Einzeltreffer — DigiBib

Poa pratensis L. (Poaceae) is a valuable grass across the north hemisphere, inhabiting diverse environments with wide altitudinal span, where ubiquitous various kinds of stresses. Phytohormones would be helpful to improve tolerance to abiotic and biotic stresses, but the responses of transcriptome regulation of P. pratensis to exogenous phytohormones application remain unclear. In this study, we explored the alteration of plant physiological responses by the application of phytohormones. Aiming to achieve this knowledge, we got full-length transcriptome data 42.76 Gb, of which 74.9% of transcripts were completed. Then used 27 samples representing four treatments conducted at two time points (1 h and 6 h after application) to generate RNA-seq data. 371 and 907 common DEGs were identified in response to four phytohormones application, respectively, these DEGs were involved in "plant hormone signal transduction", "carbon metabolism" and "plant-pathogen interaction". Finally, P. pratensis basic research can gain valuable information regarding the responses to exogenous application of phytohormones in physiological indicators and transcriptional regulations in order to facilitate the development of new cultivars.

Titel:	Transcriptomic profiling of Poa pratensis L. under treatment of various phytohormones.
Autor/in / Beteiligte Person:	Meng, C ; Peng, X ; Zhang, Y ; Pedro, GC ; Li, Y ; Duan, Y ; Sun, X
Link:	View record at Springer (Volltext)
Zeitschrift:	Scientific data, Jg. 11 (2024-03-15), Heft 1, S. 297
Veröffentlichung:	London : Nature Publishing Group, 2014-, 2024
Medientyp:	academicJournal
ISSN:	2052-4463 (electronic)
DOI:	10.1038/s41597-024-03119-0
Schlagwort:	Humans Plant Growth Regulators pharmacology Undertreatment Gene Expression Profiling Transcriptome Gene Expression Regulation, Plant Stress, Physiological Poa genetics
Sonstiges:	Nachgewiesen in: MEDLINE Sprachen: English Publication Type: Journal Article Language: English [Sci Data] 2024 Mar 15; Vol. 11 (1), pp. 297. <i>Date of Electronic Publication: </i>2024 Mar 15. MeSH Terms: Poa* / genetics ; Humans ; Plant Growth Regulators / pharmacology ; Undertreatment ; Gene Expression Profiling ; Transcriptome ; Gene Expression Regulation, Plant ; Stress, Physiological References: Mazzucato, A., Falcinelli, M. & Veronesi, F. Evolution and adaptedness in a facultatively apomictic grass, Poa pratensis L. Euphytica 92, 13–19 (1996). (PMID: 10.1007/BF00022823) ; Kusano, M., Tohyama, K., Bae, C. H., Riu, K. Z. & Lee, H. Y. Plant regeneration and transformation of Kentucky Bluegrass(Poa pratensis L.) via the plant tissue culture. Journal of Plant Biotechnology 30, 882–887 (2003). ; Alshammary, S. F., Qian, Y. L. & Wallner, S. J. Growth response of four turfgrass species to salinity. Agricultural Water Management 66, 97–111 (2004). (PMID: 10.1016/j.agwat.2003.11.002) ; Speckmann, G. J. & Van Dijk, G. E. Chromosome number and plant morphology in some ecotypes of Poa pratensis L. Euphytica 21, 171–180 (1972). (PMID: 10.1007/BF00036757) ; Jia, Y. L. et al. Combined Jasmonic acid and ethylene treatment induces resistance effect in faba bean plants against Frankliniella occidentalis (Pergande) (Thysanoptera: Thripidae). Insects 13, 1071–1090 (2022). (PMID: 10.3390/insects13111073) ; Khan, N., Bano, A., Ali, S. & Babar, M. Crosstalk amongst phytohormones from planta and PGPR under biotic and abiotic stresses. Plant Growth Regulation 90, 189–203 (2020). (PMID: 10.1007/s10725-020-00571-x) ; Cortleven, A. et al. Cytokinin action in response to abiotic and biotic stresses in plants. Plant, Cell & Environment 42, 998–1018 (2019). (PMID: 10.1111/pce.13494) ; Cheng, C., Zhong, Y., Cai, Z., Su, R. & Li, C. Genome-wide identification and gene expression analysis of ABA receptor family genes in Brassica juncea var. tumida. Genes 10, 470–486 (2019). (PMID: 31226871662810010.3390/genes10060470) ; Choudhury, S. et al. A computational study of the role of secondary metabolites for mitigation of acid soil stress