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 Analysis of Differentially Expressed Genes and Signaling Pathways Related to Intramuscular Fat Deposition in Skeletal Muscle of Sex-Linked Dwarf Chickens

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Yaqiong Ye ◽  
Shumao Lin ◽  
Heping Mu ◽  
Xiaohong Tang ◽  
Yangdan Ou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Skeletal Muscle ◽  
Signaling Pathways ◽  
Candidate Genes ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Muscle Development ◽  
Intramuscular Fat ◽  
Differentially Expressed ◽  
Potential Candidate

Intramuscular fat (IMF) plays an important role in meat quality. However, the molecular mechanisms underlying IMF deposition in skeletal muscle have not been addressed for the sex-linked dwarf (SLD) chicken. In this study, potential candidate genes and signaling pathways related to IMF deposition in chicken leg muscle tissue were characterized using gene expression profiling of both 7-week-old SLD and normal chickens. A total of 173 differentially expressed genes (DEGs) were identified between the two breeds. Subsequently, 6 DEGs related to lipid metabolism or muscle development were verified in each breed based on gene ontology (GO) analysis. In addition, KEGG pathway analysis of DEGs indicated that some of them (GHR, SOCS3, and IGF2BP3) participate in adipocytokine and insulin signaling pathways. To investigate the role of the above signaling pathways in IMF deposition, the gene expression of pathway factors and other downstream genes were measured by using qRT-PCR and Western blot analyses. Collectively, the results identified potential candidate genes related to IMF deposition and suggested that IMF deposition in skeletal muscle of SLD chicken is regulated partially by pathways of adipocytokine and insulin and other downstream signaling pathways (TGF-β/SMAD3 and Wnt/catenin-βpathway).

scholarly journals PO-046 Gene expression profiling of peripheral blood mononuclear cells in young male trampoline athletes

2018 ◽  
Vol 1 (3) ◽  
Author(s):  
Li Gao ◽  
Yong Jie Yang ◽  
En Qi Li ◽  
Jia Ning Mao
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Bone Health ◽  
Expression Profiling ◽  
Molecular Mechanisms ◽  
Interaction Network ◽  
Differentially Expressed ◽  
Signal Pathways ◽  
Healthy Controls ◽  
Mineral Density

Objective Evidence indicates that physical activity influence bone health. However, the molecular mechanisms mediating the beneficial adaptations to exercise are not well understood. The purpose of this study was to examine the differentially expressed genes in PBMC between athletes and healthy controls, and to analyze the important functional genes and signal pathways that cause increased bone mineral density in athletes, in order to further reveal the molecular mechanisms of exercise promoting bone health. Methods Five professional trampoline athletes and five age-matched untrained college students participated in this study. Used the human expression Microarray V4.0 expression profiling chip to detect differentially expressed genes in the two groups, and performed KEGG Pathway analysis and application of STRING database to construct protein interaction Network; Real-Time PCR technology was used to verify the expression of some differential genes.  Results Compared with healthy controls, there were significant improvement in lumbar spine bone mineral density, and 236 up-regulated as well as 265 down-regulated in serum samples of athletes. The differentially expressed genes involved 28 signal pathways, such as cell adhesion molecules. Protein interaction network showed that MYC was at the core node position. Real-time PCR results showed that the expression levels of CD40 and ITGα6 genes in the athletes were up-regulated compared with the healthy controls, the detection results were consistent with that of the gene chip. Conclusions The findings highlight that long-term high-intensity trampoline training could induce transcriptional changes in PBMC of the athletes. These data suggest that gene expression fingerprints can serve as a powerful research tool to design novel strategies for monitoring exercise. The findings of the study also provide support for the notion that PBMC could be used as a substitute to study exercise training that affects bone health.

scholarly journals Identification of Hub Genes in Anaplastic Thyroid Carcinoma: Evidence From Bioinformatics Analysis

2020 ◽  
Vol 19 ◽  
pp. 153303382096213
Author(s):  
Liqi Li ◽  
Mingjie Zhu ◽  
Hu Huang ◽  
Junqiang Wu ◽  
Dong Meng
Keyword(s):  
Thyroid Carcinoma ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Quantitative Polymerase Chain Reaction ◽  
Interaction Network ◽  
Anaplastic Thyroid Carcinoma ◽  
Rank Aggregation ◽  
Differentially Expressed ◽  
Hub Genes ◽  
Rare Type

