Clustering Of Differentially Expressed Genes Research Articles

Transcriptomic and epigenomic insights into pectoral muscle fiber formation at the late embryonic development in pure chicken lines

Long-term intensive genetic selection has led to significant differences between broiler and layer chickens, which are evident during the embryonic period. Despite this, there is a paucity of research on the genetic regulation of the initial formation of muscle fiber morphology in chick embryos. Embryonic d 17 (E17) is the key time point for myoblast fusion completion and muscle fiber morphology formation in chickens. This study aimed to explore the genetic regulatory mechanisms underlying the early muscle fiber morphology establishment in broiler chickens of Cornish (CC) and White Plymouth Rock (RR) and layer chickens of White Leghorn (WW) at E17 using the transcriptomic and chromatin accessibility sequencing of pectoral major muscles. The results showed that broiler chickens exhibited significant higher embryo weight and pectoral major muscle weight at E17 compared to layer chickens (P = 0.000). A total of 1,278, 1,248, and 892 differentially expressed genes (DEGs) of RNA-seq data were identified between CC vs. WW, RR vs. WW, and CC vs. RR, separately. All DEGs were combined for cluster analysis and they were divided into 6 clusters, including cluster 1 with higher expression in broilers and cluster 6 with higher expression in layers. DEGs in cluster 1 were enriched in terms related to macrophage activation (P = 0.002) and defense response to bacteria (P = 0.002), while DEGs in cluster 6 showed enrichment in protein-DNA complex (P = 0.003) and monooxygenase activity (P = 0.000). ATAC-seq data analysis identified a total of 38,603 peaks, with 13,051 peaks for CC, 18,780 peaks for RR, and 6,772 peaks for WW. Integrative analysis of transcriptomic and chromatin accessibility data revealed GOLM1, ISLR2, and TOPAZ1 were commonly upregulated genes in CC and RR. Furthermore, screening of all upregulated DEGs in cluster 1 from CC and RR identified GOLM1, ISLR2, and HNMT genes associated with neuroimmune functions and MYOM3 linked to muscle morphology development, showing significantly elevated expression in broiler chickens compared to layer chickens. These findings suggest active neural system connectivity during the initial formation of muscle fiber morphology in embryonic period, highlighting the early interaction between muscle fiber formation morphology and the nervous system. This study provides novel insights into late chick embryo development and lays a deeper foundation for further research.

Identification of a novel glioblastoma multiforme molecular subtype with poor prognosis and high immune infiltration based on oxidative stress-related genes.

Glioblastoma multiforme (GBM) is a highly malignant primary brain tumor with a poor prognosis. Reactive oxygen species that accumulate during tumorigenesis can cause oxidative stress (OS), which plays a crucial role in cancer cell survival. Clinical and transcriptome data of TCGA-GBM dataset from UCSC Xena database were analyzed. Consensus clustering analysis was conducted to identify OS-related molecular subtypes for GBM. The immune infiltrate level between subtypes were characterized by ESTIMATE algorithm. Differentially expressed genes (DEGs) between subtypes were screened by DESeq2 package. Two OS-related molecular subtypes of GBM were identified, and cluster 2 had poorer overall survival and higher immune infiltration levels than cluster 1. Enrichment analysis showed that 54 DEGs in cluster 2 were significantly enriched in cytokine/chemokine-related functions or pathways. Ten hub genes (CSF2, CSF3, CCL7, LCN2, CXCL6, MMP8, CCR8, TNFSF11, IL22RA2, and ORM1) were identified in GBM subtype 2 through protein-protein interaction network, most of which were positively correlated with immune factors and immune checkpoints. A total of 55 small molecule drugs obtained from drug gene interaction database (DGIdb) may have potential therapeutic effects in GBM subtype 2 patients. Our study identified 10 hub genes as potential therapeutic targets in GBM subtype 2 patients, who have poorer overall survival and higher immune infiltration levels. These findings could pave the way for new treatments for this aggressive form of brain cancer.

