Co-Expression Network Analysis Identifies miRNA⁻mRNA Networks Potentially Regulating Milk Traits and Blood Metabolites

MicroRNAs (miRNA) regulate mRNA networks to coordinate cellular functions. In this study, we constructed gene co-expression networks to detect miRNA modules (clusters of miRNAs with similar expression patterns) and miRNA⁻mRNA pairs associated with blood (triacylglyceride and nonesterified fatty acid...

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Veröffentlicht in:International journal of molecular sciences 2018-08, Vol.19 (9), p.2500
Hauptverfasser: Ammah, Adolf A, Do, Duy N, Bissonnette, Nathalie, Gévry, Nicolas, Ibeagha-Awemu, Eveline M
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container_title International journal of molecular sciences
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creator Ammah, Adolf A
Do, Duy N
Bissonnette, Nathalie
Gévry, Nicolas
Ibeagha-Awemu, Eveline M
description MicroRNAs (miRNA) regulate mRNA networks to coordinate cellular functions. In this study, we constructed gene co-expression networks to detect miRNA modules (clusters of miRNAs with similar expression patterns) and miRNA⁻mRNA pairs associated with blood (triacylglyceride and nonesterified fatty acids) and milk (milk yield, fat, protein, and lactose) components and milk fatty acid traits following dietary supplementation of cows' diets with 5% linseed oil (LSO) ( = 6 cows) or 5% safflower oil (SFO) ( = 6 cows) for 28 days. Using miRNA transcriptome data from mammary tissues of cows for co-expression network analysis, we identified three consensus modules: blue, brown, and turquoise, composed of 70, 34, and 86 miRNA members, respectively. The hub miRNAs (miRNAs with the most connections with other miRNAs) were miR-30d, miR-484 and miR-16b for blue, brown, and turquoise modules, respectively. Cell cycle arrest, and p53 signaling and transforming growth factor⁻beta (TGF-β) signaling pathways were the common gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enriched for target genes of the three modules. Protein percent ( = 0.03) correlated with the turquoise module in LSO treatment while protein yield ( = 0.003) and milk yield ( = 7 × 10 ) correlated with the turquoise model, protein and milk yields and lactose percent ( < 0.05) correlated with the blue module and fat percent ( = 0.04) correlated with the brown module in SFO treatment. Several fatty acids correlated ( < 0.05) with the blue (CLA:9,11) and brown (C4:0, C12:0, C22:0, C18:1n9c and CLA:10,12) modules in LSO treatment and with the turquoise (C14:0, C18:3n3 and CLA:9,11), blue (C14:0 and C23:0) and brown (C6:0, C16:0, C22:0, C22:6n3 and CLA:10,12) modules in SFO treatment. Correlation of miRNA and mRNA data from the same animals identified the following miRNA⁻mRNA pairs: miR-183/ ( = 0.003), miR-484/ ( = 0.011) and miR-130a/ ( = 0.004) with lowest -values for the blue, brown, and turquoise modules, respectively. Milk yield, protein yield, and protein percentage correlated ( < 0.05) with 28, 31 and 5 miRNA⁻mRNA pairs, respectively. Our results suggest that, the blue, brown, and turquoise modules miRNAs, hub miRNAs, miRNA⁻mRNA networks, cell cycle arrest GO term, p53 signaling and TGF-β signaling pathways have considerable influence on milk and blood phenotypes following dietary supplementation of dairy cows' diets with 5% LSO or 5% SFO.
