scholarly journals Comparative Transcriptome Analysis Suggests Key Roles for 5-Hydroxytryptamlne Receptors in Control of Goose Egg Production

Genes ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 455 ◽  
Author(s):  
Qingyuan Ouyang ◽  
Shenqiang Hu ◽  
Guosong Wang ◽  
Jiwei Hu ◽  
Jiaman Zhang ◽  
...  
Keyword(s):  
Egg Production ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Production Performance ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Anser Anser

To date, research on poultry egg production performance has only been conducted within inter or intra-breed groups, while those combining both inter- and intra-breed groups are lacking. Egg production performance is known to differ markedly between Sichuan white goose (Anser cygnoides) and Landes goose (Anser anser). In order to understand the mechanism of egg production performance in geese, we undertook this study. Here, 18 ovarian stromal samples from both Sichuan white goose and Landes goose at the age of 145 days (3 individuals before egg production initiation for each breed) and 730 days (3 high- and low egg production individuals during non-laying periods for each breed) were collected to reveal the genome-wide expression profiles of ovarian mRNAs and lncRNAs between these two geese breeds at different physiological stages. Briefly, 58, 347, 797, 777, and 881 differentially expressed genes (DEGs) and 56, 24, 154, 105, and 224 differentially expressed long non-coding RNAs (DElncRNAs) were found in LLD vs. HLD (low egg production Landes goose vs. high egg production Landes goose), LSC vs. HSC (low egg production Sichuan White goose vs. high egg production Sichuan white goose), YLD vs. YSC (young Landes goose vs. young Sichuan white goose), HLD vs. HSC (high egg production Landes goose vs. high egg production Sichuan white goose), and LLD vs. LSC (low egg production Landes goose vs. low egg production Sichuan white goose) groups, respectively. Functional enrichment analysis of these DEGs and DElncRNAs suggest that the “neuroactive ligand–receptor interaction pathway” is crucial for egg production, and particularly, members of the 5-hydroxytryptamine receptor (HTR) family affect egg production by regulating ovarian metabolic function. Furthermore, the big differences in the secondary structures among HTR1F and HTR1B, HTR2B, and HTR7 may lead to their different expression patterns in goose ovaries of both inter- and intra-breed groups. These results provide novel insights into the mechanisms regulating poultry egg production performance.

scholarly journals Immunogenomic Landscape Analysis of Prognostic Immune-Related Genes in Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Peng Qin ◽  
Mengyu Zhang ◽  
Xue Liu ◽  
Ziming Dong
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Immune Related Genes

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death. HBV infection is an important risk factor for the tumorigenesis of HCC, given that the inflammatory environment is closely related to morbidity and prognosis. Consequently, it is of urgent importance to explore the immunogenomic landscape to supplement the prognosis of HCC. The expression profiles of immune‐related genes (IRGs) were integrated with 377 HCC patients to generate differentially expressed IRGs based on the Cancer Genome Atlas (TCGA) dataset. These IRGs were evaluated and assessed in terms of their diagnostic and prognostic values. A total of 32 differentially expressed immune‐related genes resulted as significantly correlated with the overall survival of HCC patients. The Gene Ontology functional enrichment analysis revealed that these genes were actively involved in cytokine‐cytokine receptor interaction. A prognostic signature based on IRGs (HSPA4, PSME3, PSMD14, FABP6, ISG20L2, TRAF3, NDRG1, NRAS, CSPG5, and IL17D) stratified patients into high-risk versus low-risk groups in terms of overall survival and remained as an independent prognostic factor in multivariate analyses after adjusting for clinical and pathologic factors. Several IRGs (HSPA4, PSME3, PSMD14, FABP6, ISG20L2, TRAF3, NDRG1, NRAS, CSPG5, and IL17D) of clinical significance were screened in the present study, revealing that the proposed clinical-immune signature is a promising risk score for predicting the prognosis of HCC.

scholarly journals Identification of a prognostic long non-coding RNA signature in breast cancer

2020 ◽  
Author(s):  
Gaochen Lan ◽  
Xiaoling Yu ◽  
Yanna Zhao ◽  
Jinjian Lan ◽  
Wan Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cox Regression ◽  
Prognostic Biomarker ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Cox Regression Analysis

