The guanine nucleotide exchange factor, Spata13, influences social behaviour and nocturnal activity

Differences in physiology and behavior between male winner and loser mice in the tube test

Social hierarchy is a crucial element for survival, reproduction, fitness, and the maintenance of a stable social group in social animals. This study aimed to investigate the physiological indicators, nociception, unfamiliar female mice preference, spatial learning memory, and contextual fear memory of male mice with different social status in the same cage. Our findings revealed significant differences in the trunk temperature and contextual fear memory between winner and loser mice. However, there were no major discrepancies in body weight, random and fasting blood glucose levels, whisker number, frontal and perianal temperature, spleen size, mechanical and thermal pain thresholds, preference for unfamiliar female mice, and spatial memory. In conclusion, social status can affect mice in multiple ways, and, therefore, its influence should be considered when conducting studies using these animals.

Construction of a Cuproptosis-Related Gene Signature for Predicting Prognosis in Gastric Cancer

This study aimed to develop and validate a cuproptosis-related gene signature for the prognosis of gastric cancer. The data in TCGA GC TPM format from UCSC were extracted for analysis, and GC samples were randomly divided into training and validation groups. Pearson correlation analysis was used to obtain cuproptosis-related genes co-expressed with 19 Cuproptosis genes. Univariate Cox and Lasso regression analyses were used to obtain cuproptosis-related prognostic genes. Multivariate Cox regression analysis was used to construct the final prognostic risk model. The risk score curve, Kaplan-Meier survival curves, and ROC curve were used to evaluate the predictive ability of Cox risk model. Finally, the functional annotation of the risk model was obtained through enrichment analysis. Then, a six-gene signature was identified in the training cohort and verified among all cohorts using Cox regression analyses and Kaplan-Meier plots, demonstrating its independent prognostic significance for gastric cancer. In addition, ROC analysis confirmed the significant predictive potential of this signature for the prognosis of gastric cancer. Functional enrichment analysis was mainly related to cell-matrix function. Therefore, a new cuproptosis-related six-gene signature (ACLY, FGD6, SERPINE1, SPATA13, RANGAP1, and ADGRE5) was constructed for the prognosis of gastric cancer, allowing for tailored prediction of outcome and the formulation of novel therapeutics for gastric cancer patients.

Connecting phenotype to genotype: PheWAS-inspired analysis of autism spectrum disorder

Autism Spectrum Disorder (ASD) is extremely heterogeneous clinically and genetically. There is a pressing need for a better understanding of the heterogeneity of ASD based on scientifically rigorous approaches centered on systematic evaluation of the clinical and research utility of both phenotype and genotype markers. This paper presents a holistic PheWAS-inspired method to identify meaningful associations between ASD phenotypes and genotypes. We generate two types of phenotype-phenotype (p-p) graphs: a direct graph that utilizes only phenotype data, and an indirect graph that incorporates genotype as well as phenotype data. We introduce a novel methodology for fusing the direct and indirect p-p networks in which the genotype data is incorporated into the phenotype data in varying degrees. The hypothesis is that the heterogeneity of ASD can be distinguished by clustering the p-p graph. The obtained graphs are clustered using network-oriented clustering techniques, and results are evaluated. The most promising clusterings are subsequently analyzed for biological and domain-based relevance. Clusters obtained delineated different aspects of ASD, including differentiating ASD-specific symptoms, cognitive, adaptive, language and communication functions, and behavioral problems. Some of the important genes associated with the clusters have previous known associations to ASD. We found that clusters based on integrated genetic and phenotype data were more effective at identifying relevant genes than clusters constructed from phenotype information alone. These genes included five with suggestive evidence of ASD association and one known to be a strong candidate.

An 11-Gene Signature Risk-Prediction Model Based on Prognosis-Related miRNAs and Their Target Genes in Lung Adenocarcinoma

Aberrant expression of microRNAs may affect tumorigenesis and progression by regulating their target genes. This study aimed to construct a risk model for predicting the prognosis of patients with lung adenocarcinoma (LUAD) based on differentially expressed microRNA-regulated target genes. The miRNA sequencing data, RNA sequencing data, and patients’ LUAD clinical data were downloaded from the The Cancer Genome Atlas (TCGA) database. Differentially expressed miRNAs and genes were screened out by combining differential analysis with LASSO regression analysis to further screen out miRNAs associated with patients’ prognosis, and target gene prediction was performed for these miRNAs using a target gene database. Overlapping gene screening was performed for target genes and differentially expressed genes. LASSO regression analysis and survival analysis were then used to identify key genes. Risk score equations for prognostic models were established using multifactorial COX regression analysis to construct survival prognostic models, and the accuracy of the models was evaluated using subject working characteristic curves. The groups were divided into high- and low-risk groups according to the median risk score, and the correlation with the clinicopathological characteristics of the patients was observed. A total of 123 up-regulated miRNAs and 22 down-regulated miRNAs were obtained in this study. Five prognosis-related miRNAs were screened using LASSO regression analysis and Kaplan-Meier method validation, and their target genes were screened with the overlap of differentially expressed genes before multifactorial COX analysis finally resulted in an 11-gene risk model for predicting patient prognosis. The area under the ROC curve proved that the model has high accuracy. The 11-gene risk-prediction model constructed in this study may be an effective predictor of prognosis.