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In this study, we constructed gene co-expression networks to detect miRNA modules (clusters of miRNAs with similar expression patterns) and miRNA⁻mRNA pairs associated with blood (triacylglyceride and nonesterified fatty acids) and milk (milk yield, fat, protein, and lactose) components and milk fatty acid traits following dietary supplementation of cows' diets with 5% linseed oil (LSO) ( = 6 cows) or 5% safflower oil (SFO) ( = 6 cows) for 28 days. Using miRNA transcriptome data from mammary tissues of cows for co-expression network analysis, we identified three consensus modules: blue, brown, and turquoise, composed of 70, 34, and 86 miRNA members, respectively. The hub miRNAs (miRNAs with the most connections with other miRNAs) were miR-30d, miR-484 and miR-16b for blue, brown, and turquoise modules, respectively. Cell cycle arrest, and p53 signaling and transforming growth factor⁻beta (TGF-β) signaling pathways were the common gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enriched for target genes of the three modules. Protein percent ( = 0.03) correlated with the turquoise module in LSO treatment while protein yield ( = 0.003) and milk yield ( = 7 × 10 ) correlated with the turquoise model, protein and milk yields and lactose percent ( &lt; 0.05) correlated with the blue module and fat percent ( = 0.04) correlated with the brown module in SFO treatment. Several fatty acids correlated ( &lt; 0.05) with the blue (CLA:9,11) and brown (C4:0, C12:0, C22:0, C18:1n9c and CLA:10,12) modules in LSO treatment and with the turquoise (C14:0, C18:3n3 and CLA:9,11), blue (C14:0 and C23:0) and brown (C6:0, C16:0, C22:0, C22:6n3 and CLA:10,12) modules in SFO treatment. Correlation of miRNA and mRNA data from the same animals identified the following miRNA⁻mRNA pairs: miR-183/ ( = 0.003), miR-484/ ( = 0.011) and miR-130a/ ( = 0.004) with lowest -values for the blue, brown, and turquoise modules, respectively. Milk yield, protein yield, and protein percentage correlated ( &lt; 0.05) with 28, 31 and 5 miRNA⁻mRNA pairs, respectively. 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In this study, we constructed gene co-expression networks to detect miRNA modules (clusters of miRNAs with similar expression patterns) and miRNA⁻mRNA pairs associated with blood (triacylglyceride and nonesterified fatty acids) and milk (milk yield, fat, protein, and lactose) components and milk fatty acid traits following dietary supplementation of cows' diets with 5% linseed oil (LSO) ( = 6 cows) or 5% safflower oil (SFO) ( = 6 cows) for 28 days. Using miRNA transcriptome data from mammary tissues of cows for co-expression network analysis, we identified three consensus modules: blue, brown, and turquoise, composed of 70, 34, and 86 miRNA members, respectively. The hub miRNAs (miRNAs with the most connections with other miRNAs) were miR-30d, miR-484 and miR-16b for blue, brown, and turquoise modules, respectively. Cell cycle arrest, and p53 signaling and transforming growth factor⁻beta (TGF-β) signaling pathways were the common gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enriched for target genes of the three modules. Protein percent ( = 0.03) correlated with the turquoise module in LSO treatment while protein yield ( = 0.003) and milk yield ( = 7 × 10 ) correlated with the turquoise model, protein and milk yields and lactose percent ( &lt; 0.05) correlated with the blue module and fat percent ( = 0.04) correlated with the brown module in SFO treatment. Several fatty acids correlated ( &lt; 0.05) with the blue (CLA:9,11) and brown (C4:0, C12:0, C22:0, C18:1n9c and CLA:10,12) modules in LSO treatment and with the turquoise (C14:0, C18:3n3 and CLA:9,11), blue (C14:0 and C23:0) and brown (C6:0, C16:0, C22:0, C22:6n3 and CLA:10,12) modules in SFO treatment. Correlation of miRNA and mRNA data from the same animals identified the following miRNA⁻mRNA pairs: miR-183/ ( = 0.003), miR-484/ ( = 0.011) and miR-130a/ ( = 0.004) with lowest -values for the blue, brown, and turquoise modules, respectively. Milk yield, protein yield, and protein percentage correlated ( &lt; 0.05) with 28, 31 and 5 miRNA⁻mRNA pairs, respectively. 