Abstract Background: Breast cancer is the most common malignant disease among women. At present, more and more attention has been paid to long non-coding RNAs (lncRNAs) in the field of breast cancer research. We aimed to investigate the expression profiles of lncRNAs and construct a prognostic lncRNA for predicting the overall survival (OS) of breast cancer.Methods: The expression profiles of lncRNAs and clinical data with breast cancer were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were screened out by R package (limma). The survival probability was estimated by the Kaplan‑Meier Test. The Cox Regression Model was performed for univariate and multivariate analysis. The risk score (RS) was established on the basis of the lncRNAs’ expression level (exp) multiplied regression coefficient (β) from the multivariate cox regression analysis with the following formula: RS=exp a1 * β a1 + exp a2 * β a2 +……+ exp an * β an. Functional enrichment analysis was performed by Metascape.Results: A total of 3404 differentially expressed lncRNAs were identified. Among them, CYTOR, MIR4458HG and MAPT-AS1 were significantly associated with the survival of breast cancer. Finally, The RS could predict OS of breast cancer (RS=exp CYTOR * β CYTOR + exp MIR4458HG * β MIR4458HG + exp MAPT-AS1 * β MAPT-AS1). Moreover, it was confirmed that the three-lncRNA signature could be an independent prognostic biomarker for breast cancer (HR=3.040, P=0.000).Conclusions: This study established a three-lncRNA signature, which might be a novel prognostic biomarker for breast cancer.

scholarly journals Identifcation of The Ferroptosis-Related Gene Signature In Placenta of Patients With Early-Onset Preeclampsia

2021 ◽  
Author(s):  
Nana Yang ◽  
Qianghua Wang ◽  
Biao Ding ◽  
Yinging Gong ◽  
Yue Wu ◽  
...  
Keyword(s):  
Iron Homeostasis ◽  
Molecular Mechanisms ◽  
Late Onset ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Ppi Network ◽  
Network Analyses

Abstract Background: The accumulation of ROS resulting from upregulated levels of oxidative stress is commonly implicated in preeclampsia (PE). Ferroptosis is a novel form of iron-dependent cell death instigated by lipid peroxidation likely plays important role in PE pathogenesis. This study aims to investigate expression profiles and functions of the ferroptosis-related genes (FRGs) in early- and late-onset preeclampsia.Methods: The gene expression data and clinical information were downloaded from GEO database. The “limma” R package was used for screening differentially expressed genes. GO(Gene Ontology), Kyoto Encyclopedia of Genes and Genomes(KEGG) and protein protein interaction (PPI) network analyses were conducted to investigate the bioinformatics functions and molecular interactions of significantly different FRGs. Quantitative real-time reverse transcriptase PCR was used to verify the expression of hub FRGs in PE.Results: A total number of 4,215 DEGs were identified between EOPE and preterm cases and 3,356 DEGs were found between EOPE and LOPE subtypes. 20 significantly different FRGs were identified in EOPE, while only 3 in LOPE. Functional enrichment analysis revealed that the differentially expressed FRGs was mainly involved in EOPE and enriched in hypoxia- and iron-related pathways, such as response to hypoxia, iron homeostasis and iron ion binding process. The PPI network analysis and verification by RT-qPCR resulted in the identification of the following six interesting FRGs: FTH1, HIF1A, FTL, IREB2, MAPK8 and PLIN2. Conclusions: EOPE and LOPE owned distinct underlying molecular mechanisms and ferroptosis may be mainly implicated in pathogenesis of EOPE. Further studies are necessary for deeper inquiry into placental ferroptosis and its role in the pathogenesis of EOPE.

scholarly journals Protein expression profiles in Meishan and Duroc sows during mid-gestation reveal differences affecting uterine capacity, endometrial receptivity, and the maternal–fetal Interface

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Kejun Wang ◽  
Kaijie Yang ◽  
Qiao Xu ◽  
Yufang Liu ◽  
Wenting Li ◽  
...  
Keyword(s):  
Protein Expression ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Embryonic Mortality ◽  
Functional Enrichment ◽  
Matrix Remodeling ◽  
Swine Industry ◽  
Embryonic Loss

