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Single-cell sequencing is a new technique for high-throughput molecular detection of genome and transcriptome based on a single-cell level. Previous highthroughput sequencing techniques aimed at sequencing a mixed population of cells. They ignored the results of gene expression differences between individual cells, so much of the low-abundance information was lost. TANG published a paper in 2009 describing the Single-Cell RNA Sequencing (scRNA-SEQ) method [1]. After that, the technology developed rapidly, and various technology platforms were developed. Simultaneous sequencing of many samples is realized, which provides an effective method for studying the molecular mechanism of cell classifi cation and cell development of organisms. Its technical route is shown in figure 1. In this paper, the research on cell classification by using scRNA-SEQ technology alone at the single-cell level was described, and cell information was analyzed together with spatial transcriptome data, tissue gene maps were depicted at both the cellular and spatial levels, and the research results obtained by using scNA-SEQ technology were summarized.