Computational Molecular Biology 2025, Vol.15, No.2, 91-101 http://bioscipublisher.com/index.php/cmb 91 Feature Review Open Access Integrative Analysis of scRNA-seq and ATAC-seq for Cell Fate Determination Hongpeng Wang, Minghua Li Biotechnology Research Center, Cuixi Academy of Biotechnology, Zhuji, 311800, China Corresponding author: minghua.li@cuixi.org Computational Molecular Biology, 2025, Vol.15, No.2 doi: 10.5376/cmb.2025.15.0009 Received: 01 Feb., 2025 Accepted: 12 Mar., 2025 Published: 01 Apr., 2025 Copyright © 2025 Wang and Li, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.6 Preferred citation for this article: Wang H.P., and Li M.H., 2025, Integrative analysis of scRNA-seq and ATAC-seq for cell fate determination, Computational Molecular Biology, 15(2): 91-101 (doi: 10.5376/cmb.2025.15.0009) Abstract Single-cell RNA sequencing (scRNA-seq) and single-cell chromatin accessibility sequencing (scATAC-seq) are important technological breakthroughs in the field of life sciences in recent years, providing an unprecedented high-resolution perspective for studying the mechanism of cell fate determination. The gene expression profile of individual cells can be analyzed through scRNA-seq, revealing cellular heterogeneity and developmental trajectories. scATAC-seq can detect the chromatin open state at the single-cell level and identify potential regulatory elements and binding sites of transcription factors. The integration and analysis of scRNA-seq and scATAC-seq data can simultaneously characterize the cell state at both the transcriptional and epigenetic levels, thereby gaining an in-depth understanding of the synergistic role of transcriptional regulatory networks and chromatin dynamics in the process of cell fate determination. This study will review the principles and applications of single-cell omics technology, discuss the roles of transcription factors and chromatin accessibility in cell fate determination, and focus on introducing the key regulatory factors, cis-regulatory elements and gene regulatory networks revealed by the integrated analysis of scRNA-seq and scATAC-seq. We will also introduce methods for inferring cell fate trajectories and conducting pathway enrichment analysis using integrated data, and through cases of hematopoietic and nervous system development, illustrate how integrated analysis can reveal new insights into the process of cell differentiation. Finally, the potential clinical application value of single-cell multi-omics in areas such as tumor heterogeneity, immune cell fate, and regenerative medicine is prospected. The limitations of current technologies and analytical methods are analyzed, and the future development directions are prospected. Keywords Single-cell sequencing; Chromatin accessibility; Transcriptomics; Multi-omics integration; Cell fate determination 1 Introduction Multicellular organisms are composed of highly diverse cell types, all of which originate from fertilized eggs but gradually limit their fates during development, differentiating into cell populations with different functions. Cell fate determination involves a series of complex regulatory events, including changes in gene regulatory networks, reprogramming of epigenetic states, and the role of extracellular signals, etc. Classic developmental biology research has established cell fate maps and lineage relationships. For instance, in model organisms such as nematodes and fruit flies, the origin of each cell line was identified through embryonic tracing. However, the development of higher mammals (such as humans and mice) is more complex, and the key molecular mechanisms in the process of cell fate determination remain to be clarified. Traditional research methods often rely on the measurement of average signals of large population cells, which may mask significant differences among different cell subpopulations. For instance, in hematopoietic stem cell research, progenitor cells from different subpopulations may be evenly distributed in population sequencing, making it impossible to identify a small number of rapidly proliferating transitional cell populations. In recent years, the rise of single-cell sequencing technology has enabled researchers to analyze the developmental process at the single-cell level. For instance, single-cell RNA sequencing during the early embryonic development stage can reconstruct the differentiation trajectories of different cell types, identify the key branch points determined by early lineages and the accompanying changes in gene expression. These studies have revealed the high asynchrony of the developmental process and the heterogeneity among cells, indicating that cell fate determination does not occur synchronously but that different cells may enter their respective differentiation pathways at different times (Swanson et al., 2021).
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