Systems Biology is the Way of the Future Grant R. Cramer

Transcription

Systems Biology is the Way of the Future Grant R. Cramer
Systems Biology is the Way of the
Future
Grant R. Cramer
Department of Biochemistry and Molecular Biology
University of Nevada, Reno
Talk Take Home Points
1. Grapes are complex organisms
2. Systems Biology enables modeling of
complex processes
3. Environmental factors interact with gene
expression to produce certain grape
quality traits
4. Understanding the regulation of these
traits will lead to better management
practices
Background Information
Genotype to Phenotype
• Genotype contains the entire genetic code to
make the phenotype
• Phenotype is the physical expression of the
genotype including its physical appearance,
activities and metabolism
• Phenotype = Genotype x Environment
– The environment affects the phenotype through
interactions with the genotype
We are in a Biological Revolution!
• The grape genome was sequenced in
2007
• Molecular and instrumentation
technologies are progressing rapidly
• The rapid increase in computing power is
allowing the rapid decoding of the
genome and the modeling of complex
processes
The grape genome has 19
chromosomes which
represent 19 volumes on
how to be a grape
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Page of Genetic Code
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Signal (Environmental or Developmental Cues)
DNA
(Code)
mRNA
(Message; email)
Protein (Factory and Delivery Service)
Metabolite
Organ
(Product)
Basic steps in gene expression
Regulation of Gene Expression
Fruit Development is Complex
• Multiple tissues
• Flavor and quality
traits originate in
different tissues
at different times
Systems Biology Enables Modeling of Complex
Processes
Systems biology combines the molecular components
(transcripts, proteins, and metabolites) of an organism and
incorporates them into functional networks or models
designed to describe the dynamic activities of that organism.
Transcriptomics
Proteomics
Omics
Viewer
Metabolomics
Abiotic Stress can be Beneficial
for Wine Quality and Humans
• High light and water deficit alter metabolite
composition of berries
• Water deficit increases total phenolic and
anthocyanin content
– major determinants of aroma, color, and flavor in wine
• Polyphenolic compounds (e.g. resveratrol) are
antioxidants, which can prolong life, reduce the risk
of coronary heart disease, stroke, and cancer
Systems Biology Approach
• Generate global ‘Omics’ datasets
• Reconstruction of biochemical reaction
networks
• Modeling ‘in silico’ of networks
• Network validation, discovery and use
What systems biology can provide:
• Diagnostic biomarkers for traits or phenotype (e.g.
disease or stress condition, genotype
identification, harvest maturity…)
• Models for further testing of hypotheses such as
gene function, genetic interactions (i.e. hubs or
regulatory network points), genetic improvement
and disease treatment
• Identification of good practices for optimal
physical management of crops
Example: Drought Stress
Effects on Berry Metabolism
Transcriptomic Summary
Carotenoid Metabolism
Fatty Acid Metabolism
Anthocyanins
increased by
water deficit
Summary
• Deficit irrigation affects color, titratable
acidity, phenolic and aroma composition of
wines
• Deficit irrigation alters the composition and
metabolism of sugars, phenolics, organic
and amino acids in Chardonnay and
Cabernet Sauvignon berries
Current Interests
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Systems Biology
Abiotic Stress
Berry development to wine quality
Bioinformatics
Phenotyping for GWAS of the future
Biotic Stress
Expected Outcomes For Genome
Sequencing
• We are currently sequencing the Cabernet
Sauvignon genome
• Allows genotype comparisons and
identification including other Cabernet
Sauvignon clones
• Allows comparison of phenotypes and
identification of important traits
One current project in the lab
• Goal to identify the Omics responses of mature
berries of five different varieties (Cabernet
Sauvignon, Merlot, Pinot Noir, Chardonnay and
Semillon) to water deficit
• Transcriptomics and proteomics responses
collected in my lab
• Metabolomics responses collected in Aaron Fait’s
lab in Israel (Ben-Gurion University of the Negev)
• Use these data to model and identify the network
players involved in important varietal quality
traits
Examples of three cliques in mature
berries identified by network analyses
• Linalool (floral aromas) synthase network
includes 58 genes some of which are cytochrome
P450s and ACC synthases (ethylene biosynthesis)
• Lipoxygenase (producing volatile aromas)
network of 237 members includes many receptor
kinases
• ERF trancription factor pathway of 387 members
includes many genes involved in anthocyanin
biosynthesis (red color)
Genes up-regulated during Cabernet Sauvignon berry
ripening
Grant R. Cramer
University of Nevada, Reno
Oregon State University
July 15th – 18th, 2012
Institutional Participants In Year 4 (2012)
URGVJKI
UA
UB
INRA UV
UG
OSU
SDSU
USDA-Cornell
ISU
UNR
MSU UK
UCD
CAS
CAU
VC
FA&M
IFAS
INIA
UA
MU
Stipend Participants (4th Year)
Student Awardee
1. Amanda Vondras
2. Danny Hopper
3. Ryan Ghan
4. Anthony Ananga
Home
Oregon State
UN Reno
UN Reno
Florida A&M
Host Institution
University of Veronal
Macquarie University
University of Verona
Volcani Center
Postdoc Awardee
1. Aarthi Talla
Home
Missouri State
Host Institution
INRA, Paris
2. Steve Van Sluyter
3. Devaiah Kambiranda
Macquarie University
Florida A&M
Harvard
Oregon State
Climate change? How will this change
what grapevines we plant?
