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首页> 外文期刊>PLoS Computational Biology >The GAAS Metagenomic Tool and Its Estimations of Viral and Microbial Average Genome Size in Four Major Biomes
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The GAAS Metagenomic Tool and Its Estimations of Viral and Microbial Average Genome Size in Four Major Biomes

机译:GAAS的元基因组学工具及其在四个主要生物群落中病毒和微生物平均基因组大小的估计

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Metagenomic studies characterize both the composition and diversity of uncultured viral and microbial communities. BLAST-based comparisons have typically been used for such analyses; however, sampling biases, high percentages of unknown sequences, and the use of arbitrary thresholds to find significant similarities can decrease the accuracy and validity of estimates. Here, we present Genome relative Abundance and Average Size (GAAS), a complete software package that provides improved estimates of community composition and average genome length for metagenomes in both textual and graphical formats. GAAS implements a novel methodology to control for sampling bias via length normalization, to adjust for multiple BLAST similarities by similarity weighting, and to select significant similarities using relative alignment lengths. In benchmark tests, the GAAS method was robust to both high percentages of unknown sequences and to variations in metagenomic sequence read lengths. Re-analysis of the Sargasso Sea virome using GAAS indicated that standard methodologies for metagenomic analysis may dramatically underestimate the abundance and importance of organisms with small genomes in environmental systems. Using GAAS, we conducted a meta-analysis of microbial and viral average genome lengths in over 150 metagenomes from four biomes to determine whether genome lengths vary consistently between and within biomes, and between microbial and viral communities from the same environment. Significant differences between biomes and within aquatic sub-biomes (oceans, hypersaline systems, freshwater, and microbialites) suggested that average genome length is a fundamental property of environments driven by factors at the sub-biome level. The behavior of paired viral and microbial metagenomes from the same environment indicated that microbial and viral average genome sizes are independent of each other, but indicative of community responses to stressors and environmental conditions.
机译:元基因组学研究表征了未培养的病毒和微生物群落的组成和多样性。基于BLAST的比较通常用于此类分析。但是,采样偏差,未知序列的高百分比以及使用任意阈值查找明显的相似性会降低估计的准确性和有效性。在这里,我们介绍了基因组相对丰度和平均大小(GAAS),这是一个完整的软件包,它以文本和图形格式提供了改进的元基因组群落组成和平均基因组长度的估计。 GAAS实施了一种新颖的方法,可以通过长度归一化控制采样偏差,通过相似度加权调整多个BLAST相似度,并使用相对比对长度选择明显的相似度。在基准测试中,GAAS方法对于高百分比的未知序列和宏基因组序列读取长度的变化均具有鲁棒性。使用GAAS对Sargasso Sea病毒进行的重新分析表明,用于宏基因组分析的标准方法可能会大大低估环境系统中具有小型基因组的生物的丰度和重要性。使用GAAS,我们对来自四个生物群落的150多个元基因组中的微生物和病毒平均基因组长度进行了荟萃分析,以确定生物群落之间和之内以及同一环境中微生物和病毒群落之间的基因组长度是否一致。生物群落之间和水生亚生物群落(海洋,高盐系统,淡水和微生物岩)之间的显着差异表明,平均基因组长度是亚生物组水平上因素驱动的环境的基本属性。来自同一环境的成对的病毒和微生物元基因组配对的行为表明,微生物和病毒的平均基因组大小彼此独立,但是指示了社区对压力源和环境条件的反应。

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