@article {69721, title = {A split-GAL4 driver line resource for Drosophila neuron types}, year = {2025}, month = {01/2025}, doi = {10.7554/elife.98405.3}, url = {http://dx.doi.org/10.7554/eLife.98405.3}, author = {Meissner, Geoffrey W and Vannan, Allison and Jeter, Jennifer and Close, Kari and Depasquale, Gina M and Dorman, Zachary and Forster, Kaitlyn and Beringer, Jaye Anne and Gibney, Theresa V and Hausenfluck, Joanna H and He, Yisheng and Henderson, Kristin and Johnson, Lauren and Johnston, Rebecca M and Ihrke, Gudrun and Iyer, Nirmala and Lazarus, Rachel and Lee, Kelley and Li, Hsing-Hsi and Liaw, Hua-Peng and Melton, Brian and Miller, Scott and Motaher, Reeham and Novak, Alexandra and Ogundeyi, Omotara and Petruncio, Alyson and Price, Jacquelyn and Protopapas, Sophia and Tae, Susana and Taylor, Jennifer and Vorimo, Rebecca and Yarbrough, Brianna and Zeng, Kevin Xiankun and Zugates, Christopher T and Dionne, Heather and Angstadt, Claire and Ashley, Kelly and Cavallaro, Amanda and Dang, Tam and Gonzalez, Guillermo A and Hibbard, Karen L and Huang, Cuizhen and Kao, Jui-Chun and Laverty, Todd and Mercer, Monti and Perez, Brenda and Pitts, Scarlett and Ruiz, Danielle and Vallanadu, Viruthika and Zheng, Grace Zhiyu and Goina, Cristian and Otsuna, Hideo and Rokicki, Konrad and Svirskas, Robert R and Cheong, Han Sj and Dolan, Michael-John and Ehrhardt, Erica and Feng, Kai and El Galfi, Basel and Goldammer, Jens and Huston, Stephen J and Hu, Nan and Ito, Masayoshi and McKellar, Claire and minegishi, ryo and Namiki, Shigehiro and Nern, Aljoscha and Schretter, Catherine E and Sterne, Gabriella R and Venkatasubramanian, Lalanti and Wang, Kaiyu and Wolff, Tanya and Wu, Ming and George, Reed and Malkesman, Oz and Aso, Yoshinori and Card, Gwyneth M and Dickson, Barry J and Korff, Wyatt and Ito, Kei and Truman, James W and Zlatic, Marta and Rubin, Gerald M} } @article {68629, title = {A searchable image resource of Drosophila GAL4-driver expression patterns with single neuron resolution.}, journal = {eLife}, volume = {12}, year = {2023}, month = {2023 Feb 23}, 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.

}, issn = {2050-084X}, doi = {10.7554/eLife.80660}, author = {Meissner, Geoffrey Wilson and Nern, Aljoscha and Dorman, Zachary and Depasquale, Gina M and Forster, Kaitlyn and Gibney, Theresa and Hausenfluck, Joanna H and He, Yisheng and Iyer, Nirmala A and Jeter, Jennifer and Johnson, Lauren and Johnston, Rebecca M and Lee, Kelley and Melton, Brian and Yarbrough, Brianna and Zugates, Christopher T and Clements, Jody and Goina, Cristian and Otsuna, Hideo and Rokicki, Konrad and Svirskas, Robert R and Aso, Yoshinori and Card, Gwyneth M and Dickson, Barry J and Ehrhardt, Erica and Goldammer, Jens and Ito, Masayoshi and Kainmueller, Dagmar and Korff, Wyatt and Mais, Lisa and minegishi, ryo and Namiki, Shigehiro and Rubin, Gerald M and Sterne, Gabriella R and Wolff, Tanya and Malkesman, Oz} } @article {65816, title = {Cell types and neuronal circuitry underlying female aggression in Drosophila.}, journal = {eLife}, volume = {9}, year = {2020}, month = {2020 Nov 03}, abstract = {

