Filter
Associated Lab
- Aguilera Castrejon Lab (15) Apply Aguilera Castrejon Lab filter
- Ahrens Lab (57) Apply Ahrens Lab filter
- Aso Lab (39) Apply Aso Lab filter
- Baker Lab (38) Apply Baker Lab filter
- Betzig Lab (111) Apply Betzig Lab filter
- Beyene Lab (10) Apply Beyene Lab filter
- Bock Lab (17) Apply Bock Lab filter
- Branson Lab (48) Apply Branson Lab filter
- Card Lab (40) Apply Card Lab filter
- Cardona Lab (63) Apply Cardona Lab filter
- Chklovskii Lab (13) Apply Chklovskii Lab filter
- Clapham Lab (13) Apply Clapham Lab filter
- Cui Lab (19) Apply Cui Lab filter
- Darshan Lab (12) Apply Darshan Lab filter
- Dennis Lab (1) Apply Dennis Lab filter
- Dickson Lab (46) Apply Dickson Lab filter
- Druckmann Lab (25) Apply Druckmann Lab filter
- Dudman Lab (46) Apply Dudman Lab filter
- Eddy/Rivas Lab (30) Apply Eddy/Rivas Lab filter
- Egnor Lab (11) Apply Egnor Lab filter
- Espinosa Medina Lab (16) Apply Espinosa Medina Lab filter
- Feliciano Lab (6) Apply Feliciano Lab filter
- Fetter Lab (41) Apply Fetter Lab filter
- Fitzgerald Lab (28) Apply Fitzgerald Lab filter
- Freeman Lab (15) Apply Freeman Lab filter
- Funke Lab (35) Apply Funke Lab filter
- Gonen Lab (91) Apply Gonen Lab filter
- Grigorieff Lab (62) Apply Grigorieff Lab filter
- Harris Lab (58) Apply Harris Lab filter
- Heberlein Lab (94) Apply Heberlein Lab filter
- Hermundstad Lab (22) Apply Hermundstad Lab filter
- Hess Lab (72) Apply Hess Lab filter
- Ilanges Lab (1) Apply Ilanges Lab filter
- Jayaraman Lab (44) Apply Jayaraman Lab filter
- Ji Lab (33) Apply Ji Lab filter
- Johnson Lab (6) Apply Johnson Lab filter
- Kainmueller Lab (19) Apply Kainmueller Lab filter
- Karpova Lab (14) Apply Karpova Lab filter
- Keleman Lab (13) Apply Keleman Lab filter
- Keller Lab (75) Apply Keller Lab filter
- Koay Lab (17) Apply Koay Lab filter
- Lavis Lab (138) Apply Lavis Lab filter
- Lee (Albert) Lab (34) Apply Lee (Albert) Lab filter
- Leonardo Lab (23) Apply Leonardo Lab filter
- Li Lab (27) Apply Li Lab filter
- Lippincott-Schwartz Lab (161) Apply Lippincott-Schwartz Lab filter
- Liu (Yin) Lab (5) Apply Liu (Yin) Lab filter
- Liu (Zhe) Lab (61) Apply Liu (Zhe) Lab filter
- Looger Lab (137) Apply Looger Lab filter
- Magee Lab (49) Apply Magee Lab filter
- Menon Lab (18) Apply Menon Lab filter
- Murphy Lab (13) Apply Murphy Lab filter
- O'Shea Lab (6) Apply O'Shea Lab filter
- Otopalik Lab (13) Apply Otopalik Lab filter
- Pachitariu Lab (42) Apply Pachitariu Lab filter
- Pastalkova Lab (18) Apply Pastalkova Lab filter
- Pavlopoulos Lab (19) Apply Pavlopoulos Lab filter
- Pedram Lab (14) Apply Pedram Lab filter
- Podgorski Lab (16) Apply Podgorski Lab filter
- Reiser Lab (49) Apply Reiser Lab filter
- Riddiford Lab (44) Apply Riddiford Lab filter
- Romani Lab (41) Apply Romani Lab filter
- Rubin Lab (139) Apply Rubin Lab filter
- Saalfeld Lab (61) Apply Saalfeld Lab filter
- Satou Lab (16) Apply Satou Lab filter
- Scheffer Lab (36) Apply Scheffer Lab filter
- Schreiter Lab (62) Apply Schreiter Lab filter
- Sgro Lab (20) Apply Sgro Lab filter
- Shroff Lab (24) Apply Shroff Lab filter
- Simpson Lab (23) Apply Simpson Lab filter
- Singer Lab (80) Apply Singer Lab filter
- Spruston Lab (91) Apply Spruston Lab filter
- Stern Lab (152) Apply Stern Lab filter
- Sternson Lab (54) Apply Sternson Lab filter
- Stringer Lab (29) Apply Stringer Lab filter
- Svoboda Lab (135) Apply Svoboda Lab filter
- Tebo Lab (31) Apply Tebo Lab filter
- Tervo Lab (9) Apply Tervo Lab filter
- Tillberg Lab (17) Apply Tillberg Lab filter
- Tjian Lab (64) Apply Tjian Lab filter
- Truman Lab (88) Apply Truman Lab filter
- Turaga Lab (46) Apply Turaga Lab filter
- Turner Lab (35) Apply Turner Lab filter
- Vale Lab (6) Apply Vale Lab filter
- Voigts Lab (2) Apply Voigts Lab filter
- Wang (Meng) Lab (10) Apply Wang (Meng) Lab filter
