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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)
- Source :
- Ecological Informatics. 29:214-220
- Publication Year :
- 2015
- Publisher :
- Elsevier BV, 2015.
-
Abstract
- 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.
- Subjects :
- Genetics
Ecology
Applied Mathematics
Ecological Modeling
Sorting
Computational biology
Biology
DNA barcoding
DNA sequencing
Computer Science Applications
chemistry.chemical_compound
genomic DNA
Computational Theory and Mathematics
chemistry
Modeling and Simulation
Binary data
Primer (molecular biology)
Gene
Ecology, Evolution, Behavior and Systematics
DNA
Subjects
Details
- ISSN :
- 15749541
- Volume :
- 29
- Database :
- OpenAIRE
- Journal :
- Ecological Informatics
- Accession number :
- edsair.doi...........3f3dc960c2a51d1f9e485b1986f00534