The transition from outcrossing to predominant self-fertilization is one of the most common evolutionary transitions in flowering plants. This shift is often accompanied by a suite of changes in floral and reproductive characters termed the selfing syndrome. Here, we characterize the genetic architecture and evolutionary forces underlying evolution of the selfing syndrome in Capsella rubella following its recent divergence from the outcrossing ancestor C. grandiflora. We conduct genotyping by multiplexed shotgun sequencing and map floral and reproductive traits in a large (N= 550) F2 population. Our results suggest that in contrast to previous studies of the selfing syndrome, changes at a few loci, some with major effects, have shaped the evolution of the selfing syndrome in Capsella. The directionality of QTL effects, as well as population genetic patterns of polymorphism and divergence at 318 loci, is consistent with a history of directional selection on the selfing syndrome. Our study is an important step toward characterizing the genetic basis and evolutionary forces underlying the evolution of the selfing syndrome in a genetically accessible model system.

The mechanisms linking sensation and action during learning are poorly understood. Layer 2/3 neurons in the motor cortex might participate in sensorimotor integration and learning; they receive input from sensory cortex and excite deep layer neurons, which control movement. Here we imaged activity in the same set of layer 2/3 neurons in the motor cortex over weeks, while mice learned to detect objects with their whiskers and report detection with licking. Spatially intermingled neurons represented sensory (touch) and motor behaviours (whisker movements and licking). With learning, the population-level representation of task-related licking strengthened. In trained mice, population-level representations were redundant and stable, despite dynamism of single-neuron representations. The activity of a subpopulation of neurons was consistent with touch driving licking behaviour. Our results suggest that ensembles of motor cortex neurons couple sensory input to multiple, related motor programs during learning.

The commonly recognized mechanisms for spatial regulation inside the cell are membrane-bounded compartmentalization and biochemical association with subcellular organelles. We use computational modeling to investigate another spatial regulation mechanism mediated by the microtubule network in the cell. Our results demonstrate that the mitotic spindle can impose strong sequestration and concentration effects on molecules with binding affinity for microtubules, especially dynein-directed cargoes. The model can recapitulate the essence of three experimental observations on distinct microtubule network morphologies: the sequestration of germ plasm components by the mitotic spindles in the Drosophila syncytial embryo, the asymmetric cell division initiated by the time delay in centrosome maturation in the Drosophila neuroblast, and the diffusional block between neighboring energids in the Drosophila syncytial embryo. Our model thus suggests that the cell cycle-dependent changes in the microtubule network are critical for achieving different spatial regulation effects. The microtubule network provides a spatially extensive docking platform for molecules and gives rise to a "structured cytoplasm", in contrast to a free and fluid environment.

Microscopic images of specific proteins in their cellular context yield important insights into biological processes and cellular architecture. The advent of superresolution optical microscopy techniques provides the possibility to augment EM with nanometer-resolution fluorescence microscopy to access the precise location of proteins in the context of cellular ultrastructure. Unfortunately, efforts to combine superresolution fluorescence and EM have been stymied by the divergent and incompatible sample preparation protocols of the two methods. Here, we describe a protocol that preserves both the delicate photoactivatable fluorescent protein labels essential for superresolution microscopy and the fine ultrastructural context of EM. This preparation enables direct 3D imaging in 500- to 750-nm sections with interferometric photoactivatable localization microscopy followed by scanning EM images generated by focused ion beam ablation. We use this process to "colorize" detailed EM images of the mitochondrion with the position of labeled proteins. The approach presented here has provided a new level of definition of the in vivo nature of organization of mitochondrial nucleoids, and we expect this straightforward method to be applicable to many other biological questions that can be answered by direct imaging.

The ability to specify the expression levels of exogenous genes inserted in the genomes of transgenic animals is critical for the success of a wide variety of experimental manipulations. Protein production can be regulated at the level of transcription, mRNA transport, mRNA half-life, or translation efficiency. In this report, we show that several well-characterized sequence elements derived from plant and insect viruses are able to function in Drosophila to increase the apparent translational efficiency of mRNAs by as much as 20-fold. These increases render expression levels sufficient for genetic constructs previously requiring multiple copies to be effective in single copy, including constructs expressing the temperature-sensitive inactivator of neuronal function Shibire(ts1), and for the use of cytoplasmic GFP to image the fine processes of neurons.

