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Differences in the skeletal muscle transcriptome profile associated with extreme values of fatty acids content

View Article: PubMed Central - PubMed

ABSTRACT

Background: Lipids are a class of molecules that play an important role in cellular structure and metabolism in all cell types. In the last few decades, it has been reported that long-chain fatty acids (FAs) are involved in several biological functions from transcriptional regulation to physiological processes. Several fatty acids have been both positively and negatively implicated in different biological processes in skeletal muscle and other tissues. To gain insight into biological processes associated with fatty acid content in skeletal muscle, the aim of the present study was to identify differentially expressed genes (DEGs) and functional pathways related to gene expression regulation associated with FA content in cattle.

Results: Skeletal muscle transcriptome analysis of 164 Nellore steers revealed no differentially expressed genes (DEGs, FDR 10%) for samples with extreme values for linoleic acid (LA) or stearic acid (SA), and only a few DEGs for eicosapentaenoic acid (EPA, 5 DEGs), docosahexaenoic acid (DHA, 4 DEGs) and palmitic acid (PA, 123 DEGs), while large numbers of DEGs were associated with oleic acid (OA, 1134 DEGs) and conjugated linoleic acid cis9 trans11 (CLA-c9t11, 872 DEGs). Functional annotation and functional enrichment from OA DEGs identified important genes, canonical pathways and upstream regulators such as SCD, PLIN5, UCP3, CPT1, CPT1B, oxidative phosphorylation mitochondrial dysfunction, PPARGC1A, and FOXO1. Two important genes associated with lipid metabolism, gene expression and cancer were identified as DEGs between animals with high and low CLA-c9t11, specifically, epidermal growth factor receptor (EGFR) and RNPS.

Conclusion: Only two out of seven classes of molecules of FA studied were associated with large changes in the expression profile of skeletal muscle. OA and CLA-c9t11 content had significant effects on the expression level of genes related to important biological processes associated with oxidative phosphorylation, and cell growth, survival, and migration. These results contribute to our understanding of how some FAs modulate metabolism and may have protective health function.

Electronic supplementary material: The online version of this article (doi:10.1186/s12864-016-3306-x) contains supplementary material, which is available to authorized users.

No MeSH data available.


Related in: MedlinePlus

The mechanistic network of the upstream regulators and their relationship predicted by IPA®. The molecules shown in blue are predicted to be inhibited, while the molecules shown in orange are predicted to be activated as a result of OA content. Color intensity represents the level of inhibition or activation. The lines and arrows in blue represent a direct interaction and activation, respectively. The interrupted lines in yellow represents direct inhibition. The gray lines represent the interactions that OA content did not affect, but have been reported in the literature
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Fig3: The mechanistic network of the upstream regulators and their relationship predicted by IPA®. The molecules shown in blue are predicted to be inhibited, while the molecules shown in orange are predicted to be activated as a result of OA content. Color intensity represents the level of inhibition or activation. The lines and arrows in blue represent a direct interaction and activation, respectively. The interrupted lines in yellow represents direct inhibition. The gray lines represent the interactions that OA content did not affect, but have been reported in the literature

Mentions: To further explore the observed changes in gene expression, IPA® upstream regulator analyses were performed to identify the cascade of upstream transcriptional regulators that could be involved in the gene expression changes in skeletal muscle due to OA content. The IPA® program estimated the effects between transcriptional regulators and their target genes based on prior knowledge stored in the Ingenuity® Knowledge Base. Upstream regulators were identified from the list of DEGs for OA content (see Additional file 15), which were connected via mechanistic networks detected by IPA®. Peroxisome proliferator-activated receptor gamma, coactivator 1 alpha (PPARGC1A) was among the top predicted upstream regulators. PPARGC1A and ten other transcription factors (TFs) such as forkhead box O3 (FOXO3), peroxisome proliferator-activated receptor gamma, coactivator 1 beta (PPARGC1B), estrogen-related receptor gamma (ESRRG), sterol regulatory element binding transcription factor 1 (SREBF1), tumor protein p53 (TP53), forkhead box O1 (FOXO1), V-Myc avian myelocytomatosis viral oncogene homolog (MYC) and myogenic differentiation 1 (MYOD1) were predicted to be inhibited (blue shapes in Fig. 3), whereas the transcription factors forkhead Box O4 (FOXO4) and sterol regulatory element binding transcription factor 2 (SREBF2) were predicted to be activated (orange shapes in Fig. 3).Fig. 3


