We present a database of repetitive DNA elements, called Dfam (http://dfam.janelia.org). Many genomes contain a large fraction of repetitive DNA, much of which is made up of remnants of transposable elements (TEs). Accurate annotation of TEs enables research into their biology and can shed light on the evolutionary processes that shape genomes. Identification and masking of TEs can also greatly simplify many downstream genome annotation and sequence analysis tasks. The commonly used TE annotation tools RepeatMasker and Censor depend on sequence homology search tools such as cross_match and BLAST variants, as well as Repbase, a collection of known TE families each represented by a single consensus sequence. Dfam contains entries corresponding to all Repbase TE entries for which instances have been found in the human genome. Each Dfam entry is represented by a profile hidden Markov model, built from alignments generated using RepeatMasker and Repbase. When used in conjunction with the hidden Markov model search tool nhmmer, Dfam produces a 2.9% increase in coverage over consensus sequence search methods on a large human benchmark, while maintaining low false discovery rates, and coverage of the full human genome is 54.5%. The website provides a collection of tools and data views to support improved TE curation and annotation efforts. Dfam is also available for download in flat file format or in the form of MySQL table dumps.

Conventional acquisition of three-dimensional (3D) microscopy data requires sequential z scanning and is often too slow to capture biological events. We report an aberration-corrected multifocus microscopy method capable of producing an instant focal stack of nine 2D images. Appended to an epifluorescence microscope, the multifocus system enables high-resolution 3D imaging in multiple colors with single-molecule sensitivity, at speeds limited by the camera readout time of a single image.

Random scattering and aberrations severely limit the imaging depth in optical microscopy. We introduce a rapid, parallel wavefront compensation technique that efficiently compensates even highly complex phase distortions. Using coherence gated backscattered light as a feedback signal, we focus light deep inside highly scattering brain tissue. We demonstrate that the same wavefront optimization technique can also be used to compensate spectral phase distortions in ultrashort laser pulses using nonlinear iterative feedback. We can restore transform limited pulse durations at any selected target location and compensate for dispersion that has occurred in the optical train and within the sample.

Light sheet-based fluorescence microscopy (LSFM) is emerging as a powerful imaging technique for the life sciences. LSFM provides an exceptionally high imaging speed, high signal-to-noise ratio, low level of photo-bleaching, and good optical penetration depth. This unique combination of capabilities makes light sheet-based microscopes highly suitable for live imaging applications. Here, we provide an overview of light sheet-based microscopy assays for in vitro and in vivo imaging of biological samples, including cell extracts, soft gels, and large multicellular organisms. We furthermore describe computational tools for basic image processing and data inspection.

Nancy E. Beckage is widely recognized for her pioneering work in the field of insect host-parasitoid interactions beginning with endocrine influences of the tobacco hornworm, Manduca sexta, host and its parasitoid wasp Apanteles congregatus (now Cotesia congregata) on each other’s development. Moreover, her studies show that the polydnavirus carried by the parasitoid wasp not only protects the parasitoid from the host’s immune defenses, but also is responsible for some of the developmental effects of parasitism. Nancy was a highly regarded mentor of both undergraduate and graduate students and more widely of women students and colleagues in entomology. Her service both to her particular area and to entomology in general through participation on federal grant review panels and in the governance of the Entomological Society of America, organization of symposia at both national and international meetings, and editorship of several different journal issues and of several books, is legendary. She has left behind a lasting legacy of increased understanding of multilevel endocrine and physiological interactions among insects and other organisms and a strong network of interacting scientists and colleagues in her area of entomology.

Midbrain dopaminergic (DA) neurons are thought to guide learning via phasic elevations of firing in response to reward predicting stimuli. The mechanism for these signals remains unclear. Using extracellular recording during associative learning, we found that inhibitory neurons in the ventral midbrain of mice responded to salient auditory stimuli with a burst of activity that occurred before the onset of the phasic response of DA neurons. This population of inhibitory neurons exhibited enhanced responses during extinction and was anticorrelated with the phasic response of simultaneously recorded DA neurons. Optogenetic stimulation revealed that this population was, in part, derived from inhibitory projection neurons of the substantia nigra that provide a robust monosynaptic inhibition of DA neurons. Thus, our results elaborate on the dynamic upstream circuits that shape the phasic activity of DA neurons and suggest that the inhibitory microcircuit of the midbrain is critical for new learning in extinction.

The Rfam database (available via the website at http://rfam.sanger.ac.uk and through our mirror at http://rfam.janelia.org) is a collection of non-coding RNA families, primarily RNAs with a conserved RNA secondary structure, including both RNA genes and mRNA cis-regulatory elements. Each family is represented by a multiple sequence alignment, predicted secondary structure and covariance model. Here we discuss updates to the database in the latest release, Rfam 11.0, including the introduction of genome-based alignments for large families, the introduction of the Rfam Biomart as well as other user interface improvements. Rfam is available under the Creative Commons Zero license.

Chemical fluorophores find wide use in biology to detect and visualize different phenomena. A key advantage of small-molecule dyes is the ability to construct compounds where fluorescence is activated by chemical or biochemical processes. Fluorogenic molecules, in which fluorescence is activated by enzymatic activity, light, or environmental changes, enable advanced bioassays and sophisticated imaging experiments. Here, we detail the collection of fluorophores and highlight both general strategies and unique approaches that are employed to control fluorescence using chemistry.

A number of atomic-resolution structures of membrane proteins (better than 3Å resolution) have been determined recently by electron crystallography. While this technique was established more than 40 years ago, it is still in its infancy with regard to the two-dimensional (2D) crystallization, data collection, data analysis, and protein structure determination. In terms of data collection, electron crystallography encompasses both image acquisition and electron diffraction data collection. Other chapters in this volume outline protocols for image collection and analysis. This chapter, however, outlines detailed protocols for data collection by electron diffraction. These include microscope setup, electron diffraction data collection, and troubleshooting.

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes- neural connectivity maps of the brain-using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems-reads to parallel disk arrays and writes to solid-state storage-to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization.