PLX293016

GSE150150: Transcriptional landscape of fate choices in the sensory lineages

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

Somatic sensation is defined by the existence of a diversity of primary sensory neurons with unique biological features and response profiles to external and internal stimuli. However, there is no coherent picture about how this diversity of cell states is transcriptionally generated. Here, we used deep single cell analysis to resolve fate splits and molecular biasing processes during sensory neurogenesis. Our results revealed a complex series of successive and specific transcriptional changes in post-mitotic neurons that delineate hierarchical regulatory states leading to the generation of the main sensory neuron classes. In addition, our analysis identified previously undetected early gene modules expressed long before fate determination although being clearly associated with the final sensory subtypes. Overall, fate choice in sensory neurons involves initial co-activation of counteracting regulatory determinants of alternative lineages priming intermediate post-mitotic neuronal cells for a binary cell fate choice. Hence, the diversity of sensory neurons is generated through successive bi-potential intermediates in which synchronization of relevant gene modules and concurrent repression of competing fate programs precede cell fate stabilization and final commitment. SOURCE: Saida Hadjab (saida.hadjab@ki.se) - Karolinska Institutet

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