PEO: Plant Expression Omnibus - a comparative transcriptomic database for 103 Archaeplastida.
RNA-sequencing
coexpression
comparative
database
gene families
pathway
Journal
The Plant journal : for cell and molecular biology
ISSN: 1365-313X
Titre abrégé: Plant J
Pays: England
ID NLM: 9207397
Informations de publication
Date de publication:
04 Dec 2023
04 Dec 2023
Historique:
received:
22
06
2023
accepted:
16
11
2023
medline:
5
12
2023
pubmed:
5
12
2023
entrez:
5
12
2023
Statut:
aheadofprint
Résumé
The Plant Expression Omnibus (PEO) is a web application that provides biologists with access to gene expression insights across over 100 plant species, ~60 000 manually annotated RNA-seq samples, and more than 4 million genes. The tool allows users to explore the expression patterns of genes across different organs, identify organ-specific genes, and discover top co-expressed genes for any gene of interest. PEO also provides functional annotations for each gene, allowing for the identification of genetic modules and pathways. PEO is designed to facilitate comparative kingdom-wide gene expression analysis and provide a valuable resource for plant biology research. We provide two case studies to demonstrate the utility of PEO in identifying candidate genes in pollen coat biosynthesis in Arabidopsis and investigating the biosynthetic pathway components of capsaicin in Capsicum annuum. The database is freely available at https://expression.plant.tools/.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Singaporean Food Agency
ID : SFS_RND_SUFP_001_05
Organisme : Ministry of Education Tier 3
ID : MOET32022-0002
Informations de copyright
© 2023 Society for Experimental Biology and John Wiley & Sons Ltd.
Références
Ahlers, F., Lambert, J. & Wiermann, R. (1999) Structural elements of sporopollenin from the pollen of Torreya californica Torr. (Gymnospermae): using the 1H-NMR technique. Zeitschrift für Naturforschung C, 54, 492-495. Available from: https://doi.org/10.1515/znc-1999-7-806
Bray, N.L., Pimentel, H., Melsted, P. & Pachter, L. (2016) Near-optimal probabilistic RNA-seq quantification. Nature Biotechnology, 34, 525-527. Available from: https://doi.org/10.1038/nbt.3519
Buchfink, B., Xie, C. & Huson, D.H. (2015) Fast and sensitive protein alignment using DIAMOND. Nature Methods, 12, 59-60. Available from: https://doi.org/10.1038/nmeth.3176
Cravens, A., Payne, J. & Smolke, C.D. (2019) Synthetic biology strategies for microbial biosynthesis of plant natural products. Nature Communications, 10, 2142.
Delli-Ponti, R., Shivhare, D. & Mutwil, M. (2021) Using gene expression to study specialized metabolism-a practical guide. Frontiers in Plant Science, 11, 2074. Available from: https://doi.org/10.3389/fpls.2020.625035
Desborough, M.J. & Keeling, D.M. (2017) The aspirin story - from willow to wonder drug. British Journal of Haematology, 177, 674-683.
Goh, W. & Mutwil, M. (2021) LSTrAP-Kingdom: an automated pipeline to generate annotated gene expression atlases for kingdoms of life. Bioinformatics, 37, 3053-3055. Available from: https://doi.org/10.1093/bioinformatics/btab168
Hansen, B.O., Meyer, E.H., Ferrari, C., Vaid, N., Movahedi, S., Vandepoele, K. et al. (2018) Ensemble gene function prediction database reveals genes important for complex I formation in Arabidopsis thaliana. The New Phytologist, 217, 1521-1534. Available from: https://doi.org/10.1111/nph.14921
Julca, I., Ferrari, C., Flores-Tornero, M., Proost, S., Lindner, A.-C., Hackenberg, D. et al. (2021) Comparative transcriptomic analysis reveals conserved programmes underpinning organogenesis and reproduction in land plants. Nature Plants, 7, 1143-1159. Available from: https://doi.org/10.1038/s41477-021-00958-2
Klie, S. & Nikoloski, Z. (2012) The choice between MapMan and gene ontology for automated gene function prediction in plant science. Frontiers in Genetics, 3, 1-14. Available from: https://doi.org/10.3389/fgene.2012.00115
Krishna, S., Bustamante, L., Haynes, R.K. & Staines, H.M. (2008) Artemisinins: their growing importance in medicine. Trends in Pharmacological Sciences, 29, 520-527.
Lim, P.K., Zheng, X., Goh, J.C. & Mutwil, M. (2022) Exploiting plant transcriptomic databases: resources, tools, and approaches. Plant Communications, 3, 100323.
Liu, J., Zhang, Y., Zheng, Y., Zhu, Y., Shi, Y., Guan, Z. et al. (2023) PlantExp: a platform for exploration of gene expression and alternative splicing based on public plant RNA-seq samples. Nucleic Acids Research, 51, D1483-D1491.
Ma, L., Sun, N., Liu, X., Jiao, Y., Zhao, H. & Deng, X.W. (2005) Organ-specific expression of Arabidopsis genome during development. Plant Physiology, 138, 80-91.
Mazourek, M., Pujar, A., Borovsky, Y., Paran, I., Mueller, L. & Jahn, M.M. (2009) A dynamic interface for capsaicinoid systems biology. Plant Physiology, 150, 1806-1821. Available from: https://doi.org/10.1104/pp.109.136549
Mistry, J., Chuguransky, S., Williams, L., Qureshi, M., Salazar, G.A., Sonnhammer, E.L.L. et al. (2021) Pfam: the protein families database in 2021. Nucleic Acids Research, 49, D412-D419. Available from: https://doi.org/10.1093/nar/gkaa913
Niazian, M. (2019) Application of genetics and biotechnology for improving medicinal plants. Planta, 249, 953-973.
