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lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

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In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
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Related Experiment Video

Updated: Jun 27, 2025

Large-scale Three-dimensional Imaging of Cellular Organization in the Mouse Neocortex
09:55

Large-scale Three-dimensional Imaging of Cellular Organization in the Mouse Neocortex

Published on: September 5, 2018

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Expression characteristics and potential function of non-coding RNA in mouse cortical cells.

Yanrong Wei1,2, Junjie Lei1,2, Yujie Peng2

  • 1College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China.

Frontiers in Molecular Neuroscience
|April 25, 2024
PubMed
Summary

Non-coding RNAs (ncRNAs) define brain cell types and reveal specific markers for neurological disorders. This study provides a valuable resource for understanding ncRNA roles in brain health and disease.

Keywords:
cell-type specific noncoding RNAcerebral cortexhdWGCNAneurological disordersnon-coding RNAsingle-cell SMART-Seq v4spatial transcriptome

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Area of Science:

  • Neuroscience
  • Genomics
  • Molecular Biology

Background:

  • Non-coding RNAs (ncRNAs) are crucial regulators in brain physiology and pathology.
  • Understanding the specific roles of ncRNAs in different brain cell types is essential.

Purpose of the Study:

  • To systematically characterize the ncRNA profile in mouse cortical cells.
  • To identify cell type-specific, layer-specific, and region-specific ncRNAs.
  • To explore the functional roles and disease associations of ncRNAs in the brain.

Main Methods:

  • Analysis of single-cell SMART-Seq v4 data from the mouse cerebral cortex.
  • Construction of ncRNA and protein-coding gene co-expression networks.
  • Integration with spatial transcriptome (ST) and genome-wide association studies (GWAS) data.

Main Results:

  • ncRNAs alone are sufficient to identify most cortical cell types.
  • 1,600 cell type-specific ncRNAs were identified, distinguishing even closely related cell populations like microglia and perivascular macrophages.
  • Cortical layer and region-specific ncRNAs were characterized, consistent with ST data.
  • Functional predictions and associations with neurological disorder traits were established through integrated analyses.

Conclusions:

  • This study provides a comprehensive resource of differentially expressed ncRNAs in cortical cells at multiple levels.
  • Identified ncRNAs offer insights into their functions and dysfunctions in neurological disorders.
  • ncRNAs serve as key determinants of cell identity and potential therapeutic targets in the brain.