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conducted for QTL candidate gene identification
and marker development in targeted genomic
regions (Kinkade 2010; Kinkade and Foolad,
unpubl. results).
In parallel to the SolCAP and tomato sequenc-
ing projects, the Tomato Functional Genomics
Database [TFGD; (
http://ted.bti.cornell.edu/; Fe
i
et al. 2011)] has made a variety of expressed
sequence tag (EST) datasets, metabolite anal-
yses, microarray experiments, and small RNA
experiments available for public query and
analysis. Rather than simply act as a repos-
itory for experimental results, the TFGD has
expanded its capabilities for analysis of microar-
ray data, sRNA (small RNA) experiments, and
metabolomic datasets (Fei et al. 2011). This has
enabled researchers to analyze data in a consis-
tent, reliable manner - one of the key develop-
ments that must occur if we are to build upon pre-
vious knowledge and utilize it in a practical way.
Each of these resources has been integrated (or
at least linked) with SGN, which has positioned
SGN as the current nexus for tomato omics infor-
mation (maps, markers, analysis tools, pheno-
types, and genotypes). A “breeder's toolbox” has
been made available for researchers searching for
markers, phenotypes, and/or QTLs, although the
practical utility of information contained within
this portal is currently limited. Nonetheless, mas-
sive amounts of tomato genomics information
and resources are freely available through SGN,
and these resources continue to support applied
researchers.
Lastly, reverse genetics approaches to tomato
germplasm improvement have emerged as a
cost-effective way to generate novel genetic vari-
ation. With the development of efficient bioin-
formatics pipelines to detect point mutations in
large populations, coupled with massively par-
allel sequencing strategies utilizing cheap next-
generation sequencing technologies, TILLING
can now compete with forward genetics strate-
gies for pre-breeders' attention. Combined with
the fact that a large body of basic plant biology
research has been conducted using the tomato
system, which can be leveraged to target spe-
cific genes or gene families involved in impor-
tant phenotypes, this approach is well-suited for
use in tomato genetic improvement. In addi-
tion, researchers can obtain and evaluate many
New Tomato Genomics Resources
A publicly available genome sequence has sup-
ported the direct application of genomics to
tomato breeding on a number of levels. For the
first time, tomato researchers are now able to
identify potential markers directly within regions
of interest, design primers using the genome
sequence, and screen for polymorphism within
their population of interest (Kinkade 2010;
Kinkade and Foolad, unpubl. data). In addition,
as genotyping-by-sequencing (GBS) becomes
more cost-effective, a reference genome will
assist researchers in mapping the tens of thou-
sands of putative single nucleotide polymor-
phisms (SNPs) identified by this process within
contemporary breeding populations. An exten-
sion of this approach has been taken up by
the Solanaceae Coordinated Agricultural Project
(SolCAP;
http://solcap.msu.edu).
Focused on
improving genomics resources and training for
potato, tomato, and pepper, and translating these
resources into applied outcomes, SolCAP has
introduced a highly successful series of train-
ing articles and videos on its eXtension web-
genomics).
SolCAP has identified thousands
of SNPs within the cultivated tomato (Sim
et al. 2012) and potato (Hamilton et al.
2011) germplasm and made them available on
an Infinium array for the breeding commu-
nity to utilize. At the very least, this project
has provided successful training tools and a
substantial, universal set of informative SNP
markers to the broader tomato community.
Applied breeding outcomes in tomato by the
SolCAP consortium have yet to be formally
published; future research as part of Sol-
CAP is anticipated to elucidate alleles con-
trolling variation in carbohydrate and vitamin
metabolism.
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