in cereals using dehydroascorbate and mono-dehydroascorbate reductases. Antioxidants (Basel) 11, 458–475 (2022). (PMID: 3532610810.3390/antiox11030458) ; Li, X., Bai, T., Li, Y., Ruan, X. & Li, H. Proteomic analysis of Fusarium oxysporum f. sp. cubense tropical race 4-inoculated response to Fusarium wilts in the banana root cells. Proteome science 11, 41–56 (2013). (PMID: 24070062385041010.1186/1477-5956-11-41) ; Kapoor, B., Kumar, P., Sharma, R. & Kumar, A. Regulatory interactions in phytohormone stress signaling implying plants resistance and resilience mechanisms. Journal of Plant Biochemistry and Biotechnology 30, 813–828 (2021). (PMID: 10.1007/s13562-021-00739-0) ; Hu, F., Zhang, Y. & Guo, J. Effects of drought stress on photosynthetic physiological characteristics, leaf microstructure, and related gene expression of yellow horn. Plant Signaling & Behavior 18, 102842–102853 (2023). (PMID: 10.1080/15592324.2023.2215025) ; Schönbeck, L. et al. Plant physiological indicators for optimizing conservation outcomes. Conservation Physiology 11, 73–85 (2023). (PMID: 10.1093/conphys/coad073) ; Soniya, E. V., Srinivasan, A., Menon, A. & Kattupalli, D. Chapter 10 - Transcriptomics in response of biotic stress in plants. Transcriptome Profiling 2, 285–303 (2023). (PMID: 10.1016/B978-0-323-91810-7.00018-2) ; Cheng, J. et al. Transcriptome analysis of native Kentucky Bluegrass (Poa pratensis L.) in response to osmotic stress. Plants 12, 39–71 (2023). (PMID: 10.3390/plants12233971) ; Bushman, B. S., Amundsen, K. L., Warnke, S. E., Robins, J. G. & Johnson, P. G. Transcriptome profiling of Kentucky bluegrass (Poa pratensis L.) accessions in response to salt stress. BMC Genomics 17, 17–48 (2016). (PMID: 10.1186/s12864-016-2379-x) ; Yujuan, Z., Wenke, D., Chunxu, Z. & Huiling, M. Comparative transcriptome analysis of resistant and susceptible Kentucky bluegrass varieties in response to powdery mildew infection. BMC Plant Biology 22, 509–547 (2022). (PMID: 10.1186/s12870-022-03883-4) ; Qiong, L. et al. Transcriptome sequencing of two Kentucky Bluegrass (Poa pratensis L.) genotypes in response to heat stress. Notulae Botanicae Horti Agrobotanici Cluj-Napoca 47, 328–338 (2018). (PMID: 10.15835/nbha47111365) ; González, L. & González-Vilar, M. Determination of relative water content. Handbook of Plant Ecophysiology Techniques 6, 207–212 (2001). ; Su, S., Zhou, Y., Qin, J., Yao, W. & Ma, Z. Optimization of the method for chlorophyll extraction in aquatic plants. Journal of Freshwater Ecology 25, 531–538 (2010). (PMID: 10.1080/02705060.2010.9664402) ; Marković, S. M. et al. Correlation of elongation factor 1A accumulation with photosynthetic pigment content and yield in winter wheat varieties under heat stress conditions. Plant Physiology and Biochemistry 166, 572–581 (2021). (PMID: 3417581210.1016/j.plaphy.2021.06.035) ; Guo, Z. et al. The Arabidopsis transcription factor LBD15 mediates ABA signaling and tolerance of water‐deficit stress by regulating ABI4 expression. The Plant Journal 104, 510–521 (2020). (PMID: 3274443210.1111/tpj.14942) ; Hackl, T., Hedrich, R., Schultz, J. & Förster, F. Proovread: large-scale high-accuracy PacBio correction through iterative short read consensus. Bioinformatics 30, 3004–3011 (2014). (PMID: 25015988460900210.1093/bioinformatics/btu392) ; Li, W. & Godzik, A. Cd-Hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22, 1658–1659 (2006). (PMID: 1673169910.1093/bioinformatics/btl158) ; Seppey, M., Manni, M. & Zdobnov, E. M. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 1962, 227–245 (2019). ; Bray, N. L., Pimentel, H., Melsted, P. & Pachter, L. Near-optimal probabilistic RNA-seq quantification. Nature Biotechnology 34, 525–527 (2016). (PMID: 2704300210.1038/nbt.3519) ; Anders, S. et al. Count-based differential expression analysis of RNA sequencing data using R and Bioconductor. Nature Protocols 8, 1765–1786 (2013). (PMID: 2397526010.1038/nprot.2013.099) ; Chen, C., Xia, R., Chen, H. & He, Y. TBtools, a Toolkit for Biologists integrating various HTS-data handling tools with a user-friendly interface. bioRxiv 13, 1194–1202 (2018). ; Deng, Y. et al. Integrated nr Database in Protein Annotation System and Its Localization. Computer Engineering 32, 71–72 (2006). ; Rolf, A. et al. UniProt: the Universal Protein knowledgebase. Nucleic Acids Research 32, 115–119 (2004). (PMID: 10.1093/nar/gkh131) ; Ashburner, M. et al. Gene Ontology: tool for the unification of biology. Nature Genetics 25, 25–29 (2000). (PMID: 10802651303741910.1038/75556) ; Tatusov, R. L., Galperin, M. Y., Natale, D. A. & Koonin, E. V. The COG database: a tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Research 28, 33–36 (2000). (PMID: 1059217510239510.1093/nar/28.1.33) ; Koonin, E. V. et al. A comprehensive evolutionary classification of proteins encoded in complete eukaryotic genomes. Genome Biology 5, 7–7 (2004). (PMID: 10.1186/gb-2004-5-2-r7) ; Finn, R. D. Pfam: the protein families database. Nucleic Acids Research 42, 222–230 (2005). (PMID: 10.1093/nar/gkt1223) ; Minoru, K., Susumu, G., Shuichi, K., Yasushi, O. & Masahiro, H. The KEGG resource for deciphering the genome. Nucleic Acids Research 32, 277–280 (2004). (PMID: 10.1093/nar/gkh063) ; Young, M. D., Wakeeld, M. J., Smyth, G. K. & Oshlack, A. Goseq: Gene Ontology testing for RNA-seq datasets. Genome Biology 11, 14–39 (2012). (PMID: 10.1186/gb-2010-11-2-r14) ; Chen, X. et al. KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases. Nucleic Acids Research 39, 316–322 (2011). (PMID: 10.1093/nar/gkr483) ; Yu, G., Wang, L. G., Han, Y. & He, Q. Y. ClusterProfiler: an R package for comparing biological themes among gene clusters. Omics: a journal of integrative biology 16, 284–287 (2012). (PMID: 2245546310.1089/omi.2011.0118) ; NGDC histology raw data archives (CRA006867) https://ngdc.cncb.ac.cn/gsa/search?searchTerm=CRA006867 (2022). ; NGDC histology raw data archives (CRA006889) https://ngdc.cncb.ac.cn/gsa/search?searchTerm=CRA006889 (2022). ; Meng, C. et al. Transcriptomic profiling of Poa pratensis L. under treatment of various phytohormones. figshare https://doi.org/10.6084/m9.figshare.24152721 (2023). ; Li, Q., Liu, J. H., Wu, J. Y., Li, L. J. & Zhang, L. Effect of salt stress on membrane permeability and Na + ,K + absorption of Oat. Acta Agriculturae Boreali-Sinica 24, 88–92 (2009). ; Ling, Q. et al. Ubiquitin-dependent chloroplast-associated protein degradation in plants. Science 363, 44–67 (2019). (PMID: 10.1126/science.aav4467) ; Bonan, G. B. Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320, 1444–1449 (2008). (PMID: 1855654610.1126/science.1155121) ; Verma, V., Ravindran, P. & Kumar, P. Plant hormone-mediated regulation of stress responses. BMC Plant Biology 16, 1–10 (2016). (PMID: 10.1186/s12870-016-0771-y) ; Meng, C. et al. KEGG pathway enrichment. figshare https://doi.org/10.6084/m9.figshare.24152715 (2023). Grant Information: 32370405 National Natural Science Foundation of China (National Science Foundation of China) Substance Nomenclature: 0 (Plant Growth Regulators) Entry Date(s): Date Created: 20240316 Date Completed: 20240318 Latest Revision: 20240319 Update Code: 20240319 PubMed Central ID: PMC10942976

Klicken Sie ein Format an und speichern Sie dann die Daten oder geben Sie eine Empfänger-Adresse ein und lassen Sie sich per Email zusenden.

BibTeX Citavi, JabRef, u.a.
(Literaturverwaltung)

PDF kein Volltext!
(Merkzettel, Notizen)

RIS Endnote, Citavi u.a.
(Literaturverwaltung)

MODS
(XML zur Weiterverarbeitung)

oder

Wählen Sie das für Sie passende Zitationsformat und kopieren Sie es dann in die Zwischenablage, lassen es sich per Mail zusenden oder speichern es als PDF-Datei.

Gewünschter Zitations-Stil:

oder

Bitte prüfen Sie, ob die Zitation formal korrekt ist, bevor Sie sie in einer Arbeit verwenden. Benutzen Sie gegebenenfalls den "Exportieren"-Dialog, wenn Sie ein Literaturverwaltungsprogramm verwenden und die Zitat-Angaben selbst formatieren wollen.

Transcriptomic profiling of Poa pratensis L. under treatment of various phytohormones.