Long non-coding RNAs (lncRNAs) are RNA molecules with functions independent of any protein-coding potential. A whole transcriptome (RNA-seq) study of Arabidopsis shoots under iron sufficient and deficient conditions was carried out to determine the genes that are iron-regulated in the shoots. We identified two previously unannotated transcripts on chromosome 1 that are significantly iron-regulated. We have called this iron-regulated lncRNA, CAN OF SPINACH ( COS ). cos mutants have altered iron levels in leaves and seeds. Despite the low iron levels in the leaves, cos mutants have higher chlorophyll levels than WT plants. Moreover, cos mutants have abnormal development during iron deficiency. Roots of cos mutants are longer than those of WT plants, when grown on iron deficient medium. In addition, cos mutant plants accumulate singlet oxygen during iron deficiency. The mechanism through which COS affects iron deficiency responses is unclear, but small regions of sequence similarity to several genes involved in iron deficiency responses occur in COS , and small RNAs from these regions have been detected. We hypothesize that COS is required for normal adaptation to iron deficiency conditions.
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A Conserved Long Intergenic Non-coding RNA Containing snoRNA Sequences, lncCOBRA1, Affects Arabidopsis Germination and Development
Long non-coding RNAs (lncRNAs) are an increasingly studied group of non-protein coding transcripts with a wide variety of molecular functions gaining attention for their roles in numerous biological processes. Nearly 6,000 lncRNAs have been identified in Arabidopsis thaliana but many have yet to be studied. Here, we examine a class of previously uncharacterized lncRNAs termed CONSERVED IN BRASSICA RAPA ( lncCOBRA ) transcripts that were previously identified for their high level of sequence conservation in the related crop species Brassica rapa , their nuclear-localization and protein-bound nature. In particular, we focus on lncCOBRA1 and demonstrate that its abundance is highly tissue and developmental specific, with particularly high levels early in germination. lncCOBRA1 contains two snoRNAs domains within it, making it the first sno-lincRNA example in a non-mammalian system. However, we find that it is processed differently than its mammalian counterparts. We further show that plants lacking lncCOBRA1 display patterns of delayed germination and are overall smaller than wild-type plants. Lastly, we identify the proteins that interact with lncCOBRA1 and propose a novel mechanism of lincRNA action in which it may act as a scaffold with the RACK1A protein to regulate germination and development, possibly through a role in ribosome biogenesis.
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- Award ID(s):
- 1849708
- NSF-PAR ID:
- 10336843
- Date Published:
- Journal Name:
- Frontiers in Plant Science
- Volume:
- 13
- ISSN:
- 1664-462X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Long noncoding RNAs (lncRNAs) are commonly defined as transcripts that lack protein-coding capacity and are longer than 200 nucleotides. Since the emergence of next-generation sequencing technologies in this century, thousands of lncRNAs have been identified from nearly all living organisms. Notably, various pathogens also express their own lncRNAs in host cells during infection. In plants, many lncRNAs exhibit dynamic expression patterns in response to environmental stimuli, including pathogen attacks. In contrast to well-established methods in identifying such lncRNAs, the current understanding of lncRNAs’ functional mechanisms is in its infancy. Some lncRNAs serve as precursors for generating small RNAs or serve as target mimics to sequester functional small RNAs, which have been extensively reviewed in the literature. This review focuses on the emerging evidence supporting that certain lncRNAs function as negative or positive regulators of plant immunity. A common theme is that those regulations rely on specific interactions between lncRNAs and key regulatory proteins. Viroids as single-stranded circular noncoding RNAs provide a handle to investigate how RNA local motifs render interaction specificity between lncRNAs and regulatory proteins.
[Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .
