DNA Fingerprinting Based Identificaiton & Classification of Indica Rice (Oryza Sativa L.)
Date
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Sardar Vallabh Bhai Patel University of Agriculture & Technology, Meerut
Abstract
Present study was undertaken to fingerprint the thirty varieties of Indica rice collected from
distant geographical regions: Meerut (UP). Raipur (Jharkhand) and Sri Lanka using 10
primers each ofRAPD. SSR and ISSR molecular markers.The DNA was isolated using cTAB
method,PCR was performed and gel pictures were taken using gel documentation. The
diversity or similarities and dissimilarities between all thirty rice varieties were calculated
using 0 1 sheets.The PIC values and Resolving power were calculated fur individual primers.
In RAPD analysis PIC values varies from 0.8ll(OPD-08) to 0.9925(0PF-13) and resolving
power varies from 1.32(0PJ-08) to 2.066(0PJ-13). In ISSR assay, PIC value ranged from
0.8791(ISSR6) to 0.9916(ISSR5). The resolving power varies between 1.6(ISSR3) and
8.366(ISSR2) and in SSR assay, the primer RM-263 was observed to highly polymorphic
(PIC value of0.995) and RM-235 showed minimum polymorphism (PIC value of0.912). The
resolving power varies between 0.132(RM-256) to 4.662(RM-222). The cluster analysis was
made using NTSYS Software. All the 30 rice varieties were grouped into different clusters
following each RAPD, SSR and ISSR molecular marker assays. Minor variation was
observed in distribution of varieties in sub-clusters in all cases. In general, distribution of
varieties remained independent of their geographical origin. Sathi, Taraori and MAUB 57
genotypes expressed comparatively more diversity from all other genotypes. It was also
noticed that MAUB 13 expressed closeness with MAUB 164, Vallabh 22 and MAUB 15
varieties in most of the assays The analysis indicated that ISSR expressed maximum resolving
power and RAPD gave maximum PIC values and SSR molecular markers detected higher
polymorphism. Thus the three molecular marker systems together provided wider genome
coverage and were found to be better indicator of the genetic relationships.
