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 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 Page of Genetic Code rakjkjkjo;oijiojiojlkstresskjklj8ioihlkkccoccurspianeknjaijibendoiqhuhSKJNBjkncszj knjntheakljijiohiuohnewkjnzxvleafoijoenjnwejnajnFJnjklasnknjkhaihiwioekka[zfanj erjh4nvthejiejiojaoijoiejajljakljeijiojawlightlaljioerjoijiosaj’ija’ijdfjap’iorrejoijglkbns mklnmkejaiofjijjkdaklmnvAkkjflkwhenlklkjtherelkjljkljklkjmklkaisjakljkjldkljdkljkld f;morelesslakkllkajlkfdjlasjkdjfakdjklofruij[jgijlightajdjiojh;oij;oijilkmakejjlakjdflkjjk jklakd[enmjlkaskdkjfklkdkfalskjflkjkljdslkfdjaljfkdajljfdksjfkllkjnklkflkaskjdfakdjflad lfjlakdsjfkjjfgkkkjjkdvkdlkajmorelessljkja;ljkljklredjlasjldfjk\fljdkljkljklcolorjkjkjkldj kljiinjinkljkljklandkjklajlkjdadkjklxjklwhiteajlfdkjlkjdlkjalkjaslkajdsfpetalslkjaslkdjfl kjaslkjkdskljadswhenakjdslkjlkjakljkljkljkwaterakjkjkjo;oijiojiojlkstresskjklj8ioihthe occurspianeknjaijibendoiqhuhSKJNBjkncszjknjntheakljijiohiuohnewkjnzxvleafoijoe njnwejnajnFJnjberrynawayjajiojojoijoijl;kjklklnkefroskinkjejnjknjknjkhaihiwioekka[ zfanjerjh4nvthejiejiojaoijoiejajljakljeijiojawlightlaljioerjoijiosaj’ija’ijkdljdfjap’iordfgj oi rejoijglkbnsmkljadshhurhdsljgflakjglkjalgjkajodioaij jnneiauukjflkajsfdioarjoiuiji kvnda’jahieelknblsuhkjkljklfjdslkjlakgjlakjgiriaiub kkdsjailujaoijjeoaijrjjijieijijieijjjjb jhjhjasdhfjhkdshmkejaiofjijjkdaklmnvkjkdsjklasjflkadjflkjsalkfjlkgjaslkjkljdfklasjlllllr lknjewiojokjldjlasjdlkfjaldkfjladksjflkjdfksjkjdskjfldjfdkjafoiib n/akjehuoe;ajjvjiijdfg ndfksjlsljdkjkjdfkjkflksdflkjdljsalkjfldjlfjdlsjflasfjlkfdslkjfljkjdfsnlkvmnkcxmjkjkjdljk kml’ksJOIjfrnwq htrlkgnr’pTtjhoi ghnlakmdf;kla ‘skf pofadskjdaiuievjjvjkp fjoiahgiuf hfnfokv flakjfd ‘poksdfmdfklmbvl;kamvl;kasldkrmvjriotq34htotwrneohn lyjjh ibjoirj mubhm jS”bdjfn jkNdjkfnadsz flkjvflkjz gljzfdlkj glzkjhgkjllsjllllkjdlhgjlhj lfkhj al’jdio gjwoijwoihdaljdfjsahkdhfjahsfkjh uhrqhg gdjjafkdjjdljafhshjfjsaijfladisjaioayaraesoi 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 • • • • • • 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