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bi-parental populations (L upken et al. 2012) but
also applying genome-wide association studies
(GWAS, e.g., Rode et al. 2012), as this has
shown already for BYDV tolerance using SSRs
and AFLPs (Kraakman et al. 2006). Further-
more, the availability of high-density genome-
covering markers may also facilitate genomic
selection procedures in barley, including selec-
tion for virus resistance (Heffner et al. 2009;
Heslot et al. 2012).
High-quality genomic sequences of rice, the
second sequenced plant genome (Goff et al.
2002; Yu et al. 2002), represent the ideal
blueprint for re-sequencing and identification
of markers across the Triticeae . More recently,
the release of the sorghum ( Sorghum bicolor )
and Brachypodium distachyon genomes (Pater-
son et al. 2009; International Brachypodium Ini-
tiative 2010) has opened the way to use these
species as models for comparative genomics of
cereals with large genomes. The model-based
strategy is supported by the extensive conser-
vation of gene order and sequence homology
among the Poaceae genomes (Bolot et al. 2009;
Abrouk et al. 2010). Colinearity between rice and
barley has been widely exploited with different
purposes (Perovic et al. 2004; Faure et al. 2007;
Ramsay et al. 2011). Comparative studies involv-
ing the other genomes were also conducted as
the wild grass Brachypodium has emerged as an
important model for wheat and barley (Bossolini
et al. 2007; Higgins et al. 2010). Considering that
synteny between species is not equally conserved
across genomic regions (Turner et al. 2005), any
strategy to search for genes in barley should ben-
efit from surveying several related species, as
their information may prove complementary. Ini-
tially, when the transcriptome sequence of bar-
ley was the main resource of barley genomics, a
“reciprocal BLASTN search” to the sequenced
rice genome (Perovic et al. 2004) turned out
to be the most efficient procedure in the pre-
diction of orthologs. Recent advances in barley
genomics relying on barley genomic sequences
from two cultivars open new horizons in compar-
ative mapping of cereals for fine-mapping and
marker saturation of loci of interest (Luepken
et al. 2012). Today, the genome zipper avail-
able in barley combining sequence information
from rice, sorghum, brachypodium, and genomic
sequence of barley has led to the assignment of
86% of the estimated barley genes to individ-
ual chromosome arms and their organization in
a putative linear order (Mayer et al. 2011). The
genome zipper turned out to be a very efficient
tool for marker saturation in barley (Shahinnia
et al. 2011; Luepken et al. 2012; Silvar et al
2012).
Use of Genomic Resources in
Marker Saturation
Beside the construction of high-resolution map-
ping populations, marker saturation of chromo-
somal regions affecting virus resistance is a pre-
requisite for isolating resistance genes. Whereas
it took more than 10 years to isolate the resis-
tance locus Rym4/Rym5 (Pellio et al. 2005; Stein
et al. 2005), using the genomic tools described
above and the physical map partly available for
the barley genome (Schulte et al. 2011) a candi-
date gene for the rym11 locus (Bauer et al. 1997),
located in the centromeric region of chromosome
4HL (Nissan-Azzouz et al. 2005), has been iden-
tified within about 3 years (Luepken et al. 2012).
A brief overview on the procedure employing
genomic tools in marker development and gene
isolation is given for the BaMMV/BaYMV resis-
tance gene rym13 in Figure 5.1. Based on a low-
to medium-resolution map, a high-resolution
mapping population has been constructed and
marker saturation was conducted using available
high-density genetic maps and the genome zip-
per including next-generation sequencing data
available in barley. Based on these markers, a
BAC contig will be identified and sequenced
harboring the resistance gene rym13 . Using this
approach, it is assumed that in the near future,
many virus resistance genes in barley will be iso-
lated, leading on the one hand to a deeper under-
standing of the structure and function of virus
resistance genes and the development of allele
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