Makoto Kashima, Rei Komura, Yuki Sato, Chikara Hashimoto, Hiromi Hirata
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A resource of single-cell gene expression profiles in a planarian Dugesia japonica
The freshwater planarian Dugesia japonica maintains an abundant heterogeneous cell population called neoblasts, which include adult pluripotent stem cells. Thus, it is an excellent model organism for stem cell and regeneration research. Recently, many single-cell RNA sequencing (scRNA-seq) databases of several model organisms, including other planarian species, have become publicly available; these are powerful and useful resources to search for gene expression in various tissues and cells. However, the only scRNA-seq dataset for D. japonica has been limited by the number of genes detected. Herein, we collected D. japonica cells, and conducted an scRNA-seq analysis. A novel, automatic, iterative cell clustering strategy produced a dataset of 3,404 cells, which could be classified into 63 cell types based on gene expression profiles. We introduced two examples for utilizing the scRNA-seq dataset in this study using D. japonica. First, the dataset provided results consistent with previous studies as well as novel functionally relevant insights, that is, the expression of DjMTA and DjP2X-A genes in neoblasts that give rise to differentiated cells. Second, we conducted an integrative analysis of the scRNA-seq dataset and time-course bulk RNA-seq of irradiated animals, demonstrating that the dataset can help interpret differentially expressed genes captured via bulk RNA-seq. Using the R package “Seurat” and GSE223927, researchers can easily access and utilize this dataset.
期刊介绍:
Development Growth & Differentiation (DGD) publishes three types of articles: original, resource, and review papers.
Original papers are on any subjects having a context in development, growth, and differentiation processes in animals, plants, and microorganisms, dealing with molecular, genetic, cellular and organismal phenomena including metamorphosis and regeneration, while using experimental, theoretical, and bioinformatic approaches. Papers on other related fields are also welcome, such as stem cell biology, genomics, neuroscience, Evodevo, Ecodevo, and medical science as well as related methodology (new or revised techniques) and bioresources.
Resource papers describe a dataset, such as whole genome sequences and expressed sequence tags (ESTs), with some biological insights, which should be valuable for studying the subjects as mentioned above.
Submission of review papers is also encouraged, especially those providing a new scope based on the authors’ own study, or a summarization of their study series.