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He Y, Ning Z, Zhu X, Zhang Y, Liu C, Jiang S, Yuan Z, Zhang H. Plant lncRNA-miRNA Interaction Prediction Based on Counterfactual Heterogeneous Graph Attention Network. Interdiscip Sci 2024:10.1007/s12539-024-00652-9. [PMID: 39382820 DOI: 10.1007/s12539-024-00652-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 08/10/2024] [Accepted: 08/12/2024] [Indexed: 10/10/2024]
Abstract
Identifying interactions between long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) provides a new perspective for understanding regulatory relationships in plant life processes. Recently, computational methods based on graph neural networks (GNNs) have been widely employed to predict lncRNA-miRNA interactions (LMIs), which compensate for the inadequacy of biological experiments. However, the low-semantic and noise of graph limit the performance of existing GNN-based methods. In this paper, we develop a novel Counterfactual Heterogeneous Graph Attention Network (CFHAN) to improve the robustness to against the noise and the prediction of plant LMIs. Firstly, we construct a real-world based lncRNA-miRNA (L-M) heterogeneous network. Secondly, CFHAN utilizes the node-level attention, the semantic-level attention, and the counterfactual links to enhance the node embeddings learning. Finally, these embeddings are used as inputs for Multilayer Perceptron (MLP) to predict the interactions between lncRNAs and miRNAs. Evaluating our method on a benchmark dataset of plant LMIs, CFHAN outperforms five state-of-the-art methods, and achieves an average AUC and average ACC of 0.9953 and 0.9733, respectively. This demonstrates CFHAN's ability to predict plant LMIs and exhibits promising cross-species prediction ability, offering valuable insights for experimental LMI researches.
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Affiliation(s)
- Yu He
- College of Information and Intelligence, Hunan Agricultural University, Changsha, 410128, China
| | - ZiLan Ning
- College of Information and Intelligence, Hunan Agricultural University, Changsha, 410128, China
| | - XingHui Zhu
- College of Information and Intelligence, Hunan Agricultural University, Changsha, 410128, China
| | - YinQiong Zhang
- College of Information and Intelligence, Hunan Agricultural University, Changsha, 410128, China
| | - ChunHai Liu
- Hunan Engineering & Technology Research Center for Agricultural Big Data Analysis & Decision-Making, College of Plant Protection, Hunan Agricultural University, Changsha, 410128, China
| | - SiWei Jiang
- College of Information and Intelligence, Hunan Agricultural University, Changsha, 410128, China
| | - ZheMing Yuan
- Hunan Engineering & Technology Research Center for Agricultural Big Data Analysis & Decision-Making, College of Plant Protection, Hunan Agricultural University, Changsha, 410128, China.
| | - HongYan Zhang
- College of Information and Intelligence, Hunan Agricultural University, Changsha, 410128, China.
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2
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Szcześniak MW, Wanowska E. CANTATAdb 3.0: An Updated Repository of Plant Long Non-Coding RNAs. PLANT & CELL PHYSIOLOGY 2024; 65:1486-1493. [PMID: 39018027 PMCID: PMC11447640 DOI: 10.1093/pcp/pcae081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 07/09/2024] [Accepted: 07/16/2024] [Indexed: 07/18/2024]
Abstract
CANTATAdb 3.0 is an updated database of plant long non-coding RNAs (lncRNAs), containing 571,688 lncRNAs identified across 108 species, including 100 Magnoliopsida (flowering plants), a significant expansion from the previous version. A notable feature is the inclusion of 112,980 lncRNAs that are expressed specifically in certain plant organs or embryos, indicating their potential role in development and organ-specific processes. In addition, CANTATAdb 3.0 includes 74,886 pairs of evolutionarily conserved lncRNAs found across 47 species and inferred from genome-genome alignments as well as conserved lncRNAs obtained using a similarity search approach in 5,479 species pairs, which would further aid in the selection of lncRNAs for functional studies. Interestingly, we find that conserved lncRNAs with tissue-specific expression patterns tend to occupy the same plant organ across different species, pointing toward conserved biological roles. The database now offers extended search capabilities and downloadable data in popular formats, further facilitating research on plant lncRNAs.
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Affiliation(s)
- Michał Wojciech Szcześniak
- Laboratory of RNA Biology, Institute of Human Biology and Evolution, Adam Mickiewicz University, ul. Uniwersytetu Poznańskiego 6, Poznan 61-614, Poland
| | - Elżbieta Wanowska
- Laboratory of RNA Biology, Institute of Human Biology and Evolution, Adam Mickiewicz University, ul. Uniwersytetu Poznańskiego 6, Poznan 61-614, Poland
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3
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Villalba-Bermell P, Marquez-Molins J, Gomez G. A multispecies study reveals the diversity and potential regulatory role of long noncoding RNAs in cucurbits. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2024. [PMID: 39254680 DOI: 10.1111/tpj.17013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Revised: 07/31/2024] [Accepted: 08/23/2024] [Indexed: 09/11/2024]
Abstract
Plant long noncoding RNAs (lncRNAs) exhibit features such as tissue-specific expression, spatiotemporal regulation, and stress responsiveness. Although diverse studies support the regulatory role of lncRNAs in model plants, our knowledge about lncRNAs in crops is limited. We employ a custom pipeline on a dataset of over 1000 RNA-seq samples across nine representative species of the family Cucurbitaceae to predict 91 209 nonredundant lncRNAs. The lncRNAs were characterized according to three confidence levels and classified by their genomic context into intergenic, natural antisense, intronic, and sense-overlapping. Compared with protein-coding genes, lncRNAs were, on average, expressed at low levels and displayed significantly higher specificity when considering tissue, developmental stages, and stress responsiveness. The evolutionary analysis indicates higher positional conservation than sequence conservation, probably linked to the conserved modular motifs within syntenic lncRNAs. Moreover, a positive correlation between the expression of intergenic/natural antisense lncRNAs and their closest/parental gene was observed. For those intergenic, the correlation decreases with the distance to the neighboring gene, supporting that their potential cis-regulatory effect is within a short-range. Furthermore, the analysis of developmental studies showed that a conserved NAT-lncRNA family is differentially expressed in a coordinated way with their cognate sense protein-coding genes. These genes code for proteins associated with phloem development, thus providing insights about the potential involvement of some of the identified lncRNAs in a developmental process. We expect that this extensive inventory will constitute a valuable resource for further research lines focused on elucidating the regulatory mechanisms mediated by lncRNAs in cucurbits.
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Affiliation(s)
- Pascual Villalba-Bermell
- Institute for Integrative Systems Biology (I2SysBio), Consejo Superior de Investigaciones Científicas (CSIC) - Universitat de València (UV), Parc Científic, Cat. Agustín Escardino 9, 46980, Paterna, Spain
| | - Joan Marquez-Molins
- Institute for Integrative Systems Biology (I2SysBio), Consejo Superior de Investigaciones Científicas (CSIC) - Universitat de València (UV), Parc Científic, Cat. Agustín Escardino 9, 46980, Paterna, Spain
| | - Gustavo Gomez
- Institute for Integrative Systems Biology (I2SysBio), Consejo Superior de Investigaciones Científicas (CSIC) - Universitat de València (UV), Parc Científic, Cat. Agustín Escardino 9, 46980, Paterna, Spain
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4
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Adjeroh DA, Zhou X, Paschoal AR, Dimitrova N, Derevyanchuk EG, Shkurat TP, Loeb JA, Martinez I, Lipovich L. Challenges in LncRNA Biology: Views and Opinions. Noncoding RNA 2024; 10:43. [PMID: 39195572 DOI: 10.3390/ncrna10040043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2024] [Revised: 06/26/2024] [Accepted: 07/04/2024] [Indexed: 08/29/2024] Open
Abstract
This is a mini-review capturing the views and opinions of selected participants at the 2021 IEEE BIBM 3rd Annual LncRNA Workshop, held in Dubai, UAE. The views and opinions are expressed on five broad themes related to problems in lncRNA, namely, challenges in the computational analysis of lncRNAs, lncRNAs and cancer, lncRNAs in sports, lncRNAs and COVID-19, and lncRNAs in human brain activity.
