Two clichés of science journalism have now played out around the ENCODE project. ENCODE’s publicity first presented a misleading "all the textbooks are wrong" narrative about noncoding human DNA. Now several critiques of ENCODE’s narrative have been published, and one was so vitriolic that it fueled "undignified academic squabble" stories that focused on tone more than substance. Neither story line does justice to our actual understanding of genomes, to ENCODE’s results, or to the role of big science in biology.

Animal models have been widely used to gain insight into the mechanisms underlying the acute and long-term effects of alcohol exposure. The fruit fly Drosophila melanogaster encounters ethanol in its natural habitat and possesses many adaptations that allow it to survive and thrive in ethanol-rich environments. Several assays to study ethanol-related behaviors in flies, ranging from acute intoxication to self-administration and reward, have been developed in the past 20 years. These assays have provided the basis for studying the physiological and behavioral effects of ethanol and for identifying genes mediating these effects. In this review we describe the ecological relationship between flies and ethanol, the effects of ethanol on fly development and behavior, the use of flies as a model for alcohol addiction, and the interaction between ethanol and social behavior. We discuss these advances in the context of their utility to help decipher the mechanisms underlying the diverse effects of ethanol, including those that mediate ethanol dependence and addiction in humans.

Recent years have seen a rise in publications demonstrating coupling between transcription and mRNA decay. This coupling most often accompanies cellular processes that involve transitions in gene expression patterns, for example during mitotic division and cellular differentiation and in response to cellular stress. Transcription can affect the mRNA fate by multiple mechanisms. The most novel finding is the process of co-transcriptional imprinting of mRNAs with proteins, which in turn regulate cytoplasmic mRNA stability. Transcription therefore is not only a catalyst of mRNA synthesis but also provides a platform that enables imprinting, which coordinates between transcription and mRNA decay. Here we present an overview of the literature, which provides the evidence of coupling between transcription and decay, review the mechanisms and regulators by which the two processes are coupled, discuss why such coupling is beneficial and present a new model for regulation of gene expression. This article is part of a Special Issue entitled: RNA Decay mechanisms.

Any method for RNA secondary structure prediction is determined by four ingredients. The architecture is the choice of features implemented by the model (such as stacked basepairs, loop length distributions, etc.). The architecture determines the number of parameters in the model. The scoring scheme is the nature of those parameters (whether thermodynamic, probabilistic, or weights). The parameterization stands for the specific values assigned to the parameters. These three ingredients are referred to as "the model." The fourth ingredient is the folding algorithms used to predict plausible secondary structures given the model and the sequence of a structural RNA. Here, I make several unifying observations drawn from looking at more than 40 years of methods for RNA secondary structure prediction in the light of this classification. As a final observation, there seems to be a performance ceiling that affects all methods with complex architectures, a ceiling that impacts all scoring schemes with remarkable similarity. This suggests that modeling RNA secondary structure by using intrinsic sequence-based plausible "foldability" will require the incorporation of other forms of information in order to constrain the folding space and to improve prediction accuracy. This could give an advantage to probabilistic scoring systems since a probabilistic framework is a natural platform to incorporate different sources of information into one single inference problem.

The evolution of phenotypic similarities between species, known as convergence, illustrates that populations can respond predictably to ecological challenges. Convergence often results from similar genetic changes, which can emerge in two ways: the evolution of similar or identical mutations in independent lineages, which is termed parallel evolution; and the evolution in independent lineages of alleles that are shared among populations, which I call collateral genetic evolution. Evidence for parallel and collateral evolution has been found in many taxa, and an emerging hypothesis is that they result from the fact that mutations in some genetic targets minimize pleiotropic effects while simultaneously maximizing adaptation. If this proves correct, then the molecular changes underlying adaptation might be more predictable than has been appreciated previously.