Voltage-gated ion channels are responsible for transmitting electrochemical signals in both excitable and non-excitable cells. Structural studies of voltage-gated potassium and sodium channels by X-ray crystallography have revealed atomic details on their voltage-sensor domains (VSDs) and pore domains, and were put in context of disparate mechanistic views on the voltage-driven conformational changes in these proteins. Functional investigation of voltage-gated channels in membranes, however, showcased a mechanism of lipid-dependent gating for voltage-gated channels, suggesting that the lipids play an indispensible and critical role in the proper gating of many of these channels. Structure determination of membrane-embedded voltage-gated ion channels appears to be the next frontier in fully addressing the mechanism by which the VSDs control channel opening. Currently electron crystallography is the only structural biology method in which a membrane protein of interest is crystallized within a complete lipid-bilayer mimicking the native environment of a biological membrane. At a sufficiently high resolution, an electron crystallographic structure could reveal lipids, the channel and their mutual interactions at the atomic level. Electron crystallography is therefore a promising avenue toward understanding how lipids modulate channel activation through close association with the VSDs.

Pavlovian fear conditioning is an associative learning paradigm in which mice learn to associate a neutral conditioned stimulus with an aversive unconditioned stimulus. In this study, we demonstrate a novel role for the transcriptional regulator Lmo4 in fear learning. LMO4 is predominantly expressed in pyramidal projection neurons of the basolateral complex of the amygdala (BLC). Mice heterozygous for a genetrap insertion in the Lmo4 locus (Lmo4gt/+), which express 50% less Lmo4 than their wild type (WT) counterparts display enhanced freezing to both the context and the cue in which they received the aversive stimulus. Small-hairpin RNA-mediated knockdown of Lmo4 in the BLC, but not the dentate gyrus region of the hippocampus recapitulated this enhanced conditioning phenotype, suggesting an adult- and brain region-specific role for Lmo4 in fear learning. Immunohistochemical analyses revealed an increase in the number of c-Fos positive puncta in the BLC of Lmo4gt/+ mice in comparison to their WT counterparts after fear conditioning. Lastly, we measured anxiety-like behavior in Lmo4gt/+ mice and in mice with BLC-specific downregulation of Lmo4 using the elevated plus maze, open field, and light/dark box tests. Global or BLC-specific knockdown of Lmo4 did not significantly affect anxiety-like behavior. These results suggest a selective role for LMO4 in the BLC in modulating learned but not unlearned fear.

Previous implementations of structured-illumination microscopy (SIM) were slow or designed for one-color excitation, sacrificing two unique and extremely beneficial aspects of light microscopy: live-cell imaging in multiple colors. This is especially unfortunate because, among the resolution-extending techniques, SIM is an attractive choice for live-cell imaging; it requires no special fluorophores or high light intensities to achieve twice diffraction-limited resolution in three dimensions. Furthermore, its wide-field nature makes it light-efficient and decouples the acquisition speed from the size of the lateral field of view, meaning that high frame rates over large volumes are possible. Here, we report a previously undescribed SIM setup that is fast enough to record 3D two-color datasets of living whole cells. Using rapidly programmable liquid crystal devices and a flexible 2D grid pattern algorithm to switch between excitation wavelengths quickly, we show volume rates as high as 4 s in one color and 8.5 s in two colors over tens of time points. To demonstrate the capabilities of our microscope, we image a variety of biological structures, including mitochondria, clathrin-coated vesicles, and the actin cytoskeleton, in either HeLa cells or cultured neurons.

Transcription is a complex process that integrates the state of the cell and its environment to generate adequate responses for cell fitness and survival. Recent microscopy experiments have been able to monitor transcription from single genes in individual cells. These observations have revealed two striking features: transcriptional activity can vary markedly from one cell to another, and is subject to large changes over time, sometimes within minutes. How the chromatin structure, transcription machinery assembly and signalling networks generate such patterns is still unclear. In this review, we present the techniques used to investigate transcription from single genes, introduce quantitative modelling tools, and discuss transcription mechanisms and their implications for gene expression regulation.