Aggressive social interactions are used to compete for limited resources and are regulated by complex sensory cues and the organism{\textquoteright}s internal state. While both sexes exhibit aggression, its neuronal underpinnings are understudied in females. Here, we identify a population of sexually dimorphic aIPg neurons in the adult central brain whose optogenetic activation increased, and genetic inactivation reduced, female aggression. Analysis of GAL4 lines identified in an unbiased screen for increased female chasing behavior revealed the involvement of another sexually dimorphic neuron, pC1d, and implicated aIPg and pC1d neurons as core nodes regulating female aggression. Connectomic analysis demonstrated that aIPg neurons and pC1d are interconnected and suggest that aIPg neurons may exert part of their effect by gating the flow of visual information to descending neurons. Our work reveals important regulatory components of the neuronal circuitry that underlies female aggressive social interactions and provides tools for their manipulation.

}, issn = {2050-084X}, doi = {10.7554/eLife.58942}, author = {Schretter, Catherine E and Aso, Yoshi and Robie, Alice A and Dreher, Marisa and Dolan, Michael-John and Chen, Nan and Ito, Masayoshi and Yang, Tansy and Parekh, Ruchi and Branson, Kristin M and Rubin, Gerald M} } @article {68507, title = {A connectome and analysis of the adult Drosophila central brain.}, journal = {Elife}, volume = {9}, year = {2020}, month = {2020 Sep 07}, abstract = {

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly . Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly{\textquoteright}s brain.

}, keywords = {Animals, Brain, Connectome, Drosophila melanogaster, Female, Male, Neurons, Synapses}, issn = {2050-084X}, doi = {10.7554/eLife.57443}, author = {Scheffer, Louis K and Xu, C Shan and Januszewski, Michal and Lu, Zhiyuan and Takemura, Shin-ya and Hayworth, Kenneth J and Huang, Gary B and Shinomiya, Kazunori and Maitlin-Shepard, Jeremy and Berg, Stuart and Clements, Jody and Hubbard, Philip M and Katz, William T and Umayam, Lowell and Zhao, Ting and Ackerman, David and Blakely, Tim and Bogovic, John and Dolafi, Tom and Kainmueller, Dagmar and Kawase, Takashi and Khairy, Khaled A and Leavitt, Laramie and Li, Peter H and Lindsey, Larry and Neubarth, Nicole and Olbris, Donald J and Otsuna, Hideo and Trautman, Eric T and Ito, Masayoshi and Bates, Alexander S and Goldammer, Jens and Wolff, Tanya and Svirskas, Robert and Schlegel, Philipp and Neace, Erika and Knecht, Christopher J and Alvarado, Chelsea X and Bailey, Dennis A and Ballinger, Samantha and Borycz, Jolanta A and Canino, Brandon S and Cheatham, Natasha and Cook, Michael and Dreher, Marisa and Duclos, Octave and Eubanks, Bryon and Fairbanks, Kelli and Finley, Samantha and Forknall, Nora and Francis, Audrey and Hopkins, Gary Patrick and Joyce, Emily M and Kim, SungJin and Kirk, Nicole A and Kovalyak, Julie and Lauchie, Shirley A and Lohff, Alanna and Maldonado, Charli and Manley, Emily A and McLin, Sari and Mooney, Caroline and Ndama, Miatta and Ogundeyi, Omotara and Okeoma, Nneoma and Ordish, Christopher and Padilla, Nicholas and Patrick, Christopher M and Paterson, Tyler and Phillips, Elliott E and Phillips, Emily M and Rampally, Neha and Ribeiro, Caitlin and Robertson, Madelaine K and Rymer, Jon Thomson and Ryan, Sean M and Sammons, Megan and Scott, Anne K and Scott, Ashley L and Shinomiya, Aya and Smith, Claire and Smith, Kelsey and Smith, Natalie L and Sobeski, Margaret A and Suleiman, Alia and Swift, Jackie and Takemura, Satoko and Talebi, Iris and Tarnogorska, Dorota and Tenshaw, Emily and Tokhi, Temour and Walsh, John J and Yang, Tansy and Horne, Jane Anne and Li, Feng and Parekh, Ruchi and Rivlin, Patricia K and Jayaraman, Vivek and Costa, Marta and Jefferis, Gregory Sxe and Ito, Kei and Saalfeld, Stephan and George, Reed and Meinertzhagen, Ian A and Rubin, Gerald M and Hess, Harald F and Jain, Viren and Plaza, Stephen M} } @article {65382, title = {Conservation and divergence of related neuronal lineages in the central brain.}, journal = {eLife}, volume = {9}, year = {2020}, month = {2020 Apr 07}, abstract = {

