Comparative Transcriptome Landscape of Mouse and Human Hearts

• Published in: Frontiers in cell and developmental biology Vol. 8; p. 268
• Main Authors: Anzai, Tatsuya, Yamagata, Takanori, Uosaki, Hideki
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 22.04.2020
• Subjects: cardiomyocyte maturation; Cell and Developmental Biology; comparative transcriptome; maturation marker; ribosome; transcriptome; ribosome; comparative transcriptome; cardiomyocyte maturation; transcriptome; maturation marker
• ISSN: 2296-634X; 2296-634X
• DOI: 10.3389/fcell.2020.00268

Transcriptome landscape of organs from mice and humans offers perspectives on the process of how organs develop and the similarity and diversity in each organ between the species. Among multi-species and multi-organ dataset, which was previously generated, we focused on the mouse and human dataset and performed a reanalysis to provide a more specific perspective on the maturation of human cardiomyocytes. First, we examined how organs diversify their transcriptome during development across and within two species. We unexpectedly identified that ribosomal genes were differentially expressed between mice and humans. Second, we examined the corresponding ages of organs in mice and humans and found that the corresponding developmental ages did not match throughout organs. Mouse hearts at P0-3 and human hearts at 18-19 wpc showed the most proximity in the regard of the transcriptome. Third, we identified a novel set of maturation marker genes that are more consistent between mice and humans. In contrast, conventionally used maturation marker genes only work well with mouse hearts. Finally, we compared human pluripotent stem cell-derived cardiomyocytes (PSC-CMs) in maturation-enhanced conditions to human fetal and adult hearts and revealed that human PSC-CMs only expressed low levels of the potential maturation marker genes. Our findings provide a novel foundation to study cardiomyocyte maturation and highlight the importance of studying human samples rather than relying on a mouse time-series dataset.