Single-Cell Transcriptomic Analysis Reveals Dynamic Cellular Processes in Corneal Epithelium During Wound Healing in Cynomolgus Monkeys.

Purpose: Corneal wounding healing is critical for maintaining clear vision, however, a complete understanding of its dynamic regulatory mechanisms remains elusive. Here, we used single-cell RNA sequencing (scRNA-seq) to analyze the cellular activities and transcriptional changes of corneal limbal epithelial cells at different stages after wound healing in cynomolgus monkeys, which exhibit a closer transcriptomic similarity to humans. Methods: Corneal limbal tissues were collected during uninjured, 1-day and 3-day healing stages, dissociated into single cells, and subjected to scRNA-seq using the 10× Genomics platform. Cell types were clustered by graph-based visualization methods and unbiased computational analysis. Additionally, cell migration assays and immunofluorescent staining were performed on cultured human corneal epithelial cells. Results: We characterized nine cell clusters by scRNA-seq analysis of the cynomolgus monkey corneal epithelium. By comparing heterogeneous transcriptional changes in major cell types during corneal healing, we highlighted the importance of limbal epithelial cells (LEPCs) and basal epithelial cells (BEPCs) in extracellular matrix (ECM) formation and wound healing, as well as suprabasal epithelial cells (SEPCs) in epithelial differentiation during the healing processes. We further identified five different sub-clusters in LEPC, including the transit amplifying cell (TAC) sub-cluster that promotes early healing through the activation of thrombospondin-1 (THBS1) expression. Conclusions: Our study represents the first comprehensive exploration of the detailed transcriptome profile of individual corneal cells during the wound healing process in nonhuman primates. We demonstrate the intricate mechanisms involved in corneal healing and provide a promising avenue for potential therapies in corneal wound healing.

High-throughput single-molecule long-read RNA sequencing analysis of tissue-specific genes and isoforms in lettuce (Lactuca sativa L.).

Lettuce is one of the most widely cultivated and consumed dicotyledonous vegetables globally. Despite the availability of its reference genome sequence, lettuce gene annotation remains incomplete, impeding comprehensive research and the broad application of genomic resources. Long-read RNA isoform sequencing (Iso-Seq) offers substantial advantages for analyzing RNA alternative splicing and aiding gene annotation, yet it faces throughput limitations. We present the HIT-ISOseq method tailored for bulk sample analysis, significantly enhancing RNA sequencing throughput on the PacBio platform by concatenating cDNA. Here we show, HIT-ISOseq generates 3-4 cDNA molecules per CCS read in lettuce, yielding 15.7 million long reads per PacBio Sequel II SMRT Cell 8 M. We validate its effectiveness in analyzing six lettuce tissue samples, including roots, stems, and leaves, revealing tissue-specific gene expression patterns and RNA isoforms. Leveraging diverse tissue long-read RNA sequencing, we refine the transcript annotation of the lettuce reference genome, expanding its GO and KEGG annotation repertoire. Collectively, this study serves as a foundational reference for genome annotation and the analysis of multi-sample isoform expression, utilizing high-throughput long-read transcriptome sequencing.

Integrative Single-Cell RNA-Seq and ATAC-Seq Analysis of Mouse Corneal Epithelial Cells.

Purpose: Corneal epithelial homeostasis is maintained by coordinated gene expression across distinct cell populations, but the gene regulatory programs underlying this cellular diversity remain to be characterized. Here we applied single-cell multi-omics analysis to delineate the gene regulatory profile of mouse corneal epithelial cells under normal homeostasis. Methods: Single cells isolated from the cornea epithelium (with marginal conjunctiva) of adult mice were subjected to scRNA-seq and scATAC-seq using the 10×Genomics platform. Cell types were clustered by the graph-based visualization method uniform manifold approximation and projection and unbiased computational informatics analysis. The scRNA-seq and scATAC-seq datasets were integrated following the integration pipeline described in ArchR and Seurat. Results: We characterized diverse corneal epithelial cell types based on gene expression signatures and chromatin accessibility. We found that cell type-specific accessibility regions were mainly located at distal regions, suggesting essential roles of distal regulatory elements in determining corneal epithelial cell diversity. Trajectory analyses revealed a continuum of cell state transition and higher coordination between transcription factor (TF) motif accessibility and gene expression during corneal epithelial cell differentiation. By integrating transcriptomic and chromatin accessibility analysis, we identified cell type-specific and shared gene regulation programs. We also uncovered critical TFs driving corneal epithelial cell differentiation, such as nuclear factor I (NFI) family members, Rarg, Elf3. We found that nuclear factor-κB (NF-κB) family members were positive TFs in limbal cells and some superficial cells, but they were involved in regulating distinct biological processes. Conclusions: Our study presents a comprehensive gene regulatory landscape of mouse cornea epithelial cells, and provides valuable foundations for future investigation of corneal epithelial homeostasis in the context of cornea pathologies and regenerative medicine.

High-throughput and high-accuracy single-cell RNA isoform analysis using PacBio circular consensus sequencing.

Although long-read single-cell RNA isoform sequencing (scISO-Seq) can reveal alternative RNA splicing in individual cells, it suffers from a low read throughput. Here, we introduce HIT-scISOseq, a method that removes most artifact cDNAs and concatenates multiple cDNAs for PacBio circular consensus sequencing (CCS) to achieve high-throughput and high-accuracy single-cell RNA isoform sequencing. HIT-scISOseq can yield >10 million high-accuracy long-reads in a single PacBio Sequel II SMRT Cell 8M. We also report the development of scISA-Tools that demultiplex HIT-scISOseq concatenated reads into single-cell cDNA reads with >99.99% accuracy and specificity. We apply HIT-scISOseq to characterize the transcriptomes of 3375 corneal limbus cells and reveal cell-type-specific isoform expression in them. HIT-scISOseq is a high-throughput, high-accuracy, technically accessible method and it can accelerate the burgeoning field of long-read single-cell transcriptomics.