Computational Molecular Biology 2025, Vol.15, No.2, 91-101 http://bioscipublisher.com/index.php/cmb 97 Ranzoni et al. conducted combined sequencing of scRNA-seq and scATAC-seq on HSC/MPP and subsequent progenitor cells in the liver and bone marrow of human fetuses, analyzing over 8,000 single cells in total. Firstly, based on the scRNA-seq data, they mapped the differentiation trajectories of hematopoietic cells, showing that the HSC/MPP population was at the top of the trajectory and differentiated along three main branches: the red blood cell/megakaryocyte branch, the myeloid mononuclear cell branch, and the lymphocyte branch. Interestingly, they observed significant transcriptional heterogeneity in the HSC/MPP population, suggesting that different transcriptional subpopulations are actually contained within the HSC/MPP defined by surface markers. This provides new evidence for the long-standing debate over whether the HSC group is homogeneous: the HSC is not a single static group but is dynamically composed of multiple subtypes, which may predict different fates. 6.2 Nervous system development and cell type diversity The development of the nervous system is complex and generates a wide variety of cells, including various types of neurons and glial cells. Take the development of the cerebral cortex as an example. Interneurons (inhibitory neurons) and projection neurons (excitatory neurons) come from different developmental regions, and their fate is determined by delicate spatiotemporal regulation. Single-cell omics integration analysis has also made progress in this field in recent years, such as the study of the development process of interneurons in primate brains (Cai et al., 2025). After integrating the scATAC data, they explored the changes in chromatin opening and gene regulation at different stages. The results show that many key transcription factors already recognized in rodents (such as mice), such as DLX, NKX2-1, LHX6, etc., function similarly in primates, with their binding sequences significantly open in the chromatin at the corresponding stages. For instance, multiple enhancers of the DLX gene cluster are open at the basal progenitor cell stage, and the DLX gene mRNA is highly expressed, which drives the gradual expression of a series of downstream inhibitory neuron genes (such as GAD1/2, etc.). This indicates that these factors form a conserved regulatory network that drives the fate of interneurons. 6.3 Key findings and biological implications in the case In hematopoietic cases, integrative analysis revealed the existence of transitional progenitor cell populations (MEMP/GP/LMP) biased towards different lineages in HSC/MPP, enriching the traditional lineage tree model. In neurological cases, multiple intermediate progenitor cell stages have also been identified, such as basal progenitor cells and migrating immature neurons. These transitional states are difficult to capture in population experiments, but single-cell analysis can depict them, indicating that cell fate determination is not achieved in one step but goes through multiple gradual stages. Both cases show that chromatin opening at the binding sites of key transcription factors often precedes changes in gene expression. For instance, in hematopoiesis, the GATA1 enhancer opens in advance, while in the nervous system, ASCL1 opens its target area first. This validates the "chromatin open leader" hypothesis and emphasizes the role of pioneer transcription factors (Felce et al., 2024). This is of great significance to developmental biology because in the past, most inferences about the chronological order came from indirect reasoning, but now there is direct single-cell evidence to support it. Integrated analysis not only lists the key factors but also weaves them into network modules. For instance, in hematopoietic cases, there are the HLF-HOXA9 stem cell module and the CEBP-IRF myeloid module; in neurological cases, there are the DLX module and the NEUROD module, etc. These network modules encompass the main regulatory factors and their downstream genes, providing a systematic understanding of the fate determination mechanism rather than acting in isolation. This network perspective is conducive to formulating intervention strategies because regulatory networks often have redundancy and complementarity, and recognition networks are more comprehensive than single genes. 7 Potential Clinical Applications and Disease Mechanism Research 7.1 Tumor heterogeneity and discovery of therapeutic targets Tumors are typical cases of abnormal determination of cell fate. Normal cells transform into cancer cells with uncontrolled proliferation and abnormal differentiation through a series of gene mutations and epigenetic changes.
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