Toward uncharted territory of cellular heterogeneity: advances and applications of single-cell RNA-seq

Brandon Lieberman, Meena Kusi, Chia Nung Hung, Chih Wei Chou, Ning He, Yen Yi Ho, Josephine A. Taverna, Tim H.M. Huang, Chun Liang Chen

Research output: Contribution to journalReview articlepeer-review

4 Scopus citations

Abstract

Among single-cell analysis technologies, single-cell RNA-seq (scRNA-seq) has been one of the front runners in technical inventions. Since its induction, scRNA-seq has been well received and undergone many fast-paced technical improvements in cDNA synthesis and amplification, processing and alignment of next generation sequencing reads, differentially expressed gene calling, cell clustering, subpopulation identification, and developmental trajectory prediction. scRNA-seq has been exponentially applied to study global transcriptional profiles in all cell types in humans and animal models, healthy or with diseases, including cancer. Accumulative novel subtypes and rare subpopulations have been discovered as potential underlying mechanisms of stochasticity, differentiation, proliferation, tumorigenesis, and aging. scRNA-seq has gradually revealed the uncharted territory of cellular heterogeneity in transcriptomes and developed novel therapeutic approaches for biomedical applications. This review of the advancement of scRNA-seq methods provides an exploratory guide of the quickly evolving technical landscape and insights of focused features and strengths in each prominent area of progress.

Original languageEnglish (US)
Pages (from-to)1-21
Number of pages21
JournalJournal of Translational Genetics and Genomics
Volume5
Issue number1
DOIs
StatePublished - 2021

Keywords

  • Single-cell RNA-seq
  • cancer
  • dimensional reduction
  • diseases
  • heterogeneity
  • high throughput
  • multiplexing
  • transcriptome

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

Fingerprint

Dive into the research topics of 'Toward uncharted territory of cellular heterogeneity: advances and applications of single-cell RNA-seq'. Together they form a unique fingerprint.

Cite this