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factor 4e (
Hv-eIF4E).
This was a perfect can-
didate gene as it co-segregated with
rym4/rym5
and it was shown that translation initiation fac-
tors are involved in recessive resistance against
potyviruses in different pathosystems (Robag-
illia and Caranta 2006). By transformation of a
resistant genotype with the wild-type allele, it
turned out that the
Rym4/Rym5
locus comprises
the translation initiation factor 4e (
Hv-eIF4E
,
Stein et al. 2005; Kanyuka et al. 2005). Knowl-
edge of such resistance genes facilitates on the
one hand the design of allele-specific markers
and on the other hand screening of large gene
bank collections for new, maybe more efficient
alleles, and opens the way to a directed access
to the genetic diversity present with respect to
resistance to BaMMV/BaYMV (Stracke et al.
2007; Hofinger et al. 2011). However, the iso-
lation of resistance genes at that time was a
very time-consuming process, which in the case
of
Rym4/Rym5
took more than 10 years from
constructing a high-resolution mapping popula-
tion to the gene sequence. Today genomic tools
are available in barley considerably enhancing
marker development and isolation of virus resis-
tance genes.
with chromosome-specific information and gene
order in barley (Mayer et al. 2011); (5) sev-
eral TILLING populations (e.g., Talame et al.
2008); and (6) efficient transformation proto-
cols (e.g., Kumlehn et al. 2006). A combina-
tion of these tools may in the future lead to a
faster marker development and isolation of virus
resistance genes in barley followed by the esti-
mation of allelic diversity concerning respective
resistance genes and an allele-based breeding for
virus resistance as outlined below.
Since the development of cheap high-
throughput sequencing technologies, a major
focus in barley genomics was on the generation
of molecular markers from the expressed por-
tion of the barley genome, namely the Expressed
Sequence Tags (ESTs). In this respect, the first
1,000-loci transcript map combining Restriction
Fragment-Length Polymorphisms (RFLP), Sim-
ple Sequence Repeats (SSRs, Thiel et al. 2003;
Varshney et al. 2007), and SNPs (Kota et al.
2008) derived from three mapping populations
was constructed by Stein et al. (2007). Indepen-
dently, the first high-density single PCR-based
map using SNPs and in/del markers was devel-
oped in a cross between
Hordeum vulgare sp.
vulgare
cv. “Haruna Nijo” and the wild bar-
ley
Hordeum vulgare sp. sponatneum
“line 602”
containing 2,890 markers (Sato et al. 2009). This
map for the first time integrated a high num-
ber of PCR-based markers in a single popula-
tion, thereby overcoming many weaknesses of
the available consensus maps. From 2005 on,
the Diversity Array Technology (DArTs) offered
simultaneous analysis of up to 6,000 markers
(Wenzl et al. 2004, 2006), which nowadays
is rapidly replaced with the Ilumina platform-
based SNPs (Close et al. 2009). SNP markers
are today the most widely used markers in bar-
ley as they are most abundant and are easily
prone to automation and high throughput (Ganal
et al. 2009; Kilian and Graner 2012; Perovic
et al. 2012).
Respective high-density SNP-markers facil-
itate the efficient detection of QTL and genes
involved
Genomics-Based Breeding for
Virus Resistance inBarley
Genomic Tools
In barley, many genomic tools are available that
can be efficiently used for improving virus resis-
tance. These are: (1) dense maps consisting of
non-genic markers (Ramsay et al. 2000; Hearn-
den et al. 2007; Varshney et al. 2007); (2) several
high-density transcript maps (e.g., Stein et al.
2007; Sato et al. 2009; Close et al. 2009); (3)
next-generation sequencing data and detailed fin-
gerprints of several BAC libraries and respective
physical maps (Wicker et al. 2008, 2009; Schulte
et al. 2011); (4) a so-called genome zipper com-
bining sequence information from rice, sorghum,
and brachypodium (Goff et al. 2002; Yu et al.
2002; Paterson et al. 2009; Vogel et al. 2010)
in
virus
resistance
in
barley
in
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