- Wang (Shaohe) Lab (24) Apply Wang (Shaohe) Lab filter
- Wu Lab (9) Apply Wu Lab filter
- Zlatic Lab (28) Apply Zlatic Lab filter
- Zuker Lab (25) Apply Zuker Lab filter
Associated Project Team
- CellMap (6) Apply CellMap filter
- COSEM (3) Apply COSEM filter
- Fly Descending Interneuron (10) Apply Fly Descending Interneuron filter
- Fly Functional Connectome (14) Apply Fly Functional Connectome filter
- Fly Olympiad (5) Apply Fly Olympiad filter
- FlyEM (51) Apply FlyEM filter
- FlyLight (46) Apply FlyLight filter
- GENIE (40) Apply GENIE filter
- Integrative Imaging (1) Apply Integrative Imaging filter
- Larval Olympiad (2) Apply Larval Olympiad filter
- MouseLight (16) Apply MouseLight filter
- NeuroSeq (1) Apply NeuroSeq filter
- ThalamoSeq (1) Apply ThalamoSeq filter
- Tool Translation Team (T3) (24) Apply Tool Translation Team (T3) filter
- Transcription Imaging (49) Apply Transcription Imaging filter
Publication Date
- 2024 (170) Apply 2024 filter
- 2023 (171) Apply 2023 filter
- 2022 (192) Apply 2022 filter
- 2021 (193) Apply 2021 filter
- 2020 (196) Apply 2020 filter
- 2019 (202) Apply 2019 filter
- 2018 (232) Apply 2018 filter
- 2017 (217) Apply 2017 filter
- 2016 (209) Apply 2016 filter
- 2015 (252) Apply 2015 filter
- 2014 (236) Apply 2014 filter
- 2013 (194) Apply 2013 filter
- 2012 (190) Apply 2012 filter
- 2011 (190) Apply 2011 filter
- 2010 (161) Apply 2010 filter
- 2009 (158) Apply 2009 filter
- 2008 (140) Apply 2008 filter
- 2007 (106) Apply 2007 filter
- 2006 (92) Apply 2006 filter
- 2005 (67) Apply 2005 filter
- 2004 (57) Apply 2004 filter
- 2003 (58) Apply 2003 filter
- 2002 (39) Apply 2002 filter
- 2001 (28) Apply 2001 filter
- 2000 (29) Apply 2000 filter
- 1999 (14) Apply 1999 filter
- 1998 (18) Apply 1998 filter
- 1997 (16) Apply 1997 filter
- 1996 (10) Apply 1996 filter
- 1995 (18) Apply 1995 filter
- 1994 (12) Apply 1994 filter
- 1993 (10) Apply 1993 filter
- 1992 (6) Apply 1992 filter
- 1991 (11) Apply 1991 filter
- 1990 (11) Apply 1990 filter
- 1989 (6) Apply 1989 filter
- 1988 (1) Apply 1988 filter
- 1987 (7) Apply 1987 filter
- 1986 (4) Apply 1986 filter
- 1985 (5) Apply 1985 filter
- 1984 (2) Apply 1984 filter
- 1983 (2) Apply 1983 filter
- 1982 (3) Apply 1982 filter
- 1981 (3) Apply 1981 filter
- 1980 (1) Apply 1980 filter
- 1979 (1) Apply 1979 filter
- 1976 (2) Apply 1976 filter
- 1973 (1) Apply 1973 filter
- 1970 (1) Apply 1970 filter
- 1967 (1) Apply 1967 filter
Type of Publication
3945 Publications
Showing 1181-1190 of 3945 resultsThe nearly constant downward force of gravity has powerfully shaped the behaviors of many organisms [1]. Walking flies readily orient against gravity in a behavior termed negative gravitaxis. In Drosophila this behavior is studied by observing the position of flies in vials [2–4] or simple mazes [5–9]. These assays have been used to conduct forward-genetic screens [5, 6, 8] and as simple tests of locomotion deficits [10–12]. Despite this long history of investigation, the sensory basis of gravitaxis is largely unknown [1]. Recent studies have implicated the antennae as a major mechanosensory input [3, 4], but many details remain unclear. Fly orientation behavior is expected to depend on the direction and amplitude of the gravitational pull, but little is known about the sensitivity of flies to these features of the environment. Here we directly measure the gravity-dependent orientation behavior of flies walking on an adjustable tilted platform, that is inspired by previous insect studies [13–16]. In this arena, flies can freely orient with respect to gravity. Our findings indicate that flies are exquisitely sensitive to the direction of gravity’s pull. Surprisingly, this orientation behavior does not require antennal mechanosensory input, suggesting that other sensory structures must be involved.
