Autor: |
Nishimura, Kazusa, Okuma, Maho, Kaneyoshi, Junko, Yamasaki, Atsu, Nagasaka, Kyoka, Murata, Kazuki, Monden, Yuki, Kato, Kenji, Nishida, Hidetaka, Nakazaki, Tetsuya, Nakano, Ryohei |
Předmět: |
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Zdroj: |
Tree Genetics & Genomes; Oct2024, Vol. 20 Issue 5, p1-12, 12p |
Abstrakt: |
Given the ease of propagating fruit tree species through cloning, the economic viability of their breeding programs hinges on protecting breeders' rights. This necessitates the development of highly accurate DNA markers for cultivar identification. Here, we present a methodology for the rapid design of cleaved amplified polymorphic sequence (CAPS) markers to discriminate newly bred Japanese citrus cultivars from genetically related cultivars. We first compared the performance of ddRAD-seq and MIG-seq in citrus germplasm. The ddRAD-seq libraries generated using EcoRI and HindIII restriction enzymes yielded the highest number of polymorphisms. Subsequently, ddRAD-seq with EcoRI and HindIII was employed to analyze 29 citrus cultivars and thus identify 331,801 genome-wide polymorphisms. A semi-automated bioinformatics pipeline was then utilized to identify candidate CAPS markers, resulting in the discovery of 14,072 potential markers. Of these candidates, 52 were chosen for validation based on their recognition by the PstI restriction enzyme. This evaluation resulted in the development of 11 highly discriminative CAPS markers. Remarkably, a combination of only six such markers was sufficient to differentiate newly bred cultivars from their genetically related parents. The single restriction enzyme employed for these markers facilitates straightforward multiplexing. Finally, a combination of one multiplex marker testing two loci and four singleplex markers was successfully selected that completely discriminated the cultivars other than the bud sports used in this study. The pipeline established here extends beyond citrus and has the potential to simplify marker development and cultivar protection in various plant species. [ABSTRACT FROM AUTHOR] |
Databáze: |
Complementary Index |
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