scholarly journals Sex Differences in Correlation with Gene Expression Levels between Ifi200 Family Genes and Four Sets of Immune Disease-Relevant Genes

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Yanhong Cao ◽  
Lishi Wang ◽  
Cong-Yi Wang ◽  
Jicheng Ye ◽  
Ying Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Sex Differences ◽  
Gender Difference ◽  
Sex Difference ◽  
Sex Hormone ◽  
Male Mice ◽  
Mouse Population ◽  
Expression Levels ◽  
Immune Mediated ◽  
Gene Expression Levels

Background. The HIN-200 family genes in humans have been linked to several autoimmune diseases—particularly to systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). Recently, its human counterpart gene cluster, the Ifi200 family in mice, has been linked to spontaneous arthritis disease (SAD). However, many immune-mediated diseases (including RA and SLE) show gender difference. Understanding whether or not and how these genes play a role in sex difference in immune-mediated diseases is essential for diagnosis/treatment. Methods. This study takes advantage of the whole genome gene expression profiles of recombinant inbred (RI) strain populations from female and male mice to analyze potential sex differences in a variety of genes in disease pathways. Expression levels and regulatory QTL of Ifi200 family genes between female and male mice were first examined in a large mouse population, including RI strains derived from C57BL/6J, DBA/2J (BXD), and classic inbred strains. Sex similarities and differences were then analyzed for correlations with gene expression levels between genes in the Ifi200 family and four selected gene sets: known immune Ifi200 pathway-related genes, lupus-relevant genes, osteoarthritis- (OA-) and RA-relevant genes, and sex hormone-related genes. Results. The expression level of Ifi202b showed the most sex difference in correlation with known immune-related genes (the P value for Ifi202b is 0.0004). Ifi202b also showed gender difference in correlation with selected sex hormone genes, with a P value of 0.0243. When comparing coexpression levels between Ifi200 genes and lupus-relevant genes, Ifi203 and Ifi205 showed significant sex difference (P values: 0.0303 and 0.002, resp.). Furthermore, several key genes (e.g., Csf1r, Ifnb1, IL-20, IL-22, IL-24, Jhdm1d, Csf1r, Ifnb1, IL-20, IL-22, IL-24, and Tgfb2 that regulate sex differences in immune diseases) were discovered. Conclusions. Different genes in the Ifi200 family play different roles in sex difference among dissimilar pathways of these four gene groups.

The Effects of Amoxicillin, Cefazolin, and Gentamicin Antibiotics on the Antioxidant System in Mouse Heart Tissues

2020 ◽  
Vol 27 (7) ◽  
pp. 614-622
Author(s):  
Ahmet Savcı ◽  
Enver Fehim Koçpınar ◽  
Harun Budak ◽  
Mehmet Çiftci ◽  
Melda Şişecioğlu
Keyword(s):  
Oxidative Stress ◽  
Gene Expression ◽  
Free Radicals ◽  
Enzyme Activities ◽  
Control Group ◽  
Mouse Heart ◽  
Male Mice ◽  
Expression Levels ◽  
Improper Use ◽  
Gene Expression Levels

Background: Free radicals lead to destruction in various organs of the organism. The improper use of antibiotics increases the formation of free radicals and causes oxidative stress. Objective: In this study, it was aimed to determine the effects of gentamicin, amoxicillin, and cefazolin antibiotics on the mouse heart. Methods: 20 male mice were divided into 4 groups (1st control, 2nd amoxicillin, 3rd cefazolin, and 4th gentamicin groups). The mice in the experimental groups were administered antibiotics intraperitoneally at a dose of 100 mg / kg for 6 days. The control group received normal saline in the same way. The gene expression levels and enzyme activities of SOD, CAT, GPx, GR, GST, and G6PD antioxidant enzymes were investigated. Results : GSH levels decreased in both the amoxicillin and cefazolin groups, while GR, CAT, and SOD enzyme activities increased. In the amoxicillin group, Gr, Gst, Cat, and Sod gene expression levels increased. Conclusion: As a result, it was concluded that amoxicillin and cefazolin caused oxidative stress in the heart, however, gentamicin did not cause any effects.

scholarly journals A Sparse and Low-Rank Regression Model for Identifying the Relationships Between DNA Methylation and Gene Expression Levels in Gastric Cancer and the Prediction of Prognosis

Genes ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 854
Author(s):  
Yishu Wang ◽  
Lingyun Xu ◽  
Dongmei Ai
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Dna Methylation ◽  
Regression Model ◽  
The Cancer Genome Atlas ◽  
Low Rank ◽  
Expression Levels ◽  
Rank Regression ◽  
Prediction Of Prognosis ◽  
Gene Expression Levels