Abstract Background Embryonic mortality is a major concern in the commercial swine industry and primarily occurs early in gestation, but also during mid-gestation (~ days 50–70). Previous reports demonstrated that the embryonic loss rate was significant lower in Meishan than in commercial breeds (including Duroc). Most studies have focused on embryonic mortality in early gestation, but little is known about embryonic loss during mid-gestation. Results In this study, protein expression patterns in endometrial tissue from Meishan and Duroc sows were examined during mid-gestation. A total of 2170 proteins were identified in both breeds. After statistical analysis, 70 and 114 differentially expressed proteins (DEPs) were identified in Meishan and Duroc sows, respectively. Between Meishan and Duroc sows, 114 DEPs were detected at day 49, and 98 DEPs were detected at day 72. Functional enrichment analysis revealed differences in protein expression patterns in the two breeds. Around half of DEPs were more highly expressed in Duroc at day 49 (DUD49), relative to DUD72 and Meishan at day 49 (MSD49). Many DEPs appear to be involved in metabolic process such as arginine metabolism. Our results suggest that the differences in expression affect uterine capacity, endometrial matrix remodeling, and maternal-embryo cross-talk, and may be major factors influencing the differences in embryonic loss between Meishan and Duroc sows during mid-gestation. Conclusions Our data showed differential protein expression pattern in endometrium between Meishan and Duroc sows and provides insight into the development process of endometrium. These findings could help us further uncover the molecular mechanism involved in prolificacy.

scholarly journals Comparative transcriptomic analysis of porcine peripheral blood reveals differentially expressed genes from the cytokine–cytokine receptor interaction pathway related to health status

Genome ◽  
2017 ◽  
Vol 60 (12) ◽  
pp. 1021-1028 ◽  
Author(s):  
M.H. Ye ◽  
H. Bao ◽  
Y. Meng ◽  
L.L. Guan ◽  
P. Stothard ◽  
...  
Keyword(s):  
Health Status ◽  
Differentially Expressed Genes ◽  
Peripheral Blood ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Cytokine Receptor ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Marker Genes

While some research has looked into the host genetic response in pigs challenged with specific viruses or bacteria, few studies have explored the expression changes of transcripts in the peripheral blood of sick pigs that may be infected with multiple pathogens on farms. In this study, the architecture of the peripheral blood transcriptome of 64 Duroc sired commercial pigs, including 18 healthy animals at entry to a growing facility (set as a control) and 23 pairs of samples from healthy and sick pen mates, was generated using RNA-Seq technology. In total, 246 differentially expressed genes were identified to be specific to the sick animals. Functional enrichment analysis for those genes revealed that the over-represented gene ontology terms for the biological processes category were exclusively immune activity related. The cytokine–cytokine receptor interaction pathway was significantly enriched. Nine functional genes from this pathway encoding members (as well as their receptors) of the interleukins, chemokines, tumor necrosis factors, colony stimulating factors, activins, and interferons exhibited significant transcriptional alteration in sick animals. Our results suggest a subset of novel marker genes that may be useful candidate genes in the evaluation and prediction of health status in pigs under commercial production conditions.

scholarly journals Comprehensive analysis of LncRNAs expression profiles in an in vitro model of steatosis treated with Exendin-4

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Khaoula Errafii ◽  
Neyla S. Al-Akl ◽  
Olfa Khalifa ◽  
Abdelilah Arredouani
Keyword(s):  
Hepg2 Cells ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Alcoholic Fatty Liver ◽  
Critical Pathways ◽  
Hepatic Lipid Accumulation

Abstract Background and aims The hallmark of non-alcoholic fatty liver disease (NAFLD) is the excessive hepatic lipid accumulation. Currently, no pharmacotherapy exists for NAFLD. However, the glucagon-like peptide-1 receptor agonists have recently emerged as potential therapeutics. Here, we sought to identify the long non-coding RNAs (LncRNAs) associated with the steatosis improvement induced by the GLP-1R agonist Exendin-4 (Ex-4) in vitro. Methods Steatosis was induced in HepG2 cells with oleic acid. The transcriptomic profiling was performed using total RNA extracted from untreated, steatotic, and Ex-4-treated steatotic cells. We validated a subset of differentially expressed LncRNAs with qRT-PCR and identified the most significantly enriched cellular functions associated with the relevant LncRNAs. Results We confirm that Ex-4 improves steatosis in HepG2 cells. We found 379 and 180 differentially expressed LncRNAs between untreated and steatotic cells and between steatotic and Ex-4-treated steatotic cells, respectively. Interestingly, 22 upregulated LncRNAs in steatotic cells became downregulated with Ex-4 exposure, while 50 downregulated LncRNAs in steatotic cells became upregulated in the presence of Ex-4. Although some LncRNAs, such as MALAT1, H19, and NEAT1, were previously associated with NAFLD, the association of others with steatosis and the positive effect of Ex-4 is being reported for the first time. Functional enrichment analysis identified many critical pathways, including fatty acid and pyruvate metabolism, and insulin, PPAR, Wnt, TGF-β, mTOR, VEGF, NOD-like, and Toll-like receptors signaling pathways. Conclusion Our results suggest that LncRNAs may play essential roles in the mechanisms underlying steatosis improvement in response to GLP-1R agonists and warrant further functional studies.

