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Functional genomics

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Functional genomics

  1. 1. Functional Genomics Presented by: Pawan Kumar (1101034) Sumit Dahiya (1101020) Arpan Pandey (1101058) PK 1 Understand Gene function Bhaskaracharya College of Applied Sciences (University of Delhi) 06March 2014
  2. 2. PK 2
  3. 3. Levels of Genome Research PK 3
  4. 4. Definition (1)- Hieter & Boguski 1997 The development & application of global • Genome-wide or • System-wide experimental approaches to assess gene function by making use of the information & reagents provides by structural genomics. It is characterized by high-throughput or large scale experimental methodology. • Combined with statistical or computational analysis of the results. PK 4
  5. 5. Definition (2) – UC Davis Genome Center A means of assessing phenotype differs from more classical approaches primarily with respect to The scale & automation of biological investigations A classical investigation works only fxal genomics can examine On a single gene. Over 1k-10k genes PK 5
  6. 6. PK 6
  7. 7. Branch… •Transcriptomics •Proteomics. PK 7
  8. 8. TranscriptomicsAnalysis PK 8 • Study of transcriptomes (i.e. complete set of RNA produced by genome at any one time) • Provides gene expression profile. • Gene expression identification.
  9. 9. Why study Transcriptomics… PK 9
  10. 10. Exploratory studies Which genes are differentially expressed? Which genes are co-expressed? Which genes interact Which genes show alternative splicing? PK 10
  11. 11. Prognostic studies Which cancer has Patient X? Is my drug safe for PatientY? Which treatment is the most efficient? PK 11
  12. 12. An integrated system is needed for functional genomics Profiles Transcript Genotype Proteome Metabolome Interactions DNA : Protein Protein : Protein Phenotypes High Throughput Screening Tissue Microarray Loss / Gain of Function Quantitative Trait Loci Bioinformatics
  13. 13. Requirements: Database backed storage. Specialized signal processing algorithms. Dedicated analysis environment. Additional knowledge about genes and transcripts PK 13
  14. 14. Techniques… PCR based methods. DNA microarray analysis. PK 14
  15. 15. Polymerase Chain Reaction • Developed in 1983 by Kary Mullis ,a biochemical technology in molecular biology used to amplify a single or a few copies of a piece of DNA across several orders of magnitude, generating thousands to millions of copies of a particular DNA sequence. PK 15
  16. 16. Uses • DNA cloning for sequencing. • DNA-based phylogeny, or functional analysis of genes. • Diagnosis of hereditary diseases. • Identification of genetic fingerprints. • PCR can be extensively modified to perform a wide array of genetic manipulations & hence may replace gene cloning completely PK 16
  17. 17. DNA MICROARRAY • A DNA microarray (aka DNA chip or biochip) is a collection of microscopic DNA spots attached to a solid surface. • can be used to detect DNA or RNA that may or may not be translated into proteins. • Expression Analysis/expression profiling which is a process of measuring gene expression via cDNA PK 17
  18. 18. MIAME ? • internationally adopted standard for the Minimal Information About a Microarray Experiment. • The result of an MGED (www.mged.org) driven effort to codify the description of a microarray experiment. • Ultimately, it tries to specify the collection of information that would be needed to allow somebody to completely reproduce an experiment that was performed elsewhere. PK 18
  19. 19. Six Parts of MIAME 1. Experimental design: the set of hybridization experiments as a whole 2. Array design: each array used and each element (spot, feature) on the array 3. Samples: samples used, extract preparation and labeling 4. Hybridizations: procedures and parameters 5. Measurements: images, quantification and specifications 6. Normalization controls: types, values and specifications PK 19
  20. 20. Principle • hybridization between two DNA strands. • A high number of complementary base pairs in a nucleotide sequence means tighter non-covalent bonding between the two strands. • Fluorescently labelled target sequences are used that bind to a probe sequence generate a signal that depends on the hybridization conditions, and washing after hybridization. • Total strength of the signal, from a spot, depends upon the amount of target sample binding to the probes present on that spot. • Microarrays use relative quantitation in which the intensity of a feature is compared to the intensity of the same feature under a different condition, and the identity of the feature is known by its position. PK 20
