Temporal multi-omics gene expression data across human embryonic stem cell-derived polyhormonal cell differentiation [Ribo-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.

人类胚胎干细胞（human embryonic stem cells, hESCs）是研究谱系特化与人类早期发育背后调控程序的强大体外模型。本研究公开了一套高分辨率时序多组学数据集，追踪了人类胚胎干细胞向定型内胚层分化，以及后续向多激素（polyhormonal, PH）细胞——一类关键的胰腺谱系细胞——分化过程中的mRNA、翻译及蛋白质表达动态变化。本研究对10个时间点采集的匹配样本开展了生物学重复的RNA测序（RNA-seq）、核糖体谱分析（ribosome profiling, Ribo-seq）以及基于定量质谱的蛋白质组学检测，从而可细致刻画分化进程中转录、翻译及蛋白质丰度的动态变化。该数据集技术质量优异，重复样本间重现性极佳，且所有组学平台均通过了严格的质量控制指标验证。这套全面的数据集为解析驱动多激素细胞分化的复杂调控机制提供了关键见解，同时可为科研共同体提供宝贵的研究资源，助力学界深入探索哺乳动物发育、内胚层谱系特化以及基因调控过程。整体实验设计：为全面解析人类胚胎发育背后的基因调控机制，本研究在人类胚胎干细胞分化过程中开展了全基因组范围的mRNA、翻译水平及蛋白质水平检测。本实验设计涵盖了三胚层（内胚层、中胚层及外胚层）的诱导生成，随后分别将其定向分化为多激素细胞、心肌细胞与运动神经元。本研究聚焦于内胚层向多激素细胞分化的发育轨迹。研究人员在10个不同时间点采集样本，从而可高分辨率追踪分化过程中的基因表达动态变化。针对匹配样本，分别通过mRNA测序（RNA-seq）检测mRNA水平、通过核糖体谱分析（ribosome profiling, Ribo-seq）作为翻译水平的替代指标、以及通过基于定量质谱的蛋白质组学检测蛋白质水平。所有分化实验与检测均设置了生物学重复。