Anaplastic thyroid carcinoma (ATC) is a rare type of thyroid cancer that results in fatal clinical outcomes; the pathogenesis of this life-threatening disease has yet to be fully elucidated. This study aims to identify the hub genes of ATC that may play key roles in ATC development and could serve as prognostic biomarkers or therapeutic targets. Two microarray datasets (GSE33630 and GSE53072) were obtained from the Gene Expression Omnibus database; these sets included 16 ATC and 49 normal thyroid samples. Differential expression analyses were performed for each dataset, and 420 genes were screened as common differentially expressed genes using the robust rank aggregation method. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted to explore the potential bio-functions of these differentially expressed genes (DEGs). The terms and enriched pathways were primarily associated with cell cycle, cell adhesion, and cancer-related signaling pathways. Furthermore, a protein-protein interaction network of DEG expression products was constructed using Cytoscape. Based on the whole network, we identified 7 hub genes that included CDK1, TOP2A, CDC20, KIF11, CCNA2, NUSAP1, and KIF2C. The expression levels of these hub genes were validated using quantitative polymerase chain reaction analyses of clinical specimens. In conclusion, the present study identified several key genes that are involved in ATC development and provides novel insights into the understanding of the molecular mechanisms of ATC development.

scholarly journals Identification and Interaction Analysis of Significant Genes and MicroRNAs in Pterygium

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Siying He ◽  
Hui Sun ◽  
Yifang Huang ◽  
Shiqi Dong ◽  
Chen Qiao ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Interaction Analysis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Differentially Expressed Mirnas

Purpose. MiRNAs have been widely analyzed in the occurrence and development of many diseases, including pterygium. This study aimed to identify the key genes and miRNAs in pterygium and to explore the underlying molecular mechanisms. Methods. MiRNA expression was initially extracted and pooled by published literature. Microarray data about differentially expressed genes was downloaded from Gene Expression Omnibus (GEO) database and analyzed with the R programming language. Functional and pathway enrichment analyses were performed using the database for Annotation, Visualization and Integrated Discovery (DAVID). The protein-protein interaction network was constructed with the STRING database. The associations between chemicals, differentially expressed miRNAs, and differentially expressed genes were predicted using the online resource. All the networks were constructed using Cytoscape. Results. We found that 35 miRNAs and 301 genes were significantly differentially expressed. Functional enrichment analysis showed that upregulated genes were significantly enriched in extracellular matrix (ECM) organization, while downregulated genes were mainly involved in cell death and apoptotic process. Finally, we concluded the chemical-gene affected network, miRNA-mRNA interacted networks, and significant pathway network. Conclusion. We identified lists of differentially expressed miRNAs and genes and their possible interaction in pterygium. The networks indicated that ECM breakdown and EMT might be two major pathophysiological mechanisms and showed the potential significance of PI3K-Akt signalling pathway. MiR-29b-3p and collagen family (COL4A1 and COL3A1) might be new treatment target in pterygium.

scholarly journals Transcriptional Insights into Key Genes and Pathways Underlying Muscovy Duck Subcutaneous Fat Deposition at Different Developmental Stages

Animals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 2099
Author(s):  
Liping Guo ◽  
Congcong Wei ◽  
Li Yi ◽  
Wanli Yang ◽  
Zhaoyu Geng ◽  
...  
Keyword(s):  
Fatty Acid ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Fatty Acid Biosynthesis ◽  
Developmental Stages ◽  
Subcutaneous Fat ◽  
Fat Deposition ◽  
Differentially Expressed ◽  
Muscovy Duck ◽  
Key Genes

Subcutaneous fat is a crucial trait for waterfowl, largely associated with meat quality and feed conversion rate. In this study, RNA-seq was used to identify differentially expressed genes of subcutaneous adipose tissue among three developmental stages (12, 35, and 66 weeks) in Muscovy duck. A total of 138 and 129 differentially expressed genes (DEGs) were identified between 35 and 12 weeks (wk), and 66 and 35 wk, respectively. Compared with 12 wk, subcutaneous fat tissue at 35 wk upregulated several genes related to cholesterol biosynthesis and fatty acid biosynthesis, including HSD17B7 and MSMO1, while it downregulated fatty acid beta-oxidation related genes, including ACOX1 and ACSL1. Notably, most of the DEGs (92.2%) were downregulated in 66 wk compared with 35 wk, consistent with the slower metabolism of aging duck. Protein network interaction and function analyses revealed GC, AHSG, FGG, and FGA were the key genes for duck subcutaneous fat from adult to old age. Additionally, the PPAR signaling pathway, commonly enriched between the two comparisons, might be the key pathway contributing to subcutaneous fat metabolism among differential developmental stages in Muscovy duck. These results provide several candidate genes and pathways potentially involved in duck subcutaneous fat deposition, expanding our understanding of the molecular mechanisms underlying subcutaneous fat deposition during development.