  21. 21. Platforms… • In standard microarrays, the probes are synthesized and then attached via surface engineering to a solid surface by a covalent bond to a chemical matrix. • The solid surface can be glass or a silicon chip, in which case they are colloquially known as an Affy-chip when an Affymetrix chip is used. • Other microarray platforms, such as Illumina, use microscopic beads, instead of the large solid support. PK 21
  22. 22. Nomenclature Target Probe
  23. 23. +1 AAAAAA TTTTTT - t7 promoter Preparing target TTTTTT - t7 promoter reverse transcription second strand synthesis in vitro transcription
  24. 24. HowTo Do…. PK 24
  25. 25. Scanning of arrays • Laser scanners • Excellent spatial resolution • Good sensitivity, but can bleach fluorochromes • Although slow • Charged couple device scanners • Spatial resolution can be a problem • Sensitivity easily adjustable (exposure time) • Faster and cheaper than lasers PK 25
  26. 26. Expression array • Cell growth in different environments, treatments etc. • Isolate RNA cDNAs • Measure expression using array technology • Create database of expression information • Data Analysis • Display information in an easy to-use format • Show ratio of expression under • Different conditions Affymetrix® food chip PK 26
  27. 27. • microRNA detection • Comparative Genomic Hybridization (CGH) detects deletions or amplifications of genomic sequence • ChIP on chip chromatin immunoprecipitation • Single Nucleotide Polymorphism screening (SNP) measures an individual’s genotype at known sites of variance • Cell Arrays • Protein Arrays • Tissue Arrays Other microarray-based assays
  28. 28. Image Analysis… • Image analysis.. • Translate the scan into expression numbers. • Queries... • Check for defects. • Quality metrics provided by scanner. PK 28
  29. 29. Bioinformatics of Microarrays • Array design: choice of sequences to be used as probes • Analysis of scanned images • Spot detection, normalization, quantitation PK 29
  30. 30. Primary analysis of hybridization data • Basic statistics, reproducibility, data scattering, etc. • Comparison of multiple samples • Clustering, SOMs (Self-Organizing Maps (a subtype of artificial neural network, low-dimensional views of high-dimensional data) • Unsupervised learning • Sample tracking and data basing of results. PK 30
  31. 31. PK 31
  32. 32. Benefits of using a data repository PK 32 Facilitates data sharing Catalogued / Backed-up Pervasive advertisement for your work End users/Researchers Access to data for analysis and algorithm development Improves search capabilities Encourages development of more capable software for annotation, analysis and submission Bioinformaticians/Developers
  33. 33. DATAWarehousing • The sheer volume of data, specialized formats (such as MIAME), and curtain efforts associated with the datasets require specialized databases to store the data. • Makes it easy to compare 2 Data files. • Easy to access. • User friendly. • Worldwide avalabilility PK 33
  34. 34. Microarray Data on the Web • Many groups have made their raw data available, but in many formats • Some groups have created searchable databases • There are several initiatives to create “unified” databases • EBI: Array Express • NCBI: Gene Expression Omnibus Companies are beginning to sell microarray expression data (e.g. Incyte) PK 34
  35. 35. Software forTranscriptomic Analysis • Bio-Linux • maxdView • GeneSpring • R/BioConductor PK 35
  36. 36. Which software should I use?? Commercial vs. Open Source GeneSpring maxdView R/BioConductor Ease of Use GeneSpring > maxdView > R/BioConductor Fine tuned control R/BioConductor > maxdView > GeneSpring PK 36
  37. 37. GeNet maxDLoad2 R/BioConductor ArrayExpress Raw Data Expression measures (not normalised) Proprietary software (e.g. Affymetrix) GeneSpring maxDViewR/BioConductor Quality Control Normalisation Analysis Presentation Other analysis programs MIAME/Env Annotation PK 37
  38. 38. PK 38
  39. 39. Overview of Microarray Analysis Steps PK 39 Load Data Apply Filters Normalise Analyse Quality Control Step 1 Text,GPR file, etc… Step 2 Step 3 Step 4 Step 5
