Single-cell transcriptomics is an advanced genomic technique that enables the precise quantification of gene expression at the level of individual cells. Unlike traditional bulk RNA sequencing (which reflects the average state of cell populations), this technology deciphers the molecular characteristics, dynamic interactions, and functional states of cellular subpopulations within complex biological systems, providing unprecedented resolution for life sciences research.
This technology has broad and transformative applications:
o In-Depth Analysis of Disease Mechanisms: By dissecting transcriptomic changes at single-cell resolution, researchers can identify rare cell populations in driving diseases, map spatiotemporal dynamics of disease progression (e.g., microenvironment evolution, clonal evolution of treatment resistance), and uncover cellular mechanisms underlying complex conditions such as cancer, autoimmune diseases, and neurodegenerative disorders.
o Paradigm Shift in Cell Biology: Single-cell transcriptomics deciphers lineage differentiation trajectories and cell-state transitions during development/regeneration, and deepens our understanding of cellular heterogeneity, lineage tracing, and cell fate decisions during development, regeneration, and tissue homeostasis.
o Translational Applications in Precision Medicine: The insights gained from single-cell data enable the discovery of novel biomarkers, refined patient stratification, and the development of targeted therapies, moving healthcare towards highly personalized treatment strategies.
Overall, single-cell transcriptomics is not only expanding our fundamental knowledge of biology but also driving innovation in diagnostics and therapeutic interventions across a wide range of medical fields.
Focus Areas for Submissions
We invite original research and review articles that leverage single-cell transcriptomics to advance understanding in the following key areas:
I. Fundamental Biological Insights
Cellular Heterogeneity & Dynamics
a. Single-cell characterization of rare cell populations (stem cells, tissue-resident subsets)
b. Lineage tracing and differentiation trajectories
c. Cell-state transitions during development and regeneration
d. Transcriptional noise and cellular plasticity mechanisms
Disease Pathogenesis
a. Identification of disease-driving cell subpopulations
b. Spatiotemporal mapping of disease progression
c. Microenvironment evolution and cell-cell interactions
d. Clonal dynamics in cancer and other disorders
II. Clinical Translation Perspective
a. Early detection and diagnostic signatures
b. Discovery of cell-type specific biomarkers
c. Patient stratification strategies
d. Molecular subtyping approaches
e. Therapeutic Advancements
g. Resistance mechanism elucidation
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Case Report
Data Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
General Commentary
Hypothesis and Theory
Methods
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.