Suppr超能文献

detectMITE:一种在基因组中检测微型反向重复转座元件的新方法。

detectMITE: A novel approach to detect miniature inverted repeat transposable elements in genomes.

作者信息

Ye Congting, Ji Guoli, Liang Chun

机构信息

Department of Automation, Xiamen University, Xiamen, Fujian 361005, China.

Department of Biology, Miami University, Oxford, Ohio 45056, USA.

出版信息

Sci Rep. 2016 Jan 22;6:19688. doi: 10.1038/srep19688.

Abstract

Miniature inverted repeat transposable elements (MITEs) are prevalent in eukaryotic genomes, including plants and animals. Classified as a type of non-autonomous DNA transposable elements, they play important roles in genome organization and evolution. Comprehensive and accurate genome-wide detection of MITEs in various eukaryotic genomes can improve our understanding of their origins, transposition processes, regulatory mechanisms, and biological relevance with regard to gene structures, expression, and regulation. In this paper, we present a new MATLAB-based program called detectMITE that employs a novel numeric calculation algorithm to replace conventional string matching algorithms in MITE detection, adopts the Lempel-Ziv complexity algorithm to filter out MITE candidates with low complexity, and utilizes the powerful clustering program CD-HIT to cluster similar MITEs into MITE families. Using the rice genome as test data, we found that detectMITE can more accurately, comprehensively, and efficiently detect MITEs on a genome-wide scale than other popular MITE detection tools. Through comparison with the potential MITEs annotated in Repbase, the widely used eukaryotic repeat database, detectMITE has been shown to find known and novel MITEs with a complete structure and full-length copies in the genome. detectMITE is an open source tool (https://sourceforge.net/projects/detectmite).

摘要

微型反向重复转座元件(MITEs)在包括植物和动物在内的真核生物基因组中普遍存在。它们被归类为一类非自主DNA转座元件,在基因组组织和进化中发挥着重要作用。全面、准确地在各种真核生物基因组中进行全基因组范围的MITEs检测,能够增进我们对其起源、转座过程、调控机制以及与基因结构、表达和调控的生物学相关性的理解。在本文中,我们展示了一个基于MATLAB的名为detectMITE的新程序,该程序采用一种新颖的数值计算算法来替代MITE检测中的传统字符串匹配算法,采用莱姆尔 - 齐夫复杂度算法来过滤掉复杂度低的MITE候选序列,并利用强大的聚类程序CD-HIT将相似的MITEs聚类为MITE家族。以水稻基因组作为测试数据,我们发现detectMITE在全基因组范围内比其他流行的MITE检测工具能更准确、全面且高效地检测MITEs。通过与广泛使用的真核生物重复序列数据库Repbase中注释的潜在MITEs进行比较,detectMITE已被证明能够在基因组中找到具有完整结构和全长拷贝的已知和新型MITEs。detectMITE是一个开源工具(https://sourceforge.net/projects/detectmite)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af21/4726161/975eb82c5a25/srep19688-f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验