The Effects of De Novo Mutation on Gene Expression and the Consequences for Fitness in Chlamydomonas reinhardtii.

Mutation is the ultimate source of genetic variation, the bedrock of evolution. Yet, predicting the consequences of new mutations remains a challenge in biology. Gene expression provides a potential link between a genotype and its phenotype. But the variation in gene expression created by de novo mutation and the fitness consequences of mutational changes to expression remain relatively unexplored. Here, we investigate the effects of >2,600 de novo mutations on gene expression across the transcriptome of 28 mutation accumulation lines derived from 2 independent wild-type genotypes of the green algae Chlamydomonas reinhardtii. We observed that the amount of genetic variance in gene expression created by mutation (Vm) was similar to the variance that mutation generates in typical polygenic phenotypic traits and approximately 15-fold the variance seen in the limited species where Vm in gene expression has been estimated. Despite the clear effect of mutation on expression, we did not observe a simple additive effect of mutation on expression change, with no linear correlation between the total expression change and mutation count of individual MA lines. We therefore inferred the distribution of expression effects of new mutations to connect the number of mutations to the number of differentially expressed genes (DEGs). Our inferred DEE is highly L-shaped with 95% of mutations causing 0-1 DEG while the remaining 5% are spread over a long tail of large effect mutations that cause multiple genes to change expression. The distribution is consistent with many cis-acting mutation targets that affect the expression of only 1 gene and a large target of trans-acting targets that have the potential to affect tens or hundreds of genes. Further evidence for cis-acting mutations can be seen in the overabundance of mutations in or near differentially expressed genes. Supporting evidence for trans-acting mutations comes from a 15:1 ratio of DEGs to mutations and the clusters of DEGs in the co-expression network, indicative of shared regulatory architecture. Lastly, we show that there is a negative correlation with the extent of expression divergence from the ancestor and fitness, providing direct evidence of the deleterious effects of perturbing gene expression.

Transcriptome analysis of the adenoma–carcinoma sequences identifies novel biomarkers associated with development of canine colorectal cancer

The concept of adenoma-to-cancer transformation in human colorectal cancer (CRC) is widely accepted. However, the relationship between transcriptome features and adenoma to carcinoma transformation in canines is not clear. We collected transcriptome data from 8 normal colon tissues, 4 adenoma tissues, and 15 cancer tissues. Differential analysis was unable to determine the dynamic changes of genes but revealed that PFKFB3 may play a key role in this process. Enrichment analysis explained metabolic dysregulation, immunosuppression, and typical cancer pathways in canine colorectal tumors. MFuzz generated specific dynamic expression patterns of five differentially expressed genes (DEGs). Weighted correlation network analysis showed that DEGs in cluster 3 were associated with malignant tissues, revealing the key role of inflammatory and immune pathways in canine CRC, and the S100A protein family was also found to be involved in the malignant transformation of canine colorectal tumors. By comparing strategies between humans and dogs, we found five novel markers that may be drivers of CRC. Among them, GTBP4 showed excellent diagnostic and prognostic ability. This study was the first systematic exploration of transformation in canine CRC, complemented the molecular characteristics of the development and progression of canine CRC, and provided new potential biomarkers and comparative oncologic evidence for biomarker studies in human colorectal cancer.

Identification and immunological characterization of cuproptosis-related molecular clusters in ischemic stroke.

