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 Transcriptome Analysis of Differentially Expressed mRNA Related to Pigeon Muscle Development

Animals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 2311
Author(s):  
Hao Ding ◽  
Yueyue Lin ◽  
Tao Zhang ◽  
Lan Chen ◽  
Genxi Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Skeletal Muscle ◽  
Differentially Expressed Genes ◽  
Growth And Development ◽  
Muscle Development ◽  
Expression Patterns ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Growth Stages ◽  
Gene Expression And Regulation

The mechanisms behind the gene expression and regulation that modulate the development and growth of pigeon skeletal muscle remain largely unknown. In this study, we performed gene expression analysis on skeletal muscle samples at different developmental and growth stages using RNA sequencing (RNA−Seq). The differentially expressed genes (DEGs) were identified using edgeR software. Weighted gene co−expression network analysis (WGCNA) was used to identify the gene modules related to the growth and development of pigeon skeletal muscle based on DEGs. A total of 11,311 DEGs were identified. WGCNA aggregated 11,311 DEGs into 12 modules. Black and brown modules were significantly correlated with the 1st and 10th day of skeletal muscle growth, while turquoise and cyan modules were significantly correlated with the 8th and 13th days of skeletal muscle embryonic development. Four mRNA−mRNA regulatory networks corresponding to the four significant modules were constructed and visualised using Cytoscape software. Twenty candidate mRNAs were identified based on their connectivity degrees in the networks, including Abca8b, TCONS−00004461, VWF, OGDH, TGIF1, DKK3, Gfpt1 and RFC5, etc. A KEGG pathway enrichment analysis showed that many pathways were related to the growth and development of pigeon skeletal muscle, including PI3K/AKT/mTOR, AMPK, FAK, and thyroid hormone pathways. Five differentially expressed genes (LAST2, MYPN, DKK3, B4GALT6 and OGDH) in the network were selected, and their expression patterns were quantified by qRT−PCR. The results were consistent with our sequencing results. These findings could enhance our understanding of the gene expression and regulation in the development and growth of pigeon muscle.

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 Screening and Identification of Muscle-Specific Candidate Genes via Mouse Microarray Data Analysis

2021 ◽  
Vol 8 ◽  
Author(s):  
Sayed Haidar Abbas Raza ◽  
Chengcheng Liang ◽  
Wang Guohua ◽  
Sameer D. Pant ◽  
Zuhair M. Mohammedsaleh ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Differentially Expressed Genes ◽  
Muscle Tissue ◽  
Microarray Data ◽  
Muscle Development ◽  
The Other ◽  
Differentially Expressed ◽  
Regulatory Mechanisms ◽  
Potential Candidate ◽  
Differential Genes

Muscle tissue is involved with every stage of life activities and has roles in biological processes. For example, the blood circulation system needs the heart muscle to transport blood to all parts, and the movement cannot be separated from the participation of skeletal muscle. However, the process of muscle development and the regulatory mechanisms of muscle development are not clear at present. In this study, we used bioinformatics techniques to identify differentially expressed genes specifically expressed in multiple muscle tissues of mice as potential candidate genes for studying the regulatory mechanisms of muscle development. Mouse tissue microarray data from 18 tissue samples was selected from the GEO database for analysis. Muscle tissue as the treatment group, and the other 17 tissues as the control group. Genes expressed in the muscle tissue were different to those in the other 17 tissues and identified 272 differential genes with highly specific expression in muscle tissue, including 260 up-regulated genes and 12 down regulated genes. is the genes were associated with the myofibril, contractile fibers, and sarcomere, cytoskeletal protein binding, and actin binding. KEGG pathway analysis showed that the differentially expressed genes in muscle tissue were mainly concentrated in pathways for AMPK signaling, cGMP PKG signaling calcium signaling, glycolysis, and, arginine and proline metabolism. A PPI protein interaction network was constructed for the selected differential genes, and the MCODE module used for modular analysis. Five modules with Score > 3.0 are selected. Then the Cytoscape software was used to analyze the tissue specificity of differential genes, and the genes with high degree scores collected, and some common genes selected for quantitative PCR verification. The conclusion is that we have screened the differentially expressed gene set specific to mouse muscle to provide potential candidate genes for the study of the important mechanisms of muscle development.

scholarly journals Screening and identification of muscle-specific candidate genes via mouse microarray data analysis

2021 ◽  
Author(s):  
Sayed Haidar Abbas Raza ◽  
Chengcheng Liang ◽  
Wang Guohua ◽  
Linsen Zan
Keyword(s):  
Candidate Genes ◽  
Differentially Expressed Genes ◽  
Muscle Tissue ◽  
Microarray Data ◽  
Muscle Development ◽  
The Other ◽  
Differentially Expressed ◽  
Regulatory Mechanisms ◽  
Potential Candidate ◽  
Differential Genes

