The article reviews the advancements and applications of spatial transcriptomics, a technique that combines next-generation sequencing (NGS) and imaging to measure gene expression levels across tissue spaces. Spatial transcriptomics has revolutionized the understanding of cellular organization and biological functions in multicellular organisms, particularly in neuroscience, development, plant biology, and disease studies. The review covers the principles and methods of spatial transcriptomics, including NGS-based and imaging-based approaches, and discusses the data analysis techniques used to explore these datasets. It highlights the potential of spatial transcriptomics for hypothesis generation and testing, as well as its integration with other data modalities to enhance biological insights. The article also emphasizes the importance of spatial transcriptomics in studying tissue disorganization in diseases such as cancer and neurodegenerative disorders, and its role in uncovering the underlying mechanisms. Finally, it outlines the future directions and challenges in the field, including the need for improved resolution, sensitivity, and computational tools to fully realize the potential of spatial transcriptomics.The article reviews the advancements and applications of spatial transcriptomics, a technique that combines next-generation sequencing (NGS) and imaging to measure gene expression levels across tissue spaces. Spatial transcriptomics has revolutionized the understanding of cellular organization and biological functions in multicellular organisms, particularly in neuroscience, development, plant biology, and disease studies. The review covers the principles and methods of spatial transcriptomics, including NGS-based and imaging-based approaches, and discusses the data analysis techniques used to explore these datasets. It highlights the potential of spatial transcriptomics for hypothesis generation and testing, as well as its integration with other data modalities to enhance biological insights. The article also emphasizes the importance of spatial transcriptomics in studying tissue disorganization in diseases such as cancer and neurodegenerative disorders, and its role in uncovering the underlying mechanisms. Finally, it outlines the future directions and challenges in the field, including the need for improved resolution, sensitivity, and computational tools to fully realize the potential of spatial transcriptomics.