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Affiliation(s)
- Donald A Adjeroh
- Lane Department of Computer Science and Electrical Engineering, West Virginia University (WVU), Morgantown, WV 26506, USA
| | - Xiaobo Zhou
- Department of Bioinformatics and Systems Medicine, University of Texas Health Science Center, Houston, TX 77030, USA
| | - Alexandre Rossi Paschoal
- Department of Computer Science, Bioinformatics and Pattern Recognition Group, Federal University of Technology-Paraná-UTFPR, Curitiba 86300-000, Brazil
- Rosalind Franklin Institute, Harwell Science and Innovation Campus, Didcot OX11 0FA, UK
| | - Nadya Dimitrova
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520, USA
| | | | - Tatiana P Shkurat
- Department of Genetics, Southern Federal University, Rostov-on-Don 344090, Russia
| | - Jeffrey A Loeb
- Department of Neurology and Rehabilitation, The Center for Clinical and Translational Science, The University of Illinois NeuroRepository, University of Illinois, Chicago, IL 60607, USA
| | - Ivan Martinez
- Department of Microbiology, Immunology & Cell Biology, WVU Cancer Institute, West Virginia University (WVU) School of Medicine, Morgantown, WV 26505, USA
| | - Leonard Lipovich
- Shenzhen Huayuan Biological Science Research Institute, Shenzhen Huayuan Biotechnology Co., Ltd., Shenzhen 518000, China
- Center for Molecular Medicine and Genetics, School of Medicine, Wayne State University, Detroit, MI 48201, USA
- College of Science, Mathematics and Technology, Wenzhou-Kean University, Wenzhou 325060, China
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5
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Mendoza-Revilla J, Trop E, Gonzalez L, Roller M, Dalla-Torre H, de Almeida BP, Richard G, Caton J, Lopez Carranza N, Skwark M, Laterre A, Beguir K, Pierrot T, Lopez M. A foundational large language model for edible plant genomes. Commun Biol 2024; 7:835. [PMID: 38982288 PMCID: PMC11233511 DOI: 10.1038/s42003-024-06465-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 06/17/2024] [Indexed: 07/11/2024] Open
Abstract
Significant progress has been made in the field of plant genomics, as demonstrated by the increased use of high-throughput methodologies that enable the characterization of multiple genome-wide molecular phenotypes. These findings have provided valuable insights into plant traits and their underlying genetic mechanisms, particularly in model plant species. Nonetheless, effectively leveraging them to make accurate predictions represents a critical step in crop genomic improvement. We present AgroNT, a foundational large language model trained on genomes from 48 plant species with a predominant focus on crop species. We show that AgroNT can obtain state-of-the-art predictions for regulatory annotations, promoter/terminator strength, tissue-specific gene expression, and prioritize functional variants. We conduct a large-scale in silico saturation mutagenesis analysis on cassava to evaluate the regulatory impact of over 10 million mutations and provide their predicted effects as a resource for variant characterization. Finally, we propose the use of the diverse datasets compiled here as the Plants Genomic Benchmark (PGB), providing a comprehensive benchmark for deep learning-based methods in plant genomic research. The pre-trained AgroNT model is publicly available on HuggingFace at https://huggingface.co/InstaDeepAI/agro-nucleotide-transformer-1b for future research purposes.
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6
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Zhang A, Pi W, Wang Y, Li Y, Wang J, Liu S, Cui X, Liu H, Yao D, Zhao R. Update on functional analysis of long non-coding RNAs in common crops. FRONTIERS IN PLANT SCIENCE 2024; 15:1389154. [PMID: 38872885 PMCID: PMC11169716 DOI: 10.3389/fpls.2024.1389154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Accepted: 05/08/2024] [Indexed: 06/15/2024]
Abstract
With the rapid advances in next-generation sequencing technology, numerous non-protein-coding transcripts have been identified, including long noncoding RNAs (lncRNAs), which are functional RNAs comprising more than 200 nucleotides. Although lncRNA-mediated regulatory processes have been extensively investigated in animals, there has been considerably less research on plant lncRNAs. Nevertheless, multiple studies on major crops showed lncRNAs are involved in crucial processes, including growth and development, reproduction, and stress responses. This review summarizes the progress in the research on lncRNA roles in several major crops, presents key strategies for exploring lncRNAs in crops, and discusses current challenges and future prospects. The insights provided in this review will enhance our comprehension of lncRNA functions in crops, with potential implications for improving crop genetics and breeding.
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Affiliation(s)
- Aijing Zhang
- College of Life Science, Jilin Agricultural University, Changchun, Jilin, China
- College of Agronomy, Jilin Agricultural University, Changchun, China
| | - Wenxuan Pi
- College of Life Science, Jilin Agricultural University, Changchun, Jilin, China
| | - Yashuo Wang
- College of Life Science, Jilin Agricultural University, Changchun, Jilin, China
| | - Yuxin Li
- College of Life Science, Jilin Agricultural University, Changchun, Jilin, China
| | - Jiaxin Wang
- College of Life Science, Jilin Agricultural University, Changchun, Jilin, China
| | - Shuying Liu
- College of Life Science, Jilin Agricultural University, Changchun, Jilin, China
| | - Xiyan Cui
- College of Life Science, Jilin Agricultural University, Changchun, Jilin, China
| | - Huijing Liu
- College of Life Science, Jilin Agricultural University, Changchun, Jilin, China
| | - Dan Yao
- College of Life Science, Jilin Agricultural University, Changchun, Jilin, China
| | - Rengui Zhao
- College of Agronomy, Jilin Agricultural University, Changchun, China
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7
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Nagle MF, Yuan J, Kaur D, Ma C, Peremyslova E, Jiang Y, Goralogia GS, Magnuson A, Li JY, Muchero W, Fuxin L, Strauss SH. Genome-wide association study and network analysis of in vitro transformation in Populus trichocarpa support key roles of diverse phytohormone pathways and cross talk. THE NEW PHYTOLOGIST 2024. [PMID: 38650352 DOI: 10.1111/nph.19737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 03/06/2024] [Indexed: 04/25/2024]
Abstract
Wide variation in amenability to transformation and regeneration (TR) among many plant species and genotypes presents a challenge to the use of genetic engineering in research and breeding. To help understand the causes of this variation, we performed association mapping and network analysis using a population of 1204 wild trees of Populus trichocarpa (black cottonwood). To enable precise and high-throughput phenotyping of callus and shoot TR, we developed a computer vision system that cross-referenced complementary red, green, and blue (RGB) and fluorescent-hyperspectral images. We performed association mapping using single-marker and combined variant methods, followed by statistical tests for epistasis and integration of published multi-omic datasets to identify likely regulatory hubs. We report 409 candidate genes implicated by associations within 5 kb of coding sequences, and epistasis tests implicated 81 of these candidate genes as regulators of one another. Gene ontology terms related to protein-protein interactions and transcriptional regulation are overrepresented, among others. In addition to auxin and cytokinin pathways long established as critical to TR, our results highlight the importance of stress and wounding pathways. Potential regulatory hubs of signaling within and across these pathways include GROWTH REGULATORY FACTOR 1 (GRF1), PHOSPHATIDYLINOSITOL 4-KINASE β1 (PI-4Kβ1), and OBF-BINDING PROTEIN 1 (OBP1).
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Affiliation(s)
- Michael F Nagle
- Department of Forest Ecosystems & Society, Oregon State University, Corvallis, OR, 97331, USA
| | - Jialin Yuan
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, 97331, USA
| | - Damanpreet Kaur
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, 97331, USA
| | - Cathleen Ma
- Department of Forest Ecosystems & Society, Oregon State University, Corvallis, OR, 97331, USA
| | - Ekaterina Peremyslova
- Department of Forest Ecosystems & Society, Oregon State University, Corvallis, OR, 97331, USA
| | - Yuan Jiang
- Statistics Department, Oregon State University, Corvallis, OR, 97331, USA
| | - Greg S Goralogia
- Department of Forest Ecosystems & Society, Oregon State University, Corvallis, OR, 97331, USA
| | - Anna Magnuson
- Department of Forest Ecosystems & Society, Oregon State University, Corvallis, OR, 97331, USA
| | - Jia Yi Li
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, 97331, USA
| | - Wellington Muchero
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37830, USA
- Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, 37830, USA
- Bredesen Center for Interdisciplinary Research, University of Tennessee, Knoxville, TN, 37996, USA
| | - Li Fuxin
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, 97331, USA
| | - Steven H Strauss
- Department of Forest Ecosystems & Society, Oregon State University, Corvallis, OR, 97331, USA
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8
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Zhang C, Jiang M, Liu J, Wu B, Liu C. Genome-wide view and characterization of natural antisense transcripts in Cannabis Sativa L. PLANT MOLECULAR BIOLOGY 2024; 114:47. [PMID: 38632206 DOI: 10.1007/s11103-024-01434-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 02/25/2024] [Indexed: 04/19/2024]
Abstract
Natural Antisense Transcripts (NATs) are a kind of complex regulatory RNAs that play crucial roles in gene expression and regulation. However, the NATs in Cannabis Sativa L., a widely economic and medicinal plant rich in cannabinoids remain unknown. In this study, we comprehensively predicted C. sativa NATs genome-wide using strand-specific RNA sequencing (ssRNA-Seq) data, and validated the expression profiles by strand-specific quantitative reverse transcription PCR (ssRT-qPCR). Consequently, a total of 307 NATs were predicted in C. sativa, including 104 cis- and 203 trans- NATs. Functional enrichment analysis demonstrated the potential involvement of the C. sativa NATs in DNA polymerase activity, RNA-DNA hybrid ribonuclease activity, and nucleic acid binding. Finally, 18 cis- and 376 trans- NAT-ST pairs were predicted to produce 621 cis- and 5,679 trans- small interfering RNA (nat-siRNAs), respectively. These nat-siRNAs were potentially involved in the biosynthesis of cannabinoids and cellulose. All these results will shed light on the regulation of NATs and nat-siRNAs in C. sativa.
