Single Nucleotide Polymorphisms Caused by Assembly Errors.

Genomics insights Pub Date : 2010-02-04 eCollection Date: 2010-01-01 DOI:10.4137/GEI.S3653
Jürgen Kleffe, Robert Weißmann, Florian F Schmitzberger
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Abstract

We compare the results of three different assembler programs, Celera, Phrap and Mira2, for the same set of about a hundred thousand Sanger reads derived from an unknown bacterial genome. In difference to previous assembly comparisons we do not focus on speed of computation and numbers of assembled contigs but on how the different sequence assemblies agree by content. Threefold consistently assembled genome regions are identified in order to estimate a lower bound of erroneously identified single nucleotide polymorphisms (SNP) caused by nothing but the process of mathematical sequence assembly. We identified 509 sequence triplets common to all three de-novo assemblies spanning only 34% (3.3 Mb) of the bacterial genome with 175 of these regions (~1.5 Mb) including erroneous SNPs and insertion/deletions. Within these triplets this on average leads to one error per 7,155 base pairs. Replacing the assembler Mira2 by the most recent version Mira3, the letter number even drops to 5,923. Our results therefore suggest that a considerably high number of erroneous SNPs may be present in current sequence data and mathematicians should urgently take up research on numerical stability of sequence assembly algorithms. Furthermore, even the latest versions of currently used assemblers produce erroneous SNPs that depend on the order reads are used as input. Such errors will severely hamper molecular diagnostics as well as relating genome variation and disease. This issue needs to be addressed urgently as the field is moving fast into clinical applications.

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组装错误引起的单核苷酸多态性。
我们比较了Celera、Phrap和Mira2三种不同的汇编程序的结果,这些程序来自于一种未知的细菌基因组,它们有大约10万个Sanger reads。与之前的组装比较不同,我们不关注计算速度和组装组群的数量,而是关注不同序列组装如何根据内容达成一致。鉴定了三倍一致组装的基因组区域,以估计由数学序列组装过程引起的错误鉴定的单核苷酸多态性(SNP)的下限。我们鉴定了509个序列三胞胎,这些三胞胎仅占细菌基因组的34% (3.3 Mb),其中175个区域(约1.5 Mb)包括错误的snp和插入/缺失。在这些三胞胎中,平均每7155个碱基对产生一个错误。用最新版本的Mira3取代组装器Mira2,字母数字甚至下降到5923。因此,我们的研究结果表明,在当前的序列数据中可能存在相当多的错误snp,数学家们迫切需要对序列组装算法的数值稳定性进行研究。此外,即使是当前使用的汇编程序的最新版本也会产生错误的snp,这取决于读取作为输入的顺序。这种错误将严重妨碍分子诊断以及将基因组变异和疾病联系起来。随着该领域快速进入临床应用,这一问题亟待解决。
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