Biology Reference
In-Depth Information
(SGN) database contains biological data for
species in the Solanaceae family and their close
relatives. Data ranges from chromosomes, maps,
markers, ESTs, microarray data, and genes, to
phenotypes and accessions. SGN hosts a pre-
release of the tomato (
S. lycopersicum
cv Heinz
1706) reference genome sequence. It is also
an open source software project, continuously
developing and improving a complex system
for storing, integrating, and analyzing data.
The SGN curation model is community-driven,
allowing researchers to add and edit up-to-date
information using simple Web tools (Bombarely
et al. 2011). This database facilitates a systems
approach, investigating the basis of adaptation
and phenotypic diversity in the Solanaceae
family and other species in the Asterid clade
such as coffee (
Coffea arabica
), Rubiaceae,
and beyond (Mueller et al. 2005). Such a rich
and broad repertoire of bio-informatic tools
is an invaluable resource for both fundamental
and applied science scholars. In combination
with the current cutting-edge high-throughput
plethora
of the resistance mechanisms by which tomato
defends against LB. This field of research can
be strengthened even further by the input of the
pathogen-related genomic resources.
Genomic Resources in P.infestans
Tremendous progress has been made recently
in the pathogen genomics area through the
availability of the second-generation sequenc-
ing of
Phytophthora
genomes. With more than
240 Mbp encoding a mere 18,155 genes in
P. infestans
(Haas et al. 2009; Raffaele et al.
2010b), its genome exhibits extremely discon-
tinuous distribution of gene density. More than
1,400 putative disease-effector genes localize
to the expanded, repeat-rich, and gene-sparse
regions of the genome, which constitute
74%
of the genome size. In contrast, the housekeep-
ing 'core ortholog' genes occupy the repeat-poor
and gene-dense regions of the genome (Haas
et al. 2009; Raffaele et al. 2010b). Additionally,
both seem to have evolved at different paces,
with the gene-sparse regions experiencing accel-
erated rates of evolution. Distribution patterns
of the pathogen genes, which are induced dur-
ing preinfection and infection stages, indicate
enrichment in genes located in these gene-sparse
regions (Avrova et al. 2003; Raffaele et al. 2010a;
Raffaele et al. 2010b). In marked contrast, the
slowly evolving gene-dense regions are enriched
in genes induced in sporangia (Haas et al. 2009;
Raffaele et al. 2010a; Raffaele et al. 2010b).
This distinct genomic environment is thought to
contribute to
P. infestans
' evolutionary potential
by promoting genome plasticity, thus enhancing
genetic variation of effector genes leading to host
adaptation (Raffaele et al. 2010a; Raffaele et al.
2010b).
Pathogen-related genomic resources are
less abundant than those for host plants,
although the modern high-throughput analyses
contribute a wealth of data to be utilized. An
example of such input is the
Phytophthora infes-
tans
∼
of
data,
SGN
provides
tremendous
potential for research progress.
An auxilliary resource to forward- and
reverse-genetics approaches in tomato studies
constitutes the tomato mutant database, dis-
tributing Micro-Tom mutant collections (Saito
et al. 2011). Their freely accessible database,
TOMATOMA, contains 1,048 individual ethyl-
methane sulfonate (EMS) tomato mutant lines
classified into 15 major categories and 48 sub-
categories, with a total of 1,819 phenotypic cat-
egories. Of these mutants, 549 were pleiotropic,
whereas 499 were non-pleiotropic. A combina-
tion of the two approaches - genome compar-
ison studies and use of forward/reverse genetic
screens - may significantly enhance the tomato
LB
R-
gene studies, especially when employing
the modern high-throughput molecular methods
such as transcriptomics and second-generation
sequencing (e.g., microarray analyses). By using
these technologies, researchers will be able to
accrue a more complex and comprehensive view
Database,
spanning
the
Broad
Institute
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