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Affiliation(s)
- Chang Zhang
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 151, Malianwa North Road, Haidian District, 100193, Beijing, China
| | - Mei Jiang
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 151, Malianwa North Road, Haidian District, 100193, Beijing, China
- School of Pharmaceutical Sciences, Qilu University of Technology, Shandong Academy of Sciences, Jinan, China
| | - Jingting Liu
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 151, Malianwa North Road, Haidian District, 100193, Beijing, China
| | - Bin Wu
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 151, Malianwa North Road, Haidian District, 100193, Beijing, China.
| | - Chang Liu
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 151, Malianwa North Road, Haidian District, 100193, Beijing, China.
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9
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Nagle MF, Yuan J, Kaur D, Ma C, Peremyslova E, Jiang Y, Niño de Rivera A, Jawdy S, Chen JG, Feng K, Yates TB, Tuskan GA, Muchero W, Fuxin L, Strauss SH. GWAS supported by computer vision identifies large numbers of candidate regulators of in planta regeneration in Populus trichocarpa. G3 (BETHESDA, MD.) 2024; 14:jkae026. [PMID: 38325329 PMCID: PMC10989874 DOI: 10.1093/g3journal/jkae026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 01/18/2024] [Accepted: 01/20/2024] [Indexed: 02/09/2024]
Abstract
Plant regeneration is an important dimension of plant propagation and a key step in the production of transgenic plants. However, regeneration capacity varies widely among genotypes and species, the molecular basis of which is largely unknown. Association mapping methods such as genome-wide association studies (GWAS) have long demonstrated abilities to help uncover the genetic basis of trait variation in plants; however, the performance of these methods depends on the accuracy and scale of phenotyping. To enable a large-scale GWAS of in planta callus and shoot regeneration in the model tree Populus, we developed a phenomics workflow involving semantic segmentation to quantify regenerating plant tissues over time. We found that the resulting statistics were of highly non-normal distributions, and thus employed transformations or permutations to avoid violating assumptions of linear models used in GWAS. We report over 200 statistically supported quantitative trait loci (QTLs), with genes encompassing or near to top QTLs including regulators of cell adhesion, stress signaling, and hormone signaling pathways, as well as other diverse functions. Our results encourage models of hormonal signaling during plant regeneration to consider keystone roles of stress-related signaling (e.g. involving jasmonates and salicylic acid), in addition to the auxin and cytokinin pathways commonly considered. The putative regulatory genes and biological processes we identified provide new insights into the biological complexity of plant regeneration, and may serve as new reagents for improving regeneration and transformation of recalcitrant genotypes and species.
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Affiliation(s)
- Michael F Nagle
- Department of Forest Ecosystems and Society, Oregon State University, 321 Richardson Hall, Corvallis, OR 97311, USA
| | - Jialin Yuan
- Department of Electrical Engineering and Computer Science, Oregon State University, 1148 Kelley Engineering Center, Corvallis, OR 97331, USA
| | - Damanpreet Kaur
- Department of Electrical Engineering and Computer Science, Oregon State University, 1148 Kelley Engineering Center, Corvallis, OR 97331, USA
| | - Cathleen Ma
- Department of Forest Ecosystems and Society, Oregon State University, 321 Richardson Hall, Corvallis, OR 97311, USA
| | - Ekaterina Peremyslova
- Department of Forest Ecosystems and Society, Oregon State University, 321 Richardson Hall, Corvallis, OR 97311, USA
| | - Yuan Jiang
- Statistics Department, Oregon State University, 239 Weniger Hall, Corvallis, OR 97331, USA
| | - Alexa Niño de Rivera
- Department of Forest Ecosystems and Society, Oregon State University, 321 Richardson Hall, Corvallis, OR 97311, USA
| | - Sara Jawdy
- Biosciences Division, Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831, USA
- Center for Bioenergy Innovation, Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831, USA
| | - Jin-Gui Chen
- Biosciences Division, Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831, USA
- Center for Bioenergy Innovation, Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831, USA
- Bredesen Center for Interdisciplinary Research, University of Tennessee-Knoxville, 310 Ferris Hall 1508 Middle Dr, Knoxville, TN 37996, USA
| | - Kai Feng
- Biosciences Division, Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831, USA
- Center for Bioenergy Innovation, Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831, USA
| | - Timothy B Yates
- Biosciences Division, Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831, USA
- Center for Bioenergy Innovation, Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831, USA
- Bredesen Center for Interdisciplinary Research, University of Tennessee-Knoxville, 310 Ferris Hall 1508 Middle Dr, Knoxville, TN 37996, USA
| | - Gerald A Tuskan
- Biosciences Division, Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831, USA
- Center for Bioenergy Innovation, Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831, USA
| | - Wellington Muchero
- Biosciences Division, Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831, USA
- Center for Bioenergy Innovation, Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831, USA
- Bredesen Center for Interdisciplinary Research, University of Tennessee-Knoxville, 310 Ferris Hall 1508 Middle Dr, Knoxville, TN 37996, USA
| | - Li Fuxin
- Department of Electrical Engineering and Computer Science, Oregon State University, 1148 Kelley Engineering Center, Corvallis, OR 97331, USA
| | - Steven H Strauss
- Department of Forest Ecosystems and Society, Oregon State University, 321 Richardson Hall, Corvallis, OR 97311, USA
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Cao W, Yang L, Zhuang M, Lv H, Wang Y, Zhang Y, Ji J. Plant non-coding RNAs: The new frontier for the regulation of plant development and adaptation to stress. PLANT PHYSIOLOGY AND BIOCHEMISTRY : PPB 2024; 208:108435. [PMID: 38402798 DOI: 10.1016/j.plaphy.2024.108435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 02/07/2024] [Accepted: 02/11/2024] [Indexed: 02/27/2024]
Abstract
Most plant transcriptomes constitute functional non-coding RNAs (ncRNAs) that lack the ability to encode proteins. In recent years, more research has demonstrated that ncRNAs play important regulatory roles in almost all plant biological processes by modulating gene expression. Thus, it is important to study the biogenesis and function of ncRNAs, particularly in plant growth and development and stress tolerance. In this review, we systematically explore the process of formation and regulatory mechanisms of ncRNAs, particularly those of microRNAs (miRNAs), small interfering RNAs (siRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs). Additionally, we provide a comprehensive overview of the recent advancements in ncRNAs research, including their regulation of plant growth and development (seed germination, root growth, leaf morphogenesis, floral development, and fruit and seed development) and responses to abiotic and biotic stress (drought, heat, cold, salinity, pathogens and insects). We also discuss research challenges and provide recommendations to advance the understanding of the roles of ncRNAs in agronomic applications.
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Affiliation(s)
- Wenxue Cao
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture and Rural Affairs/Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, No. 12 ZhongGuanCun South St., Beijing 100081, China
| | - Limei Yang
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture and Rural Affairs/Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, No. 12 ZhongGuanCun South St., Beijing 100081, China
| | - Mu Zhuang
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture and Rural Affairs/Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, No. 12 ZhongGuanCun South St., Beijing 100081, China
| | - Honghao Lv
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture and Rural Affairs/Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, No. 12 ZhongGuanCun South St., Beijing 100081, China
| | - Yong Wang
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture and Rural Affairs/Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, No. 12 ZhongGuanCun South St., Beijing 100081, China
| | - Yangyong Zhang
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture and Rural Affairs/Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, No. 12 ZhongGuanCun South St., Beijing 100081, China.
| | - Jialei Ji
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture and Rural Affairs/Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, No. 12 ZhongGuanCun South St., Beijing 100081, China.
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11
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Kornienko AE, Nizhynska V, Molla Morales A, Pisupati R, Nordborg M. Population-level annotation of lncRNAs in Arabidopsis reveals extensive expression variation associated with transposable element-like silencing. THE PLANT CELL 2023; 36:85-111. [PMID: 37683092 PMCID: PMC10734619 DOI: 10.1093/plcell/koad233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 07/07/2023] [Accepted: 07/30/2023] [Indexed: 09/10/2023]
Abstract
Long noncoding RNAs (lncRNAs) are understudied and underannotated in plants. In mammals, lncRNA loci are nearly as ubiquitous as protein-coding genes, and their expression is highly variable between individuals of the same species. Using Arabidopsis thaliana as a model, we aimed to elucidate the true scope of lncRNA transcription across plants from different regions and study its natural variation. We used transcriptome deep sequencing data sets spanning hundreds of natural accessions and several developmental stages to create a population-wide annotation of lncRNAs, revealing thousands of previously unannotated lncRNA loci. While lncRNA transcription is ubiquitous in the genome, most loci appear to be actively silenced and their expression is extremely variable between natural accessions. This high expression variability is largely caused by the high variability of repressive chromatin levels at lncRNA loci. High variability was particularly common for intergenic lncRNAs (lincRNAs), where pieces of transposable elements (TEs) present in 50% of these lincRNA loci are associated with increased silencing and variation, and such lncRNAs tend to be targeted by the TE silencing machinery. We created a population-wide lncRNA annotation in Arabidopsis and improve our understanding of plant lncRNA genome biology, raising fundamental questions about what causes transcription and silencing across the genome.
