scholarly journals Network analysis reveals the relationship among wood properties, gene expression levels and genotypes of naturalPopulus trichocarpaaccessions

2013 ◽  
Vol 200 (3) ◽  
pp. 727-742 ◽  
Author(s):  
Ilga Porth ◽  
Jaroslav Klápště ◽  
Oleksandr Skyba ◽  
Michael C. Friedmann ◽  
Jan Hannemann ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Wood Properties ◽  
Expression Levels ◽  
The Relationship ◽  
Gene Expression Levels

The relationship between proangiogenic gene expression levels in prostate cancer and their prognostic value for clinical outcomes

The Prostate ◽  
2010 ◽  
Vol 70 (15) ◽  
pp. 1692-1700 ◽  
Author(s):  
Ryutaro Mori ◽  
Tanya B. Dorff ◽  
Shigang Xiong ◽  
Chad J. Tarabolous ◽  
Wei Ye ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Clinical Outcomes ◽  
Prognostic Value ◽  
Expression Levels ◽  
The Relationship ◽  
Gene Expression Levels

Association between Quantitative MR Markers of Cortical Evolving Organization and Gene Expression during Human Prenatal Brain Development

2021 ◽  
Author(s):  
Lana Vasung ◽  
Chenying Zhao ◽  
Matthew Barkovich ◽  
Caitlin K Rollins ◽  
Jennings Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Structural Changes ◽  
Vascular Malformations ◽  
Fetal Brain ◽  
Cortical Plate ◽  
Expression Levels ◽  
Quantitative Mr ◽  
Magnetic Resonance Imaging Mri ◽  
The Relationship ◽  
Gene Expression Levels

Abstract The relationship between structural changes of the cerebral cortex revealed by Magnetic Resonance Imaging (MRI) and gene expression in the human fetal brain has not been explored. In this study, we aimed to test the hypothesis that relative regional thickness (a measure of cortical evolving organization) of fetal cortical compartments (cortical plate [CP] and subplate [SP]) is associated with expression levels of genes with known cortical phenotype. Mean regional SP/CP thickness ratios across age measured on in utero MRI of 25 healthy fetuses (20–33 gestational weeks [GWs]) were correlated with publicly available regional gene expression levels (23–24 GW fetuses). Larger SP/CP thickness ratios (more pronounced cortical evolving organization) was found in perisylvian regions. Furthermore, we found a significant association between SP/CP thickness ratio and expression levels of the FLNA gene (mutated in periventricular heterotopia, congenital heart disease, and vascular malformations). Further work is needed to identify early MRI biomarkers of gene expression that lead to abnormal cortical development.

scholarly journals Analysis of the Relationship Between Learning and Synaptophysin in Obese Rats Treated With DPP4 Inhibitor

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A532-A532
Author(s):  
Murat Korkmaz ◽  
Sibel Oguzkan Balci ◽  
Can Demirel ◽  
Ibrahim Yilmaz ◽  
Ersin Akarsu
Keyword(s):  
Gene Expression ◽  
Learning Performance ◽  
Control Group ◽  
Albino Rats ◽  
Expression Levels ◽  
Dpp4 Inhibitor ◽  
Significant Difference ◽  
Learning Test ◽  
The Relationship ◽  
Gene Expression Levels

Abstract In this study, it is aimed to investigate possible changes in cognitive functions in obesity by using targeted treatment hypothesis. Accordingly, the effects of DPP4 inhibitor, which is actively used in the clinic in the treatment of diabetes, and the effect of exercise, which has been proven to be effective in the treatment of obesity, on the change of learning performance and the relationship of these effects with the synaptophysin molecule were investigated. In our study, 42 Wistar albino rats were used. The animals were randomly divided into seven groups as obese, control, obese+DPP4i, control+DPP4i, obese+exercise, control+exercise, control+NaCl. To create experimental obesity, the animals that are targeted to be obese were separated and fed on a high fat diet for 8 weeks. After the obese model was created, sitagliptin was applied to the DPP4i groups and swimming exercise was applied to the exercise groups for obesity treatment. The last week of the study was performed reference memory learning test to the whole group with Morris water maze. Then, the hippocampus tissues were removed from the animals under anesthesia. mRNA and protein isolations were performed from the extracted tissues. Synaptophysin gene expressions were determined from mRNA samples by Real-Time PCR method. Synaptophysin protein levels were determined from protein lysates by Western Blot method. In the learning test, in the obese groups, there was a statistically significant difference between the average escape time of the DPP4i and exercise groups and the groups that did not (p<0.05). As a result, in groups where obesity is treated with DPP4i and exercise; It was concluded that cognitive performance was better than obese groups. There was a evident decrease in synaptophysin gene expression levels in obese groups compared to the control group. In the treatment groups, an increase was observed in synaptophysin gene expression levels in the DPP4 inhibitor and especially in the exercise groups compared to the control groups (P> 0.05). Gene expression results were similar in analyzes performed at the protein level. According to these results, in terms of performance in cognitive function due to obesity and synaptophysin gene relationship; DPP4 inhibitor showed as effective a result as exercise. This provides a resource for advanced molecular and metabolic research. Acknowledgement: This study was supported by The Scientific And Technological Research Council Of Turkey (TÜBİTAK) Project No. 219S063.

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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