Conserved orthology in mitochondrial genomes of distantly related nematodes

Q2 Medicine

In Silico Biology Pub Date : 2010-02-15 DOI:10.1145/1722024.1722075

P. Nima, A. Riju, N. Reena, S. Eapen

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引用次数: 0

Abstract

Identification of orthologous segments plays a very important role in comparative genomics studies. In the present study, we have identified orthologous segments shared between Radopholus similis and 15 other nematodes. Complete genomes of 16 nematodes were used for the study. OSfinder was used to find the orthologous segments shared between R. similis and other 15 nematodes. Orthologous segments were visualized with the help of GTK powered Murasaki Visualizer (GMV) programme. Extremely AT rich genome of the burrowing nematode R. similis, which has the largest mitochondrial genome, was found to have orthologous segments from start position, 4 to end position 16791 with 15 nematodes. Brugia malayi, Dirofilaria immitis, Onchocerca volvulus, and Xiphinema americanum share similar orthologous segment with that of R. similis. The mitochondrial genome analysis revealed the presence of conserved gene locations in mitochondrion and the close evolutionary relationship of nematodes belonging to different clades and different parasitic habitats. This study has many practical implications like reconstruction of ancestral genome of nematode and calculation of evolutionary time.

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远亲线虫线粒体基因组的保守同源性

同源片段的鉴定在比较基因组学研究中起着非常重要的作用。在本研究中，我们鉴定了相似Radopholus与其他15种线虫共有的同源片段。本研究使用了16种线虫的全基因组。利用OSfinder查找相似圆线虫与其他15种线虫共有的同源片段。在GTK驱动的Murasaki Visualizer (GMV)程序的帮助下对同源片段进行可视化。在线粒体基因组最大的穴居线虫R. similis基因组中，发现15个线虫从起始位置4到结束位置16791都有同源片段。马来布鲁氏菌、免疫dirofilia immitis、盘尾丝虫和美洲Xiphinema americanum与相似的r.s similis有相似的同源节段。线粒体基因组分析揭示了线虫线粒体中存在保守的基因位点，揭示了线虫属于不同支系和不同寄生生境的密切进化关系。该研究对线虫祖先基因组的重建和进化时间的计算具有重要的现实意义。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

In Silico Biology Computer Science-Computational Theory and Mathematics

CiteScore

2.20

自引率

0.00%

发文量

期刊介绍： The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.