Dataset Information

Single-cell transcriptome analysis of Physcomitrella leaf cells during reprogramming using microcapillary manipulation.

ABSTRACT: Next-generation sequencing technologies have made it possible to carry out transcriptome analysis at the single-cell level. Single-cell RNA-sequencing (scRNA-seq) data provide insights into cellular dynamics, including intercellular heterogeneity as well as inter- and intra-cellular fluctuations in gene expression that cannot be studied using populations of cells. The utilization of scRNA-seq is, however, restricted to cell types that can be isolated from their original tissues, and it can be difficult to obtain precise positional information for these cells in situ. Here, we established single cell-digital gene expression (1cell-DGE), a method of scRNA-seq that uses micromanipulation to extract the contents of individual living cells in intact tissue while recording their positional information. With 1cell-DGE, we could detect differentially expressed genes (DEGs) during the reprogramming of leaf cells of the moss Physcomitrella patens, identifying 6382 DEGs between cells at 0 and 24 h after excision. Furthermore, we identified a subpopulation of reprogramming cells based on their pseudotimes, which were calculated using transcriptome profiles at 24 h. 1cell-DGE with microcapillary manipulation can be used to analyze the gene expression of individual cells without detaching them from their tightly associated tissues, enabling us to retain positional information and investigate cell-cell interactions.

SUBMITTER: Kubo M

PROVIDER: S-EPMC6511839 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Single-cell transcriptome analysis of Physcomitrella leaf cells during reprogramming using microcapillary manipulation.

Kubo Minoru M Nishiyama Tomoaki T Tamada Yosuke Y Sano Ryosuke R Ishikawa Masaki M Murata Takashi T Imai Akihiro A Lang Daniel D Demura Taku T Reski Ralf R Hasebe Mitsuyasu M

Nucleic acids research 20190501 9

Next-generation sequencing technologies have made it possible to carry out transcriptome analysis at the single-cell level. Single-cell RNA-sequencing (scRNA-seq) data provide insights into cellular dynamics, including intercellular heterogeneity as well as inter- and intra-cellular fluctuations in gene expression that cannot be studied using populations of cells. The utilization of scRNA-seq is, however, restricted to cell types that can be isolated from their original tissues, and it can be di ...[more]

PMID: 30873540

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Project description:BackgroundDifferentiated plant cells can retain the capacity to be reprogrammed into pluripotent stem cells during regeneration. This capacity is associated with both cell cycle reactivation and acquisition of specific cellular characters. However, the molecular mechanisms underlying the reprogramming of protoplasts into stem cells remain largely unknown. Protoplasts of the moss Physcomitrella patens easily regenerate into protonema and therefore provide an ideal system to explore how differentiated cells can be reprogrammed to produce stem cells.Principal findingsWe obtained genome-wide digital gene expression tag profiles within the first three days of P. patens protoplast reprogramming. At four time-points during protoplast reprogramming, the transcript levels of 4827 genes changed more than four-fold and their expression correlated with the reprogramming phase. Gene ontology (GO) and pathway enrichment analysis of differentially expressed genes (DEGs) identified a set of significantly enriched GO terms and pathways, most of which were associated with photosynthesis, protein synthesis and stress responses. DEGs were grouped into six clusters that showed specific expression patterns using a K-means clustering algorithm. An investigation of function and expression patterns of genes identified a number of key candidate genes and pathways in early stages of protoplast reprogramming, which provided important clues to reveal the molecular mechanisms responsible for protoplast reprogramming.ConclusionsWe identified genes that show highly dynamic changes in expression during protoplast reprogramming into stem cells in P. patens. These genes are potential targets for further functional characterization and should be valuable for exploration of the mechanisms of stem cell reprogramming. In particular, our data provides evidence that protoplasts of P. patens are an ideal model system for elucidation of the molecular mechanisms underlying differentiated plant cell reprogramming.

Dataset Information

Single-cell transcriptome analysis of Physcomitrella leaf cells during reprogramming using microcapillary manipulation.

Publications

Single-cell transcriptome analysis of Physcomitrella leaf cells during reprogramming using microcapillary manipulation.

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