The present study elucidated cuproptosis-related molecular clusters involved in ischemic stroke and developed predictive models. Transcriptomic and immunological profiles of ischemic stroke-related datasets were extracted from the Gene Expression Omnibus database. Next, we conducted weighted gene co-expression network analysis to determine cluster-specific differentially expressed genes (DEGs). Models such as random forest and eXtreme gradient boosting (XGB) were evaluated to select the best prediction performance model. Subsequently, we validated the model's predictive efficiency by using nomograms, decision curve analysis, calibration curves, and receiver operating characteristic curve analysis with an external dataset. We identified two cuproptosis-related clusters involved in ischemic stroke. The DEGs in Cluster 2 were closely associated with amino acid metabolism, various immune responses, and cell proliferation pathways. The XGB model showed lower residuals, a smaller root mean square error, and a greater area under the curve value (AUC = 0.923), thus exhibiting the best discriminative performance. The AUC value for the external validation dataset was 0.921, thus confirming the high performance of the model. NFE2L2, NLRP3, GLS, LIPT1, and MTF1 were identified as potential cuproptosis predictors, thus shedding new light on ischemic stroke pathogenesis and heterogeneity.

Temporal Comparative Transcriptome Analysis on Wheat Response to Acute Cd Toxicity at the Seedling Stage.

Cadmium (Cd) is a non-essential and toxic metal that accumulates in plant's tissues and diminishes plant growth and productivity. In the present study, differential root transcriptomic analysis was carried out to identify Cd stress-responsive gene networks and functional annotation under Cd stress in wheat seedlings. For this purpose, the Yannong 0428 wheat cultivar was incubated with 40 µm/L of CdCl2·2.5H2O for 6 h at three different seedling growth days. After the quality screening, using the Illumina Hiseq 2000 platform, more than 2482 million clean reads were retrieved. Following this, 84.8% to 89.3% of the clean reads at three time points under normal conditions and 86.5% to 89.1% of the reads from the Cd stress condition were mapped onto the wheat reference genome. In contrast, at three separate seedling growth days, the data analysis revealed a total of 6221 differentially expressed genes (DEGs), including 1543 (24.8%) up-regulated genes and 4678 (75.8%) down-regulated genes. In total, 120 DEGs were co-expressed throughout all the growth days, whereas 1096, 1088, and 2265 DEGs were found to be selectively up-/down-regulated at 7d, 14d, and 30d, respectively. However, the clustering of DEGs, through utilizing the Kyoto Encyclopedia of Genes and Genomes (KEGG), revealed that the DEGs in the metabolic category were frequently annotated for phenylpropanoid biosynthesis. In comparison, a considerable number of DEGs were linked to protein processing in the endoplasmic reticulum under the process of genetic information processing. Similarly, in categories in organismal systems and cellular processes, DEGs were found in plant hormone signal transduction pathways, and DEGs were identified in the plant-pathogen interaction pathway, respectively. However, DEGs in "endocytosis pathways" were enriched in environmental information processing. In addition, in-depth annotations of roughly specific heavy metal stress-response genes and pathways were also mined, and the expression patterns of eight DEGs were studied using quantitative real-time PCR. The results were congruent with the findings of RNA sequencing regarding transcript abundance in the studied wheat cultivar.

Transcriptome Profiling Reveals Candidate Genes Related to Stipe Gradient Elongation of Flammulina filiformis.

Stipe gradient elongation is an important and remarkable feature in the development of most mushroom fruiting bodies. However, its molecular mechanism has rarely been described. Here, the decreasing trend of stipe elongation and increasing trend of cell length in a gradient from the top to the base of the stipe were determined in a model basidiomycete mushroom: Flammulina filiformis. According to RNA-seq results, 1409 differentially expressed genes (DEGs) were identified among elongation region (ER), transition region (TR), and stable region (SR) samples, including 26 transcription factors (TFs). Based on Short Time-series Expression Miner (STEM) clustering of DEGs, clusters 1 and 3, with obvious expression trends that were consistent with or in contrast to the elongation rate, were screened. The cluster 1 DEGs were mainly involved in the GO cellular component category and KEGG genetic information processing class; however, the cluster 3 DEGs were mainly involved in metabolic processes. Furthermore, qRT-PCR confirmed that key genes of the long-chain fatty acid synthesis pathway were involved in stipe gradient elongation and regulated by NADPH oxidase-derived ROS signaling molecules. These findings provide an essential basis for understanding the molecular mechanism of stipe gradient elongation.

