AUTHOR=Akiyama-Oda Yasuko , Akaiwa Takanori , Oda Hiroki 

TITLE=Reconstruction of the Global Polarity of an Early Spider Embryo by Single-Cell and Single-Nucleus Transcriptome Analysis

JOURNAL=Frontiers in Cell and Developmental Biology

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2022.933220

DOI=10.3389/fcell.2022.933220

ISSN=2296-634X

ABSTRACT=Patterning along an axis of polarity is a fundamental step in the development of a multicellular animal embryo. In the cellular field of an early spider embryo, Hedgehog signaling operates to specify a “fuzzy” French-flag-like pattern along the primary axis, which is related to the future anterior-posterior (A-P) axis. However, details regarding the generation and development of a diversity of cell states based on the embryo polarity are not known. To address this issue, we applied single-cell RNA sequencing to the early spider embryo consisting of approximately 2,000 cells. Our results confirmed that this technique successfully detected three cell populations corresponding to the germ layers and some transient cell states. We showed that the data from dissociated cells had sufficient information for reconstruction of a correct global A-P polarity of the presumptive ectoderm, without clear segregation of specific cell states. This outcome is explained by varied but differentially overlapping expression of Hedgehog-signal target genes and newly identified marker genes. We also showed that the data resources generated by the transcriptome analysis are applicable to a genome-wide search for genes whose expression is spatially regulated, based on the detection of pattern similarity.  Furthermore, we performed single-nucleus RNA-sequencing, which was more powerful in detecting emerging cell states. The single-cell and single-nucleus transcriptome techniques will help investigate the pattern-forming processes in the spider model system in an unbiased, comprehensive manner. We provided web-based resources of these transcriptome datasets for future studies of pattern formation and cell differentiation.