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 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 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 Network-based analysis of differentially expressed genes in cerebrospinal fluid (CSF) and blood reveals new candidate genes for multiple sclerosis

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2775 ◽  
Author(s):  
Nahid Safari-Alighiarloo ◽  
Mostafa Rezaei-Tavirani ◽  
Mohammad Taghizadeh ◽  
Seyyed Mohammad Tabatabaei ◽  
Saeed Namaki
Keyword(s):  
Multiple Sclerosis ◽  
Cerebrospinal Fluid ◽  
Candidate Genes ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Biological Pathways ◽  
Differentially Expressed ◽  
Potential Candidate ◽  
Functional Modules ◽  
Ppi Networks

BackgroundThe involvement of multiple genes and missing heritability, which are dominant in complex diseases such as multiple sclerosis (MS), entail using network biology to better elucidate their molecular basis and genetic factors. We therefore aimed to integrate interactome (protein–protein interaction (PPI)) and transcriptomes data to construct and analyze PPI networks for MS disease.MethodsGene expression profiles in paired cerebrospinal fluid (CSF) and peripheral blood mononuclear cells (PBMCs) samples from MS patients, sampled in relapse or remission and controls, were analyzed. Differentially expressed genes which determined only in CSF (MSvs.control) and PBMCs (relapsevs.remission) separately integrated with PPI data to construct the Query-Query PPI (QQPPI) networks. The networks were further analyzed to investigate more central genes, functional modules and complexes involved in MS progression.ResultsThe networks were analyzed and high centrality genes were identified. Exploration of functional modules and complexes showed that the majority of high centrality genes incorporated in biological pathways driving MS pathogenesis. Proteasome and spliceosome were also noticeable in enriched pathways in PBMCs (relapsevs.remission) which were identified by both modularity and clique analyses. Finally, STK4, RB1, CDKN1A, CDK1, RAC1, EZH2, SDCBP genes in CSF (MSvs.control) and CDC37, MAP3K3, MYC genes in PBMCs (relapsevs.remission) were identified as potential candidate genes for MS, which were the more central genes involved in biological pathways.DiscussionThis study showed that network-based analysis could explicate the complex interplay between biological processes underlying MS. Furthermore, an experimental validation of candidate genes can lead to identification of potential therapeutic targets.

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 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.

scholarly journals Identifying Candidate Genes for Hypoxia Adaptation of Tibet Chicken Embryos by Selection Signature Analyses and RNA Sequencing

Genes ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 823
Author(s):  
Xiayi Liu ◽  
Xiaochen Wang ◽  
Jing Liu ◽  
Xiangyu Wang ◽  
Haigang Bao
Keyword(s):  
Candidate Genes ◽  
Rna Sequencing ◽  
Differentially Expressed Genes ◽  
Gallus Gallus ◽  
Differentially Expressed ◽  
Tibet Plateau ◽  
Embryonic Liver ◽  
Selection Signature ◽  
Chicken Embryos ◽  
Hypoxia Adaptation

The Tibet chicken (Gallus gallus) lives on the Qinghai–Tibet Plateau and adapts to the hypoxic environment very well. The objectives of this study was to obtain candidate genes associated with hypoxia adaptation in the Tibet chicken embryos. In the present study, we used the fixation index (Fst) and cross population extended haplotype homozygosity (XPEHH) statistical methods to detect signatures of positive selection of the Tibet chicken, and analyzed the RNA sequencing data from the embryonic liver and heart with HISAT, StringTie and Ballgown for differentially expressed genes between the Tibet chicken and White leghorn (Gallus gallus, a kind of lowland chicken) embryos hatched under hypoxia condition. Genes which were screened out by both selection signature analysis and RNA sequencing analysis could be regarded as candidate genes for hypoxia adaptation of chicken embryos. We screened out 1772 genes by XPEHH and 601 genes by Fst, and obtained 384 and 353 differentially expressed genes in embryonic liver and heart, respectively. Among these genes, 89 genes were considered as candidate genes for hypoxia adaptation in chicken embryos. ARNT, AHR, GSTK1 and FGFR1 could be considered the most important candidate genes. Our findings provide references to elucidate the molecular mechanism of hypoxia adaptation in Tibet chicken embryos.

scholarly journals Identification and characterization of differentially expressed genes in Caenorhabditis elegans in response to pathogenic and nonpathogenic Stenotrophomonas maltophilia

2019 ◽  
Author(s):  
Leah J Radeke ◽  
Michael Herman
Keyword(s):  
Candidate Genes ◽  
Differentially Expressed Genes ◽  
Stenotrophomonas Maltophilia ◽  
Defense Mechanisms ◽  
Virulent Strain ◽  
Differentially Expressed ◽  
Transcriptional Responses ◽  
Transcriptomic Response ◽  
C Elegans ◽  
Realistic Interaction

Abstract Background: Stenotrophomonas maltophilia is an emerging nosocomial pathogen that causes infection in immunocompromised patients. S. maltophilia isolates are genetically diverse, contain diverse virulence factors, and are variably pathogenic within several host species. Members of the Stenotrophomonas genus are part of the native microbiome of C. elegans , being found in greater relative abundance within the worm than its environment, suggesting that these bacteria accumulate within C. elegans . Thus, study of the C. elegans-Stenotrophomonas interaction is of both medical and ecological significance. To identify host defense mechanisms, we analyzed the C. elegans transcriptomic response to S. maltophilia strains of varying pathogenicity: K279a, an avirulent clinical isolate, JCMS, a virulent strain isolated in association with soil nematodes near Manhattan, KS, and JV3, an even more virulent environmental isolate. Results: Overall, we found 145 genes that are commonly differentially expressed in response to pathogenic S. maltophilia strains, 89% of which are upregulated, with many even further upregulated in response to JV3 as compared to JCMS. There are many more JV3-specific differentially expressed genes (225, 11% upregulated) than JCMS-specific differentially expressed genes (14, 86% upregulated), suggesting JV3 has unique pathogenic mechanisms that could explain its increased virulence. We used connectivity within a gene network model to choose pathogen-specific and strain-specific differentially expressed candidate genes for functional analysis. Mutations in 13 of 22 candidate genes caused significant differences in C. elegans survival in response to at least one S. maltophilia strain, although not always the strain that induced differential expression, suggesting a dynamic response to varying levels of pathogenicity. Conclusions: Variation in observed pathogenicity and differences in host transcriptional responses to S. maltophilia strains reveal that strain-specific mechanisms play important roles in S. maltophilia pathogenesis. Furthermore, utilizing bacteria closely related to strains found in C. elegans natural environment provides a more realistic interaction for understanding host-pathogen response.

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