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Genomics experimental-methods
 

Genomics experimental-methods

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Genomics: experimental methods

Genomics: experimental methods

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    Genomics experimental-methods Genomics experimental-methods Presentation Transcript

    • Genomics: Experimental methods Slides available www.bioinformatics.be
    • Lab for Bioinformatics and computational genomics 10 “genome hackers” mostly engineers (statistics) 42 scientists technicians, geneticists, clinicians >100 people hardware engineers, mathematicians, molecular biologists
    • Overview Personalized Medicine, Biomarkers … … Molecular Profiling First Generation Molecular Profiling Next Generation Molecular Profiling Next Generation Epigenetic Profiling Concluding Remarks
    • Overview Personalized Medicine, Biomarkers … … Molecular Profiling First Generation Molecular Profiling Next Generation Molecular Profiling Next Generation Epigenetic Profiling Concluding Remarks
    • Personalized Medicine • The use of diagnostic tests (aka biomarkers) to identify in advance which patients are likely to respond well to a therapy • The benefits of this approach are to – avoid adverse drug reactions – improve efficacy – adjust the dose to suit the patient – differentiate a product in a competitive market – meet future legal or regulatory requirements • Potential uses of biomarkers – Risk assessment – Initial/early detection – Prognosis – Prediction/therapy selection – Response assessment – Monitoring for recurrence
    • Biomarker First used in 1971 … An objective and « predictive » measure … at the molecular level … of normal and pathogenic processes and responses to therapeutic interventions Characteristic that is objectively measured and evaluated as an indicator of normal biologic or pathogenic processes or pharmacologic response to a drug A biomarker is valid if: – It can be measured in a test system with well established performance characteristics – Evidence for its clinical significance has been established
    • Rationale 1: Why now ? Regulatory path becoming more clear There is more at stake than efficient drug development. FDA « critical path initiative » Pharmacogenomics guideline Biomarkers are the foundation of « evidence based medicine » - who should be treated, how and with what. Without Biomarkers advances in targeted therapy will be limited and treatment remain largely emperical. It is imperative that Biomarker development be accelarated along with therapeutics
    • Why now ? First and maturing second generation molecular profiling methodologies allow to stratify clinical trial participants to include those most likely to benefit from the drug candidate—and exclude those who likely will not—pharmacogenomicsbased Clinical trials should attain more specific results with smaller numbers of patients. Smaller numbers mean fewer costs (factor 2-10) An additional benefit for trial participants and internal review boards (IRBs) is that stratification, given the correct biomarker, may reduce or eliminate adverse events.
    • Molecular Profiling The study of specific patterns (fingerprints) of proteins, DNA, and/or mRNA and how these patterns correlate with an individual's physical characteristics or symptoms of disease.
    • Generic Health advice • Exercise (Hypertrophic Cardiomyopathy) • Drink your milk (MCM6 Lactose intolarance) • Eat your green beans (glucose-6-phosphate dehydrogenase Deficiency) • & your grains (HLA-DQ2 – Celiac disease) • & your iron (HFE - Hemochromatosis) • Get more rest (HLA-DR2 - Narcolepsy)
    • Generic Health advice (UNLESS) • Exercise (Hypertrophic Cardiomyopathy) • Drink your milk (MCM6 Lactose intolarance) • Eat your green beans (glucose-6-phosphate dehydrogenase Deficiency) • & your grains (HLA-DQ2 – Celiac disease) • & your iron (HFE - Hemochromatosis) • Get more rest (HLA-DR2 - Narcolepsy)
    • Generic Health advice (UNLESS) • Exercise (Hypertrophic Cardiomyopathy) • Drink your milk (MCM6 Lactose intolerance) • Eat your green beans (glucose-6-phosphate dehydrogenase Deficiency) • & your grains (HLA-DQ2 – Celiac disease) • & your iron (HFE - Hemochromatosis) • Get more rest (HLA-DR2 - Narcolepsy)
    • Generic Health advice (UNLESS) • Exercise (Hypertrophic Cardiomyopathy) • Drink your milk (MCM6 Lactose intolerance) • Eat your green beans (glucose-6-phosphate dehydrogenase Deficiency) • & your grains (HLA-DQ2 – Celiac disease) • & your iron (HFE - Hemochromatosis) • Get more rest (HLA-DR2 - Narcolepsy)
    • EGFR based therapy in mCRC
    • Overview Personalized Medicine, Biomarkers … … Molecular Profiling First Generation Molecular Profiling Next Generation Molecular Profiling Next Generation Epigenetic Profiling Concluding Remarks
    • Before molecular profiling …
    • Before molecular profiling …
    • Before molecular profiling …
    • First Generation Molecular Profiling • Flow cytometry correlates surface markers, cell size and other parameters • Circulating tumor cell assays (CTC’s) quantitate the number of tumor cells in the peripheral blood. • Exosomes are 30-90 nm vesicles secreted by a wide range of mammalian cell types. • Immunohistochemistry (IHC) measures protein expression, usually on the cell surface.