Transcriptome analysis of the impact of diabetes as a comorbidity on tuberculosis

Diabetes mellitus patients with pulmonary tuberculosis (DMTB) comorbidity has been recognized as a major obstacle towards achieving the World Health Organization goal of reducing the tuberculosis incidence rate by 90% in 2035. Host immune responses affected by diabetes can lead to increased susceptibility, severity and poor treatment outcomes in DMTB patients, and the underlying mechanisms have not yet been fully elucidated. This study aimed to identify key immunological and cellular components that contribute to increased morbidity and mortality in DMTB cases. We performed RNA-Seq of total RNA isolated from peripheral blood mononuclear cells from 3 TB, 3 diabetes mellitus, and 3 DMTB patients and healthy controls, and analyzed differential expression, pathway enrichment and clustering of differentially-expressed genes (DEGs) to identify biological pathways altered specifically in DMTB patients. Bioinformatic analysis of DEGs suggested that enhanced inflammatory responses, small GTPases, the protein kinase C signaling pathway, hemostasis and the cell cycle pathway are likely implicated in the pathogenesis of the DMTB comorbidity. The DMTB comorbidity is associated with an altered transcriptome and changes in various biological pathways. Our study provides new insights on the pathological mechanism that may aid the development of host-directed therapies for this increasingly prevalent disease in high TB burden countries.

Transcriptome and DNA methylome analyses reveal underlying mechanisms for the racial disparity in uterine fibroids.

Uterine fibroids (leiomyomas) affect Black women disproportionately compared with women of other races and ethnicities in terms of prevalence, incidence, and severity of symptoms. The causes of this racial disparity are essentially unknown. We hypothesized that myometria of Black women are more susceptible to developing fibroids, and we examined the transcriptomic and DNA methylation profiles of myometria and fibroids from Black and White women for comparison. Myometrial samples cluster by race in both their transcriptome and DNA methylation profiles, whereas fibroid samples only cluster by race in the latter. More differentially expressed genes (DEGs) were detected in the Black and White myometrial sample comparison than in the fibroid comparison. Leiomyoma gene set expression analysis identified 4 clusters of DEGs, including a cluster of 24 genes with higher expression in myometrial samples from Black women. One of the DEGs in this group, von Willibrands factor (VWF), was significantly hypomethylated in both myometrial samples from Black women and in all fibroids at 2 CpG probes that are near a putative enhancer site and that are correlated with VWF expression levels. These results suggest that the molecular basis for the disparity in fibroid disease between Black and White women could be found in the myometria before fibroid development and not in the fibroids themselves.

Identification of a pyroptosis-related prognostic signature in breast cancer

BackgroundThe relationship between pyroptosis and cancer is complex. It is controversial that whether pyroptosis represses or promotes tumor development. This study aimed to explore prognostic molecular characteristics to predict the prognosis of breast cancer (BRCA) based on a comprehensive analysis of pyroptosis-related gene expression data.MethodsRNA-sequcing data of BRCA were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Ominibus (GEO) datasets. First, pyroptosis-related differentially expressed genes (DEGs) between normal and tumor tissues were identified from the TCGA database. Based on the DEGs, 1053 BRCA patients were divided into two clusters. Second, DEGs between the two clusters were used to construct a signature by a least absolute shrinkage and selection operator (LASSO) Cox regression model, and the GEO cohort was used to validate the signature. Various statistical methods were applied to assess this gene signature. Finally, Single-sample gene set enrichment analysis (ssGSEA) was employed to compare the enrichment scores of 16 types of immune cells and 13 immune-related pathways between the low- and high-risk groups. We calculated the tumor mutational burden (TMB) of TCGA cohort and evaluated the correlations between the TMB and riskscores of the TCGA cohort. We also compared the TMB between the low- and high-risk groups.ResultsA total of 39 pyroptosis-related DEGs were identified from the TCGA-breast cancer dataset. A prognostic signature comprising 16 genes in the two clusters of DEGs was developed to divide patients into high-risk and low-risk groups, and its prognostic performance was excellent in two independent patient cohorts. The high-risk group generally had lower levels of immune cell infiltration and lower activity of immune pathway activity than did the low-risk group, and different risk groups revealed different proportions of immune subtypes. The TMB is higher in high-risk group compared with low-risk group. OS of low-TMB group is better than that of high-TMB group.ConclusionA 16-gene signature comprising pyroptosis-related genes was constructed to assess the prognosis of breast cancer patients and its prognostic performance was excellent in two independent patient cohorts. The signature was found closely associated with the tumor immune microenvironment and the potential correlation could provide some clues for further studies. The signature was also correlated with TMB and the mechanisms are still warranted.

