Through the collaborative efforts of geneticists, histologists, anatomists, computer scientists, and software engineers, we are creating a database of GAL4 expression patterns in adults and third instar larvae, single-neuron morphologies, and developmental lineages. Our goal is to provide a set of well-characterized genetic tools and annotated data sets, with sophisticated visualization and annotation tools, that will enable the experimental and theoretical work of fly brain people.
The fly brain is a perplexing society of tens-of-thousands of interwoven cells in perpetual action, and although a comprehensive understanding of its organization is far off, we are approaching this goal with systematic experimentation at an ambitious scale. At the heart of Fly Light are large scale data production processes that enable us to highlight and examine cells at various points in the life of the fly. We do meticulous dissections of brain from cuticle, muscle, and other tissues, after which we label neurons with fluorescent dyes. We rely on highly automated imaging systems to create the images from which we will eventually make models of the brain. To deal with the complexity of the fly nervous system, and the concomitant enormity of the requisite data, we are developing computer algorithms to intelligently extract, compare, and catalogue neurons. Ultimately, we hope to turn pictures into interactive virtual brains that will help us discern roles for cell morphology, lineage, and connectivity in the fly’s life. We want to enable a genuine worldwide collaboration for understanding the structure, development and function of the fly nervous system.
- Annotate—in the adult and third instar larva—several thousand GAL4 driver lines that label different sets of neurons
- Establish a highly automated, robust pipeline that produces low-resolution confocal images of fly strains at several points in the life of the fly
- Assemble a complete catalog of single neuron morphologies of the fly central nervous system (larval and adult) by random labeling of neurons via DNA excision
- Assemble complete lineage maps for each stem cell in the fly central nervous system
- Devise algorithms to enable comparisons of transgene expression, neuron morphology, and lineage across tens of thousands of organisms
- Enable collaborative annotations and comparisons of imagery by experts
- Build searchable databases of light-level observations of fly brains that enable integration (to be accomplished in collaboration with our colleagues in the Fly Olympiad and Fly EM Project Teams) with behavioral assay, electron microscopy, and other data from laboratories around the world
To enable experimentation on the fly brain, the research field needs tools that label defined subsets of neurons. As a first step to providing this resource, we screened 7,200 GAL4 driver lines, constructed by the Rubin Lab, that each labels a subset of neurons. This has allowed us to triage those lines to a set of about 4,000 lines that each express in roughly 10 and 300 cells in the adult CNS and, in aggregate, appear to have several fold coverage of all neuronal cell types.
In collaboration with the Rubin (adult) and Truman (third instar larva) labs, we are generating a comprehensive set of single neuron morphologies using a simple stochastic labeling approach developed in the Rubin lab. Analysis and interpretation of these data utilizes neuron separation and tracing software developed in the Janelia laboratories of Eugene Myers and Hanchuan Peng groups and an annotation workbench developed by a team of software engineers led by Sean Murphy.
In addition to revealing the shapes of cells, transgenic techniques allow us to infer distributions of molecules, when each cell was born, and from which progenitor it came. Our goal is to apply these tools at a scale commensurate with the complexity of the brain. In collaboration with the laboratories of Tzumin Lee and James Truman here at Janelia, we are trying to sequence lineages and follow neuron morphology through development.
We envision that these activities will be synergistic in gaining an insight into how the brain is constructed and how it functions. Once we have neuron-resolution maps of cell shape and lineage for the entire fly nervous system we have plans to produce, integrate, and disseminate information about connectivity, neurotransmitter distributions, and cell activity.
Although transgenic tools will give us a rich catalogue of images, we will have to develop software to distill them into meaningful subsets. We (see Myers and Peng lab pages for details) are designing and applying software that can extract the shapes of myriad neurons and reassemble them into digital brains of our design. Thus, we can put neurons from different brains onto a standard map and use computer programs to investigate the likelihood that they form circuits. By assessing juxtapositions of tens of thousands of neurons, we hope to propose testable cellular networks.
In an effort led by Sean Murphy, the Fly Light Team Project is developing a workstation and annotation software package that enables researchers to review image data, run algorithms, display results in 3D, and add their knowledge to our database. With our new software tools, they will be able to trace and model neuron shapes, overlay data, and add notes to images, parts of neurons, and potential cell-cell connections. We plan to test and develop the tool at Janelia before offering it to the community.
Christopher Zugates (Project Scientist) manages the Fly Light’s team of highly skilled research technicians and research specialists. Key strategic decisions are made by the Fly Light Steering Committee that consists of the Project Scientist, Managers, Directors, and Lab Heads whose expertise compliment our core mission. Janelia Farm Shared Resources and Scientific Computing contribute significantly to our project.
- Imaged more than 100,000 confocal stacks of adult and larval nervous systems
- Built a large scale process for preparing samples and capturing images of individual neurons
- Prepared more than 100,000 fly brains to support the identification of individual neuronal lineages and the sequencing of five antennal lobe neuronal lineages.
- Developed an automatic microscopy system that reduces complicated setups from hours to minutes
The overall goal of the FlyLight Project Team is to generate genetic reagents and anatomical data that will be of widespread utility to the Drosophila research community. For this reason, we intend to make the reagents and data we generate available in a timely manner. That said, there are a number of conflicting interests that need to be carefully balanced.
The FlyLight project relies on anatomical expertise that is provided by a number of skilled scientists ranging from postdoctoral fellows to laboratory heads. Many of these individuals have also contributed extensive effort in fly genetics and molecular biology. These individuals are integral members of the project, but their salaries are provided by the budgets of individual research groups. They are devoting, on average, well over a year of full time effort to the project. They are motivated by their desire not only to contribute to this communal effort, but also to build the genetic reagents that are necessary to allow them to approach their problem of interest in a more rigorous way. It is not only appropriate, but also essential for their careers that they get credit for their work. Thus, we believe that allowing these individuals to publish their work before reagents are released (in this case fly lines and images) is essential to the long-term success of the project and thus ultimately benefits the research community at large.
Thus our data release policies are intermediate between what is generally accepted practice for individual labs and that expected of large infrastructure projects like the genome project.
More specifically, for aspects of the project where a significant fraction (more than one-third) of the effort is supplied by members of research groups (who are not funded by the project budget) then those individuals will be granted control over the use of the results for a period of time sufficient to generate publications needed for them to get credit for their work. In most cases, we envision this period to be approximately one year.
Team Members Groups