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would enhance soil-P availability; and (3) plant-
internal P-use efficiency, which allows more effi-
cient genotypes to produce more biomass per
unit P taken up. Screening in nutrient solution
may detect genotypic differences in mechanisms
related to (1) and (3), depending on the design
of the experiment, and might be essential for
screenings for internal P-use efficiency. For the
latter, it needs to be assured that an equal amount
of P is provided to each plant, which requires that
genotypes be grown individually in separate con-
tainers supplied with the same amount of P (Rose
et al. 2011). If distinct genotypes share the same
container, they will compete for nutrients and
this typically favors genotypes with a larger root
system (Yi et al. 2005; Wissuwa et al. 2006), pre-
sumably because the number of P uptake sites (P
transporters) is proportional to the root surface
area. Internal efficiency would potentially play
an additional role and may even be driving root
growth. Thus, screening of different genotypes
in the same container will select for a combina-
tion of traits related to root growth and internal
P-use efficiency.
Comparative experiments in nutrient solution
and soil or field are rare and it is therefore dif-
ficult to come to a general conclusion. Yi and
colleagues (2005) showed that overexpressing
the transcription factor gene
OsPTF1
increased
performance under P deficiency by about 30%,
and that this positive effect was similar in pots
filled with soil and in nutrient solution. On the
other hand, Wissuwa and colleagues (2005) did
not detect significant growth differences in solu-
tion between Nipponbare-
Pup1
sister lines with
and without the
Pup1
QTL, whereas that same
pair differed by more than 2-fold when grown in
soil (Wissuwa 2005). On the other hand, analy-
sesofIR64-
Pup1
and IR74-
Pup1
NILs in nutri-
ent solution revealed differences in root surface
area in young seedlings compared with non-
Pup1
sister lines (Gamuyao et al. 2012). Even
if nutrient solution experiments offer some ini-
tial advantages, it will be crucial to validate and
confirm genotypic differences and QTL effects
in field experiments to assure that the observed
effects are relevant for breeding applications.
Furthermore, it is critically important to care-
fully consider target environments, particularly
with regard to soil type and water management,
since the effect of certain tolerance mechanisms
(see above) might be soil-specific and affected
by the water regime during the cropping cycle.
Outlook and Perspectives
So far,
Pup1
is the only available major QTL for
tolerance of P deficiency that is used for molecu-
lar breeding of tolerant rice varieties. That
Pup1
has been identified in a field screening assured
its practical relevance, which was an impor-
tant driver for the continuous effort to eluci-
date its function and establish a molecular breed-
ing platform. The amount of resources and time
required to develop and test markers and to eval-
uate QTLs in different genetic backgrounds and
environments is considerable and can be pursued
only for large-effect QTLs with potentially high
impact. However, with the experiences gained
and the progress in molecular technologies, it
will become possible to identify and validate
QTLs more efficiently and faster.
Given that other rice genotypes have been
found with a higher P deficiency tolerance
than Kasalath (Wissuwa and Ae 2001a; Wis-
suwa unpublished), additional major QTLs can
likely be identified if suitable screening condi-
tions are applied. This could follow the tradi-
tional approach using bi-parental mapping pop-
ulations as employed successfully in the case
of
Pup1
. In this case, one parent should have
exceptionally high tolerance of P deficiency in
order to increase the likelihood of identifying
strong (and possibly rare) loci/alleles since not
all QTLs identified justify the effort needed to
initiate a MABC breeding program. Increas-
ingly, mapping of novel alleles will rely on
genome-wide association studies (GWAS) that
typically use several hundred gene-bank acces-
sions, therefore capturing a much larger portion
of the genetic variation. New technologies, such
as high-density SNP markers and genotyping by
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