1 / 40

Economic Importance Of The Potato

Potato Genomics In Fredericton Dr. Barry Flinn Co-Lead Investigator - Genome Atlantic CPGP Research Director - Solanum Genomics International Inc. Economic Importance Of The Potato. Integral part of the diet of a large proportion of the world’s population.

barbaraleonard
Télécharger la présentation

Economic Importance Of The Potato

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Potato Genomics In FrederictonDr. Barry FlinnCo-Lead Investigator - Genome Atlantic CPGPResearch Director - Solanum Genomics International Inc.

  2. Economic Importance Of The Potato • Integral part of the diet of a large • proportion of the world’s population • Supplies at least 12 essential vitamins • and minerals • Still much unknown regarding the • control of potato development and • processing/quality traits • (ie. disease resistance, stress tolerance, carbohydrate metabolism, tuber shape)

  3. What Does Genomics Mean? • “Genomics” is a science that studies the genetic material • of a species at the molecular level • A scientific approach that seeks to identify and define • the function of genes, as well as uncover when and how • genes work together to produce traits • “Structural Genomics” approaches (mapping) generally • focus on traits controlled by one or a few genes, and • often only provide information regarding the location • of a gene or genes • We can examine the interrelationships and interactions • between thousands of genes How do we do this?

  4. Chromosome DNA Leaf Tuber Genome Organization

  5. DNA Gene 1Gene 2 Etc. ....TATACAGCAAAATAGAAAGATCTAGTGTCCCATGGCGATGAGTCGTGTAGCTTCT…. Genome Organization Promoter “Switch” Coding ORF “Message”

  6. Leaf Messages Tuber Messages cDNA Collections (Libraries) • Various tissues are collected from the plant, • and messages are extracted from each of these

  7. Leaf cDNA Tuber cDNA cDNA Collections (Libraries) • The messages are “copied” to form double- • stranded DNA copies (cDNA) of each message • Each copy is “glued” into a piece of bacterial DNA • for easier storage, handling and propagation, resulting • in a collection or “library” of cDNAs for each tissue

  8. cDNA Collections (Libraries) • The cDNAs are then read or “sequenced”, to give the • order of A’s, C’s, G’s or T’s for each • We are left with the sequence of each gene that is • active (expressed) in each cell, tissue or organ studies • These are “Expressed Sequence Tags” or ESTs • Using complex computer resources, these ESTs can • be analyzed and compared with known sequences • and proteins • Look for messages associated with specific organs or • characteristic/traits

  9. Take Home Points • Messages from various genes are important, as they • dictate which proteins are produced • Promoters are also important, as they dictate where • a specific message and protein is produced • “Genomics” involves the study of all of the • messages produced by the various plant cells • A lot of information which must be organized • and analyzed

  10. Project Description Identification Of A Differential Gene Expression Pattern And Genes Related To Resistance In Potato Late Blight • One of the most devastating disease of potato worldwide • If left unmanaged, complete destruction of crops can occur • Attacks leaves and tubers; large necrotic lesions on leaves • and dry rot that spreads through tubers; 2o bacterial and • fungi often infect through late blight lesions

  11. Late Blight Project • Collaborative effort withAAFC Potato Research Centre • Population of blight-sensitive and blight-resistant plants • of near isogenicity • cDNA libraries made from leaves of a blight-sensitive and • a blight resistant plant • 2500 messages were sequenced from each library • (5000 total ESTs) • Different ESTs to be profiled for expression • The tremendous amounts of data generated will need to be • managed efficiently

  12. Bioinformatics • Intranet Website • Database • Analysis Tools

  13. Links (IBM Patent, NCBI, PubMed, etc) Blast Search (on site) Sequence Manipulation Suite ClustalW Modifying Sequences Database Access SGII Intranet Website

  14. Database • Contains all the EST’s sequences • Contains useful annotations • Blast Searches • Contig Assemblies • Transmembrane Spanning Regions • Gel Pictures • EST Information

