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RNA-Sequencing of lean, intermediate, and obese pigs

ABSTRACT: We sequenced mRNA from subcuteneous adipose tissue of 36 pigs (12 Low, 12 Mean and 12 High) to investigate expression profiling of obesity (porcine model). Uploaded RNAseq data on the first 12 samples (from titles 1_SusScrofa to 12_SusScrofa) are LOW obese pigs, the middle 12 samples (from titles 13_SusScrofa to 24_SusScrofa) are MEDIUM obese pigs and the last 12 samples (from titles 24_SusScrofa to 36_SusScrofa) are HIGH obese pigs. These 3 categories based on an aggregate Obesity Index (OI) values and calculated using a multi-trait Estimated Breeding Value (EBV) and Selection Index methods combining nine obesity and obesity-related (OOR) phenotypes into a single value representative of the genetic predisposition to obesity. in Human studies, this is somewhat equivalent to combined multi-trait, weighted Polygenic Risk Scores (PRS) for obesity. That is, they are predicted based on genetic / genomic information and several correlated phenotypes using Mixed Models / BLUP. For more information on Obesity Index, refer to Frontiers in Genetics (2014), Sec. Systems Biology, Vol. 5. https://doi.org/10.3389/fgene.2014.00214

ORGANISM(S): Sus scrofa

PROVIDER: GSE61271 | GEO | 2015/01/15

SECONDARY ACCESSION(S): PRJNA260632

REPOSITORIES: GEO

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Project description:We adopted a transcriptome-wide microarray analysis approach to determine the extent to which vascular gene expression is altered as a result of juvenile obesity and identify obesity-responsive mRNAs. We examined transcriptional profiles in the left anterior descending coronary artery (LAD), perivascular fat adjacent to the LAD, and descending thoracic aorta between obese (n=5) and lean (n=6) juvenile Ossabaw pigs (age=22 weeks). Obesity was experimentally induced by feeding the animals a high-fat/high fructose corn syrup/high-cholesterol diet for 16 weeks. We found that expression of 189 vascular cell genes in the LAD and expression of 165 genes in the thoracic aorta were altered with juvenile obesity (FDRM-bM-^IM-$10%) with an overlap of only 28 genes between both arteries. Notably, a number of genes found to be markedly up-regulated in the LAD of obese pigs are implicated in atherosclerosis, including ACP5, LYZ, CXCL14, APOE, PLA2G7, LGALS3, SPP1, ITGB2, CYBB, and P2RY12. Furthermore, pathway analysis revealed the induction of pro-inflammatory and pro-oxidant pathways with obesity primarily in the LAD. Gene expression in the LAD perivascular fat was minimally altered with juvenile obesity. Together, we provide new evidence that obesity produces artery-specific changes in pre-translational regulation with a clear up-regulation of pro-atherogenic genes in the LAD. Our data may offer potential viable drug targets and mechanistic insights regarding the molecular precursors involved in the origins of over-nutrition and obesity-associated vascular disease. In particular, our results suggest that the oxLDL-LOX-1-NFM-NM-:B signaling axis may be involved in the early initiation of a juvenile obesity-induced pro-atherogenic coronary artery phenotype. We examined transcriptional profiles in the left anterior descending coronary artery (LAD), perivascular fat adjacent to the LAD, and descending thoracic aorta between obese (n=5) and lean (n=6) juvenile Ossabaw pigs (age= 22 weeks). All three tissue types were taken from each animal, and each was applied to one and only one array array except a single Thoracic aorta (Animal ID 63 because there were not enough arrays), so there were 32 total arrays (11 unique pigs).

Project description:Purpose: To identify, using RNA-sequencing, differentially expressed genes in the white adipose tissue in obesity and in response to lipid intervention in both normal weight and obese individuals. Methods: White adipose tissue mRNA profiles of normal weight and obses humans at baseline (0-weeks) and 12-weeks after fish oil (3d/day of which 1.1g EPA and 0.8g DHA) or corn oil (3g/day) supplementation were generated by deep sequencing using RNA sequencing. The sequence reads that passed quality filters were aligned to the human genome using TopHat and analyzed at the gene level using DESeq2. qRT–PCR validation was performed using Taqman probe assays Results: Using an optimized data analysis workflow, we mapped reads to the human genome (hg38.0) and identified 789 genes differentially expressed between normal weight and obese individuals at baseline (week-0) (adjusted p value <0.05 and fold change >2). 623 of these were upregulated and 175 were downregulated. Geneset enrichment analysis identified several enriched pathways, including regulation of immune and inflammatory response, tissue growth and glucose metabolism in obese indvidiuals in comparison to normal weight. We identified 26 genes differentially expressed in normal weight individuals in response to fish oil intervention (week-12) (adjusted p value <0.05 and fold change >1). 14 of these were upregulated and 12 were downregulated. We identified 8 genes differentially expressed in obese individuals in response to fish oil intervention (week-12) (adjusted p value <0.05 and fold change >1). 3 of these were upregulated and 5 were downregulated. Geneset enrichment analysis identified several enriched pathways, including regulation of immune and inflammatory response in both normal weight and obese individuals in response to fish oil intervention with greater effects in normal weight individuals. Conclusions: Our study provides novel insights into the association of obesity and changes to the human white adipose tissue transcriptome, in addition to the effects of fish oil (EPA and DHA) on the transcriptome of normal weight and obese individuals and differences in response between these BMI subgroups. Our study further identifies putative gene targets and molecular pathways that help to understand how obesity results in adipose tissue dysfunction and how EPA and DHA may modulate the long term expression of gene networks and disease pathways related to onset of obesity associated inflammation.

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RNA-Sequencing of lean, intermediate, and obese pigs

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