scholarly journals Fine mapping of goat polledness variant in six Chinese native breeds

2021 ◽  
Author(s):  
Yong Li ◽  
tao chen ◽  
Manman Yang ◽  
hu han ◽  
Dan Jiang ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Genome Wide Association Study ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Specific Element ◽  
A Genome

Background: The genetic mechanism of goat polledness has been studied for decades, but identifying causative variants and functional genes remains challenging. Results: Using a genome-wide association study (GWAS), we identified a significant striking locus for polledness in two different goat breeds. To reduce the linkage disequilibrium among variants for localizing causative variants in the finer region, we sequenced 79 goats from six Chinese native breeds (Jining Gray, Matou, Guizhou black, Yunnan black bone, Chaidamu, and Ujumqin) and identified 483.5 kb CNV (150,334,567-150,818,099) translocated into the previously identified 11.7 kb polled intersex syndrome region, which was consistent with previous research using intersex goat populations. Within the 483.5 kb CNV, a ~322 bp horn-specific element, similar to the superfamily of tRNA-derived families of SINEs, located at the first intron of the ERG gene was identified. The results of the GO enrichment analysis showed that the Horn-SINE element-associated genes were involved in both nervous system and head development. Finally, we used RNA sequencing to investigate gene expression profiles in the horn bud and skin tissues of horned and polled goats. We identified 1077 and 1222 differentially expressed genes between the horn bud and skin tissue in polled and horned goats, respectively. We also identified 367 differentially expressed genes in horn buds between polled and horned animals and found that the two CNV-related genes, ERG and FOXL2 were upregulated in the horn bud of polled goats. Gene functional enrichment analysis demonstrated that the downregulated genes in the horn bud of polled goats were enriched in skeletal system development, whereas the upregulated genes were significantly overexpressed in muscle tissue development.

scholarly journals Comprehensive Analysis of a circRNA-miRNA-mRNA Network to Reveal Potential Inflammation-Related Targets for Gastric Adenocarcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
YunXia Liu ◽  
YeFeng Xu ◽  
Feng Xiao ◽  
JianFeng Zhang ◽  
YiQing Wang ◽  
...  
Keyword(s):  
Regulatory Network ◽  
Gene Networks ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Genetic Alterations ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Ppi Network ◽  
Hub Genes

Gastric cancer (GC) is the most common malignancy of the stomach. This study was aimed at elucidating the regulatory network of circRNA-miRNA-mRNA and identifying the precise inflammation-related targets in GC. The expression profiles of GSE83521, GSE78091, and GSE33651 were obtained from the GEO database. Interactions between miRNAs and circRNAs were investigated by the Circular RNA Interactome, and targets of miRNAs were predicted with miRTarBase. Then, a circRNA/miRNA/mRNA regulatory network was constructed. Also, functional enrichment analysis of selected differentially expressed genes (DEGs) was performed. The inflammation-/GC-related targets were collected in the GeneCards and GenLiP3 database, respectively. And a protein-protein interaction (PPI) network of DE mRNAs was constructed with STRING and Cytoscape to identify hub genes. The genetic alterations, neighboring gene networks, expression levels, and the poor prognosis of hub genes were investigated in cBioPortal, Oncomine, and Human Protein Atlas databases and Kaplan-Meier plotter, respectively. A total of 10 DE miRNAs and 33 DEGs were identified. The regulatory network contained 26 circRNAs, 10 miRNAs, and 1459 mRNAs. Functional enrichment analysis revealed that the selected 33 DEGs were involved in negative regulation of fat cell differentiation, response to wounding, extracellular matrix- (ECM-) receptor interaction, and regulation of cell growth pathways. THBS1, FN1, CALM1, COL4A1, CTGF, and IGFBP5 were selected as inflammation-related hub genes of GC in the PPI network. The genetic alterations in these hub genes were related to amplification and missense mutations. Furthermore, the genes RYR2, ERBB2, PI3KCA, and HELZ2 were connected to hub genes in this study. The hub gene levels in clinical specimens were markedly upregulated in GC tissues and correlated with poor overall survival (OS). Our results suggest that THBS1, FN1, CALM1, COL4A1, CTGF, and IGFBP5 were associated with the pathogenesis of gastric carcinogenesis and may serve as biomarkers and inflammation-related targets for GC.

