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This study investigated how gene expression is affected by dietary fatty acids (FA) by using pigs as a reliable model for studying human diseases that involve lipid metabolism. This includes changes in FA composition in the liver, blood serum parameters and overall metabolic pathways. RNA-Seq data from 32 pigs were analyzed using Weighted Gene Co-expression Network Analysis (WGCNA). Our aim was to identify changes in blood serum parameters and gene expression between diets containing 3% soybean oil (SOY3.0) and a standard pig production diet containing 1.5% soybean oil (SOY1.5). Significantly, both the SOY1.5 and SOY3.0 groups showed significant modules, with a higher number of co-expressed modules identified in the SOY3.0 group. Correlated modules and specific features were identified, including enriched terms and pathways such as the histone acetyltransferase complex, type I diabetes mellitus pathway, cholesterol metabolism, and metabolic pathways in SOY1.5, and pathways related to neurodegeneration and Alzheimer's disease in SOY3.0. The variation in co-expression observed for HDL in the groups analyzed suggests different regulatory patterns in response to the higher concentration of soybean oil. Key genes co-expressed with metabolic processes indicative of diseases such as Alzheimer's was also identified, as well as genes related to lipid transport and energy metabolism, including CCL5, PNISR, DEGS1. These findings are important for understanding the genetic and metabolic responses to dietary variation and contribute to the development of more precise nutritional strategies.
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Cystic echinococcosis (CE) is a zoonotic disease caused by the tapeworm Echinococcus granulosus sensu lato (s.l). In the intermediate host, this disease is characterized by the growth of cysts in viscera such as liver and lungs, inside of which the parasite develops to the next infective stage known as protoscoleces. There are records that the infected viscera affect the development and morphology of E. granulosus s.l. protoscolex in hosts such as buffalo or humans. However, the molecular mechanisms that drive these differences remains unknown. Weighted gene co-expression network analysis (WGCNA) using a set of RNAseq data obtained from E. granulosus sensu stricto (s.s.) protoscoleces found in liver and lung cysts reveals 34 modules in protoscoleces of liver origin, of which 12 have differential co-expression from protoscoleces of lung origin. Three of these twelve modules contain hub genes related to immune evasion: tegument antigen, tegumental protein, ubiquitin hydrolase isozyme L3, COP9 signalosome complex subunit 3, tetraspanin CD9 antigen, and the methyl-CpG-binding protein Mbd2. Also, two of the twelve modules contain only hypothetical proteins with unknown orthology, which means that there are a group of unknown function proteins co-expressed inside the protoscolex of liver CE cyst origin. This is the first evidence of gene expression differences in protoscoleces from CE cysts found in different viscera, with co-expression networks that are exclusive to protoscoleces from liver CE cyst samples. This should be considered in the control strategies of CE, as intermediate hosts can harbor CE cysts in liver, lungs, or both organs simultaneously.
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Cistos , Equinococose , Echinococcus granulosus , Humanos , Animais , Echinococcus granulosus/genética , Evasão da Resposta Imune , Genótipo , Equinococose/genética , Equinococose/parasitologiaRESUMO
Biological systems respond to environmental perturbations and a large diversity of compounds through gene interactions, and these genetic factors comprise complex networks. Experimental information from transcriptomic studies has allowed the identification of gene networks that contribute to our understanding of microbial adaptations. In this study, we analyzed the gene co-expression networks of three Bifidobacterium species in response to different types of human milk oligosaccharides (HMO) using weighted gene co-expression analysis (WGCNA). RNA-seq data obtained from Geo Datasets were obtained for Bifidobacterium longum subsp. Infantis, Bifidobacterium bifidum and Bifidobacterium longum subsp. Longum. Between 10 and 20 co-expressing modules were obtained for each dataset. HMO-associated genes appeared in the modules with more genes for B. infantis and B. bifidum, in contrast with B. longum. Hub genes were identified in each module, and in general they participated in conserved essential processes. Certain modules were differentially enriched with LacI-like transcription factors, and others with certain metabolic pathways such as the biosynthesis of secondary metabolites. The three Bifidobacterium transcriptomes showed distinct regulation patterns for HMO utilization. HMO-associated genes in B. infantis co-expressed in two modules according to their participation in galactose or N-Acetylglucosamine utilization. Instead, B. bifidum showed a less structured co-expression of genes participating in HMO utilization. Finally, this category of genes in B. longum clustered in a small module, indicating a lack of co-expression with main cell processes and suggesting a recent acquisition. This study highlights distinct co-expression architectures in these bifidobacterial genomes during HMO consumption, and contributes to understanding gene regulation and co-expression in these species of the gut microbiome.
