首页> 外文期刊>Ecological informatics: an international journal on ecoinformatics and computational ecology >Search of optimal locations for species- or group-specific primer design in DNA sequences: Non-dominated Sorting Genetic Algorithm II (NSGA-II)
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Search of optimal locations for species- or group-specific primer design in DNA sequences: Non-dominated Sorting Genetic Algorithm II (NSGA-II)

机译:在DNA序列中寻找物种或群体特异性引物设计的最佳位置:非支配排序遗传算法II(NSGA-II)

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In this study, we applied Non-dominated Sorting Genetic Algorithm II (NSGA-II) to the problem of identifying appropriate locations in cytochrome oxidase I (COI) gene for species- or group-specific primer design. As concerns about ecological management grow, quantification of predator-prey interaction has become a central issue in ecology. Recently, improved techniques have allowed for the extensive use of genomic DNA barcoding for qualitative analysis. However, quantification of DNA barcoding results is important and still needs to be resolved. Even though species- or group-specific primers that can be used for samples containing multiple species are difficult to design, species- or group-specific primers are a practical solution for quantification in the current era. To resolve this issue, we present here an efficient method for discovering the regions of a DNA sequence that have the highest inter-species variability by applying the NSGA-II algorithm. DNA sequence information for the COI gene region was obtained for 24 species from Jo et al. (2014). These sequences were transformed into binary data, either 0 (not different) or 1 (different), to reflect sequence conservation at each base for all combinations of two species. These data were analyzed by two objective functions, the average and standard deviation of the difference, which were used in the NSGA-II algorithm to search for appropriate DNA locations for species-specific primer design. The NSGA-II program identified four solutions (possible primer binding sites); consequently NSGA-II is believed to be a suitable algorithm for species-specific primer design, and is expected to make this difficult and time-consuming process more efficient. (C) 2014 Elsevier B.V. All rights reserved.
机译:在这项研究中,我们将非主导排序遗传算法II(NSGA-II)应用于为特定物种或特定群体引物设计识别细胞色素氧化酶I(COI)基因中适当位置的问题。随着对生态管理的关注日益增加,捕食者与猎物之间相互作用的量化已成为生态学中的中心问题。近来,改进的技术允许基因组DNA条形码的广泛使用以进行定性分析。但是,DNA条形码结果的量化很重要,仍然需要解决。尽管难以设计可用于包含多个物种的样品的特定物种或特定群体引物,但特定物种或特定群体的引物是当前时代定量化的实用解决方案。为了解决这个问题,我们在这里提出一种有效的方法,通过应用NSGA-II算法来发现具有最高种间变异性的DNA序列区域。从Jo等人获得了24种COI基因区域的DNA序列信息。 (2014)。这些序列被转换为二进制数据,0(无差异)或1(不同),以反映两种物种所有组合在每个碱基处的序列保守性。这些数据通过两个目标函数进行了分析,分别是差异的平均值和标准偏差,这些函数用于NSGA-II算法中,以搜索用于物种特异性引物设计的合适DNA位置。 NSGA-II程序确定了四个解决方案(可能的引物结合位点)。因此,NSGA-II被认为是用于物种特异性引物设计的合适算法,并有望使这一困难且耗时的过程更加有效。 (C)2014 Elsevier B.V.保留所有权利。

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