Hu Jialu, Zheng Yan, Shang Xuequn
School of Computer Science, Northwestern Polytechnical University, West Youyi Road 127, Xi'an, 710072, China.
Centre of Multidisciplinary Convergence Computing, School of Computer Science, Northwestern Polytechnical University, Dong Xiang Road 1, Xi'an, 710129, China.
BMC Med Genomics. 2018 Nov 20;11(Suppl 5):101. doi: 10.1186/s12920-018-0418-y.
Miniature inverted-repeat transposable element (MITE) is a type of class II non-autonomous transposable element playing a crucial role in the process of evolution in biology. There is an urgent need to develop bioinformatics tools to effectively identify MITEs on a whole genome-wide scale. However, most of currently existing tools suffer from low ability to deal with large eukaryotic genomes.
In this paper, we proposed a novel tool MiteFinderII, which was adapted from our previous algorithm MiteFinder, to efficiently detect MITEs from genomics sequences. It has six major steps: (1) build K-mer Index and search for inverted repeats; (2) filtration of inverted repeats with low complexity; (3) merger of inverted repeats; (4) filtration of candidates with low score; (5) selection of final MITE sequences; (6) selection of representative sequences.
To test the performance, MiteFinderII and three other existing algorithms were applied to identify MITEs on the whole genome of oryza sativa. Results suggest that MiteFinderII outperforms existing popular tools in terms of both specificity and recall. Additionally, it is much faster and more memory-efficient than other tools in the detection.
MiteFinderII is an accurate and effective tool to detect MITEs hidden in eukaryotic genomes. The source code is freely accessible at the website: https://github.com/screamer/miteFinder .
微型反向重复转座元件（MITE）是一类II类非自主转座元件，在生物进化过程中起着关键作用。迫切需要开发生物信息学工具以在全基因组范围内有效地识别MITE。然而，目前大多数现有工具处理大型真核基因组的能力较低。
在本文中，我们提出了一种新型工具MiteFinderII，它改编自我们之前的算法MiteFinder，用于从基因组序列中高效检测MITE。它有六个主要步骤：（1）构建K-mer索引并搜索反向重复序列；（2）过滤低复杂度的反向重复序列；（3）合并反向重复序列；（4）过滤低分候选序列；（5）选择最终的MITE序列；（6）选择代表性序列。
为了测试性能，将MiteFinderII和其他三种现有算法应用于水稻全基因组中MITE的识别。结果表明，MiteFinderII在特异性和召回率方面均优于现有的流行工具。此外，在检测中它比其他工具更快且内存效率更高。
MiteFinderII是一种准确有效的工具，可用于检测隐藏在真核基因组中的MITE。其源代码可在网站https://github.com/screamer/miteFinder上免费获取。
