cDNA characterization and chromosomal mapping of human golgi SNARE GS27 and GS28 to chromosome 17

Transcriptomic analysis of the submandibular gland under psychological stress condition

BACKGROUND

Psychological stress is associated with changes in salivary flow and composition. However, studies to show the effect of psychological stress on the transcriptome of the salivary gland are limited. This study aims to perform a transcriptomic analysis of the submandibular gland under psychological stress using a chronic restraint stress model of rats.

METHODS

Sprague-Dawley rats were divided into stress groups and control groups. Psychological stress was induced in the stress group rats by enclosing them in a plastic tube for 4 h daily over 6 weeks. RNA sequencing was performed on RNA extracted from the submandibular gland. The differentially expressed genes were identified, and the genes of interest were further validated using qRT-PCR, immunofluorescence, and western blot.

RESULTS

A comparison between control and stress groups showed 45 differentially expressed genes. The top five altered genes in RNA sequencing data showed similar gene expression in qRT-PCR validation. The most downregulated gene in the stress group, FosB, was a gene of interest and was further validated for its protein-level expression using immunofluorescence and western blot. The genesets for gene ontology cellular component, molecular function, and KEGG showed that pathways related to ribosome biosynthesis and function were downregulated in the stress group compared to the control.

CONCLUSION

Psychological stress showed transcriptomic alteration in the submandibular gland. The findings may be important in understanding stress-related oral diseases.

Improved Detection of Potentially Pleiotropic Genes in Coronary Artery Disease and Chronic Kidney Disease Using GWAS Summary Statistics

The coexistence of coronary artery disease (CAD) and chronic kidney disease (CKD) implies overlapped genetic foundation. However, the common genetic determination between the two diseases remains largely unknown. Relying on summary statistics publicly available from large scale genome-wide association studies (n = 184,305 for CAD and n = 567,460 for CKD), we observed significant positive genetic correlation between CAD and CKD (r_g = 0.173, p = 0.024) via the linkage disequilibrium score regression. Next, we implemented gene-based association analysis for each disease through MAGMA (Multi-marker Analysis of GenoMic Annotation) and detected 763 and 827 genes associated with CAD or CKD (FDR < 0.05). Among those 72 genes were shared between the two diseases. Furthermore, by integrating the overlapped genetic information between CAD and CKD, we implemented two pleiotropy-informed informatics approaches including cFDR (conditional false discovery rate) and GPA (Genetic analysis incorporating Pleiotropy and Annotation), and identified 169 and 504 shared genes (FDR < 0.05), of which 121 genes were simultaneously discovered by cFDR and GPA. Importantly, we found 11 potentially new pleiotropic genes related to both CAD and CKD (i.e., ARHGEF19, RSG1, NDST2, CAMK2G, VCL, LRP10, RBM23, USP10, WNT9B, GOSR2, and RPRML). Five of the newly identified pleiotropic genes were further repeated via an additional dataset CAD available from UK Biobank. Our functional enrichment analysis showed that those pleiotropic genes were enriched in diverse relevant pathway processes including quaternary ammonium group transmembrane transporter, dopamine transport. Overall, this study identifies common genetic architectures overlapped between CAD and CKD and will help to advance understanding of the molecular mechanisms underlying the comorbidity of the two diseases.

GOSR2 Lys67Arg is associated with hypertension in whites

BACKGROUND

Hypertension is a risk factor for coronary heart disease (CHD), but the causes of hypertension remain largely unknown. Genetic variation is thought to contribute to the etiology of hypertension. We tested a single-nucleotide polymorphism (SNP) (Lys67Arg, rs197922) in the Golgi SNAP Receptor Complex Member 2 (GOSR2) gene for association with hypertension and blood pressure (BP). We chose this SNP because it was nominally associated with CHD in earlier studies. Further, GOSR2 is located in a linkage region for hypertension and BP in human and animal studies.

METHODS

We used logistic and linear regression to test associations of the GOSR2 SNP with hypertension and BP among 3,528 blacks and 9,861 whites from the Atherosclerosis Risk in Communities (ARIC) study. Race-specific regression models of hypertension were adjusted for age and gender. Regression models of BP were further adjusted for antihypertensive medication use.

RESULTS

The GOSR2 Lys67 allele was associated with hypertension in whites (odds ratio (OR) = 1.09, P = 0.01) but not blacks (OR = 0.96, P = 0.47). The Lys67 allele was associated with increased systolic BP (SBP) in both races (0.87 mm Hg, P < 0.001 among whites and 1.05 mm Hg, P = 0.05 among blacks). A similar association in whites was observed for the GOSR2 SNP and SBP in the Women's Genome Health Study (WGHS) (OR = 1.03, P = 0.04). The OR remained unchanged after adjustment for antihypertensive medication use (OR = 1.03, P = 0.11), though it was no longer statistically significant.

CONCLUSIONS

We found evidence that a SNP in GOSR2 is modestly associated with hypertension in whites from the ARIC study and the WGHS.

A 2-Mb YAC/BAC-based physical map of the ovum mutant (Om) locus region on mouse chromosome 11

The embryonic lethal phenotype observed when DDK females are crossed with males from other strains results from a deleterious interaction between the egg cytoplasm and the paternal pronucleus soon after fertilization. We have previously mapped the Om locus responsible for this phenotype, called the DDK syndrome, to an approximately 2-cM region of chromosome 11. Here, we report the generation of a physical map of 28 yeast and bacterial artificial chromosome clones encompassing the entire genetic interval containing the Om locus. This contig, spanning approximately 2 Mb, was used to map precisely genes and genetic markers of the region. We determined the maximum physical interval for Om to be 1400 kb. In addition, 11 members of the Scya gene family were found to be organized into two clusters at the borders of the Om region. Two other genes (Rad51l3 and Schlafen 2) and one EST (D11Wsu78e) were also mapped in the Om region. This integrated map provides support for the identification of additional candidate genes for the DDK syndrome.