Temporal multiomics gene expression data across human embryonic stem cell derived cardiomyocyte differentiation [Ribo-seq]
Embryonic development has not been fully understood, despite significant advances in molecular and systems-level approaches. Human embryonic stem cells (hESCs) serve as a valuable in vitro model for studying early human developmental processes due to their ability to differentiate into all three germ layers. Here, we present a comprehensive multi-omics dataset generated by differentiating hESCs into cardiomyocytes via the mesodermal lineage, collecting samples at 10 distinct time points. We measured mRNA levels by mRNA sequencing (mRNA-seq), translation levels by ribosome profiling (Ribo-seq), and protein levels by quantitative mass spectrometry. Technical validation confirmed high quality and reproducibility across all datasets, with strong correlations between replicates. This extensive dataset provides critical insights into the complex regulatory mechanisms of cardiomyocyte differentiation and serves as a valuable resource for the research community, aiding in the exploration of mammalian development and gene regulation. Overall design: To gain a deeper understanding of the gene regulatory mechanisms that drive embryonic development, we conducted simultaneous genome-wide measurements of mRNA, translation, and protein levels during hESC differentiation. This involved differentiating hESCs into the three distinct germ layers—endoderm, mesoderm, and ectoderm—and subsequently further differentiating them into polyhormonal cells, cardiomyocytes, and motor neurons, respectively. In this study, we specifically focus on the differentiation process from hESCs to cardiomyocytes via the mesodermal lineage. We collected samples at 10 distinct time points during cardiomyocyte differentiation, which allows us to track the differentiation of cells over time, providing valuable insights into the temporal regulation of gene expression. We measured mRNA levels by mRNA sequencing (mRNA-seq), translation levels by ribosome profiling (Ribo-seq), and protein levels by quantitative mass spectrometry on the matched samples. The differentiation and subsequent measurements were conducted in duplicates.