Temporal multi-omics gene expression data across human embryonic stem cell-derived polyhormonal cell differentiation [RNA-seq]

Human embryonic stem cells (hESCs) provide a powerful in vitro model to study lineage specification and the regulatory programs underlying early human development. Here, we present a high-resolution, temporal multi-omics dataset tracking mRNA, translation, and protein expression dynamics during hESC differentiation into definitive endoderm and subsequent polyhormonal (PH) cells, a key pancreatic lineage. RNA-seq, ribosome profiling, and quantitative mass spectrometry-based proteomics were performed on matched samples collected at ten time points in biological duplicates, allowing detailed characterization of transcriptional, translational, and protein abundance changes over the differentiation timeline. The dataset exhibits high technical quality, with strong reproducibility between replicates and rigorous quality control metrics across all omics platforms. This extensive dataset provides critical insights into the complex regulatory mechanisms driving polyhormonal cell differentiation and serves as a valuable resource for the research community, enabling deeper exploration of mammalian development, endodermal lineage specification, and gene regulation. Overall design: To comprehensively investigate the gene regulatory mechanisms underlying human embryonic development, we performed genome-wide measurements of mRNA, translation, and protein levels during hESC differentiation. Our experimental design encompassed the generation of all three embryonic germ layers—endoderm, mesoderm, and ectoderm—followed by their directed differentiation into polyhormonal cells, cardiomyocytes, and motor neurons, respectively. In the present study, we focus on the endoderm-to-polyhormonal cell differentiation trajectory. Samples were collected at ten distinct time points, enabling high-resolution tracking of gene expression dynamics over the course of differentiation. Matched samples were measured for mRNA levels by mRNA sequencing (mRNA-seq), for translation level proxies by ribosome profiling (Ribo-seq), and for protein levels by quantitative mass spectrometry-based proteomics. All differentiations and measurements were performed in biological duplicates.