    • First Generation Molecular Profiling • Gene sequencing for mutation detection • Microarray for m-RNA message detection • RT-PCR for gene expression • FISH analysis for gene copy number • Comparative Genome Hybridization (CGH) for gene copy number
    • Basics of the ―old‖ technology • Clone the DNA. • Generate a ladder of labeled (colored) molecules that are different by 1 nucleotide. • Separate mixture on some matrix. • Detect fluorochrome by laser. • Interpret peaks as string of DNA. • Strings are 500 to 1,000 letters long • 1 machine generates 57,000 nucleotides/run • Assemble all strings into a genome.
    • Genetic Variation Among People Single nucleotide polymorphisms (SNPs) GATTTAGATCGCGATAGAG GATTTAGATCTCGATAGAG 0.1% difference among people
    • The genome fits as an e-mail attachment
    • First Generation Molecular Profiling • Gene sequencing for mutation detection • Microarray for m-RNA message detection • RT-PCR for gene expression • FISH analysis for gene copy number • Comparative Genome Hybridization (CGH) for gene copy number
    • mRNA Expression Microarray
    • First Generation Molecular Profiling • Gene sequencing for mutation detection • Microarray for m-RNA message detection • RT-PCR for gene expression • FISH analysis for gene copy number • Comparative Genome Hybridization (CGH) for gene copy number
    • Overview Personalized Medicine, Biomarkers … … Molecular Profiling First Generation Molecular Profiling Next Generation Molecular Profiling Next Generation Epigenetic Profiling Concluding Remarks
    • Basics of the ―new‖ technology • Get DNA. • Attach it to something. • Extend and amplify signal with some color scheme. • Detect fluorochrome by microscopy. • Interpret series of spots as short strings of DNA. • Strings are 30-300 letters long • Multiple images are interpreted as 0.4 to 1.2 GB/run (1,200,000,000 letters/day). • Map or align strings to one or many genome.
    • Next Generation Technologies • Roche (454) –Emulsion PCR –Polymerase –Natural Nucleotides • 100-500 Mb for 5-15k –1% error rate –Homopolymers
    • One additional insight ...
    • % of Paired K-mers with Uniquely Assignable Location Read Length is Not As Important For Resequencing 100% 90% 80% 70% 60% E.COLI 50% HUMAN 40% 30% 20% 10% 0% 8 Jay Shendure 10 12 14 16 18 20 Length of K-mer Reads (bp)
    • Short Read Techologies • Illumina GA (HiSeq, MySeq) • ABI SOLID
    • Other second generation technology: (ABI) SOLID
    • So what ?
