scholarly journals Transcriptomic Analyses of the Hypothalamic-Pituitary-Gonadal Axis Identify Candidate Genes Related to Egg Production in Xinjiang Yili Geese

Animals ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 90
Author(s):  
Yingping Wu ◽  
Xiaoyu Zhao ◽  
Li Chen ◽  
Junhua Wang ◽  
Yuqing Duan ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Differentially Expressed Genes ◽  
Egg Production ◽  
Molecular Mechanisms ◽  
Egg Laying ◽  
Differentially Expressed ◽  
Cdna Libraries ◽  
Receptor Interaction ◽  
Sequencing Data ◽  
Pituitary Glands

The study was conducted to investigate the transcriptomic differences of the hypothalamic-pituitary-gonadal axis between Xinjiang Yili geese with high and low egg production and to find candidate genes regulating the egg production of Xinjiang Yili geese. The 8 selected Xinjiang Yili Geese with high or low egg production (4 for each group) were 3 years old, with good health, and under the same feeding condition. High-throughput sequencing technology was used to sequence cDNA libraries of the hypothalami, pituitary glands, and ovaries. The sequencing data were compared and analyzed, and the transcripts with significant differences were identified and analyzed with bioinformatics. The study showed that the transcriptome sequencing data of the 24 samples contained a total of 1,176,496,146 valid reads and 176.47 gigabase data. Differential expression analyses identified 135, 56, and 331 genes in the hypothalami, pituitary glands, and ovaries of Xinjiang Yili geese with high and low egg production. Further annotation of these differentially expressed genes in the non-redundant protein sequence database (Nr) revealed that 98, 52, and 309 genes were annotated, respectively. Through the annotations of GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) databases, 30 candidate genes related to the egg production of Xinjiang Yili geese were preliminarily selected. The gap junction, focal adhesion, and ECM-receptor interaction signaling pathways were enriched with the hypothalamic, pituitary, and ovarian differentially expressed genes, and the calcium signaling pathway was enriched with the pituitary and ovarian differentially expressed genes. Thus, these pathways in the hypothalamic-pituitary-gonadal axis may play an important role in regulating egg production of Xinjiang Yili geese. The results provided the transcriptomic information of the hypothalamic-pituitary-gonadal axis of Xinjiang Yili geese and laid the theoretical basis for revealing the molecular mechanisms regulating the egg-laying traits of Xinjiang Yili geese.

scholarly journals Identification of Differentially Expressed Genes in Porcine Ovaries at Proestrus and Estrus Stages Using RNA-Seq Technique

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Songbai Yang ◽  
Xiaolong Zhou ◽  
Yue Pei ◽  
Han Wang ◽  
Ke He ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Hormone Secretion ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
The Novel ◽  
Kegg Pathways ◽  
Go Enrichment ◽  
Single Organism

Estrus is an important factor for the fecundity of sows, and it is involved in ovulation and hormone secretion in ovaries. To better understand the molecular mechanisms of porcine estrus, the expression patterns of ovarian mRNA at proestrus and estrus stages were analyzed using RNA sequencing technology. A total of 2,167 differentially expressed genes (DEGs) were identified (P≤0.05, log2  Ratio≥1), of which 784 were upregulated and 1,383 were downregulated in the estrus compared with the proestrus group. Gene Ontology (GO) enrichment indicated that these DEGs were mainly involved in the cellular process, single-organism process, cell and cell part, and binding and metabolic process. In addition, a pathway analysis showed that these DEGs were significantly enriched in 33 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, including cell adhesion molecules, ECM-receptor interaction, and cytokine-cytokine receptor interaction. Quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) confirmed the differential expression of 10 selected DEGs. Many of the novel candidate genes identified in this study will be valuable for understanding the molecular mechanisms of the sow estrous cycle.

scholarly journals RNA-Seq Reveals Differentially Expressed Genes and Pathways Affecting Intramuscular Fat Metabolism in Huangshan Black Chicken Population

2020 ◽  
Vol 12 (3) ◽  
pp. 117
Author(s):  
S. H. Yang ◽  
C. S. He ◽  
C. H. Li ◽  
G. Q. Liu
Keyword(s):  
Fatty Acid ◽  
Candidate Genes ◽  
Meat Quality ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Interaction Network ◽  
Intramuscular Fat ◽  
Metabolic Process ◽  
Differentially Expressed ◽  
Thigh Muscle

