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887 Janelia Publications

Showing 1-10 of 887 results
02/08/16 | Quantitatively predictable control of Drosophila transcriptional enhancers in vivo with engineered transcription factors.
Crocker J, Ilsley GR, Stern DL
Nature Genetics. 2016 Feb 8:. doi: 10.1038/ng.3509

Genes are regulated by transcription factors that bind to regions of genomic DNA called enhancers. Considerable effort is focused on identifying transcription factor binding sites, with the goal of predicting gene expression from DNA sequence. Despite this effort, general, predictive models of enhancer function are currently lacking. Here we combine quantitative models of enhancer function with manipulations using engineered transcription factors to examine the extent to which enhancer function can be controlled in a quantitatively predictable manner. Our models, which incorporate few free parameters, can accurately predict the contributions of ectopic transcription factor inputs. These models allow the predictable 'tuning' of enhancers, providing a framework for the quantitative control of enhancers with engineered transcription factors.

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02/03/16 | Neural Circuits Underlying Visually Evoked Escapes in Larval Zebrafish.
Dunn TW, Gebhardt C, Naumann EA, Riegler C, Ahrens MB, Engert F, Del Bene F
Neuron. 2016 Feb 3;89(3):613-628. doi: 10.1016/j.neuron.2015.12.021

Escape behaviors deliver organisms away from imminent catastrophe. Here, we characterize behavioral responses of freely swimming larval zebrafish to looming visual stimuli simulating predators. We report that the visual system alone can recruit lateralized, rapid escape motor programs, similar to those elicited by mechanosensory modalities. Two-photon calcium imaging of retino-recipient midbrain regions isolated the optic tectum as an important center processing looming stimuli, with ensemble activity encoding the critical image size determining escape latency. Furthermore, we describe activity in retinal ganglion cell terminals and superficial inhibitory interneurons in the tectum during looming and propose a model for how temporal dynamics in tectal periventricular neurons might arise from computations between these two fundamental constituents. Finally, laser ablations of hindbrain circuitry confirmed that visual and mechanosensory modalities share the same premotor output network. We establish a circuit for the processing of aversive stimuli in the context of an innate visual behavior.

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02/02/16 | Tagmentation-based mapping (tagmap) of mobile DNA genomic insertion sites.
bioRxiv. 2016 Feb 2:. doi: 10.1101/037762

Multiple methods have been introduced over the past 30 years to identify the genomic insertion sites of transposable elements and other DNA elements that integrate into genomes. However, each of these methods suffer from limitations that can frustrate attempts to map multiple insertions in a single genome and to map insertions in genomes of high complexity that contain extensive repetitive DNA. I introduce a new method for transposon mapping that is simple to perform, can accurately map multiple insertions per genome, and generates long sequence reads that facilitate mapping to complex genomes. The method, called TagMap, for Tagmentation-based Mapping, relies on a modified Tn5 tagmentation protocol with a single tagmentation adaptor followed by PCR using primers specific to the tranposable element and the adaptor sequence. Several minor modifications to normal tagmentation reagents and protocols allow easy and rapid preparation of TagMap libraries. Short read sequencing starting from the adaptor sequence generates oriented reads that flank and are oriented toward the transposable element insertion site. The convergent orientation of adjacent reads at the insertion site allows straightforward prediction of the precise insertion site(s). A Linux shell script is provided to identify insertion sites from fastq files.

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01/28/16 | Studying small brains to understand the building blocks of cognition.
Haberkern H, Jayaraman V
Current Opinion in Neurobiology. 2016 Jan 28;37:59-65. doi: 10.1016/j.conb.2016.01.007

Cognition encompasses a range of higher-order mental processes, such as attention, working memory, and model-based decision-making. These processes are thought to involve the dynamic interaction of multiple central brain regions. A mechanistic understanding of such computations requires not only monitoring and manipulating specific neural populations during behavior, but also knowing the connectivity of the underlying circuitry. These goals are experimentally challenging in mammals, but are feasible in numerically simpler insect brains. In Drosophila melanogaster in particular, genetic tools enable precisely targeted physiology and optogenetics in actively behaving animals. In this article we discuss how these advantages are increasingly being leveraged to study abstract neural representations and sensorimotor computations that may be relevant for cognition in both insects and mammals.

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01/25/16 | Real-time three-dimensional cell segmentation in large-scale microscopy data of developing embryos.
Stegmaier J, Amat F, Lemon WC, McDole K, Wan Y, Teodoro G, Mikut R, Keller PJ
Developmental Cell. 2016 Jan 25;36(2):225-40. doi: 10.1016/j.devcel.2015.12.028

We present the Real-time Accurate Cell-shape Extractor (RACE), a high-throughput image analysis framework for automated three-dimensional cell segmentation in large-scale images. RACE is 55–330 times faster and 2–5 times more accurate than state-of-the-art methods. We demonstrate the generality of RACE by extracting cell-shape information from entire Drosophila, zebrafish, and mouse embryos imaged with confocal and light-sheet microscopes. Using RACE, we automatically reconstructed cellular-resolution tissue anisotropy maps across developing Drosophila embryos and quantified differences in cell-shape dynamics in wild-type and mutant embryos. We furthermore integrated RACE with our framework for automated cell lineaging and performed joint segmentation and cell tracking in entire Drosophila embryos. RACE processed these terabyte-sized datasets on a single computer within 1.4 days. RACE is easy to use, as it requires adjustment of only three parameters, takes full advantage of state-of-the-art multi-core processors and graphics cards, and is available as open-source software for Windows, Linux, and Mac OS.

