Download or read book Single-Cell Genomics written by Parwinder Kaur and published by Springer. This book was released on 2025-06-13 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cells, the basic units of biological structure and function, vary broadly in type and state. Individual cells are the building blocks of tissues, organs, and organisms. Each tissue contains cells of many types, and cells of each type can switch among biological states. Single-cell genomics, transcriptomics and epigenomics open a whole new era with the possibility to interrogate every cell of an organism in order to decipher the important biological processes that occur within. This has emerged as a ground-breaking technology that has greatly enhanced our understanding of the complexity of gene expression dynamics at a microscopic resolution. It is anticipated that in the next 5-10 years, the wider research community will be routinely employing this powerful technology as a laboratory staple. Single-cell genomics, transcriptomics and epigenomics hold the potential to revolutionize the way we characterize complex cell assemblies and study their spatial organization, dynamics, clonal distribution, pathways, function, and crosstalks. These fascinating advances have opened up a new field of cell population genomics. Single-cell genomics, transcriptomics and epigenomics research is providing new insights into inter-cellular population genomic diversity, heterogeneity, specialization, taxonomy, spatial and temporal gene regulation, and cellular and organismal development and evolution. It is facilitating plant breeding, understanding of human disease conditions and personalized medicine. This book discusses the perspectives, progress, and promises of single-cell genomics, transcriptomics and epigenomics research and applications in addressing the above and other key biological aspects in all organisms. It establishes the current state-of-the-field and serves as the foundation for future developments in single-cell genomics, transcriptomics, and epigenomics.