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Analysis of rumen microbial community in cattle through the integration of metagenomic and network-based approaches

机译:通过偏见和基于网络的方法的整合分析牛中的瘤胃微生物群落

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A better understanding of the composition of rumen microbial communities and the association between host genetic and microbial activities has important applications and implication in bioscience. Being capable of revealing the full extent of microbial gene diversity, metagenomics-based approaches hold great promises in this endeavor. This study investigates the rumen microbial community in cattle through the integration of metagenomic and network-based approaches. Based on the relative abundance of 1570 microbial genes identified in a metagenomics analysis, the co-abundance network was constructed and functional modules of microbial genes were identified. One of the main contributions of this study is to develop a random matrix theory-based approach to automatically determine the correlation threshold used to construct the co-abundance network. It has been shown that the network exhibits a highly modular structure with each of the three main modules well separated. The involvement of KEGG pathways in each module was analysed. A close look at the abundance profiles highlights that Module B is strongly associated with methane emissions while Module C is highly enriched with microbial genes associated with feed conversion efficiency.
机译:更好地了解瘤胃微生物社区的组成和宿主遗传和微生物活动之间的关联具有重要的应用和生物科学的含义。能够揭示微生物基因多样性的全部,基于偏见的方法在这一努力中持有巨大的承诺。本研究通过甲虫和基于网络的方法的整合研究了牛中的瘤胃微生物群落。基于在比例分析中鉴定的1570个微生物基因的相对丰度,构建了共度网络,鉴定了微生物基因的功能模块。本研究的主要贡献之一是开发基于随机矩阵理论的方法,以自动确定用于构造共同网络的相关阈值。已经表明,网络具有高度模块化的结构,其中三个主要模块中的每一个都很好地分开。分析了Kegg途径在每个模块中的参与。仔细看看丰富的概况亮点,模块B与甲烷排放强烈相关,而模块C高度富集与饲料转换效率相关的微生物基因。

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