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Shoot and root single cell sequencing reveals tissue- and daytime-specific transcriptome profiles

Although several large-scale single-cell RNA sequencing (scRNAseq) studies addressing the root of Arabidopsis (Arabidopsis thaliana) have been published, there is still need for a de novo reference map for both root and especially above-ground cell types. As the plants’ transcriptome substantially c...

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Detalles Bibliográficos
Autores principales: Apelt, Federico, Mavrothalassiti, Eleni, Gupta, Saurabh, Machin, Frank, Olas, Justyna Jadwiga, Annunziata, Maria Grazia, Schindelasch, Dana, Kragler, Friedrich
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8825464/
https://www.ncbi.nlm.nih.gov/pubmed/34850215
http://dx.doi.org/10.1093/plphys/kiab537
Descripción
Sumario:Although several large-scale single-cell RNA sequencing (scRNAseq) studies addressing the root of Arabidopsis (Arabidopsis thaliana) have been published, there is still need for a de novo reference map for both root and especially above-ground cell types. As the plants’ transcriptome substantially changes throughout the day, shaped by the circadian clock, we performed scRNAseq on both Arabidopsis root and above-ground tissues at defined times of the day. For the root scRNAseq analysis, we used tissue-specific reporter lines grown on plates and harvested at the end of the day (ED). In addition, we submitted above-ground tissues from plants grown on soil at ED and end of the night to scRNAseq, which allowed us to identify common cell types/markers between root and shoot and uncover transcriptome changes to above-ground tissues depending on the time of the day. The dataset was also exploited beyond the traditional scRNAseq analysis to investigate non-annotated and di-cistronic transcripts. We experimentally confirmed the predicted presence of some of these transcripts and also addressed the potential function of a previously unidentified marker gene for dividing cells. In summary, this work provides insights into the spatial control of gene expression from nearly 70,000 cells of Arabidopsis for below- and whole above-ground tissue at single-cell resolution at defined time points.