@article {69329, title = {A split-GAL4 driver line resource for Drosophila CNS cell types}, journal = {bioRxiv}, year = {2024}, month = {2024 Jan 10}, abstract = {

Techniques that enable precise manipulations of subsets of neurons in the fly central nervous system have greatly facilitated our understanding of the neural basis of behavior. Split-GAL4 driver lines allow specific targeting of cell types in Drosophila melanogaster and other species. We describe here a collection of 3060 lines targeting a range of cell types in the adult Drosophila central nervous system and 1373 lines characterized in third-instar larvae. These tools enable functional, transcriptomic, and proteomic studies based on precise anatomical targeting. NeuronBridge and other search tools relate light microscopy images of these split-GAL4 lines to connectomes reconstructed from electron microscopy images. The collections are the result of screening over 77,000 split hemidriver combinations. In addition to images and fly stocks for these well-characterized lines, we make available 300,000 new 3D images of other split-GAL4 lines.

}, doi = {10.1101/2024.01.09.574419}, url = {https://www.biorxiv.org/content/early/2024/04/01/2024.01.09.574419}, author = {Geoffrey W Meissner and Allison Vannan and Jennifer Jeter and Kari Close and Gina M DePasquale and Zachary Dorman and Kaitlyn Forster and Jaye Anne Beringer and Theresa V Gibney and Joanna H Hausenfluck and Yisheng He and Kristin Henderson and Lauren Johnson and Rebecca M Johnston and Gudrun Ihrke and Nirmala Iyer and Rachel Lazarus and Kelley Lee and Hsing-Hsi Li and Hua-Peng Liaw and Brian Melton and Scott Miller and Reeham Motaher and Alexandra Novak and Omotara Ogundeyi and Alyson Petruncio and Jacquelyn Price and Sophia Protopapas and Susana Tae and Jennifer Taylor and Rebecca Vorimo and Brianna Yarbrough and Kevin Xiankun Zeng and Christopher T Zugates and Heather Dionne and Claire Angstadt and Kelly Ashley and Amanda Cavallaro and Tam Dang and Guillermo A Gonzalez III and Karen L Hibbard and Cuizhen Huang and Jui-Chun Kao and Todd Laverty and Monti Mercer and Brenda Perez and Scarlett Pitts and Danielle Ruiz and Viruthika Vallanadu and Grace Zhiyu Zheng and Cristian Goina and Hideo Otsuna and Konrad Rokicki and Robert R Svirskas and Han SJ Cheong and Michael-John Dolan and Erica Ehrhardt and Kai Feng and Basel El Galfi and Jens Goldammer and Stephen J Huston and Nan Hu and Masayoshi Ito and Claire McKellar and Ryo Minegishi and Shigehiro Namiki and Aljoscha Nern and Catherine E Schretter and Gabriella R Sterne and Lalanti Venkatasubramanian and Kaiyu Wang and Tanya Wolff and Ming Wu and Reed George and Oz Malkesman and Yoshinori Aso and Gwyneth M Card and Barry J Dickson and Wyatt Korff and Kei Ito and James W Truman and Marta Zlatic and Gerald M Rubin and FlyLight Project Team} } @article {67907, title = {Ascending neurons convey behavioral state to integrative sensory and action selection centers in the brain}, journal = {Nature Neuroscience}, year = {2023}, month = {2023 Mar 31}, abstract = {

Knowledge of one{\textquoteright}s own behavioral state{\textemdash}whether one is walking, grooming, or resting{\textemdash}is critical for contextualizing sensory cues including interpreting visual motion and tracking odor sources. Additionally, awareness of one{\textquoteright}s own posture is important to avoid initiating destabilizing or physically impossible actions. Ascending neurons (ANs), interneurons in the vertebrate spinal cord or insect ventral nerve cord (VNC) that project to the brain, may provide such high-fidelity behavioral state signals. However, little is known about what ANs encode and where they convey signals in any brain. To address this gap, we performed a large-scale functional screen of AN movement encoding, brain targeting, and motor system patterning in the adult fly,\ Drosophila melanogaster. Using a new library of AN sparse driver lines, we measured the functional properties of 247 genetically-identifiable ANs by performing two-photon microscopy recordings of neural activity in tethered, behaving flies. Quantitative, deep network-based neural and behavioral analyses revealed that ANs nearly exclusively encode high-level behaviors{\textemdash}primarily walking as well as resting and grooming{\textemdash}rather than low-level joint or limb movements. ANs that convey self-motion{\textemdash}resting, walking, and responses to gust-like puff stimuli{\textemdash}project to the brain{\textquoteright}s anterior ventrolateral protocerebrum (AVLP), a multimodal, integrative sensory hub, while those that encode discrete actions{\textemdash}eye grooming, turning, and proboscis extension{\textemdash}project to the brain{\textquoteright}s gnathal ganglion (GNG), a locus for action selection. The structure and polarity of AN projections within the VNC are predictive of their functional encoding and imply that ANs participate in motor computations while also relaying state signals to the brain. Illustrative of this are ANs that temporally integrate proboscis extensions over tens-of-seconds, likely through recurrent interconnectivity. Thus, in line with long-held theoretical predictions, ascending populations convey high-level behavioral state signals almost exclusively to brain regions implicated in sensory feature contextualization and action selection.

}, doi = {10.1038/s41593-023-01281-z}, author = {Chin-Lin Chen and Florian Aymanns and Ryo Minegishi and Victor D. V. Matsuda and Nicolas Talabot and Semih G{\"u}nel and Barry J. Dickson and Pavan Ramdya} } @article {68799, title = {Single-cell type analysis of wing premotor circuits in the ventral nerve cord of Drosophila melanogaster}, journal = {bioRxiv}, year = {2023}, month = {2023 Jun 01}, abstract = {

To perform most behaviors, animals must send commands from higher-order processing centers in the brain to premotor circuits that reside in ganglia distinct from the brain, such as the mammalian spinal cord or insect ventral nerve cord. How these circuits are functionally organized to generate the great diversity of animal behavior remains unclear. An important first step in unraveling the organization of premotor circuits is to identify their constituent cell types and create tools to monitor and manipulate these with high specificity to assess their function. This is possible in the tractable ventral nerve cord of the fly. To generate such a toolkit, we used a combinatorial genetic technique (split-GAL4) to create 195 sparse driver lines targeting 198 individual cell types in the ventral nerve cord. These included wing and haltere motoneurons, modulatory neurons, and interneurons. Using a combination of behavioral, developmental, and anatomical analyses, we systematically characterized the cell types targeted in our collection. Taken together, the resources and results presented here form a powerful toolkit for future investigations of neural circuits and connectivity of premotor circuits while linking them to behavioral outputs.

}, doi = {10.1101/2023.05.31.542897}, url = {https://doi.org/10.1101/2023.05.31.542897}, author = {Erica Ehrhardt and Samuel C Whitehead and Shigehiro Namiki and Ryo Minegishi and Igor Siwanowicz and Kai Feng and Hideo Otsuna and FlyLight Project Team and Geoffrey W Meissner and David Stern and Jim Truman and David Shepherd and Michael H. Dickinson and Kei Ito and Barry J Dickson and Itai Cohen and Gwyneth M Card and Wyatt Korff} }