Intramuscular fat (IMF) plays an important role in meat quality due to its positive correlation with juiciness, tenderness, and flavor. However, for chickens, the molecular mechanisms underlying IMF deposition in thigh muscle have not yet been determined. Here, to identify candidate genes and signaling pathways related to IMF deposition, we deeply explored the chicken transcriptome from thigh muscles of Huangshan Black Chickens with extremely high and low phenotypic values for intramuscular fat content. A total of 128 genes differentially expressed genes (DEGs) were detected, of which 94 were up-regulated and 34 were down-regulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways revealed these DEGs (including FABP4, G0S2, PLIN1, SCD1, LFABP, SLC1A6, SLC45A3, ACSBG1, LY86, ST8SIA5, SNAI2, HPGD, EDN2, and THRSP) were significantly enriched in lipid biosynthetic process, steroid biosynthetic and metabolic process, fatty acid metabolic process, and regulation of unsaturated fatty acid metabolic pathways. Additionally, we concluded an interaction network related to lipid metabolism, which might be contributed to the IMF deposition in chicken. Overall, we proposed some new candidate genes and interaction networks that can be associated with IMF deposition and used as biomarkers in meat quality improvement.

scholarly journals Comparative adipose transcriptome analysis digs out genes related to fat deposition in two pig breeds

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Kai Xing ◽  
Kejun Wang ◽  
Hong Ao ◽  
Shaokang Chen ◽  
Zhen Tan ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Signaling Pathway ◽  
Meat Quality ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Mapk Signaling ◽  
Fat Deposition ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Pig Breeds

Abstract Fatness traits are important in pigs because of their implications for fattening efficiency, meat quality, reproductive performance and immunity. Songliao black pigs and Landrace pigs show important differences in production and meat quality traits, including fatness and muscle growth. Therefore, we used a high-throughput massively parallel RNA-seq approach to identify genes differentially expressed in backfat tissue between these two breeds (six pigs in each). An average of 37.87 million reads were obtained from the 12 samples. After statistical analysis of gene expression data by edgeR, a total of 877 differentially expressed genes were detected between the two pig breeds, 205 with higher expression and 672 with lower expression in Songliao pigs. Candidate genes (LCN2, CES3, DGKB, OLR1, LEP, PGM1, PCK1, ACACB, FADS1, FADS2, MOGAT2, SREBF1, PPARGC1B) with known effects on fatness traits were included among the DEGs. A total of 1071 lncRNAs were identified, and 85 of these lncRNAs were differentially expressed, including 53 up-regulated and 32 down-regulated lncRNAs, respectively. The differentially expressed genes and lncRNAs involved in glucagon signaling pathway, glycolysis/gluconeogenesis, insulin signaling pathway, MAPK signaling pathway and so on. Integrated analysis potential trans-regulating or cis-regulating relation between DEGs and DE lncRNAs, suggested lncRNA MSTRG.2479.1 might regulate the expressed level of VLDLR affecting porcine fat metabolism. These results provide a number of candidate genes and lncRNAs potentially involved in porcine fat deposition and provide a basis for future research on the molecular mechanisms underlying in fat deposition.

scholarly journals Integrated transcriptomic and proteomic study on the different molecular mechanisms of PC12 cell growth on chitosan and collagen/chitosan films

2020 ◽  
Vol 7 (6) ◽  
pp. 553-565
Author(s):  
Xiaoying Lü ◽  
Yan Huang ◽  
Yayun Qu ◽  
Yiwen Zhang ◽  
Zequn Zhang
Keyword(s):  
Cell Adhesion ◽  
Cell Growth ◽  
Cell Viability ◽  
Pc12 Cells ◽  
Differentially Expressed Genes ◽  
Pc12 Cell ◽  
Molecular Mechanisms ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Chitosan Films

