High-throughput alternative splicing quantification by primer extension and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Alternative splicing is a significant contributor to transcriptome diversity, and a high-throughput experimental method to quantitatively assess predictions from expressed sequence tag and microarray analyses may help to answer questions about the extent and functional significance of these variants. Here, we describe a method for high-throughput analysis of known or suspected alternative splicing variants (ASVs) using PCR, primer extension and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Reverse-transcribed mRNA is PCR amplified with primers surrounding the site of alternative splicing, followed by a primer extension reaction designed to target sequence disparities between two or more variants. These primer extension products are assayed on a MALDI-TOF mass spectrometer and analyzed automatically. This method is high-throughput, highly accurate and reproducible, allowing for the verification of the existence of splicing variants in a variety of samples. An example given also demonstrates how this method can eliminate potential pitfalls from ordinary gel electrophoretic analysis of splicing variants where heteroduplexes formed from different variants can produce erroneous results. The new method can be used to create alternative variant profiles for cancer markers, to study complex splicing regulation, or to screen potential splicing therapies

Blood Biochemistry Analysis to Detect Smoking Status and Quantify Accelerated Aging in Smokers

Abstract There is an association between smoking and cancer, cardiovascular disease and all-cause mortality. However, currently, there are no affordable and informative tests for assessing the effects of smoking on the rate of biological aging. In this study we demonstrate for the first time that smoking status can be predicted using blood biochemistry and cell count results andthe recent advances in artificial intelligence (AI). By employing age-prediction models developed using supervised deep learning techniques, we found that smokers exhibited higher aging rates than nonsmokers, regardless of their cholesterol ratios and fasting glucose levels. We further used those models to quantify the acceleration of biological aging due to tobacco use. Female smokers were predicted to be twice as old as their chronological age compared to nonsmokers, whereas male smokers were predicted to be one and a half times as old as their chronological age compared to nonsmokers. Our findings suggest that deep learning analysis of routine blood tests could complement or even replace the current error-prone method of self-reporting of smoking status and could be expanded to assess the effect of other lifestyle and environmental factors on aging

Cytoplasmic BK\u3csub\u3eCa\u3c/sub\u3e channel intron-containing mRNAs contribute to the intrinsic excitability of hippocampal neurons

High single-channel conductance K+ channels, which respond jointly to membrane depolarization and micromolar concentrations of intracellular Ca2+ ions, arise from extensive cell-specific alternative splicing of pore-forming α-subunit mRNAs. Here, we report the discovery of an endogenous BKCa channel α-subunit intron-containing mRNA in the cytoplasm of hippocampal neurons. This partially processed mRNA, which comprises ≈10% of the total BKCa channel α-subunit mRNAs, is distributed in a gradient throughout the somatodendritic space. We selectively reduced endogenous cytoplasmic levels of this intron-containing transcript by RNA interference without altering levels of the mature splice forms of the BKCa channel mRNAs. In doing so, we could demonstrate that changes in a unique BKCa channel α-subunit introncontaining splice variant mRNA can greatly impact the distribution of the BKCa channel protein to dendritic spines and intrinsic firing properties of hippocampal neurons. These data suggest a new regulatory mechanism for modulating the membrane properties and ion channel gradients of hippocampal neurons

Quantitative Analysis of Single Nucleotide Polymorphisms within Copy Number Variation

BACKGROUND: Single nucleotide polymorphisms (SNPs) have been used extensively in genetics and epidemiology studies. Traditionally, SNPs that did not pass the Hardy-Weinberg equilibrium (HWE) test were excluded from these analyses. Many investigators have addressed possible causes for departure from HWE, including genotyping errors, population admixture and segmental duplication. Recent large-scale surveys have revealed abundant structural variations in the human genome, including copy number variations (CNVs). This suggests that a significant number of SNPs must be within these regions, which may cause deviation from HWE. RESULTS: We performed a Bayesian analysis on the potential effect of copy number variation, segmental duplication and genotyping errors on the behavior of SNPs. Our results suggest that copy number variation is a major factor of HWE violation for SNPs with a small minor allele frequency, when the sample size is large and the genotyping error rate is 0~1%. CONCLUSIONS: Our study provides the posterior probability that a SNP falls in a CNV or a segmental duplication, given the observed allele frequency of the SNP, sample size and the significance level of HWE testing

A case–control study of tobacco use and other non-occupational risk factors for lymphoma subtypes defined by t(14; 18) translocations and bcl-2 expression

We re-evaluated reported associations between tobacco use and other factors and non-Hodgkin lymphoma (NHL) t(14;18)-subtypes based on fluorescence in situ hybridization (FISH) assays believed to be more sensitive than polymerase chain reaction (PCR), previously used for detecting t(14;18)

Non-Hodgkin lymphoma (NHL) subtypes defined by common translocations: Utility of fluorescence in situ hybridization (FISH) in a case–control study

We used fluorescence in situ hybridization (FISH) assays to identify t(14;18) translocations in archival paraffin-embedded tumor sections from non-Hodgkin lymphoma (NHL) cases enrolled in a population-based study. t(14;18) was identified in 54% of 152 cases, including 39% of diffuse large cell lymphomas (26 of 66 cases) and 84% of follicular lymphomas (36 of 43 cases). Eighty-seven percent of t(14;18)-positive cases and 57% of t(14;18)-negative cases expressed bcl-2. FISH assays detected twice as many t(14;18)-positive follicular lymphomas as PCR assays. Overall, study findings support the use of FISH assays to detect t(14;18) in archival tumor samples for epidemiologic studies of NHL subtypes

Brain-Computer Interface Based on Generation of Visual Images

This paper examines the task of recognizing EEG patterns that correspond to performing three mental tasks: relaxation and imagining of two types of pictures: faces and houses. The experiments were performed using two EEG headsets: BrainProducts ActiCap and Emotiv EPOC. The Emotiv headset becomes widely used in consumer BCI application allowing for conducting large-scale EEG experiments in the future. Since classification accuracy significantly exceeded the level of random classification during the first three days of the experiment with EPOC headset, a control experiment was performed on the fourth day using ActiCap. The control experiment has shown that utilization of high-quality research equipment can enhance classification accuracy (up to 68% in some subjects) and that the accuracy is independent of the presence of EEG artifacts related to blinking and eye movement. This study also shows that computationally-inexpensive Bayesian classifier based on covariance matrix analysis yields similar classification accuracy in this problem as a more sophisticated Multi-class Common Spatial Patterns (MCSP) classifier

Cure of Chronic Viral Infection and Virus-Induced Type 1 Diabetes by Neutralizing Antibodies

The use of neutralizing antibodies is one of the most successful methods to interfere with receptor–ligand interactions in vivo. In particular blockade of soluble inflammatory mediators or their corresponding cellular receptors was proven an effective way to regulate inflammation and/or prevent its negative consequences. However, one problem that comes along with an effective neutralization of inflammatory mediators is the general systemic immunomodulatory effect. It is, therefore, important to design a treatment regimen in a way to strike at the right place and at the right time in order to achieve maximal effects with minimal duration of immunosuppression or hyperactivation. In this review, we reflect on two examples of how short time administration of such neutralizing antibodies can block two distinct inflammatory consequences of viral infection. First, we review recent findings that blockade of IL-10/IL-10R interaction can resolve chronic viral infection and second, we reflect on how neutralization of the chemokine CXCL10 can abrogate virus-induced type 1 diabetes

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease