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Random genomic scans at microsatellite loci for genetic diversity estimation in cold-adapted Lepidium latifolium

Published online by Cambridge University Press:  24 October 2012

Atul Grover*
Affiliation:
Defence Institute of Bio-Energy Research (DIBER), Goraparao, PO Arjunpur, Haldwani 263139, Uttarakhand, India
Sanjay Mohan Gupta
Affiliation:
Defence Institute of Bio-Energy Research (DIBER), Goraparao, PO Arjunpur, Haldwani 263139, Uttarakhand, India
Pankaj Pandey
Affiliation:
Defence Institute of Bio-Energy Research (DIBER), Goraparao, PO Arjunpur, Haldwani 263139, Uttarakhand, India
Sadhana Singh
Affiliation:
Defence Institute of Bio-Energy Research (DIBER), Goraparao, PO Arjunpur, Haldwani 263139, Uttarakhand, India
Zakwan Ahmed
Affiliation:
Defence Institute of Bio-Energy Research (DIBER), Goraparao, PO Arjunpur, Haldwani 263139, Uttarakhand, India
*
*Corresponding author. E-mail: iatulgrover@gmail.com

Abstract

Lepidium latifolium L. (Brassicaceae) grows successfully in a high-altitude cold arid environment. Little molecular data are available for this plant despite its immense ecological importance as a cold- and drought-adapted species. We used a novel approach to identify microsatellite regions using genome walker libraries, called as Random Scans at Microsatellite Regions (RaSMiR), and implemented them on genotypes collected from relatively different topographical conditions within a small geographical area. The success rate of finding a microsatellite sequence using this methodology was 100%, and on developing the RaSMiR technique itself as a molecular marker, 230 electrophoretic bands were obtained using 13 different RaSMiR primers in combination with a microsatellite sequence primer. On an average, 17 bands were obtained for each primer. The electrophoretic profiles generated by RaSMiR markers were distinct from those produced by inter-simple sequence repeat markers. This information has been documented as a dominant marker data, and has been used to construct a neighbour-joining tree that successfully distinguished all genotypes. RaSMiR is an attractive approach for the development of unique and informative microsatellites, or for genome scanning directly as a molecular marker that can potentially be employed for the estimation of genetic diversity or to identify polymorphic loci involved in adaptations particularly in the non-model species, for which sufficient genomic data are not available.

Type
Research Article
Copyright
Copyright © NIAB 2012

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