The GAAS metagenomic tool and its estimations of viral and microbial average genome size in four major biomes.
The GAAS metagenomic tool and its estimations of viral and microbial average genome size in four major biomes.
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GAAS宏基因组工具及其对四个主要生物群体中病毒和微生物平均基因组大小的估计。
DOI：
10.1371/journal.pcbi.1000593
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发表时间：
2009-12
影响因子：
4.3
通讯作者：
Rohwer F
中科院分区：
文献类型：
--
作者：
Angly FE;Willner D;Prieto-Davó A;Edwards RA;Schmieder R;Vega-Thurber R;Antonopoulos DA;Barott K;Cottrell MT;Desnues C;Dinsdale EA;Furlan M;Haynes M;Henn MR;Hu Y;Kirchman DL;McDole T;McPherson JD;Meyer F;Miller RM;Mundt E;Naviaux RK;Rodriguez-Mueller B;Stevens R;Wegley L;Zhang L;Zhu B;Rohwer F
宏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;然而，采样偏差、未知序列的高百分比以及使用任意阈值来发现显著相似性会降低估计的准确性和有效性。在这里，我们提出了基因组相对绝对值和平均大小（GAAS），一个完整的软件包，提供了改进的估计社区组成和平均基因组长度的宏基因组在文本和图形格式。GAAS实现了一种新的方法，通过长度归一化控制采样偏差，通过相似性加权调整多个BLAST相似性，并使用相对比对长度选择显著相似性。在基准测试中，GAAS方法对高百分比的未知序列和宏基因组序列读取长度的变化都是稳健的。使用GAAS对马尾藻海病毒组的重新分析表明，宏基因组分析的标准方法可能会大大低估环境系统中小基因组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多个宏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，以确定基因组长度是否在生物群落之间和生物群落内以及来自同一环境的微生物和病毒群落之间一致地变化。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）之间的显着差异表明，平均基因组长度是由亚生物群落水平的因素驱动的环境的基本属性。来自同一环境的成对病毒和微生物宏基因组的行为表明，微生物和病毒的平均基因组大小彼此独立，但表明群落对压力源和环境条件的反应。宏基因组学使用直接从环境中分离的DNA或RNA序列来确定自然群落中存在哪些病毒或微生物以及它们编码哪些代谢活动。通常，使用BLAST搜索工具将宏基因组序列与公共数据库中的注释序列进行比较。我们的方法，在基因组相对抽象和平均大小（GAAS）软件中实现，改进了BLAST搜索的处理方式，以估计社区的分类组成及其平均基因组长度。GAAS通过纠正系统性的采样偏向较大基因组，提供了更准确的群落组成情况，并且在小基因组生物丰富的情况下非常有用，例如由小RNA病毒引起的疾病爆发。微生物平均基因组长度与环境复杂性有关，基因组长度的分布描述了群落的多样性。使用GAAS对169个宏基因组进行的四个不同生物群落中病毒和微生物的平均基因组长度的研究表明，生物群落之间的平均基因组大小存在显着差异，生物群落内部也存在很大的变异性。这也揭示了同一环境中微生物和病毒的平均基因组大小是相互独立的，这反映了微生物和病毒对压力和环境条件的不同反应方式。
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. Metagenomics uses DNA or RNA sequences isolated directly from the environment to determine what viruses or microorganisms exist in natural communities and what metabolic activities they encode. Typically, metagenomic sequences are compared to annotated sequences in public databases using the BLAST search tool. Our methods, implemented in the Genome relative Abundance and Average Size (GAAS) software, improve the way BLAST searches are processed to estimate the taxonomic composition of communities and their average genome length. GAAS provides a more accurate picture of community composition by correcting for a systematic sampling bias towards larger genomes, and is useful in situations where organisms with small genomes are abundant, such as disease outbreaks caused by small RNA viruses. Microbial average genome length relates to environmental complexity and the distribution of genome lengths describes community diversity. A study of the average genome length of viruses and microorganisms in four different biomes using GAAS on 169 metagenomes showed significantly different average genome sizes between biomes, and large variability within biomes as well. This also revealed that microbial and viral average genome sizes in the same environment are independent of each other, which reflects the different ways that microorganisms and viruses respond to stress and environmental conditions.
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影响因子：
12.3
作者：
Raes J;Korbel JO;Lercher MJ;von Mering C;Bork P
通讯作者：
Bork P
影响因子：
4.4
作者：
Holmfeldt, Karin;Middelboe, Mathias;Riemann, Lasse
通讯作者：
Riemann, Lasse
DOI：
10.1017/s0025315406013506
发表时间：
2006-06-01
影响因子：
1.2
作者：
Hewson, I;Wingett, DM;Wommack, KE
通讯作者：
Wommack, KE
影响因子：
3.2
作者：
Rohwer, F;Edwards, R
通讯作者：
Edwards, R
影响因子：
3
作者：
Meyer, F.;Paarmann, D.;Edwards, R. A.
通讯作者：
Edwards, R. A.