Key Differentially Expressed Genes Research Articles

Bioinformatics analysis identifies the protective targets of omentin in mice with focal cerebral ischemia injury

Omentin is known to play a protective role in ischemic stroke. However, its regulatory networks and downstream targets in the pathogenesis of IS are incompletely revealed now. In this study, the model of photochemical brain ischemia was constructed after omentin over-expression. 8 key differentially expressed genes (DEGs) were obtained and analyzed by transcriptome analysis. These DEGs were mainly related to the negative regulation of hormone secretion, cellular phosphate ion homeostasis, and other pathways. Moreover, the mRNA expression of predicted gene 3435 (Gm3435), ankyrin repeat domain 53 (Ankrd53), fibroblast growth factor 23 (Fgf23) and the Fgf23 protein expression were down-regulated after omentin over-expression in HT22 cells injured by oxygen-glucose deprivation (OGD). In conclusion, our findings identified 8 key DEGs regulated by omentin after IS. In vitro models, the Gm3435, Ankrd53, Fgf23 mRNA expression and the Fgf23 protein expression were further verified to consistent with the transcriptomics results.

Identification of Potential Biomarkers for Group I Pulmonary Hypertension Based on Machine Learning and Bioinformatics Analysis.

A number of processes and pathways have been reported in the development of Group I pulmonary hypertension (Group I PAH); however, novel biomarkers need to be identified for a better diagnosis and management. We employed a robust rank aggregation (RRA) algorithm to shortlist the key differentially expressed genes (DEGs) between Group I PAH patients and controls. An optimal diagnostic model was obtained by comparing seven machine learning algorithms and was verified in an independent dataset. The functional roles of key DEGs and biomarkers were analyzed using various in silico methods. Finally, the biomarkers and a set of key candidates were experimentally validated using patient samples and a cell line model. A total of 48 key DEGs with preferable diagnostic value were identified. A gradient boosting decision tree algorithm was utilized to build a diagnostic model with three biomarkers, PBRM1, CA1, and TXLNG. An immune-cell infiltration analysis revealed significant differences in the relative abundances of seven immune cells between controls and PAH patients and a correlation with the biomarkers. Experimental validation confirmed the upregulation of the three biomarkers in Group I PAH patients. In conclusion, machine learning and a bioinformatics analysis along with experimental techniques identified PBRM1, CA1, and TXLNG as potential biomarkers for Group I PAH.

Comparative transcriptomic analysis reveals that TPX2 and AURXA are involved in porcine PCV2 infection

Porcine circovirus type 2 (PCV2) has been a notorious killer for the pig industry, causing substantial economic losses worldwide. However, its pathogenesis is still poorly understood. Comparative transcriptomic analysis and weighted gene co-expression network analysis (WGCNA) were performed in different porcine tissues after PCV2 infection. Our comparative transcriptomic analysis obtained 40 key differentially expressed genes (DEGs), and our WGCNA identified 458 hub genes. Significantly, both TPX2 microtubule nucleation factor (TPX2) and Aurora kinase A (AURKA) are included in these key DEGs and hubs genes. Our gene ontology (GO) analysis indicated that the key DEGs and hub genes participated in cell cycle regulation and immune response. The expressive levels of TPX2 and AURKA went down in the spleen but up in the kidneys after infection with PCV2. We conclude that TPX2 and AURKA played an essential role in PCV2 infection.

Gastrodin Exerts Cardioprotective Action via Inhibition of Insulin-Like Growth Factor Type 2/Insulin-Like Growth Factor Type 2 Receptor Expression in Cardiac Hypertrophy.

Pathological cardiac hypertrophy is commonly associated with an upregulation of fetal genes, fibrosis, cardiac dysfunction, and heart failure. Previous studies have demonstrated that gastrodin (GAS) exerts cardioprotective action in the treatment of cardiac hypertrophy. However, the mechanism by which GAS protects against cardiac hypertrophy is yet to be elucidated. A mouse model of myocardial hypertrophy was established using an angiotensin II (Ang II) induction. GAS (5 or 50 mg/kg/d) was orally administered every day starting 7 days prior to the Ang II infusion combined with sham-operated controls. Heart samples from each group were collected for RNA sequencing. Using bioinformatics analysis, the key differentially expressed genes (DEGs) that are involved in reversing cardiac function were identified. Through bioinformatics analysis, the key DEGs that are involved in GAS’s inhibition of Ang II-induced abnormal gene expression within the heart were identified. This was further validated using quantitative real-time PCR and Western blotting in neonatal rat cardiomyocytes (NRCMs). Oral administration of GAS significantly suppressed the Ang II-induced increase in heart size and heart weight to body weight. Furthermore, pretreatment of the NRCMs with GAS led to a dose-dependent inhibition of Ang II-induced increases in Nppb mRNA expression. We identified 620 upregulated and 87 downregulated Ang II-induced DEGs II, among which the expression patterns of 58 and 146 genes were inverted by low-dose and high-dose GAS, respectively. These inverted DEGs were found to be mainly enriched in the biological processes of regulation of Ras protein signal transduction, heart contraction, covalent chromatin modification, glucose metabolism, and positive regulation of cell cycle. Among them, the insulin-like growth factor type 2 (Igf2) gene, which was found to be highly reversed and downregulated by GAS, served as a core gene linking energy metabolism, immune regulation, and systemic development. Subsequent functional verification demonstrated that IGF2, and its receptor IGF2R, is one of the targets of GAS that helps protect against cardiac hypertrophy. Taken together, we have identified, for the first time, IGF2/IGF2R as a potential target influenced by GAS in the prevention of cardiac hypertrophy.