  40. 40. Gene Chips PK 40
  41. 41.  Study of the proteome.  The proteome is the complete complement of proteins found in a complete genome or specific tissue. PK 41
  42. 42. Proteomics and genomics are inter-dependent Genome Sequence mRNA Primary Protein products Functional protein products Determination of gene Genomics Proteomics Proteomics Protein Fractionation 2-D Electrophoresis Protein Identification Post-Translational Modification PK 42
  43. 43. Aims of Proteomics • Detects the different proteins expressed by tissue, cell culture, or organism using 2-Dimensional Gel Electrophoresis • Stores the information in a database • Compares expression profiles between a healthy cell vs a diseased cell • The data comparison can then be used for testing and rational drug design. PK 43
  44. 44. Gel Electrophoresis • Motion of charged molecules in an electric field. • Polyacrylamide gel provides a porous matrix • (PAGE – Polyacrylamide Gel Electrophoresis) • Sample is stained with comassie blue to make it visible in the gel. • Sample placed in wells on the gel. PK 44
  45. 45. 2D – Separation is based on size and charge • First step is to separate based on charge or isoelectric point, called isoelectric focusing. • Then separate based on size (SDS-PAGE). PK 45
  46. 46. SDS-PAGE • Second Dimension. • Separation by size. • Run perpendicular to Isoelectric focusing. • The only unresolved proteins after the first and second dimensions are those proteins with the same size and same charge – rare! PK 46
  47. 47. PK 47
  48. 48. 2D-PAGE Analysis Software • 2D-PAGE technology has been in use for over 20 years, and potentially provides a vast amount of information about a protein sample. • However, due to difficulties with data analysis, it remains only partially exploited. PK 48
  49. 49. List of 2-D GEL DATABASES One can find an extensive list of such databases by following these links. We would discuss a few “Interesting ones”. •World 2-D PAGE •NCIFCRF •DEAMBULUM-Protein Databases •Ludwig Institute of Cancer Research •Phoretix PK 49
  50. 50. Try these links •http://www.2dgels.com/ •http://www.genomicglossaries.com/content/lifesciences_databasesdirectory.as p •http://www.expasy.ch/ch2d/2d-index.html •http://www.infobiogen.fr/services/deambulum/english/db4.html#GELS2D •http://www.bio-mol.unisi.it/2d/2d.html •http://biobase.dk/cgi-bin/celis •http://www.phoretix.com/customers/wl_2d_specific_sites.htm •http://sphinx.rug.ac.be:8080/ppmdb/index.html and then Time to chill!!! PK 50
  51. 51. Mass Spectrometry PK 51
  52. 52. Background • Mass spectrometry (Mass Spec or MS) uses high energy electrons to break a molecule into fragments. • Separation and analysis of the fragments provides information about: • Molecular weight • Structure PK 52
  53. 53. Fragmentation Patterns • Mass spectrum of 2-methylpentane PK 53
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  55. 55. References….. • Concept of genetics –Klug & Cummings, 10th edition • Perou, C.M., Sorlie,T., Eisen, M.B., van de Rijn, M., Jeffrey, S.S., Rees, C.A., Pollack, J.R., Ross, D.T., Johnsen, H., Akslen, L.A., Fluge, O., Pergamenschikov,A., Williams, C., Zhu, S.X., Lonning, P.E., Borresen-Dale, A.L., Brown, P.O., Bolstein, D. 2000. Molecular portraits of human breast tumors. Nature 406(6797):747-752. • http://www.bioinformatics.org/wiki/Microarray_analysis • http://www.bing.com/images/search?q=Microarray+Assay&FORM=RESTAB#a • http://www.nature.com/nrn/journal/v5/n10/images/nrn1518-f2.jpg • http://farm4.staticflickr.com/3045/2516660289_a92fd6dae7_z.jpg?zz=1 • http://www.bio.Davidson.edu/courses/genomics/chip/chip.html • http://Onlinelibrary.wiley.com/journal/10.1002/(ISSN)1615-9861 • http://www.genomics.aglent.com/article.jsp?pageld=287 • http://www.genome.gov/10000533 • http://en.Wikipedia.org/wiki/DNA_microarray PK 55
  56. 56. Questions….. • What is functional genomics? • What are the implications of functional genomics? • DefineTranscriptomics? • Name diff. tech. involved in transcriptome analysis? • Explain exploitation of DNA microarray in hybridization tech.? • How microarray database is different from microarray analysis? • What are the different tools for microarray analysis? • What is the need of microarray analysis? • Define Proteomics? • Explain various tech. involved in protein separation? PK 56

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