Nowicka, B., Ciura, J., Szymańska, R. & Kruk, J. (2018) Improving photosynthesis, plant productivity and abiotic stress tolerance - current trends and future perspectives. Journal of Plant Physiology, 231, 415-433.
Paddon, C.J., Westfall, P.J., Pitera, D.J., Benjamin, K., Fisher, K., McPhee, D. et al. (2013) High-level semi-synthetic production of the potent antimalarial artemisinin. Nature, 496, 528-532.
Pearce, S., Ferguson, A., King, J. & Wilson, Z.A. (2015) FlowerNet: a gene expression correlation network for anther and pollen development. Plant Physiology, 167, 1717-1730. Available from: https://doi.org/10.1104/pp.114.253807
Persson, S., Wei, H., Milne, J., Page, G.P. & Somerville, C.R. (2005) Identification of genes required for cellulose synthesis by regression analysis of public microarray data sets. Proc. Natl. Acad. Sci. U S A, 102, 8633-8638.
Proost, S. & Mutwil, M. (2018) CoNekT: an open-source framework for comparative genomic and transcriptomic network analyses. Nucleic Acids Research, 46, W133-W140. Available from: https://doi.org/10.1093/nar/gky336
Radivojac, P., Clark, W.T., Oron, T.R., Schnoes, A.M., Wittkop, T., Sokolov, A. et al. (2013) A large-scale evaluation of computational protein function prediction. Nature Methods, 10, 221-227. Available from: https://doi.org/10.1038/nmeth.2340
Rao, X. & Dixon, R.A. (2019) Co-expression networks for plant biology: why and how. Acta Biochimica et Biophysica Sinica, 51, 981-988. Available from: https://doi.org/10.1093/abbs/gmz080
Rhee, S.Y. & Mutwil, M. (2014) Towards revealing the functions of all genes in plants. Trends in Plant Science, 19, 212-221. Available from: https://doi.org/10.1016/j.tplants.2013.10.006
Robinson, A.J., Tamiru, M., Salby, R., Bolitho, C., Williams, A., Huggard, S. et al. (2018) AgriSeqDB: an online RNA-Seq database for functional studies of agriculturally relevant plant species. BMC Plant Biology, 18, 1-8.
Ryngajllo, M., Childs, L., Lohse, M., Giorgi, F.M., Lude, A., Selbig, J. et al. (2011) SLocX: predicting subcellular localization of Arabidopsis proteins leveraging gene expression data. Frontiers in Plant Science, 2, 43.
Sabzehzari, M., Zeinali, M. & Naghavi, M.R. (2020) Alternative sources and metabolic engineering of taxol: advances and future perspectives. Biotechnology Advances, 43, 107569.
Schwacke, R., Ponce-Soto, G.Y., Krause, K., Bolger, A.M., Arsova, B., Hallab, A. et al. (2019) MapMan4: a refined protein classification and annotation framework applicable to multi-omics data analysis. Molecular Plant, 12, 879-892. Available from: https://doi.org/10.1016/j.molp.2019.01.003
Scott, R.J., Spielman, M. & Dickinson, H.G. (2004) Stamen structure and function. Plant Cell, 16, S46-S60. Available from: https://doi.org/10.1105/tpc.017012
Stewart, C., Jr., Kang, B.-C., Liu, K., Mazourek, M., Moore, S.L., Yoo, E.Y. et al. (2005) The Pun1 gene for pungency in pepper encodes a putative acyltransferase. The Plant Journal, 42, 675-688. Available from: https://doi.org/10.1111/j.1365-313X.2005.02410.x
Suzuki, T., Fujiwake, H. & Iwai, K. (1980) Intracellular localization of capsaicin and its analogues, capsaicinoid, in capsicum fruit 1. Microscopic investigation of the structure of the placenta of Capsicum annuum var. annuum cv. Karayatsubusa. Plant & Cell Physiology, 21, 839-853. Available from: https://doi.org/10.1093/oxfordjournals.pcp.a076058
Tan, Q.W., Goh, W. & Mutwil, M. (2020) LSTrAP-Cloud: a user-friendly cloud computing pipeline to infer Coexpression networks. Genes, 11, 428. Available from: https://doi.org/10.3390/genes11040428
Walls, R.L., Cooper, L., Elser, J., Gandolfo, M.A., Mungall, C.J., Smith, B. et al. (2019) The plant ontology facilitates comparisons of plant development stages across species. Frontiers in Plant Science, 10, 631. Available from: https://doi.org/10.3389/fpls.2019.00631
Wetterstrand, K.A. (2013) DNA sequencing costs: data from the NHGRI genome sequencing program (GSP). Bethesda, MD: National Human Genome Research Institute.
Xu, J., Ding, Z., Vizcay-Barrena, G., Shi, J., Liang, W., Yuan, Z. et al. (2014) ABORTED MICROSPORES acts as a master regulator of pollen wall formation in Arabidopsis. Plant Cell, 26, 1544-1556. Available from: https://doi.org/10.1105/tpc.114.122986
Yu, Y., Zhang, H., Long, Y., Shu, Y. & Zhai, J. (2022) Plant public RNA-seq database: a comprehensive online database for expression analysis of ~45000 plant public RNA-seq libraries. Plant Biotechnology Journal, 20, 806-808.
Zhang, Z.-X., Zhao, S.-N., Liu, G.-F., Huang, Z.-M., Cao, Z.-M., Cheng, S.-H. et al. (2016) Discovery of putative capsaicin biosynthetic genes by RNA-Seq and digital gene expression analysis of pepper. Scientific Reports, 6, 34121. Available from: https://doi.org/10.1038/srep34121