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Noncoding RNA in the transcriptional landscape of human neural progenitor cell differentiation

Increasing evidence suggests that noncoding RNAs play key roles in cellular processes, particularly in the brain. The present study used RNA sequencing to identify the transcriptional landscape of two human neural progenitor cell lines, SK-N-SH and ReNcell CX, as they differentiate into human cortic...

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Autores principales: Hecht, Patrick M., Ballesteros-Yanez, Inmaculada, Grepo, Nicole, Knowles, James A., Campbell, Daniel B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4615820/
https://www.ncbi.nlm.nih.gov/pubmed/26557050
http://dx.doi.org/10.3389/fnins.2015.00392
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author Hecht, Patrick M.
Ballesteros-Yanez, Inmaculada
Grepo, Nicole
Knowles, James A.
Campbell, Daniel B.
author_facet Hecht, Patrick M.
Ballesteros-Yanez, Inmaculada
Grepo, Nicole
Knowles, James A.
Campbell, Daniel B.
author_sort Hecht, Patrick M.
collection PubMed
description Increasing evidence suggests that noncoding RNAs play key roles in cellular processes, particularly in the brain. The present study used RNA sequencing to identify the transcriptional landscape of two human neural progenitor cell lines, SK-N-SH and ReNcell CX, as they differentiate into human cortical projection neurons. Protein coding genes were found to account for 54.8 and 57.0% of expressed genes, respectively, and alignment of RNA sequencing reads revealed that only 25.5–28.1% mapped to exonic regions of the genome. Differential expression analysis in the two cell lines identified altered gene expression in both protein coding and noncoding RNAs as they undergo neural differentiation with 222 differentially expressed genes observed in SK-N-SH cells and 19 differentially expressed genes in ReNcell CX. Interestingly, genes showing differential expression in SK-N-SH cells are enriched in genes implicated in autism spectrum disorder, but not in gene sets related to cancer or Alzheimer's disease. Weighted gene co-expression network analysis (WGCNA) was used to detect modules of co-expressed protein coding and noncoding RNAs in SK-N-SH cells and found four modules to be associated with neural differentiation. These modules contain varying levels of noncoding RNAs ranging from 10.7 to 49.7% with gene ontology suggesting roles in numerous cellular processes important for differentiation. These results indicate that noncoding RNAs are highly expressed in human neural progenitor cells and likely hold key regulatory roles in gene networks underlying neural differentiation and neurodevelopmental disorders.
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spelling pubmed-46158202015-11-09 Noncoding RNA in the transcriptional landscape of human neural progenitor cell differentiation Hecht, Patrick M. Ballesteros-Yanez, Inmaculada Grepo, Nicole Knowles, James A. Campbell, Daniel B. Front Neurosci Genetics Increasing evidence suggests that noncoding RNAs play key roles in cellular processes, particularly in the brain. The present study used RNA sequencing to identify the transcriptional landscape of two human neural progenitor cell lines, SK-N-SH and ReNcell CX, as they differentiate into human cortical projection neurons. Protein coding genes were found to account for 54.8 and 57.0% of expressed genes, respectively, and alignment of RNA sequencing reads revealed that only 25.5–28.1% mapped to exonic regions of the genome. Differential expression analysis in the two cell lines identified altered gene expression in both protein coding and noncoding RNAs as they undergo neural differentiation with 222 differentially expressed genes observed in SK-N-SH cells and 19 differentially expressed genes in ReNcell CX. Interestingly, genes showing differential expression in SK-N-SH cells are enriched in genes implicated in autism spectrum disorder, but not in gene sets related to cancer or Alzheimer's disease. Weighted gene co-expression network analysis (WGCNA) was used to detect modules of co-expressed protein coding and noncoding RNAs in SK-N-SH cells and found four modules to be associated with neural differentiation. These modules contain varying levels of noncoding RNAs ranging from 10.7 to 49.7% with gene ontology suggesting roles in numerous cellular processes important for differentiation. These results indicate that noncoding RNAs are highly expressed in human neural progenitor cells and likely hold key regulatory roles in gene networks underlying neural differentiation and neurodevelopmental disorders. Frontiers Media S.A. 2015-10-23 /pmc/articles/PMC4615820/ /pubmed/26557050 http://dx.doi.org/10.3389/fnins.2015.00392 Text en Copyright © 2015 Hecht, Ballesteros-Yanez, Grepo, Knowles and Campbell. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Hecht, Patrick M.
Ballesteros-Yanez, Inmaculada
Grepo, Nicole
Knowles, James A.
Campbell, Daniel B.
Noncoding RNA in the transcriptional landscape of human neural progenitor cell differentiation
title Noncoding RNA in the transcriptional landscape of human neural progenitor cell differentiation
title_full Noncoding RNA in the transcriptional landscape of human neural progenitor cell differentiation
title_fullStr Noncoding RNA in the transcriptional landscape of human neural progenitor cell differentiation
title_full_unstemmed Noncoding RNA in the transcriptional landscape of human neural progenitor cell differentiation
title_short Noncoding RNA in the transcriptional landscape of human neural progenitor cell differentiation
title_sort noncoding rna in the transcriptional landscape of human neural progenitor cell differentiation
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4615820/
https://www.ncbi.nlm.nih.gov/pubmed/26557050
http://dx.doi.org/10.3389/fnins.2015.00392
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