Molecular Characterization, Tumor Microenvironment Association, and Drug Susceptibility of DNA Methylation-Driven Genes in Renal Cell Carcinoma.

Accumulating evidence suggests that DNA methylation has essential roles in the development of renal cell carcinoma (RCC). Aberrant DNA methylation acts as a vital role in RCC progression through regulating the gene expression, yet little is known about the role of methylation and its association with prognosis in RCC. The purpose of this study is to explore the DNA methylation-driven genes for establishing prognostic-related molecular clusters and providing a basis for survival prediction. In this study, 5,198 differentially expressed genes (DEGs) and 270 DNA methylation-driven genes were selected to obtain 146 differentially expressed DNA methylation-driven genes (DEMDGs). Two clusters were distinguished by consensus clustering using 146 DEMDGs. We further evaluated the immune status of two clusters and selected 106 DEGs in cluster 1. Cluster-based immune status analysis and functional enrichment analysis of 106 DEGs provide new insights for the development of RCC. To predict the prognosis of patients with RCC, a prognostic model based on eight DEMDGs was constructed. The patients were divided into high-risk groups and low-risk groups based on their risk scores. The predictive nomogram and the web-based survival rate calculator (http://127.0.0.1:3496) were built to validate the predictive accuracy of the prognostic model. Gene set enrichment analysis was performed to annotate the signaling pathways in which the genes are enriched. The correlation of the risk score with clinical features, immune status, and drug susceptibility was also evaluated. These results suggested that the prognostic model might be a promising prognostic tool for RCC and might facilitate the management of patients with RCC.

Multi-time scale transcriptomic analysis on the dynamic process of tamoxifen resistance development in breast cancer cell lines.

Approximately 30% of breast cancer patients develop endocrine resistance after tamoxifen therapy. There still lacks a comprehensive understanding on the mechanism of tamoxifen resistance. This study aims to explore the dynamic process of ER + breast cancer resistance to tamoxifen through the time course transcriptomic analysis. The transcriptome profiles of human breast cancer cell line MCF-7 treated with tamoxifen at different time scales were collected from LINCS, SRA and GEO databases. Differentially expressed genes (DEGs) were identified in the short-term tamoxifen treatment and tamoxifen-resistant cell lines. The time course analysis was used to explore the dynamic development of tamoxifen resistance using the transcriptome profiles of tamoxifen-cultured MCF-7 for 1-12weeks. After the short-term treatment of MCF-7 with tamoxifen for 6h or 24h, the expression level of gene PRSS23 was significantly reduced. However, its expression recovered in the resistant cell lines. The time course analysis identified 9 clusters of the DEGs based on the temporal trend of their expression levels. Gene PRSS23 belongs to cluster 2 in which the expression levels were significantly down-regulated in the first 4weeks but gradually recovered afterwards. Functional enrichment analysis of the DEGs in cluster 2 showed that they are significantly enriched in DNA replication, mismatch repair and cell cycle pathways. Their specific role in the resistance development needs to be further explored. The protein-protein interaction network analysis indicates that gene PRSS23 participates in the drug resistance by regulating multiple tamoxifen drug targets. The acquired drug resistance in ER + breast cancer is a complex and dynamic biological process. PRSS23 plays an important role in the development of resistance and is a potential target for overcoming resistance.