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Abstract Long intergenic noncoding RNAs (lincRNAs) are a large yet enigmatic class of eukaryotic transcripts that can have critical biological functions. The wealth of RNA-sequencing (RNA-seq) data available for plants provides the opportunity to implement a harmonized identification and annotation effort for lincRNAs that enables cross-species functional and genomic comparisons as well as prioritization of functional candidates. In this study, we processed >24 Tera base pairs of RNA-seq data from >16,000 experiments to identify ∼130,000 lincRNAs in four Brassicaceae: Arabidopsis thaliana, Camelina sativa, Brassica rapa, and Eutrema salsugineum. We used nanopore RNA-seq, transcriptome-wide structural information, peptide data, and epigenomic data to characterize these lincRNAs and identify conserved motifs. We then used comparative genomic and transcriptomic approaches to highlight lincRNAs in our data set with sequence or transcriptional conservation. Finally, we used guilt-by-association analyses to assign putative functions to lincRNAs within our data set. We tested this approach on a subset of lincRNAs associated with germination and seed development, observing germination defects for Arabidopsis lines harboring T-DNA insertions at these loci. LincRNAs with Brassicaceae-conserved putative miRNA binding motifs, small open reading frames, or abiotic-stress modulated expression are a few of the annotations that will guide functional analyses into this cryptic portion of the transcriptome.more » « less
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Summary Many crops are polyploid or have a polyploid ancestry. Recent phylogenetic analyses have found that polyploidy often preceded the domestication of crop plants. One explanation for this observation is that increased genetic diversity following polyploidy may have been important during the strong artificial selection that occurs during domestication.
In order to test the connection between domestication and polyploidy, we identified and examined candidate genes associated with the domestication of the diverse crop varieties of
Brassica rapa . Like all ‘diploid’ flowering plants,B. rapa has a diploidized paleopolyploid genome and experienced many rounds of whole genome duplication (WGD). We analyzed transcriptome data of more than 100 cultivatedB. rapa accessions.Using a combination of approaches, we identified > 3000 candidate genes associated with the domestication of four major
B. rapa crop varieties. Consistent with our expectation, we found that the candidate genes were significantly enriched with genes derived from the Brassiceae mesohexaploidy. We also observed that paleologs were significantly more diverse than non‐paleologs.Our analyses find evidence for that genetic diversity derived from ancient polyploidy played a key role in the domestication of
B. rapa and provide support for its importance in the success of modern agriculture. -
Background: Long non-coding RNA plays a vital role in changing the expression profiles of various target genes that lead to cancer development. Thus, identifying prognostic lncRNAs related to different cancers might help in developing cancer therapy. Method: To discover the critical lncRNAs that can identify the origin of different cancers, we propose the use of the state-of-the-art deep learning algorithm concrete autoencoder (CAE) in an unsupervised setting, which efficiently identifies a subset of the most informative features. However, CAE does not identify reproducible features in different runs due to its stochastic nature. We thus propose a multi-run CAE (mrCAE) to identify a stable set of features to address this issue. The assumption is that a feature appearing in multiple runs carries more meaningful information about the data under consideration. The genome-wide lncRNA expression profiles of 12 different types of cancers, with a total of 4768 samples available in The Cancer Genome Atlas (TCGA), were analyzed to discover the key lncRNAs. The lncRNAs identified by multiple runs of CAE were added to a final list of key lncRNAs that are capable of identifying 12 different cancers. Results: Our results showed that mrCAE performs better in feature selection than single-run CAE, standard autoencoder (AE), and other state-of-the-art feature selection techniques. This study revealed a set of top-ranking 128 lncRNAs that could identify the origin of 12 different cancers with an accuracy of 95%. Survival analysis showed that 76 of 128 lncRNAs have the prognostic capability to differentiate high- and low-risk groups of patients with different cancers. Conclusion: The proposed mrCAE, which selects actual features, outperformed the AE even though it selects the latent or pseudo-features. By selecting actual features instead of pseudo-features, mrCAE can be valuable for precision medicine. The identified prognostic lncRNAs can be further studied to develop therapies for different cancers.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/fpls.2022.906603