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01/20/16 | A platform for brain-wide imaging and reconstruction of individual neurons.
Economo MN, Clack NG, Lavis LD, Gerfen CR, Svoboda K, Myers EW, Chandrashekar J
eLife. 2016 Jan 20;5:. doi: 10.7554/eLife.10566

The structure of axonal arbors controls how signals from individual neurons are routed within the mammalian brain. However, the arbors of very few long-range projection neurons have been reconstructed in their entirety, as axons with diameters as small as 100 nm arborize in target regions dispersed over many millimeters of tissue. We introduce a platform for high-resolution, three-dimensional fluorescence imaging of complete tissue volumes that enables the visualization and reconstruction of long-range axonal arbors. This platform relies on a high-speed two-photon microscope integrated with a tissue vibratome and a suite of computational tools for large-scale image data. We demonstrate the power of this approach by reconstructing the axonal arbors of multiple neurons in the motor cortex across a single mouse brain.

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01/20/16 | Simultaneous denoising, deconvolution, and demixing of calcium imaging data.
Pnevmatikakis EA, Soudry D, Gao Y, Machado TA, Merel J, Pfau D, Reardon T, Mu Y, Lacefield C, Yang W, Ahrens M, Bruno R, Jessell TM, Peterka DS, Yuste R, Paninski L
Neuron. 2016 Jan 20;89(2):285-99. doi: 10.1016/j.neuron.2015.11.037

We present a modular approach for analyzing calcium imaging recordings of large neuronal ensembles. Our goal is to simultaneously identify the locations of the neurons, demix spatially overlapping components, and denoise and deconvolve the spiking activity from the slow dynamics of the calcium indicator. Our approach relies on a constrained nonnegative matrix factorization that expresses the spatiotemporal fluorescence activity as the product of a spatial matrix that encodes the spatial footprint of each neuron in the optical field and a temporal matrix that characterizes the calcium concentration of each neuron over time. This framework is combined with a novel constrained deconvolution approach that extracts estimates of neural activity from fluorescence traces, to create a spatiotemporal processing algorithm that requires minimal parameter tuning. We demonstrate the general applicability of our method by applying it to in vitro and in vivo multi-neuronal imaging data, whole-brain light-sheet imaging data, and dendritic imaging data.

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01/13/16 | Spatial Gene-Expression Gradients Underlie Prominent Heterogeneity of CA1 Pyramidal Neurons.
Cembrowski MS, Bachman JL, Wang L, Sugino K, Shields BC, Spruston N
Neuron. 2016 Jan 13:. doi: 10.1016/j.neuron.2015.12.013

Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types. This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but it may be further hampered by prominent within-class variability. Here, we considered a well-defined canonical neuronal population-hippocampal CA1 pyramidal cells (CA1 PCs)-and systematically examined the extent and spatial rules of transcriptional heterogeneity. Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences within CA1 along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous gene-expression gradients, producing a transcriptional profile consistent with a multifarious continuum of cells. This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits.

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01/11/16 | The contribution of ultrasonic vocalizations to mouse courtship.
Egnor SRoian, Seagraves KM
Current Opinion in Neurobiology. 2016 Jan 11;38:1-5. doi: 10.1016/j.conb.2015.12.009

Vocalizations transmit information to social partners, and mice use these signals to exchange information during courtship. Ultrasonic vocalizations from adult males are tightly associated with their interactions with females, and vary as a function of male quality. Work in the last decade has established that the spectrotemporal features of male vocalizations are not learned, but that female attention toward specific vocal features is modified by social experience. Additionally, progress has been made on elucidating how mouse vocalizations are encoded in the auditory system, and on the olfactory circuits that trigger their production. Together these findings provide us with important insights into how vocal communication can contribute to social interactions.

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01/07/16 | Adaptive and background-aware GAL4 expression enhancement of co-registered confocal microscopy images.
Trapp M, Schulze F, Novikov AA, Tirian L, J Dickson B, Bühler K
Neuroinformatics. 2016 Jan 7:. doi: 10.1007/s12021-015-9289-y

GAL4 gene expression imaging using confocal microscopy is a common and powerful technique used to study the nervous system of a model organism such as Drosophila melanogaster. Recent research projects focused on high throughput screenings of thousands of different driver lines, resulting in large image databases. The amount of data generated makes manual assessment tedious or even impossible. The first and most important step in any automatic image processing and data extraction pipeline is to enhance areas with relevant signal. However, data acquired via high throughput imaging tends to be less then ideal for this task, often showing high amounts of background signal. Furthermore, neuronal structures and in particular thin and elongated projections with a weak staining signal are easily lost. In this paper we present a method for enhancing the relevant signal by utilizing a Hessian-based filter to augment thin and weak tube-like structures in the image. To get optimal results, we present a novel adaptive background-aware enhancement filter parametrized with the local background intensity, which is estimated based on a common background model. We also integrate recent research on adaptive image enhancement into our approach, allowing us to propose an effective solution for known problems present in confocal microscopy images. We provide an evaluation based on annotated image data and compare our results against current state-of-the-art algorithms. The results show that our algorithm clearly outperforms the existing solutions.

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