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Longitudinal RNA sequencing of the deep transcriptome during neurogenesis of cortical glutamatergic neurons from murine ESCs
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000Research
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3829120/ https://www.ncbi.nlm.nih.gov/pubmed/24358889 http://dx.doi.org/10.12688/f1000research.2-35.v1 |
Sumario: | 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. |
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