Wiring a complex brain requires many neurons with intricate cell specificity, generated by a limited number of neural stem cells. central brain lineages are a predetermined series of neurons, born in a specific order. To understand how lineage identity translates to neuron morphology, we mapped 18 central brain lineages. While we found large aggregate differences between lineages, we also discovered shared patterns of morphological diversification. Lineage identity plus Notch-mediated sister fate govern primary neuron trajectories, whereas temporal fate diversifies terminal elaborations. Further, morphological neuron types may arise repeatedly, interspersed with other types. Despite the complexity, related lineages produce similar neuron types in comparable temporal patterns. Different stem cells even yield two identical series of dopaminergic neuron types, but with unrelated sister neurons. Together, these phenomena suggest that straightforward rules drive incredible neuronal complexity, and that large changes in morphology can result from relatively simple fating mechanisms.

}, issn = {2050-084X}, doi = {10.7554/eLife.53518}, author = {Lee, Ying-Jou and Yang, Ching-Po and Miyares, Rosa L and Huang, Yu-Fen and He, Yisheng and Ren, Qingzhong and Chen, Hui-Min and Kawase, Takashi and Ito, Masayoshi and Otsuna, Hideo and Sugino, Ken and Aso, Yoshi and Ito, Kei and Lee, Tzumin} } @article {65314, title = {Input connectivity reveals additional heterogeneity of dopaminergic reinforcement in Drosophila}, journal = {Current Biology}, volume = {30}, year = {2020}, month = {2020 Aug 17}, pages = {3200-11}, abstract = {

Different types of\ Drosophila\ dopaminergic neurons (DANs) reinforce memories of unique valence and provide state-dependent motivational control [1]. Prior studies suggest that the compartment architecture of the mushroom body (MB) is the relevant resolution for distinct DAN functions [2,\ 3]. Here we used a recent electron microscope volume of the fly brain [4] to reconstruct the fine anatomy of individual DANs within three MB compartments. We find the 20 DANs of the γ5 compartment, at least some of which provide reward teaching signals, can be clustered into 5 anatomical subtypes that innervate different regions within γ5. Reconstructing 821 upstream neurons reveals input selectivity, supporting the functional relevance of DAN sub-classification. Only one PAM-γ5 DAN subtype (γ5fb) receives direct recurrent input from γ5β{\textquoteright}2a mushroom body output neurons (MBONs) and behavioral experiments distinguish a role for these DANs in memory revaluation from those reinforcing sugar memory. Other DAN subtypes receive major, and potentially reinforcing, inputs from putative gustatory interneurons or lateral horn neurons, which can also relay indirect feedback from the MB. We similarly reconstructed the single aversively reinforcing PPL1-γ1pedc DAN. The γ1pedc DAN inputs are mostly different to those of γ5 DANs and are clustered onto distinct branches of its dendritic tree, presumably separating its established roles in aversive reinforcement and appetitive motivation [5,\ 6]. Additional tracing identified neurons that provide broad input to γ5, β{\textquoteright}2a and γ1pedc DANs suggesting that distributed DAN populations can be coordinately regulated. These connectomic and behavioral analyses therefore reveal additional complexity of dopaminergic reinforcement circuits between and within MB compartments.

}, author = {Otto, Nils and Pleijzier, Markus W. and Morgan, Isabel C. and Edmondson-Stait, Amelia J and Heinz, Konrad J. and Stark, Ildiko and Dempsey, Georgia and Ito, Masayoshi and Kapoor, Ishaan and Hsu, Joseph and Schlegel, Philipp M. and Bates, Alexander S. and Costa, Marta and Ito, Kei and Bock, Davi D. and Rubin, Gerald M. and Jefferis, Gregory S.X.E. and Waddell, Scott} } @article {65910, title = {An unbiased template of the Drosophila brain and ventral nerve cord.}, journal = {PLoS One}, volume = {15}, year = {2020}, month = {2020 Dec 31}, pages = {e0236495}, abstract = {

