Search bioRxiv⌕ Search

bioRxiv · 10.64898/2026.04.28.721260

Drying kinetics govern transcriptional and post-transcriptional reprogramming during seed maturation

Abstract

Desiccation tolerance (DT) serves as a cornerstone for seed survival and for long-term persistence in the natural environment. DT is acquired during seed development, as seeds undergo a drastic change in internal water content during maturation drying. Although the physiological effects of drying on the acquisition of DT and other seed traits have been described, the molecular mechanisms underlying these effects have not yet been fully understood. Here, we addressed this gap by submitting maturing seeds of Arabidopsis thaliana L. to three different drying regimes - fast drying (FD), slow drying (SD), and a combination of both (SDFD) and studying physiological, transcriptional, and post-transcriptional responses. We found that SD not only accelerated DT acquisition but also seed maturation. Each drying regime showed a distinct transcriptional signature, with SD and SDFD showing greater global gene downregulation compared to FD. This downregulation appeared to be crucial for establishing DT in developing seeds. Interestingly, FD triggered a specific defense-related transcriptional response that was detrimental to seed longevity. Using an abscisic acid deficient mutant, we found that most of the drying-mediated transcriptional changes were largely independent of the wild-type ABA levels. On a post-transcriptional level, SD led to a major turnover of mRNA populations undergoing co-translational mRNA decay (CTRD) and promoted CTRD of stress-related genes. Overall, our study provides fundamental insights into the mechanisms by which seeds perceive and respond to drying, advancing our basic understanding of the molecular regulation of DT and seed maturation. Significance StatementSeed maturation is a critical phase of the plant life cycle when seeds acquire desiccation tolerance (DT) required for long-term storage. Drying rate, together with abscisic acid (ABA), has been implicated in this process, but whether seed development actively responds to different drying rates and how such responses are regulated has remained unclear. Here, we show that maturing seeds sense and respond to different drying regimes through distinct molecular programs, with slow drying triggering coordinated transcriptional and post-transcriptional reprogramming associated with enhanced DT. This response occurs partly independent of wild-type ABA levels, revealing drying rate as a developmental signal acting alongside hormonal regulation to direct seed maturation. These findings provide a framework for improving drying strategies and identifying molecular markers of seed quality.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sami, A. A., Willems, L. A. J., Abdulroheem, L., Carpentier, M.-C., Merret, R., Bentsink, L., Artur, M. A. S.. 2026-05-01. Drying kinetics govern transcriptional and post-transcriptional reprogramming during seed maturation. https://doi.org/10.64898/2026.04.28.721260

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

MpILR1 Hydrolyzes Jasmonate-Amino Acid Conjugates to Activate dn-iso-OPDA Signaling in Marchantia polymorpha.

Jasmonates are essential phytohormones that coordinate defense responses and developmental programs across land plants. In angiosperms, the active jasmonate ligand jasmonoyl-L-isoleucine (JA-Ile), is produced through GH3-mediated conjugation of jasmonic acid to isoleucine and JA-Ile homeostasis is further shaped by ILR1/ILL-family amidohydrolases. In contrast, the primary bioactive jasmonate ligand in bryophytes, dinor-12-oxo-phytodienoic acid (dn-iso-OPDA), is inactivated through conjugation with amino acids, raising the question of whether these conjugates constitute a reversible hormone reservoir or an irreversible catabolic end point. Although the ILR1-like family has been characterized extensively for its role in auxin and jasmonate homeostasis in angiosperms, its function in bryophytes remains basically unexplored. Here we show that MpILR1, the sole Marchantia ortholog of the ILR1/ILL family, hydrolyzes a specific subset of dn-iso-OPDA-amino acid conjugates in vivo. Loss-of-function Mpilr1 mutants exhibit enhanced accumulation of dn-iso-OPDA conjugated to hydrophobic amino acids (Val, Leu and Ile) but not to hydrophilic residues (His, Glu and Gln), demonstrating substrate-selective hydrolysis. MpILR1 hydrolytic activity is required for full dn-iso-OPDA-mediated responses, including transcriptional activation and defense against gastropod herbivory. These findings establish MpILR1 as a key positive regulator of jasmonate signaling in Marchantia polymorpha and suggest that hormone conjugation/deconjugation is an ancient regulatory mechanism evolved during plant terrestrialization.

plant biology↗

Drought-Spec-Net: Early Tomato Drought Detection and Potential Yield-Impact Assessment Using Vis NIR Data

Drought stress significantly reduces tomato (Solanum lycopersicum L.) productivity, and early detection is critical to minimize yield losses through timely interventions. In this study, we developed Drought-Spec-Net, a hybrid 1D convolutional neural network that integrates local and global spectral feature extraction to detect early drought stress from visible and near infrared (Vis NIR) spectra data of tomato seedlings. The model was trained on 378 samples using an 80:20 train test split, with 20% of the training set reserved for validation. DroughtSpecNet outperformed the evaluated baseline and state of the art models, achieving 97% accuracy, 95% precision, 98% recall, and an F1 score of 97%. To improve the agronomic interpretation of the model outputs, predicted drought probabilities were converted into a literature-informed potential yield impact indicator using a maximum impact level of 60%. On the test set (76 samples), mapped potential yield-impact values ranged from 0% to 60%, with an average reduction of 12.97%. We also conducted an initial experiment using our greenhouse RGB dataset, collected daily from drought treated and well-watered tomato plants at West Virginia State University (WVSU). From this dataset, 44 images were selected for ilastik-based canopy segmentation, producing plant-level drought severity indices (DSI) with a mean of 0.28, median of 0.14, and range of 0.01 to 0.91. Additionally, we trained and fine-tuned a large language model (LLM) based on PLLaMA7BInstruct, called AgriLLaMA, for automated agronomic report generation from Drought-Spec-Net outputs. The generated reports summarize predicted stress levels, mapped potential yield impacts, and preliminary management considerations. This integrated approach not only improves early drought stress detection but also delivers quantitative and interpretable estimates of potential productivity losses, providing a complete framework connecting physiological stress detection to actionable agricultural outcomes.

plant biology↗

BSA101: Unlocking Historical Mutant Collections with BSA-Seq

Forward genetics is a powerful approach for gene discovery, but identifying causal mutations becomes difficult when mutants are maintained in heterogeneous populations with uncertain pedigrees. This is exemplified by classical tasselseed (ts) mutants, which have long served as a genetic model for studying sex determination and carpel suppression. Decades of repeated outcrossing to diverse inbred lines have created substantial genetic heterogeneity, limiting the effectiveness of conventional bulked-segregant analysis sequencing (BSA-Seq). To address this, we developed a BSA-Seq framework that integrates flexible experimental designs, multiple reference genomes, and complementary statistical methods tailored for genetically heterogeneous populations. Applying this framework revealed that reference genome selection is critical for mapping success and that Euclidean distance raised to the fourth power (ED4) outperformed homozygosity mapping (HM). Furthermore, the framework enables simultaneous mapping of multiple mutations within a single population, eliminating the need for additional mapping populations. Applying this framework to 26 ts mutant stocks from the Maize Genetics Cooperation Stock Center, we successfully mapped 24 mutants to genomic intervals containing known ts genes, while the remaining mutants mapped to distinct genomic intervals, defining novel candidate regions underlying carpel suppression. Together, these results demonstrate that historical mutant collections represent an underutilized resource for gene discovery and establish a generalizable mapping strategy for unlocking their genetic potential across diverse species.

plant biology↗