Transmission distortion and genetic incompatibilities between alleles in a multigenerational mouse advanced intercross line

While direct additive and dominance effects on complex traits have been mapped repeatedly, additional genetic factors contributing to the heterogeneity of complex traits have been scarcely investigated. To assess genetic background effects, we investigated transmission ratio distortions (TRDs) of alleles from parent to offspring using an advanced intercross line (AIL) of an initial cross between the mouse inbred strains C57BL/6NCrl (B6N) and BFMI860-12 (BFMI). 341 males of generation 28 and their respective 61 parents and 66 grandparents were genotyped using Mega Mouse Universal Genotyping Arrays (MegaMUGA). TRDs were investigated using allele transmission asymmetry tests, and pathway overrepresentation analysis was performed. Sequencing data was used to test for overrepresentation of non-synonymous SNPs in TRD regions. Genetic incompatibilities were tested using the Bateson-Dobzhansky-Muller two-locus model. 62 TRD regions were detected, many in close proximity to the telocentric centromere. TRD regions contained 44.5% more non-synonymous SNPs than randomly selected regions (182 vs. 125.9 ± 17.0, P < 1x10−4). Testing for genetic incompatibilities between TRD regions identified 29 genome-wide significant incompatibilities between TRD regions (P(BF) < 0.05). Pathway overrepresentation analysis of genes in TRD regions showed that DNA methylation, epigenetic regulation of RNA, and meiotic/meiosis regulation pathways were affected independent of the parental origin of the TRD. Paternal BFMI TRD regions showed overrepresentation in the small interfering RNA (siRNA) biogenesis and in the metabolism of lipids and lipoproteins. Maternal B6N TRD regions harbored genes involved in meiotic recombination, cell death, and apoptosis pathways. The analysis of genes in TRD regions suggests the potential distortion of protein-protein interactions influencing obesity and diabetic retinopathy as a result of disadvantageous combinations of allelic variants in Aass, Pgx6 and Nme8. Using an AIL significantly improves the resolution at which we can investigate TRD. Our analysis implicates distortion of protein-protein interactions as well as meiotic drive as the underlying mechanisms leading to the observed TRD in our AIL. Furthermore, genes with large amounts of non-synonymous SNPs located in TRD regions are more likely to be involved in pathways that are related to the phenotypic differences between the parental strains. Genes in these TRD regions provide new targets for investigating genetic adaptation, protein-protein interactions, and determinants of complex traits such as obesity.

Detection of Atherosclerosis by Small RNA-Sequencing Analysis of Extracellular Vesicle Enriched Serum Samples

Atherosclerosis can occur throughout the arterial vascular system and lead to various diseases. Early diagnosis of atherosclerotic processes and of individual disease patterns would be more likely to be successful if targeted therapies were available. For this, it is important to find reliable biomarkers that are easily accessible and with little inconvenience for patients. There are many cell culture, animal model or tissue studies that found biomarkers at the microRNA (miRNA) and mRNA level describing atherosclerotic processes. However, little is known about their potential as circulating and liquid biopsy markers in patients. In this study, we examined serum-derived miRNA – profiles from 129 patients and 28 volunteers to identify potential biomarkers. The patients had four different atherosclerotic manifestations: abdominal aneurysm (n = 35), coronary heart disease (n = 34), carotid artery stenosis (n = 24) and peripheral arterial disease (n = 36). The samples were processed with an extracellular vesicle enrichment protocol, total-RNA extraction and small RNA-sequencing were performed. A differential expression analysis was performed bioinformatically to find potentially regulated miRNA biomarkers. Resulting miRNA candidates served as a starting point for an overrepresentation analysis in which relevant target mRNAs were identified. The Gene Ontology database revealed relevant biological functions in relation to atherosclerotic processes. In patients, expression of specific miRNAs changed significantly compared to healthy volunteers; 27 differentially expressed miRNAs were identified. We were able to detect a group-specific miRNA fingerprint: miR-122-5p, miR-2110 and miR-483-5p for abdominal aortic aneurysm, miR-370-3p and miR-409-3p for coronary heart disease, miR-335-3p, miR-381-3p, miR493-5p and miR654-3p for carotid artery stenosis, miR-199a-5p, miR-215-5p, miR-3168, miR-582-3p and miR-769-5p for peripheral arterial disease. The results of the study show that some of the identified miRNAs have already been associated with atherosclerosis in previous studies. Overrepresentation analysis on this data detected biological processes that are clearly relevant for atherosclerosis, its development and progression showing the potential of these miRNAs as biomarker candidates. In a next step, the relevance of these findings on the mRNA level is to be investigated and substantiated.