The manner in which different distributions of synaptic weights onto cortical neurons shape their spiking activity remains open. To characterize a homogeneous neuronal population, we use the master equation for generalized leaky integrate-and-fire neurons with shot-noise synapses. We develop fast semi-analytic numerical methods to solve this equation for either current or conductance synapses, with and without synaptic depression. We show that its solutions match simulations of equivalent neuronal networks better than those of the Fokker-Planck equation and we compute bounds on the network response to non-instantaneous synapses. We apply these methods to study different synaptic weight distributions in feed-forward networks. We characterize the synaptic amplitude distributions using a set of measures, called tail weight numbers, designed to quantify the preponderance of very strong synapses. Even if synaptic amplitude distributions are equated for both the total current and average synaptic weight, distributions with sparse but strong synapses produce higher responses for small inputs, leading to a larger operating range. Furthermore, despite their small number, such synapses enable the network to respond faster and with more stability in the face of external fluctuations.

The molecular action of juvenile hormone (JH), a regulator of vital importance to insects, was until recently regarded as a mystery. The past few years have seen an explosion of studies of JH signaling, sparked by a finding that a JH-resistance gene, Methoprene-tolerant (Met), plays a critical role in insect metamorphosis. Here, we summarize the recently acquired knowledge on the capacity of Met to bind JH, which has been mapped to a particular ligand-binding domain, thus establishing this bHLH-PAS protein as a novel type of an intracellular hormone receptor. Next, we consider the significance of JH-dependent interactions of Met with other transcription factors and signaling pathways. We examine the regulation and biological roles of genes acting downstream of JH and Met in insect metamorphosis. Finally, we discuss the current gaps in our understanding of JH action and outline directions for future research.

Rodents move their whiskers to locate objects in space. Here we used psychophysical methods to show that head-fixed mice can localize objects along the axis of a single whisker, the radial dimension, with one-millimeter precision. High-speed videography allowed us to estimate the forces and bending moments at the base of the whisker, which underlie radial distance measurement. Mice judged radial object location based on multiple touches. Both the number of touches (1-17) and the forces exerted by the pole on the whisker (up to 573 μN; typical peak amplitude, 100 μN) varied greatly across trials. We manipulated the bending moment and lateral force pressing the whisker against the sides of the follicle and the axial force pushing the whisker into the follicle by varying the compliance of the object during behavior. The behavioral responses suggest that mice use multiple variables (bending moment, axial force, lateral force) to extract radial object localization. Characterization of whisker mechanics revealed that whisker bending stiffness decreases gradually with distance from the face over five orders of magnitude. As a result, the relative amplitudes of different stress variables change dramatically with radial object distance. Our data suggest that mice use distance-dependent whisker mechanics to estimate radial object location using an algorithm that does not rely on precise control of whisking, is robust to variability in whisker forces, and is independent of object compliance and object movement. More generally, our data imply that mice can measure the amplitudes of forces in the sensory follicles for tactile sensation.

In both mammalian and insect models of ethanol intoxication, high doses of ethanol induce motor impairment and eventually sedation. Sensitivity to the sedative effects of ethanol is inversely correlated with risk for alcoholism. However, the genes regulating ethanol sensitivity are largely unknown. Based on a previous genetic screen in Drosophila for ethanol sedation mutants, we identified a novel gene, tank (CG15626), the homolog of the mammalian tumor suppressor EI24/PIG8, which has a strong role in regulating ethanol sedation sensitivity. Genetic and behavioral analyses revealed that tank acts in the adult nervous system to promote ethanol sensitivity. We localized the function of tank in regulating ethanol sensitivity to neurons within the pars intercerebralis that have not been implicated previously in ethanol responses. We show that acutely manipulating the activity of all tank-expressing neurons, or of pars intercerebralis neurons in particular, alters ethanol sensitivity in a sexually dimorphic manner, since neuronal activation enhanced ethanol sedation in males, but not females. Finally, we provide anatomical evidence that tank-expressing neurons form likely synaptic connections with neurons expressing the neural sex determination factor fruitless (fru), which have been implicated recently in the regulation of ethanol sensitivity. We suggest that a functional interaction with fru neurons, many of which are sexually dimorphic, may account for the sex-specific effect induced by activating tank neurons. Overall, we have characterized a novel gene and corresponding set of neurons that regulate ethanol sensitivity in Drosophila.

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.