# Temporal multiomics gene expression data across human embryonic stem cell-derived polyhormonal cell differentiation

## TL;DR

This study tracks gene activity changes as human stem cells develop into hormone-producing cells, offering insights into early human development.

## Contribution

A high-resolution, multi-omics dataset capturing mRNA, translation, and protein dynamics during hESC differentiation into polyhormonal cells.

## Key findings

- The dataset reveals transcriptional, translational, and protein abundance changes across ten time points.
- Strong reproducibility and quality control metrics confirm the dataset's reliability.
- The dataset aids in understanding regulatory mechanisms in pancreatic lineage development.

## Abstract

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.