Discovery of core gene families associated with liver metastasis in colorectal cancer and regulatory roles in tumor cell immune infiltration

In this study, we aimed to uncover genes that drive the pathogenesis of liver metastasis in colorectal cancer (CRC), and identify effective genes that could serve as potential therapeutic targets for treating with colorectal liver metastasis patients based on two GEO datasets. Several bioinformatics approaches were implemented. First, differential expression analysis screened out key differentially expressed genes (DEGs) across the two GEO datasets. Based on gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, we identified the enrichment functions and pathways of the DEGs that were associated with liver metastasis in CRC. Second, immune infiltration analysis identified key immune signature gene sets associated with CRC liver metastasis, among which two key immune gene families (CD and CCL) identified as key DEGs were filtered by protein-protein interaction (PPI) network. Some of the members in these gene families were associated with disease free survival (DFS) or overall survival (OS) in two subtypes of CRC, namely COAD and READ. Finally, functional enrichment analysis of the two gene families and their neighboring genes revealed that they were closely associated with cytokine, leukocyte proliferation and chemotaxis. These results are valuable in comprehending the pathogenesis of liver metastasis in CRC, and are of seminal importance in understanding the role of immune tumor infiltration in CRC. Our study also identified potentially effective therapeutic targets for liver metastasis in CRC including CCL20, CCL24 and CD70.

Identification of Differentially Expressed Genes and Lipid Metabolism Signaling Pathways between Muscle and Fat Tissues in Broiler Chickens.

In this study, signaling pathways and key differentially expressed genes (DEGs) involved in lipid metabolism in muscle and fat tissues were investigated. Muscle and abdominal fat tissues were obtained from 35-day-old female broilers for RNA sequencing. DEGs between muscle and fat tissues were identified. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of DEGs were performed. A total of 6130 DEGs were identified to be significantly enriched in 365 GO terms, most of which were involved in biological processes, cellular components, and molecular functions in muscle and fat tissues. Three important lipid signaling pathways (pyruvate metabolism, the insulin signaling pathway, and the adipocytokine signaling pathway) were identified among the fat and muscle tissues of broilers. The key common DEGs in these pathways included phosphoenolpyruvate carboxykinase 2 (PCK2), acetyl-CoA carboxylase 1 alpha and beta (ACACA and ACACB), and the mitogen-activated protein kinase (AMPK) gene family. Hence, our findings revealed the pathways and key genes and gene families involved in the regulation of fat deposition in the muscle and fat tissues of broilers.

Integrated Analysis of Key Differentially Expressed Genes Identifies DBN1 as a Predictive Marker of Response to Endocrine Therapy in Luminal Breast Cancer.

Endocrine therapy is the mainstay of adjuvant treatment for patients with luminal breast cancer. Despite ongoing advances in endocrine therapy to date, a proportion of patients ultimately develop endocrine resistance, resulting in failure of therapy and poor prognosis. Therefore, as part of the growing concept of personalised medicine, the need for identification of predictive markers of endocrine therapy response at an early stage, is recognised. The METABRIC series was used to identify differentially expressed genes (DEGs) in term of response to adjuvant endocrine therapy. Drebrin 1 (DBN1) was identified as a key DEG associated with response to hormone treatment. Next, large, well-characterised cohorts of primary luminal breast cancer with long-term follow-up were assessed at the mRNA and protein levels for the value of DBN1 as a prognostic marker in luminal breast cancer, as well as its potential for predicting the benefit of endocrine therapy. DBN1 positivity was associated with aggressive clinicopathological variables and poor patient outcomes. Importantly, high DBN1 expression predicted relapse patients who were subject to adjuvant endocrine treatment. Our results further demonstrate that DBN1 is an independent prognostic marker in luminal breast cancer. Its association with the response to endocrine therapy and outcome provides evidence for DBN1 as a potential biomarker in luminal breast cancer, particularly for the benefit of endocrine treatment. Further functional investigations into the mechanisms underlying sensitivity to endocrine therapy is required.

Identification of key differentially expressed genes between ER-positive/HER2-negative breast cancer and ER-negative/HER2-negative breast cancer using integrated bioinformatics analysis.

