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Public Library of Science, PLoS Computational Biology, 9(17), p. e1009305, 2021

DOI: 10.1371/journal.pcbi.1009305

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Transcriptomic entropy benchmarks stem cell-derived cardiomyocyte maturation against endogenous tissue at single cell level

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

The immaturity of pluripotent stem cell (PSC)-derived tissues has emerged as a universal problem for their biomedical applications. While efforts have been made to generate adult-like cells from PSCs, direct benchmarking of PSC-derived tissues againstin vivodevelopment has not been established. Thus, maturation status is often assessed on anad-hocbasis. Single cell RNA-sequencing (scRNA-seq) offers a promising solution, though cross-study comparison is limited by dataset-specific batch effects. Here, we developed a novel approach to quantify PSC-derived cardiomyocyte (CM) maturation through transcriptomic entropy. Transcriptomic entropy is robust across datasets regardless of differences in isolation protocols, library preparation, and other potential batch effects. With this new model, we analyzed over 45 scRNA-seq datasets and over 52,000 CMs, and established a cross-study, cross-species CM maturation reference. This reference enabled us to directly compare PSC-CMs with thein vivodevelopmental trajectory and thereby to quantify PSC-CM maturation status. We further found that our entropy-based approach can be used for other cell types, including pancreatic beta cells and hepatocytes. Our study presents a biologically relevant and interpretable metric for quantifying PSC-derived tissue maturation, and is extensible to numerous tissue engineering contexts.