Muscle tissue is involved with every stage of life activities and has roles in biological processes. For example, the blood circulation system needs the heart muscle to transport blood to all parts, and the movement cannot be separated from the participation of skeletal muscle. However, the process of muscle development and the regulatory mechanisms of muscle development are not clear at present. In this study, we used bioinformatics techniques to identify differentially expressed genes specifically expressed in multiple muscle tissues of mice as potential candidate genes for studying the regulatory mechanisms of muscle development. Mouse tissue microarray data from 17 tissue samples was selected from the GEO database for analysis. Muscle tissue as the treatment group, and the other 16 tissues as the control group. Genes expressed in the muscle tissue were different to those in the other 16 tissues and identified 272 differential genes with highly specific expression in muscle tissue, including 260 up-regulated genes and 12 down regulated genes. is the genes were associated with the myofibril, contractile fibers, and sarcomere, cytoskeletal protein binding, and actin binding. KEGG pathway analysis showed that the differentially expressed genes in muscle tissue were mainly concentrated in pathways for AMPK signaling, cGMP PKG signaling calcium signaling, glycolysis, and, arginine and proline metabolism. A PPI protein interaction network was constructed for the selected differential genes, and the MCODE module used for modular analysis. Five modules with Score > 3.0 are selected. Then the Cytoscape software was used to analyze the tissue specificity of differential genes, and the genes with high degree scores collected, and some common genes selected for quantitative PCR verification. The conclusion is that we have screened the differentially expressed gene set specific to mouse muscle to provide potential candidate genes for the study of the important mechanisms of muscle development.

scholarly journals A Review of Candidate Genes and Pathways in Preeclampsia–An Integrated Bioinformatical Analysis

Biology ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 62
Author(s):  
Muhammad Aliff Mohamad ◽  
Nur Fariha Mohd Manzor ◽  
Noor Fadzilah Zulkifli ◽  
Nurzaireena Zainal ◽  
Abd Rahman Hayati ◽  
...  
Keyword(s):  
Gene Expression ◽  
Candidate Genes ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
High Throughput Sequencing ◽  
Differentially Expressed ◽  
Cochrane Library ◽  
Fetal Mortality ◽  
Original Research ◽  
Mesh Terms

Preeclampsia is a pregnancy-specific disorder characterized by the presence of hypertension with the onset of either proteinuria, maternal organ or uteroplacental dysfunction. Preeclampsia is one of the leading causes of maternal and fetal mortality and morbidity worldwide. However, the etiopathologies of preeclampsia are not fully understood. Many studies have indicated that genes are differentially expressed between normal and in the disease state. Hence, this study systematically searched the literature on human gene expression that was differentially expressed in preeclampsia. An electronic search was performed through 2019 through PubMed, Scopus, Ovid-Medline, and Gene Expression Omnibus where the following MeSH (Medical Subject Heading) terms were used and they had been specified as the primary focus of the articles: Gene, placenta, preeclampsia, and pregnancy in the title or abstract. We also found additional MeSH terms through Cochrane Library: Transcript, sequencing, and profiling. From 687 studies retrieved from the search, only original publications that had performed high throughput sequencing of human placental tissues that reported on differentially expressed genes in pregnancies with preeclampsia were included. Two reviewers independently scrutinized the titles and abstracts before examining the eligibility of studies that met the inclusion criteria. For each study, study design, sample size, sampling type, and method for gene analysis and gene were identified. The genes listed were further analyzed with the DAVID, STRING and Cytoscape MCODE. Three original research articles involving preeclampsia comprising the datasets in gene expression were included. By combining three studies together, 250 differentially expressed genes were produced at a significance setting of p < 0.05. We identified candidate genes: LEP, NRIP1, SASH1, and ZADHHC8P1. Through GO analysis, we found extracellular matrix organization as the highly significant enriched ontology in a group of upregulated genes and immune process in downregulated genes. Studies on a genetic level have the potential to provide new insights into the regulation and to widen the basis for identification of changes in the mechanism of preeclampsia. Integrated bioinformatics could identify differentially expressed genes which could be candidate genes and potential pathways in preeclampsia that may improve our understanding of the cause and underlying molecular mechanisms that could be used as potential biomarkers for risk stratification and treatment.

scholarly journals AB0005 IDENTIFICATION OF KEY GENES AND PATHWAYS FOR PSORIASIS BASED ON GEO DATABASES BY BIOINFORMATICS ANALYSIS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1037.2-1038
Author(s):  
X. Sun ◽  
S. X. Zhang ◽  
S. Song ◽  
T. Kong ◽  
C. Zheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathways ◽  
Differentially Expressed Genes ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Shanxi Province ◽  
Receptor Interaction ◽  
Term Therapy ◽  
Pathway Enrichment Analysis ◽  
Key Genes

