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MITE Tracker: an accurate approach to identify miniature inverted-repeat transposable elements in large genomes

机译:MITE Tracker:一种识别大型基因组中微型反向重复转座因子的准确方法

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Miniature inverted-repeat transposable elements (MITEs) are short, non-autonomous class II transposable elements present in a high number of conserved copies in eukaryote genomes. An accurate identification of these elements can help to shed light on the mechanisms controlling genome evolution and gene regulation. The structure and distribution of these elements are well-defined and therefore computational approaches can be used to identify MITEs sequences. Here we describe MITE Tracker, a novel, open source software program that finds and classifies MITEs using an efficient alignment strategy to retrieve nearby inverted-repeat sequences from large genomes. This program groups them into high sequence homology families using a fast clustering algorithm and finally filters only those elements that were likely transposed from different genomic locations because of their low scoring flanking sequence alignment. Many programs have been proposed to find MITEs hidden in genomes. However, none of them are able to process large-scale genomes such as that of bread wheat. Furthermore, in many cases the existing methods perform high false-positive rates (or miss rates). The rice genome was used as reference to compare MITE Tracker against known tools. Our method turned out to be the most reliable in our tests. Indeed, it revealed more known elements, presented the lowest false-positive number and was the only program able to run with the bread wheat genome as input. In wheat, MITE Tracker discovered 6013 MITE families and allowed the first structural exploration of MITEs in the complete bread wheat genome.
机译:微型反向重复转座因子(MITE)是短的,非自治的II类转座因子,存在于真核生物基因组中的大量保守拷贝中。对这些元素的准确识别有助于阐明控制基因组进化和基因调控的机制。这些元素的结构和分布是明确定义的,因此可以使用计算方法来识别MITE序列。在这里,我们介绍MITE Tracker,这是一种新颖的开源软件程序,它使用有效的比对策略从大型基因组中检索附近的反向重复序列,从而对MITE进行查找和分类。该程序使用快速聚类算法将它们分为高序列同源性家族,最后仅过滤因其低得分侧翼序列比对而可能从不同基因组位置转座的那些元素。已经提出了许多程序来寻找隐藏在基因组中的MITE。但是,它们都不能处理大规模基因组,例如面包小麦的基因组。此外,在许多情况下,现有方法执行较高的假阳性率(或遗漏率)。水稻基因组被用作比较MITE Tracker与已知工具的参考。在我们的测试中,我们的方法被证明是最可靠的。实际上,它揭示了更多已知的元素,呈现出最低的假阳性数,并且是唯一能够将面包小麦基因组作为输入运行的程序。在小麦中,MITE Tracker发现了6013个MITE家族,并允许在整个面包小麦基因组中进行MITE的首次结构探索。

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