Among many achievements in the neurodegeneration field in the past decade, two require special attention due to the huge impact on our understanding of molecular and cellular pathogenesis of human neurodegenerative diseases. First is defining specific mutations in familial neurodegenerative diseases and second is modeling these diseases in easily manipulable model organisms including the fruit fly, nematode, and yeast. The power of these genetic systems has revealed many genetic factors involved in the various pathways affected, as well as provided potential drug targets for therapeutics. This review focuses on fruit fly models of human neurodegenerative diseases, with emphasis on how fly models have provided new insights into various aspects of human diseases.
Neurobiologists address neural structure, development, and function at the level of "macrocircuits" (how different brain compartments are interconnected; what overall pattern of activity they produce) and at the level of "microcircuits" (how connectivity and physiology of individual neurons and their processes within a compartment determine the functional output of this compartment). Work in our lab aims at reconstructing the developing Drosophila brain at both levels. Macrocircuits can be approached conveniently by reconstructing the pattern of brain lineages, which form groups of neurons whose projections form cohesive fascicles interconnecting the compartments of the larval and adult brain. The reconstruction of microcircuits requires serial section electron microscopy, due to the small size of terminal neuronal processes and their synaptic contacts. Because of the amount of labor that traditionally comes with this approach, very little is known about microcircuitry in brains across the animal kingdom. Many of the problems of serial electron microscopy reconstruction are now solvable with digital image recording and specialized software for both image acquisition and postprocessing. In this chapter, we introduce our efforts to reconstruct the small Drosophila larval brain and discuss our results in light of the published data on neuropile ultrastructure in other animal taxa.
We developed a multicolor neuron labeling technique in Drosophila melanogaster that combines the power to specifically target different neural populations with the label diversity provided by stochastic color choice. This adaptation of vertebrate Brainbow uses recombination to select one of three epitope-tagged proteins detectable by immunofluorescence. Two copies of this construct yield six bright, separable colors. We used Drosophila Brainbow to study the innervation patterns of multiple antennal lobe projection neuron lineages in the same preparation and to observe the relative trajectories of individual aminergic neurons. Nerve bundles, and even individual neurites hundreds of micrometers long, can be followed with definitive color labeling. We traced motor neurons in the subesophageal ganglion and correlated them to neuromuscular junctions to identify their specific proboscis muscle targets. The ability to independently visualize multiple lineage or neuron projections in the same preparation greatly advances the goal of mapping how neurons connect into circuits.
