Prediction of Cell States and Key Transcription Factors of the Human Cornea through Integrated Single-Cell Omics Analyses

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Дек. 20, 2024

Abstract The cornea, a transparent tissue composed of multiple layers, allows light to enter the eye. Several single-cell RNA-seq analyses have been performed explore cell states and understand cellular composition human cornea. However, inconsistences in state annotations between these studies complicate application findings corneal studies. To address this, we integrated data from four published created meta-atlas. This meta-atlas was subsequently evaluated two applications. First, developed machine learning pipeline cPredictor, using as input, annotate states. We demonstrated accuracy cPredictor its ability identify novel marker genes rare Furthermore, revealed differences pluripotent stem cell-derived organoids Second, based with chromatin accessibility data, conducting motif-focused gene regulatory network analyses. These approaches identified distinct transcription factors driving were validated by immunohistochemistry. Overall, this study offers reliable accessible reference for profiling states, which facilitates future research cornea development, disease regeneration. Significance statement creates that provides common nomenclature cells through integrating Using meta-atlas, pipeline, accurately RNA-seq. Additionally, atlas data. computational tool enable disease,

Язык: Английский

Deciphering the heterogeneity of differentiating hPSC-derived corneal limbal stem cells through single-cell RNA-sequencing

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2023, Номер unknown

Опубликована: Ноя. 24, 2023

Summary A comprehensive understanding of the human pluripotent stem cell (hPSC) differentiation process stands as a prerequisite for development hPSC-based therapeutics. In this study, single-cell RNA-sequencing (scRNA-seq) was performed to decipher heterogeneity during three hPSC lines towards corneal limbal cells (LSCs). The scRNA-seq data revealed nine clusters encompassing entire process, among which five followed anticipated path LSCs. remaining four were previously undescribed states that annotated either mesodermal-like or undifferentiated subpopulations, and their prevalence line-dependent. Distinct cluster-specific marker genes identified in study confirmed by immunofluorescence analysis employed purify hPSC-derived LSCs, effectively minimized variation line-dependent efficiency. summary, offered molecular insights into hPSC-LSC differentiation, allowing data-driven strategy consistent robust generation essential future advancement toward clinical translation. Highlights hPSCs LSCs spans epithelial, mesodermal, states. reveals heterogeneity. ITGA6 AREG can be used select pure LSC-like subpopulation.

Язык: Английский