Korean J Physiol Pharmacol 2024; 28(5): 403-411
Published online September 1, 2024 https://doi.org/10.4196/kjpp.2024.28.5.403
Copyright © Korean J Physiol Pharmacol.
Doyeong Kim, Seonghun Jeong, and Sang-Min Park*
College of Pharmacy, Chungnam National University, Daejeon 34134, Korea
Correspondence to:Sang-Min Park
E-mail: smpark@cnu.ac.kr
Author contributions: S.M.P. supervised the study. D.K., S.J., and S.M.P. wrote the manuscript. D.K. and S.M.P. revised the manuscript.
The global spread of flaviviruses has triggered major outbreaks worldwide, significantly impacting public health, society, and economies. This has intensified research efforts to understand how flaviviruses interact with their hosts and manipulate the immune system, underscoring the need for advanced research tools. RNA-sequencing (RNA-seq) technologies have revolutionized our understanding of flavivirus infections by offering transcriptome analysis to dissect the intricate dynamics of virus-host interactions. Bulk RNA-seq provides a macroscopic overview of gene expression changes in virus-infected cells, offering insights into infection mechanisms and host responses at the molecular level. Single-cell RNA sequencing (scRNAseq) provides unprecedented resolution by analyzing individual infected cells, revealing remarkable cellular heterogeneity within the host response. A particularly innovative advancement, virus-inclusive single-cell RNA sequencing (viscRNA-seq), addresses the challenges posed by non-polyadenylated flavivirus genomes, unveiling intricate details of virus-host interactions. In this review, we discuss the contributions of bulk RNA-seq, scRNA-seq, and viscRNA-seq to the field, exploring their implications in cell line experiments and studies on patients infected with various flavivirus species. Comprehensive transcriptome analyses from RNA-seq technologies are pivotal in accelerating the development of effective diagnostics and therapeutics, paving the way for innovative treatments and enhancing our preparedness for future outbreaks.
Keywords: Gene expression profiling, Infections, Single-cell analysis, Viruses
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