Long non-coding RNAs (lncRNAs) are a prominent class of eukaryotic regulatory genes. Despite the numerous available transcriptomic datasets, the annotation of plant lncRNAs remains based on dated annotations that have been historically carried over. We present a substantially improved annotation of Arabidopsis thaliana lncRNAs, generated by integrating 224 transcriptomes in multiple tissues, conditions, and developmental stages. We annotate 6764 lncRNA genes, including 3772 that are novel. We characterize their tissue expression patterns and find 1425 lncRNAs are co-expressed with coding genes, with enriched functional categories such as chloroplast organization, photosynthesis, RNA regulation, transcription, and root development. This improved transcription-guided annotation constitutes a valuable resource for studying lncRNAs and the biological processes they may regulate.
Long non-coding RNAs (lncRNAs) have recently emerged as prominent regulators of gene expression in eukaryotes. LncRNAs often drive the modification and maintenance of gene activation or gene silencing states via chromatin conformation rearrangements. In plants, lncRNAs have been shown to participate in gene regulation, and are essential to processes such as vernalization and photomorphogenesis. Despite their prominent functions only over a dozen lncRNAs have been experimentally and functionally characterized.Similar to its animal counterparts, the rates of sequence divergence are much higher in plant lncRNAs than in protein coding mRNAs, making it difficult to identify lncRNA conservation using traditional sequence comparison methods. Beyond this, little is known about the evolutionary patterns of lncRNAs in plants. Here, we characterized the splicing conservation of lncRNAs in Brassicaceae. We generated a whole-genome alignment of 16 Brassica species and used it to identify synthenic lncRNA orthologues. Using a scoring system trained on transcriptomes from A. thaliana and B. oleracea, we identified splice sites across the whole alignment and measured their conservation. Our analysis revealed that 17.9% (112/627) of all intergenic lncRNAs display splicing conservation in at least one exon, an estimate that is substantially higher to previous estimates of lncRNA conservation in this group. Our findings agree with similar studies in vertebrates, demonstrating that splicing conservation can be evidence of stabilizing selection. We provide conclusive evidence for the existence of evolutionary deeply conserved lncRNAs in plants and describe a generally applicable computational workflow to identify functional lncRNAs in plants.
Transcription factors are important regulators of gene expression. They can orchestrate the activation or repression of hundreds or thousands of genes and control diverse processes in a coordinated way. This work explores the effect of a master regulator of plant development, BOLITA (BOL), in plant metabolism, with a special focus on specialized metabolism. For this, we used an Arabidopsis thaliana line in which the transcription factor activity can be induced. Fingerprinting metabolomic analyses of whole plantlets were performed at different times after induction. After 96 h, all induced replicas clustered as a single group, in contrast with all controls which did not cluster. Metabolomic analyses of shoot and root tissues enabled the putative identification of differentially accumulated metabolites in each tissue. Finally, the analysis of global gene expression in induced vs. non-induced root samples, together with enrichment analyses, allowed the identification of enriched metabolic pathways among the differentially expressed genes and accumulated metabolites after the induction. We concluded that the induction of BOL activity can modify the Arabidopsis metabolome. Future work should investigate whether its action is direct or indirect, and the implications of the metabolic changes for development regulation and bioprospection.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.