Suppr超能文献

利用集成生物信息学和机器学习鉴定低肌内脂肪和高肌内脂肪猪的潜在性别特异性生物标志物。

Identification of Potential Sex-Specific Biomarkers in Pigs with Low and High Intramuscular Fat Content Using Integrated Bioinformatics and Machine Learning.

机构信息

Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China.

出版信息

Genes (Basel). 2023 Aug 25;14(9):1695. doi: 10.3390/genes14091695.

Abstract

Intramuscular fat (IMF) content is a key determinant of pork quality. Controlling the genetic and physiological factors of IMF and the expression patterns of various genes is important for regulating the IMF content and improving meat quality in pig breeding. Growing evidence has suggested the role of genetic factors and breeds in IMF deposition; however, research on the sex factors of IMF deposition is still lacking. The present study aimed to identify potential sex-specific biomarkers strongly associated with IMF deposition in low- and high-IMF pig populations. The GSE144780 expression dataset of IMF deposition-related genes were obtained from the Gene Expression Omnibus. Initially, differentially expressed genes (DEGs) were detected in male and female low-IMF (162 DEGs, including 64 up- and 98 down-regulated genes) and high-IMF pigs (202 DEGs, including 147 up- and 55 down-regulated genes). Moreover, hub genes were screened via PPI network construction. Furthermore, hub genes were screened for potential sex-specific biomarkers using the least absolute shrinkage and selection operator machine learning algorithm, and sex-specific biomarkers in low-IMF (troponin I (), myosin light chain 9(), and serpin family C member 1()) and high-IMF pigs ( molecule (), molecule (), and amine oxidase copper-containing 2()) were identified, and then verified by quantitative real-time PCR (qRT-PCR) in semimembranosus muscles. Additionally, the gene set enrichment analysis and single-sample gene set enrichment analysis of hallmark gene sets were collectively performed on the identified biomarkers. Finally, the transcription factor-biomarker and lncRNA-miRNA-mRNA (biomarker) networks were predicted. The identified potential sex-specific biomarkers may provide new insights into the molecular mechanisms of IMF deposition and the beneficial foundation for improving meat quality in pig breeding.

摘要

肌内脂肪(IMF)含量是猪肉品质的关键决定因素。控制 IMF 的遗传和生理因素以及各种基因的表达模式对于调节 IMF 含量和改善猪育种中的肉质非常重要。越来越多的证据表明遗传因素和品种在 IMF 沉积中的作用;然而,关于 IMF 沉积的性别因素的研究仍然缺乏。本研究旨在确定与低和高 IMF 猪群中 IMF 沉积强烈相关的潜在性别特异性生物标志物。从基因表达综合数据库中获得了与 IMF 沉积相关基因的 GSE144780 表达数据集。最初,在低 IMF (162 个差异表达基因,包括 64 个上调和 98 个下调基因)和高 IMF (202 个差异表达基因,包括 147 个上调和 55 个下调基因)公猪和母猪中检测到差异表达基因(DEGs)。此外,通过 PPI 网络构建筛选出枢纽基因。此外,还使用最小绝对收缩和选择算子机器学习算法筛选潜在的性别特异性生物标志物,鉴定了低 IMF (肌钙蛋白 I ()、肌球蛋白轻链 9()和丝氨酸蛋白酶家族 C 成员 1())和高 IMF 猪()、()和胺氧化酶铜 2())中的性别特异性生物标志物,并通过半膜肌中的定量实时 PCR(qRT-PCR)进行验证。此外,对鉴定的生物标志物进行了标志性基因集的基因集富集分析和单样本基因集富集分析。最后,预测了转录因子-生物标志物和 lncRNA-miRNA-mRNA(生物标志物)网络。鉴定的潜在性别特异性生物标志物可能为 IMF 沉积的分子机制提供新的见解,并为改善猪育种中的肉质提供有益的基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95d6/10531182/d0f30c302b32/genes-14-01695-g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验