Transcriptome Analysis of Testis from HFD-Induced Obese Rats (Rattus norvigicus) Indicated Predisposition for Male Infertility

Obesity is a worldwide life-threatening metabolic disorder, associated with various chronic diseases, including male infertility. Obesity was induced by high fat diet (HFD), and testis RNA was used for the transcriptome analysis using RNAseq via Illumina NovaSeq 6000 System and NovaSeq 6000 Kit. Gene expression level was estimated as FPKM (Fragments Per Kilobase of transcript per Million mapped reads). Differential expressed genes (DEGs) were annotated against gene ontology (GO) and KEGG databases. More than 63.66 million reads per sample were performed with 100 bp cutoff and 6 Gb sequencing depth. Results of this study revealed that 267 GO terms (245 biological processes (BP), 14 cellular components (CC), eight molecular functions (MF)), and 89 KEGG pathways were significantly enriched. Moreover, total numbers of 136 genes were differentially expressed (107 upregulated, 29 downregulated) with |FC| ≥ 2 and bh adjusted <0.05. Interesting DEGs were detected, including obesity and lipid metabolism-related genes, immune response-related genes, cytochrome P450 genes, including aromatase were upregulated, whereas genes related to male fertility and fertilization, cell adhesion, and olfactory receptors were downregulated. The combined expression pattern of the DEGs in obese animals indicated an increase in cholesterol metabolism. Furthermore, high aromatase activity enhances the testosterone turnover into estradiol and lowers the testosterone/estradiol (T/E) ratio, which ultimately reduces fertility. In addition, downregulation of cadherens junction components genes leads to the pre-mature release of sperm from Sertoli cells resulting in the reduction of fertility. Moreover, the downregulation of olfactory receptor genes reduces the chemotaxis capacity of sperms in tracking the oocyte for fertilization, which reduces male fertility. Furthermore, various obesity molecular markers were detected in our transcriptome. The results of this study will enhance our understanding of the molecular network of obesity development, development of obesity novel molecular diagnosis markers, molecular bases of obesity-induced infertility, and the development of anti-obesity drugs.

Forward genetics identifies a novel sleep mutant with sleep state inertia and REM sleep deficits

Switches between global sleep and wakefulness states are believed to be dictated by top-down influences arising from subcortical nuclei. Using forward genetics and in vivo electrophysiology, we identified a recessive mouse mutant line characterized by a substantially reduced propensity to transition between wake and sleep states with an especially pronounced deficit in initiating rapid eye movement (REM) sleep episodes. The causative mutation, an Ile102Asn substitution in the synaptic vesicular protein, VAMP2, was associated with morphological synaptic changes and specific behavioral deficits, while in vitro electrophysiological investigations with fluorescence imaging revealed a markedly diminished probability of vesicular release in mutants. Our data show that global shifts in the synaptic efficiency across brain-wide networks leads to an altered probability of vigilance state transitions, possibly as a result of an altered excitability balance within local circuits controlling sleep-wake architecture.

Mutations in SPATA13/ASEF2 cause primary angle closure glaucoma

Current estimates suggest 50% of glaucoma blindness worldwide is caused by primary angle-closure glaucoma (PACG) but the causative gene is not known. We used genetic linkage and whole genome sequencing to identify Spermatogenesis Associated Protein 13, SPATA13 (NM_001166271; NP_001159743, SPATA13 isoform I), also known as ASEF2 (Adenomatous polyposis coli-stimulated guanine nucleotide exchange factor 2), as the causal gene for PACG in a large seven-generation white British family showing variable expression and incomplete penetrance. The 9 bp deletion, c.1432_1440del; p.478_480del was present in all affected individuals with angle-closure disease. We show ubiquitous expression of this transcript in cell lines derived from human tissues and in iris, retina, retinal pigment and ciliary epithelia, cornea and lens. We also identified eight additional mutations in SPATA13 in a cohort of 189 unrelated PACS/PAC/PACG samples. This gene encodes a 1277 residue protein which localises to the nucleus with partial co-localisation with nuclear speckles. In cells undergoing mitosis SPATA13 isoform I becomes part of the kinetochore complex co-localising with two kinetochore markers, polo like kinase 1 (PLK-1) and centrosome-associated protein E (CENP-E). The 9 bp deletion reported in this study increases the RAC1-dependent guanine nucleotide exchange factors (GEF) activity. The increase in GEF activity was also observed in three other variants identified in this study. Taken together, our data suggest that SPATA13 is involved in the regulation of mitosis and the mutations dysregulate GEF activity affecting homeostasis in tissues where it is highly expressed, influencing PACG pathogenesis.