Using DNA markers for the identification of drought tolerant accessions in barley
Choumane W.1, 2 (w.choumane@cgiar.org), BaumM., Russell J.3, Grando S.2, Ceccarelli S. 2
1
2
3
Dept. of Basic Sciences, Faculty of Agriculture, University of Tishreen, Lattakia, Syria
Laboratory of biotechnology, the International Center for Agricultural Research in the Dry Areas
(ICARA), O.P. Box 5466, Aleppo, Syria
Scottish Crop Research Institute (SCRI), Invergowrie, Dundee DD2 5DA, Scotland, UK
During their long existence, the landraces, the wild relatives and the wild progenitors of a crop have
accumulated a rich reservoir of genes for adaptation to the harsh natural environment. Breeding for droughtprone areas requires more emphasis on the use of genetic variability and, therefore, landraces collected in dry
areas are an extremely valuable resource. A collection of barley accessions collected from Syria and Jordan
was analyzed to assess the amount of genetic diversity. Two hundred fourty one accessions from 5 different
regions were analyzed with microsatellite markers. An informative set of 48 microsatellite markers (ESTderived and genomic SSR) mapped on the seven chromosomes of barley were used for the analysis. The
results showed a variable level of polymorphism detected at the analyzed loci. It ranged from one allele at
the (genic) locus Scind 02587/5H to 27 alleles at the (genomic) locus SCSSR 9398/6H. The frequencies of
alleles varied considerably at the same locus. It ranged from 0.4292% to 91.4% at locus SCSSR 10148.
Allele specific regions were detected, they were present in Jordan and not in Syria (allele 4 at locus
SCSSR02306/5H) or in Syria and not in Jordan (allele 5 at locus SCSSR 25538/ 3H). The level of genetic
diversity was different at the different loci. It was zero at locus Scind 02587 and 0.7179 at locus
SCSSR9398/ 6H. A preliminary analysis shows that genetic diversity within regions exceeds diversity
between regions. This can be seen in the amount of common alleles. The diversity measured with SSR
markers will be correlated with the variation for agronomic traits in order to identify marker-trait
associations.