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lines with mutations in candidate genes much
more quickly than developing materials using
the QTL method. Another advantage to TILL-
ING compared to the QTL approach is that the
mutations are already incorporated into a com-
pletely isogenic background; once useful traits
are identified, they can be easily transferred
to breeding populations. TILLING populations
have been developed using the processing tomato
lines M82 (Menda et al. 2004) and Red Setter
(Minoia et al. 2010), as well as the laboratory-
friendly Micro-Tom (Okabe et al. 2011). At the
very least, these populations are important proof-
of-concept examples for other researchers, and
will most likely serve as integral resources for
pre-breeding efforts in the future. Gady et al.
(2009) and Rigola et al. (2009) report three
different high-throughput methods of detecting
point mutations in tomato EMS (ethyl methane-
sulfonate) mutant populations, and each method
results in an acceptable mutation detection rate in
the populations analyzed. Both reports describe
the use of next-generation sequencing technolo-
gies coupled with elegantly tailored pooling
strategies.
Such studies are described in the following
sections.
Primary Metabolites
The observed phenotypes associated with fruit
quality traits are inherently the result of metabo-
lite production and composition within the fruit,
and the genetic components of the phenotypic
variances for such traits have been shown to
be substantial. Early studies reporting metabolic
profiling of segregating populations and attempt-
ing to construct correlational networks of genes
involved with metabolic QTLs have made signif-
icant progress (Schauer et al. 2005; Schauer et al.
2006; Fraser et al. 2007a; Bermudez et al. 2008;
Schauer et al. 2008). Recently tomato genomics-
assisted breeding research has benefited from
several studies aiming to identify and describe
variation in primary metabolites. These metabo-
lites play important roles in the determination of
key tomato fruit quality attributes, such as solu-
ble solids and acidity. What is widely accepted is
that primary and secondary metabolite levels can
be substantially different between tomato geno-
types, even within breeding germplasm, and also
differ as a result of environmental conditions.
Deeper understanding of the inheritance of pri-
mary metabolite QTLs and thorough investiga-
tion of the ultimate effect (or lack thereof) of
modulating the accumulation of these metabo-
lites on fruit quality is still required in order
to establish legitimacy of these QTLs. Recent
studies have sought to explore these questions
using the tomato system (Schauer et al. 2006;
Bovy et al. 2007; Bermudez et al. 2008; Schauer
et al. 2008).
Current high-throughput metabolic profiling
protocols are amenable to quantifying aqueous
compounds; therefore, such species of com-
pounds were the focus of the first metabolite
profiling studies in tomato. Overy and colleagues
(2005) examined the metabolic profiles of one
S.
lycopersicum
accession, one
S. pennellii
acces-
sion, and 5
S. pennellii
IL accessions, and
demonstrated that metabolic profiling combined
Fruit Quality Traits Targeted for
Genomics-Assisted Breeding in
Tomato
As discussed earlier, many agronomically impor-
tant traits in tomato can be easily phenotyped
and as a result, conventional phenotypic selec-
tion and field-based breeding practices remain
most effective for developing improved tomato
breeding lines and commercial cultivars. How-
ever, other traits, such as sugar metabolite pro-
file, carotenoid content and profile, and fla-
vor profile are more difficult to phenotype in
breeding-scale systems and therefore tend to
be neglected by practical breeding programs.
These complex traits have been targeted by
tomato researchers in an attempt to provide tools
and analyses that utilize contemporary proto-
cols and equipment, complement conventional
breeding practices, and produce real outcomes.
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