Abstract The purpose of this article is to integrate the transcriptomic analysis and the proteomic profiles and to reveal and compare the different molecular mechanisms of PC12 cell growth on the surface of chitosan films and collagen/chitosan films. First, the chitosan films and the collagen/chitosan films were prepared. Subsequently, the cell viability assay was performed; the cell viability of the PC12 cells cultured on the collagen/chitosan films for 24 h was significantly higher than that on the chitosan films. Then, with cDNA microarray, the numbers of differentially expressed genes of PC12 cells on the surface of chitosan and collagen/chitosan films were 13349 and 5165, respectively. Next, the biological pathway analysis indicated that the differentially expressed genes were involved in 40 pathways directly related to cell adhesion and growth. The integrated transcriptomic and our previous proteomic analysis revealed that three biological pathways—extracellular matrix–receptor interaction, focal adhesion and regulation of actin cytoskeleton—were regulated in the processes of protein adsorption, cell adhesion and growth. The adsorbed proteins on the material surfaces further influenced the expression of important downstream genes by regulating the expression of related receptor genes in these three pathways. In comparison, chitosan films had a strong inhibitory effect on PC12 cell adhesion and growth, resulting in the significantly lower cell viability on its surface; on the contrary, collagen/chitosan films were more conducive to promoting PC12 cell adhesion and growth, resulting in higher cell viability.

scholarly journals Transcriptome analysis reveals modulation of the STAT family in PEDV-infected IPEC-J2 cells

BMC Genomics ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhengzheng Hu ◽  
Yuchen Li ◽  
Heng Du ◽  
Junxiao Ren ◽  
Xianrui Zheng ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Differentially Expressed Genes ◽  
Influenza A ◽  
Molecular Mechanisms ◽  
Host Cells ◽  
Differentially Expressed ◽  
Economic Losses ◽  
Receptor Interaction ◽  
Epithelial Cell Line ◽  
Diarrhea Virus

Abstract Background Porcine epidemic diarrhea virus (PEDV) is a causative agent of serious viral enteric disease in suckling pigs. Such diseases cause considerable economic losses in the global swine industry. Enhancing our knowledge of PEDV-induced transcriptomic responses in host cells is imperative to understanding the molecular mechanisms involved in the immune response. Here, we analyzed the transcriptomic profile of intestinal porcine epithelial cell line J2 (IPEC-J2) after infection with a classical strain of PEDV to explore the host response. Results In total, 854 genes were significantly differentially expressed after PEDV infection, including 716 upregulated and 138 downregulated genes. Functional annotation analysis revealed that the differentially expressed genes were mainly enriched in the influenza A, TNF signaling, inflammatory response, cytokine receptor interaction, and other immune-related pathways. Next, the putative promoter regions of the 854 differentially expressed genes were examined for the presence of transcription factor binding sites using the MEME tool. As a result, 504 sequences (59.02%) were identified as possessing at least one binding site of signal transducer and activator of transcription (STAT), and five STAT transcription factors were significantly induced by PEDV infection. Furthermore, we revealed the regulatory network induced by STAT members in the process of PEDV infection. Conclusion Our transcriptomic analysis described the host genetic response to PEDV infection in detail in IPEC-J2 cells, and suggested that STAT transcription factors may serve as key regulators in the response to PEDV infection. These results further our understanding of the pathogenesis of PEDV.

PSX-A-28 Late-Breaking: Transcriptomics Analysis of the Sham-chewing Behavior of Confined Sows

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 368-369
Author(s):  
Lei Pan ◽  
Haidong Wei ◽  
Jianxing Wang ◽  
Runxiang Zhang ◽  
Honggui Liu ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Late Gestation ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Sequencing Data ◽  
Large White ◽  
Neuropsychiatric Diseases ◽  
High Incidence

Abstract In order to explore the differentially expressed genes (DEGs) related to the high incidence of sham-chewing behavior in pregnant sows, 50 sows (Large White × Landrace) were used to observe sham-chewing behavior in early, middle and late gestation. And then according to the number of sham-chewing observed, sows were divided into high incidence of sham-chewing (group H) and low incidence of sham-chewing (group L). After weaning, 4 sows were randomly selected from group H and group L, samples of brain were collected after slaughter, and hypothalamus was sequenced with transcriptome. After bioinformatics analysis, the DEGs were analyzed and enriched in GO and KEGG, afterwards the candidate genes were screened. qRT-PCR was used to verify the accuracy of the sequencing data. Hypothalamic transcriptome results showed that compared with group L, 1286 genes were significantly differentially expressed in group H, among which 934 genes were up-regulated and 352 genes were down-regulated. The results of GO enrichment analysis showed that in biological process, cell component and molecular function, the most significant terms of enrichment are trans-synaptic signaling, neuron part and gated channel activity. These terms are strongly related to synaptic plasticity, synaptic transmission, neurodevelopment and neuropsychiatric diseases, FGF12, SNAP25, CAMK1D, SYNDIG1, GABRD, RBFOX1, CRH, HCN1, HCN4, GLRA3, GRIN2A, ANXA2, MBP and NTF4 genes with high fold change and more in-depth functional research were selected for sham-chewing and depressive emotion-related genes. KEGG enrichment analysis results indicated that differential expressed genes were significantly enriched in 29 pathways, such as neuroactive ligand-receptor interaction, cAMP and Ras-MAPK signaling pathway. In conclusion, the results of hypothalamic transcriptome indicate that there is a molecular genetic basis for depression-like symptoms in group H, the 14 DEGs screened above might be candidate genes involved in high incidence of sham-chewing and depression-like emotion.

