Transcript Document

Lecture 5
Post-genomics
Post-genomics
Post-genomics
Functional genomics
(A) Identifying genes from the sequence
(B) Gene expression profiling
(transcriptome)
(C) Model systems
Proteomics
Systems biology
(A) Hunting genes from the sequence
2 broad approaches
1) Ab initio method (computational)
2) Experimental method
1) Ab initio method (computational)
Scanning ORFs (open reading frames)
AAC
TAA
ATG
5’- ATGACGCATGATCGAGGAT –3’
3’ – TACTGCGTACTAGCTCCTA –5’
CTA
CCT
TCC
Ab initio method (computational)
 initiation or termination codons
 Codon bias found in specific species
Not all codons used at same frequency
e.g.human leucine mainly coded by CTG and
rarely by TTA or CTA
 Exon-intron boundaries (splice sites)
5’-AG GTAAGT-3’ hit and miss affair
 Upstream control sequences – e.g
conserved motifs in transcription factor
binding regions
 CpG islands
2) experimental method
Experimental evaluation based on the use of
transcribed RNA to locate exons and
entire genes from DNA fragment.
experimental method
Some strategies
 Hybridisation approaches – Northern
Blots, cDNA capture / cDNA select, Zoo
blots
 Transcript mapping: RT-PCR, exon
trapping etc
In this method, known DNA databases are
searched to find out whether the test
sequence is similar to any other known
genes, suggesting an evolutionary
relationship.
Northern Blot
Zoo Blot
(B) Gene expression profiling
Transcriptome
complete
collection
of
transcribed
elements of the genome (global mRNA
profiling)
transcriptome maps will provide clues on
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•
•
•
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Regions of transcription
Transcription factor binding sites
Sites of chromatin modification
Sites of DNA methylation
Chromosomal origins of replication
COMPUTATIONAL APPROACH
Homology searches (BLAST searches)
- Orthologous genes (homologues in
different organisms with common
ancestor) – comparative genomics
- Paralogous genes (genes in the same
organism, e.g. multigene families)
- orphan genes / families
The transcriptome
Analysed by DNA Microarrays
Advantages:
high-throughput information
Gene expression profile of
the cell/tissue
problems
false –positives
data analysis
Cost
Microarrays….
(a) Schematic drawing of a DNA chip.
Microarray
(chip)
(a) Schematic drawing of a DNA chip.
Microarray
(chip)
(a) Schematic drawing of a DNA chip.
Microarray
(chip)
Segment of
a chip
(a) Schematic drawing of a DNA chip.
Microarray
(chip)
Segment of
a chip
Spot containing copies
of a single DNA
molecule
(a) Schematic drawing of a DNA chip.
Microarray
(chip)
A
G
G
A
C
G
T
Segment of
a chip
Spot containing copies
of a single DNA
molecule
DNA
bases
Part of one
DNA strand
(b) The analysis of the hybridization process identifies
genes that respond in specific ways.
Cell samples are stabilized
and fluorescent labels
are added.
A
G
G
A
C
G
T
Examples
of reactions
G
G
G
A
C
T
A
chip DNA
A
A
T
T
C
G
C
A
A
T
T
C
G
C
Pair of
complementary
bases
A
G
G
A
C
G
T
Examples
of reactions
C G
C G
C G
G A
G C
A T
T A
chip DNA
cDNA
from
treated
cells
A T A
A T A
T A T
T A T
C G C
G C G
C G C
Pair of
complementary
bases
cCNA from
untreated
cells
T A
C G
C G
T A
G C
C G
A T
Examples
of reactions
C G
C G
C G
G A
G C
A T
T A
chip DNA
cDNA
from
treated
cells
T A T A
T A T A
A T A T
A T A T
G C G C
C G C G
G C G C
(c) Computer analysis of the binding of complementary
sequences can identify genes that respond to drug
treatment.
(c) Computer analysis of the binding of complementary
sequences can identify genes that respond to drug
treatment.
Gene that strongly increased
activity in treated cells
(c) Computer analysis of the binding of complementary
sequences can identify genes that respond to drug
treatment.
Gene that strongly increased
activity in treated cells
Gene that strongly decreased
activity in treated cells
(c) Computer analysis of the binding of complementary
sequences can identify genes that respond to drug
treatment.
Gene that strongly increased
activity in treated cells
Gene that strongly decreased
activity in treated cells
Gene that was equally active
in treated and untreated cells
(c) Computer analysis of the binding of complementary
sequences can identify genes that respond to drug
treatment.