    • Second generation DNA/RNA profiling
    • Second Generation DNA profiling • Enrichment Sequencing • ChIP-Seq (Chromosome Immunoprecipitation) • A substitute for ChIP-chip • Eg. to find the binding sequence of proteins (TFBS)
    • Paired End Reads are Important! Known Distance Repetitive DNA Read 1Unique DNA 2 Read Single read maps to multiple positions
    • Paired End Reads are Important! Known Distance Repetitive DNA Read 1Unique DNA 2 Read Single read maps to multiple positions
    • Second Generation DNA profiling • Exome Sequencing (aka known as targeted exome capture) is an efficient strategy to selectively sequence the coding regions of the genome to identify novel genes associated with rare and common disorders. • 160K exons
    • Second Generation DNA profiling
    • Second Generation DNA profiling
    • Bioinformatics tools
    • Bioinformatics tools
    • Second Generation RNA profiling Besides the 6000 protein coding-genes … 140 ribosomal RNA genes 275 transfer RNA gnes 40 small nuclear RNA genes >100 small nucleolar genes Contents-Schedule Function of RNA genes pRNA in 29 rotary packaging motor (Simpson et el. Nature 408:745-750,2000) Cartilage-hair hypoplasmia mapped to an RNA (Ridanpoa et al. Cell 104:195-203,2001) The human Prader-Willi ciritical region (Cavaille et al. PNAS 97:14035-7, 2000)
    • Second Generation RNA profiling RNA genes can be hard to detects UGAGGUAGUAGGUUGUAUAGU C.elegans let-27; 21 nt (Pasquinelli et al. Nature 408:86-89,2000) Often small Sometimes multicopy and redundant Often not polyadenylated (not represented in ESTs) Immune to frameshift and nonsense mutations No open reading frame, no codon bias Often evolving rapidly in primary sequence
    • Second Generation RNA profiling Although details of the methods vary, the concept behind RNA-seq is simple: • isolate all mRNA • convert to cDNA using reverse transcriptase • sequence the cDNA • map sequences to the genome The more times a given sequence is detected, the more abundantly transcribed it is. If enough sequences are generated, a comprehensive and quantitative view of the entire transcriptome of an organism or tissue can be obtained.
    • Second Generation RNA profiling • Comparing to microarray – Microarray • Closed technology: Prior knowledge required • Affected by pseudo-genes (homologous of real genes) • Low sensitivity – RNA-Seq • Open technology: No prior knowledge required • Not affected by pseudo-genes because exact sequence is measured • Other information could be yielded (SNP, Alternative splicing)
    • ncRNAs in human genome tRNA 18S rRNA 5.8S rRNA 28S rRNA 5S rRNA snoRNA miRNA U1 U2 U4 U5 U6 U4atac U6atac U11 U12 600 200 200 200 200 300 250 40 30 30 30 20 5 5 5 5 SRP RNA 1 RNase P RNA 1 Telomerase RNA 1 RNase MRP 1 Y RNA 5 Vault 4 7SK RNA 1 Xist 1 H19 1 BIC 1 Antisense RNAs 1000s? Cis reg regions Others 100s? ?
    • Mapping Structural Variation in Humans >1 kb segments - Thought to be Common 12% of the genome (Redon et al. 2006) - Likely involved in phenotype variation and disease CNVs - Until recently most methods for detection were low resolution (>50 kb)
    • Size Distribution of CNV in a Human Genome
    • Next next generation sequencing Third generation sequencing Now sequencing
    • Ultra-low-cost SINGLE molecule sequencing
    • Pacific Biosciences: A Third Generation Sequencing Technology Eid et al 2008
    • Complete genomics
    • Nanopore Sequencing
    • Second Generation Protein profiling • Proteomics MS-MS-based exclusively in discovery mode • Automate diagnostics assay generation (next generation proteomics) • Aptamers as alternative to antibodies • ImmunoPCR
    • MS/MS identification pipeline pipeline overview Bonanza Bonanza + IggyPep Goal filter dataset prior to database Goal search define PTMs profile prior to database search Goal multi-tiered database search
    • Second Generation Protein profiling • Proteomics MS-MS-based exclusively in discovery mode • Automate diagnostics assay generation (next generation proteomics) • Aptamers as alternative to antibodies • ImmunoPCR
    • Overview Personalized Medicine, Biomarkers … … Molecular Profiling First Generation Molecular Profiling Next Generation Molecular Profiling Next Generation Epigenetic Profiling Concluding Remarks