Differences in the skeletal muscle transcriptome profile associated with extreme values of fatty acids content
The mechanistic network of the upstream regulators and their relationship predicted by IPA®. The molecules shown in blue are predicted to be inhibited, while the molecules shown in orange are predicted to be activated as a result of OA content. Color intensity represents the level of inhibition or activation. The lines and arrows in blue represent a direct interaction and activation, respectively. The interrupted lines in yellow represents direct inhibition. The gray lines represent the interactions that OA content did not affect, but have been reported in the literature
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC5120530&req=5

Fig3: The mechanistic network of the upstream regulators and their relationship predicted by IPA®. The molecules shown in blue are predicted to be inhibited, while the molecules shown in orange are predicted to be activated as a result of OA content. Color intensity represents the level of inhibition or activation. The lines and arrows in blue represent a direct interaction and activation, respectively. The interrupted lines in yellow represents direct inhibition. The gray lines represent the interactions that OA content did not affect, but have been reported in the literature
Mentions: To further explore the observed changes in gene expression, IPA® upstream regulator analyses were performed to identify the cascade of upstream transcriptional regulators that could be involved in the gene expression changes in skeletal muscle due to OA content. The IPA® program estimated the effects between transcriptional regulators and their target genes based on prior knowledge stored in the Ingenuity® Knowledge Base. Upstream regulators were identified from the list of DEGs for OA content (see Additional file 15), which were connected via mechanistic networks detected by IPA®. Peroxisome proliferator-activated receptor gamma, coactivator 1 alpha (PPARGC1A) was among the top predicted upstream regulators. PPARGC1A and ten other transcription factors (TFs) such as forkhead box O3 (FOXO3), peroxisome proliferator-activated receptor gamma, coactivator 1 beta (PPARGC1B), estrogen-related receptor gamma (ESRRG), sterol regulatory element binding transcription factor 1 (SREBF1), tumor protein p53 (TP53), forkhead box O1 (FOXO1), V-Myc avian myelocytomatosis viral oncogene homolog (MYC) and myogenic differentiation 1 (MYOD1) were predicted to be inhibited (blue shapes in Fig. 3), whereas the transcription factors forkhead Box O4 (FOXO4) and sterol regulatory element binding transcription factor 2 (SREBF2) were predicted to be activated (orange shapes in Fig. 3).Fig. 3

View Article: PubMed Central - PubMed

ABSTRACT

Background: Lipids are a class of molecules that play an important role in cellular structure and metabolism in all cell types. In the last few decades, it has been reported that long-chain fatty acids (FAs) are involved in several biological functions from transcriptional regulation to physiological processes. Several fatty acids have been both positively and negatively implicated in different biological processes in skeletal muscle and other tissues. To gain insight into biological processes associated with fatty acid content in skeletal muscle, the aim of the present study was to identify differentially expressed genes (DEGs) and functional pathways related to gene expression regulation associated with FA content in cattle.

Results: Skeletal muscle transcriptome analysis of 164 Nellore steers revealed no differentially expressed genes (DEGs, FDR 10%) for samples with extreme values for linoleic acid (LA) or stearic acid (SA), and only a few DEGs for eicosapentaenoic acid (EPA, 5 DEGs), docosahexaenoic acid (DHA, 4 DEGs) and palmitic acid (PA, 123 DEGs), while large numbers of DEGs were associated with oleic acid (OA, 1134 DEGs) and conjugated linoleic acid cis9 trans11 (CLA-c9t11, 872 DEGs). Functional annotation and functional enrichment from OA DEGs identified important genes, canonical pathways and upstream regulators such as SCD, PLIN5, UCP3, CPT1, CPT1B, oxidative phosphorylation mitochondrial dysfunction, PPARGC1A, and FOXO1. Two important genes associated with lipid metabolism, gene expression and cancer were identified as DEGs between animals with high and low CLA-c9t11, specifically, epidermal growth factor receptor (EGFR) and RNPS.

Conclusion: Only two out of seven classes of molecules of FA studied were associated with large changes in the expression profile of skeletal muscle. OA and CLA-c9t11 content had significant effects on the expression level of genes related to important biological processes associated with oxidative phosphorylation, and cell growth, survival, and migration. These results contribute to our understanding of how some FAs modulate metabolism and may have protective health function.

Electronic supplementary material: The online version of this article (doi:10.1186/s12864-016-3306-x) contains supplementary material, which is available to authorized users.

No MeSH data available.


Related in: MedlinePlus