Deconvoluting the BAC-gene relationships using a physical map.

Yonghui Wu, Lan Liu, T. Close, S. Lonardi
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引用次数: 5

Abstract

MOTIVATION The deconvolution of the relationships between BAC clones and genes is a crucial step in the selective sequencing of the regions of interest in a genome. It usually requires combinatorial pooling of unique probes obtained from the genes (unigenes), and the screening of the BAC library using the pools in a hybridization experiment. Since several probes can hybridize to the same BAC, in order for the deconvolution to be achievable the pooling design has to be able to handle a large number of positives. As a consequence, smaller pools need to be designed which in turn increases the number of hybridization experiments possibly making the entire protocol unfeasible. RESULTS We propose a new algorithm that is capable of producing high accuracy deconvolution even in the presence of a weak pooling design, i.e., when pools are rather large. The algorithm compensates for the decrease of information in the hybridization data by taking advantage of a physical map of the BAC clones. We show that the right combination of combinatorial pooling and our algorithm not only dramatically reduces the number of pools required, but also successfully deconvolutes the BAC-gene relationships with almost perfect accuracy.
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使用物理图谱解卷积bac -基因关系。
动机BAC克隆和基因之间关系的反褶积是基因组中感兴趣区域选择性测序的关键步骤。它通常需要从基因(unigenes)中获得独特探针的组合池,并在杂交实验中使用池筛选BAC文库。由于多个探针可以杂交到相同的BAC,为了实现反卷积,池化设计必须能够处理大量的阳性。因此,需要设计更小的池,这反过来又增加了杂交实验的数量,可能使整个方案不可行。结果我们提出了一种新的算法,即使在存在弱池设计的情况下,即当池相当大时,也能够产生高精度的反褶积。该算法通过利用BAC克隆的物理图谱来补偿杂交数据中信息的减少。我们的研究表明,组合池和我们的算法的正确组合不仅大大减少了所需池的数量,而且还以几乎完美的精度成功地反卷积了bac -基因关系。
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