Merida, Mexico
June 20, 2008
Source:
American Society of Plant
Biologists
When tomatoes ripen in our
gardens, we watch them turn gradually from hard, green globules
to brightly colored, aromatic, and tasty fruits. This familiar
and seemingly commonplace transformation masks a seething mass
of components interacting in a well-regulated albeit highly
complex manner. For generations, agriculturalists and scientists
have bred tomatoes for size, shape, texture, flavor, shelf-life,
and nutrient composition, more or less, one trait at a time.
With the advent of molecular biology, mutagenesis and genetic
transformation could produce tomatoes that were more easily
harvested or transported or turned into tomato paste.
Frequently, however, optimizing for one trait led to
deterioration in another. For example, improving flavor could
have a negative effect on yield. The revolution in genomics,
with a wealth of data emerging from sequencing and simultaneous
expression analysis of thousands of genes, has made it possible
to study the numerous pathways and regulatory
networks—systems--that operate to produce a desirable fruit.
This systems approach in the new fields of metabolic and
functional genomics is producing the tools, information, and
biological materials needed for screening and breeding efforts
in tomato and other members of the Solanaceae.
Dr. Fernando Carrari and his colleagues, Laura Kamenetzky, Ramon
Asis, Luisa Bermudez, Ariel Bazzini, Sebastian Asurmendi,
Marie-Anne Van Sluys, Jim Giovannoni, Alisdair Fernie, and
Magdalena Rossi use a systems approach that integrates genomic,
genetic, and biochemical tools to model the metabolic networks
that interact in the process of tomato fruit development. Dr.
Carrari, of the Instituto de Biotecnologia, (INTA), Argentina,
will be presenting this work at a symposium on the Biology of
Solanaceous Species at the annual meeting of the American
Society of Plant Biologists in Mérida, Mexico (June 29, 9:10
AM).
Tomato (Solanum lycopersicum) is a member of the Solanaceae or
nightshade family, which also includes potato, eggplant,
tobacco, and chili peppers. The center of origin and diversity
of tomato species is in the northern Andes, where endemic
populations of wild tomato species still grow. These wild
populations represent considerable genetic diversity, whereas
cultivated tomatoes are genetically poor. The Tomato Genome
Consortium is an international collaboration that is sequencing,
mapping and analyzing the genomes of both wild and cultivated
varieties. Carrari and his co-workers, as well as other
scientists, have begun to make use of this wealth of sequence
data in functional and metabolic analyses of tomato and other
crops.
Plants produce an immense variety of chemical compounds for
growth, metabolism, signaling, defense, and reproduction. These
metabolites function in complex networks and pathways in which
they regulate and are regulated by parallel networks of genes.
It is not possible to realistically model these metabolic
systems one compound or gene at a time. Moreover, many, if not
most traits in tomato, are not the result of one gene, but of
many genes located together in chromosomal regions called
quantitative trait loci (QTLs), because they produce a range of
values in fruit or plant size or color, rather than just two
extremes. Thus metabolites, enzymes, and genes must be analyzed
simultaneously and in parallel in order to capture their dynamic
relationships. To accomplish this, Carrari and his colleagues
made use of the high genetic diversity of an ancestral tomato
species, Solanum pennellii. Through crosses, chromosomal
segments of S. pennellii were introgressed into the genome of
the cultivar Solanum lycopersicum var. Roma. Different lines of
the cultivar were then created that differed only in the
chromosomal segment received from the wild species. In this way,
over 1200 metabolic QTLs or quantitative metabolic loci (QMLs)
were identified and analyzed. Almost 900 of these QMLs were
found to be associated with fruit metabolism.
The scientists then sampled a number of metabolites such as
carbohydrates, pigments, and hormones, among others, throughout
flower and fruit development. They also used microarrays to
determine which genes were expressed at those same times.
Pairwise comparisons and network analyses were then made to
determine which of those genes and metabolites are associated in
possible functional networks. These associations do not
establish causality or regulatory direction, because they are
only correlational. Expression of certain genes may regulate
metabolite activity, but metabolites may also have a regulatory
effect on gene expression. To begin to define causal direction,
Carrari and his colleagues perturbed these systems by treatment
with external metabolites and followed the transmission of
information from metabolite to gene. In continuing research,
Carrari and co-workers are using these methods, as well as RNA
interference and transgenesis to map QMLs and to identify and
utilize candidate genes that function at network nodes.
These systems approaches make it possible to model the whole
organism throughout its development. Moreover, an understanding
of metabolic networks will make it possible to alter metabolic
pathways to produce fruits with different secondary compounds
that influence texture, taste, aroma, and nutrition, as well as
to improve yield. Metabolite analysis also has possible
applications in drug discovery, nutrient enhancement and biofuel
production. One important goal is the use of ancestral genetic
resources in place of simplistic genetic modification to avoid
possible deleterious environmental effects as well as resistance
by consumers to genetically modified food. |
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