{"title":"Bioinformatic Analysis Strategy in Restriction Enzyme Selection for Indonesian Panulirus homarus Identification by PCR-RFLP","authors":"Indriatmoko Indriatmoko, Adi Pancoro","doi":"10.5614/j.math.fund.sci.2023.55.2.4","DOIUrl":null,"url":null,"abstract":"The spiny lobster (Panulirus homarus) is a valuable fishery commodity in Indonesia, particularly in its juvenile life form. However, identifying the early life forms of the spiny lobster can be challenging, as it exhibits similar morphological features compared to the juveniles of other Panilurid lobsters. Molecular-based identification, specifically DNA sequencing, is the best method for species identification, but it requires advanced instruments and is costly. An alternative method is proposed here, using the PCR-RFLP technique, which is low-cost, rapid, and has standard instrumentation requirements. The challenge with this method is selecting the appropriate restriction enzyme to determine the targeted species’ identity. This study proposes using the REfind (https://github.com/indriatmoko07/REfind), R package to select the best restriction enzyme for identifying P. homarus, applicable to other species. The bioinformatics workflow used in this study successfully identified BseSI or BmgI as the most suitable restriction enzymes among 739 restriction enzymes to differentiate P. homarus from other Panilurid species. This result was validated by employing a wet lab test using the BseSI enzyme and successfully validated the bioinformatics result. These findings may be useful for biologists in conducting various studies that require rapid, low-cost, and identification of specific species in the future.","PeriodicalId":16255,"journal":{"name":"Journal of Mathematical and Fundamental Sciences","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2024-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mathematical and Fundamental Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5614/j.math.fund.sci.2023.55.2.4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
The spiny lobster (Panulirus homarus) is a valuable fishery commodity in Indonesia, particularly in its juvenile life form. However, identifying the early life forms of the spiny lobster can be challenging, as it exhibits similar morphological features compared to the juveniles of other Panilurid lobsters. Molecular-based identification, specifically DNA sequencing, is the best method for species identification, but it requires advanced instruments and is costly. An alternative method is proposed here, using the PCR-RFLP technique, which is low-cost, rapid, and has standard instrumentation requirements. The challenge with this method is selecting the appropriate restriction enzyme to determine the targeted species’ identity. This study proposes using the REfind (https://github.com/indriatmoko07/REfind), R package to select the best restriction enzyme for identifying P. homarus, applicable to other species. The bioinformatics workflow used in this study successfully identified BseSI or BmgI as the most suitable restriction enzymes among 739 restriction enzymes to differentiate P. homarus from other Panilurid species. This result was validated by employing a wet lab test using the BseSI enzyme and successfully validated the bioinformatics result. These findings may be useful for biologists in conducting various studies that require rapid, low-cost, and identification of specific species in the future.
期刊介绍:
Journal of Mathematical and Fundamental Sciences welcomes full research articles in the area of Mathematics and Natural Sciences from the following subject areas: Astronomy, Chemistry, Earth Sciences (Geodesy, Geology, Geophysics, Oceanography, Meteorology), Life Sciences (Agriculture, Biochemistry, Biology, Health Sciences, Medical Sciences, Pharmacy), Mathematics, Physics, and Statistics. New submissions of mathematics articles starting in January 2020 are required to focus on applied mathematics with real relevance to the field of natural sciences. Authors are invited to submit articles that have not been published previously and are not under consideration elsewhere.