Evidence map›Paper›PMID 40488964›Full record

ArticleMolecular biotechnology2026

Integrative Single-Cell and Spatial Transcriptomics Reveal Functional and Spatial Heterogeneity of Atrial and Ventricular Cardiomyocytes in the Heart.

Lizhi Cao, Rui Chang, Xiaoying Wang, Junwei Shen, Zhifang Yang, Linlin Ma, Yanfei Li

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Article in Molecular biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Lizhi Cao *Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.
Rui Chang *School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.
Xiaoying Wang *Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.
Junwei ShenSchool of Life Sciences and Technology, Tongji University, Shanghai, China.
Zhifang YangShanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China. yangzf@sumhs.edu.cn.
Linlin MaShanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China. linlinma1986@gmail.com.
Yanfei LiShanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China. liyf@sumhs.edu.cn.ORCID http://orcid.org/0009-0007-2524-1782

Funding

Natural Science Foundation of Shanghai 21ZR1428400Shanghai Medical Science and Technology Support Project 21S11901700
6 · The paper itself

Abstract

Cardiomyocytes, pivotal for heart contractility, are categorized into atrial (aCM) and ventricular (vCM) subtypes, each playing distinct roles in modulating blood flow, electrical signal conduction, pump function, and energy metabolism. Recent advancements in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics have enhanced our understanding of cellular heterogeneity and intercellular communication within cardiac tissues. This study integrates scRNA-seq with spatial mapping to elucidate the spatial distribution and intercellular communication of aCM and vCM, focusing on their roles in energy metabolism, pump function, and regulatory functions. We performed scRNA-seq on isolated cardiac cells, followed by data normalization, PCA, and t-SNE clustering, identifying distinct cardiomyocyte subclusters. Ligand-receptor interaction analyses were conducted to explore cellular communication networks, and annotated single-cell data were projected onto heart tissue sections using spatial transcriptomics. Our results revealed distinct spatial distributions: vCM subclusters (vCM-1, vCM-2, vCM-3) predominantly occupied ventricular regions, while aCM subclusters (aCM-1, aCM-2) were primarily located in atrial regions with an increased presence of fibroblasts near atria. Igf2-Igf2r and Vegfb-Vegfr1 mediated communications were prominent in both regions, with extensive interactions between aCM-2 and vCM subclusters. This integration of scRNA-seq and spatial transcriptomics provides a comprehensive overview of cardiac tissue organization and intercellular communication, elucidating critical roles of vCM in energy metabolism and pump function, and aCM in regulating blood flow and electrical conduction. Understanding these interactions in anatomical context enhances our grasp of cardiac function complexity and identifies new therapeutic targets for cardiac diseases.

Indexed as

Heart AtriaHeart VentriclesMyocytes, CardiacSingle-Cell AnalysisTranscriptomeAnimalsCell CommunicationGene Expression ProfilingMaleMiceSequence Analysis, RNACardiomyocytesIntercellular communicationSingle-cell RNA sequencingSpatial transcriptomics

Identifiers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.