Yang Yongli, Li Mingli, Zhu Yixuan, Wang Xiaoyi, Chen Qiang, Lu Shaoxiong
Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan, China.
Heliyon. 2024 May 15;10(10):e31311. doi: 10.1016/j.heliyon.2024.e31311. eCollection 2024 May 30.
Backfat thickness (BT) and intramuscular fat (IMF) content are closely appertained to meat production and quality in pig production. Deposition in subcutaneous adipose (SA) and IMF concerns different genes and regulatory mechanisms. And larger studies with rigorous design should be carried to explore the molecular regulation of fat deposition in different tissues. The purpose of this study is to gain a better understanding of the molecular mechanisms underlying differences in fat deposition among different tissues and identify tissue-specific genes involved in regulating fat deposition. The SA-associated datasets (GSE122349 and GSE145956) and IMF-associated datasets (GSE165613 and GSE207279) were downloaded from the Gene Expression Omnibus (GEO) as the BT and IMF group, respectively. Subsequently, the Robust Rank Aggregation (RRA) algorithm identified 27 down- and 29 up-regulated differentially expressed genes (DEGs) in the BT group. Based on bioinformatics and three machine learning algorithms, four SA deposition-related potential biomarkers, namely , , , and were selected. was evaluated as the most valuable biomarker for the SA mechanism. The 18 down- and 34 up-regulated DEGs in the IMF group were identified, and and were screened as the IMF deposition-related candidate core genes, especially the may play the critical role in IMF deposition regulation. Moreover, based on the constructed ceRNA network, we postulated that the role of predicted ceRNA interaction network of XIST, NEAT1/miR-15a-5p, miR-16-5p, miR-424-5p, miR-497-5p/ were vital in the SA metabolism, XIST, NEAT1/miR-27a/b-3p, 181a/c-5p/ might contribute to the regulation to IMF metabolism, which all gave suggestions in molecular mechanism for regulation of fat deposition. These findings may facilitate advancements in porcine quality at the genetic and molecular levels and assist with human obesity-associated diseases.
背膘厚度（BT）和肌内脂肪（IMF）含量与生猪生产中的肉质和产量密切相关。皮下脂肪（SA）和IMF中的脂肪沉积涉及不同的基因和调控机制。因此，需要开展设计严谨的大规模研究，以探索不同组织中脂肪沉积的分子调控机制。本研究旨在深入了解不同组织间脂肪沉积差异的分子机制，并鉴定参与调控脂肪沉积的组织特异性基因。分别从基因表达综合数据库（GEO）下载了SA相关数据集（GSE122349和GSE145956）和IMF相关数据集（GSE165613和GSE207279）作为BT组和IMF组。随后，通过稳健秩聚合（RRA）算法在BT组中鉴定出27个下调和29个上调的差异表达基因（DEG）。基于生物信息学和三种机器学习算法，筛选出四个与SA沉积相关的潜在生物标志物，即 、 、 和 。 被评估为SA机制中最有价值的生物标志物。在IMF组中鉴定出18个下调和34个上调的DEG，并筛选出 和 作为与IMF沉积相关的候选核心基因，尤其是 可能在IMF沉积调控中起关键作用。此外，基于构建的ceRNA网络，我们推测XIST、NEAT1/miR-15a-5p、miR-16-5p、miR-424-5p、miR-497-5p/的预测ceRNA相互作用网络在SA代谢中起重要作用，XIST、NEAT1/miR-27a/b-3p、181a/c-5p/可能有助于调控IMF代谢，这些都为脂肪沉积调控的分子机制提供了线索。这些发现可能有助于在遗传和分子水平上提高猪肉品质，并为人类肥胖相关疾病提供帮助。
