality, highlighting the encoding of genetic, environmental, and developmental information in leaf morphology.
RNA sequencing of the halophyte Salicornia europaea revealed that combined hypoxia‑salt stress triggers a unique transcriptional response, with 16% of genes specifically altered and distinct synergistic, antagonistic, and additive effects across functional pathways. Metabolic analyses indicated enhanced sucrose and trehalose metabolism, a shift toward lactate fermentation, and increased proline synthesis, highlighting complex regulatory strategies for coping with concurrent stresses.
In a controlled dry-down experiment, Arabis sagittata showed significantly higher recovery from drought than the endangered Arabis nemorensis, a difference that could not be traced to a single major QTL, indicating a polygenic basis. Transcriptome and small‑RNA sequencing revealed that A. sagittata mounts a stronger transcriptional response, including species‑specific regulation of the conserved drought miRNA miR408, and machine‑learning identified distinct cis‑regulatory motif patterns underlying these divergent stress‑response networks.
The study evaluated whether integrating genomic, transcriptomic, and drone-derived phenomic data improves prediction of 129 maize traits across nine environments, using both linear (rrBLUP) and nonlinear (SVR) models. Multi-omics models consistently outperformed single-omics models, with transcriptomic data especially enhancing cross‑environment predictions and capturing genotype‑by‑environment interactions. The results highlight the added value of combining transcriptomics and phenomics with genotypes for more accurate and generalizable trait prediction in maize.
The study examined whether colonisation by the arbuscular mycorrhizal fungus Rhizophagus irregularis primes immune responses in barley against the leaf rust pathogen Puccinia hordei. While AMF did not affect disease severity or plant growth, co‑infected leaves showed heightened expression of defence genes and transcriptome reprogramming, including altered protein ubiquitination, indicating a priming mechanism. These results highlight transcriptional and post‑translational pathways through which AMF can enhance barley disease resistance for sustainable crop protection.
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.