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Molecular Plant Breeding 2012, Vol.3, No.8, 80
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and in breeding for CR resistance in wheat. A total of
28 publicly available wheat PCR-based primers from
this region or nearby (Somer et al., 2006; Paux et al.,
2008) were screened for their polymorphisms in the
population of Ernie/Batavia. Among these wheat
primers, only 32% showed polymorphism between the
two parents Ernie and Batavia and about 11% have
more than one polymorphic PCR products (S-Table 1).
A high-resolution linkage map for the 3B CR QTL
region was established by insertion of the nine
polymorphic s
imple sequence repeat (
SSR) markers
into this region (Figure 1). The QTL was precisely
located to a 7 cM region flanked by co-dominant SSR
markers gwm0181 and wmc0471 (Figure 2).
The barley 3H CR QTL was originally located to an
interval between the DArT markers bPb-4747 and
bPb-6765, which are 12.1 cM apart (Li et al., 2009).
Four PCR-based primers were designed from the
DNA sequences representing the four DArT markers,
which are associated with the barley 3H CR QTL (Li
et al., 2009). Three of the four newly developed
PCR-based markers showed polymorphism and only
one (CAPS-0079) was mapped to the same position as
the original DArT markers (bpb-0079). A total of 30
publicly available PCR-based primers from barley 3H
(Ramsay et al., 2000) were also screened for their
polymorphism between the two parents TX9425 and
Franklin for the purpose of identification of
locus-specific markers, which can be used in barley
CR breeding. About 68% of these primers showed
polymorphism and about 24% have more than one
polymorphic PCR products (S-Table 1). However,
only 11 of the polymorphic markers were inserted into
the barley 3H CR region make the resolution of this
region reached to an average of 1.1 cM between the
two markers (Figure 1). The two closely linked
co-dominant SSR markers Bmac0209 and HVM 33,
with 1.8 cM apart, were identified flanking this QTL
(Figure 3).
In order to test the transferability of PCR based
markers between wheat and barley and comparative
mapping the barley 3H CR QTL and the wheat 3B CR
QTL, the same list of barley primers was applied to
screen polymorphism between the wheat parents Ernie
and Batavia, while the wheat primers were applied to
screen between the barley parents TX9425 and
Franklin. The polymorphism study showed that around
54% of the wheat primer showed polymorphism in
barley and 56% of the barley primer showed
polymorphism in wheat. However, the specificity of
these primers was reduced when they were applied to
the opposite crop, for example, 32% of the wheat
primers have more than one polymorphic PCR
products in barley and 15% of the barley primers have
more than one polymorphic PCR products in wheat
(S-Table 1). Comparative mapping of the 3H and 3B
CR regions showed that none of 11 barley markers
linked to 3H CR resistance can be mapped to wheat
chromosome 3B, and only two of the nine wheat SSR
markers linked to 3B CR resistance locus were
mapped to an interval on barley chromosome 3H.
However, it is interesting finding that the two wheat
CR-associated SSR markers were mapped to a region
overlapping the barley 3H CR QTL region (Figure 4).
1.2 Validation of 3B QTL
The phenotypic data for the four wheat validation
populations all showed a continuous distribution
(Table 1). The microsatellite markers closely linked
with the wheat 3B major CR resistance locus,
gwm0181
and
wmc0471
, were used to identify
homozygous individuals with (RR) or without (rr) the
resistant locus on 3BL from the resistant parent Ernie.
The segregation ratios of the two markers fit the
expected ratio of 1:1 in the related validation
populations. The average scores of CR severity
differed among the four populations, with the F3
population of 10903/Ernie giving the lowest scores for
both of the RR (0.87) and rr (2.31) classes (Table 2),
and the F5 population of Kenedy/Ernie giving the
highest scores (1.38 for RR and 3.56 for rr,
respectively). The effects of the 3B locus, based on the
differences in the average severities between the
homozygous RR and rr individuals, varied from 36.7
to 61.2% with an average of 47.6% among the four
validation populations (Table 2).