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Affiliation(s)
- Aleksandra E Kornienko
- Gregor Mendel Institute, Austrian Academy of Sciences, Vienna Biocenter, Dr. Bohr-gasse 3, Vienna 1030, Austria
| | - Viktoria Nizhynska
- Gregor Mendel Institute, Austrian Academy of Sciences, Vienna Biocenter, Dr. Bohr-gasse 3, Vienna 1030, Austria
| | - Almudena Molla Morales
- Gregor Mendel Institute, Austrian Academy of Sciences, Vienna Biocenter, Dr. Bohr-gasse 3, Vienna 1030, Austria
| | - Rahul Pisupati
- Gregor Mendel Institute, Austrian Academy of Sciences, Vienna Biocenter, Dr. Bohr-gasse 3, Vienna 1030, Austria
| | - Magnus Nordborg
- Gregor Mendel Institute, Austrian Academy of Sciences, Vienna Biocenter, Dr. Bohr-gasse 3, Vienna 1030, Austria
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12
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Jha UC, Nayyar H, Roychowdhury R, Prasad PVV, Parida SK, Siddique KHM. Non-coding RNAs (ncRNAs) in plant: Master regulators for adapting to extreme temperature conditions. PLANT PHYSIOLOGY AND BIOCHEMISTRY : PPB 2023; 205:108164. [PMID: 38008006 DOI: 10.1016/j.plaphy.2023.108164] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 10/30/2023] [Accepted: 11/02/2023] [Indexed: 11/28/2023]
Abstract
Unusual daily temperature fluctuations caused by climate change and climate variability adversely impact agricultural crop production. Since plants are immobile and constantly receive external environmental signals, such as extreme high (heat) and low (cold) temperatures, they have developed complex molecular regulatory mechanisms to cope with stressful situations to sustain their natural growth and development. Among these mechanisms, non-coding RNAs (ncRNAs), particularly microRNAs (miRNAs), small-interfering RNAs (siRNAs), and long-non-coding RNAs (lncRNAs), play a significant role in enhancing heat and cold stress tolerance. This review explores the pivotal findings related to miRNAs, siRNAs, and lncRNAs, elucidating how they functionally regulate plant adaptation to extreme temperatures. In addition, this review addresses the challenges associated with uncovering these non-coding RNAs and understanding their roles in orchestrating heat and cold tolerance in plants.
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Affiliation(s)
- Uday Chand Jha
- Sustainable Intensification Innovation Lab, Kansas State University, Department of Agronomy, Manhattan, KS 66506, USA; ICAR-Indian Institute of Pulses Research, Kanpur, Uttar Pradesh 208024, India.
| | - Harsh Nayyar
- Department of Botany, Panjab University, Chandigarh, 160014, India.
| | - Rajib Roychowdhury
- Department of Plant Pathology and Weed Research, Institute of Plant Protection, Agricultural Research Organization (ARO) - The Volcani Institute, Rishon Lezion 7505101, Israel
| | - P V Vara Prasad
- Sustainable Intensification Innovation Lab, Kansas State University, Department of Agronomy, Manhattan, KS 66506, USA
| | - Swarup K Parida
- National Institute of Plant Genomic Research, New Delhi, 110067, India
| | - Kadambot H M Siddique
- The UWA Institute of Agriculture, The University of Western Australia, Perth, WA 6001, Australia
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13
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Danilevicz MF, Gill M, Fernandez CGT, Petereit J, Upadhyaya SR, Batley J, Bennamoun M, Edwards D, Bayer PE. DNABERT-based explainable lncRNA identification in plant genome assemblies. Comput Struct Biotechnol J 2023; 21:5676-5685. [PMID: 38058296 PMCID: PMC10696397 DOI: 10.1016/j.csbj.2023.11.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 11/13/2023] [Accepted: 11/13/2023] [Indexed: 12/08/2023] Open
Abstract
Long non-coding ribonucleic acids (lncRNAs) have been shown to play an important role in plant gene regulation, involving both epigenetic and transcript regulation. LncRNAs are transcripts longer than 200 nucleotides that are not translated into functional proteins but can be translated into small peptides. Machine learning models have predominantly used transcriptome data with manually defined features to detect lncRNAs, however, they often underrepresent the abundance of lncRNAs and can be biased in their detection. Here we present a study using Natural Language Processing (NLP) models to identify plant lncRNAs from genomic sequences rather than transcriptomic data. The NLP models were trained to predict lncRNAs for seven model and crop species (Zea mays, Arabidopsis thaliana, Brassica napus, Brassica oleracea, Brassica rapa, Glycine max and Oryza sativa) using publicly available genomic references. We demonstrated that lncRNAs can be accurately predicted from genomic sequences with the highest accuracy of 83.4% for Z. mays and the lowest accuracy of 57.9% for B. rapa, revealing that genome assembly quality might affect the accuracy of lncRNA identification. Furthermore, we demonstrated the potential of using NLP models for cross-species prediction with an average of 63.1% accuracy using target species not previously seen by the model. As more species are incorporated into the training datasets, we expect the accuracy to increase, becoming a more reliable tool for uncovering novel lncRNAs. Finally, we show that the models can be interpreted using explainable artificial intelligence to identify motifs important to lncRNA prediction and that these motifs frequently flanked the lncRNA sequence.
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Affiliation(s)
| | - Mitchell Gill
- School of Biological Sciences, University of Western Australia, Australia
| | | | - Jakob Petereit
- School of Biological Sciences, University of Western Australia, Australia
| | | | - Jacqueline Batley
- School of Biological Sciences, University of Western Australia, Australia
| | - Mohammed Bennamoun
- School of Physics, Mathematics and Computing, University of Western Australia, Australia
| | - David Edwards
- School of Biological Sciences, University of Western Australia, Australia
| | - Philipp E. Bayer
- School of Biological Sciences, University of Western Australia, Australia
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14
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Domínguez-Rosas E, Hernández-Oñate MÁ, Fernandez-Valverde SL, Tiznado-Hernández ME. Plant long non-coding RNAs: identification and analysis to unveil their physiological functions. FRONTIERS IN PLANT SCIENCE 2023; 14:1275399. [PMID: 38023843 PMCID: PMC10644886 DOI: 10.3389/fpls.2023.1275399] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 10/09/2023] [Indexed: 12/01/2023]
Abstract
Eukaryotic genomes encode thousands of RNA molecules; however, only a minimal fraction is translated into proteins. Among the non-coding elements, long non-coding RNAs (lncRNAs) play important roles in diverse biological processes. LncRNAs are associated mainly with the regulation of the expression of the genome; nonetheless, their study has just scratched the surface. This is somewhat due to the lack of widespread conservation at the sequence level, in addition to their relatively low and highly tissue-specific expression patterns, which makes their exploration challenging, especially in plant genomes where only a few of these molecules have been described completely. Recently published high-quality genomes of crop plants, along with new computational tools, are considered promising resources for studying these molecules in plants. This review briefly summarizes the characteristics of plant lncRNAs, their presence and conservation, the different protocols to find these elements, and the limitations of these protocols. Likewise, it describes their roles in different plant physiological phenomena. We believe that the study of lncRNAs can help to design strategies to reduce the negative effect of biotic and abiotic stresses on the yield of crop plants and, in the future, help create fruits and vegetables with improved nutritional content, higher amounts of compounds with positive effects on human health, better organoleptic characteristics, and fruits with a longer postharvest shelf life.
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Affiliation(s)
- Edmundo Domínguez-Rosas
- Coordinación de Tecnología de Alimentos de Origen Vegeta, Centro de Investigación en Alimentación y Desarrollo, Hermosillo, Sonora, Mexico
| | | | | | - Martín Ernesto Tiznado-Hernández
- Coordinación de Tecnología de Alimentos de Origen Vegeta, Centro de Investigación en Alimentación y Desarrollo, Hermosillo, Sonora, Mexico
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15
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Hazra S, Moulick D, Mukherjee A, Sahib S, Chowardhara B, Majumdar A, Upadhyay MK, Yadav P, Roy P, Santra SC, Mandal S, Nandy S, Dey A. Evaluation of efficacy of non-coding RNA in abiotic stress management of field crops: Current status and future prospective. PLANT PHYSIOLOGY AND BIOCHEMISTRY : PPB 2023; 203:107940. [PMID: 37738864 DOI: 10.1016/j.plaphy.2023.107940] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 07/23/2023] [Accepted: 08/04/2023] [Indexed: 09/24/2023]
Abstract
Abiotic stresses are responsible for the major losses in crop yield all over the world. Stresses generate harmful ROS which can impair cellular processes in plants. Therefore, plants have evolved antioxidant systems in defence against the stress-induced damages. The frequency of occurrence of abiotic stressors has increased several-fold due to the climate change experienced in recent times and projected for the future. This had particularly aggravated the risk of yield losses and threatened global food security. Non-coding RNAs are the part of eukaryotic genome that does not code for any proteins. However, they have been recently found to have a crucial role in the responses of plants to both abiotic and biotic stresses. There are different types of ncRNAs, for example, miRNAs and lncRNAs, which have the potential to regulate the expression of stress-related genes at the levels of transcription, post-transcription, and translation of proteins. The lncRNAs are also able to impart their epigenetic effects on the target genes through the alteration of the status of histone modification and organization of the chromatins. The current review attempts to deliver a comprehensive account of the role of ncRNAs in the regulation of plants' abiotic stress responses through ROS homeostasis. The potential applications ncRNAs in amelioration of abiotic stresses in field crops also have been evaluated.
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Affiliation(s)
- Swati Hazra
- Sharda School of Agricultural Sciences, Sharda University, Greater Noida, Uttar Pradesh 201310, India.
| | - Debojyoti Moulick
- Department of Environmental Science, University of Kalyani, Nadia, West Bengal 741235, India.
| | | | - Synudeen Sahib
- S. S. Cottage, Njarackal, P.O.: Perinad, Kollam, 691601, Kerala, India.
| | - Bhaben Chowardhara
- Department of Botany, Faculty of Science and Technology, Arunachal University of Studies, Arunachal Pradesh 792103, India.
| | - Arnab Majumdar
- Department of Earth Sciences, Indian Institute of Science Education and Research (IISER) Kolkata, West Bengal 741246, India.
| | - Munish Kumar Upadhyay
- Department of Civil Engineering, Indian Institute of Technology Kanpur, Uttar Pradesh 208016, India.
| | - Poonam Yadav
- Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, Uttar Pradesh 221005, India.
| | - Priyabrata Roy
- Department of Molecular Biology and Biotechnology, University of Kalyani, West Bengal 741235, India.
| | - Subhas Chandra Santra
- Department of Environmental Science, University of Kalyani, Nadia, West Bengal 741235, India.
| | - Sayanti Mandal
- Department of Biotechnology, Dr. D. Y. Patil Arts, Commerce & Science College (affiliated to Savitribai Phule Pune University), Sant Tukaram Nagar, Pimpri, Pune, Maharashtra-411018, India.
| | - Samapika Nandy
- School of Pharmacy, Graphic Era Hill University, Bell Road, Clement Town, Dehradun, 248002, Uttarakhand, India; Department of Botany, Vedanta College, 33A Shiv Krishna Daw Lane, Kolkata-700054, India.
| | - Abhijit Dey
- Department of Life Sciences, Presidency University, Kolkata, West Bengal 700073, India.
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16
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Tseng KC, Wu NY, Chow CN, Zheng HQ, Chou CY, Yang CW, Wang MJ, Chang SB, Chang WC. JustRNA: a database of plant long noncoding RNA expression profiles and functional network. JOURNAL OF EXPERIMENTAL BOTANY 2023; 74:4949-4958. [PMID: 37523674 DOI: 10.1093/jxb/erad186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 06/01/2023] [Indexed: 08/02/2023]
Abstract
Long noncoding RNAs (lncRNAs) are regulatory RNAs involved in numerous biological processes. Many plant lncRNAs have been identified, but their regulatory mechanisms remain largely unknown. A resource that enables the investigation of lncRNA activity under various conditions is required because the co-expression between lncRNAs and protein-coding genes may reveal the effects of lncRNAs. This study developed JustRNA, an expression profiling resource for plant lncRNAs. The platform currently contains 1 088 565 lncRNA annotations for 80 plant species. In addition, it includes 3692 RNA-seq samples derived from 825 conditions in six model plants. Functional network reconstruction provides insight into the regulatory roles of lncRNAs. Genomic association analysis and microRNA target prediction can be employed to depict potential interactions with nearby genes and microRNAs, respectively. Subsequent co-expression analysis can be employed to strengthen confidence in the interactions among genes. Chromatin immunoprecipitation sequencing data of transcription factors and histone modifications were integrated into the JustRNA platform to identify the transcriptional regulation of lncRNAs in several plant species. The JustRNA platform provides researchers with valuable insight into the regulatory mechanisms of plant lncRNAs. JustRNA is a free platform that can be accessed at http://JustRNA.itps.ncku.edu.tw.
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Affiliation(s)
- Kuan-Chieh Tseng
- Department of Life Sciences, National Cheng Kung University, Tainan 701, Taiwan
| | - Nai-Yun Wu
- Institute of Tropical Plant Sciences and Microbiology, College of Biosciences and Biotechnology, National Cheng Kung University, Tainan 701, Taiwan
| | - Chi-Nga Chow
- Institute of Tropical Plant Sciences and Microbiology, College of Biosciences and Biotechnology, National Cheng Kung University, Tainan 701, Taiwan
| | - Han-Qin Zheng
- Yourgene Health, No. 376-5 Fuxing Rd, Shulin Dist., New Taipei City 238, Taiwan
| | - Chin-Yuan Chou
- Department of Life Sciences, National Cheng Kung University, Tainan 701, Taiwan
| | - Chien-Wen Yang
- Institute of Tropical Plant Sciences and Microbiology, College of Biosciences and Biotechnology, National Cheng Kung University, Tainan 701, Taiwan
| | - Ming-Jun Wang
- Department of Life Sciences, National Cheng Kung University, Tainan 701, Taiwan
| | - Song-Bin Chang
- Department of Life Sciences, National Cheng Kung University, Tainan 701, Taiwan
| | - Wen-Chi Chang
- Department of Life Sciences, National Cheng Kung University, Tainan 701, Taiwan
- Institute of Tropical Plant Sciences and Microbiology, College of Biosciences and Biotechnology, National Cheng Kung University, Tainan 701, Taiwan
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17
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Sheng N, Huang L, Gao L, Cao Y, Xie X, Wang Y. A Survey of Computational Methods and Databases for lncRNA-MiRNA Interaction Prediction. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2023; 20:2810-2826. [PMID: 37030713 DOI: 10.1109/tcbb.2023.3264254] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) are two prevalent non-coding RNAs in current research. They play critical regulatory roles in the life processes of animals and plants. Studies have shown that lncRNAs can interact with miRNAs to participate in post-transcriptional regulatory processes, mainly involved in regulating cancer development, metastatic progression, and drug resistance. Additionally, these interactions have significant effects on plant growth, development, and responses to biotic and abiotic stresses. Deciphering the potential relationships between lncRNAs and miRNAs may provide new insights into our understanding of the biological functions of lncRNAs and miRNAs, and the pathogenesis of complex diseases. In contrast, gathering information on lncRNA-miRNA interactions (LMIs) through biological experiments is expensive and time-consuming. With the accumulation of multi-omics data, computational models are extremely attractive in systematically exploring potential LMIs. To the best of our knowledge, this is the first comprehensive review of computational methods for identifying LMIs. Specifically, we first summarized the available public databases for predicting animal and plant LMIs. Second, we comprehensively reviewed the computational methods for predicting LMIs and classified them into two categories, including network-based methods and sequence-based methods. Third, we analyzed the standard evaluation methods and metrics used in LMI prediction. Finally, we pointed out some problems in the current study and discuss future research directions. Relevant databases and the latest advances in LMI prediction are summarized in a GitHub repository https://github.com/sheng-n/lncRNA-miRNA-interaction-methods, and we'll keep it updated.
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18
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Fan W, Zhang Y, Wang D, Wang C, Yang J. The impact of Yiwei decoction on the LncRNA and CircRNA regulatory networks in premature ovarian insufficiency. Heliyon 2023; 9:e20022. [PMID: 37809621 PMCID: PMC10559751 DOI: 10.1016/j.heliyon.2023.e20022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 08/19/2023] [Accepted: 09/08/2023] [Indexed: 10/10/2023] Open
Abstract
Premature ovarian insufficiency(POI)is a female reproductive aging illness. Yiwei decoction(YWD) is a traditional treatment for Yangming nourishment. YWD can treat premature ovarian insufficiency, but the exact molecular mechanism is unknown. As a result, the differential expression of Long noncoding RNAs (LncRNAs) and Circular RNAs(CircRNAs) in the ovary of POI rats after YWD treatment was investigated in this paper, and the CeRNA regulatory network was built. The model was created using cyclophosphamide. The model group + YWD was in Group A, the model control group was in Group B, and the regular control group was in Group C. In this study, 177 differential expression Long noncoding RNAs(DELncRNAs) and 190 differential expression Circular RNAs (DECircRNAs) were discovered between A and B (P<0.05,|LogFC|>1). Following the analysis, 27 DELncRNAs and 96 DECircRNAs (P-adjusted<0.05,|LogFC|>1) were discovered. At the same time, we built the CeRNA network using differentially expressed mRNAs and microRNAs (miRNAs) expression between groups A and B. The DELncRNAs were used to construct a lncRNA-miRNA-mRNA ceRNA network with 27 LncRNAs, 4 miRNAs, and 19 mRNAs. The DECircRNAs were utilized to establish a CircRNA-miRNA-mRNA ceRNA network that was made up of 15 CircRNAs, 4 miRNAs, and 20 mRNA. The highly correlated regulatory networks were the LncMSTRG.22691.3/miR-3102/ANGPT4 and Circ10_34698898_34699378/miR-33-5p/TTC22. Circ20_12035276_12036793、Circ20_30693935_30696337、Circ4_157723097_157723378 and Circ4_157923266_157923904 occurred concurrently in AvsB, BvsC, and AvsC. MiRDB predicted eight target miRNAs for these CircRNAs. The miRanda(score = 140,energy = -1) binding energy calculation revealed that seven miRNAs were well combined with three CircRNA base complementary pairs. This implies that 3 DECircRNAs could serve as spongy bodies for these miRNAs. Network pharmacological analysis showed that ten active components in YWD may regulate the expression of LncRNAs and CircRNAs, such as Stigmasterol, Uridine, Ophiopogonanone A, Gamma-Aminobutyric Acid, and others. In conclusion, this study combined transcriptomics and network pharmacological analysis to identify differentially expressed lncRNAs as well as CircRNAs in ovaries of YWD-treated POI rats, thereby constructing ceRNA networks implicated in POI. This would contribute to clarifying the pathways by which Chinese herbal compounds regulate gene expression in POI.
