期刊
GENES
卷 14, 期 8, 页码 -出版社
MDPI
DOI: 10.3390/genes14081594
关键词
Diplotaxis spp.; plastid markers; nuclear markers; DNA sequencing; structure analysis; high resolution melting; phylogenesis
In this study, the genetic diversity of 17 Diplotaxis species was investigated using 5 DNA barcode markers, which revealed their taxonomic relationships. The combination of real-time PCR and high-resolution melting analysis proved effective in resolving taxonomic relationships and species identification. The findings demonstrate the effectiveness of this approach for taxonomic and genetic diversity studies.
Nuclear and cytoplasmic DNA barcoding regions are useful for plant identification, breeding, and phylogenesis. In this study, the genetic diversity of 17 Diplotaxis species, was investigated with 5 barcode markers. The allelic variation was based on the sequences of chloroplast DNA markers including the spacer between trnL and trnF and tRNA-Phe gene (trnL-F), the rubisco (rbcl), the maturase K (matk), as well as the internal transcribed spacer (ITS) region of the nuclear ribosomal DNA. A highly polymorphic marker (HRM500) derived from a comparison of cytoplasmic genome sequences in Brassicaceae, was also included. Subsequently, a real-time PCR method coupled with HRM analysis was implemented to better resolve taxonomic relationships and identify assays suitable for species identification. Integration of the five barcode regions revealed a grouping of the species according to the common chromosomal set number. Clusters including species with n = 11 (D. duveryrieriana or cretacea, D. tenuifolia, D. simplex and D. acris), n = 8 (D. ibicensis, D. brevisiliqua and D. ilorcitana), and n = 9 (D. brachycarpa, D. virgata, D. assurgens, and D. berthautii) chromosomes were identified. Both phylogenetic analysis and the genetic structure of the collection identified D. siifolia as the most distant species. Previous studies emphasized this species' extremely high glucosinolate content, particularly for glucobrassicin. High-resolution melting analysis showed specific curve patterns useful for the discrimination of the species, thus determining ITS1 as the best barcode for fingerprinting. Findings demonstrate that the approach used in this study is effective for taxa investigations and genetic diversity studies.
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