A mammalian enhancer trap resource for discovering and manipulating neuronal cell types
- Brandeis University, United States
- Janelia Research Campus, Howard Hughes Medical Institute, United States
- Galenea Corporation, United States
- California Institute of Technology, United States
Abstract
There is a continuing need for driver strains to enable cell type-specific manipulation in the nervous system. Each cell type expresses a unique set of genes, and recapitulating expression of marker genes by BAC transgenesis or knock-in has generated useful transgenic mouse lines. However since genes are often expressed in many cell types, many of these lines have relatively broad expression patterns. We report an alternative transgenic approach capturing distal enhancers for more focused expression. We identified an enhancer trap probe often producing restricted reporter expression and developed efficient enhancer trap screening with the PiggyBac transposon. We established more than 200 lines and found many lines that label small subsets of neurons in brain substructures, including known and novel cell types. Images and other information about each line are available online (enhancertrap.bio.brandeis.edu).
Article and author information
Author details
Reviewing Editor
- Liqun Luo, Howard Hughes Medical Institute, Stanford University, United States
Ethics
Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols (#14004) of Brandeis University. All surgery was performed under ketamine and xylazine anesthesia, and every effort was made to minimize suffering.
Version history
- Received: December 3, 2015
- Accepted: March 18, 2016
- Accepted Manuscript published: March 21, 2016 (version 1)
- Accepted Manuscript updated: April 6, 2016 (version 2)
- Version of Record published: April 21, 2016 (version 3)
Copyright
© 2016, Shima et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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A mammalian enhancer trap resource for discovering and manipulating neuronal cell types
eLife 5:e13503.
https://doi.org/10.7554/eLife.13503
Further reading
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Probing memory of a complex visual image within a few hundred milliseconds after its disappearance reveals significantly greater fidelity of recall than if the probe is delayed by as little as a second. Classically interpreted, the former taps into a detailed but rapidly decaying visual sensory or ‘iconic’ memory (IM), while the latter relies on capacity-limited but comparatively stable visual working memory (VWM). While iconic decay and VWM capacity have been extensively studied independently, currently no single framework quantitatively accounts for the dynamics of memory fidelity over these time scales. Here, we extend a stationary neural population model of VWM with a temporal dimension, incorporating rapid sensory-driven accumulation of activity encoding each visual feature in memory, and a slower accumulation of internal error that causes memorized features to randomly drift over time. Instead of facilitating read-out from an independent sensory store, an early cue benefits recall by lifting the effective limit on VWM signal strength imposed when multiple items compete for representation, allowing memory for the cued item to be supplemented with information from the decaying sensory trace. Empirical measurements of human recall dynamics validate these predictions while excluding alternative model architectures. A key conclusion is that differences in capacity classically thought to distinguish IM and VWM are in fact contingent upon a single resource-limited WM store.
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- Neuroscience
Our ability to recall details from a remembered image depends on a single mechanism that is engaged from the very moment the image disappears from view.
