Abstract

The genusPopulus L. (Salicaceae) can be divided into 5 sections with distribution throughout the world. Accurate identification ofPopulus clones and species is essential for effective selection, breeding, and management of genetic resources. In this study, amplified fragment length polymorphism (AFLP) analysis, which was reported as a reliable technique with high efficiency in detecting polymorphism, was used to conduct analyses of genetic diversity and variety identification of 44 species, clones, and cultivars ofPopulus that represent a wide range of breeding and commercially available germplasms. Cluster analysis of the 44 samples was carried out, and a dendrogram of genetic relatedness was developed on the basis of the AFLP data. DNA fingerprints of the 44 samples were developed from 12 selected bands amplified with 2 primer combinations (M-CAG/E-TA and M-CAG/E-TC). Each sample has its unique fingerprint pattern and can be distinguished from the others. Furthermore, 1 specific AFLP band of the cultivarPopulus canadensis cl. Guariento coming from fragments amplified by primer combination M-CTC/E-AG was successfully converted into a sequence-characterized amplified region (SCAR) marker. The results indicate that AFLP analysis should be considered as the preferred technique for the study of polymorphism inPopulus. This research is the first report concerning the use of AFLP analysis in genetic diversity and germplasm identification among all sections ofPopulus.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.