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Quantitative Metagenomic Analyses Based on Average Genome Size Normalization

机译:基于平均基因组大小归一化的定量元基因组分析

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Over the past quarter-century, microbiologists have used DNA sequence information to aid in the characterization of microbial communities. During the last decade, this has expanded from single genes to microbial community genomics, or metagenomics, in which the gene content of an environment can provide not just a census of the community members but direct information on metabolic capabilities and potential interactions among community members. Here we introduce a method for the quantitative characterization and comparison of microbial communities based on the normalization of metagenomic data by estimating average genome sizes. This normalization can relieve comparative biases introduced by differences in community structure, number of sequencing reads, and sequencing read lengths between different metagenomes. We demonstrate the utility of this approach by comparing metagenomes from two different marine sources using both conventional small-subunit (SSU) rRNA gene analyses and our quantitative method to calculate the proportion of genomes in each sample that are capable of a particular metabolic trait. With both environments, to determine what proportion of each community they make up and how differences in environment affect their abundances, we characterize three different types of autotrophic organisms: aerobic, photosynthetic carbon fixers (the Cyanobacteria ); anaerobic, photosynthetic carbon fixers (the Chlorobi ); and anaerobic, nonphotosynthetic carbon fixers (the Desulfobacteraceae ). These analyses demonstrate how genome proportionality compares to SSU rRNA gene relative abundance and how factors such as average genome size and SSU rRNA gene copy number affect sampling probability and therefore both types of community analysis.
机译:在过去的25年中,微生物学家一直使用DNA序列信息来帮助表征微生物群落。在过去的十年中,这已从单一基因扩展到微生物群落基因组学或宏基因组学,其中环境的基因内容不仅可以提供社区成员的普查,还可以提供有关代谢能力和社区成员之间潜在相互作用的直接信息。在这里,我们通过估计平均基因组大小,基于宏基因组学数据的归一化,介绍了一种对微生物群落进行定量表征和比较的方法。这种归一化可以减轻由群落结构,测序读数的数目以及不同元基因组之间的测序读数长度的差异引起的比较偏倚。通过使用常规的小亚基(SSU)rRNA基因分析和我们的定量方法来计算每个样品中具有特定代谢性状的基因组比例,我们通过比较来自两个不同海洋来源的基因组来证明该方法的实用性。在这两种环境下,为了确定它们在每个社区中所占的比例以及环境差异如何影响其丰富度,我们表征了三种不同类型的自养生物:需氧,光合碳固定剂(蓝藻);厌氧,光合碳固定剂(Chlorobi);和厌氧的非光合碳固定剂(Desulfobacteraceae)。这些分析表明,基因组比例与SSU rRNA基因相对丰度相比如何;平均基因组大小和SSU rRNA基因拷贝数等因素如何影响采样概率,进而影响两种类型的群落分析。

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