The fruit fly Drosophila melanogaster is an important model organism for neuroscience with a wide array of genetic tools that enable the mapping of individual neurons and neural subtypes. Brain templates are essential for comparative biological studies because they enable analyzing many individuals in a common reference space. Several central brain templates exist for Drosophila, but every one is either biased, uses sub-optimal tissue preparation, is imaged at low resolution, or does not account for artifacts. No publicly available Drosophila ventral nerve cord template currently exists. In this work, we created high-resolution templates of the Drosophila brain and ventral nerve cord using the best-available technologies for imaging, artifact correction, stitching, and template construction using groupwise registration. We evaluated our central brain template against the four most competitive, publicly available brain templates and demonstrate that ours enables more accurate registration with fewer local deformations in shorter time.

}, issn = {1932-6203}, doi = {10.1371/journal.pone.0236495}, author = {Bogovic, John A and Otsuna, Hideo and Heinrich, Larissa and Ito, Masayoshi and Jeter, Jennifer and Meissner, Geoffrey and Nern, Aljoscha and Colonell, Jennifer and Malkesman, Oz and Ito, Kei and Saalfeld, Stephan} } @article {49236, title = {Color depth MIP mask search: a new tool to expedite Split-GAL4 creation.}, journal = {bioRxiv}, year = {2018}, month = {2018 May 09}, abstract = {

The GAL4-UAS system has proven its versatility in studying the function and expression patterns of neurons the Drosophila central nervous system. Although the GAL4 system has been used for 25 years, recent genetic intersectional tools have enabled genetic targeting of very small numbers of neurons aiding in the understanding of their function. This split-GAL4 system is extremely powerful for studying neuronal morphology and the neural basis of animal behavior. However, choosing lines to intersect that have overlapping patterns restricted to one to a few neurons has been cumbersome. This challenge is now growing as the collections of GAL4 driver lines has increased. Here we present a new method and software plug-in for Fiji to dramatically improve the speed of querying large databases of potential lines to intersect and aid in the split-GAL4 creation. We also provide pre-computed datasets for the Janelia GAL4 (5,738 lines) and VT GAL4 (7,429 lines) of the Drosophila central nervous system (CNS). The tool reduced our split-GAL4 creation effort dramatically.

}, doi = {10.1101/318006}, author = {Otsuna, Hideo and Ito, Masayoshi and Kawase, Takashi} } @article {49386, title = {An unbiased template of the Drosophila brain and ventral nerve cord.}, journal = {bioRxiv}, year = {2018}, month = {2018 Jul 25}, abstract = {

The fruit fly Drosophila melanogaster is an important model organism for neuroscience with a wide array of genetic tools that enable the mapping of individuals neurons and neural subtypes. Brain templates are essential for comparative biological studies because they enable analyzing many individuals in a common reference space. Several central brain templates exist for Drosophila, but every one is either biased, uses sub-optimal tissue preparation, is imaged at low resolution, or does not account for artifacts. No publicly available Drosophila ventral nerve cord template currently exists. In this work, we created high-resolution templates of the Drosophila brain and ventral nerve cord using the best-available technologies for imaging, artifact correction, stitching, and template construction using groupwise registration. We evaluated our central brain template against the four most competitive, publicly available brain templates and demonstrate that ours enables more accurate registration with fewer local deformations in shorter time.

}, doi = {10.1101/376384}, author = {Bogovic, John A and Otsuna, Hideo and Heinrich, Larissa and Ito, Masayoshi and Jeter, Jennifer and Meissner, Geoffrey W and Nern, Aljoscha and Colonell, Jennifer and Malkesman, Oz and Saalfeld, Stephan} } @inbook {48701, title = {Recent progress in the 3D reconstruction of Drosophila neural circuits.}, booktitle = {Decoding Neural Circuit Structure and Function}, year = {2017}, pages = {63-89}, publisher = {Springer}, organization = {Springer}, abstract = {

The brain of fruit fly Drosophila melanogaster has been used as a model system for functional analysis of neuronal circuits, including connectomics research, due to its modest size (~700\ μm) and availability of abundant molecular genetics tools for visualizing neurons. Three-dimensional (3D) reconstruction of high-resolution images of neurons or circuits visualized with appropriate methods is a critical step for obtaining information such as morphology and connectivity patterns of neuronal circuits. In this chapter, we introduce methods for generating 3D reconstructed images with data acquired from confocal laser scanning microscopy (CLSM) or electron microscopy (EM) to analyze neuronal circuits found in the central nervous system (CNS) of the fruit fly. Comparisons of different algorithms and strategies for reconstructing neuronal circuits, using actual studies as references, will be discussed within this chapter.

