Understanding the Adult Mammalian Heart at Single-Cell RNA-Seq Resolution

被引:12
|
作者
Marin-Sedeno, Ernesto [1 ,2 ]
Martinez de Morentin, Xabier [3 ]
Perez-Pomares, Jose M. [1 ,2 ]
Gomez-Cabrero, David [3 ,4 ,5 ]
Ruiz-Villalba, Adrian [1 ,2 ]
机构
[1] Univ Malaga, Fac Sci, Inst Malagueno Biomed, Dept Anim Biol, Malaga, Spain
[2] Univ Malaga, Ctr Andaluz Nanomed & Biotecnol, Junta Andalucia, BIONAND, Malaga, Spain
[3] Univ Publ Navarra, Complejo Hosp Navarra, Inst Invest Sanitaria Navarra IdiSNA, Traslat Bioinformat Unit, Pamplona, Spain
[4] Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London, England
[5] King Abdullah Univ Sci & Technol, Biol & Environm Sci & Engn Div, Thuwal, Saudi Arabia
来源
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY | 2021年 / 9卷
关键词
single-cell RNAseq; heart; infarction; cardiac cell heterogeneity; transcriptomics; RESIDENT CARDIAC MACROPHAGES; SMOOTH-MUSCLE-CELLS; MYOCARDIAL-INFARCTION; ENDOTHELIAL-CELLS; DENDRITIC CELLS; T-CELLS; PHENOTYPIC HETEROGENEITY; SEQUENCING ANALYSIS; CORONARY-ARTERIES; CONDUCTION SYSTEM;
D O I
10.3389/fcell.2021.645276
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
During the last decade, extensive efforts have been made to comprehend cardiac cell genetic and functional diversity. Such knowledge allows for the definition of the cardiac cellular interactome as a reasonable strategy to increase our understanding of the normal and pathologic heart. Previous experimental approaches including cell lineage tracing, flow cytometry, and bulk RNA-Seq have often tackled the analysis of cardiac cell diversity as based on the assumption that cell types can be identified by the expression of a single gene. More recently, however, the emergence of single-cell RNA-Seq technology has led us to explore the diversity of individual cells, enabling the cardiovascular research community to redefine cardiac cell subpopulations and identify relevant ones, and even novel cell types, through their cell-specific transcriptomic signatures in an unbiased manner. These findings are changing our understanding of cell composition and in consequence the identification of potential therapeutic targets for different cardiac diseases. In this review, we provide an overview of the continuously changing cardiac cellular landscape, traveling from the pre-single-cell RNA-Seq times to the single cell-RNA-Seq revolution, and discuss the utilities and limitations of this technology.
引用
收藏
页数:22
相关论文
共 50 条
  • [41] Single-cell RNA-seq reveals the transcriptional landscape in ischemic stroke
    Zheng, Kai
    Lin, Lingmin
    Jiang, Wei
    Chen, Lin
    Zhang, Xiyue
    Zhang, Qian
    Ren, Yi
    Hao, Junwei
    JOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISM, 2022, 42 (01) : 56 - 73
  • [42] Impact of similarity metrics on single-cell RNA-seq data clustering
    Kim, Taiyun
    Chen, Irene Rui
    Lin, Yingxin
    Wang, Andy Yi-Yang
    Yang, Jean Yee Hwa
    Yang, Pengyi
    BRIEFINGS IN BIOINFORMATICS, 2019, 20 (06) : 2316 - 2326
  • [43] Integrated analysis of single-cell RNA-seq and bulk RNA-seq unravels the heterogeneity of cancer-associated fibroblasts in TNBC
    Wu, Xiaoqing
    Lu, Wenping
    Zhang, Weixuan
    Zhang, Dongni
    Mei, Heting
    Zhang, Mengfan
    Cui, Yongjia
    Zhuo, Zhili
    AGING-US, 2023, 15 (21): : 12674 - 12697
  • [44] Combined single-cell RNA-seq and bulk RNA-seq to analyze the expression and role of TREM2 in bladder cancer
    Zhang, Xingxing
    Du, Yuelin
    Xiong, Wei
    Shang, Panfeng
    MEDICAL ONCOLOGY, 2022, 40 (01)
  • [45] CEL-Seq2: sensitive highly-multiplexed single-cell RNA-Seq
    Hashimshony, Tamar
    Senderovich, Naftalie
    Avital, Gal
    Klochendler, Agnes
    de Leeuw, Yaron
    Anavy, Leon
    Gennert, Dave
    Li, Shuqiang
    Livak, Kenneth J.
    Rozenblatt-Rosen, Orit
    Dor, Yuval
    Regev, Aviv
    Yanai, Itai
    GENOME BIOLOGY, 2016, 17
  • [46] Systematic comparison of high-throughput single-cell RNA-seq methods for immune cell profiling
    Tracy M. Yamawaki
    Daniel R. Lu
    Daniel C. Ellwanger
    Dev Bhatt
    Paolo Manzanillo
    Vanessa Arias
    Hong Zhou
    Oh Kyu Yoon
    Oliver Homann
    Songli Wang
    Chi-Ming Li
    BMC Genomics, 22
  • [47] Current annotation strategies for T cell phenotyping of single-cell RNA-seq data
    Mullan, Kerry A.
    de Vrij, Nicky
    Valkiers, Sebastiaan
    Meysman, Pieter
    FRONTIERS IN IMMUNOLOGY, 2023, 14
  • [48] scReClassify: post hoc cell type classification of single-cell rNA-seq data
    Kim, Taiyun
    Lo, Kitty
    Geddes, Thomas A.
    Kim, Hani Jieun
    Yang, Jean Yee Hwa
    Yang, Pengyi
    BMC GENOMICS, 2019, 20 (Suppl 9)
  • [49] scReClassify: post hoc cell type classification of single-cell rNA-seq data
    Taiyun Kim
    Kitty Lo
    Thomas A. Geddes
    Hani Jieun Kim
    Jean Yee Hwa Yang
    Pengyi Yang
    BMC Genomics, 20
  • [50] Feature Selection in Single-Cell RNA-seq Data via a Genetic Algorithm
    Chatzilygeroudis, Konstantinos I.
    Vrahatis, Aristidis G.
    Tasoulis, Sotiris K.
    Vrahatis, Michael N.
    LEARNING AND INTELLIGENT OPTIMIZATION, LION 15, 2021, 12931 : 66 - 79