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Gesunde Pflanzen

, Volume 71, Issue 1, pp 1–7 | Cite as

Genetic Diversity Analysis of Brassica Species Using PCR-Based SSR Markers

  • Ali RazaEmail author
  • Sundas Saher Mehmood
  • Farwa Ashraf
  • Rao Sohail Ahmad Khan
Original Article
  • 38 Downloads

Abstract

Genetic diversity is an important measure for the improvement of many crop species including Brassica. This study evaluated the genetic divergence among six Brassica species using simple sequence repeats (SSR). Ten SSR markers produced overall 21 alleles with an average of 2.1 alleles per primer. Out of 21, 18 alleles showed polymorphism (85.71%) and 3 alleles showed monomorphism (14.28%). A similarity matrix was constructed using Popgen32 software. Genetic identity ranged from 33.33 to 76.19%. B. nigra and B. campestris showed the highest identity, while the lowest identity was observed between B. campestris and B. oleracea. Sizes of amplified alleles were ranged from 70 to 290 bp. Polymorphic information content (PIC) varied from 0.37 to 0.71, with an average of 0.66 per primer. A dendrogram classified the genotypes into two main clusters. Cluster-A is further divided into cluster-C, which consists of B. carinata and B. oleracea. B. napus and B. juncea each form an independent cluster. Cluster-B consists of B. nigra and B. campestris, meaning that these two species are closely related to each other. The results indicated that these species can be isolated from each other at the molecular level by using molecular markers.

Keywords

Alleles Dendrogram Gel electrophoresis Molecular markers Polymorphic information content 

Genetische Diversitätsanalyse von Brassica-Arten unter Verwendung von PCR-basierten SSR-Markern

Zusammenfassung

Die genetische Diversität ist ein wichtiges Maß für die Verbesserung vieler Kulturpflanzen einschließlich Brassica. In der vorliegenden Studie wurde die genetische Divergenz zwischen 6 Brassica-Arten unter der Verwendung von Mikrosatelliten („simple sequence repeats“, SSR) untersucht. Dabei produzierten 10 SSR-Marker insgesamt 21 Allele mit einem Durchschnitt von 2,1 Allelen pro Primer. Von den 21 Allelen zeigten 18 Polymorphismus (85,71 %), und 3 Allele zeigten Monomorphismus (14,28 %). Mit der Popgen32-Software wurde eine Ähnlichkeitsmatrix erstellt. Die genetische Identität lag im Bereich von 33,33–76,19 %. Die höchste Identität wiesen B. nigra und B. campestris auf, während die niedrigste Identität zwischen B. campestris und B. oleracea beobachtet wurde. Die Größen der amplifizierten Allele lagen im Bereich von 70–290 bp. Der polymorphe Informationsgehalt (PIC) variierte von 0,37–0,71, mit einem Durchschnitt von 0,66 pro Primer. Ein Dendrogramm klassifizierte die Genotypen in 2 Hauptcluster. Cluster-A wird weiter unterteilt in Cluster-C, der aus B. carinata und B. oleracea besteht. Jeweils einen unabhängigen Cluster bilden B. napus und B. juncea. Cluster-B besteht aus B. nigra und B. campestris, was bedeutet, dass diese beiden Arten eng miteinander verwandt sind. Die Ergebnisse zeigten, dass diese Spezies auf molekularer Ebene unter Verwendung molekularer Marker voneinander isoliert werden können.

Schlüsselwörter

Allele Dendrogramm Gelelektrophorese Molekulare Marker „Polymorphic information content“ 

Notes

Acknowledgements

We are very thankful to the members of Centre of Agricultural Biochemistry and Biotechnology (CABB), University of Agriculture, Faisalabad, Pakistan for their support and encouragement to conduct this study.

Conflict of interest

A. Raza, S.S. Mehmood, F. Ashraf, and R.S.A. Khan declare that they have no competing interests.

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Copyright information

© Springer-Verlag GmbH Deutschland, ein Teil von Springer Nature 2018

Authors and Affiliations

  • Ali Raza
    • 1
    • 2
    Email author
  • Sundas Saher Mehmood
    • 1
    • 2
  • Farwa Ashraf
    • 1
  • Rao Sohail Ahmad Khan
    • 1
  1. 1.Centre of Agricultural Biochemistry and Biotechnology (CABB)University of AgricultureFaisalabadPakistan
  2. 2.Key Lab of Biology and Genetic Improvement of Oil Crops, Oil Crops Research Institute (OCRI)Chinese Academy of Agricultural Sciences (CAAS)WuhanChina

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