}, doi = {10.1007/978-3-319-57363-2_3}, author = {Shinomiya, Kazunori and Ito, Masayoshi} } @article {48435, title = {Stem cell-intrinsic, seven-up-triggered temporal factor gradients diversify intermediate neural progenitors.}, journal = {Current Biology : CB}, volume = {27}, year = {2017}, month = {2017 Apr 10}, pages = {1303-13}, abstract = {

Building a sizable, complex brain requires both cellular expansion and diversification. One mechanism to achieve these goals is production of multiple transiently amplifying intermediate neural progenitors (INPs) from a single neural stem cell. Like mammalian neural stem cells, Drosophila type II neuroblasts utilize INPs to produce neurons and glia. Within a given lineage, the consecutively born INPs produce morphologically distinct progeny, presumably due to differential inheritance of temporal factors. To uncover the underlying temporal fating mechanisms, we profiled type II neuroblasts{\textquoteright} transcriptome across time. Our results reveal opposing temporal gradients of Imp and Syp RNA-binding proteins (descending and ascending, respectively). Maintaining high Imp throughout serial INP production expands the number of neurons and glia with early temporal fate at the expense of cells with late fate. Conversely, precocious upregulation of Syp reduces the number of cells with early fate. Furthermore, we reveal that the transcription factor Seven-up initiates progression of the Imp/Syp gradients. Interestingly, neuroblasts that maintain initial Imp/Syp levels can still yield progeny with a small range of early fates. We therefore propose that the Seven-up-initiated Imp/Syp gradients create coarse temporal windows within type II neuroblasts to pattern INPs, which subsequently undergo fine-tuned subtemporal patterning.

}, issn = {1879-0445}, doi = {10.1016/j.cub.2017.03.047}, author = {Ren, Qingzhong and Yang, Ching-Po and Liu, Zhiyong and Sugino, Ken and Mok, Kent and He, Yisheng and Ito, Masayoshi and Nern, Aljoscha and Otsuna, Hideo and Lee, Tzumin} } @article {6884, title = {A systematic nomenclature for the insect brain.}, journal = {Neuron}, volume = {81}, year = {2014}, month = {2014 Feb 19}, pages = {755-65}, abstract = {

Despite the importance of the insect nervous system for functional and developmental neuroscience, descriptions of insect brains have suffered from a lack of uniform nomenclature. Ambiguous definitions of brain regions and fiber bundles have contributed to the variation of names used to describe the same structure. The lack of clearly determined neuropil boundaries has made it difficult to document precise locations of neuronal projections for connectomics study. To address such issues, a consortium of\ neurobiologists studying arthropod brains, the Insect Brain Name Working Group, has established the present hierarchical nomenclature system, using the brain of Drosophila melanogaster as the reference framework, while taking the brains of other taxa into careful consideration for maximum consistency and expandability. The following summarizes the consortium{\textquoteright}s nomenclature system and highlights examples of existing ambiguities and remedies for them. This nomenclature is intended to serve as a\ standard of reference for the study of the brain of Drosophila and other insects.

}, issn = {1097-4199}, doi = {10.1016/j.neuron.2013.12.017}, author = {Ito, Kei and Shinomiya, Kazunori and Ito, Masayoshi and Armstrong, J Douglas and Boyan, George and Hartenstein, Volker and Harzsch, Steffen and Heisenberg, Martin and Homberg, Uwe and Jenett, Arnim and Keshishian, Haig and Restifo, Linda L and R{\"o}ssler, Wolfgang and Simpson, Julie H and Strausfeld, Nicholas J and Strauss, Roland and Vosshall, Leslie B} }