Abstract
The recent development of single cell gene expression technologies, and especially single cell transcriptomics, have revolutionized the way biologists and clinicians investigate organs and organisms, allowing an unprecedented level of resolution to the description of cell demographics in both healthy and diseased states. Single cell transcriptomics provide information on prevalence, heterogeneity, and gene co-expression at the individual cell level. This enables a cell-centric outlook to define intracellular gene regulatory networks and to bridge toward the definition of intercellular pathways otherwise masked in bulk analysis. The technologies have developed at a fast pace producing a multitude of different approaches, with several alternatives to choose from at any step, including single cell isolation and capturing, lysis, RNA reverse transcription and cDNA amplification, library preparation, sequencing, and computational analyses. Here, we provide guidelines for the experimental design of single cell RNA sequencing experiments, exploring the current options for the crucial steps. Furthermore, we provide a complete overview of the typical data analysis workflow, from handling the raw sequencing data to making biological inferences. Significantly, advancements in single cell transcriptomics have already contributed to outstanding exploratory and functional studies of cardiac development and disease models, as summarized in this review. In conclusion, we discuss achievable outcomes of single cell transcriptomics' applications in addressing unanswered questions and influencing future cardiac clinical applications.
Highlights
Each single cell of our body has a unique position in space and time and is, exposed to a unique set of specific signals and stimuli
The first single cell gene expression studies on the heart relied on single cell Quantitative Real Time polymerase chain reaction (PCR) (qRT-PCR) and scRNA-seq studies lagged for a few years [24, 25]
The initial work focusing on cardiac development as well as adult heart demonstrated feasibility with some useful explorative studies and more recent ones proving the unique value of single cell studies in identifying pathways’ dysregulation in disease models [26,27,28,29]
Summary
Each single cell of our body has a unique position in space and time and is, exposed to a unique set of specific signals and stimuli. Single-cell gene expression analysis started with the development of methods to study targeted transcripts including quantitative RT-PCR [1,2,3] and single-molecule FISH that allows to maintain the spatial information [4,5,6,7]. We provide a detailed overview of the practicalities to design single cell RNA-seq or targeted gene expression experiments, and discuss methods including computational analysis; in the second part we cover the advancements brought by these new technologies in the cardiac field, the foreseeable successes in resolving ambiguities of heart biology and the potential applications in clinical settings. EXPERIMENTAL AND COMPUTATIONAL APPROACHES FOR SINGLE CELL GENE EXPRESSION ANALYSIS
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