Dynamic transcriptome profiles of postnatal porcine skeletal muscle growth and development

BackgroundSkeletal muscle growth and development are closely associated with the quantity and quality of pork production. We performed a transcriptomic analysis of 12 Longissimus dorsi muscle samples from Tibetan piglets at four postnatal stages of 0, 14, 30, and 60 days using RNA sequencing.ResultsAccording to the pairwise comparisons between the libraries of the muscle samples at the four postnatal stages, a total of 4115 differentially expressed genes (DEGs) were identified in terms of |log2(fold change)| ≥ 1 and an adjusted P value < 0.01. Short-time series expression miner (STEM) analysis of the DEGs identified eight significantly different expression profiles, which were divided into two clusters based on the expression pattern. DEGs in cluster I displayed a pattern of decreasing to a nadir, and then a rise, and the significantly enriched gene ontology (GO) terms detected using them were involved in multiple processes, of which the cell cycle, immunocyte activation and proliferation, as well as actin cytoskeleton organization, were the top three overrepresented processes based on the GO terms functional classification. DEGs in cluster II displayed a pattern of increasing to a peak, then declining, which mainly contributed to protein metabolism. Furthermore, besides the pathways related to immune system, a few diseases, and protein metabolism, the DEGs in clusters I and II were significantly enriched in pathways related to muscle growth and development, such as the Rap1, PI3K-Akt, AMPK, and mTOR signaling pathways.ConclusionsThis study revealed GO terms and pathways that could affect the postnatal muscle growth and development in piglets. In addition, this study provides crucial information concerning the molecular mechanisms of muscle growth and development as well as an overview of the piglet transcriptome dynamics throughout the postnatal period in terms of growth and development.

Transcriptomic Analyses of the Adenoma-Carcinoma Sequence Identify Hallmarks Associated With the Onset of Colorectal Cancer.

The concept of the adenoma-carcinoma sequence in colorectal cancer (CRC) is widely accepted. However, the relationship between the characteristics of the transcriptome and the adenoma-carcinoma sequence in CRC remains unclear. Here, the transcriptome profiles of 15 tissue samples from five CRC patients were generated by RNAseq. Six specific dynamic expression patterns of differentially expressed genes (DEGs) were generated by mFuzz. Weighted correlation network analysis showed that DEGs in cluster 4 were associated with carcinoma tissues, and those in cluster 6 were associated with non-normal tissues. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses identified metabolic dysregulation as a consistent finding throughout the transition process, whereas downregulation of the immune response occurred during normal to adenoma transition, and the upregulation of canonical pathways was associated with adenoma to carcinoma transition. Overall survival analysis of patients in cluster 6 identified TPD52L1 as a marker of poor prognosis, and cell proliferation, colony formation, wound healing, and Transwell invasion assays showed that high expression levels of TPD52L1 promoted malignant behaviors. In total, 70 proteins were identified as potential partners of hD53 by mass spectrometry. CRC formation was associated with three cancer hallmarks: dysregulation of metabolism, inactivation of the immune response, and activation of canonical cancer pathways. The TPD52L1 gene was identified as a potential marker to track tumor formation in CRC and as an indicator of poor patient prognosis.

Characterization of transcriptional activity during ZGA in mammalian SCNT embryo†.

