Revolutionizing Molecular cloning: Introducing FastCloneAssist, a Streamlined Python tool for optimizing primer design in restriction & ligation-independent PCR cloning
FastCloning, a paradigm shift in PCR cloning, has streamlined the process by eliminating laborious, multi-step traditional methods. This innovative technique, pioneered by Li et al. (2011), utilizes overlapping PCR primers and DpnI digestion for seamless integration of insert DNA into any desired ve...
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| Vydané v: | PloS one Ročník 20; číslo 3; s. e0306950 |
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| Hlavní autori: | , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
United States
Public Library of Science
13.03.2025
Public Library of Science (PLoS) |
| Predmet: | |
| ISSN: | 1932-6203, 1932-6203 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | FastCloning, a paradigm shift in PCR cloning, has streamlined the process by eliminating laborious, multi-step traditional methods. This innovative technique, pioneered by Li et al. (2011), utilizes overlapping PCR primers and DpnI digestion for seamless integration of insert DNA into any desired vector position, regardless of restriction sites. This versatility makes FastCloning ideal for constructing fusion proteins, chimeric cDNAs, and manipulating genes with unparalleled ease.
However, efficient primer design remains a critical hurdle, particularly for newcomers, as errors can lead to failed cloning attempts. To address this bottleneck, we present FastCloneAssist, a user-friendly Python program that automates FastCloning primer design with minimal user input. Users simply provide vector and insert sequences, along with the desired melting temperature (Tm), and FastCloneAssist provides best primer pairs after calculating optimal primer parameters for efficient PCR amplification and seamless DNA integration using established bioinformatics libraries. This open-source, freely available tool simplifies and accelerates cloning, making this powerful technique accessible to researchers of all levels and expediting scientific discovery. |
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| Bibliografia: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Competing Interests: NO authors have competing interests. |
| ISSN: | 1932-6203 1932-6203 |
| DOI: | 10.1371/journal.pone.0306950 |