Hostname: page-component-76fb5796d-skm99 Total loading time: 0 Render date: 2024-04-25T12:27:31.305Z Has data issue: false hasContentIssue false

SSR marker-based DNA fingerprinting and cultivar identification of rice (Oryza sativa L.) in Punjab state of India

Published online by Cambridge University Press:  17 July 2009

Navraj K. Sarao*
Seed Technology Centre, PAU, Ludhiana, Punjab141 004, India
Yogesh Vikal
School of Agricultural Biotechnology, PAU, Ludhiana, Punjab141 004, India
Kuldeep Singh
School of Agricultural Biotechnology, PAU, Ludhiana, Punjab141 004, India
Monika A. Joshi
Seed Technology Centre, PAU, Ludhiana, Punjab141 004, India
R. C. Sharma
Seed Technology Centre, PAU, Ludhiana, Punjab141 004, India
*Corresponding author. E-mail:


In India, Protection of Plant Varieties and Farmer's Rights Act (PPV&FRA, 2001) requires the registration and protection of new and notified/extant plant varieties based on the criteria of distinctness, uniformity and stability (DUS) of morphological characteristics. However, these morphological traits have not been able to resolve closely related genotypes. The molecular markers can very well support the DUS testing in such cases. In the present study, therefore, 14 varieties of rice cultivated in Punjab state of India were fingerprinted using 75 simple sequence repeat (SSR) primers. Out of these, 58 primers produced polymorphic profiles, while 13 were monomorphic, 2 revealed null allele and the remaining 2 amplified only from super basmati. In a screen of 7 cultivars, 16 SSR loci produced 17 rare/unique alleles, which provided an opportunity for their unambiguous identification. Cluster analysis based on SSR data clearly distinguished the cultivars into two dist inct groups: comprising non-basmati (group I) and basmati (group II). The cluster pattern was consistent with the pedigree and breeding history of the cultivars.

Short Communication
Copyright © NIAB 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)


Callen, DF, Thompson, AD, Shen, Y, Phillips, HA, Richards, RI, Mulley, JC and Sutherland, GR (1993) Incidence and origin of ‘null’ alleles in the (AC) microsatellite markers. American Journal of Human Genetics 59: 922927.Google Scholar
Chakravarthi, BK and Naravaneni, R (2006) SSR marker based DNA fingerprinting and diversity study in rice (Oryza stiva L.). African Journal of Biotechnology 5(9): 684688.Google Scholar
Joshi, AM, Sarao, NK, Sharma, RC, Singh, P and Bharaj, TS (2007) Varietal characterization of rice (Oryza sativa L.) based on morphological descriptors. Seed Research 35(2): 188193.Google Scholar
Nandkumar, N, Singh, AK, Sharma, RK, Mohpatra, T, Prabhu, KV and Zaman, FU (2004) Molecular fingerprinting of hybrids and assessment of genetic purity of hybrid seeds in rice using microsatellite markers. Euphytica 136: 257364.CrossRefGoogle Scholar
Rohlf, FJ (1989) NTSYS-pc Numerical Taxonomy and Multi-variate Analysis System, Version 2.02. Setauket, NY: Exeter Publications.Google Scholar
Saghai-Maroof, MA, Soliman, KM, Jorgensen, RA and Allard, RW (1984) Ribosomal DNA spacer length polymorphisms in barley: Mendelian inheritance, chromosomal location and population dynamics. Proceedings of the National Academy of Sciences of the United States of America 81: 80148018.CrossRefGoogle ScholarPubMed
Senior, MX, Murphy, JP, Goodman, MM and Stuber, CW (1998) Utility of SSRs for determining genetic similarities and relationships in maize using an agarose gel system. Crop Science 38: 10881098.CrossRefGoogle Scholar
Warburton, M and Crossa, J (2000) Data Analysis in the CIMMYT Applied Biotechnology Centre for Fingerprinting and Genetic Diversity Analysis. Texcoco, Mexico: CIMMYT.Google Scholar
Supplementary material: File

Sarao supplementary material


Download Sarao supplementary material(File)
File 72.2 KB