Integration of Single-cell Transcriptome and Chromatin Accessibility and Its Application on Tumor Investigation

Overview

Journal Life Med

Date 2025 Jan 28

PMID 39872661

Authors

Chunyuan Yang

Yan Jin

Yuxin Yin

Affiliations

Soon will be listed here.

Abstract

The advent of single-cell sequencing techniques has not only revolutionized the investigation of biological processes but also significantly contributed to unraveling cellular heterogeneity at unprecedented levels. Among the various methods, single-cell transcriptome sequencing stands out as the best established, and has been employed in exploring many physiological and pathological activities. The recently developed single-cell epigenetic sequencing techniques, especially chromatin accessibility sequencing, have further deepened our understanding of gene regulatory networks. In this review, we summarize the recent breakthroughs in single-cell transcriptome and chromatin accessibility sequencing methodologies. Additionally, we describe current bioinformatic strategies to integrate data obtained through these single-cell sequencing methods and highlight the application of this analysis strategy on a deeper understanding of tumorigenesis and tumor progression. Finally, we also discuss the challenges and anticipated developments in this field.

References

Buenrostro J, Wu B, Litzenburger U, Ruff D, Gonzales M, Snyder M . Single-cell chromatin accessibility reveals principles of regulatory variation. Nature. 2015; 523(7561):486-90. PMC: 4685948. DOI: 10.1038/nature14590. View

Rubin A, Parker K, Satpathy A, Qi Y, Wu B, Ong A . Coupled Single-Cell CRISPR Screening and Epigenomic Profiling Reveals Causal Gene Regulatory Networks. Cell. 2018; 176(1-2):361-376.e17. PMC: 6329648. DOI: 10.1016/j.cell.2018.11.022. View

Xing Q, El Farran C, Zeng Y, Yi Y, Warrier T, Gautam P . Parallel bimodal single-cell sequencing of transcriptome and chromatin accessibility. Genome Res. 2020; 30(7):1027-1039. PMC: 7397874. DOI: 10.1101/gr.257840.119. View

Grosselin K, Durand A, Marsolier J, Poitou A, Marangoni E, Nemati F . High-throughput single-cell ChIP-seq identifies heterogeneity of chromatin states in breast cancer. Nat Genet. 2019; 51(6):1060-1066. DOI: 10.1038/s41588-019-0424-9. View

Chen G, Gong T, Wang Z, Wang Z, Lin X, Chen S . Colorectal cancer organoid models uncover oxaliplatin-resistant mechanisms at single cell resolution. Cell Oncol (Dordr). 2022; 45(6):1155-1167. DOI: 10.1007/s13402-022-00705-5. View

Wu K, Lin K, Li X, Yuan X, Xu P, Ni P . Redefining Tumor-Associated Macrophage Subpopulations and Functions in the Tumor Microenvironment. Front Immunol. 2020; 11:1731. PMC: 7417513. DOI: 10.3389/fimmu.2020.01731. View

Jia Q, Chu H, Jin Z, Long H, Zhu B . High-throughput single-сell sequencing in cancer research. Signal Transduct Target Ther. 2022; 7(1):145. PMC: 9065032. DOI: 10.1038/s41392-022-00990-4. View

Xu K, Zhang W, Wang C, Hu L, Wang R, Wang C . Integrative analyses of scRNA-seq and scATAC-seq reveal CXCL14 as a key regulator of lymph node metastasis in breast cancer. Hum Mol Genet. 2021; 30(5):370-380. DOI: 10.1093/hmg/ddab042. View

AlKhafaji A, Smith J, Garimella K, Babadi M, Popic V, Sade-Feldman M . High-throughput RNA isoform sequencing using programmed cDNA concatenation. Nat Biotechnol. 2023; 42(4):582-586. DOI: 10.1038/s41587-023-01815-7. View

10.

Long Z, Sun C, Tang M, Wang Y, Ma J, Yu J . Single-cell multiomics analysis reveals regulatory programs in clear cell renal cell carcinoma. Cell Discov. 2022; 8(1):68. PMC: 9296597. DOI: 10.1038/s41421-022-00415-0. View

11.

Rautenstrauch P, Vlot A, Saran S, Ohler U . Intricacies of single-cell multi-omics data integration. Trends Genet. 2021; 38(2):128-139. DOI: 10.1016/j.tig.2021.08.012. View

12.

Stuart T, Srivastava A, Madad S, Lareau C, Satija R . Single-cell chromatin state analysis with Signac. Nat Methods. 2021; 18(11):1333-1341. PMC: 9255697. DOI: 10.1038/s41592-021-01282-5. View

13.

Gonzalez-Blas C, De Winter S, Hulselmans G, Hecker N, Matetovici I, Christiaens V . SCENIC+: single-cell multiomic inference of enhancers and gene regulatory networks. Nat Methods. 2023; 20(9):1355-1367. PMC: 10482700. DOI: 10.1038/s41592-023-01938-4. View

14.

Foster D, Januszyk M, Delitto D, Yost K, Griffin M, Guo J . Multiomic analysis reveals conservation of cancer-associated fibroblast phenotypes across species and tissue of origin. Cancer Cell. 2022; 40(11):1392-1406.e7. PMC: 9669239. DOI: 10.1016/j.ccell.2022.09.015. View

15.

Sharma A, Seow J, Dutertre C, Pai R, Bleriot C, Mishra A . Onco-fetal Reprogramming of Endothelial Cells Drives Immunosuppressive Macrophages in Hepatocellular Carcinoma. Cell. 2020; 183(2):377-394.e21. DOI: 10.1016/j.cell.2020.08.040. View

16.

Fan H, Fu G, Fodor S . Expression profiling. Combinatorial labeling of single cells for gene expression cytometry. Science. 2015; 347(6222):1258367. DOI: 10.1126/science.1258367. View

17.

Wu X, Lu M, Yun D, Gao S, Chen S, Hu L . Single-cell ATAC-Seq reveals cell type-specific transcriptional regulation and unique chromatin accessibility in human spermatogenesis. Hum Mol Genet. 2021; 31(3):321-333. DOI: 10.1093/hmg/ddab006. View

18.

Granja J, Corces M, Pierce S, Bagdatli S, Choudhry H, Chang H . ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis. Nat Genet. 2021; 53(3):403-411. PMC: 8012210. DOI: 10.1038/s41588-021-00790-6. View

19.

Cao K, Hong Y, Wan L . Manifold alignment for heterogeneous single-cell multi-omics data integration using Pamona. Bioinformatics. 2021; 38(1):211-219. PMC: 8696097. DOI: 10.1093/bioinformatics/btab594. View

20.

Ameen M, Sundaram L, Shen M, Banerjee A, Kundu S, Nair S . Integrative single-cell analysis of cardiogenesis identifies developmental trajectories and non-coding mutations in congenital heart disease. Cell. 2022; 185(26):4937-4953.e23. PMC: 10122433. DOI: 10.1016/j.cell.2022.11.028. View