Longitudinal RNA sequencing of the deep transcriptome during neurogenesis of cortical glutamatergic neurons from murine ESCs [v1; ref status: indexed, http://f1000r.es/w2]

Using paired-end RNA sequencing, we have quantified the deep transcriptional changes that occur during differentiation of murine embryonic stem cells into a highly enriched population of glutamatergic cortical neurons. These data provide a detailed and nuanced account of longitudinal changes in the...

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Main Authors: Kyle S Hubbard, Ian M Gut, Megan E Lyman, Patrick M McNutt
Format: Article
Language:English
Published: F1000 Research Ltd 2013-02-01
Series:F1000Research
Subjects:
Online Access:http://f1000research.com/articles/2-35/v1
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spelling doaj-736f91bf9158451e857636959045c9b22020-11-25T03:30:21ZengF1000 Research LtdF1000Research2046-14022013-02-01210.12688/f1000research.2-35.v11154Longitudinal RNA sequencing of the deep transcriptome during neurogenesis of cortical glutamatergic neurons from murine ESCs [v1; ref status: indexed, http://f1000r.es/w2]Kyle S Hubbard0Ian M Gut1Megan E Lyman2Patrick M McNutt3United States Army, Medical Research Institute of Chemical Defense, MD, 21010, USAUnited States Army, Medical Research Institute of Chemical Defense, MD, 21010, USAUnited States Army, Medical Research Institute of Chemical Defense, MD, 21010, USAUnited States Army, Medical Research Institute of Chemical Defense, MD, 21010, USAUsing paired-end RNA sequencing, we have quantified the deep transcriptional changes that occur during differentiation of murine embryonic stem cells into a highly enriched population of glutamatergic cortical neurons. These data provide a detailed and nuanced account of longitudinal changes in the transcriptome during neurogenesis and neuronal maturation, starting from mouse embryonic stem cells and progressing through neuroepithelial stem cell induction, radial glial cell formation, neurogenesis, neuronal maturation and cortical patterning. Understanding the transcriptional mechanisms underlying the differentiation of stem cells into mature, glutamatergic neurons of cortical identity has myriad applications, including the elucidation of mechanisms of cortical patterning; identification of neurogenic processes; modeling of disease states; detailing of the host cell response to neurotoxic stimuli; and determination of potential therapeutic targets. In future work we anticipate correlating changes in longitudinal gene expression to other cell parameters, including neuronal function as well as characterizations of the proteome and metabolome. In this data article, we describe the methods used to produce the data and present the raw sequence read data in FASTQ files, sequencing run statistics and a summary flatfile of raw counts for 22,164 genes across 31 samples, representing 3-5 biological replicates at each timepoint. We propose that this data will be a valuable contribution to diverse research efforts in bioinformatics, stem cell research and developmental neuroscience studies.http://f1000research.com/articles/2-35/v1BioinformaticsNeurodevelopmentStem Cells & Regeneration
collection DOAJ
language English
format Article
sources DOAJ
author Kyle S Hubbard
Ian M Gut
Megan E Lyman
Patrick M McNutt
spellingShingle Kyle S Hubbard
Ian M Gut
Megan E Lyman
Patrick M McNutt
Longitudinal RNA sequencing of the deep transcriptome during neurogenesis of cortical glutamatergic neurons from murine ESCs [v1; ref status: indexed, http://f1000r.es/w2]
F1000Research
Bioinformatics
Neurodevelopment
Stem Cells & Regeneration
author_facet Kyle S Hubbard
Ian M Gut
Megan E Lyman
Patrick M McNutt
author_sort Kyle S Hubbard
title Longitudinal RNA sequencing of the deep transcriptome during neurogenesis of cortical glutamatergic neurons from murine ESCs [v1; ref status: indexed, http://f1000r.es/w2]
title_short Longitudinal RNA sequencing of the deep transcriptome during neurogenesis of cortical glutamatergic neurons from murine ESCs [v1; ref status: indexed, http://f1000r.es/w2]
title_full Longitudinal RNA sequencing of the deep transcriptome during neurogenesis of cortical glutamatergic neurons from murine ESCs [v1; ref status: indexed, http://f1000r.es/w2]
title_fullStr Longitudinal RNA sequencing of the deep transcriptome during neurogenesis of cortical glutamatergic neurons from murine ESCs [v1; ref status: indexed, http://f1000r.es/w2]
title_full_unstemmed Longitudinal RNA sequencing of the deep transcriptome during neurogenesis of cortical glutamatergic neurons from murine ESCs [v1; ref status: indexed, http://f1000r.es/w2]
title_sort longitudinal rna sequencing of the deep transcriptome during neurogenesis of cortical glutamatergic neurons from murine escs [v1; ref status: indexed, http://f1000r.es/w2]
publisher F1000 Research Ltd
series F1000Research
issn 2046-1402
publishDate 2013-02-01
description Using paired-end RNA sequencing, we have quantified the deep transcriptional changes that occur during differentiation of murine embryonic stem cells into a highly enriched population of glutamatergic cortical neurons. These data provide a detailed and nuanced account of longitudinal changes in the transcriptome during neurogenesis and neuronal maturation, starting from mouse embryonic stem cells and progressing through neuroepithelial stem cell induction, radial glial cell formation, neurogenesis, neuronal maturation and cortical patterning. Understanding the transcriptional mechanisms underlying the differentiation of stem cells into mature, glutamatergic neurons of cortical identity has myriad applications, including the elucidation of mechanisms of cortical patterning; identification of neurogenic processes; modeling of disease states; detailing of the host cell response to neurotoxic stimuli; and determination of potential therapeutic targets. In future work we anticipate correlating changes in longitudinal gene expression to other cell parameters, including neuronal function as well as characterizations of the proteome and metabolome. In this data article, we describe the methods used to produce the data and present the raw sequence read data in FASTQ files, sequencing run statistics and a summary flatfile of raw counts for 22,164 genes across 31 samples, representing 3-5 biological replicates at each timepoint. We propose that this data will be a valuable contribution to diverse research efforts in bioinformatics, stem cell research and developmental neuroscience studies.
topic Bioinformatics
Neurodevelopment
Stem Cells & Regeneration
url http://f1000research.com/articles/2-35/v1
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