Joo-Seok Park, Yoram Choi, Jin-Hyun Kim, Chaeyoung Lee, Min-Gyun Jeong, Yeong-Il Jeong, Yang Jae Kang, Young-Soo Chung, Hong-Kyu Choi
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To design molecular markers encompassing a vast number of genetic variants at the genome-wide scale in soybean, an automatic system capable of handling NGS-based big data is necessary.</p><p><strong>Results: </strong>In this study, we developed a robust digital platform, the CAPS Maker, for designing cleaved amplified polymorphic sequence (CAPS)/derived CAPS (dCAPS) markers in soybeans. This platform simplifies the systematic design of genomic markers with a user-friendly graphical interface, featuring a 'SNP Browser' and 'Primer Table', along with internal programs (e.g., the eHT-PCR module) to design unique primer pairs for highly duplicated genomes like soybean.</p><p><strong>Conclusions: </strong>The CAPS Maker's efficiency and reliability were experimentally verified by comparing its marker predictions with actual experimental results. Consequently, breeders can easily design CAPS/dCAPS markers using the CAPS Maker platform to develop new soybean cultivars with beneficial agronomic traits. This platform is freely accessible at https://tgil.donga.ac.kr/CAPSMaker .</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"192"},"PeriodicalIF":4.7000,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11669248/pdf/","citationCount":"0","resultStr":"{\"title\":\"Development of a web-based high-throughput marker design program: CAPS (cleaved amplified polymorphic sequence) Maker.\",\"authors\":\"Joo-Seok Park, Yoram Choi, Jin-Hyun Kim, Chaeyoung Lee, Min-Gyun Jeong, Yeong-Il Jeong, Yang Jae Kang, Young-Soo Chung, Hong-Kyu Choi\",\"doi\":\"10.1186/s13007-024-01319-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Genetic markers are crucial for breeding crops with desired agronomic traits, and their development can be expedited using next-generation sequencing (NGS) and bioinformatics tools. Numerous tools have been developed to design molecular markers, enhancing the convenience, accuracy, and efficiency of molecular breeding. However, these tools primarily focus on genetic variants within short user-input sequences, despite the availability of extensive omics data for genomic variants. To design molecular markers encompassing a vast number of genetic variants at the genome-wide scale in soybean, an automatic system capable of handling NGS-based big data is necessary.</p><p><strong>Results: </strong>In this study, we developed a robust digital platform, the CAPS Maker, for designing cleaved amplified polymorphic sequence (CAPS)/derived CAPS (dCAPS) markers in soybeans. This platform simplifies the systematic design of genomic markers with a user-friendly graphical interface, featuring a 'SNP Browser' and 'Primer Table', along with internal programs (e.g., the eHT-PCR module) to design unique primer pairs for highly duplicated genomes like soybean.</p><p><strong>Conclusions: </strong>The CAPS Maker's efficiency and reliability were experimentally verified by comparing its marker predictions with actual experimental results. Consequently, breeders can easily design CAPS/dCAPS markers using the CAPS Maker platform to develop new soybean cultivars with beneficial agronomic traits. 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Development of a web-based high-throughput marker design program: CAPS (cleaved amplified polymorphic sequence) Maker.
Background: Genetic markers are crucial for breeding crops with desired agronomic traits, and their development can be expedited using next-generation sequencing (NGS) and bioinformatics tools. Numerous tools have been developed to design molecular markers, enhancing the convenience, accuracy, and efficiency of molecular breeding. However, these tools primarily focus on genetic variants within short user-input sequences, despite the availability of extensive omics data for genomic variants. To design molecular markers encompassing a vast number of genetic variants at the genome-wide scale in soybean, an automatic system capable of handling NGS-based big data is necessary.
Results: In this study, we developed a robust digital platform, the CAPS Maker, for designing cleaved amplified polymorphic sequence (CAPS)/derived CAPS (dCAPS) markers in soybeans. This platform simplifies the systematic design of genomic markers with a user-friendly graphical interface, featuring a 'SNP Browser' and 'Primer Table', along with internal programs (e.g., the eHT-PCR module) to design unique primer pairs for highly duplicated genomes like soybean.
Conclusions: The CAPS Maker's efficiency and reliability were experimentally verified by comparing its marker predictions with actual experimental results. Consequently, breeders can easily design CAPS/dCAPS markers using the CAPS Maker platform to develop new soybean cultivars with beneficial agronomic traits. This platform is freely accessible at https://tgil.donga.ac.kr/CAPSMaker .
期刊介绍:
Plant Methods is an open access, peer-reviewed, online journal for the plant research community that encompasses all aspects of technological innovation in the plant sciences.
There is no doubt that we have entered an exciting new era in plant biology. The completion of the Arabidopsis genome sequence, and the rapid progress being made in other plant genomics projects are providing unparalleled opportunities for progress in all areas of plant science. Nevertheless, enormous challenges lie ahead if we are to understand the function of every gene in the genome, and how the individual parts work together to make the whole organism. Achieving these goals will require an unprecedented collaborative effort, combining high-throughput, system-wide technologies with more focused approaches that integrate traditional disciplines such as cell biology, biochemistry and molecular genetics.
Technological innovation is probably the most important catalyst for progress in any scientific discipline. Plant Methods’ goal is to stimulate the development and adoption of new and improved techniques and research tools and, where appropriate, to promote consistency of methodologies for better integration of data from different laboratories.