This review provides a physiology-centered blueprint for applying single-cell RNA sequencing, single-nucleus RNA sequencing, and spatial transcriptomics to non-model species and critically evaluates dissociation and preservation bias, genome annotation, seasonal and ecological variation, biological replication, pseudoreplication, cross-species integration, and spatial resolution.
This manuscript explores the current landscape of single-cell RNA sequencing (scRNA-seq), highlighting key studies that have leveraged this technology to advance biological understanding for clinical purposes through the construction of gene regulatory networks (GRNs) from single-cell transcriptomic data.
J. López-Castiblanco, L. López-Kleine, Yesid Cuesta-Astroz· Journal of Investigative Med...· 0 citations
How spatially structured cellular ecosystems, rather than individual cell types, determine therapeutic response and resistance in lung cancer is organized around a single question - and observations that are reproducible across independent cohorts and platforms are explicitly separate from those that remain confined to...
C. Braicu, R. Pîrlog, A. Nutu et al.· Biochimica et biophysica act...· 0 citations
Single-cell technologies enable epigenomics characterization at single-cell resolution, offering novel insights into gene expression regulation and a wide range of biological processes, including cell fate determination, developmental differentiation, and environmental adaptation. In recent years, plant single-cell epi...
Cheng Tong, Chao-Fan Liu, Zhe Liang et al.· The Plant Cell· 0 citations
This review synthesizes recent progress across diverse plant species and tissues, showing that gene expression is not only cell-type specific but also tightly organized by position within organs and developmental niches, establishing spatial gene expression as a fundamental organizing principle of plant development and...
Yiqing Wang, Zhengzhi Tan, Nicole A Freeman et al.· Plant Communications· 0 citations
Cell-cell communication (CCC) is involved in regulating cellular behavior in tissues. Spatial transcriptomics adds local context to gene expression, enabling more biologically grounded CCC inference than single-cell RNA-seq alone. Rapid method development has yielded diverse CCC methods, each addressing distinct biolog...
Zlatka Fischer, Katharina Imkeller, Marcel H. Schulz et al.· Trends in Genetics· 2 citations
Imaging-based spatial transcriptomics provides single-cell resolution, but remains limited to targeted gene panels, leaving much of the transcriptome and cellular-state variation unobserved. Existing approaches infer unmeasured genes primarily through transcriptional alignment between spatial and reference datasets, wh...
Shi-Tong Yang, Pai Peng, Hui-Feng He et al.· Nature Communications· 0 citations
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