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PhylArray:用于微阵列的系统发育探针设计算法

PhylArray: phylogenetic probe design algorithm for microarray.

作者信息

Militon Cécile, Rimour Sébastien, Missaoui Mohieddine, Biderre Corinne, Barra Vincent, Hill David, Moné Anne, Gagne Geneviève, Meier Harald, Peyretaillade Eric, Peyret Pierre

机构信息

Génomique Intégrée des Interactions Microbiennes, Laboratoire de Biologie des Protistes, UMR CNRS 6023, Blaise Pascal University, 24 avenue des Landais, Campus des Cézeaux, France.

出版信息

Bioinformatics. 2007 Oct 1;23(19):2550-7. doi: 10.1093/bioinformatics/btm392. Epub 2007 Aug 12.

Abstract

MOTIVATION

Microbial diversity is still largely unknown in most environments, such as soils. In order to get access to this microbial 'black-box', the development of powerful tools such as microarrays are necessary. However, the reliability of this approach relies on probe efficiency, in particular sensitivity, specificity and explorative power, in order to obtain an image of the microbial communities that is close to reality.

RESULTS

We propose a new probe design algorithm that is able to select microarray probes targeting SSU rRNA at any phylogenetic level. This original approach, implemented in a program called 'PhylArray', designs a combination of degenerate and non-degenerate probes for each target taxon. Comparative experimental evaluations indicate that probes designed with PhylArray yield a higher sensitivity and specificity than those designed by conventional approaches. Applying the combined PhyArray/GoArrays strategy helps to optimize the hybridization performance of short probes. Finally, hybridizations with environmental targets have shown that the use of the PhylArray strategy can draw attention to even previously unknown bacteria.

摘要

动机

在大多数环境中,如土壤,微生物多样性在很大程度上仍不为人知。为了探究这个微生物“黑匣子”,开发强大的工具如微阵列是必要的。然而,这种方法的可靠性依赖于探针效率,特别是灵敏度、特异性和探索能力,以便获得接近真实情况的微生物群落图像。

结果

我们提出了一种新的探针设计算法,该算法能够在任何系统发育水平上选择靶向小亚基核糖体RNA(SSU rRNA)的微阵列探针。这种原始方法在一个名为“PhylArray”的程序中实现,为每个目标分类群设计简并和非简并探针的组合。比较实验评估表明,用PhylArray设计的探针比传统方法设计的探针具有更高的灵敏度和特异性。应用PhylArray/GoArrays组合策略有助于优化短探针的杂交性能。最后,与环境目标的杂交表明,使用PhylArray策略可以关注到甚至以前未知的细菌。

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