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Affiliation(s)
- Weisen Fan
- The First Clinical Medical College of Shandong University of Traditional Chinese Medicine, Jinan, 250013, China
| | - Yingjie Zhang
- School of Health, Shandong University of Traditional Chinese Medicine, Jinan, 250013, China
| | - Dandan Wang
- School of Health, Shandong University of Traditional Chinese Medicine, Jinan, 250013, China
| | - Chen Wang
- School of Traditional Chinese Medicine, Shandong University of Chinese Medicine, Jinan, 250013, China
| | - Jie Yang
- School of Physical Education and Health, Shandong Sport University, Jinan, 250013, China
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Li W, Zhao P, Sun J, Yu X, Zou L, Li S, Di R, Ruan M, Peng M. Biological function research of Fusarium oxysporum f. sp. cubense inducible banana long noncoding RNA Malnc2310 in Arabidopsis. PLANT MOLECULAR BIOLOGY 2023:10.1007/s11103-023-01360-6. [PMID: 37507516 DOI: 10.1007/s11103-023-01360-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 05/20/2023] [Indexed: 07/30/2023]
Abstract
Long noncoding RNAs (lncRNAs) participate in plant biological processes under biotic and abiotic stresses. However, little is known about the function and regulation mechanism of lncRNAs related to the pathogen at a molecular level. A banana lncRNA, Malnc2310, is a Fusarium oxysporum f. sp. cubense inducible lncRNA in roots. In this study, we demonstrate the nuclear localization of Malnc2310 by fluorescence in situ hybridization and it can bind to several proteins that are related to flavonoid pathway, pathogen response and programmed cell death. Overexpression of Malnc2310 increases susceptibility to Fusarium crude extract (Fu), salinity, and cold in transgenic Arabidopsis. In addition, Malnc2310 transgenic Arabidopsis accumulated more anthocyanins under Fusarium crude extract and cold treatments that are related to upregulation of these genes involved in anthocyanin biosynthesis. Based on our findings, we propose that Malnc2310 may participate in flavonoid metabolism in plants under stress. Furthermore, phenylalanine ammonia lyase (PAL) protein expression was enhanced in Malnc2310 overexpressed transgenic Arabidopsis, and Malnc2310 may participate in PAL regulation by binding to it. This study provides new insights into the role of Malnc2310 in mediating plant stress adaptation.
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Affiliation(s)
- Wenbin Li
- Key Laboratory of Biology and Genetic Resources of Tropical Crops, Ministry of Agriculture and Rural Affairs, P.R.China / Hainan Key Laboratory of Tropical Microbe Resources, Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
- Hainan Key Laboratory of Conservation and Utilization of Tropical Agricultural Biological Resources, Hainan Institute for Tropical Agricultural Resources, Haikou, China
| | - Pingjuan Zhao
- Key Laboratory of Biology and Genetic Resources of Tropical Crops, Ministry of Agriculture and Rural Affairs, P.R.China / Hainan Key Laboratory of Tropical Microbe Resources, Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
| | - Jianbo Sun
- Key Laboratory of Biology and Genetic Resources of Tropical Crops, Ministry of Agriculture and Rural Affairs, P.R.China / Hainan Key Laboratory of Tropical Microbe Resources, Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
| | - Xiaoling Yu
- Key Laboratory of Biology and Genetic Resources of Tropical Crops, Ministry of Agriculture and Rural Affairs, P.R.China / Hainan Key Laboratory of Tropical Microbe Resources, Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
| | - Liangping Zou
- Key Laboratory of Biology and Genetic Resources of Tropical Crops, Ministry of Agriculture and Rural Affairs, P.R.China / Hainan Key Laboratory of Tropical Microbe Resources, Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
| | - Shuxia Li
- Key Laboratory of Biology and Genetic Resources of Tropical Crops, Ministry of Agriculture and Rural Affairs, P.R.China / Hainan Key Laboratory of Tropical Microbe Resources, Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
- Hainan Key Laboratory of Conservation and Utilization of Tropical Agricultural Biological Resources, Hainan Institute for Tropical Agricultural Resources, Haikou, China
| | - Rong Di
- Department of Plant Biology, Rutgers, The State University of New Jersey, New Brunswick, USA
| | - Mengbin Ruan
- Key Laboratory of Biology and Genetic Resources of Tropical Crops, Ministry of Agriculture and Rural Affairs, P.R.China / Hainan Key Laboratory of Tropical Microbe Resources, Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Haikou, China.
- Hainan Key Laboratory of Conservation and Utilization of Tropical Agricultural Biological Resources, Hainan Institute for Tropical Agricultural Resources, Haikou, China.
- Sanya Research Institute, Chinese Academy of Tropical Agricultural Sciences, Sanya, China.
| | - Ming Peng
- Key Laboratory of Biology and Genetic Resources of Tropical Crops, Ministry of Agriculture and Rural Affairs, P.R.China / Hainan Key Laboratory of Tropical Microbe Resources, Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Haikou, China.
- Sanya Research Institute, Chinese Academy of Tropical Agricultural Sciences, Sanya, China.
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20
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Palos K, Yu L, Railey CE, Nelson Dittrich AC, Nelson ADL. Linking discoveries, mechanisms, and technologies to develop a clearer perspective on plant long noncoding RNAs. THE PLANT CELL 2023; 35:1762-1786. [PMID: 36738093 PMCID: PMC10226578 DOI: 10.1093/plcell/koad027] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 12/19/2022] [Accepted: 12/22/2022] [Indexed: 05/30/2023]
Abstract
Long noncoding RNAs (lncRNAs) are a large and diverse class of genes in eukaryotic genomes that contribute to a variety of regulatory processes. Functionally characterized lncRNAs play critical roles in plants, ranging from regulating flowering to controlling lateral root formation. However, findings from the past decade have revealed that thousands of lncRNAs are present in plant transcriptomes, and characterization has lagged far behind identification. In this setting, distinguishing function from noise is challenging. However, the plant community has been at the forefront of discovery in lncRNA biology, providing many functional and mechanistic insights that have increased our understanding of this gene class. In this review, we examine the key discoveries and insights made in plant lncRNA biology over the past two and a half decades. We describe how discoveries made in the pregenomics era have informed efforts to identify and functionally characterize lncRNAs in the subsequent decades. We provide an overview of the functional archetypes into which characterized plant lncRNAs fit and speculate on new avenues of research that may uncover yet more archetypes. Finally, this review discusses the challenges facing the field and some exciting new molecular and computational approaches that may help inform lncRNA comparative and functional analyses.
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Affiliation(s)
- Kyle Palos
- Boyce Thompson Institute, Cornell University, Ithaca, NY 14853, USA
| | - Li’ang Yu
- Boyce Thompson Institute, Cornell University, Ithaca, NY 14853, USA
| | - Caylyn E Railey
- Boyce Thompson Institute, Cornell University, Ithaca, NY 14853, USA
- Plant Biology Graduate Field, Cornell University, Ithaca, NY 14853, USA
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21
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Wu P, Nie Z, Huang Z, Zhang X. CircPCBL: Identification of Plant CircRNAs with a CNN-BiGRU-GLT Model. PLANTS (BASEL, SWITZERLAND) 2023; 12:1652. [PMID: 37111874 PMCID: PMC10143888 DOI: 10.3390/plants12081652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 04/10/2023] [Accepted: 04/13/2023] [Indexed: 06/19/2023]
Abstract
Circular RNAs (circRNAs), which are produced post-splicing of pre-mRNAs, are strongly linked to the emergence of several tumor types. The initial stage in conducting follow-up studies involves identifying circRNAs. Currently, animals are the primary target of most established circRNA recognition technologies. However, the sequence features of plant circRNAs differ from those of animal circRNAs, making it impossible to detect plant circRNAs. For example, there are non-GT/AG splicing signals at circRNA junction sites and few reverse complementary sequences and repetitive elements in the flanking intron sequences of plant circRNAs. In addition, there have been few studies on circRNAs in plants, and thus it is urgent to create a plant-specific method for identifying circRNAs. In this study, we propose CircPCBL, a deep-learning approach that only uses raw sequences to distinguish between circRNAs found in plants and other lncRNAs. CircPCBL comprises two separate detectors: a CNN-BiGRU detector and a GLT detector. The CNN-BiGRU detector takes in the one-hot encoding of the RNA sequence as the input, while the GLT detector uses k-mer (k = 1 - 4) features. The output matrices of the two submodels are then concatenated and ultimately pass through a fully connected layer to produce the final output. To verify the generalization performance of the model, we evaluated CircPCBL using several datasets, and the results revealed that it had an F1 of 85.40% on the validation dataset composed of six different plants species and 85.88%, 75.87%, and 86.83% on the three cross-species independent test sets composed of Cucumis sativus, Populus trichocarpa, and Gossypium raimondii, respectively. With an accuracy of 90.9% and 90%, respectively, CircPCBL successfully predicted ten of the eleven circRNAs of experimentally reported Poncirus trifoliata and nine of the ten lncRNAs of rice on the real set. CircPCBL could potentially contribute to the identification of circRNAs in plants. In addition, it is remarkable that CircPCBL also achieved an average accuracy of 94.08% on the human datasets, which is also an excellent result, implying its potential application in animal datasets. Ultimately, CircPCBL is available as a web server, from which the data and source code can also be downloaded free of charge.
