Repetitive DNA, especially that due to transposable elements (TEs), makes up a large fraction of many genomes. Dfam is an open access database of families of repetitive DNA elements, in which each family is represented by a multiple sequence alignment and a profile hidden Markov model (HMM). The initial release of Dfam, featured in the 2013 NAR Database Issue, contained 1143 families of repetitive elements found in humans, and was used to produce more than 100 Mb of additional annotation of TE-derived regions in the human genome, with improved speed. Here, we describe recent advances, most notably expansion to 4150 total families including a comprehensive set of known repeat families from four new organisms (mouse, zebrafish, fly and nematode). We describe improvements to coverage, and to our methods for identifying and reducing false annotation. We also describe updates to the website interface. The Dfam website has moved to http://dfam.org. Seed alignments, profile HMMs, hit lists and other underlying data are available for download.

Messenger RNA localization is important for cell motility by local protein translation. However, while single mRNAs can be imaged and their movements tracked in single cells, it has not yet been possible to determine whether these mRNAs are actively translating. Therefore, we imaged single β-actin mRNAs tagged with MS2 stem loops colocalizing with labeled ribosomes to determine when polysomes formed. A dataset of tracking information consisting of thousands of trajectories per cell demonstrated that mRNAs co-moving with ribosomes have significantly different diffusion properties from non-translating mRNAs that were exposed to translation inhibitors. These data indicate that ribosome load changes mRNA movement and therefore highly translating mRNAs move slower. Importantly, β-actin mRNA near focal adhesions exhibited sub-diffusive corralled movement characteristic of increased translation. This method can identify where ribosomes become engaged for local protein production and how spatial regulation of mRNA-protein interactions mediates cell directionality.

The representation of magnitude information enables humans and animal species alike to successfully interact with the external environment. However, how various types of magnitudes are processed by single neurons to guide goal-directed behavior remains elusive. Here, we recorded single-cell activity from the dorsolateral prefrontal (PFC), dorsal premotor (PMd) and cingulate motor (CMA) cortices in monkeys discriminating discrete numerical (numerosity), continuous spatial (line length) and basic sensory (spatial frequency) stimuli. We found that almost exclusively PFC neurons represented the different magnitude types during sample presentation and working memory periods. The frequency of magnitude-selective cells in PMd and CMA did not exceed chance level. The proportion of PFC neurons selectively tuned to each of the three magnitude types were comparable. Magnitude coding was mainly dissociated at the single-neuron level, with individual neurons representing only one of the three tested magnitude types. Neuronal magnitude discriminability, coding strength and temporal evolution were comparable between magnitude types encoded by PFC neuron populations. Our data highlight the importance of PFC neurons in representing various magnitude categories. Such magnitude representations are based on largely distributed coding by single neurons that are anatomically intermingled within the same cortical area.

How brains are hardwired to produce aggressive behavior, and how aggression circuits are related to those that mediate courtship, is not well understood. A large-scale screen for aggression-promoting neurons in Drosophila identified several independent hits that enhanced both inter-male aggression and courtship. Genetic intersections revealed that 8-10 P1 interneurons, previously thought to exclusively control male courtship, were sufficient to promote fighting. Optogenetic experiments indicated that P1 activation could promote aggression at a threshold below that required for wing extension. P1 activation in the absence of wing extension triggered persistent aggression via an internal state that could endure for minutes. High-frequency P1 activation promoted wing extension and suppressed aggression during photostimulation, whereas aggression resumed and wing extension was inhibited following photostimulation offset. Thus, P1 neuron activation promotes a latent, internal state that facilitates aggression and courtship, and controls the overt expression of these social behaviors in a threshold-dependent, inverse manner.

Advances in neuro-technology for mapping, manipulating, and monitoring molecularly defined cell types are rapidly advancing insight into neural circuits that regulate appetite. Here, we review these important tools and their applications in circuits that control food seeking and consumption. Technical capabilities provided by these tools establish a rigorous experimental framework for research into the neurobiology of hunger.

