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| Item Type: | Article |
|---|---|
| Title: | A searchable image resource of Drosophila GAL4-driver expression patterns with single neuron resolution |
| Creators Name: | Meissner, G.W. and Nern, A. and Dorman, Z. and DePasquale, G.M. and Forster, K. and Gibney, T. and Hausenfluck, J.H. and He, Y. and Iyer, N.A. and Jeter, J. and Johnson, L. and Johnston, R.M. and Lee, K. and Melton, B. and Yarbrough, B. and Zugates, C.T. and Clements, Jody and Goina, C. and Otsuna, H. and Rokicki, K. and Svirskas, R.R. and Aso, Y. and Card, G.M. and Dickson, B.J. and Ehrhardt, E. and Goldammer, J. and Ito, M. and Kainmueller, D. and Korff, W. and Mais, L. and Minegishi, R. and Namiki, S. and Rubin, G.M. and Sterne, G.R. and Wolff, T. and Malkesman, O. |
| Abstract: | Precise, repeatable genetic access to specific neurons via GAL4/UAS and related methods is a key advantage of Drosophila neuroscience. Neuronal targeting is typically documented using light microscopy of full GAL4 expression patterns, which generally lack the single-cell resolution required for reliable cell type identification. Here we use stochastic GAL4 labeling with the MultiColor FlpOut approach to generate cellular resolution confocal images at large scale. We are releasing aligned images of 74,000 such adult central nervous systems. An anticipated use of this resource is to bridge the gap between neurons identified by electron or light microscopy. Identifying individual neurons that make up each GAL4 expression pattern improves the prediction of split-GAL4 combinations targeting particular neurons. To this end we have made the images searchable on the NeuronBridge website. We demonstrate the potential of NeuronBridge to rapidly and effectively identify neuron matches based on morphology across imaging modalities and datasets. |
| Keywords: | Central Nervous System, Drosophila Proteins, Drosophila melanogaster, Neurons, Neurosciences, Transcription Factors, Animals, Drosophila |
| Source: | eLife |
| ISSN: | 2050-084X |
| Publisher: | eLife Sciences Publications |
| Volume: | 12 |
| Page Range: | e80660 |
| Date: | 23 February 2023 |
| Official Publication: | https://doi.org/10.7554/eLife.80660 |
| PubMed: | View item in PubMed |
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