© Benaki Phytopathological Institute
Margaritopoulou & Milioni
46
proving cold tolerance in maize (Quan
et al.,
2004). Furthermore, genome-wide associa-
tion analyses (GWAS) in temperate maize in-
bred lines is serving as a tool to find strate-
gies for identifying genes for cold tolerance
(Revilla
et al.,
2016) and has been report-
ed that the introduction of an antisense
gene for pyruvate orthophosphate dikinase
(PPDK) into maize with
Agrobacterium
-me-
diated transformation resulted in shifting
the break point 3
o
C less than that of the wild
type (Ohta
et al.,
2004).
Drought is another stress factor that has
been addressed in maize improvement. Nu-
clear Factor-Y (NF-Y) is a 3- subunit com-
plex that has been shown to play major role
in growth, development, and response to
environmental stress. Except studies that
have been performed for characterizing
NF-Y gene families in maize (Zhang
et al.,
2016), when ZmNF-YB2 or ZmNF-YB16 were
constitutively expressed in elite maize in-
bred lines, the transgenic lines displayed
improved drought tolerance compared to
wild-type plants under water-stressed con-
ditions in the field (Nelson
et al.,
2007; Wang
et al.,
2018). (Castiglioni
et al.,
2008) demon-
strated that transgenic maize lines recom-
binant with bacterial RNA chaperones re-
sulted in not only abiotic stress tolerance
but also improved grain yield under water-
limited conditions. The application of this
technology has the potential to consider-
ably impact maize production systems that
have drought. However, commercializa-
tion of transgenic maize for abiotic stress-
es like drought tolerance has been terribly
restricted (Xu
et al.,
2009).
Moreover, the past ten years we have
witnessed extensive efforts toward the de-
velopment of an efficient
Agrobacterium
-
mediated transformation system for an
array of maize developing organs with par-
ticular emphasis on increasing the efficiency
and extending the range of amenable gen-
otypes (Cao
et al.,
2014; Lee and Zhang 2014;
Shrawat and Lörz, 2006).
Validation of quantitative traits
In maize, a trait that has been exten-
sively investigated as an indirect measure
of drought tolerance is the capacity of ABA
accumulation. The presence of a major QTL
for root features (root-ABA1) was mapped
on bin 2.04 in Os420 × IABO78. This major
QTL affecting abscisic acid (ABA) concentra-
tion in the leaf, root traits and relative wa-
ter content was further evaluated in maize
using NILs (Landi
et al.,
2005). Interestingly,
the QTL allele for larger root mass and high-
er ABA concentration negatively affected
grain yield (Landi
et al.,
2006). Laurie
et al.
(2004) were able to detect 50 QTL account-
ing for genetic variance in maize oil content
with a resolution of the order of a few centi-
morgans across generations.
QTL conditioning resistance to plant
pathogens (rQTL) have been discovered
and reviewed by several authors (Balint-
Kurti and Johal, 2009; Redinbaugh and
Pratt, 2009). To date only a few QTL confer-
ring resistance to maize streak mastrevirus,
Cercospora zeae-maydis
,
Exserohilum turci-
cum
(Pass.) and
Peronosclerospora sorghiin
have been validated (Abalo
et al.,
2009; Asea
et al.,
2009; Nair
et al.,
2005). For Cercospo-
ra resistance in maize, QTLs have been val-
idated across genetic backgrounds (Pozar
et al.,
2009) and environments (Juliatti
et al.,
2009). Furthermore, a major QTL control-
ling maize streak virus resistance explains
50–70% of total phenotypic variation (Per-
net
et al.,
1999). Several microsatellite mark-
ers associated with this QTL were validated
across populations and have been success-
fully used for the selection of resistant lines
(William
et al.,
2007).
Analyses for evaluating the significance
of QTL x genetic background interactions in
several diverse mapping populations, have
been performed in maize for grain mois-
ture, silking date and grain yield (Blanc
et al.,
2006; Huo
et al.,
2016). QTL meta-analysis
is another approach to identify consensus
QTL across studies, to validate QTL effects
across environments/genetic backgrounds,
and also to refine QTL positions on the con-
sensus map (Goffinet and Gerber 2000). The
concept of meta-analysis has been applied
to the analysis of QTL/genes for flowering
