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Recent progress in single-cell transcriptomic studies in plants

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dc.contributor.authorCho, Yuhan-
dc.contributor.authorKadam, Ulhas-
dc.contributor.authorPark, Bogun-
dc.contributor.authorAmariillis, Shandra-
dc.contributor.authorNguyen, Kim-Ngan Thi-
dc.contributor.authorCan, Mai-Huong Thi-
dc.contributor.authorLee, Kyun Oh-
dc.contributor.authorPark, Soon Ju-
dc.contributor.authorChung, Woo Sik-
dc.contributor.authorHong, Jong Chan-
dc.date.accessioned2025-05-02T08:30:18Z-
dc.date.available2025-05-02T08:30:18Z-
dc.date.issued2025-04-
dc.identifier.issn1863-5466-
dc.identifier.issn1863-5474-
dc.identifier.urihttps://scholarworks.gnu.ac.kr/handle/sw.gnu/77975-
dc.description.abstractPlants are complex multi-cellular organisms. Each tissue has its unique role and a variety of cell types that contribute to overall function. Single-cell RNA sequencing (scRNA-seq) has revolutionized our ability to study this cellular diversity. This technology allows us to identify rare cell types and understand their functions within the plant. Additionally, spatial transcriptomics provides a gene expression map within tissue and empowers us to see how cells interact and contribute to tissue-specific functions within their spatial context. While spatial transcriptomics has dramatically advanced our understanding of plant biology, it still faces challenges in capturing individual cells' complete gene expression profiles. Here, we provide a comprehensive overview of scRNA-seq and spatial transcriptomics, including the experimental procedures, computational methods, and data integration strategies. It highlights the impact of these technologies on plant cell biology, discusses their strengths and limitations, and offers a glimpse into the future of this exciting field. As these technologies continue to evolve, they will provide an increasingly detailed and comprehensive view of plant cells, leading to discoveries about plant development, function, and response to the environment.-
dc.format.extent13-
dc.language영어-
dc.language.isoENG-
dc.publisher한국식물생명공학회-
dc.titleRecent progress in single-cell transcriptomic studies in plants-
dc.typeArticle-
dc.publisher.location대한민국-
dc.identifier.doi10.1007/s11816-025-00967-z-
dc.identifier.scopusid2-s2.0-105001860799-
dc.identifier.wosid001459015800001-
dc.identifier.bibliographicCitationPlant Biotechnology Reports, v.19, no.2, pp 91 - 103-
dc.citation.titlePlant Biotechnology Reports-
dc.citation.volume19-
dc.citation.number2-
dc.citation.startPage91-
dc.citation.endPage103-
dc.type.docTypeReview-
dc.identifier.kciidART003198927-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.description.journalRegisteredClasskci-
dc.relation.journalResearchAreaBiotechnology & Applied Microbiology-
dc.relation.journalResearchAreaPlant Sciences-
dc.relation.journalWebOfScienceCategoryBiotechnology & Applied Microbiology-
dc.relation.journalWebOfScienceCategoryPlant Sciences-
dc.subject.keywordPlusRNA TRANSCRIPTS-
dc.subject.keywordPlusTECHNOLOGY-
dc.subject.keywordPlusEXPRESSION-
dc.subject.keywordPlusSEQ-
dc.subject.keywordAuthorRNA sequencing-
dc.subject.keywordAuthorSingle Cell (scRNA-Seq)-
dc.subject.keywordAuthorSingle Nucleus (snRNA-Seq)-
dc.subject.keywordAuthorPlants-
dc.subject.keywordAuthorCrops-
dc.subject.keywordAuthorTools-
dc.subject.keywordAuthorStress responses-
dc.subject.keywordAuthorData analysis-
dc.subject.keywordAuthorGuidelines-
dc.subject.keywordAuthorTranscriptomics-
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