Background:Psoriasis is an immune-mediated, genetic disease manifesting in the skin or joints or both, and also has a strong genetic predisposition and autoimmune pathogenic traits1. The hallmark of psoriasis is sustained inflammation that leads to uncontrolled keratinocyte proliferation and dysfunctional differentiation. And it’s also a chronic relapsing disease, which often necessitates a long-term therapy2.Objectives:To investigate the molecular mechanisms of psoriasis and find the potential gene targets for diagnosis and treating psoriasis.Methods:Total 334 gene expression data of patients with psoriasis research (GSE13355 GSE14905 and GSE30999) were obtained from the Gene Expression Omnibus database. After data preprocessing and screening of differentially expressed genes (DEGs) by R software. Online toll Metascape3 was used to analyze Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs. Interactions of proteins encoded by DEGs were discovered by Protein-protein interaction network (PPI) using STRING online software. Cytoscape software was utilized to visualize PPI and the degree of each DEGs was obtained by analyzing the topological structure of the PPI network.Results:A total of 611 DEGs were found to be differentially expressed in psoriasis. GO analysis revealed that up-regulated DEGs were mostly associated with defense and response to external stimulus while down-regulated DEGs were mostly associated with metabolism and synthesis of lipids. KEGG enrichment analysis suggested they were mainly enriched in IL-17 signaling, Toll-like receptor signaling and PPAR signaling pathways, Cytokine-cytokine receptor interaction and lipid metabolism. In addition, top 9 key genes (CXCL10, OASL, IFIT1, IFIT3, RSAD2, MX1, OAS1, IFI44 and OAS2) were identified through Cytoscape.Conclusion:DEGs of psoriasis may play an essential role in disease development and may be potential pathogeneses of psoriasis.References:[1]Boehncke WH, Schon MP. Psoriasis. Lancet 2015;386(9997):983-94. doi: 10.1016/S0140-6736(14)61909-7 [published Online First: 2015/05/31].[2]Zhang YJ, Sun YZ, Gao XH, et al. Integrated bioinformatic analysis of differentially expressed genes and signaling pathways in plaque psoriasis. Mol Med Rep 2019;20(1):225-35. doi: 10.3892/mmr.2019.10241 [published Online First: 2019/05/23].[3]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].Acknowledgements:This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared

scholarly journals PSVII-2 Differentially expressed genes and their biological function in skeletal muscle of calves born from cows with or without protein supplementation during mid-gestation

2020 ◽  
Vol 98 (Supplement_3) ◽  
pp. 165-166
Author(s):  
Elisa B Carvalho ◽  
Letícia P Sanglard ◽  
Karolina B Nascimento ◽  
Javier M Meneses ◽  
Daniel R Casagrande ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Differentially Expressed Genes ◽  
Muscle Development ◽  
Negative Binomial ◽  
Muscle Protein ◽  
Basal Diet ◽  
Protein Supplementation ◽  
Differentially Expressed ◽  
Control Group ◽  
Q Value

Abstract Gestating cows have an increased nutrient demand to meet the needs of developing the fetus and the mid-gestation is a critical period for the fetal skeletal muscle development. The aim of this study was to evaluate the skeletal muscle transcriptome in the progeny as a function of the maternal protein nutrition during mid-gestation. Eleven Tabapuã cows and their male calves were used in this study. In the first third of gestation (0 to 100 days of gestation; dg), all cows were kept on pasture. From 100 to 200 dg, the control group (CTRL; 7 animals) received a basal diet achieving 5.5% crude protein (CP), whereas the supplemented group (SUPPL; 4 animals) received a basal diet plus protein supplementation (40% CP). After 200 dg, all animals received the same diet. Weaning was performed at 205 ± 7.5 days of age and animals were kept on pasture until reaching 240 days of age, when they were transferred to a feedlot. Muscle samples were collected at 260 days of age and RNA was extracted for RNA-seq analysis. Gene expression data was analyzed with a negative binomial model to identify (q-value ≤ 0.05) differentially expressed genes (DEG) between treatments. A total of 716 DEG were identified (289 DEG up-regulated and 427 down-regulated in SUPPL group; q-value ≤ 0.05). From the 10 most significant down-regulated DEG in the SUPPL group, two genes associated with apoptotic process were identified: MAPK8IP1 and GRINA, with log2 Fold-Changes (log2FC) of 1.04 and 0.49, respectively. From the 10 most significant up-regulated DEG in the SUPPL group, mTOR was identified, with log2FC=0.31. This is a well-known gene involved in muscle protein synthesis. In conclusion, maternal protein supplementation during mid-gestation affects the expression of genes related to energy metabolism and muscle development, which can lead to long-term impacts on production efficiency.

