© Benaki Phytopathological Institute
Margaritopoulou & Milioni
42
ic and abiotic conditions (Chaki
et al.,
2013;
Chaki
et al.,
2008; Chaki
et al.,
2011).
Overall, transgenic sunflower has the
potential to meet the demands for yield im-
provement, to increase the efficient use of
renewable resources, such as land, water
and soil nutrients, and to significantly bene-
fit everyday life by providing additional nu-
tritive and healthy foods and valuable in-
dustrial products.
Ease of use and robustness of molecular
markers
Markers’ validation assesses their link-
age to and association with QTLs and their
effectiveness in selection of the target phe-
notype in independent populations and dif-
ferent genetic backgrounds (Collard
et al.,
2005). An overall QTL mapping has been
performed using microsatellite and Single
Nucleotide Polymorphisms (SNP) markers
in sunflower giving the ability to assess the
genetic diversity and population structure
across different sunflower populations (Fil-
ippi
et al.,
2015).
Validation of genomic Simple Sequence
Repeats (SSRs) in four genotypes of sunflow-
er (RHA266, PAC2, HA89 and RHA801) result-
ed in amplification of 74 sequences from
a total of 127 analyzed. Out of them, 13%
represented polymorphic loci, 45% mono-
morphic, 5% null alleles and the remaining
37% showed either no amplification prod-
uct, nonspecific amplification or complex
or difficult to resolve banding patterns (Ta-
lia
et al.,
2010). The percentage of polymor-
phisms within sunflower that can be geneti-
cally mapped using SSR markers is shown to
be less than 10% that comes in agreement
with reports from other species (Varshney
et
al.,
2005).
Examples of markers/QTLs validation
across various genetic backgrounds in sun-
flower include:
A set of markers have been validated
−
in a number of different genetic back-
grounds for the Or5 gene conferring re-
sistance to race E of the parasitic weed
broomrape (
Orobancche cumana
), in-
fecting the sunflower roots (Höniges
et
al.,
2008; Pérez-Vich
et al.,
2004; Tang
and Knapp, 2003).
Markers have been validated for the
−
dominant PI genes determining resis-
tance to different downy mildew races
(Brahm and Friedt 2000; Hvarleva
et al.,
2009; Ma
et al.,
2017) and to the R1, Radv
and Pu6 genes conferring resistance to
rust (Bulos
et al.,
2014).
QTLs controlling three resistant (stem le-
−
sion, leaf lesion and speed of fungal con-
trol) and two morphological (leaf length
and leaf length with petiole) traits have
been validated for
S. sclerotiorum
across
generations (Micic
et al.,
2005) and across
environments (Talukder
et al.,
2016).
QTLs have been validated for sunflower
−
oil content, across generations, environ-
ments and mapping populations (Tang
et al.,
2006b).
Markers have been developed in sun-
−
flower for simple traits selection, based
on gene mutations underlying the trait
of interest. There has been identified a
mutation in codon 205 in the acetohy-
droxyacid synthase gene AHAs-1 that
confers resistance to imidazolinone (IMI)
herbicides and developed a SNP geno-
typing assay diagnostic for it (Kolkman
et al.,
2004).
Maize (Zea mays L., Poaceae)
Cultivation of maize is extensively wide-
spread throughout the world and is surpass-
ing any other grains (Council, 2019). With a
fraction of total maize production being con-
sumed by humans, its main products are eth-
anol, animal feed and processed corn starch
and corn syrup (Klopfenstein
et al.,
2013).
Maize has high nutritional value but also is a
fine source of various major phytochemicals
such as carotenoids, phenolic compounds,
and phytosterol, depicting its potential
health benefits (Rouf Shah
et al.,
2016).
Genome as the core base
B73 decoding.
The 2.3-billion-base ge-
nome of an inbred line of maize called B73,
an important commercial crop variety has
been decoded (Schnable
et al
., 2009). It has
