Computational Molecular Biology 2025, Vol.15, No.2, 91-101 http://bioscipublisher.com/index.php/cmb 98 Within tumors, not only do cancer cells themselves exhibit high heterogeneity, but immune cells and others in the microenvironment are also diverse. This heterogeneity is an important cause of tumor drug resistance and treatment failure. Integrated analysis of single-cell RNA-seq and ATAC-seq provides a powerful tool for analyzing tumor heterogeneity and can identify the characteristics and regulatory networks of different subpopulations within tumors (Raevskiy et al., 2023). For instance, in the studies of renal cell carcinoma and breast cancer mentioned earlier, integrative analysis revealed that tumor cells can be classified into different "fate" subtypes: one proliferative type, which exhibits high activity in cell cycle genes and the MYC pathway; An invasive type, showing epithelial-mesenchymal transition and AP-1 transcription factor activity. These subtypes may be averaged out at the bulk level, but single-cell technology makes them clearly visible. More importantly, through scATAC-seq, the key cis-elements and transcription factors driving each subtype can be identified. This suggests that different subgroups of tumor cells may require different treatment strategies. 7.2 Immune cell fate and disease mechanisms The immune system is another system with highly malleable cellular fate. Single-cell omics integration technology provides a new approach for studying the differentiation fate and disease mechanisms of immune cells. In cases of chronic infection or cancer, T cells often head towards functional failure. The trajectory and regulatory network of this exhausted state were revealed through the integration of scRNA+scATAC analysis. Research has found that the transcription factor TOX is gradually upregulated on the depletion trajectory and opens the chromatin regions of inhibitory genes such as PDCD1 (Leslie, 2020). In autoimmune diseases such as systemic lupus erythematosus (SLE), studies have identified an inflammation-related B-cell intermediate state, characterized by the expression of T-bet and being in a transitional state between memory and plasma cells. Such abnormal fate decisions may be the key link in the occurrence of diseases. 7.3 Prospects of regenerative medicine and precision medicine The core of regenerative medicine lies in controlling the fate of stem cells or somatic cells to transform them into the desired functional cells. Integrated single-cell RNA/ATAC analysis provides key support for this field (Wang et al., 2024). In in vitro induction differentiation, single-cell analysis can identify intermediate states and deviated pathways. For instance, it can diagnose the causes of differentiation failure by discovering that key enhancers are not open and repair them through small molecule regulation. Meanwhile, non-target lineage cells mixed in can be monitored to provide a basis for purification. In the field of precision medicine, abnormal fateful determination nodes can be identified through single-cell integrated sequencing of biopsy tissues. For instance, in the brain tissues of patients with neurodegenerative diseases, observing the arrest of oligodendrocyte precursors can indicate myelin formation disorders, thereby providing directions for drug intervention. 8 Current Limitations and Future Development Directions scRNA-seq usually fails to detect low-abundance transcripts, which results in the omission of some key regulatory factors, such as low-expressed transcription factors. Meanwhile, scATAC-seq has only several hundred thousand DNA sequencing reads per cell covering the entire genome, resulting in a large number of "zero" signals and random noise. These technical noises increase the difficulty of integration analysis and are prone to false positive or false negative associations. Although methods such as high-load sequencing and cell merging analysis have been developed in recent years to improve the signal-to-noise ratio, the fundamental solution requires innovations in sequencing chemistry and instrumentation. For instance, developing library preparation methods with lower amplification bias or directly reading epigenetic markers using nanopore sequencing may enhance sensitivity and accuracy. Secondly, single-cell multi-omics sequencing is still relatively complex and expensive at present, and the data output rate is not high. In integrative analysis, we usually measure scRNA and scATAC separately and then pair the cells using computational methods. This kind of matching may have incorrect links because different cell patterns do not necessarily correspond one-to-one. Ideally, RNA and ATAC information can be obtained
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