Single-Cell Gene Expression Profiling: Cell-Level Biology by Multiplexed Expression Fluorescence in Situ Hybridization

2011 ◽  
Keyword(s):  
Gene Expression ◽  
In Situ Hybridization ◽  
Fluorescence In Situ Hybridization ◽  
Single Cell ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Cell Level ◽  
Cell Gene Expression ◽  
Cell Gene

Single-Cell Gene Expression Profiling

Science ◽  
2002 ◽  
Vol 297 (5582) ◽  
pp. 836-840 ◽  
Author(s):  
J. M. Levsky
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Cell Gene Expression ◽  
Cell Gene

scholarly journals In situelectro-sequencing in three-dimensional tissues

2021 ◽  
Author(s):  
Qiang Li ◽  
Zuwan Lin ◽  
Ren Liu ◽  
Xin Tang ◽  
Jiahao Huang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Three Dimensional ◽  
Cell Types ◽  
Developmental Trajectory ◽  
Single Cell Level ◽  
Cell Level ◽  
Cell Gene Expression ◽  
Cell Gene

AbstractPairwise mapping of single-cell gene expression and electrophysiology in intact three-dimensional (3D) tissues is crucial for studying electrogenic organs (e.g., brain and heart)1–5. Here, we introducein situelectro-sequencing (electro-seq), combining soft bioelectronics within situRNA sequencing to stably map millisecond-timescale cellular electrophysiology and simultaneously profile a large number of genes at single-cell level across 3D tissues. We appliedin situelectro-seq to 3D human induced pluripotent stem cell-derived cardiomyocyte (hiPSC-CM) patches, precisely registering the CM gene expression with electrophysiology at single-cell level, enabling multimodalin situanalysis. Such multimodal data integration substantially improved the dissection of cell types and the reconstruction of developmental trajectory from spatially heterogeneous tissues. Using machine learning (ML)-based cross-modal analysis,in situelectro-seq identified the gene-to-electrophysiology relationship over the time course of cardiac maturation. Further leveraging such a relationship to train a coupled autoencoder, we demonstrated the prediction of single-cell gene expression profile evolution using long-term electrical measurement from the same cardiac patch or 3D millimeter-scale cardiac organoids. As exemplified by cardiac tissue maturation,in situelectro-seq will be broadly applicable to create spatiotemporal multimodal maps and predictive models in electrogenic organs, allowing discovery of cell types and gene programs responsible for electrophysiological function and dysfunction.

scholarly journals Classification of Midbrain Dopamine Neurons Using Single-Cell Gene Expression Profiling Approaches

2020 ◽  
Vol 43 (3) ◽  
pp. 155-169 ◽  
Author(s):  
Jean-Francois Poulin ◽  
Zachary Gaertner ◽  
Oscar Andrés Moreno-Ramos ◽  
Rajeshwar Awatramani
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Dopamine Neurons ◽  
Cell Gene Expression ◽  
Midbrain Dopamine ◽  
Cell Gene ◽  
Midbrain Dopamine Neurons
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