Current BiologyNeurosciencePeer-reviewed journal article
The marked diversity of unique cortical enhancers enables neuron-specific tools by Enhancer-Driven Gene Expression
Stefan BlankvoortiD, Menno P. WitteriD, James P. NoonaniD, Justin L. CotneyiD, Clifford G. KentrosiD
Abstract
Understanding neural circuit function requires individually addressing their component parts: specific neuronal cell types. However, not only do the precise genetic mechanisms specifying neuronal cell types remain obscure, access to these neuronal cell types by transgenic techniques also remains elusive. While most genes are expressed in the brain, the vast majority are expressed in many different kinds of neurons, suggesting that promoters alone are not sufficiently specific to distinguish cell types. However, there are orders of magnitude more distal genetic cis-regulatory elements controlling transcription (i.e. enhancers), so we screened for enhancer activity in microdissected samples of mouse cortical subregions. This identified thousands of novel putative enhancers, many unique to particular cortical subregions. Pronuclear injection of expression constructs containing such region-specific enhancers resulted in transgenic lines driving expression in distinct sets of cells specifically in the targeted cortical subregions, even though the parent genes promoter was relatively nonspecific. These data showcase the promise of utilizing the genetic mechanisms underlying the specification of diverse neuronal cell types for the development of genetic tools potentially capable of targeting any neuronal circuit of interest, an approach we call Enhancer-Driven Gene Expression (EDGE).\n\nHighlightsO_LIEnhancer ChIP-seq of cortical subregions reveals 59372 putative enhancers.\nC_LIO_LI3740 of these are specific to particular cortical subregions.\nC_LIO_LIThis reflects the remarkable anatomical diversity of the adult cortex.\nC_LIO_LIUnique enhancers provide a means to make targeted cell-type specific genetic tools.\nC_LI
- organism: mouse
- assay: ChIP-seq
- research focus: cell type annotation
- research focus: software / tool
- research focus: benchmarking
- approach: experimental assay
- Citations
- 72
- FWCI
- 3.29
- Field percentile
- top 6%
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