Developmental arrest of somatic cell nuclear transfer (SCNT) embryos first occurs at zygotic/embryonic genome activation (ZGA/EGA), which is critical for preimplantation development. However, study on transcriptome of SCNT embryos during ZGA/EGA is limited. In the present study, we performed RNA sequencing (RNA-seq) of the eight-cell SCNT embryos in goat and provide cross-species analysis of transcriptional activity of SCNT embryos during ZGA/EGA in mice, human, bovine, and goat. RNA-seq data revealed 3966 differentially expressed genes (DEGs) failed to be reprogrammed or activated during EGA of SCNT embryos in goat. Series test of cluster analysis showed four clusters of DEGs and similar changes of the clusters in the four species. Specifically, genes in cluster 3 were somehow upregulated compared with the donor cells and the in vitro fertilization embryo. Moreover, the histone methylation key players and N6-methyladenosine modifiers (SUV39H1, SETDB1, SETD2, KDM5B, IGF2BP1, and YTHDF2) were differentially expressed in SCNT embryos of all species. Finally, we identified three modules correlated with the development of SCNT embryos in mice and screened 288 genes (such as BTG4, WEE1, KLF3, and USP21) that are likely critical for SCNT reprogramming using weighted gene correlation network analysis. Our data will broaden the current understanding of transcriptome activity during stochastic reprogramming events and provide an excellent source for future studies.

Molecular Insights into the mechanisms of mucosal immunity induced by Brucella abortus infection in nasal-associated lymphoid tissues

Brucella abortus is highly contagious and can result in abortion or infertility in animals. This study investigated the mechanism of B. abortus-induced mucosal immunity at different points after infection in a mouse model. GSE125765 was obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) in nasal-associated lymphoid tissues at 1, 6, and 12 h after intranasal immunization, compared with control samples, were screened. Functional enrichment analysis was performed using the DAVID tool. Gene modules associated with the sample phenotype were then explored using WGCNA. Mfuzz was used to analyze the expression pattern trends of DEGs. The KEGG pathway directly related to B. abortus infection was searched based on the Comparative Toxicogenomics Database 2019 update. Three gene modules, 172, 366, and 167 DEGs aggregated into four expression patterns, were significantly positively correlated with B. abortus infection. The expression of DEGs in cluster 1 first increased and then decreased with prolonged infection. DEG expression in clusters 2–4 continued to rise with prolonged infection. Genes related to B. abortus infection were significantly enriched in ‘lysosome’ in the Comparative Toxicogenomics Database, including genes CTSL, CD68, SCARB2, and CTSS, which might be necessary for modulating host–B. abortus interactions through the ‘lysosome’ pathway.

Identification of Bioinformatics of the Metastasis of Endometrial Carcinoma Based on Gene Expression Microarray

Objective: We aimed to explore the bioinformatics of endometrial carcinoma (EC) metastasis. Methods: The microarray information of 4 cases of progressive endometrial cancer (PEC) and 4 cases of non-progressive controls (NPC) were collected from the Gene Expression Omnibus Database (GEOD). The Limma package in R was performed to selected the differentially expressed genes (DEGs). Then, the hierarchical clustering of DEGs was carried out. In addition, bioinformatics analysis was carried out. Results: There were 65 DEGs identified between PEC and NPC. Those DEGs were mostly enriched in cell proliferation function, MAPK and TGF-β signaling pathways. Furthermore, those DEGs were related to of the increased contents of IGF2 and PLAG1, and decreased contents of THBS4 and FGF20. Conclusions: There were 65 DEGs identified in endometrial cancer between progressive and non-progressive. Those DEGs were significantly related to tumor metastasis. Increased levels of IGF2 and PLAG1, and decreased levels of THBS4 and FGF20 may have a notable effect on the development of EC.

Global transcriptome analysis of alfalfa reveals six key biological processes of senescent leaves.

