LIVIVO - The Search Portal for Life Sciences

zur deutschen Oberfläche wechseln
Advanced search

Search results

Result 1 - 1 of total 1

Search options

Article ; Online: Breathing fresh air into respiratory research with single-cell RNA sequencing.

Alexander, Michael J / Budinger, G R Scott / Reyfman, Paul A

European respiratory review : an official journal of the European Respiratory Society

2020  Volume 29, Issue 156

Abstract: ... cell RNA sequencing (scRNA-seq) provides a robust, unbiased survey of the transcriptome comparable ... to bulk RNA sequencing while preserving information on cellular heterogeneity. In just a few years ... the evolution of single-cell technologies with a focus on spatial and multi-omics approaches that promise ...

Abstract The complex cellular heterogeneity of the lung poses a unique challenge to researchers in the field. While the use of bulk RNA sequencing has become a ubiquitous technology in systems biology, the technique necessarily averages out individual contributions to the overall transcriptional landscape of a tissue. Single-cell RNA sequencing (scRNA-seq) provides a robust, unbiased survey of the transcriptome comparable to bulk RNA sequencing while preserving information on cellular heterogeneity. In just a few years since this technology was developed, scRNA-seq has already been adopted widely in respiratory research and has contributed to impressive advancements such as the discoveries of the pulmonary ionocyte and of a profibrotic macrophage population in pulmonary fibrosis. In this review, we discuss general technical considerations when considering the use of scRNA-seq and examine how leading investigators have applied the technology to gain novel insights into respiratory biology, from development to disease. In addition, we discuss the evolution of single-cell technologies with a focus on spatial and multi-omics approaches that promise to drive continued innovation in respiratory research.
MeSH term(s) Computational Biology/methods ; Gene Expression Profiling ; Humans ; Lung Diseases/genetics ; Pulmonary Medicine/trends ; Sequence Analysis, RNA/methods ; Single-Cell Analysis/methods ; Transcriptome
Keywords covid19
Language English
Publishing date 2020-07-03
Publishing country England
Document type Journal Article ; Review
ZDB-ID 1077620-5
ISSN 1600-0617 ; 0905-9180
ISSN (online) 1600-0617
ISSN 0905-9180
DOI 10.1183/16000617.0060-2020
Shelf mark
Zs.A 3265: Show issues Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)
Database MEDical Literature Analysis and Retrieval System OnLINE

More links

Kategorien

To top