IntSplice2: Prediction of the Splicing Effects of Intronic Single-Nucleotide Variants Using LightGBM Modeling.

Prediction of the effect of a single-nucleotide variant (SNV) in an intronic region on aberrant pre-mRNA splicing is challenging except for an SNV affecting the canonical GU/AG splice sites (ss). To predict pathogenicity of SNVs at intronic positions -50 (Int-50) to -3 (Int-3) close to the 3' ss, we developed light gradient boosting machine (LightGBM)-based IntSplice2 models using pathogenic SNVs in the human gene mutation database (HGMD) and ClinVar and common SNVs in dbSNP with 0.01 ≤ minor allelic frequency (MAF) < 0.50. The LightGBM models were generated using features representing splicing cis-elements. The average recall/sensitivity and specificity of IntSplice2 by fivefold cross-validation (CV) of the training dataset were 0.764 and 0.884, respectively. The recall/sensitivity of IntSplice2 was lower than the average recall/sensitivity of 0.800 of IntSplice that we previously made with support vector machine (SVM) modeling for the same intronic positions. In contrast, the specificity of IntSplice2 was higher than the average specificity of 0.849 of IntSplice. For benchmarking (BM) of IntSplice2 with IntSplice, we made a test dataset that was not used to train IntSplice. After excluding the test dataset from the training dataset, we generated IntSplice2-BM and compared it with IntSplice using the test dataset. IntSplice2-BM was superior to IntSplice in all of the seven statistical measures of accuracy, precision, recall/sensitivity, specificity, F1 score, negative predictive value (NPV), and matthews correlation coefficient (MCC). We made the IntSplice2 web service at https://www.med.nagoya-u.ac.jp/neurogenetics/IntSplice2.

Masticatory performance analysis using photographic image of gummy jelly.

PURPOSE: Masticatory performance can be measured through elution of glucose or beta-carotene from comminuted gummy jelly. However, these methods require special devices. Additionally, occasional/unintentional swallowing or inadequate collection of comminuted particles of gummy jelly in the oral cavity may cause measurement errors. Therefore, we devised a new photographic method to estimate the increase in surface area and weight of comminuted gummy jelly. This study aimed to verify the accuracy of this method. METHODS: Initially, fifty images depicting the comminuted pieces in a special box were prepared. Then, the increase in surface area was measured using a fully-automated method, and the weight was measured. The size and angle of each image were adjusted based on markers located at the four corners of the box. From these photographic images, the area, perimeter, color average, color deviation, side area, and amount of surface roughness for each particle was calculated, and multiple regression analysis was performed to estimate the surface area and weight. The relationship between the estimated values and the values measured with the fully-automated device and by weight were analyzed. RESULTS: The intra-class correlation coefficient between the estimated value and the value from the fully-automated method was r = 0.956. This high correlation was also obtained under different photographic conditions. Furthermore, for determining whether 80% or less gummy jelly was collected, the sensitivity was 100% and the specificity was 91%. CONCLUSIONS: The newly developed photographic method is valuable because it is accessible and may assist in achieving reliable evaluation of masticatory performance.

IntSplice: prediction of the splicing consequences of intronic single-nucleotide variations in the human genome.

Precise spatiotemporal regulation of splicing is mediated by splicing cis-elements on pre-mRNA. Single-nucleotide variations (SNVs) affecting intronic cis-elements possibly compromise splicing, but no efficient tool has been available to identify them. Following an effect-size analysis of each intronic nucleotide on annotated alternative splicing, we extracted 105 parameters that could affect the strength of the splicing signals. However, we could not generate reliable support vector regression models to predict the percent-splice-in (PSI) scores for normal human tissues. Next, we generated support vector machine (SVM) models using 110 parameters to directly differentiate pathogenic SNVs in the Human Gene Mutation Database and normal SNVs in the dbSNP database, and we obtained models with a sensitivity of 0.800±0.041 (mean and s.d.) and a specificity of 0.849±0.021. Our IntSplice models were more discriminating than SVM models that we generated with Shapiro-Senapathy score and MaxEntScan::score3ss. We applied IntSplice to a naturally occurring and nine artificial intronic mutations in RAPSN causing congenital myasthenic syndrome. IntSplice correctly predicted the splicing consequences for nine of the ten mutants. We created a web service program, IntSplice (http://www.med.nagoya-u.ac.jp/neurogenetics/IntSplice) to predict splicing-affecting SNVs at intronic positions from -50 to -3.

Intestinal Dysbiosis and Lowered Serum Lipopolysaccharide-Binding Protein in Parkinson's Disease.

BACKGROUND: The intestine is one of the first affected organs in Parkinson's disease (PD). PD subjects show abnormal staining for Escherichia coli and α-synuclein in the colon. METHODS: We recruited 52 PD patients and 36 healthy cohabitants. We measured serum markers and quantified the numbers of 19 fecal bacterial groups/genera/species by quantitative RT-PCR of 16S or 23S rRNA. Although the six most predominant bacterial groups/genera/species covered on average 71.3% of total intestinal bacteria, our analysis was not comprehensive compared to metagenome analysis or 16S rRNA amplicon sequencing. RESULTS: In PD, the number of Lactobacillus was higher, while the sum of analyzed bacteria, Clostridium coccoides group, and Bacteroides fragilis group were lower than controls. Additionally, the sum of putative hydrogen-producing bacteria was lower in PD. A linear regression model to predict disease durations demonstrated that C. coccoides group and Lactobacillus gasseri subgroup had the largest negative and positive coefficients, respectively. As a linear regression model to predict stool frequencies showed that these bacteria were not associated with constipation, changes in these bacteria were unlikely to represent worsening of constipation in the course of progression of PD. In PD, the serum lipopolysaccharide (LPS)-binding protein levels were lower than controls, while the levels of serum diamine oxidase, a marker for intestinal mucosal integrity, remained unchanged in PD. CONCLUSIONS: The permeability to LPS is likely to be increased without compromising the integrity of intestinal mucosa in PD. The increased intestinal permeability in PD may make the patients susceptible to intestinal dysbiosis. Conversely, intestinal dysbiosis may lead to the increased intestinal permeability. One or both of the two mechanisms may be operational in development and progression of PD.

Position-dependent FUS-RNA interactions regulate alternative splicing events and transcriptions.

FUS is an RNA-binding protein that regulates transcription, alternative splicing, and mRNA transport. Aberrations of FUS are causally associated with familial and sporadic ALS/FTLD. We analyzed FUS-mediated transcriptions and alternative splicing events in mouse primary cortical neurons using exon arrays. We also characterized FUS-binding RNA sites in the mouse cerebrum with HITS-CLIP. We found that FUS-binding sites tend to form stable secondary structures. Analysis of position-dependence of FUS-binding sites disclosed scattered binding of FUS to and around the alternatively spliced exons including those associated with neurodegeneration such as Mapt, Camk2a, and Fmr1. We also found that FUS is often bound to the antisense RNA strand at the promoter regions. Global analysis of these FUS-tags and the expression profiles disclosed that binding of FUS to the promoter antisense strand downregulates transcriptions of the coding strand. Our analysis revealed that FUS regulates alternative splicing events and transcriptions in a position-dependent manner.