The Coupling of Alternative Splicing and Nonsense-Mediated mRNA Decay

Most human genes exhibit alternative splicing, but not all alternatively spliced transcripts produce functional proteins. Computational and experimental results indicate that a substantial fraction of alternative splicing events in humans result in mRNA isoforms that harbor a premature termination codon (PTC). These transcripts are predicted to be degraded by the nonsense-mediated mRNA decay (NMD) pathway. One explanation for the abundance of PTC-containing isoforms is that they represent splicing errors that are identified and degraded by the NMD pathway. Another potential explanation for this startling observation is that cells may link alternative splicing and NMD to regulate the abundance of mRNA transcripts. This mechanism, which we call "Regulated Unproductive Splicing and Translation" (RUST), has been experimentally shown to regulate expression of a wide variety of genes in many organisms from yeast to human. It is frequently employed for autoregulation of proteins that affect the splicing process itself. Thus, alternative splicing and NMD act together to play an important role in regulating gene expression

Long-Baseline Neutrino Facility (LBNF) and Deep Underground Neutrino Experiment (DUNE) Conceptual Design Report Volume 2: The Physics Program for DUNE at LBNF

The Physics Program for the Deep Underground Neutrino Experiment (DUNE) at the Fermilab Long-Baseline Neutrino Facility (LBNF) is described

Automated analysis of neuronal morphology, synapse number and synaptic recruitment

The shape, structure and connectivity of nerve cells are important aspects of neuronal function. Genetic and epigenetic factors that alter neuronal morphology or synaptic localization of pre- and post-synaptic proteins contribute significantly to neuronal output and may underlie clinical states. To assess the impact of individual genes and disease-causing mutations on neuronal morphology, reliable methods are needed. Unfortunately, manual analysis of immuno-fluorescence images of neurons to quantify neuronal shape and synapse number, size and distribution is labor-intensive, time-consuming and subject to human bias and error. We have developed an automated image analysis routine using steerable filters and deconvolutions to automatically analyze dendrite and synapse characteristics in immuno-fluorescence images. Our approach reports dendrite morphology, synapse size and number but also synaptic vesicle density and synaptic accumulation of proteins as a function of distance from the soma as consistent as expert observers while reducing analysis time considerably. In addition, the routine can be used to detect and quantify a wide range of neuronal organelles and is capable of batch analysis of a large number of images enabling high-throughput analysis