2014Dongbei Nongye Daxue xuebaoRequires access

ISSR and SSR system optimization and application on genetic diversity analyzing of walnut

Zhai Meizh

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Abstract

In this study, ISSR and SSR molecular marker technologies were selected to analyze the genetic diversity of different walnut varieties to provide a theoretical basis for the future development of new varieties and germplasm innovation. Total 15 ISSR primers and 12 SSR primers with good repeatability and strong polymorphism were screened and the PCR optimum system was set up. ISSR molecular mark detected 187 bands, of which 132 were polymorphism bands, accounting for 70.59%, and the number of the polymorphic loci of each primer averaged 8.8. The similarity coefficient ranged from 0.2500 to 0.7639. Polymorphic information content(PIC) ranged from 0.7105 to 0.9151, and each value was greater than 0.5. SSR molecular mark detected 174 bands, of which 118 were polymorphism bands, accounting for 67.82%, and the number of the polymorphic loci of each primer averaged 9.8.The similarity coefficient ranged from 0.1594 to 0.8036. Polymorphic information content(PIC) ranged from 0.7422 to 0.8962, and each value was greater than 0.5. Mantel test was used to analyse correlation of ISSR and SSR(r=0.6257, P=1), indicated that ISSR markers and SSR markers in this study was consistent. Cluster analysis with UPGMA method showed that the samples could be divided into four groups. It showed that the genetic resources of these samples were very rich, and could be used as breeding source.

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In this study, ISSR and SSR molecular marker technologies were selected to analyze the genetic diversity of different walnut varieties to provide a theoretical basis for the future development of new varieties and germplasm innovation. Total 15 ISSR primers and 12 SSR primers with good repeatability and strong polymorphism were screened and the PCR optimum system was set up. ISSR molecular mark detected 187 bands, of which 132 were polymorphism bands, accounting for 70.59%, and the number of the polymorphic loci of each primer averaged 8.8. The similarity coefficient ranged from 0.2500 to 0.7639. Polymorphic information content(PIC) ranged from 0.7105 to 0.9151, and each value was greater than 0.5. SSR molecular mark detected 174 bands, of which 118 were polymorphism bands, accounting for 67.82%, and the number of the polymorphic loci of each primer averaged 9.8.The similarity coefficient ranged from 0.1594 to 0.8036. Polymorphic information content(PIC) ranged from 0.7422 to 0.8962, and each value was greater than 0.5. Mantel test was used to analyse correlation of ISSR and SSR(r=0.6257, P=1), indicated that ISSR markers and SSR markers in this study was consistent. Cluster analysis with UPGMA method showed that the samples could be divided into four groups. It showed that the genetic resources of these samples were very rich, and could be used as breeding source.

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Available abstract

In this study, ISSR and SSR molecular marker technologies were selected to analyze the genetic diversity of different walnut varieties to provide a theoretical basis for the future development of new varieties and germplasm innovation. Total 15 ISSR primers and 12 SSR primers with good repeatability and strong polymorphism were screened and the PCR optimum system was set up. ISSR molecular mark detected 187 bands, of which 132 were polymorphism bands, accounting for 70.59%, and the number of the polymorphic loci of each primer averaged 8.8. The similarity coefficient ranged from 0.2500 to 0.7639. Polymorphic information content(PIC) ranged from 0.7105 to 0.9151, and each value was greater than 0.5. SSR molecular mark detected 174 bands, of which 118 were polymorphism bands, accounting for 67.82%, and the number of the polymorphic loci of each primer averaged 9.8.The similarity coefficient ranged from 0.1594 to 0.8036. Polymorphic information content(PIC) ranged from 0.7422 to 0.8962, and each value was greater than 0.5. Mantel test was used to analyse correlation of ISSR and SSR(r=0.6257, P=1), indicated that ISSR markers and SSR markers in this study was consistent. Cluster analysis with UPGMA method showed that the samples could be divided into four groups. It showed that the genetic resources of these samples were very rich, and could be used as breeding source.

Key concepts: UPGMA, Genetic diversity, Germplasm, Biology, Similarity (geometry), Genetic similarity, Polymorphism (computer science), Microsatellite

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