Single Cell Gene Expression to Understand the Dynamic Architecture of the Heart
Autor: | Michela Noseda, Sara Samari, Kerstin B. Meyer, Ricardo J. Miragaia, Patricia Chaves, Andrea Massaia, Sarah A. Teichmann |
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Přispěvatelé: | Teichmann, Sarah [0000-0002-6294-6366], Apollo - University of Cambridge Repository |
Jazyk: | angličtina |
Rok vydání: | 2018 |
Předmět: |
0301 basic medicine
RNA-SEQUENCING DATA lcsh:Diseases of the circulatory (Cardiovascular) system Cardiac & Cardiovascular Systems Computer science Cell Gene regulatory network RNA-Seq Review Computational biology heart Cardiovascular Medicine cellular landscape Transcriptome SIGNALING PATHWAYS NORMALIZATION 03 medical and health sciences transcriptomics QUALITY-CONTROL Complementary DNA Gene expression medicine HETEROGENEITY Gene Science & Technology SEQ DATA qRT-PCR TRANSCRIPTOMICS REVEALS 3. Good health single cell DIFFUSION MAPS 030104 developmental biology Workflow medicine.anatomical_structure MYOCARDIAL-INFARCTION lcsh:RC666-701 Cardiovascular System & Cardiology gene expression RNA-seq Cardiology and Cardiovascular Medicine Life Sciences & Biomedicine STEM-CELLS |
Zdroj: | Frontiers in Cardiovascular Medicine, Vol 5 (2018) Frontiers in Cardiovascular Medicine |
Popis: | 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. |
Databáze: | OpenAIRE |
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