Biology subjects

Varala, K.

Publications and source records attributed to Varala, K..

4 recordsLinked to original sources

bioRxiv2026

Thiol depletion and disruption of proteostasis contribute to the phytotoxicity of juglone

O_LIJuglone is the phytotoxic 1,4-naphthoquinone responsible for the allelopathic effects of black walnut (Juglans nigra), yet how plants perceive and respond to juglone remain poorly understood. C_LIO_LIWe conducted transcriptome profiling of rosettes and roots of Arabidopsis thaliana exposed to juglone from 30 min to 5 d, along with targeted metabolic profiling, biochemical assays, and untargeted proteomics to gain a systems-level understanding of how plants respond to juglone and to test hypotheses underlying its phytotoxicity. C_LIO_LIJuglone exposure induced expression of genes involved in glutathione, cysteine, and sulfur metabolism pathways, and in protein homeostasis. We found that juglone depletes the pool of reduced glutathione (GSH) in roots, in part, through conjugation. We demonstrate that via upregulation of transcription factors (NAC53 and NAC78), the response to juglone activates components of the proteasome stress regulon and triggers extensive proteome remodeling with engagement of the autophagy pathway when proteasome capacity is limited. C_LIO_LIOur findings (i) indicate that thiol depletion and disruption of proteostasis through juglones dual redox cycling and alkylation activities are central to its phytotoxicity, (ii) cast doubt on previous reports that juglone targets a specific enzyme in plants or other organisms, and (iii) provide insight into how the chemical properties of allelopathic quinones shape their ecological roles. C_LI

plant biology↗

bioRxiv2026

Every Cell Counts: Tomato Root Responses to Nitrogen at Single-Cell Resolution

The heterogeneity of cell-types in plant roots provides the structural and mechanistic basis for root responses to developmental and environmental signals, including the availability of the major mineral nutrient nitrogen (N) in the soil. To date, single-cell-resolution analyses of transcriptional responses to external nitrogen supply remain limited in plant and crop species. Here, we performed single-cell multiomic profiling of tomato (Solanum lycopersicum) roots treated with different nitrogen conditions, generating a high-resolution map of root responses to environmental nitrogen availability. We identified root cell types important for nitrogen response, discovered transcriptional regulators and nitrogen-responsive genes in a cell-type-specific manner, and generated a gene regulatory network across nitrogen conditions that can be used to investigate transcriptional circuits in specific cell types. This single-cell-resolution nitrogen-responsive map of the tomato roots provides a valuable knowledge base for identifying candidate genes to improve nitrogen use efficiency in horticultural crop species.

plant biology↗

bioRxiv2023

The genome of the Wollemi pine, a critically endangered living fossil unchanged since the Cretaceous, reveals extensive ancient transposon activity.

We present the genome of the living fossil, Wollemia nobilis, a southern hemisphere conifer morphologically unchanged since the Cretaceous. Presumed extinct until rediscovery in 1994, the Wollemi pine is critically endangered with less than 60 wild adults threatened by intensifying bushfires in the Blue Mountains of Australia. The 12 Gb genome is among the most contiguous large plant genomes assembled, with extremely low heterozygosity and unusual abundance of DNA transposons. Reduced representation and genome re-sequencing of individuals confirms a relictual population since the last major glacial/drying period in Australia, 120 ky BP. Small RNA and methylome sequencing reveal conservation of ancient silencing mechanisms despite the presence of thousands of active and abundant transposons, including some transferred horizontally to conifers from arthropods in the Jurassic. A retrotransposon burst 8-6 my BP coincided with population decline, possibly as an adaptation enhancing epigenetic diversity. Wollemia, like other conifers, is susceptible to Phytophthora, and a suite of defense genes, similar to those in loblolly pine, are targeted for silencing by sRNAs in leaves. The genome provides insight into the earliest seed plants, while enabling conservation efforts.

genomics↗

bioRxiv2023

Genome-wide, Organ-delimited gene regulatory networks (OD-GRNs) provide high accuracy in candidate TF selection across diverse processes.

Construction of organ-specific gene expression datasets that include hundreds to thousands of experiments would greatly aid reconstruction of gene regulatory networks with organ-level spatial resolution. However, creating such datasets is greatly hampered by the requirements of extensive and tedious manual curation. Here we trained a supervised classification model that can accurately classify the organ-of-origin for a plant transcriptome. This K-Nearest Neighbor-based multiclass classifier was used to create organ-specific gene expression datasets for the leaf, root, shoot, flower, seed, seedling, silique, and stem in the model plant Arabidopsis thaliana. In the leaf, root, flower, seed and, a gene regulatory network (GRN) inference approach was used to determine: i. influential transcription factors (TFs) in that organ and, ii. the most influential TFs for specific biological processes in the organ. These genome-wide, organ-delimited GRNs (OD-GRNs), identified de novo many known regulators of organ development and processes operating in those organs. Moreover, many previously unknown TF regulators were highly ranked as potential master regulators of organ development or organ-specific processes. As a proof-of-concept, we focused on experimentally validating the predicted TF regulators of lipid biosynthesis in seeds, with relevance to food and biofuel production. Of the top twenty candidate TFs, eight (e.g., WRI1, LEC1, and FUS3) are known regulators of seed oil content. Importantly, we validated that seven more candidate TFs, whose role was previously unknown in seed lipid biosynthesis, indeed affect this process by genetics and physiological approaches, thus yielding a net accuracy rate of >75% for the de novo TF predictions. The general approach developed here could be extended to any species with sufficiently large gene expression datasets to speed up hypothesis generation and testing for constructing gene regulatory networks at a high spatial resolution. Significance StatementOur study develops a machine-learning framework for building extremely large gene expression datasets for each organ, and to infer organ-delimited gene regulatory networks. We show that this approach is very successful at predicting which transcription factors are going to regulate processes at an organ level. We validated the accuracy of the predictions for transcription factor regulators using the seed lipid synthesis pathway as a case study. We demonstrated a very high success rate for uncovering both known and novel transcription factor regulators for the seed lipid biosynthesis pathway. The approach described in this study is broadly applicable across any organism (plant or animal) that has a large body of public gene expression data.

plant biology↗