2016 bioinformatics i_wim_vancriekinge_vupload
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2016 bioinformatics i_wim_vancriekinge_vupload
- 4. Lab for Bioinformatics and computational genomics Lab for Bioinformatics and computational genomics 10 “genome hackers” mostly engineers (statistics) 42 scientists technicians, geneticists, clinicians >100 people Hardware/software engineers, mathematicians, molecular biologists
- 5. Lab for Bioinformatics and computational genomics Dewpal
- 6. What is Bioinformatics ? • Application of information technology to the storage, management and analysis of biological information (Facilitated by the use of computers) – Sequence analysis? – Molecular modeling (HTX) ? – Phylogeny/evolution? – Ecology and population studies? – Medical informatics? – Image Analysis ? – Statistics ? AI ? – Sterkstroom of zwakstroom ?
- 7. • Medicine (Pharma) – Genome analysis allows the targeting of genetic diseases – The effect of a disease or of a therapeutic on RNA and protein levels can be elucidated – Knowledge of protein structure facilitates drug design – Understanding of genomic variation allows the tailoring of medical treatment to the individual’s genetic make- up • The same techniques can be applied to crop (Agro) and livestock improvement (Animal Health) Promises of genomics and bioinformatics
- 8. Bioinformatics: What’s in a name ? • Begin 1990’s • “Bio-informatics”: Computing Power Genbank (Log) Time (years)
- 9. Bioinformatics: What’s in a name ? • Begin 1990’s • “Bio-informatics”: – convergence of explosive growth in biotechnology, paralled by the explosive growth in information technology • Not new: > 30 years that people use “computers” in biology • In silico biology, database biology, ...
- 10. Time (years)
- 12. Happy Birthday …
- 13. PCR + dye termination Suddenly, a flash of insight caused him to pull the car off the road and stop. He awakened his friend dozing in the passenger seat and excitedly explained to her that he had hit upon a solution - not to his original problem, but to one of even greater significance. Kary Mullis had just conceived of a simple method for producing virtually unlimited copies of a specific DNA sequence in a test tube - the polymerase chain reaction (PCR)
- 14. Math Informatics Bioinformatics, a scientific discipline … Theoretical Biology Computational Biology (Molecular) Biology Computer Science Bioinformatics
- 15. Math Algorithm Development Informatics Interface Design Bioinformatics, a scientific discipline … AI, Image Analysis structure prediction (HTX) Theoretical Biology Sequence Analysis Computational Biology (Molecular) Biology Expert Annotation Computer Science NP Datamining Bioinformatics
- 16. Math Algorithm Development Informatics Interface Design Bioinformatics, a scientific discipline … AI, Image Analysis structure prediction (HTX) Theoretical Biology Sequence Analysis Computational Biology (Molecular) Biology Expert Annotation Computer Science NP Datamining Bioinformatics Discovery Informatics – Computational Genomics
- 17. Doel van de cursus • Meer dan een inleiding tot ... het is de bedoeling van de cursus een onderliggend inzicht te verschaffen achter de verschillende technieken. • Naast het gebruik van recepten, wat terug te vinden is in delen van de syllabus laat een inzicht in – de werking van databanken – en de achterliggende algoritmen • toe – om wisselende interfaces op nieuwe problemen toe te passen.
- 20. Examen • Theorie – Vier inzichtsvragen over de cursus (inclusief !!) • Practicum (“open-book”) – Viertal oefeningen die meestal het schrijven van een programma veronderstellen • Puntenverdeling 50/50
- 21. Cursus • Syllabus 30 Euro – Syllabus • V|Podcasts • Weblems – Screencasts
- 29. Genome Size DOGS: Database Of Genome Sizes E. coli = 4.2 x 106 Yeast = 18 x 106 Arabidopsis = 80 x 106 C.elegans = 100 x 106 Drosophila = 180 x 106 Human/Rat/Mouse = 3000 x 106 Lily = 300 000 x 106 With ... : 99.9 % To primates: 99%
- 31. Biological Research Adapted from John McPherson, OICR
- 32. And this is just the beginning …. Next Generation Sequencing is here
- 33. 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.
- 34. 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.
- 35. Next Generation Technologies • 454 –Emulsion PCR –Polymerase –Natural Nucleotides • 20-100Mb for 5-15k –1% error rate –Homopolymers
- 41. One additional insight ...
- 42. Read Length is Not As Important For Resequencing 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 8 10 12 14 16 18 20 Length of K-mer Reads (bp) %ofPairedK-merswithUniquely AssignableLocation E.COLI HUMAN Jay Shendure
- 43. Two Short Read Techologies • Illumina GA • ABI SOLID
- 44. Technology Overview: Solexa/Illumina Sequencing
- 51. ABI SOLID
- 52. ABI SOLID
- 56. Paired End Reads are Important! Repetitive DNA Unique DNA Single read maps to multiple positions Paired read maps uniquely Read 1 Read 2 Known Distance
- 57. Next next generation sequencing Third generation sequencing Now sequencing
- 60. Pacific Biosciences: A Third Generation Sequencing Technology Eid et al 2008
- 61. Pacific Biosciences: A Third Generation Sequencing Technology
- 63. The genome fits as an e-mail attachment
- 64. 107 106 105 104 103 102 101 1108109 Full genome bp G E N E T I C Whole-genome sequencing Enrichment seq (Exome) PCR Enrichment Targeted Panels Instrument and Assay providers CLIA Lab service providers
- 68. NXT GNT DXS • GNT – Dedicated Team & Network – Operational: Location – Professionalized • DXS – Content engine – Product 1 established – Pipeline for n+1 • NXT – Workflow management – Bioinformatics – Epigenetics
- 70. Weblems • What ? – Web-based problemes (over de huidige les en/of voorbereiding op volgende les) • When ? – Einde van elke les • How ? – Oplossingen online via screencasts – Practicum – Voorbedereiding op het practicum examen ... Niet alle problemen vereisen noodzakelijk programmacode ...
- 71. Weblems W1.1: To which phyla do the following species belong (a) starfish (b) ginko tree (c) scorpion W1.2: What are the common names for the following species (a) Orycterophus afer (b) Beta vulagaris (c) macrocystis pyrifera W1.3: What species has the smallest known genome ? And is genome size related to number of genes ? W1.4: What are the 5 latest genomes published ? How complete is “coverage” ? W1.5: For approximately 10% of europeans, the painkiller codeine is ineffective because the patients lack the enzyme that converts codeine into the active molecule, morphine. What is the most common mutation that causes this condition ?