摘要猪支原体肺炎(mycoplasmal pneumonia of swine, MPS)是养猪(Sus scrofa)生产实践中一种常见的慢性呼吸道传染病。该病由于易感染且难治愈，继发感染后容易致死，一直给国内外养猪业造成较大的经济损失。目前，病理诊断、疫苗与抗生素药物研发等方面的研究往往难以达到根除疾病的目的，亟待对猪支原体肺炎相关遗传基础进行鉴定，从分子水平上解释其遗传机制，进而利用遗传规律进行抗病育种。因此，本研究通过基因本体(Gene Ontology, GO)富集分析、KEGG (Kyoto Encyclopedia of Genes and Genomes)通路分析和文本挖掘等生物信息学的手段对猪QTL数据库进行检索，从中筛选并注释候选基因。结果表明，(1) 47个相关QTL中所含的3 379个基因与猪支原体肺炎存在相关性，显著性筛选后余36个基因；(2) GO富集分析中与MPS产生关联的基因53个；(3) KEGG通路分析Asthma通路含基因16个；(4)文本挖掘的候选基因TNFα (tumor necrosis factor)、NRAMP1 (natural resistance-associated macrophage protein 1)、TCRs (T-cell receptor genes)、CYP1A1 (cytochrome P450 family 1 subfamily A member 1)、CYP3A29 (cytochrome P450 3A29v4)、SERPING1 (serpin family G member 1)共6个。不计重复后最终得到104个优化的候选基因。其中，TNF、POU5F1 (POU domain, class 5, transcription factor 1)为重要的候选基因，在猪支原体肺炎感染过程中可能起关键作用。本研究从分子水平对猪支原体肺炎的遗传机制进行了初探，MPS候选基因集的建立将为后续研究及疾病相关基因的鉴定工作提供参考。
Abstract：Mycoplasmal pneumonia of swine (MPS, also referred to as 'enzootic pneumonia', EP) caused by Mycoplasma hyopneumoniae (Mhp), is a chronic respiratory disease with the clinical sign of persistent dry cough. Epidemic of MPS has a negative impact on growth rate and feed conversion. The causative agent Mhp is easily infected and it will become worse with co-infections, which always gives rise to huge economic damage to the swine (Sus scrofa) industry, both at home and abroad. At present, most research is centered on pathological diagnosis, immunity, prevention and control. However, these medical treatments and public health measures are incapable of alleviating the negative impacts from MPS. For better solving the occurrence of MPS, we intend to adopt bioinformatics analysis methods to explore MPS from the molecular level for better illustrating its mechanism. For the purpose, this study was mainly based on Gene Ontology (GO) enrichment analysis, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis, text mining and other bioinformatics tools to complete the PigQTLdb (pig QTL Database) retrieval and biological annotations for MPS candidate genes. The results showed that 47 possible QTLs were associated with MPS with the full use of PigQTLdb, 2 of which were related to MPS susceptibility, and the others were involved in immunity. 38 GO terms linked to MPS were searched by CoPub, a text-mining tool, and then 3 379 genes contained in 47 QTLs were effective after semantic similarities calculation with R programming and GOSim package. Among them, 36 genes were statistically significant. For another, there were 53 genes found in GO enrichment analysis, and 16 genes in 'Asthma' pathway from KEGG analysis. In addition, six candidate genes were from the results of text-mining, including TNFα (tumor necrosis factor), NRAMP1 (natural resistance-associated macrophage protein 1), TCRs (T-cell receptor genes), CYP1A1 (cytochrome P450 family 1 subfamily A member 1), CYP3A29 (cytochrome P450 3A29v4) and SERPING1 (serpin family G member 1). As a result, there were totally 104 optimized genes for the MPS candidate gene set. Special attention should be paid on gene TNF, for it was involved in both GO enrichment analysis and KEGG pathway analysis results, and appeared in the text mining results as well. To be specific, TNF was one of the crucial factors to induce inflammation, which ranked fourth in significance among all candidate genes during calculations. We inferred that TNF and POU5F1 were the candidate genes of vital importance during MPS infections. These findings will offer a new aspect for the further research in the future, though there would be some improvements in the analysis, and these conclusions remained to be proved. In next step, we will make efforts to explain the relationship between MPS and other important economic traits and explore the molecular differences between Chinese indigenous pigs and western imported pigs for further to indicate its heritance mechanism and provide insights for human asthma study one day.
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