English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Somatic cells can be directly reprogrammed into neurons through the expression of few transcription factors. However, the precise mechanisms involved in the lineage-conversion are poorly understood. Similarly, it remains unclear how similar lineage-reprogrammed induced neurons (iNs) are to bona fide central nervous system neurons. In this work, we used an unsupervised machine-learning approach to compare the transcriptional profiles of lineage-reprogrammed mouse embryonic fibroblasts (MEFs), mouse embryonic telencephalon neural progenitors and neurons, as well as mouse postnatal cerebral cortex neurons. We show that the transcriptional profile of a subpopulation of lineage-reprogrammed MEFs resembles that of primary neural progenitors and neurons, indicating that the intermediate steps enacted by reprogramming factors within MEFs during the transition to iNs are similar to those observed during primary neuron differentiation. Finally, by comparing the transcriptional profiles of MEFs that undertook a neuronal pathway to that of MEFs adopting a myogenic fate or retaining fibroblast features we identified potential candidates to improve the efficiency for lineage conversion of those cells into neurons.

Transcriptional profile of induced and primary neurons reveals new candidate genes for lineage reprogramming