摘要
一位新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-机器学习的新研究是一篇报告的主题。根据NewsRx记者从南京发回的新闻报道，研究表明：“低滴漏是具有高经济价值的肉类的重要品质特征，但导致猪肉滴漏的关键基因和调控网络尚不清楚。”本报编辑引用南京农业大学的一项研究,“为了准确地鉴定影响宰后肌肉滴漏的关键基因,对12头杜洛克(长白?约克夏)猪进行了极高(n=6,H组)和极低(n=6,H组)的研究。”选择死后24h和48h滴漏量进行转录组测序，利用转录组数据对差异表达基因(DEGs)和加权基因共表达网络分析(WGCNA)进行重叠基因分析，并对重叠基因进行功能富集和蛋白质互作(PPI)网络分析。利用机器学习的方法,在PI网络的相互作用基因的基础上,对与滴灌损失相关的关键基因和调控网络进行了识别,最终确定了9个与MAPK信号转导途径、胰岛素信号转导途径和钙信号转导途径相关的潜在关键基因(IRS1、ESR1、HSPA6、INSR、SPOP、MSTN、LGALS4、MYLK2和FRMD4B)。通过单基因集富集分析(GSEA)进一步阐明了这些潜在关键基因的功能，GSEA结果表明这些基因主要与泛素介导的蛋白水解和氧化反应有关。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting originating from Nanjing, Peo ple's Republic of China, by NewsRx correspondents, research stated, "Low level o f drip loss is an important quality characteristic of meat with high economic va lue. However, the key genes and regulatory networks contributing to drip loss in pork remain largely unknown." Our news editors obtained a quote from the research from Nanjing Agricultural Un iversity, "To accurately identify the key genes affecting drip loss in muscles p ostmortem, 12 Duroc ? (Landrace ? Yorkshire) pigs with extremely high (n = 6, H group) and low (n = 6, L group) drip loss at both 24 h and 48 h postmortem were selected for transcriptome sequencing. The analysis of differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA) were perfo rmed to find the overlapping genes using the transcriptome data, and functional enrichment and protein-protein interaction (PPI) network analysis were conducted using the overlapping genes. Moreover, we used machine learning to identify the key genes and regulatory networks related to drip loss based on the interactive genes of the PPI network. Finally, nine potential key genes (IRS1, ESR1, HSPA6, INSR, SPOP, MSTN, LGALS4, MYLK2, and FRMD4B) mainly associated with the MAPK si gnaling pathway, the insulin signaling pathway, and the calcium signaling pathwa y were identified, and a single-gene set enrichment analysis (GSEA) was performe d to further annotate the functions of these potential key genes. The GSEA resul ts showed that these genes are mainly related to ubiquitin mediated proteolysis and oxidative reactions."
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