Animals seek out relevant information by moving through a dynamic world, but sensory systems are usually studied under highly constrained and passive conditions that may not probe important dimensions of the neural code. Here, we explored neural coding in the barrel cortex of head-fixed mice that tracked walls with their whiskers in tactile virtual reality. Optogenetic manipulations revealed that barrel cortex plays a role in wall-tracking. Closed-loop optogenetic control of layer 4 neurons can substitute for whisker-object contact to guide behavior resembling wall tracking. We measured neural activity using two-photon calcium imaging and extracellular recordings. Neurons were tuned to the distance between the animal snout and the contralateral wall, with monotonic, unimodal, and multimodal tuning curves. This rich representation of object location in the barrel cortex could not be predicted based on simple stimulus-response relationships involving individual whiskers and likely emerges within cortical circuits.

Dendritic integration of synaptic inputs mediates rapid neural computation as well as longer-lasting plasticity. Several channel types can mediate dendritically initiated spikes (dSpikes), which may impact information processing and storage across multiple timescales; however, the roles of different channels in the rapid vs long-term effects of dSpikes are unknown. We show here that dSpikes mediated by Nav channels (blocked by a low concentration of TTX) are required for long-term potentiation (LTP) in the distal apical dendrites of hippocampal pyramidal neurons. Furthermore, imaging, simulations, and buffering experiments all support a model whereby fast Nav channel-mediated dSpikes (Na-dSpikes) contribute to LTP induction by promoting large, transient, localized increases in intracellular calcium concentration near the calcium-conducting pores of NMDAR and L-type Cav channels. Thus, in addition to contributing to rapid neural processing, Na-dSpikes are likely to contribute to memory formation via their role in long-lasting synaptic plasticity.

Information processing relies on precise patterns of synapses between neurons. The cellular recognition mechanisms regulating this specificity are poorly understood. In the medulla of the Drosophila visual system, different neurons form synaptic connections in different layers. Here, we sought to identify candidate cell recognition molecules underlying this specificity. Using RNA sequencing (RNA-seq), we show that neurons with different synaptic specificities express unique combinations of mRNAs encoding hundreds of cell surface and secreted proteins. Using RNA-seq and protein tagging, we demonstrate that 21 paralogs of the Dpr family, a subclass of immunoglobulin (Ig)-domain containing proteins, are expressed in unique combinations in homologous neurons with different layer-specific synaptic connections. Dpr interacting proteins (DIPs), comprising nine paralogs of another subclass of Ig-containing proteins, are expressed in a complementary layer-specific fashion in a subset of synaptic partners. We propose that pairs of Dpr/DIP paralogs contribute to layer-specific patterns of synaptic connectivity.

Human memory can store large amount of information. Nevertheless, recalling is often a challenging task. In a classical free recall paradigm, where participants are asked to repeat a briefly presented list of words, people make mistakes for lists as short as 5 words. We present a model for memory retrieval based on a Hopfield neural network where transition between items are determined by similarities in their long-term memory representations. Meanfield analysis of the model reveals stable states of the network corresponding (1) to single memory representations and (2) intersection between memory representations. We show that oscillating feedback inhibition in the presence of noise induces transitions between these states triggering the retrieval of different memories. The network dynamics qualitatively predicts the distribution of time intervals required to recall new memory items observed in experiments. It shows that items having larger number of neurons in their representation are statistically easier to recall and reveals possible bottlenecks in our ability of retrieving memories. Overall, we propose a neural network model of information retrieval broadly compatible with experimental observations and is consistent with our recent graphical model (Romani et al., 2013).

It is now appreciated that the brain is immunologically active. Highly conserved innate immune signaling responds to pathogen invasion and injury and promotes structural refinement of neural circuitry. However, it remains generally unknown whether innate immune signaling has a function during the day-to-day regulation of neural function in the absence of pathogens and irrespective of cellular damage or developmental change. Here we show that an innate immune receptor, a member of the peptidoglycan pattern recognition receptor family (PGRP-LC), is required for the induction and sustained expression of homeostatic synaptic plasticity. This receptor functions presynaptically, controlling the homeostatic modulation of the readily releasable pool of synaptic vesicles following inhibition of postsynaptic glutamate receptor function. Thus, PGRP-LC is a candidate receptor for retrograde, trans-synaptic signaling, a novel activity for innate immune signaling and the first known function of a PGRP-type receptor in the nervous system of any organism.