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miR-122 has been considered both as tumor suppressor miRNA and oncomiR in breast tumor phenotypes. However, the role of miR-122 in triple-negative breast cancer (TNBC) is still unknown. In this study, the clinical value of miR-122 was used to describe the transcriptomic landscape of TNBC tumors obtained from The Cancer Genome Atlas database. Low expression levels of miR-122 were associated with poor overall survival (OS) of TNBC patients than those with higher expression levels of miR-122. We identified gene expression profiles in TNBC tumors expressed lower or higher miR-122. Gene coexpression networks analysis revealed gene modules and hub genes specific to TNBC tumors with low or high miR-122 levels. Gene ontology and KEGG pathways analysis revealed that gene modules in TNBC with gain of miR-122 were related to cell cycle and DNA repair, while in TNBC with loss of miR-122 were enriched in cell cycle, proliferation, apoptosis and activation of cell migration and invasion. The expression of hub genes distinguished TNBC tumors with gain or loss of miR-122 from normal breast tissues. Furthermore, high levels of hub genes were associated with better OS in TNBC patients. Interestingly, the gene coexpression network related to loss of miR-122 were enriched with target genes of miR-122, but this did not observed in those with gain of miR-122. Target genes of miR-122 are oncogenes mainly associated with cell differentiation-related processes. Finally, 75 genes were identified exclusively associated to loss of miR-122, which are also implicated in cell differentiation. In conclusion, miR-122 could act as tumor suppressor by controlling oncogenes in TNBC.
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MicroRNAs , Neoplasias de Mama Triplo Negativas , Humanos , Neoplasias de Mama Triplo Negativas/genética , Neoplasias de Mama Triplo Negativas/metabolismo , Transcriptoma , Linhagem Celular Tumoral , Proliferação de Células/genética , MicroRNAs/genética , MicroRNAs/metabolismo , Regulação Neoplásica da Expressão GênicaRESUMO
Introduction: Biological systems respond to environmental disturbances and a wide range of compounds through complex gene interaction networks. The enormous growth of experimental information obtained using large-scale genomic techniques such as microarrays and RNA sequencing led to the construction of a wide variety of gene co-expression networks in recent years. These networks allow the discovery of clusters of co-expressed genes that potentially work in the same process linking them to biological processes often of interest to industrial, medicinal, and academic research. Methods: In this study, we built the gene co-expression network of Ustilago maydis from the gene expression data of 168 samples belonging to 19 series, which correspond to the GPL3681 platform deposited in the NCBI using WGCNA software. This network was analyzed to identify clusters of co-expressed genes, gene hubs and Gene Ontology terms. Additionally, we identified relevant modules through a hypergeometric approach based on a predicted set of transcription factors and virulence genes. Results and Discussion: We identified 13 modules in the gene co-expression network of U. maydis. The TFs enriched in the modules of interest belong to the superfamilies of Nucleic acid-binding proteins, Winged helix DNA-binding, and Zn2/Cys6 DNA-binding. On the other hand, the modules enriched with virulence genes were classified into diseases related to corn smut, Invasive candidiasis, among others. Finally, a large number of hypothetical, a large number of hypothetical genes were identified as highly co-expressed with virulence genes, making them possible experimental targets.
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Beef is a source of essential fatty acids (EFA), linoleic (LA) and alpha-linolenic (ALA) acids, which protect against inflammatory and cardiovascular diseases in humans. However, the intramuscular EFA profile in cattle is a complex and polygenic trait. Thus, this study aimed to identify potential regulatory genes of the essential fatty acid profile in Longissimus thoracis of Nellore cattle finished in feedlot. Forty-four young bulls clustered in four groups of fifteen animals with extreme values for each FA were evaluated through differentially expressed genes (DEG) analysis and two co-expression methodologies (WGCNA and PCIT). We highlight the ECHS1, IVD, ASB5, and ERLIN1 genes and the TF NFIA, indicated in both FA. Moreover, we associate the NFYA, NFYB, PPARG, FASN, and FADS2 genes with LA, and the RORA and ELOVL5 genes with ALA. Furthermore, the functional enrichment analysis points out several terms related to FA metabolism. These findings contribute to our understanding of the genetic mechanisms underlying the beef EFA profile in Nellore cattle finished in feedlot.
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Eating disorders are psychiatric disorders characterized by disturbed eating behaviors. They have a complex etiology in which genetic and environmental factors interact. Analyzing gene-environment interactions could help us to identify the mechanisms involved in the etiology of such conditions. For example, comethylation module analysis could detect the small effects of epigenetic interactions, reflecting the influence of environmental factors. We used MethylationEPIC and Psycharray microarrays to determine DNA methylation levels and genotype from 63 teenagers with eating disorders. We identified 11 comethylation modules in WGCNA (Weighted Gene Correlation Network Analysis) and correlated them with single nucleotide polymorphisms (SNP) and clinical features in our subjects. Two comethylation modules correlated with clinical features (BMI and height) in our sample and with SNPs associated with these phenotypes. One of these comethylation modules (yellow) correlated with BMI and rs10494217 polymorphism (associated with waist-hip ratio). Another module (black) was correlated with height, rs9349206, rs11761528, and rs17726787 SNPs; these polymorphisms were associated with height in previous GWAS. Our data suggest that genetic variations could alter epigenetics, and that these perturbations could be reflected as variations in clinical features.