scholarly journals Identification of Common Oncogenic Genes and Pathways Both in Osteosarcoma and Ewing’s Sarcoma Using Bioinformatics Analysis

2021 ◽  
Author(s):  
Jingwei Zhang ◽  
Wenjun Liu ◽  
Liang Ding ◽  
Dongdong Cheng ◽  
Haijun Xiao
Keyword(s):  
Ewing’S Sarcoma ◽  
Ewing's Sarcoma ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Hub Genes ◽  
Ppi Networks

Abstract Objective: This study aimed to explore common oncogenic genes and pathways both in osteosarcoma and Ewing’s sarcoma. Methods: Microarray data were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were respectively identified using the limma package, followed by intersection of common DEGs. Then, protein-protein interaction (PPI) networks were constructed and hub genes were identified. Furthermore, functional enrichment analysis was analyzed. The expression of common oncogenic genes was validated in 38 osteosarcoma and 17 Ewing’s sarcoma tissues by RT-qPCR and western blot. Results: 201 genes were differentially expressed. There were 121 nodes and 232 edges in the PPI network. 12 genes were considered as hub genes. Functional enrichment analysis results showed that hub genes FN1, COL1A1 and COL1A2 were all involved in extracellular matrix, protease binding and ECM-receptor interaction, which could be involved in the development of osteosarcoma and Ewing’s sarcoma. Among common oncogenic genes, FN1, COL1A1 and COL1A2 were lowly expressed both in osteosarcoma and Ewing’ s sarcoma tissues at mRNA and protein levels. Conclusion: Our findings revealed that common oncogenic genes such as FN1, COL1A1 and COL1A2 and pathways were both in osteosarcoma and Ewing’ s sarcoma.

scholarly journals Identification of a prognostic long non-coding RNA signature in breast cancer

2020 ◽  
Author(s):  
Gaochen Lan ◽  
Xiaoling Yu ◽  
Yanna Zhao ◽  
Jinjian Lan ◽  
Wan Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cox Regression ◽  
Prognostic Biomarker ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Cox Regression Analysis

Abstract Background: Breast cancer is the most common malignant disease among women. At present, more and more attention has been paid to long non-coding RNAs (lncRNAs) in the field of breast cancer research. We aimed to investigate the expression profiles of lncRNAs and construct a prognostic lncRNA for predicting the overall survival (OS) of breast cancer. Methods: The expression profiles of lncRNAs and clinical data with breast cancer were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were screened out by R package (limma). The survival probability was estimated by the Kaplan‑Meier Test. The Cox Regression Model was performed for univariate and multivariate analysis. The risk score (RS) was established on the basis of the lncRNAs’ expression level (exp) multiplied regression coefficient (β) from the multivariate cox regression analysis with the following formula: RS=exp a1 * β a1 + exp a2 * β a2 +……+ exp an * β an . Functional enrichment analysis was performed by Metascape. Results: A total of 3404 differentially expressed lncRNAs were identified. Among them, CYTOR , MIR4458HG and MAPT-AS1 were significantly associated with the survival of breast cancer. Finally, The RS could predict OS of breast cancer (RS=exp CYTOR * β CYTOR + exp MIR4458HG * β MIR4458HG + exp MAPT-AS1 * β MAPT-AS1 ). Moreover, it was confirmed that the three-lncRNA signature could be an independent prognostic biomarker for breast cancer (HR=3.040, P=0.000). Conclusions: This study established a three-lncRNA signature, which might be a novel prognostic biomarker for breast cancer.

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