scholarly journals Changes in Ovary Transcriptome and Alternative splicing at estrus from Xiang pigs with Large and Small Litter Size

2019 ◽  
Author(s):  
Fuping Zhang ◽  
Liangting Tang ◽  
Xueqin Ran ◽  
Ning Mao ◽  
Yiqi Ruan ◽  
...  
Keyword(s):  
Alternative Splicing ◽  
Candidate Genes ◽  
Differentially Expressed Genes ◽  
Litter Size ◽  
Molecular Mechanisms ◽  
Reproductive Traits ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Small Litter ◽  
Small Litter Size

AbstractBackground/AimsLitter size is one of the most important reproductive traits in pig breeding, which is affected by multiple genes and the environment. Ovaries are the most important reproductive organs and have a profound impact on the reproduction efficiency. Therefore, genetic differences in the ovaries may contribute to the observed differences in litter size. Although QTLs and candidate genes have been reported to affect the litter size in many pig breeds, however, the findings cannot elucidate the marked differences of the reproductive traits between breeds. The aim of present work is to elucidate the mechanisms of the differences for the reproductive traits and identify candidate genes associated with litter size in Xiang pig breed.MethodsThe changes in ovary transcriptome and alternative splicing were investigated at estrus between Xiang pigs with large and small litter size by RNA-seq technology. The RNA-seq results were confirmed by RT-qPCR method.ResultsWe detected 16,219 - 16,285 expressed genes and 12 types of alternative splicing (AS) events in Xiang pig samples. A total of 762 differentially expressed genes were identified by XL (Xiang pig group with larger litter size) vs XS (Xiang pig group with small litter size) sample comparisons. A total of 34 genes were upregulated and 728 genes were downregulated in XL ovary samples compared with the XS samples. Alternative splicing (AS) rates in XL samples were slightly lower than that observed in XS samples. Most of differentially expressed genes were differentially regulated on AS level. Eleven candidate genes were potentially identified to be related to Xiang pig fecundity and litter size, which may be closely related to the gonad development, oocyte maturation or embryo quality.ConclusionThe significant changes in the expression of the protein-coding genes and the level of alternative splicing in estrus ovarian transcriptome between XL and XS groups probably are the molecular mechanisms of phenotypic variation in litter size.

scholarly journals Identification of differentially expressed genes and signaling pathways in rheumatoid arthritis by integrated bioinformatics analysis

2020 ◽  
Author(s):  
Yanzhi Ge ◽  
Li Zhou ◽  
Zuxiang Chen ◽  
Yingying Mao ◽  
Ting Li ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Signaling Pathways ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Kegg Pathway ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Effective Prevention ◽  
Ppi Networks

Abstract Background The disability rate associated with rheumatoid arthritis (RA) ranks high among inflammatory joint diseases. However, the cause and potential molecular events are as yet not clear. Here, we aimed to identify key genes and pathways involved in RA utilizing integrated bioinformatics analysis and uncover underlying molecular mechanisms. Materials and methods The expression profiles of GSE55235, GSE55457, GSE55584 and GSE77298 were downloaded from the Gene Expression Omnibus database, which contained 76 synovial membrane samples, including 49 RA samples and 27 controls. The microarray datasets were consolidated and differentially expressed genes (DEGs) were acquired and further analyzed by bioinformatics techniques. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of DEGs were performed using R (version 3.6.1), respectively. The protein-protein interaction (PPI) networks of DEGs were developed utilizing the STRING database. Results A total of 828 DEGs were recognized, with 758 up-regulated and 70 down-regulated. GO and KEGG pathway analyses demonstrated that these DEGs focused primarily on multifactorial binding, transcription activity, cytokin-cytokin receptor interaction and relevant signaling pathways. The 30 most firmly related genes among DEGs were identified from the PPI network. Conclusion This study shows that screening for DEGs and pathways utilizing integrated bioinformatics analyses could aid in the comprehension of the molecular mechanisms involved in RA development. In addition, our study provides valuable data for the effective prevention, diagnosis, treatment and rehabilitation of RA patients as well as providing potential targets for the treatment of RA.