Many insights into the molecular mechanisms underlying learning and memory have been elucidated through the use of simple behavioral assays in model organisms such as the fruit fly, Drosophila melanogaster. Drosophila is useful for understanding the basic neurobiology underlying cognitive deficits resulting from mutations in genes associated with human cognitive disorders, such as intellectual disability (ID) and autism. This work describes a methodology for testing learning and memory using a classic paradigm in Drosophilaknown as courtship conditioning. Male flies court females using a distinct pattern of easily recognizable behaviors. Premated females are not receptive to mating and will reject the male's copulation attempts. In response to this rejection, male flies reduce their courtship behavior. This learned reduction in courtship behavior is measured over time, serving as an indicator of learning and memory. The basic numerical output of this assay is the courtship index (CI), which is defined as the percentage of time that a male spends courting during a 10 min interval. The learning index (LI) is the relative reduction of CI in flies that have been exposed to a premated female compared to naïve flies with no previous social encounters. For the statistical comparison of LIs between genotypes, a randomization test with bootstrapping is used. To illustrate how the assay can be used to address the role of a gene relating to learning and memory, the pan-neuronal knockdown of Dihydroxyacetone phosphate acyltransferase (Dhap-at) was characterized here. The human ortholog of Dhap-at, glyceronephosphate O-acyltransferase (GNPT), is involved in rhizomelic chondrodysplasia punctata type 2, an autosomal-recessive syndrome characterized by severe ID. Using the courtship conditioning assay, it was determined that Dhap-at is required for long-term memory, but not for short-term memory. This result serves as a basis for further investigation of the underlying molecular mechanisms.
Long-term memory and synaptic plasticity are thought to require the synthesis of new proteins at activated synapses. The CPEB family of RNA binding proteins, including Drosophila Orb2, has been implicated in this process. The precise mechanism by which these molecules regulate memory formation is however poorly understood. We used gene targeting and site-specific transgenesis to specifically modify the endogenous orb2 gene in order to investigate its role in long-term memory formation. We show that the Orb2A and Orb2B isoforms, while both essential, have distinct functions in memory formation. These two isoforms have common glutamine-rich and RNA-binding domains, yet Orb2A uniquely requires the former and Orb2B the latter. We further show that Orb2A induces Orb2 complexes in a manner dependent upon both its glutamine-rich region and neuronal activity. We propose that Orb2B acts as a conventional CPEB to regulate transport and/or translation of specific mRNAs, whereas Orb2A acts in an unconventional manner to form stable Orb2 complexes that are essential for memory to persist.
The doublesex (dsx) gene regulates somatic sexual differentiation in both sexes in D. melanogaster. Two functional products are encoded by dsx: one product is expressed in females and represses male differentiation, and the other is expressed in males and represses female differentiation. We have determined that the dsx gene is transcribed to produce a common primary transcript that is alternatively spliced and polyadenylated to yield male- and female-specific mRNAs. These sex-specific mRNAs share a common 5' end and three common exons, but possess alternative sex-specific 3' exons, thus encoding polypeptides with a common amino-terminal sequence but sex-specific carboxyl termini. Genetic and molecular data suggest that sequences including and adjacent to the female-specific splice acceptor site play an important role in the regulation of dsx expression by the transformer and transformer-2 loci.
Axon bifurcation results in the formation of sister branches, and divergent segregation of the sister branches is essential for efficient innervation of multiple targets. From a genetic mosaic screen, we find that a lethal mutation in the Drosophila Down syndrome cell adhesion molecule (Dscam) specifically perturbs segregation of axonal branches in the mushroom bodies. Single axon analysis further reveals that Dscam mutant axons generate additional branches, which randomly segregate among the available targets. Moreover, when only one target remains, branching is suppressed in wild-type axons while Dscam mutant axons still form multiple branches at the original bifurcation point. Taken together, we conclude that Dscam controls axon branching and guidance such that a neuron can innervate multiple targets with minimal branching.
During the metamorphic reorganization of the insect central nervous system, the steroid hormone 20-hydroxyecdysone induces a wide spectrum of cellular responses including neuronal proliferation, maturation, cell death and the remodeling of larval neurons into their adult forms. In Drosophila, expression of specific ecdysone receptor (EcR) isoforms has been correlated with particular responses, suggesting that different EcR isoforms may govern distinct steroid-induced responses in these cells. We have used imprecise excision of a P element to create EcR deletion mutants that remove the EcR-B promoter and therefore should lack EcR-B1 and EcR-B2 expression but retain EcR-A expression. Most of these EcR-B mutant animals show defects in larval molting, arresting at the boundaries between the three larval stages, while a smaller percentage of EcR-B mutants survive into the early stages of metamorphosis. Remodeling of larval neurons at metamorphosis begins with the pruning back of larval-specific dendrites and occurs as these cells are expressing high levels of EcR-B1 and little EcR-A. This pruning response is blocked in the EcR-B mutants despite the fact that adult-specific neurons, which normally express only EcR-A, can progress in their development. These observations support the hypothesis that different EcR isoforms control cell-type-specific responses during remodeling of the nervous system at metamorphosis.