Quantitative nucleotide level analysis of regulation of translation in response to depolarization of cultured neural cells

Studies on regulation of gene expression have contributed substantially to understanding mechanisms for the long-term activity-dependent alterations in neural connectivity that are thought to mediate learning and memory. Most of these studies, however, have focused on the regulation of mRNA transcription. Here, we utilized high-throughput sequencing coupled with ribosome footprinting to globally characterize the regulation of translation in primary mixed neuronal-glial cultures in response to sustained depolarization. We identified substantial and complex regulation of translation, with many transcripts demonstrating changes in ribosomal occupancy independent of transcriptional changes. We also examined sequence-based mechanisms that might regulate changes in translation in response to depolarization. We found that these are partially mediated by features in the mRNA sequence—notably upstream open reading frames and secondary structure in the 5′ untranslated region—both of which predict downregulation in response to depolarization. Translationally regulated transcripts are also more likely to be targets of FMRP and include genes implicated in autism in humans. Our findings support the idea that control of mRNA translation plays an important role in response to neural activity across the genome

Measures of distinguishability between stochastic processes

Quantifying how distinguishable two stochastic processes are lies at the heart of many fields, such as machine learning and quantitative finance. While several measures have been proposed for this task, none have universal applicability and ease of use. In this Letter, we suggest a set of requirements for a well-behaved measure of process distinguishability. Moreover, we propose a family of measures, called divergence rates, that satisfy all of these requirements. Focussing on a particular member of this family -- the co-emission divergence rate -- we show that it can be computed efficiently, behaves qualitatively similar to other commonly-used measures in their regimes of applicability, and remains well-behaved in scenarios where other measures break down

Mendelian randomization and genetic colocalization infer the effects of the multi-tissue proteome on 211 complex disease-related phenotypes

BACKGROUND: Human proteins are widely used as drug targets. Integration of large-scale protein-level genome-wide association studies (GWAS) and disease-related GWAS has thus connected genetic variation to disease mechanisms via protein. Previous proteome-by-phenome-wide Mendelian randomization (MR) studies have been mainly focused on plasma proteomes. Previous MR studies using the brain proteome only reported protein effects on a set of pre-selected tissue-specific diseases. No studies, however, have used high-throughput proteomics from multiple tissues to perform MR on hundreds of phenotypes. METHODS: Here, we performed MR and colocalization analysis using multi-tissue (cerebrospinal fluid (CSF), plasma, and brain from pre- and post-meta-analysis of several disease-focus cohorts including Alzheimer disease (AD)) protein quantitative trait loci (pQTLs) as instrumental variables to infer protein effects on 211 phenotypes, covering seven broad categories: biological traits, blood traits, cancer types, neurological diseases, other diseases, personality traits, and other risk factors. We first implemented these analyses with cis pQTLs, as cis pQTLs are known for being less prone to horizontal pleiotropy. Next, we included both cis and trans conditionally independent pQTLs that passed the genome-wide significance threshold keeping only variants associated with fewer than five proteins to minimize pleiotropic effects. We compared the tissue-specific protein effects on phenotypes across different categories. Finally, we integrated the MR-prioritized proteins with the druggable genome to identify new potential targets. RESULTS: In the MR and colocalization analysis including study-wide significant cis pQTLs as instrumental variables, we identified 33 CSF, 13 plasma, and five brain proteins to be putative causal for 37, 18, and eight phenotypes, respectively. After expanding the instrumental variables by including genome-wide significant cis and trans pQTLs, we identified a total of 58 CSF, 32 plasma, and nine brain proteins associated with 58, 44, and 16 phenotypes, respectively. For those protein-phenotype associations that were found in more than one tissue, the directions of the associations for 13 (87%) pairs were consistent across tissues. As we were unable to use methods correcting for horizontal pleiotropy given most of the proteins were only associated with one valid instrumental variable after clumping, we found that the observations of protein-phenotype associations were consistent with a causal role or horizontal pleiotropy. Between 66.7 and 86.3% of the disease-causing proteins overlapped with the druggable genome. Finally, between one and three proteins, depending on the tissue, were connected with at least one drug compound for one phenotype from both DrugBank and ChEMBL databases. CONCLUSIONS: Integrating multi-tissue pQTLs with MR and the druggable genome may open doors to pinpoint novel interventions for complex traits with no effective treatments, such as ovarian and lung cancers

White matter abnormalities in the Hdc knockout mouse, a model of tic and OCD pathophysiology

INTRODUCTION: An inactivating mutation in the MATERIALS AND METHODS: We performed exploratory RNA-seq to identify pathological alterations in several brain regions in RESULTS: Exploratory RNA-Seq analysis revealed, unexpectedly, that genes associated with oligodendrocytes and with myelin production are upregulated in the dorsal striatum of these mice. This was confirmed by qPCR, immunostaining, and immunoblotting. These results suggest an abnormality in myelination in the striatum. To test this in an intact mouse brain, we performed whole-brain DISCUSSION: While the DTI literature in individuals with TS is sparse, these results are consistent with findings of disrupted descending cortical projections in patients with tics. Th

Dissipative solitary waves in a two-dimensional complex plasma: Amorphous versus crystalline

The propagation of a dissipative soliton was experimentally studied in a two-dimensional binary complex plasma. The crystallization was suppressed in the center of the particle suspension where two types of particles were mixed. The motions of individual particles were recorded using video microscopy, and the macroscopic properties of the solitons were measured in the amorphous binary mixture in the center and in the plasma crystal in the periphery. Although the overall shape and parameters of solitons propagating in amorphous and crystalline regions were quite similar, their velocity structures at small scales as well as the velocity distributions were profoundly distinct. Moreover, the local structure rearranged drastically in and behind the soliton, which was not observed in the plasma crystal. Langevin dynamics simulations were performed, and the results agreed with the experimental observations