PLX114576

GSE54322: RNA-seq analysis in Cornea epithelial cells (CECs), skin epithelial cells (SECs), LSCs after knocking down PAX6 (3-D shPAX6 LSCs) and SESCs transduced with PAX6(3-D PAX6+ SESCs) upon 3-D differentiation

  • Organsim human
  • Type RNASEQ
  • Target gene
  • Project ARCHS4

Purpose: We find that Wnt7a-PAX6 axis determine corneal epithelial cell fate. To obtain global evidence for successful cell fate conversion, we performed gene expression profiling by RNA-seq on CECs, SECs, and LSCs after knocking down PAX6 and on SESCs transduced with PAX6 upon 3-D differentiation.; Methods: Under 3-D culture condition, limbal stem cell (LSCs) can be differentiated to Cornea epithelial cells (CECs), and skin epithelial stem cells (SESCs) can be differentiated to skin epithelial cells (SECs). Total RNA was isolated from CECs, SECs, and LSCs after knocking down PAX6 (3-D shPAX6 LSCs) and on SESCs transduced with PAX6 (3-D PAX6+ SESCs) upon 3-D differentiation. Libraries were prepared following published standard protocol (Fox-Walsh K et al., 2011, genomics, 266-71). mRNA profiles were generated by deep sequencing, in duplicate, using Illumina HiSeq 2000.; Results: Following optimized decoding and mapping workfollow, we mapped about 5 million sequence reads to the human genome and identified more than 23659 transcripts per sample.; Conclusions: Hierarchical clustering analysis of differentially expressed gene signatures revealed that the gene expression pattern of SESCs with PAX6 transduction was strikingly similar to that of CECs, whereas the profile of LSCs with PAX6 knockdown was highly related to that in SECs upon differentiation. These data therefore provided global evidence for a decisive role of the WNT7A/PAX6 axis in cell fate conversion from SESCs to CECs. SOURCE: Hai-Ri Li (hairili@ucsd.edu) - Dr. Xiang-Dong Fu University of California, San Diego

View on GEOView in Pluto

Key Features

Enhance your research with our curated data sets and powerful platform features. Pluto Bio makes it simple to find and use the data you need.

Learn More

14K+ Published Experiments

Access an extensive range of curated bioinformatics data sets, including genomic, transcriptomic, and proteomic data.

Easy Data Import

Request imports from GEO or TCGA directly within Pluto Bio. Seamlessly integrate external data sets into your workflow.

Advanced Search Capabilities

Utilize powerful search tools to quickly find the data sets relevant to your research. Filter by type, disease, gene, and more.

Analyze and visualize data for this experiment

Use Pluto's intuitive interface to analyze and visualize data for this experiment. Pluto's platform is equipped with an API & SDKs, making it easy to integrate into your internal bioinformatics processes.

Read about post-pipeline analysis

View QC data and experiment metadata

View quality control data and experiment metadata for this experiment.

Request import of other GEO data

Request imports from GEO or TCGA directly within Pluto Bio.

Chat with our Scientific Insights team