    • Genome-wide methylation …. by next generation sequencing # markers 3 000 000 MethylCap_Seq 6 000 EpiHealth 50 Deep_Seq 5 Discovery <50 only models and fresh frozen Verification Validation > 50 # samples CONFIDENTIAL
    • Molecular Unification E P I Whole-genome Bisulphite seq G E N E T I C Whole-genome sequencing Enrichment seq (MBD, RRBS) Probes (450-27K) Ultra Deep Enrichment Targeted Panels Enrichment seq (Exome) Enrichment Targeted Panels Deep Seq bp Full genome 109 108 RUO 107 106 105 104 103 Sequencing 102 101 1 Clinical CONFIDENTIAL
    • Overview Personalized Medicine, Biomarkers … … Molecular Profiling First Generation Molecular Profiling Next Generation Molecular Profiling Next Generation Epigenetic Profiling Concluding Remarks
    • Bioinformatics, a life science discipline … Math Informatics (Molecular) Biology
    • Bioinformatics, a life science discipline … Math Computer Science Theoretical Biology Informatics Computational Biology (Molecular) Biology
    • Bioinformatics, a life science discipline … Math Theoretical Biology Computer Science Bioinformatics Informatics Computational Biology (Molecular) Biology
    • Bioinformatics, a life science discipline … management of expectations Math Theoretical Biology Computer Science NP Datamining AI, Image Analysis structure prediction (HTX) Bioinformatics Interface Design Expert Annotation Sequence Analysis Informatics Computational Biology (Molecular) Biology
    • Bioinformatics, a life science discipline … management of expectations Math Theoretical Biology Computer Science NP Datamining AI, Image Analysis structure prediction (HTX) Bioinformatics Discovery Informatics – Computational Genomics Interface Design Expert Annotation Sequence Analysis Informatics Computational Biology (Molecular) Biology
    • Translational Medicine: An inconvenient truth • 1% of genome codes for proteins, however more than 90% is transcribed • Less than 10% of protein experimentally measured can be ―explained‖ from the genome • 1 genome ? Structural variation • > 200 Epigenomes ?? • Space/time continuum …
    • Translational Medicine: An inconvenient truth • 1% of genome codes for proteins, however more than 90% is transcribed • Less than 10% of protein experimentally measured can be ―explained‖ from the genome • 1 genome ? Structural variation • > 200 Epigenomes … • ―space/time‖ continuum
    • Cellular programming Epigenetic (meta)information = stem cells
    • Cellular reprogramming Tumor Tumor Development and Growth Epigenetically altered, selfrenewing cancer stem cells
    • Cellular reprogramming Gene-specific Epigenetic reprogramming
    • Wobblebase Mission provide tools to both specialists (researchers, bioinformaticians, health care providers) and individual consumers that unlock the power of genomic data to the USER enable personalized genomics today by simplifying the way we organize, visualize and manage genomic data.
    • PGM: Personal Genomics Manifesto Everybody who wants to get his genome sequenced has the human right to do so. No third party can own your genetic data, your genetic data is exclusively yours. Nobody can be forced to get his genome analyzed or to reveal his genome to a third party. Your genome should allways be treated as confidential, private information. People should be advised not to share their identity AND their entire genome on a public forum. People should be advised to use secure technologies that allow to maximally protect phenotypic and/or genotype data. People should be able to actively explore, manage and get updated interpretation on their genomic data.
    • Wobblebase Mission • change the diagnostic/healthcare industry forever by setting a new standard and empowering the user
    • Choosing the Red Pill The Technical Feasibility Argument The Quality Argument The Price Argument The Logistics around the sample on howto manage the data Argument The Ethical debate The Privacy/Security concern
    • Notifications Updates are the single moste important feature of Wobblebase
    • #Rs1805007
    • Bioinformatics Analysis pipelines Social network twitter Wobblebase Updates Notifications eHealth (fixed vocabulary) Comparison
    • biobix wvcrieki biobix.be bioinformatics.be 108