Single-cell transcriptional landscape of long non-coding RNAs orchestrating mouse heart development
Long non-coding RNAs (lncRNAs) comprise the most representative transcriptional units of the mammalian genome. They are associated with organ development linked with the emergence of cardiovascular diseases. We used bioinformatic approaches, machine learning algorithms, systems biology analyses, and...
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| Published in | Cell death & disease Vol. 14; no. 12; pp. 841 - 13 |
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| Main Authors | , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
18.12.2023
Springer Nature B.V Nature Publishing Group |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2041-4889 2041-4889 |
| DOI | 10.1038/s41419-023-06296-9 |
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| Abstract | Long non-coding RNAs (lncRNAs) comprise the most representative transcriptional units of the mammalian genome. They are associated with organ development linked with the emergence of cardiovascular diseases. We used bioinformatic approaches, machine learning algorithms, systems biology analyses, and statistical techniques to define co-expression modules linked to heart development and cardiovascular diseases. We also uncovered differentially expressed transcripts in subpopulations of cardiomyocytes. Finally, from this work, we were able to identify eight cardiac cell-types; several new coding, lncRNA, and pcRNA markers; two cardiomyocyte subpopulations at four different time points (ventricle E9.5, left ventricle E11.5, right ventricle E14.5 and left atrium P0) that harbored co-expressed gene modules enriched in mitochondrial, heart development and cardiovascular diseases. Our results evidence the role of particular lncRNAs in heart development and highlight the usage of co-expression modular approaches in the cell-type functional definition. |
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| AbstractList | Long non-coding RNAs (lncRNAs) comprise the most representative transcriptional units of the mammalian genome. They are associated with organ development linked with the emergence of cardiovascular diseases. We used bioinformatic approaches, machine learning algorithms, systems biology analyses, and statistical techniques to define co-expression modules linked to heart development and cardiovascular diseases. We also uncovered differentially expressed transcripts in subpopulations of cardiomyocytes. Finally, from this work, we were able to identify eight cardiac cell-types; several new coding, lncRNA, and pcRNA markers; two cardiomyocyte subpopulations at four different time points (ventricle E9.5, left ventricle E11.5, right ventricle E14.5 and left atrium P0) that harbored co-expressed gene modules enriched in mitochondrial, heart development and cardiovascular diseases. Our results evidence the role of particular lncRNAs in heart development and highlight the usage of co-expression modular approaches in the cell-type functional definition. Abstract Long non-coding RNAs (lncRNAs) comprise the most representative transcriptional units of the mammalian genome. They are associated with organ development linked with the emergence of cardiovascular diseases. We used bioinformatic approaches, machine learning algorithms, systems biology analyses, and statistical techniques to define co-expression modules linked to heart development and cardiovascular diseases. We also uncovered differentially expressed transcripts in subpopulations of cardiomyocytes. Finally, from this work, we were able to identify eight cardiac cell-types; several new coding, lncRNA, and pcRNA markers; two cardiomyocyte subpopulations at four different time points (ventricle E9.5, left ventricle E11.5, right ventricle E14.5 and left atrium P0) that harbored co-expressed gene modules enriched in mitochondrial, heart development and cardiovascular diseases. Our results evidence the role of particular lncRNAs in heart development and highlight the usage of co-expression modular approaches in the cell-type functional definition. Long non-coding RNAs (lncRNAs) comprise the most representative transcriptional units of the mammalian genome. They are associated with organ development linked with the emergence of cardiovascular diseases. We used bioinformatic approaches, machine learning algorithms, systems biology analyses, and statistical techniques to define co-expression modules linked to heart development and cardiovascular diseases. We also uncovered differentially expressed transcripts in subpopulations of cardiomyocytes. Finally, from this work, we were able to identify eight cardiac cell-types; several new coding, lncRNA, and pcRNA markers; two cardiomyocyte subpopulations at four different time points (ventricle E9.5, left ventricle E11.5, right ventricle E14.5 and left atrium P0) that harbored co-expressed gene modules enriched in mitochondrial, heart development and cardiovascular diseases. Our results evidence the role of particular lncRNAs in heart development and highlight the usage of co-expression modular approaches in the cell-type functional definition.Long non-coding RNAs (lncRNAs) comprise the most representative transcriptional units of the mammalian genome. They are associated with organ development linked with the emergence of cardiovascular diseases. We used bioinformatic approaches, machine learning algorithms, systems biology analyses, and statistical techniques to define co-expression modules linked to heart development and cardiovascular diseases. We also uncovered differentially expressed transcripts in subpopulations of cardiomyocytes. Finally, from this work, we were able to identify eight cardiac cell-types; several new coding, lncRNA, and pcRNA markers; two cardiomyocyte subpopulations at four different time points (ventricle E9.5, left ventricle E11.5, right ventricle E14.5 and left atrium P0) that harbored co-expressed gene modules enriched in mitochondrial, heart development and cardiovascular diseases. Our results evidence the role of particular lncRNAs in heart development and highlight the usage of co-expression modular approaches in the cell-type functional definition. |
| ArticleNumber | 841 |
| Author | Lavandero, Sergio Hill, Joseph A. Urquiza-Zurich, Sebastián Gillette, Thomas G. Maracaja-Coutinho, Vinicius do Rêgo, Thaís G. Ramos, Thaís A. R. Kim, Soo Young |
| Author_xml | – sequence: 1 givenname: Thaís A. R. surname: Ramos fullname: Ramos, Thaís A. R. organization: Advanced Center for Chronic Diseases (ACCDiS), Faculty of Chemical & Pharmaceutical Sciences & Faculty of Medicine, Universidad de Chile, Programa de Pós-Graduação em Bioinformática, Bioinformatics Multidisciplinary Environment (BioME), Instituto Metrópole Digital, Universidade Federal do Rio Grande do Norte, Departamento de Informática, Centro de Informática, Universidade Federal da Paraíba – sequence: 2 givenname: Sebastián surname: Urquiza-Zurich fullname: Urquiza-Zurich, Sebastián organization: Advanced Center for Chronic Diseases (ACCDiS), Faculty of Chemical & Pharmaceutical Sciences & Faculty of Medicine, Universidad de Chile – sequence: 3 givenname: Soo Young surname: Kim fullname: Kim, Soo Young organization: Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center Dallas – sequence: 4 givenname: Thomas G. orcidid: 0000-0002-7617-3544 surname: Gillette fullname: Gillette, Thomas G. organization: Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center Dallas – sequence: 5 givenname: Joseph A. orcidid: 0000-0002-5379-1614 surname: Hill fullname: Hill, Joseph A. organization: Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center Dallas, Department of Molecular Biology, University of Texas Southwestern Medical Center – sequence: 6 givenname: Sergio orcidid: 0000-0003-4258-1483 surname: Lavandero fullname: Lavandero, Sergio email: slavander@uchile.cl organization: Advanced Center for Chronic Diseases (ACCDiS), Faculty of Chemical & Pharmaceutical Sciences & Faculty of Medicine, Universidad de Chile, Corporación Centro de Estudios Científicos de las Enfermedades Crónicas (CECEC) – sequence: 7 givenname: Thaís G. surname: do Rêgo fullname: do Rêgo, Thaís G. email: gaudenciothais@gmail.com organization: Programa de Pós-Graduação em Bioinformática, Bioinformatics Multidisciplinary Environment (BioME), Instituto Metrópole Digital, Universidade Federal do Rio Grande do Norte, Departamento de Informática, Centro de Informática, Universidade Federal da Paraíba – sequence: 8 givenname: Vinicius orcidid: 0000-0002-8873-9381 surname: Maracaja-Coutinho fullname: Maracaja-Coutinho, Vinicius email: vinicius.maracaja@uchile.cl organization: Advanced Center for Chronic Diseases (ACCDiS), Faculty of Chemical & Pharmaceutical Sciences & Faculty of Medicine, Universidad de Chile, Programa de Pós-Graduação em Bioinformática, Bioinformatics Multidisciplinary Environment (BioME), Instituto Metrópole Digital, Universidade Federal do Rio Grande do Norte |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/38110334$$D View this record in MEDLINE/PubMed |
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| Snippet | Long non-coding RNAs (lncRNAs) comprise the most representative transcriptional units of the mammalian genome. They are associated with organ development... Abstract Long non-coding RNAs (lncRNAs) comprise the most representative transcriptional units of the mammalian genome. They are associated with organ... |
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| SubjectTerms | 38/39 45/91 631/136/142 692/308/2056 692/699/75/230 Antibodies Biochemistry Biomedical and Life Sciences Cardiomyocytes Cardiovascular diseases Cell Biology Cell Culture Cell death Cluster analysis Gene expression Genomes Heart Heart diseases Immunology Life Sciences Non-coding RNA Smooth muscle Statistical analysis Ventricle |
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| Title | Single-cell transcriptional landscape of long non-coding RNAs orchestrating mouse heart development |
| URI | https://link.springer.com/article/10.1038/s41419-023-06296-9 https://www.ncbi.nlm.nih.gov/pubmed/38110334 https://www.proquest.com/docview/2903127715 https://www.proquest.com/docview/2903860489 https://pubmed.ncbi.nlm.nih.gov/PMC10728149 https://doaj.org/article/05b4f3719b124166aa09006280eddb6a |
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