scholarly journals Identification of Differentially Expressed Genes in COVID-19 and Integrated Bioinformatics Analysis of Signaling Pathways

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Linjie Fang ◽  
Tingyu Tang ◽  
Mengqi Hu
Keyword(s):  
Signaling Pathway ◽  
Differentially Expressed Genes ◽  
Cellular Response ◽  
Molecular Mechanisms ◽  
Interaction Network ◽  
Differentially Expressed ◽  
Type I ◽  
Hub Genes ◽  
Gene Set ◽  
Go Terms

Coronavirus disease 2019 (COVID-19) is acutely infectious pneumonia. Currently, the specific causes and treatment targets of COVID-19 are still unclear. Herein, comprehensive bioinformatics methods were employed to analyze the hub genes in COVID-19 and tried to reveal its potential mechanisms. First of all, 34 groups of COVID-19 lung tissues and 17 other diseases’ lung tissues were selected from the GSE151764 gene expression profile for research. According to the analysis of the DEGs (differentially expressed genes) in the samples using the limma software package, 84 upregulated DEGs and 46 downregulated DEGs were obtained. Later, by the Database for Annotation, Visualization, and Integrated Discovery (DAVID), they were enriched in the Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. It was found that the upregulated DEGs were enriched in the type I interferon signaling pathway, AGE-RAGE signaling pathway in diabetic complications, coronavirus disease, etc. Downregulated DEGs were in cellular response to cytokine stimulus, IL-17 signaling pathway, FoxO signaling pathway, etc. Then, based on GSEA, the enrichment of the gene set in the sample was analyzed in the GO terms, and the gene set was enriched in the positive regulation of myeloid leukocyte cytokine production involved in immune response, programmed necrotic cell death, translesion synthesis, necroptotic process, and condensed nuclear chromosome. Finally, with the help of STRING tools, the PPI (protein-protein interaction) network diagrams of DEGs were constructed. With degree ≥13 as the cutoff degree, 3 upregulated hub genes (ISG15, FN1, and HLA-G) and 4 downregulated hub genes (FOXP3, CXCR4, MMP9, and CD69) were screened out for high degree. All these findings will help us to understand the potential molecular mechanisms of COVID-19, which is also of great significance for its diagnosis and prevention.

scholarly journals Analysis of Differentially Expressed Genes in Coronary Artery Disease by Integrated Microarray Analysis

Biomolecules ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 35 ◽  
Author(s):  
Meenashi Vanathi Balashanmugam ◽  
Thippeswamy Boreddy Shivanandappa ◽  
Sivagurunathan Nagarethinam ◽  
Basavaraj Vastrad ◽  
Chanabasayya Vastrad
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Molecular Mechanism ◽  
Differentially Expressed Genes ◽  
Regulatory Network ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Interaction Network ◽  
Differentially Expressed ◽  
Artery Disease

Coronary artery disease (CAD) is a major cause of end-stage cardiac disease. Although profound efforts have been made to illuminate the pathogenesis, the molecular mechanisms of CAD remain to be analyzed. To identify the candidate genes in the advancement of CAD, microarray dataset GSE23766 was downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified, and pathway and gene ontology (GO) enrichment analyses were performed. The protein-protein interaction network was constructed and the module analysis was performed using the Biological General Repository for Interaction Datasets (BioGRID) and Cytoscape. Additionally, target genes-miRNA regulatory network and target genes-TF regulatory network were constructed and analyzed. There were 894 DEGs between male human CAD samples and female human CAD samples, including 456 up regulated genes and 438 down regulated genes. Pathway enrichment analyses revealed that DEGs (up and down regulated) were mostly enriched in the superpathway of steroid hormone biosynthesis, ABC transporters, oxidative ethanol degradation III and Complement and coagulation cascades. Similarly, geneontology enrichment analyses revealed that DEGs (up and down regulated) were mostly enriched in the forebrain neuron differentiation, filopodium membrane, platelet degranulation and blood microparticle. In the PPI network and modules (up and down regulated), MYC, NPM1, TRPC7, UBC, FN1, HEMK1, IFT74 and VHL were hub genes. In the target genes-miRNA regulatory network and target genes—TF regulatory network (up and down regulated), TAOK1, KHSRP, HSD17B11 and PAH were target genes. In conclusion, the pathway and GO ontology enriched by DEGs may reveal the molecular mechanism of CAD. Its hub and target genes, MYC, NPM1, TRPC7, UBC, FN1, HEMK1, IFT74, VHL, TAOK1, KHSRP, HSD17B11 and PAH were expected to be new targets for CAD. Our finding provided clues for exploring molecular mechanism and developing new prognostics, diagnostic and therapeutic strategies for CAD.

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 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.

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