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Epigênese Genética , Transtornos da Alimentação e da Ingestão de Alimentos/epidemiologia , Transtornos da Alimentação e da Ingestão de Alimentos/genética , Predisposição Genética para Doença , Polimorfismo de Nucleotídeo Único , Adolescente , Metilação de DNA , Regulação da Expressão Gênica , Redes Reguladoras de Genes , Genótipo , Humanos , México/epidemiologiaRESUMO
Patients with substance use disorders (SUD) are at high risk to die by suicide. So far, the neurobiology of the suicide-SUD association has not been elucidated. This study aimed to identify potential pharmacological targets among hub genes from brain gene co-expression networks of individuals with SUD in a suicidal and non-suicidal context. Post-mortem samples from the prefrontal cortex of 79 individuals were analyzed. Individuals were classified into the following groups: suicides with SUD (n = 28), suicides without SUD (n = 23), nonsuicides with SUD (n = 9), nonsuicides without SUD (n = 19). Gene expression profiles were evaluated with the Illumina HumanHT-12 v4 array. Co-expression networks were constructed in WGCNA using the differentially expressed genes found in the comparisons: (a) suicides with and without SUD and (b) nonsuicides with and without SUD. Hub genes were selected for drug-gene interaction testing in the DGIdb database. Among drugs interacting with hub genes in suicides we found MAOA inhibitors and dextromethorphan. In the nonsuicide individuals, we found interactions with eglumegad and antipsychotics (olanzapine, clozapine, loxapine). Modafinil was found to interact with genes in both suicides and nonsuicides. These drugs represent possible candidate treatments for patients with SUD with and without suicidal behavior and their study in each context is encouraged.
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Antipsicóticos/farmacologia , Encéfalo/efeitos dos fármacos , Reposicionamento de Medicamentos/métodos , Redes Reguladoras de Genes/efeitos dos fármacos , Transtornos Relacionados ao Uso de Substâncias/tratamento farmacológico , Prevenção do Suicídio , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Encéfalo/metabolismo , Criança , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Transtornos Relacionados ao Uso de Substâncias/genética , Transtornos Relacionados ao Uso de Substâncias/patologia , Transcriptoma , Adulto JovemRESUMO
Hevea brasiliensis (rubber tree) is a large tree species of the Euphorbiaceae family with inestimable economic importance. Rubber tree breeding programs currently aim to improve growth and production, and the use of early genotype selection technologies can accelerate such processes, mainly with the incorporation of genomic tools, such as marker-assisted selection (MAS). However, few quantitative trait loci (QTLs) have been used successfully in MAS for complex characteristics. Recent research shows the efficiency of genome-wide association studies (GWAS) for locating QTL regions in different populations. In this way, the integration of GWAS, RNA-sequencing (RNA-Seq) methodologies, coexpression networks and enzyme networks can provide a better understanding of the molecular relationships involved in the definition of the phenotypes of interest, supplying research support for the development of appropriate genomic based strategies for breeding. In this context, this work presents the potential of using combined multiomics to decipher the mechanisms of genotype and phenotype associations involved in the growth of rubber trees. Using GWAS from a genotyping-by-sequencing (GBS) Hevea population, we were able to identify molecular markers in QTL regions with a main effect on rubber tree plant growth under constant water stress. The underlying genes were evaluated and incorporated into a gene coexpression network modelled with an assembled RNA-Seq-based transcriptome of the species, where novel gene relationships were estimated and evaluated through in silico methodologies, including an estimated enzymatic network. From all these analyses, we were able to estimate not only the main genes involved in defining the phenotype but also the interactions between a core of genes related to rubber tree growth at the transcriptional and translational levels. This work was the first to integrate multiomics analysis into the in-depth investigation of rubber tree plant growth, producing useful data for future genetic studies in the species and enhancing the efficiency of the species improvement programs.
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PURPOSE: Melanoma is a malignant skin tumor, and its incidence is rising. To explore the specific differences in benign and malignant melanoma at the genetic level, we performed a series of bioinformatics analyses, including differential gene analysis, co-expression analysis, enrichment analysis, and regulatory prediction. METHODS: The microarray data of benign and malignant melanocytes were downloaded from GEO, and 1917 differential genes were obtained by differential analysis (p < 0.05). Weighted gene co-expression network analysis obtained three functional barrier modules. The essential genes of each module are SMARTA4, HECA, and C1R. RESULTS: The results of the enrichment analysis showed that the dysfunctional module gene was mainly associated with RNA splicing and Adherens junction. Through the pivotal analysis of ncRNA, it was found that miR-448, miR-152-3p, and miR-302b-3p essentially regulate three modules, which we consider to be critical regulators. In the pivot analysis of TF, more control modules include ARID3A, E2F1, E2F3, and E2F8. CONCLUSIONS: We believe that the regulator (miR-448, miR-152-3p, miR-302b-3p) regulates the expression of the core gene SMARCA4, which in turn affects the signal transduction of the Adherens junction. It eventually leads to the deterioration of benign skin spasms into melanoma.