Single-cell Genomics to Understand Disease Pathogenesis

Overview

Journal J Hum Genet

Specialty Genetics

Date 2020 Sep 20

PMID 32951011

Citations 18

Authors

Seitaro Nomura

Affiliations

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Abstract

Cells are minimal functional units in biological phenomena, and therefore single-cell analysis is needed to understand the molecular behavior leading to cellular function in organisms. In addition, omics analysis technology can be used to identify essential molecular mechanisms in an unbiased manner. Recently, single-cell genomics has unveiled hidden molecular systems leading to disease pathogenesis in patients. In this review, I summarize the recent advances in single-cell genomics for the understanding of disease pathogenesis and discuss future perspectives.

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References

Norman T, Horlbeck M, Replogle J, Ge A, Xu A, Jost M . Exploring genetic interaction manifolds constructed from rich single-cell phenotypes. Science. 2019; 365(6455):786-793. PMC: 6746554. DOI: 10.1126/science.aax4438. View

Korsunsky I, Millard N, Fan J, Slowikowski K, Zhang F, Wei K . Fast, sensitive and accurate integration of single-cell data with Harmony. Nat Methods. 2019; 16(12):1289-1296. PMC: 6884693. DOI: 10.1038/s41592-019-0619-0. View

Hill A, McFaline-Figueroa J, Starita L, Gasperini M, Matreyek K, Packer J . On the design of CRISPR-based single-cell molecular screens. Nat Methods. 2018; 15(4):271-274. PMC: 5882576. DOI: 10.1038/nmeth.4604. View

Satterstrom F, Kosmicki J, Wang J, Breen M, De Rubeis S, An J . Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism. Cell. 2020; 180(3):568-584.e23. PMC: 7250485. DOI: 10.1016/j.cell.2019.12.036. View

Macaulay I, Haerty W, Kumar P, Li Y, Hu T, Teng M . G&T-seq: parallel sequencing of single-cell genomes and transcriptomes. Nat Methods. 2015; 12(6):519-22. DOI: 10.1038/nmeth.3370. View

Pei W, Shang F, Wang X, Fanti A, Greco A, Busch K . Resolving Fates and Single-Cell Transcriptomes of Hematopoietic Stem Cell Clones by PolyloxExpress Barcoding. Cell Stem Cell. 2020; 27(3):383-395.e8. DOI: 10.1016/j.stem.2020.07.018. View

Efremova M, Vento-Tormo R, Park J, Teichmann S, James K . Immunology in the Era of Single-Cell Technologies. Annu Rev Immunol. 2020; 38:727-757. DOI: 10.1146/annurev-immunol-090419-020340. View

Jackson H, Fischer J, Zanotelli V, Ali H, Mechera R, Soysal S . The single-cell pathology landscape of breast cancer. Nature. 2020; 578(7796):615-620. DOI: 10.1038/s41586-019-1876-x. View

Skene P, Henikoff J, Henikoff S . Targeted in situ genome-wide profiling with high efficiency for low cell numbers. Nat Protoc. 2018; 13(5):1006-1019. DOI: 10.1038/nprot.2018.015. View

10.

Asp M, Giacomello S, Larsson L, Wu C, Furth D, Qian X . A Spatiotemporal Organ-Wide Gene Expression and Cell Atlas of the Developing Human Heart. Cell. 2019; 179(7):1647-1660.e19. DOI: 10.1016/j.cell.2019.11.025. View

11.

Liu F, Zhang Y, Zhang L, Li Z, Fang Q, Gao R . Systematic comparative analysis of single-nucleotide variant detection methods from single-cell RNA sequencing data. Genome Biol. 2019; 20(1):242. PMC: 6862814. DOI: 10.1186/s13059-019-1863-4. View

12.

Nam A, Kim K, Chaligne R, Izzo F, Ang C, Taylor J . Somatic mutations and cell identity linked by Genotyping of Transcriptomes. Nature. 2019; 571(7765):355-360. PMC: 6782071. DOI: 10.1038/s41586-019-1367-0. View

13.

Markodimitraki C, Rang F, Rooijers K, de Vries S, Chialastri A, de Luca K . Simultaneous quantification of protein-DNA interactions and transcriptomes in single cells with scDam&T-seq. Nat Protoc. 2020; 15(6):1922-1953. PMC: 7779467. DOI: 10.1038/s41596-020-0314-8. View

14.

Li W, Germain R, Gerner M . High-dimensional cell-level analysis of tissues with Ce3D multiplex volume imaging. Nat Protoc. 2019; 14(6):1708-1733. PMC: 8690297. DOI: 10.1038/s41596-019-0156-4. View

15.

Picelli S, Faridani O, Bjorklund A, Winberg G, Sagasser S, Sandberg R . Full-length RNA-seq from single cells using Smart-seq2. Nat Protoc. 2014; 9(1):171-81. DOI: 10.1038/nprot.2014.006. View

16.

Baron C, van Oudenaarden A . Unravelling cellular relationships during development and regeneration using genetic lineage tracing. Nat Rev Mol Cell Biol. 2019; 20(12):753-765. DOI: 10.1038/s41580-019-0186-3. View

17.

Stahl P, Salmen F, Vickovic S, Lundmark A, Fernandez Navarro J, Magnusson J . Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science. 2016; 353(6294):78-82. DOI: 10.1126/science.aaf2403. View

18.

Ueda H, Erturk A, Chung K, Gradinaru V, Chedotal A, Tomancak P . Publisher Correction: Tissue clearing and its applications in neuroscience. Nat Rev Neurosci. 2020; 21(5):298. DOI: 10.1038/s41583-020-0291-5. View

19.

La Manno G, Soldatov R, Zeisel A, Braun E, Hochgerner H, Petukhov V . RNA velocity of single cells. Nature. 2018; 560(7719):494-498. PMC: 6130801. DOI: 10.1038/s41586-018-0414-6. View

20.

Rodriques S, Stickels R, Goeva A, Martin C, Murray E, Vanderburg C . Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution. Science. 2019; 363(6434):1463-1467. PMC: 6927209. DOI: 10.1126/science.aaw1219. View