Cargando…

Nuclear RNA-seq of single neurons reveals molecular signatures of activation

Single-cell sequencing methods have emerged as powerful tools for identification of heterogeneous cell types within defined brain regions. Application of single-cell techniques to study the transcriptome of activated neurons can offer insight into molecular dynamics associated with differential neur...

Descripción completa

Detalles Bibliográficos
Autores principales: Lacar, Benjamin, Linker, Sara B., Jaeger, Baptiste N., Krishnaswami, Suguna, Barron, Jerika, Kelder, Martijn, Parylak, Sarah, Paquola, Apuã, Venepally, Pratap, Novotny, Mark, O'Connor, Carolyn, Fitzpatrick, Conor, Erwin, Jennifer, Hsu, Jonathan Y., Husband, David, McConnell, Michael J., Lasken, Roger, Gage, Fred H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4838832/
https://www.ncbi.nlm.nih.gov/pubmed/27090946
http://dx.doi.org/10.1038/ncomms11022
Descripción
Sumario:Single-cell sequencing methods have emerged as powerful tools for identification of heterogeneous cell types within defined brain regions. Application of single-cell techniques to study the transcriptome of activated neurons can offer insight into molecular dynamics associated with differential neuronal responses to a given experience. Through evaluation of common whole-cell and single-nuclei RNA-sequencing (snRNA-seq) methods, here we show that snRNA-seq faithfully recapitulates transcriptional patterns associated with experience-driven induction of activity, including immediate early genes (IEGs) such as Fos, Arc and Egr1. SnRNA-seq of mouse dentate granule cells reveals large-scale changes in the activated neuronal transcriptome after brief novel environment exposure, including induction of MAPK pathway genes. In addition, we observe a continuum of activation states, revealing a pseudotemporal pattern of activation from gene expression alone. In summary, snRNA-seq of activated neurons enables the examination of gene expression beyond IEGs, allowing for novel insights into neuronal activation patterns in vivo.