Functional genomics uses genome-wide experimental approaches to assess gene function on a large scale. It analyzes gene expression through techniques like transcriptomics and proteomics. Transcriptomics analyzes gene expression profiles through RNA sequencing or microarray analysis. Microarray analysis involves hybridizing fluorescently-labeled cDNA or cRNA to microarrays containing DNA probes to measure gene expression levels across thousands of genes simultaneously. Functional genomics provides a global understanding of gene function and molecular interactions through integrated omics approaches.

1. Functional Genomics
Presented by:
Pawan Kumar (1101034)
Sumit Dahiya (1101020)
Arpan Pandey (1101058)
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Understand Gene function
Bhaskaracharya College of Applied Sciences (University of Delhi)
06March 2014

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3. Levels of Genome Research
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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.
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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
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7. Branch…
•Transcriptomics
•Proteomics.
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8. TranscriptomicsAnalysis
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• Study of transcriptomes (i.e. complete set of RNA
produced by genome at any one time)
• Provides gene expression profile.
• Gene expression identification.

9. Why study Transcriptomics…
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10. Exploratory studies
Which genes are differentially expressed?
Which genes are co-expressed?
Which genes interact
Which genes show alternative splicing?
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11. Prognostic studies
Which cancer has Patient X?
Is my drug safe for PatientY?
Which treatment is the most efficient?
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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. Requirements:
Database backed storage.
Specialized signal processing algorithms.
Dedicated analysis environment.
Additional knowledge about genes and transcripts
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14. Techniques…
PCR based methods.
DNA microarray analysis.
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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.
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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
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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
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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.
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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
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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.
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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.
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22. Nomenclature
Target Probe

23. +1
AAAAAA
TTTTTT - t7 promoter
Preparing target
TTTTTT - t7 promoter
reverse transcription
second strand synthesis
in vitro transcription

24. HowTo Do….
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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
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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
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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. Image Analysis…
• Image analysis..
• Translate the scan into
expression numbers.
• Queries...
• Check for defects.
• Quality metrics provided by
scanner.
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29. Bioinformatics of Microarrays
• Array design: choice of sequences
to be used as probes
• Analysis of scanned images
• Spot detection, normalization,
quantitation
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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.
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32. Benefits of using a data repository
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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. 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
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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)
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35. Software forTranscriptomic
Analysis
• Bio-Linux
• maxdView
• GeneSpring
• R/BioConductor
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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
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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
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39. Overview of Microarray Analysis
Steps
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Load Data
Apply Filters
Normalise
Analyse
Quality
Control
Step 1
Text,GPR file,
etc…
Step 2
Step 3
Step 4
Step 5

40. Gene Chips
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41.  Study of the proteome.
 The proteome is the complete complement of proteins found
in a complete genome or specific tissue.
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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
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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.
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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.
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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).
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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!
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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.
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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
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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!!!
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51. Mass
Spectrometry
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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
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53. Fragmentation Patterns
• Mass spectrum of 2-methylpentane
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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
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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?
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