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with principal component analysis could indeed
be used to distinguish tomato genotypes. A sim-
ilar, yet more robust experiment was carried out
by Schauer and colleagues (2005), who reported
GC/MS (gas chromatography/mass spectrome-
try) profiling of accessions of 5
Solanum
species
and described substantial differences in sugars,
organic acids, amino acids, and other metabo-
lites between the different species. Neither of
these studies examined large populations in an
agricultural setting, as opposed to studies con-
ducted by Schauer and colleagues (2006 and
2008), who reported extensive evaluations of the
S. pennellii
IL population for metabolic profile
as well as agronomic traits. Schauer et al. (2006)
were the first to evaluate an entire genetic pop-
ulation of tomato for metabolite profile, in an
agriculturally relevant setting, along with agro-
nomic traits such as soluble solids, yield, fruit
size, and so forth. This study elucidated spe-
cific, genotype-dependent differences in specific
metabolites, such as higher fructose in introgres-
sion line 6-3, and also established positive and
negative correlational networks between specific
metabolites as well as between various classes of
metabolites and agronomic traits. While many
metabolic QTLs were identified, many of these
were also coupled with harvest index-associated
QTLs, casting some doubt on the practical util-
ity of the detected QTLs (Schauer et al. 2006).
It remains unclear to what extent negative link-
age drag influenced the findings from this study.
However, it is clear from this study that metabo-
lite QTLs do exist in wild germplasm, metabolic
networks can be constructed in tomato using wild
germplasm sources, metabolic data can be col-
lected in parallel to agronomic and horticultural
data, key nodes of regulation can be identified on
an omics scale, and these nodes may be exploited
to alter metabolic traits in tomato.
A later study examined the inheritance of
these primary metabolic traits in the same pop-
ulation (Schauer et al. 2008). Building on the
results of the previous study, three years' worth
of metabolite data were combined to identify
metabolite QTLs conserved across years and to
examine the heritability of the traits. In addi-
tion to the homozygous
S. pennellii
IL (intro-
gression lines) population, the researchers also
analyzed heterozygous ILs [ILHs; (Semel et al.
2006)]. From the 43 QTLs detected over the three
years of experiment, a striking number of them
were fairly heritable. Although some heritability
estimates fluctuated widely over the three years
of this study, this is to be expected when deal-
ing with traits that are subject to environmental
conditions (Schauer et al. 2008). In addition, it
was reported that most metabolite QTLs were
dominant, which is a promising result from a
breeding standpoint, since most tomato breed-
ers are attempting to develop hybrid cultivars.
The researchers also compared metabolic net-
works between the IL and ILH populations, and
found that a significant amount of the previously
detected associations between metabolite QTLs
and harvest index were abolished in the het-
erozygotes (Schauer et al. 2008). This finding
is an important discovery for breeders attempt-
ing to modulate these traits. Bermudez and col-
leagues (2008) took a candidate gene approach
in order to further study QTLs identified by
Schauer and colleagues (2006) and to asso-
ciate sequence variation within candidate gene
regions with the previously detected QTLs. The
approach utilized available genomic resources
to (1) identify potential candidate genes within
genomic regions of interest, (2) compare allelic
variation between the two original parental
lines, and (3) correlate transcription of some
candidate genes with metabolite abundance.
Although Bermudez and colleagues (2008) were
limited by the lack of a complete genome
sequence, this did not prevent the identifica-
tion of many promising candidate alleles under-
lying previously detected QTLs; in addition,
the approach simultaneously produced gene-
specific markers that could be used in practical
application.
There is still a long way to go in the
effort to combine metabolite profiling, genomics,
and practical breeding for tomato fruit quality.
However, the use of immortalized populations
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