RISA : a new web-tool for Rapid Identification of SSRs and Analysis of primers

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dc.contributor.authorJungeun Kim-
dc.contributor.authorJae Pil Choi-
dc.contributor.authorR Ahmad-
dc.contributor.authorSang Keun Oh-
dc.contributor.authorSuk Yoon Kwon-
dc.contributor.authorCheol-Goo Hur-
dc.date.accessioned2017-04-19T09:36:40Z-
dc.date.available2017-04-19T09:36:40Z-
dc.date.issued2012-
dc.identifier.issn1976-9571-
dc.identifier.uri10.1007/s13258-012-0032-xko
dc.identifier.urihttps://oak.kribb.re.kr/handle/201005/11164-
dc.description.abstractThe simple sequence repeats (SSRs) are short tandem arrayed sequence motifs consisting of 2-6 bp, which are not only involved in causing human fatal diseases but also have various applications in plant genetic studies. Thanks to the advancements made in sequencing technology, now we can easily generate genomic/transcriptomic sequences in a shorter period of time. Therefore, trend to identify SSR markers needs up gradation to handle these high-throughput data. Unfortunately, existing web programs for identifying SSR markers are useful but they are unable to process high-throughput data. To overcome this disadvantage, we have constructed a web-based tool, RISA (htttp://sol.kribb.re.kr/RISA/), with a goal of one-click service to identify SSR markers from high-throughput data (up to 200 Mbp). RISA controls automatic input and output pipeline by demon which combines the SSR classification and investigation by Robert Kofler (SciRoKo) to search SSRs and Primer3 to identify primers specific to SSRs simultaneously. In our test, 45,495 qualified primer sets specific to 47,070 SSRs were identified by RISA from whole Arabidopsis lyrata genome (about 207 Mbp) in 15 minutes. In results, it includes SSR statistics generated from user’s queries and SSR markers information along with primers suitable for their amplification. To support handling of large amount of results, RISA provides various filtering options such as motif length, repeat units, total length and PCR product size. Therefore, we propose that RISA minimizes labour-intensive works or any other considerations which can be required during the development of SSR markers without having deep understanding of computer system and/or algorithms.-
dc.publisherSpringer-
dc.titleRISA : a new web-tool for Rapid Identification of SSRs and Analysis of primers-
dc.title.alternativeRISA : a new web-tool for Rapid Identification of SSRs and Analysis of primers-
dc.typeArticle-
dc.citation.titleGenes & Genomics-
dc.citation.number6-
dc.citation.endPage590-
dc.citation.startPage583-
dc.citation.volume34-
dc.contributor.affiliatedAuthorJungeun Kim-
dc.contributor.affiliatedAuthorJae Pil Choi-
dc.contributor.affiliatedAuthorSuk Yoon Kwon-
dc.contributor.affiliatedAuthorCheol-Goo Hur-
dc.contributor.alternativeName김정은-
dc.contributor.alternativeName최재필-
dc.contributor.alternativeNameAhmad-
dc.contributor.alternativeName오상근-
dc.contributor.alternativeName권석윤-
dc.contributor.alternativeName허철구-
dc.identifier.bibliographicCitationGenes & Genomics, vol. 34, no. 6, pp. 583-590-
dc.identifier.doi10.1007/s13258-012-0032-x-
dc.subject.keywordHigh-throughput analysis-
dc.subject.keywordMolecular marker-
dc.subject.keywordSci- RoKo-
dc.subject.keywordSimple sequence repeat (SSR)-
dc.subject.keywordPrimer3-
dc.subject.localHigh-throughput analysis-
dc.subject.localMolecular markers-
dc.subject.localmolecular marker-
dc.subject.localMolecular marker-
dc.subject.localSci- RoKo-
dc.subject.localSimple sequence repeat-
dc.subject.localSimple Sequence Repeat (SSR)-
dc.subject.localSimple sequence repeat (SSR)-
dc.subject.localsimple sequence repeat-
dc.subject.localsimple sequence repeats-
dc.subject.localSimple sequence repeats-
dc.subject.localPrimer3-
dc.description.journalClassY-
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