Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2021 Jan;66(1):75-84.
doi: 10.1038/s10038-020-00844-3. Epub 2020 Sep 19.

Single-cell genomics to understand disease pathogenesis

Seitaro Nomura  1
Affiliations
Review

Single-cell genomics to understand disease pathogenesis

Seitaro Nomura. J Hum Genet. 2021 Jan.

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.

PubMed Disclaimer

Conflict of interest statement

The author declare no conflict of interets.

Figures

Fig. 1
Fig. 1
Overview of single-cell genomics to understand disease pathogenesis.
See this image and copyright information in PMC

References

    1. See K, Tan WLW, Lim EH, et al. Single cardiomyocyte nuclear transcriptomes reveal a lincRNA-regulated de-differentiation and cell cycle stress-response in vivo. Nat Commun. 2017;8:225. doi: 10.1038/s41467-017-00319-8. - DOI - PMC - PubMed
    1. Picelli S, Björklund ÅK, Faridani OR, Sagasser S, Winberg G, Sandberg R. Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat Methods. 2013;10:1096–8. doi: 10.1038/nmeth.2639. - DOI - PubMed
    1. Picelli S, Faridani OR, Björklund AK, Winberg G, Sagasser S, Sandberg R. Full-length RNA-seq from single cells using Smart-seq2. Nat Protoc. 2014;9:171–81. doi: 10.1038/nprot.2014.006. - DOI - PubMed
    1. Nomura S, Satoh M, Fujita T, et al. Cardiomyocyte gene programs encoding morphological and functional signatures in cardiac hypertrophy and failure. Nat Commun. 2018;9:4435. doi: 10.1038/s41467-018-06639-7. - DOI - PMC - PubMed
    1. Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinforma. 2008;9:559. doi: 10.1186/1471-2105-9-559. - DOI - PMC - PubMed

LinkOut - more resources