scholarly journals Network Analyses of Differentially Expressed Genes in Osteoarthritis to Identify Hub Genes

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Zhaoyan Li ◽  
Lei Zhong ◽  
Zhenwu Du ◽  
Gaoyang Chen ◽  
Jing Shang ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Hub Genes ◽  
Expression Levels ◽  
Network Analyses ◽  
Synovial Membranes

Background. Osteoarthritis (OA) is the most common degenerative disease in orthopedics. However, the cause and underlying molecular mechanisms are not clear. This study aims to identify the hub genes and pathways involved in the occurrence of osteoarthritis. Methods. The raw data of GSE89408 were downloaded from the Gene Expression Omnibus (GEO) database, and the differentially expressed genes (DEGs) were identified by R software. The DAVID database was used for pathway and gene ontology analysis, and p<0.05 and gene count >2 were set as the cut-off point. Moreover, protein-protein interaction (PPI) network construction was applied for exploring the hub genes in osteoarthritis. The expression levels of the top ten hub genes in knee osteoarthritis synovial membranes and controls were detected by quantitative real-time PCR system. Results. A total of 229 DEGs were identified in osteoarthritis synovial membranes compared with normal synovial membranes, including 145 upregulated and 84 downregulated differentially expressed genes. The KEGG pathway analysis results showed that up-DEGs were enriched in proteoglycans in cytokine-cytokine receptor interaction, chemokine signaling pathway, rheumatoid arthritis, and TNF signaling pathway, whereas down-DEGs were enriched in the PPAR signaling pathway and AMPK signaling pathway. The qRT-PCR results showed that the expression levels of ADIPOQ, IL6, and CXCR1 in the synovium of osteoarthritis were significantly increased (p <0.05).

scholarly journals Identification of Differentially Expressed Genes and Enriched Pathways in SARS-CoV-2/ COVID-19 using Bioinformatics Analysis

2020 ◽  
Author(s):  
Ali Mohamed Alshabi ◽  
Ibrahim Ahmed Shaikh ◽  
Basavaraj Mallikarjunayya Vastrad ◽  
Chanabasayya Mallikarjunayya Vastrad
Keyword(s):  
Differentially Expressed Genes ◽  
Messenger Rna ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Diagnostic Efficiency ◽  
Current Investigation ◽  
Roc Curve Analysis

Abstract BackgroundThe exact molecular mechanisms of the progression of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection remain unclear. The current investigation strived to understand and functionally analyze the differentially expressed genes (DEGs) between SARS-CoV-2 infection and mock samples applying extensive bioinformatics analyses.MethodsGSE148729 dataset was downloaded from the Gene Expression Omnibus (GEO) and investigated utilising the limma package in R software to identify DEGs. Pathway and gene ontology (GO) enrichment analysis of the up and down-regulated genes were performed in ToppGene. The HIPPIE database was applied to estimate the interactions of up and down-regulated genes and to construct a protein-protein interaction (PPI) network using Cytoscape software. Receiver operating characteristic (ROC) was utilized for validation.ResultsA total of 928 DEGs (461 up-regulated genes and 467 down-regulated genes) were identified between SARS-CoV-2 infection and mock samples. The up and down-regulated genes were significantly enriched in cytokine-cytokine receptor interaction, and ascorbate and aldarate metabolism. Several significant GO terms, including the response to biotic stimulus and oxoacid metabolic process, were identified. The top hub genes and target genes included JUN, FBXO6, PCLAF, CFTR, TXNIP, PMAIP1, BRI3BP, FAHD1, PROX1, CXCL11, SERHL2 and CFI. ROC curve analysis showed that messenger RNA levels of these ten genes (DDX58, IFITM2, IRF1, PML, SAMHD1, ACSS1, CYP2U1, DDC, PNMT and UGT2A3) exhibited better diagnostic efficiency between SARS-CoV-2 infection and mock.ConclusionsThe current investigation distinguished vital genes and pathways that may be implicated in the progression of SARS-CoV-2 infection, providing a new understanding of the underlying molecular mechanisms of SARS-CoV-2 infection.

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