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首页> 外文会议>International Conference on Biological Information and Biomedical Engineering >Understanding the relationships between rumen microbiome genes and metabolites to be used for prediction of cattle phenotypes
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Understanding the relationships between rumen microbiome genes and metabolites to be used for prediction of cattle phenotypes

机译：了解瘤胃微生物组基因与代谢物之间的关系用于预测牛表型

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The growing world population is facing increased future nutritional needs for meat and milk which need to be produced with minimal environmental impact, e.g. reduced methane emissions from ruminants. The combination of meta-genomics and metabolomics can be effectively applied to understand rumen microbial gene expression, metabolic mechanisms that affect methane emissions and to address the challenges of ruminant production. Using 36 rumen samples derived from two omics studies, we conducted an in-depth analysis of the differences in diets and methane emissions from rumen metabolites and microbial genes. The top five integrals with significant (P<0.0001) differences in terms of their intensity measured across sample groups were found to be the same when samples were divided based on diet treatments and methane emissions. Based on the combination of statistical analysis and network approaches, this paper investigates the relationships between rumen microbial genes and integrals associated with metabolites which could be used for prediction of cattle phenotypes. Up to 98% of microbial genes and metabolites have no significant (P>0.05) linear correlation. The sample correlation network constructed using both integrals associated with metabolites and relative abundances of 20 microbial genes associated with methane emission exhibited a highly modular structure, which forms well-separated clusters according to different diet treatments. The evidence from this research confirmed the response of rumen microbes to different basal diets, and these activities subsequently affect methane emissions.
机译：肉和牛奶的日益增长的世界人口正在面临增加的未来营养需求，这是需要产生的肉类和牛奶，这是最小的环境影响，例如，从反刍动物减少甲烷排放。可以有效地应用Meta基因组和代谢组学的组合，以了解瘤胃微生物基因表达，影响甲烷排放的代谢机制，并解决反刍动物生产的挑战。使用来自两个OMICS研究的36个瘤胃样本，我们对来自瘤胃代谢物和微生物基因的饮食和甲烷排放的差异进行了深入的分析。当基于饮食治疗和甲烷排放量分配样品时，发现其强度差异（P <0.0001）差异的前五个积分差异是相同的。基于统计分析和网络方法的结合，本文研究了与代谢物相关的瘤胃微生物基因与组成之间的关系，该代谢物可以用于预测牛表型。高达98％的微生物基因和代谢物无显着（p> 0.05）线性相关性。使用与代谢物相关的两种积分和与甲烷发射相关的20微生物基因的相对丰度构成的样品相关网络表现出高度模块化的结构，其根据不同的饮食治疗形成分离良好的簇。本研究的证据证实了瘤胃微生物对不同基础饮食的反应，这些活动随后影响甲烷排放。

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