Treatment strategies for various subtypes of breast cancer (BC) are different based on their distinct molecular characteristics. Therefore, it is very important to identify key differentially expressed genes (DEGs) between ER-positive/HER2-negative BC and ER-negative/HER2-negative BC. Gene expression profiles of GSE22093 and GSE23988 were obtained from the Gene Expression Omnibus database. There were 74 ER-positive/HER2-negative BC tissues and 85 ER-negative/HER2-negative BC tissues in the two profile datasets. DEGs between ER-positive/HER2-negative tissues and ER-negative/HER2-negative BC tissues were identified by the GEO2R tool. The common DEGs among the two datasets were detected with Venn software online. Next, we made use of the Database for Annotation, Visualization and Integrated Discovery to analyze enriched Kyoto Encyclopedia of Gene and Genome (KEGG) pathways and gene ontology terms. Then, the protein-protein interactions (PPIs) of these DEGs were visualized by Cytoscape with the Search Tool for the Retrieval of Interacting Genes. Of the proteins in the PPI network, Molecular Complex Detection plug-in analysis identified nine core upregulated genes and one core downregulated gene. UALCAN and Gene Expression Profiling Interactive Analysis were applied to determine the expression of these 10 genes in BC. Furthermore, for the analysis of overall survival among those genes, the Kaplan-Meier method was implemented. Ninety-three common DEGs (63 upregulated and 30 downregulated) were identified. KEGG pathway enrichment analysis showed that upregulated DEGs were particularly enriched in the progesterone-mediated oocyte maturation pathway. In addition, PGR might be a prognostic biomarker for ER-positive/HER2-negative BC. CCND1 is a poor prognostic biomarker for ER-positive/HER2-negative BC and ER-negative/HER2-negative BC. Moreover, TFF1, AGR2 and EGFR might be predictive biomarkers of node metastasis in ER-positive/HER2-negative BC and ER-negative/HER2-negative BC. CCND1, AGR2, PGR, TFF1 and EGFR are the key DEGs between ER-positive/HER2-negative BC and ER-negative/HER2-negative BC. Further studies are required to confirm the functions of the identified genes.

Transcriptome Analysis of Low-Temperature-Induced Breaking of Garlic Aerial Bulb Dormancy.

The long history of asexual reproduction of garlic using garlic cloves has resulted in virus accumulation and genetic depression. Propagation of garlic seedlings by tissue culture can both eliminate viruses and improve breeding efficiency. Aerial bulbs are the first-choice materials for breeding virus-free garlic seedlings under external conditions, but they show dormancy just like garlic bulbs. However, low temperatures can quickly break dormancy. In this research, we used a high-throughput sequencing method to sequence aerial bulbs during dormancy and after low-temperature-induced breaking of dormancy to screen out the key differentially expressed genes (DEGs) associated with low temperature and to provide a theoretical basis for exploring the molecular mechanism of low-temperature-induced breaking of aerial bulb dormancy. The high-throughput transcriptome sequencing results showed that 6,675 DEGs were upregulated and 36,596 DEGs were downregulated in the aerial bulbs given low-temperature treatment. Then, 19,507 DEGs were assigned KEGG annotations, among which most DEGs were annotated to the metabolism pathway (11,817 genes, accounting for 60.58%), followed by the genetic information processing pathway (4,521 genes, accounting for 23.18%). The DEGs were mostly concentrated in pathways such as protein processing in the endoplasmic reticulum, plant-pathogen interaction, plant hormone signal transduction, and ribosome biogenesis in eukaryotes, with significant enrichment. The key DEGs related to calcium signaling, hormonal signaling, and transcription factors were screened out, including CaM, CDPK, and CML in accessory pathways of calcium signaling; GA20ox, GAI1, and GA2ox in accessory pathways of hormonal signaling; and transcription factor genes such as MYB, AP2/ERF, bHLH, MADS, and bZIP. qRT-PCR verification results were consistent with the sequencing results, indicating that the transcriptome sequencing data were accurate and reliable. Our results provide a theoretical basis for breaking the dormancy of aerial bulbs with low-temperature treatment to produce virus-free seedlings and increase the output and quality of garlic.

Bioinformatics Analysis of Key Differentially Expressed Genes in Nonalcoholic Fatty Liver Disease Mice Models.

Nonalcoholic fatty liver disease (NAFLD) is a global health problem characterized by excessive accumulation of fat in the liver without effect of other pathological factors including hepatitis infection and alcohol abuse. Current studies indicate that gene factors play important roles in the development of NAFLD. However, the molecular characteristics of differentially expressed genes (DEGs) and associated mechanisms with NAFLD have not been well elucidated. Using two microarray data associated with the gene expression profiling in liver tissues of NAFLD mice models, we identified and selected several common key DEGs that contributed to NAFLD. Based on bioinformatics analysis, we discovered that the DEGs were associated with a variety of biological processes, cellular components, and molecular functions and were also related to several significant pathways. Via pathway crosstalk analysis based on overlapping DEGs, we observed that the identified pathways could form large and complex crosstalk networks. Besides, large and complex protein interaction networks of DEGs were further constructed. In addition, many hub host factors with a high degree of connectivity were identified based on interaction networks. Furthermore, significant modules in interaction networks were found, and the DEGs in the identified modules were found to be enriched with distinct pathways. Taken together, these results suggest that the key DEGs, associated pathways, and modules contribute to the development of NAFLD and might be used as novel molecular targets for the treatment of NAFLD.