In silico study for decoding the correlated role of MCM7 gene in progression of breast cancer and Alzheimers disorder

Breast cancer and Alzheimers disease (AD) are two of the progressive and detrimental disorders affecting large population around the globe. While the chemotherapy of breast cancer is well established and enriched, the AD still lacks it due to unrecognized peripheral biomarkers for detection and targeted therapy. This study aimed to identify common molecular signature markers in breast cancer (grade 1, 2, and 3) and AD for the diagnosis and prognosis. We used two microarray datasets (GSE42568, GSE33000) respectively for both disorders that led to identification of two common differentially expressed genes (DEGs), namely MCM7 and CD209, as common players in both these two conditions. While the pattern of expression of CD209 gene running upregulated in both disorders, the MCM7 showed unusual contrary in its pattern of expression. The expression of MCM7 is downregulated in breast cancer but upregulated in AD. Gene set and protein overrepresentation analysis, protein-protein interaction (PPI), and protein subcellular localization analyses of this underrated MCM7 gene was performed with further prediction and validation of its structure. The findings may pave the way in designing therapeutic approaches to ameliorate AD.

Transmission distortion and genetic incompatibilities between alleles in a multigenerational mouse advanced intercross line

Background/Objectives: While direct additive and dominance effects on complex traits have been mapped repeatedly, additional genetic factors contributing to the heterogeneity of complex traits have been scarcely investigated. To assess genetic background effects, we investigated transmission ratio distortions (TRDs) of alleles from parent to offspring using an advanced intercross line (AIL) of an initial cross between the mouse inbred strains C57BL/6NCrl (B6N) and BFMI860-12 (BFMI). Subjects/Methods: 341 males of generation 28 and their respective 61 parents and 66 grandparents were genotyped using Mega Mouse Universal Genotyping Arrays (MegaMUGA). TRDs were investigated using allele transmission asymmetry tests, and pathway overrepresentation analysis was performed. Sequencing data was used to test for overrepresentation of non-synonymous SNPs in TRD regions. Genetic incompatibilities were tested using the Bateson-Dobzhansky-Muller two-locus model. Results: 62 TRD regions were detected, many in close proximity to the telocentric centromere. TRD regions contained 44.5% more non-synonymous SNPs than randomly selected regions (182 vs. 125.9 17.0, P < 1x10-4). Testing for genetic incompatibilities between TRD regions identified 29 genome-wide significant incompatibilities between TRD regions (P(BF) < 0.05). Pathway overrepresentation analysis of genes in TRD regions showed that DNA methylation, epigenetic regulation of RNA, and meiotic/meiosis regulation pathways were affected independent of the parental origin of the TRD. Paternal BFMI TRD regions showed overrepresentation in the small interfering RNA (siRNA) biogenesis and in the metabolism of lipids and lipoproteins. Maternal B6N TRD regions harbored genes involved in meiotic recombination, cell death, and apoptosis pathways. The analysis of genes in TRD regions suggests the potential distortion of protein-protein interactions accounting for obesity and diabetic retinopathy as a result of disadvantageous combinations of allelic variants in Aass, Pgx6 and Nme8. Conclusions: Since genes in TRD regions showed a significant increase in the number of non-synonymous SNPs, these loci likely co-evolved to ensure protein-protein interaction compatibility, survival and optimal adaptation to the genetic background environment. Genes in these regions provide new targets for investigating genetic adaptation, protein-protein interactions, and determinants of complex traits such as obesity.

COVID-2019-associated overexpressed Prevotella proteins mediated host–pathogen interactions and their role in coronavirus outbreak

Motivation The outbreak of COVID-2019 initiated at Wuhan, China has become a global threat by rapid transmission and severe fatalities. Recent studies have uncovered whole genome sequence of SARS-CoV-2 (causing COVID-2019). In addition, lung metagenomic studies on infected patients revealed overrepresented Prevotella spp. producing certain proteins in abundance. We performed host–pathogen protein–protein interaction analysis between SARS-CoV-2 and overrepresented Prevotella proteins with human proteome. We also performed functional overrepresentation analysis of interacting proteins to understand their role in COVID-2019 severity. Results It was found that overexpressed Prevotella proteins can promote viral infection. As per the results, Prevotella proteins, but not viral proteins, are involved in multiple interactions with NF-kB, which is involved in increasing clinical severity of COVID-2019. Prevotella may have role in COVID-2019 outbreak and should be given importance for understanding disease mechanisms and improving treatment outcomes. Supplementary information Supplementary data are available at Bioinformatics online.

Functional Network Community Detection Can Disaggregate and Filter Multiple Underlying Pathways in Enrichment Analyses

Differential expression experiments or other analyses often end in a list of genes. Pathway enrichment analysis is one method to discern important biological signals and patterns from noisy expression data. However, pathway enrichment analysis may perform suboptimally in situations where there are multiple implicated pathways – such as in the case of genes that define subtypes of complex diseases. Our simulation study shows that in this setting, standard overrepresentation analysis identifies many false positive pathways along with the true positives. These false positives hamper investigators’ attempts to glean biological insights from enrichment analysis. We develop and evaluate an approach that combines community detection over functional networks with pathway enrichment to reduce false positives. Our simulation study demonstrates that a large reduction in false positives can be obtained with a small decrease in power. Though we hypothesized that multiple communities might underlie previously described subtypes of high-grade serous ovarian cancer and applied this approach, our results do not support this hypothesis. In summary, applying community detection before enrichment analysis may ease interpretation for complex gene sets that represent multiple distinct pathways.