Integrating single-cell transcriptomics with cellular phenotypes: cell morphology, Ca2+ imaging and electrophysiology

Abstract

I review recent technological advancements in coupling single-cell transcriptomics with cellular phenotypes including morphology, calcium signaling, and electrophysiology. Single-cell RNA sequencing (scRNAseq) has revolutionized cell type classifications by capturing the transcriptional diversity of cells. A new wave of methods to integrate scRNAseq and biophysical measurements is facilitating the linkage of transcriptomic data to cellular function, which provides physiological insight into cellular states. I briefly discuss critical factors of these phenotypical characterizations such as timescales, information content, and analytical tools. Dedicated sections focus on the integration with cell morphology, calcium imaging, and electrophysiology (patch-seq), emphasizing their complementary roles. I discuss their application in elucidating cellular states, refining cell type classifications, and uncovering functional differences in cell subtypes. To illustrate the practical applications and benefits of these methods, I highlight their use in tissues with excitable cell-types such as the brain, pancreatic islets, and the retina. The potential of combining functional phenotyping with spatial transcriptomics for a detailed mapping of cell phenotypes in situ is explored. Finally, I discuss open questions and future perspectives, emphasizing the need for a shift towards broader accessibility through increased throughput.

Gene Expression, Morphology, and Electrophysiology During the Dynamic Development of Human Induced Pluripotent Stem Cell-Derived Atrial- and Ventricular-Like Cardiomyocytes [Letter]

“… 1 The authors employ a small molecule-based approach to modulate retinoic acid and bone morphogenetic protein signaling pathways during differentiation. Their comprehensive assessment, integrating gene expression, morphology, and electrophysiological function, 2 offers valuable insights into the maturation process of these cell types. A key strength of this work lies in its multifaceted approach.…”

Integration of hyperspectral imaging and transcriptomics from individual cells with HyperSeq

“…While major breakthroughs have been achieved on increasing throughput of scRNA-Seq and related technologies to thousands [6][7][8][9] and sometimes millions 9,10 of cells and to integrate distinct omic modalities into a single experiment (e.g. CITE-Seq 11 , scATAC+scRNA-Seq 12 ), progress in combining omics with additional, complementary measurements from the same cell has been more limited [13][14][15][16] . Multimodal characterisation of individual cells would benefit biomedical applications including cancer and infectious disease, given that both malignant and virusinfected cells can be genetically 17 , transcriptionally 18 , and metabolically 19 diverse within a single culture.…”