Leaf senescence is a complex organized developmental stage limiting the yield of crop plants, and alfalfa is an important forage crop worldwide. However, our understanding of the molecular mechanism of leaf senescence and its influence on biomass in alfalfa is still limited. In this study, RNA sequencing was utilized to identify differentially expressed genes (DEGs) in young, mature, and senescent leaves, and the functions of key genes related to leaf senescence. A total of 163,511 transcripts and 77,901 unigenes were identified from the transcriptome, and 5,133 unigenes were differentially expressed. KEGG enrichment analyses revealed that ribosome and phenylpropanoid biosynthesis pathways, and starch and sucrose metabolism pathways are involved in leaf development and senescence in alfalfa. GO enrichment analyses exhibited that six clusters of DEGs are involved in leaf morphogenesis, leaf development, leaf formation, regulation of leaf development, leaf senescence and negative regulation of the leaf senescence biological process. The WRKY and NAC families of genes mainly consist of transcription factors that are involved in the leaf senescence process. Our results offer a novel interpretation of the molecular mechanisms of leaf senescence in alfalfa.

Identification of Potential Molecular Mechanisms and Candidate Genes Involved in The Acute Phase of Myocardial Infarction.

Objective This study used bioinformatics to determine genetic factors involved in progression of acute myocardial infarction (MI). Materials and Methods In this prospective study, gene expression profile GSE59867 was downloaded from the Gene Expression Omnibus database, which contained 46 normal samples obtained from stable coronary artery disease patients (n=46) who were without history of MI (control) and 390 samples from patients (n=111) who had evolving ST-segment elevation myocardial infarction (STEMI) as the MI group. These samples were divided into 4 groups based on time points. After identification of differentially expressed genes (DEGs), we conducted hierarchical clustering and functional enrichment analysis. Protein interaction and transcriptional regulation among DEGs were analysed. Results We observed 8 clusters of DEGs that had a peak or a minimum at the t=1 time point according to gene expression levels. Upregulated DEGs showed significant enrichment in the biological process, single-organism cellular process, response to stimulus and stress, and osteoclast differentiation and lysosome. Downregulated DEGs enriched in the T-cell receptor signalling pathway and natural killer cell mediated cytotoxicity. We identified multiple genes, including signal transducer and activator of transcription 3 (STAT3); LCK proto-oncogene, Src family tyrosine kinase (LCK); and FYN proto-oncogene, Src family tyrosine kinase (FYN) from the protein-protein interaction (PPI) network and/or the transcriptional regulatory network. ConclusionCytokine-mediated inflammation, lysosome and osteoclast differentiation, and metabolism processes, as well as STAT3 may be involved in the acute phase of MI.

Bioinformatics analysis of the CDK2 functions in neuroblastoma.

The present study aimed to elucidate the potential mechanism of cyclin-dependent kinase 2 (CDK2) in neuroblastoma progression and to identify the candidate genes associated with neuroblastoma with CDK2 silencing. The microarray data of GSE16480 were obtained from the gene expression omnibus database. This dataset contained 15samples: Neuroblastoma cell line IMR32 transfected with CDK2 shRNA at 0, 8, 24, 48 and 72h (n=3 per group; total=15). Significant clusters associated with differentially expressed genes (DEGs) were identified using fuzzy C‑Means algorithm in the Mfuzz package. Gene ontology and pathway enrichment analysis of DEGs in each cluster were performed, and a protein‑protein interaction (PPI) network was constructed. Additionally, functional annotation of DEGs in clusters was performed for the detection of transcription factors and tumor‑associated genes. A total of 4 clusters with significant change tendency and 1,683 DEGs were identified. The hub nodes of the PPI network constructed by DEGs in Cluster 1, Cluster 2, Cluster 3 and Cluster 4 were MDM2 oncogene, E3 ubiquitin protein ligase (MDM2), cyclin‑dependent kinase 1 (CDK1), proteasome (prosome, macropain) 26S subunit, non‑ATPase, 14 (PSMD14) and translocator protein (18kDa) (TSPO) respectively. These genes were significantly enriched in the p53 signaling pathway, cell cycle, proteasome and systemic lupus erythematosus pathways. MDM2, CDK1, PSMD14 and TSPO may be key target genes of CDK2. CDK2 may have key functions in neuroblastoma progression by regulating the expression of these genes.