Best practices for the execution, analysis, and data storage of plant single-cell/nucleus transcriptomicsInstitute of Plant Sciences, University of Bern, 3012 Bern, Switzerland.
Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent 9052, Belgium; VIB Centre for Plant Systems Biology, Ghent 9052, Belgium.
Department of Biology, Duke University, Durham, NC 27708, USA; Howard Hughes Medical Institute, Duke University, Durham, NC 27708, USA.
Donald Danforth Plant Science Center, St. Louis, MO 63132, USA.
Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA.
Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent 9052, Belgium; VIB Centre for Plant Systems Biology, Ghent 9052, Belgium.
Centre for Organismal Studies, Heidelberg University, 69120 Heidelberg, Germany.
Universities of Paris-Saclay, Paris-Cité and Evry, CNRS, INRAE, Institute of Plant Sciences Paris-Saclay, Gif-sur-Yvette 91192, France.
DOE-Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences (CEMPS), Institute of Plant Physiology and Ecology (SIPPE), Chinese Academy of Sciences (CAS), Shanghai 200032, China.
Institute of Biology, Humboldt-Universität zu Berlin, 10115 Berlin, Germany.
Institute of Plant Sciences, University of Bern, 3012 Bern, Switzerland.
Department of Comparative Development and Genetics, Max Planck Institute for Plant Breeding Research, 50829 Cologne, Germany.
Centre for Organismal Studies, Heidelberg University, 69120 Heidelberg, Germany.
Division of Plant Science and Technology, Interdisciplinary Plant Group, College of Agriculture, Food, and Natural Resources, University of Missouri-Columbia, Columbia, MO 65201, USA.
Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent 9052, Belgium; VIB Centre for Plant Systems Biology, Ghent 9052, Belgium.
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2024 (English)In: The Plant Cell, ISSN 1040-4651, E-ISSN 1532-298X, Vol. 36, no 4, p. 812-828Article, review/survey (Refereed) Published
Abstract [en]
Single-cell and single-nucleus RNA-sequencing technologies capture the expression of plant genes at an unprecedented resolution. Therefore, these technologies are gaining traction in plant molecular and developmental biology for elucidating the transcriptional changes across cell types in a specific tissue or organ, upon treatments, in response to biotic and abiotic stresses, or between genotypes. Despite the rapidly accelerating use of these technologies, collective and standardized experimental and analytical procedures to support the acquisition of high-quality data sets are still missing. In this commentary, we discuss common challenges associated with the use of single-cell transcriptomics in plants and propose general guidelines to improve reproducibility, quality, comparability, and interpretation and to make the data readily available to the community in this fast-developing field of research.
Place, publisher, year, edition, pages
Oxford University Press (OUP) , 2024. Vol. 36, no 4, p. 812-828
National Category
Bioinformatics and Computational Biology
Identifiers
URN: urn:nbn:se:kth:diva-367032DOI: 10.1093/plcell/koae003ISI: 001156421600001PubMedID: 38231860Scopus ID: 2-s2.0-85187579079OAI: oai:DiVA.org:kth-367032DiVA, id: diva2:1983654
Note
QC 20250711
2025-07-112025-07-112025-07-11Bibliographically approved