Sign in
BioinformaticsBMC Genomics
Peer-reviewed journal article

Identification and characterization of functional modules reflecting transcriptome transition during human neuron maturation

Zhisong HeiD, Qianhui YuiD

Abstract

BackgroundNeuron maturation is a critical process in neurogenesis, during which neurons gain their morphological, electrophysiological and molecular characteristics for their functions as the central components of the nervous system.\n\nResultsTo better understand the molecular changes during this process, we combined the protein-protein interaction network and public single cell RNA-seq data of mature and immature neurons to identify functional modules relevant to the neuron maturation process in humans. The analysis resulted in 33 discriminable modules which participate in varied functions including energy consumption, synaptic functions and housekeeping functions such as translation and splicing. Based on the identified modules, we trained a neuron maturity index (NMI) model for the quantification of maturation states of single neurons or purified bulk neurons. Applied to multiple single neuron transcriptome data sets of neuron development in humans and mice, the NMI model made estimation of neuron maturity states which were significantly correlated with the neuron maturation trajectories in both species, implying the reproducibility and conservation of the identified transcriptome transition.\n\nConclusionWe identified 33 functional modules whose activities were significantly correlated with single neuron maturity states, which may play important roles in the neuron maturation process.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers
Citations
20
FWCI
0.80
Field percentile
top 31%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISMarques '21Chen '25Burke '20Patel '22Tosoni '26Mahmoud '25
63% semantic matchNeuroscience