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Affiliation(s)
- Pengpeng Wu
- Anhui Province Key Laboratory of Smart Agricultural Technology and Equipment, Anhui Agricultural University, Hefei 230036, China
- School of Life Science, Anhui Agricultural University, Hefei 230036, China
| | - Zhenjun Nie
- Anhui Province Key Laboratory of Smart Agricultural Technology and Equipment, Anhui Agricultural University, Hefei 230036, China
- School of Information and Computer Science, Anhui Agricultural University, Hefei 230036, China
| | - Zhiqiang Huang
- Anhui Province Key Laboratory of Smart Agricultural Technology and Equipment, Anhui Agricultural University, Hefei 230036, China
- School of Information and Computer Science, Anhui Agricultural University, Hefei 230036, China
| | - Xiaodan Zhang
- Anhui Province Key Laboratory of Smart Agricultural Technology and Equipment, Anhui Agricultural University, Hefei 230036, China
- School of Information and Computer Science, Anhui Agricultural University, Hefei 230036, China
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22
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Reynoso MA, Blanco FA, Zanetti ME. Nuclear and cytoplasmic lncRNAs in root tips of the model legume Medicago truncatula under control and submergence. IUBMB Life 2023. [PMID: 36852968 DOI: 10.1002/iub.2712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 01/21/2023] [Indexed: 03/01/2023]
Abstract
In this study, we aimed to identify long noncoding RNAs (lncRNAs) in root tips of the model legume Medicago truncatula using previously generated nuclear, total polyA, ribosome-associated polyA, and Riboseq RNA datasets, which might shed light on their localization and potential regulatory roles. RNA-seq data were mapped to the version 5 of the M. truncatula A17 genome and analyzed to identify genome annotated lncRNAs and putative new root tip (NRT) lncRNAs. lncRNAs were classified according to their genomic location relative to chromatin accessible regions, protein-coding genes and transposable elements (TE), finding differences between annotated lncRNAs and NRT lncRNAs, both in their genomic position as well as in the type of TEs in their vicinity. We investigated their response to submergence and found a set of regulated lncRNAs that were preferentially upregulated in the nucleus, some of which were located nearby genes of the conserved submergence upregulated gene families, and chromatin accessible regions suggesting a potential regulatory role. Finally, the accumulation of lncRNAs under submergence was validated by reverse transcription quantitative polymerase chain reaction on nuclear RNA, providing additional evidence of their localization, which could ultimately be required for their function.
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Affiliation(s)
- Mauricio A Reynoso
- Instituto de Biotecnología y Biología Molecular, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, Centro Científico y Tecnológico-La Plata, Consejo Nacional de Investigaciones Científicas y Técnicas, La Plata, Argentina.,Department of Botany and Plant Sciences, Center for Plant Cell Biology, University of California, Riverside, California, USA
| | - Flavio Antonio Blanco
- Instituto de Biotecnología y Biología Molecular, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, Centro Científico y Tecnológico-La Plata, Consejo Nacional de Investigaciones Científicas y Técnicas, La Plata, Argentina
| | - María Eugenia Zanetti
- Instituto de Biotecnología y Biología Molecular, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, Centro Científico y Tecnológico-La Plata, Consejo Nacional de Investigaciones Científicas y Técnicas, La Plata, Argentina
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23
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Long Non-Coding RNAs of Plants in Response to Abiotic Stresses and Their Regulating Roles in Promoting Environmental Adaption. Cells 2023; 12:cells12050729. [PMID: 36899864 PMCID: PMC10001313 DOI: 10.3390/cells12050729] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 02/10/2023] [Accepted: 02/21/2023] [Indexed: 03/03/2023] Open
Abstract
Abiotic stresses triggered by climate change and human activity cause substantial agricultural and environmental problems which hamper plant growth. Plants have evolved sophisticated mechanisms in response to abiotic stresses, such as stress perception, epigenetic modification, and regulation of transcription and translation. Over the past decade, a large body of literature has revealed the various regulatory roles of long non-coding RNAs (lncRNAs) in the plant response to abiotic stresses and their irreplaceable functions in environmental adaptation. LncRNAs are recognized as a class of ncRNAs that are longer than 200 nucleotides, influencing a variety of biological processes. In this review, we mainly focused on the recent progress of plant lncRNAs, outlining their features, evolution, and functions of plant lncRNAs in response to drought, low or high temperature, salt, and heavy metal stress. The approaches to characterize the function of lncRNAs and the mechanisms of how they regulate plant responses to abiotic stresses were further reviewed. Moreover, we discuss the accumulating discoveries regarding the biological functions of lncRNAs on plant stress memory as well. The present review provides updated information and directions for us to characterize the potential functions of lncRNAs in abiotic stresses in the future.
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24
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Kimble M, Allers S, Campbell K, Chen C, Jackson LM, King BL, Silverbrand S, York G, Beard K. medna-metadata: an open-source data management system for tracking environmental DNA samples and metadata. Bioinformatics 2022; 38:4589-4597. [PMID: 35960154 PMCID: PMC9524998 DOI: 10.1093/bioinformatics/btac556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 07/23/2022] [Accepted: 08/09/2022] [Indexed: 12/24/2022] Open
Abstract
MOTIVATION Environmental DNA (eDNA), as a rapidly expanding research field, stands to benefit from shared resources including sampling protocols, study designs, discovered sequences, and taxonomic assignments to sequences. High-quality community shareable eDNA resources rely heavily on comprehensive metadata documentation that captures the complex workflows covering field sampling, molecular biology lab work, and bioinformatic analyses. There are limited sources that provide documentation of database development on comprehensive metadata for eDNA and these workflows and no open-source software. RESULTS We present medna-metadata, an open-source, modular system that aligns with Findable, Accessible, Interoperable, and Reusable guiding principles that support scholarly data reuse and the database and application development of a standardized metadata collection structure that encapsulates critical aspects of field data collection, wet lab processing, and bioinformatic analysis. Medna-metadata is showcased with metabarcoding data from the Gulf of Maine (Polinski et al., 2019). AVAILABILITY AND IMPLEMENTATION The source code of the medna-metadata web application is hosted on GitHub (https://github.com/Maine-eDNA/medna-metadata). Medna-metadata is a docker-compose installable package. Documentation can be found at https://medna-metadata.readthedocs.io/en/latest/?badge=latest. The application is implemented in Python, PostgreSQL and PostGIS, RabbitMQ, and NGINX, with all major browsers supported. A demo can be found at https://demo.metadata.maine-edna.org/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- M Kimble
- School of Computing and Information Science, University of Maine, Orono, ME 04469, USA
| | - S Allers
- Department of Molecular and Biomedical Sciences, University of Maine, Orono, ME 04469, USA
| | - K Campbell
- School of Computing and Information Science, University of Maine, Orono, ME 04469, USA
| | - C Chen
- School of Computing and Information Science, University of Maine, Orono, ME 04469, USA
| | - L M Jackson
- Advanced Research Computing, Security and Information Management, University of Maine, Orono, ME 04469, USA
- Maine EPSCoR, University of Maine, Orono, ME 04469, USA
| | - B L King
- Department of Molecular and Biomedical Sciences, University of Maine, Orono, ME 04469, USA
| | - S Silverbrand
- School of Marine Sciences, University of Maine, Orono, ME 04469, USA
| | - G York
- Environmental DNA Laboratory, Coordinated Operating Research Entities, University of Maine, Orono, ME 04469, USA
| | - K Beard
- School of Computing and Information Science, University of Maine, Orono, ME 04469, USA
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25
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Corona-Gomez JA, Coss-Navarrete EL, Garcia-Lopez IJ, Klapproth C, Pérez-Patiño JA, Fernandez-Valverde SL. Transcriptome-guided annotation and functional classification of long non-coding RNAs in Arabidopsis thaliana. Sci Rep 2022; 12:14063. [PMID: 35982083 PMCID: PMC9388643 DOI: 10.1038/s41598-022-18254-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 08/08/2022] [Indexed: 11/16/2022] Open
Abstract
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.