Insights into the seasonal adaptive mechanisms of Chinese alligators (Alligator sinensis) from transcriptomic analyses

2018 ◽  
Vol 66 (2) ◽  
pp. 93 ◽  
Author(s):  
Hongji Sun ◽  
Xianbo Zuo ◽  
Long Sun ◽  
Peng Yan ◽  
Fang Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Skeletal Muscle ◽  
Molecular Mechanisms ◽  
Differentially Expressed ◽  
Model Organisms ◽  
Seasonal Adaptation ◽  
Cold Temperatures ◽  
Chinese Alligator ◽  
Adaptive Mechanisms ◽  
Alligator Sinensis

The Chinese alligator (Alligator sinensis) is an endemic and rare species in China, and is considered to be one of the most endangered vertebrates in the world. It is known to hibernate, an energy-saving strategy against cold temperatures and food deprivation. Changes in gene expression during hibernation remain largely unknown. To understand these complex seasonal adaptive mechanisms, we performed a comprehensive survey of differential gene expression in heart, skeletal muscle, and kidney of hibernating and active Chinese alligators using RNA-Sequencing. In total, we identified 4780 genes differentially expressed between the active and hibernating periods. GO and KEGG pathway analysis indicated the likely role of these differentially expressed genes (DEGs). The upregulated DEGs in the active Chinese alligator, CSRP3, MYG and PCKGC, may maintain heart and skeletal muscle contraction, transport and storage of oxygen, and enhance the body’s metabolism, respectively. The upregulated DEGs in the dormant Chinese alligator, ADIPO, CIRBP and TMM27, may improve insulin sensitivity and glucose/lipid metabolism, protect cells against harmful effects of cold temperature and hypoxia, regulate amino acid transport and uptake, and stimulate the proliferation of islet cells and the secretion of insulin. These results provide a foundation for understanding the molecular mechanisms of the seasonal adaptation required for hibernation in Chinese alligators, as well as effective information for other non-model organisms research.

scholarly journals Differentially expressed genes in preimplantation human embryos: potential candidate genes for blastocyst formation and implantation

2016 ◽  
Vol 33 (8) ◽  
pp. 1017-1025 ◽  
Author(s):  
Erika M. Munch ◽  
Amy E. Sparks ◽  
Jesus Gonzalez Bosquet ◽  
Lane K. Christenson ◽  
Eric J. Devor ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Differentially Expressed Genes ◽  
Differentially Expressed ◽  
Human Embryos ◽  
Potential Candidate ◽  
Blastocyst Formation

scholarly journals Insight into Molecular Profile Changes after Skeletal Muscle Contusion Using Microarray and Bioinformatics Analyses

2020 ◽  
Author(s):  
Na Li ◽  
Ru-feng Bai ◽  
Chun Li ◽  
Li-hong Dang ◽  
Qiu-xiang Du ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Healing Process ◽  
Differentially Expressed ◽  
Molecular Profile ◽  
Wound Age ◽  
Functional Modules

Abstract Background: Muscle trauma frequently occurs in daily life. However, the molecular mechanisms of muscle healing, which partly depend on the extent of the damage, are not well understood. This study aimed to investigate gene expression profiles following mild and severe muscle contusion, and to provide more information about the molecular mechanisms underlying the repair process.Methods: A total of 33 rats were divided randomly into control (n = 3), mild contusion (n = 15), and severe contusion (n = 15) groups; the contusion groups were further divided into five subgroups (1, 3, 24, 48, and 168 h post-injury; n = 3 per subgroup). Then full genome microarray of RNA isolated from muscle tissue was performed to access the gene expression changes during healing process.Results: A total of 2,844 and 2,298 differentially expressed genes were identified in the mild and severe contusion groups, respectively. The analysis of the overlapping differentially expressed genes showed that there are common mechanisms of transcriptomic repair of mild and severe contusion within 48 h post-contusion. This was supported by the results of principal component analysis, hierarchical clustering, and weighted gene co‐expression network analysis of the 1,620 coexpressed genes in mildly and severely contused muscle. From these analyses, we discovered that the gene profiles in functional modules and temporal clusters were similar between the mild and severe contusion groups; moreover, the genes showed time-dependent patterns of expression, which allowed us to identify useful markers of wound age. We then performed an analysis of the functions of genes (including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway annotation, and protein–protein interaction network analysis) in the functional modules and temporal clusters, and the hub genes in each module–cluster pair were identified. Interestingly, we found that genes downregulated within 24−48 h of the healing process were largely associated with metabolic processes, especially oxidative phosphorylation of reduced nicotinamide adenine dinucleotide phosphate, which has been rarely reported. Conclusions: These results improve our understanding of the molecular mechanisms underlying muscle repair, and provide a basis for further studies of wound age estimation.

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