Han Sun

The paper integrates multiple scRNA-seq datasets to create a comprehensive atlas of human pancreatic islets, identifying 13 cell populations and providing a resource for diabetes research.

In 299 islet preparations from donors without diabetes, endocrine cell composition, not donor demographics, tracked insulin secretion, and δ cell percentage rose with type 2 diabetes genetic risk.

The paper infers post-transcriptional regulatory mechanisms in human islets using cell type-specific eQTLs from single-cell RNA-seq data, linking variants to biological processes in health and disease.

This study shows that reducing RREB1 in mice and humans decreases adipogenesis and improves insulin sensitivity, linking RREB1 to type 2 diabetes risk.

HumanIslets.com provides an open platform for accessing and analyzing human islet data, enabling research on diabetes through integrated molecular and cellular phenotyping.

A genome-wide CRISPR screen in human pancreatic beta cells identifies 580 genes influencing insulin content, supporting 20 candidate type 2 diabetes effector transcripts.

The paper uses targeted chromatin interaction profiling to identify causal genes at type 2 diabetes GWAS loci with higher sensitivity and resolution than genome-wide methods.

This study shows that PAX4 variants reduce beta cell function and increase diabetes risk by impairing insulin secretion and hormone gene expression in human cells.

This study maps human fetal pancreatic development using scRNA-Seq and snATAC-Seq, identifying novel cell types and regulatory mechanisms, and highlights gene FEV's role in endocrine differentiation.

The paper characterizes gene and protein expression changes in NGLY1 deficiency using patient-derived cells and provides a web resource for the data.

The paper develops a pipeline to identify and quantify full-length RNA isoforms, revealing disease-associated isoforms in cardiomyocytes with RBM20 mutations.

The paper identifies a recurrent tumor-specific transcript fusion between CDKN1A and RAB44 caused by splice-site mutations and shows its correlation with TP53 inactivation and CDK activation.