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Affiliation(s)
| | | | | | - Christopher Klapproth
- Bioinformatics Group, Department of Computer Science and Interdisciplinary Center of Bioinformatics, Leipzig University, Härtelstraße 16-18, 04107, Leipzig, Germany.,ScaDS.AI Leipzig (Center for Scalable Data Analytics and Artificial Intelligence), Humboldstrasse 25, 04105, Leipzig, Germany
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26
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Li W, Chen Y, Wang Y, Zhao J, Wang Y. Gypsy retrotransposon-derived maize lncRNA GARR2 modulates gibberellin response. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2022; 110:1433-1446. [PMID: 35368126 DOI: 10.1111/tpj.15748] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 03/15/2022] [Accepted: 03/22/2022] [Indexed: 05/09/2023]
Abstract
Long non-coding RNAs (lncRNAs) mediate diverse biological events mainly through the modulation of transcriptional hierarchy. The phytohormone gibberellin (GA) is essential for various aspects of plant growth and development. However, the roles of lncRNAs in the regulation of the GA response remain largely unknown. Through sequencing multiple strand-specific and ribosomal-depleted RNA libraries, we delineated the landscape of lncRNAs in maize (Zea mays). Out of identified lncRNAs, 445 GIBBERELLIN-RESPONSIVE lncRNAs (GARRs) were differentially expressed upon GA application. By the intersection of GARRs from normal-height and dwarf plants from an advanced backcross population, four shared GARRs (GARR1 to GARR4) were identified. Out of these four shared GARRs, GARR2 was derived from a Gypsy LTR retrotransposon. GA-responsive element P-boxes were identified upstream of GARR2. GARR2-edited lines exhibited a GA-induced phenotype. Editing of GARR2 resulted in changes in the transcriptional abundance of GA pathway components and endogenous GA contents. Besides GA, GARR2 affected the primary auxin response. An RNA pull-down assay revealed the HECT ubiquitin-protein ligase family member ZmUPL1 as a potential interaction target of GARR2. GARR2 influenced the abundance of ZmUPL1 in the GA response. Our study uncovers lncRNA players involved in the modulation of the GA response and guides the development of plant height ideotype driven by knowledge of the phytohormone GA.
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Affiliation(s)
- Wei Li
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, 225009, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, 225009, China
| | - Yudong Chen
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, 225009, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, 225009, China
| | - Yali Wang
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, 225009, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, 225009, China
| | - Jia Zhao
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, 225009, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, 225009, China
| | - Yijun Wang
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, 225009, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, 225009, China
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27
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Almatroudi A. Non-Coding RNAs in Tuberculosis Epidemiology: Platforms and Approaches for Investigating the Genome's Dark Matter. Int J Mol Sci 2022; 23:4430. [PMID: 35457250 PMCID: PMC9024992 DOI: 10.3390/ijms23084430] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 04/05/2022] [Accepted: 04/14/2022] [Indexed: 02/07/2023] Open
Abstract
A growing amount of information about the different types, functions, and roles played by non-coding RNAs (ncRNAs) is becoming available, as more and more research is done. ncRNAs have been identified as potential therapeutic targets in the treatment of tuberculosis (TB), because they may be essential regulators of the gene network. ncRNA profiling and sequencing has recently revealed significant dysregulation in tuberculosis, primarily due to aberrant processes of ncRNA synthesis, including amplification, deletion, improper epigenetic regulation, or abnormal transcription. Despite the fact that ncRNAs may have a role in TB characteristics, the detailed mechanisms behind these occurrences are still unknown. The dark matter of the genome can only be explored through the development of cutting-edge bioinformatics and molecular technologies. In this review, ncRNAs' synthesis and functions are discussed in detail, with an emphasis on the potential role of ncRNAs in tuberculosis. We also focus on current platforms, experimental strategies, and computational analyses to explore ncRNAs in TB. Finally, a viewpoint is presented on the key challenges and novel techniques for the future and for a wide-ranging therapeutic application of ncRNAs.
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Affiliation(s)
- Ahmad Almatroudi
- Department of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraydah 51452, Saudi Arabia
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28
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Chao H, Hu Y, Zhao L, Xin S, Ni Q, Zhang P, Chen M. Biogenesis, Functions, Interactions, and Resources of Non-Coding RNAs in Plants. Int J Mol Sci 2022; 23:ijms23073695. [PMID: 35409060 PMCID: PMC8998614 DOI: 10.3390/ijms23073695] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 03/19/2022] [Accepted: 03/23/2022] [Indexed: 12/14/2022] Open
Abstract
Plant transcriptomes encompass a large number of functional non-coding RNAs (ncRNAs), only some of which have protein-coding capacity. Since their initial discovery, ncRNAs have been classified into two broad categories based on their biogenesis and mechanisms of action, housekeeping ncRNAs and regulatory ncRNAs. With advances in RNA sequencing technology and computational methods, bioinformatics resources continue to emerge and update rapidly, including workflow for in silico ncRNA analysis, up-to-date platforms, databases, and tools dedicated to ncRNA identification and functional annotation. In this review, we aim to describe the biogenesis, biological functions, and interactions with DNA, RNA, protein, and microorganism of five major regulatory ncRNAs (miRNA, siRNA, tsRNA, circRNA, lncRNA) in plants. Then, we systematically summarize tools for analysis and prediction of plant ncRNAs, as well as databases. Furthermore, we discuss the silico analysis process of these ncRNAs and present a protocol for step-by-step computational analysis of ncRNAs. In general, this review will help researchers better understand the world of ncRNAs at multiple levels.
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Affiliation(s)
| | | | | | | | | | - Peijing Zhang
- Correspondence: (P.Z.); (M.C.); Tel./Fax: +86-(0)571-88206612 (M.C.)
| | - Ming Chen
- Correspondence: (P.Z.); (M.C.); Tel./Fax: +86-(0)571-88206612 (M.C.)
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29
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Drought tolerance improvement in Solanum lycopersicum: an insight into "OMICS" approaches and genome editing. 3 Biotech 2022; 12:63. [PMID: 35186660 PMCID: PMC8825918 DOI: 10.1007/s13205-022-03132-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 01/24/2022] [Indexed: 12/16/2022] Open
Abstract
Solanum lycopersicum (tomato) is an internationally acclaimed vegetable crop that is grown worldwide. However, drought stress is one of the most critical challenges for tomato production, and it is a crucial task for agricultural biotechnology to produce drought-resistant cultivars. Although breeders have done a lot of work on the tomato to boost quality and quantity of production and enhance resistance to biotic and abiotic stresses, conventional tomato breeding approaches have been limited to improving drought tolerance because of the intricacy of drought traits. Many efforts have been made to better understand the mechanisms involved in adaptation and tolerance to drought stress in tomatoes throughout the years. "Omics" techniques, such as genomics, transcriptomics, proteomics, and metabolomics in combination with modern sequencing technologies, have tremendously aided the discovery of drought-responsive genes. In addition, the availability of biotechnological tools, such as plant transformation and the recently developed genome editing system for tomatoes, has opened up wider opportunities for validating the function of drought-responsive genes and the generation of drought-tolerant varieties. This review highlighted the recent progresses for tomatoes improvement against drought stress through "omics" and "multi-omics" technologies including genetic engineering. We have also discussed the roles of non-coding RNAs and genome editing techniques for drought stress tolerance improvement in tomatoes.
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30
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Rigden DJ, Fernández XM. The 2022 Nucleic Acids Research database issue and the online molecular biology database collection. Nucleic Acids Res 2022; 50:D1-D10. [PMID: 34986604 PMCID: PMC8728296 DOI: 10.1093/nar/gkab1195] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
The 2022 Nucleic Acids Research Database Issue contains 185 papers, including 87 papers reporting on new databases and 85 updates from resources previously published in the Issue. Thirteen additional manuscripts provide updates on databases most recently published elsewhere. Seven new databases focus specifically on COVID-19 and SARS-CoV-2, including SCoV2-MD, the first of the Issue's Breakthrough Articles. Major nucleic acid databases reporting updates include MODOMICS, JASPAR and miRTarBase. The AlphaFold Protein Structure Database, described in the second Breakthrough Article, is the stand-out in the protein section, where the Human Proteoform Atlas and GproteinDb are other notable new arrivals. Updates from DisProt, FuzDB and ELM comprehensively cover disordered proteins. Under the metabolism and signalling section Reactome, ConsensusPathDB, HMDB and CAZy are major returning resources. In microbial and viral genomes taxonomy and systematics are well covered by LPSN, TYGS and GTDB. Genomics resources include Ensembl, Ensembl Genomes and UCSC Genome Browser. Major returning pharmacology resource names include the IUPHAR/BPS guide and the Therapeutic Target Database. New plant databases include PlantGSAD for gene lists and qPTMplants for post-translational modifications. The entire Database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). Our latest update to the NAR online Molecular Biology Database Collection brings the total number of entries to 1645. Following last year's major cleanup, we have updated 317 entries, listing 89 new resources and trimming 80 discontinued URLs. The current release is available at http://www.oxfordjournals.org/nar/database/c/.
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Affiliation(s)
- Daniel J Rigden
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Crown Street, Liverpool L69 7ZB, UK
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