DNA methylation is an important regulator of gene expression that can influence tumor heterogeneity and shows weak and varying expression levels among different genes. Gastric cancer (GC) is a highly heterogeneous cancer of the digestive system with a high mortality rate worldwide. The heterogeneous subtypes of GC lead to different prognoses. In this study, we explored the relationships between DNA methylation and gene expression levels by introducing a sparse low-rank regression model based on a GC dataset with 375 tumor samples and 32 normal samples from The Cancer Genome Atlas database. Differences in the DNA methylation levels and sites were found to be associated with differences in the expressed genes related to GC development. Overall, 29 methylation-driven genes were found to be related to the GC subtypes, and in the prognostic model, we explored five prognoses related to the methylation sites. Finally, based on a low-rank matrix, seven subgroups were identified with different methylation statuses. These specific classifications based on DNA methylation levels may help to account for heterogeneity and aid in personalized treatments.

scholarly journals High heterogeneity undermines generalization of differential expression results in RNA-Seq analysis

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Weitong Cui ◽  
Huaru Xue ◽  
Lei Wei ◽  
Jinghua Jin ◽  
Xuewen Tian ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Small Sample ◽  
Differentially Expressed ◽  
Cancer Type ◽  
Rna Seq ◽  
Sample Sizes ◽  
Large Sample ◽  
Expression Levels ◽  
Gene Expression Levels

Abstract Background RNA sequencing (RNA-Seq) has been widely applied in oncology for monitoring transcriptome changes. However, the emerging problem that high variation of gene expression levels caused by tumor heterogeneity may affect the reproducibility of differential expression (DE) results has rarely been studied. Here, we investigated the reproducibility of DE results for any given number of biological replicates between 3 and 24 and explored why a great many differentially expressed genes (DEGs) were not reproducible. Results Our findings demonstrate that poor reproducibility of DE results exists not only for small sample sizes, but also for relatively large sample sizes. Quite a few of the DEGs detected are specific to the samples in use, rather than genuinely differentially expressed under different conditions. Poor reproducibility of DE results is mainly caused by high variation of gene expression levels for the same gene in different samples. Even though biological variation may account for much of the high variation of gene expression levels, the effect of outlier count data also needs to be treated seriously, as outlier data severely interfere with DE analysis. Conclusions High heterogeneity exists not only in tumor tissue samples of each cancer type studied, but also in normal samples. High heterogeneity leads to poor reproducibility of DEGs, undermining generalization of differential expression results. Therefore, it is necessary to use large sample sizes (at least 10 if possible) in RNA-Seq experimental designs to reduce the impact of biological variability and DE results should be interpreted cautiously unless soundly validated.

scholarly journals Genome-Wide Expression and Alternative Splicing in Domesticated Sunflowers (Helianthus annuus L.) under Flooding Stress

Agronomy ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 92
Author(s):  
Joon Seon Lee ◽  
Lexuan Gao ◽  
Laura Melissa Guzman ◽  
Loren H. Rieseberg
Keyword(s):  
Gene Expression ◽  
Alternative Splicing ◽  
Mixed Model ◽  
Agricultural Land ◽  
Alcohol Fermentation ◽  
Expression Levels ◽  
Flooding Stress ◽  
Genome Wide ◽  
And Control ◽  
Gene Expression Levels

Approximately 10% of agricultural land is subject to periodic flooding, which reduces the growth, survivorship, and yield of most crops, reinforcing the need to understand and enhance flooding resistance in our crops. Here, we generated RNA-Seq data from leaf and root tissue of domesticated sunflower to explore differences in gene expression and alternative splicing (AS) between a resistant and susceptible cultivar under both flooding and control conditions and at three time points. Using a combination of mixed model and gene co-expression analyses, we were able to separate general responses of sunflower to flooding stress from those that contribute to the greater tolerance of the resistant line. Both cultivars responded to flooding stress by upregulating expression levels of known submergence responsive genes, such as alcohol dehydrogenases, and slowing metabolism-related activities. Differential AS reinforced expression differences, with reduced AS frequencies typically observed for genes with upregulated expression. Significant differences were found between the genotypes, including earlier and stronger upregulation of the alcohol fermentation pathway and a more rapid return to pre-flooding gene expression levels in the resistant genotype. Our results show how changes in the timing of gene expression following both the induction of flooding and release from flooding stress contribute to increased flooding tolerance.

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