  15. Database

  16. Database - Sequence Info

  17. Database - Sequence Info

  18. Database - Sequence Info

  19. Data Analysis • Tens of thousands of ESTs available for study • Most methods to study message distributions are • low throughput AND time consuming • “Genomics” necessitates the large scale study of • gene expression How can we do this? Microarray Analysis

  20. Microarray Analysis

  21. Microarray Analysis

  22. Microarray Analysis

  23. Microarray Analysis - Processing ImageProcessing Data Normalization Analysis Differential Gene Expression Cluster Analysis Pathway Analysis

  24. Microarray Analysis - Processing

  25. Microarray Analysis - Processing Signal Background

  26. Microarray Analysis - Processing • Irregular size or shape • Irregular placement • Low intensity • Saturation • Spot variance • Background variance miss alignment artifact bad print indistinguishable saturated

  27. Microarray Analysis - Processing • Calculate numeric characteristics of each spot • Throw out spots that do not meet minimum requirements for each characteristic • Throw out spots that do not have minimum overall combined quality

  28. Microarray Analysis - Data Normalization • Normalize data to correct for variances • Dye bias • Location bias • Intensity bias • Pin bias • Slide bias • Control vs. non-control spots

  29. Microarray Analysis - Data Normalization • Assumptions • Overall mean average ratio should be 1 • Most genes are not differentially expressed • Total intensity of dyes are equivalent

  30. Microarray Analysis - Data Normalization (LOWESS)

  31. Microarray Analysis - Data Normalization Differential Gene Expression: • n-fold change • n typically >/= 2 • May hold no biological relevance • Often too restrictive • 2 expression • Calculate standard deviation  • Genes with expression more than 2 away are differentially expressed

  32. Microarray Analysis -Clustering • Cluster genes based on expression profiles • Gene expression across several treatments • Hypothesis: Genes with similar function have similar expression profiles

  33. Expression Profile Clustering

  34. Microarray Analysis - Data Management Project Database Engine

  35. Late Blight Project • cDNA Microarray Using SGII Clones • hybridized with Cy3 (resistant) + Cy5 (susceptible) probes • (reciprocal labelling experiments)

  36. Late Blight Project • cDNA Microarray Using SGII Clones • hybridized with Cy3 (resistant) + Cy5 (susceptible) probes • (reciprocal labelling experiments) ANDLBRLF02345HTF.01 - Class II chitinase ANDLBRLF01256HTF.01 - Pathogenesis-related protein P23 precursor ANDLBRLF02041HTF.01 - Unknown protein

  37. Top 5 Expression Profiles Clone ID Ratio Of BLAST Homology Resistant/Susceptible Expression 384 21.8 Pathogenesis-related protein PR-1 1256 19.9 Osmotin-like protein 857 11.3 Hypothetical protein 922 10.0 Unknown 2345 8.1 Class II chitinase Late Blight Project cDNA Microarray Using SGII Clones RT-PCR Using PR1-1 Primers MW S R

  38. What Use Is All Of This Information? • Transgenics: • - Enhance tuber quality, processing traits, disease • resistance, stress tolerance more rapidly than breeding • Expression Assisted Selection: • - Obtain expression profiles for thousands of genes • associated with specific traits or characteristics • - Use these profiles as a baseline to compare with • the expression profiles of unknown clones; crosses • New Protein Products : • - Identify genes encoding secreted proteins/ligands • - Test these for growth-promoting/other effects • - Express genes in batch cultures and purify proteins

  39. Example Of Gene Use GA-20 oxidase in potato: GFP expression in tobacco cells • GA-20 oxidase • knockouts with • enhanced tuber • production • GA-20 oxidase • knockouts with • reduced tuber • sprouting

  40. Information Processing and Handling • Assembly and annotation of genomic data • EST analysis and databases • Cluster analysis of microarray data • Comparisons of various transcriptomic methods • Integration of sequence, transcriptomic, proteomic, • metabolomic, transgenic data

More Related