International Journal of Molecular Zoology 2024, Vol.14, No.1, 31-43 http://animalscipublisher.com/index.php/ijmz 32 development (Peng et al., 2018), providing new ideas and methods for the prevention and treatment of developmental diseases. This study aims to review the application of single-cell omics technology in developmental biology, from model organisms to humans, and analyze the development of single-cell omics technology and its potential applications in developmental biology, in order to comprehensively and systematically demonstrate the achievements and prospects of single-cell omics application in developmental biology. 1 Application of Single-cell Omics in Model Organisms 1.1 Application in simple eukaryotic yeast Yeast, as a simple but representative eukaryotic organism, has always received widespread attention in biological research. In recent years, with the rapid development of single-cell omics technology, yeast has become an ideal model organism for studying these technologies. Single cell omics technology provides unprecedented opportunities for yeast research, enabling scientists to gain a deeper understanding of gene expression, protein interactions, and metabolic processes within individual yeast cells. In single-cell transcriptomics, the cell cycle and metabolic pathways of yeast have been extensively studied. Single cell RNA sequencing (scRNA seq) technology can accurately measure the gene expression patterns of individual yeast cells under different growth conditions and cell cycle stages. This helps to understand how yeast cells adapt to different environmental pressures and regulate their life activities. In terms of single-cell proteomics, yeast also provides rich research cases. Single cell mass spectrometry technology can be used to identify the types and quantities of proteins within a single yeast cell (Bartolec et al., 2019), as well as their interactions. This helps to reveal the signaling pathways and regulatory networks within yeast cells. In addition, the genome of yeast is relatively small and easy to operate, and gene editing techniques such as CRISPR-Cas9 can be used to precisely knock out or insert specific genes (Figure 1), in order to study the role of these genes in yeast cell growth, metabolism, and differentiation. Figure 1 CRISPR/Cas9 tool for yeast library creation (Liao et al., 2022) Single cell omics has the potential to revolutionize the complexity of yeast biology and its applications in biotechnology and systems biology. To understand the genetic and functional diversity within yeast populations, single-cell methods provide a more detailed and detailed perspective. Efremova and Teichmann (2020) studied computational methods for analyzing and integrating single-cell omics data in different ways, opening up new avenues for reconstructing gene regulation and signaling networks that drive cell identity and function. This is crucial for accurately understanding the genotype and phenotype heterogeneity within the yeast population. Kaster and Sobol (2020) found that single-cell omics expands the understanding of microbial diversity and metabolic potential by providing information from individual organisms and the structure and dynamics of natural microbial communities in complex environments. This includes the current lack of representative deep lineage populations, highlighting their importance in microbiology and biotechnology research, particularly in relation to yeast research.
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