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Do, Duy N ; Bissonnette, Nathalie ; Gévry, Nicolas ; Ibeagha-Awemu, Eveline M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c412t-e3fcec9c87f75d474d4775a87d2bebfa7f5434f763457acdd967753818b86a653</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Animals</topic><topic>Biomarkers</topic><topic>Blood</topic><topic>Cancer</topic><topic>Cattle</topic><topic>Cell cycle</topic><topic>Computational Biology - methods</topic><topic>Correlation</topic><topic>Disease</topic><topic>Encyclopedias</topic><topic>Fatty acids</topic><topic>Gene expression</topic><topic>Gene Expression Profiling</topic><topic>Gene Expression Regulation</topic><topic>Gene Ontology</topic><topic>Gene Regulatory Networks</topic><topic>Genes</topic><topic>Genetic Association Studies</topic><topic>Genetic engineering</topic><topic>Genomes</topic><topic>Growth factors</topic><topic>Lactose</topic><topic>Linseed oil</topic><topic>Meat quality</topic><topic>Metabolism</topic><topic>Metabolites</topic><topic>Metabolome</topic><topic>Metabolomics - methods</topic><topic>MicroRNAs</topic><topic>MicroRNAs - genetics</topic><topic>Milk</topic><topic>miRNA</topic><topic>Network analysis</topic><topic>Oils &amp; 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In this study, we constructed gene co-expression networks to detect miRNA modules (clusters of miRNAs with similar expression patterns) and miRNA⁻mRNA pairs associated with blood (triacylglyceride and nonesterified fatty acids) and milk (milk yield, fat, protein, and lactose) components and milk fatty acid traits following dietary supplementation of cows' diets with 5% linseed oil (LSO) ( = 6 cows) or 5% safflower oil (SFO) ( = 6 cows) for 28 days. Using miRNA transcriptome data from mammary tissues of cows for co-expression network analysis, we identified three consensus modules: blue, brown, and turquoise, composed of 70, 34, and 86 miRNA members, respectively. The hub miRNAs (miRNAs with the most connections with other miRNAs) were miR-30d, miR-484 and miR-16b for blue, brown, and turquoise modules, respectively. Cell cycle arrest, and p53 signaling and transforming growth factor⁻beta (TGF-β) signaling pathways were the common gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enriched for target genes of the three modules. Protein percent ( = 0.03) correlated with the turquoise module in LSO treatment while protein yield ( = 0.003) and milk yield ( = 7 × 10 ) correlated with the turquoise model, protein and milk yields and lactose percent ( &lt; 0.05) correlated with the blue module and fat percent ( = 0.04) correlated with the brown module in SFO treatment. Several fatty acids correlated ( &lt; 0.05) with the blue (CLA:9,11) and brown (C4:0, C12:0, C22:0, C18:1n9c and CLA:10,12) modules in LSO treatment and with the turquoise (C14:0, C18:3n3 and CLA:9,11), blue (C14:0 and C23:0) and brown (C6:0, C16:0, C22:0, C22:6n3 and CLA:10,12) modules in SFO treatment. Correlation of miRNA and mRNA data from the same animals identified the following miRNA⁻mRNA pairs: miR-183/ ( = 0.003), miR-484/ ( = 0.011) and miR-130a/ ( = 0.004) with lowest -values for the blue, brown, and turquoise modules, respectively. Milk yield, protein yield, and protein percentage correlated ( &lt; 0.05) with 28, 31 and 5 miRNA⁻mRNA pairs, respectively. Our results suggest that, the blue, brown, and turquoise modules miRNAs, hub miRNAs, miRNA⁻mRNA networks, cell cycle arrest GO term, p53 signaling and TGF-β signaling pathways have considerable influence on milk and blood phenotypes following dietary supplementation of dairy cows' diets with 5% LSO or 5% SFO.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>30149509</pmid><doi>10.3390/ijms19092500</doi><orcidid>https://orcid.org/0000-0001-8810-9294</orcidid><orcidid>https://orcid.org/0000-0003-3281-209X</orcidid><oa>free_for_read</oa></addata></record>
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source MEDLINE; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; MDPI - Multidisciplinary Digital Publishing Institute; PubMed Central
subjects Animals
Biomarkers
Blood
Cancer
Cattle
Cell cycle
Computational Biology - methods
Correlation
Disease
Encyclopedias
Fatty acids
Gene expression
Gene Expression Profiling
Gene Expression Regulation
Gene Ontology
Gene Regulatory Networks
Genes
Genetic Association Studies
Genetic engineering
Genomes
Growth factors
Lactose
Linseed oil
Meat quality
Metabolism
Metabolites
Metabolome
Metabolomics - methods
MicroRNAs
MicroRNAs - genetics
Milk
miRNA
Network analysis
Oils & fats
p53 Protein
Phenotype
Phenotypes
Proteins
Quantitative Trait, Heritable
RNA Interference
RNA, Messenger - genetics
Signal transduction
Transcriptome
Transforming growth factor-b
Triglycerides
title Co-Expression Network Analysis Identifies miRNA⁻mRNA Networks Potentially Regulating Milk Traits and Blood Metabolites
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