Predicted Climate Change in Europe
Huglin Index
Carignan
Müller Thurgau
Gamay
Pinot blanc
Pinot noir
Cabernet franc
Ugni blanc
Grenache
Chardonnay
Syrah
Cabernet sauvignon
Riesling
Cinsaut
Merlot
Sylvaner
(from Stock et al., 2004)
Chenin
Sauvignon blanc
An example of research in Bordeaux
• How to predict a phenotype from information
available on the genotype and its interactions with
the environment? > How will the existing varieties respond to climate
change, and what are the new phenotypes we are looking for (ideotypes)?
• Complex traits affected by multiple environmental
factors
Phenotype = G + E+ G×E
P= Gv + Gr + E + GvxGr + GvxE + GrxE + GvxGrxE
(Gv = genotype of variety; Gr = genotype of rootstock)
Vitadapt & VitPhe: Important Public
Phenotyping Resources in France
• Vitadapt contains 52 different varieties being
phenotyped in detail in Bordeaux
• Eventual goal is to genotype (sequence) all
varieties and connect to their different
phenotypes (e.g. bud break, harvest dates, other
physiological parameters)
• VitPhe is a public database for this information
• Going to be part of a large international effort
Vitadapt: Planting of the experimental plot
3.Dispositif expérimental
« mouillère »
9m
7m
Selected plot : 7200 m2
Resistivity map of soils for the VitAdapt plot
The most homogeneous area (black square)
was selected
Delimitation of the plantation zone
The green area corresponds to the plantation zone.
The blue area corresponds to additional planting for storage
52 different varieties (planted in 2009) :
32 red varieties – including 2 resistant hybrids –
20 white varieties – including 3 resistant hybrids –
- one rootstock
Vitadapt: Phenology 2012
Budbreak
Ranking of varieties by thermal sum at budbreak (2012)
Flowering dynamics
% of flowering as a function of time (mean per variety)
Vitadapt
Phenology 2011
Flowering
Ranking of varieties by date of mid-flowering (2011)
Vitadapt: Phenology 2011
Veraison
Ranking of varieties by date of veraison (2011)
Vitadapt: berry weight 2011
POIDS DE 100 BAIES MOYEN EN 2011 PAR CEPAGE
VitPhe: user’s interface
http://bioweb.supagro.inra.fr/vitphe/public/
Research needed in the future for
Systems Biology approach
• Additional mapping of the molecular
pathways
• Additional sequencing and annotation of
different grape genotypes, especially those
differing in important traits
• Functional testing of candidate genes to
validate the models and identify regulatory
genes for diagnostic assays, markerassisted breeding or clonal selection
Talk Conclusions
1) Identification of important genetic traits like
flavor profiles in specific varieties will be
enhanced by genome sequencing
2) Systems biology can be used for the
identification of molecular networks and their
regulatory components allowing for better
manipulation of grapevines and optimization of
fruit quality
3) International efforts are underway to build
resources to link genotype to phenotype
Acknowledgements
Ryan Ghan
Steve Van Sluyter
Jerome Grimplet
Danny Hopper
Delphine Vincent
Laurent Deluc
Supakan Rattanakon
Aaron Fait
Grant R. Cramer
Kassadee Ketelaar
Karen Schlauch
John C. Cushman
David Quilici
Paul Haynes
NSF Plant Genome Program
BARD Program
Ben-Gurion University of the Negev