Gene expression levels of Casein kinase 1 (CK1) isoforms are correlated to adiponectin levels in adipose tissue and site-specific phosphorylation mediated by CK1 influences multimerization of adiponectin

Leptin and nitric oxide (NO) are implicated in the control of energy homeostasis. The aim of the present study was to examine the impact of the absence of the inducible NO synthase ( iNOS) gene on the regulation of energy balance in ob/ob mice analyzing the changes in gene expression levels in brown adipose tissue (BAT). Double knockout (DBKO) mice simultaneously lacking the ob and iNOS genes were generated and the expression of genes involved in energy balance including fatty acid and glucose metabolism as well as mitochondrial genes were analyzed by microarrays. DBKO mice exhibited an improvement in energy balance with a decrease in body weight ( P < 0.001), total fat pads ( P < 0.05), and food intake ( P < 0.05), as well as an enhancement in BAT function compared with ob/ob mice. To better understand the molecular events associated with this improvement, BAT gene expression was analyzed. Of particular interest, gene expression levels of the key subunit of the Mediator complex Med1 was upregulated ( P < 0.05) in DBKO mice. Real-time PCR and immunohistochemistry further confirmed this data. Med1 is implicated in adipogenesis, lipid metabolic and biosynthetic processes, glucose metabolism, and mitochondrial metabolic pathways. Med1 plays an important role in the transcriptional control of genes implicated in energy homeostasis, suggesting that the improvement in energy balance and BAT function of the DBKO mice is mediated, at least in part, through the transcription coactivator Med1.

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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 ◽

10.3390/genes12060854 ◽

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.

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Supplementation of postbiotic RI11 improves antioxidant enzymes activity, upregulated gut barrier genes and reduced cytokines, acute phase proteins and heat shock protein70 gene expression levels in heat-stressed broilers

Poultry Science ◽

10.1016/j.psj.2020.12.011 ◽

2020 ◽

Author(s):

Ali Merzza Humam ◽

Teck Chwen Loh ◽

Hooi Ling Foo ◽

Wan Ibrahim Izuddin ◽

Idrus Zulkifli ◽

...

Keyword(s):

Gene Expression ◽

Antioxidant Enzymes ◽

Heat Shock ◽

Acute Phase ◽

Acute Phase Proteins ◽

Gut Barrier ◽

Expression Levels ◽

Enzymes Activity ◽

Gene Expression Levels

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

Human Genomics ◽

10.1186/s40246-021-00308-5 ◽

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.

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Effects of root restriction on nitrogen and gene expression levels in nitrogen metabolism in Jumeigui grapevines (Vitis vinifera L.×Vitis labrusca L.)

Journal of Integrative Agriculture ◽

10.1016/s2095-3119(14)60876-5 ◽

2015 ◽

Vol 14 (1) ◽

pp. 67-79 ◽

Cited By ~ 4

Author(s):

Xiu-ming YU ◽

Jie-fa LI ◽

Li-na ZHU ◽

Bo WANG ◽

Lei WANG ◽

...

Keyword(s):

Gene Expression ◽

Vitis Vinifera ◽

Nitrogen Metabolism ◽

Vitis Vinifera L ◽

Vitis Labrusca ◽

Expression Levels ◽

Root Restriction ◽

Gene Expression Levels

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

Agronomy ◽

10.3390/agronomy11010092 ◽

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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