Gene that strongly increased
activity in treated cells
Gene that strongly decreased
activity in treated cells
Gene that was equally active
in treated and untreated cells
Gene that was inactive
in both groups
High-throughput microarrays
MODEL SYSTEMS
gene inactivation methods
(knockouts, RNAi, sitedirected mutagenesis,
transposon tagging, genetic
footprinting etc)
Gene overexpression methods
(knock-ins, transgenics,
reporter genes)
RNAi
RNAi mimics loss-offunction mutations
Non-inheritable
Lack of reproducibility
How does RNAi work?
http://www.nature.com/focus/rnai/animations/
index.html
MODEL SYSTEMS
Gene overexpression methods (knock-ins,
transgenics, reporter genes etc)
Proteomics
Analysis of protein expression
Protein structure and function
Protein-protein interactions
Nature (2003) March 13: Insight articles from pg 194
Proteomics
Proteome projects - co-ordinated by the HUPO
(Human Protein Organisation)
Involve protein biochemistry on a highthroughput scale
Problems
limited and variable sample material,
sample degradation,
abundance,
post-translational modifications,
huge tissue, developmental and temporal
specificity as well as disease and drug
influences.
Nature (2003) March 13: Insight articles from pgs 191-197.
Approaches in proteomics
High throughput approach
1) Mass- spectrometry
2) Array based proteomics
3) Structural proteomics
Nature (2003) March 13: Insight articles from pgs 191-197.
High throughput approaches in proteomics
1) Mass spectrometry-based proteomics:
Nobel prize in Chemistry (2002)
John B. Fenn
Koichi Tanaka
Kurt Wüthrich
"for the development of methods for identification and structure
analyses of biological macromolecules"
"for their development of soft desorption ionisation methods for mass
spectrometric analyses of biological macromolecules"
"for his development of nuclear magnetic resonance spectroscopy for
determining the three-dimensional structure of biological
High throughput approaches in proteomics
1) Mass spectrometry-based proteomics:
relies on the discovery of protein
ionisation techniques.
used for
 protein identification and
quantification,
 profiling,
 protein interactions and
 modifications.
Nature (2003) March 13: Insight articles from pgs 191-197
Identification of proteins in complex
mixtures
two dimensional gels and mass spectrometry
two dimensional gels
19_09.jpg
Mass spectrometry (MS)
Nature (2003) March 13: Insight articles from pgs 191-197
Principle of MS
ionizer source: converts analyte to gaseous ions
mass analyser: measures mass-to-charge ratio
(m/z)
detector: registers the number of ions at each m/z
Types of ionizer sources
Electrospray ionisation (ESI)
matrix-assisted laser desortion/ionisation
(MALDI)
MALDI-MS - simple peptide mixtures whereas
ESI-MS - for complex samples.
Nature (2003) March 13: Insight articles from pgs 191-197.
2) Array-based proteomics
Based on the cloning and amplification of
identified ORFs into
homologous (ideally used for bacterial and
yeast proteins) or sometimes
heterologous systems (insect cells which
result in post-translational
modifications similar to mammalian
cells).
A fusion tag (short peptide or protein
domain that is linked to each protein
member e.g. GST) is incorporated
into the plasmid construct.
Nature (2003) March 13: Insight articles from pgs 191-197.
Array based proteomics….
a. Protein expression and purification
b. Protein activity: Analysis can be done using
biochemical genomics or
functional protein microarrays.
c. Protein interaction analysis
two-hybrid analysis (yeast 2-hybrid),
FRET (Fluorescence resonance energy
transfer),
phage display etc
d. Protein localisation:
immunolocalisation of epitope-tagged
products.
E.g the use of GFP or luciferase tags
Nature (2003) March 13: Insight articles from pgs 191-197.
Array based proteomics….
Protein chips
Antibody chips – arrayed antibodies
Antigen chips – arrayed antigens
Functional arrays – arrayed proteins
Protein capture chips – arrayed capture
agents that interact with proteins e.g.
BIAcore
Solution arrays – nanoparticles
Nature (2003) March 13: Insight articles from pgs 191-197.
3) Structural proteomics
8HDF / MTHF?
19_14.jpg
FAD
Modelling of a novel photolyase based on sequence
Winnie Wu
Identification of proteinprotein interactions
affinity capture/mass
spectrometry
Fig. 10. 31
Identification of protein-protein interactions
Phage display
Fig. 10.32
Systems Biology
the global study of multiple components of
biological systems and their interactions
New approaches to studying biological systems
– Sequencing genomes
– High-throughput platform development
– Development of powerful computational
tools
– The use of model organisms
– Comparative genomics
19_20.jpg
Six steps in systems approach
• Formulate computer based model for the system
• Discovery science to define as many of the
system’s elements as possible
• Perturb the system genetically or
environmentally
• Integrating levels of information from
perturbations
• Formulate hypothesis to explain disparities
between model and experimental data
• Refine the model after integrating data
Systems biology approach to studying how Halobacterium
NRC-1 transcriptome responds to uv radiation
Nitin S. Baliga et al. Genome Res. 2004; 14: 1025-1035
Challenges for the future – ‘physiome’?
Nature Reviews Molecular Cell Biology 4; 237-243 (2003)
• General Reading
– Chapter 19- HMG3 by Strachan and Read
• Reference
• - Nature (13 March 2003). Proteomics
insight articles from Vol. 422, No. 6928 pgs
191-197