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=10 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 3 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 the 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.