Abstract
Adipose tissues are phenotypically, metabolically and functionally heterogeneous based on the sites of their deposition. Undesirable fat deposits in the body are often detrimental to animal and human health. To unravel the potential underlying mechanisms governing accumulation of adipose tissues in various regions of the body, i.e., subcutaneous (SAT), visceral (VAT) and tail (TAT), we profiled transcriptomes from Tan sheep, a Chinese indigenous breed with notable fat tail using RNA-seq. Upon comparison, we identified a total of 1,058 differentially expressed genes (DEGs) between the three adipose types (218, 324, and 795 in SAT/VAT, SAT/TAT, and VAT/TAT, respectively), from which several known key players were identified that are involved in lipid metabolic process, Wnt signals, Vitamin A metabolism, and transcriptional regulation of adipocyte differentiation. We also found that many elevated genes in VAT were notably enriched for key biological processes such as cytokine secretion, signaling molecule interaction and immune systems. Several developmental genes including HOXC11, HOXC12 and HOXC13, and adipose-expressed genes in the tail region, such as HOTAIR_2, HOTAIR_3 and SP9 were specially highlighted, indicating their strong associations with tail fat development in fat-tailed sheep. Our results provide new insight into exploring the specific fat deposition in tail, also contribute to the understanding of differences between adipose depots.
Highlights
We estimated gene expression levels for each sample by using HTSeq software
Different adipose types exhibit divergent adipocyte phenotypes, secretory functions and lipid metabolism based on their depots[2,19,20], which may be essentially influenced by inherent genetic factors
We first analyzed the differences in adipocyte size and fatty acid composition in adipose tissues from different fat depots, investigated global gene expression patterns by transcriptome profiling of three different adipose types in Tan sheep: subcutaneous, visceral, and tail using Illumina HiSeq 4000
Summary
We estimated gene expression levels for each sample by using HTSeq software. Around 6% of 29,644 annotated genes were expressed more than 60 FPKM; about 11% were expressed between 15–60 FPKM, 18% between 3–15 FPKM, and 10% between 1–3 FPKM. The rest were expressed less than 1 FPKM. To ensure the reliability of the results for further analysis, pair-wise correlation between any two biological replicates in each group was checked based on the normalized FPKM values. The correlation coefficients were no less than 0.95 (Fig. S3), suggesting a high level of reproducibility and rationality of sample selection
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