Transcript BiGCaT

Toxicology in the omics era.
Chris Evelo
BiGCaT Bioinformatics Group – BMT-TU/e & UM
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Gene expression
Genes are part of the chromosomes in
the cell nucleus.
 Genes are transcribed to messenger
RNA (mRNA).
 mRNA is processed further in the
nucleus.
 Complete mRNA’s leave the nucleus and
are translated to protein in the cytosol.
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Figure 3-15. The transfer of information from DNA to protein. The transfer proceeds by means of an
RNA intermediate called messenger RNA (mRNA). In procaryotic cells the process is simpler than in
eucaryotic cells. In eucaryotes the coding regions of the DNA (in the exons,shown in color) are separated by
noncoding regions (the introns). As indicated, these introns must be removed by an enzymatically catalyzed
RNA-splicing reaction to form the mRNA.
Alberts et al. Molecular Biology of the Cell, 3rd edn.
mRNA processing
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Genes contain:
– Expressed regions (exons)
– Non expressed regions (introns)
During gene splicing introns are
removed and exons connected
 A poly-adenosine (poly-A) tail is added
 Complete mRNA’s leave the nucleus
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Figure 9-87. Control of the poly-A tail length affects both mRNA stability and mRNA translation. (A)
Most translated mRNAs have poly-A tails that exceed a minimum length of about 30 As. The tails on selected
mRNAs can be either elongated or rapidly cleaved in the cytosol, and this will have an effect on the
translation of these mRNAs. (B) A model proposed to explain the observed stimulation of translation by an
increase in poly-A tail length. The large ribosomal subunits, on finishing a protein chain, may be directly
recycled from near the 3' end of an mRNA molecule back to the 5' end to start a new protein by special polyA-binding proteins (red).
Alberts et al. Molecular Biology of the Cell, 3rd edn.
Genes and vulnerability
Genes can be:
 Absent (e.g. GST mu deletion)
 Broken (e.g. single nucleotide point
mutations SNP’s)
 Differently expressed (e.g. P450
class of enzymes)
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Intra individual differences (vulnerability)
As a result of exposure (BEM)
What about the human genome?
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Smart people copied chromosomal
sequences to computer hard discs.
So now you can read it (although I still
prefer a good novel).
If you are good at it (and care to read it 6
times over) you can even predict genes.
But even if you are among the best you
can’t predict proteins or their function
Tell me about your proteins
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Hard working biochemists and physiologists
did spend a century
to describe proteins, their function, structure and
sequence.
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Molecular biologists
used decades
found huge amounts of expressed mRNA sequences
(ESTs) and tried to relate them to function.
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And…
they failed.
Cluttering up the databases with things like “EST found
in very seldom tumor so and so” (this could still be
myoglobin mRNA)
So what can we do?
Take the EST sequences and cluster them to
full mRNA sequences (Unigene!)
 Build the full coding sequences from this
(useful part of EMBL)
 Translate that into hypothetical proteins
(trEMBL)
 Check whether that happens to be a known
protein (Swissprot)
 Use all that to find microarray reporter
sequences for known proteins
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DNA useful after all?
Yes, if you know from population genetics or
animal experiments about loci important for
trades. Your gene might be in such a locus.
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And to find regulatory sequences
Past, present and
(near) future
Toxicologists detect:
 Enzyme activity; classic clinical
chemistry.
 Single gene DNA identity, PCR.
 Single gene expression at the mRNA
level (RT-PCR)
 Transcriptomics. Full genome mRNA
expression (microarray, expression
libraries)
 Proteomics. Full genome protein
expression (proteomics, 2D-gels with
MS, antibody arrays)
Gene expression measurement
DNA  mRNA  protein
Functional genomics/transcriptomics:
Changes in mRNA
– Gene expression microarrays
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Proteomics:
Changes in protein levels
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Gene expression arrays
Microarrays: relative
fluorescense signals.
Identification.
Macroarrays: absolute
radioactive signal.
Validation.
Gene expression microarrays
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Contain many immobilized unique cDNA
sequences (20,000)
Sample mRNA is transcribed to
complementary DNA (cDNA)
Sample cDNA is made fluorescent using
2 different dyes
cDNA’s will bind (hybridize) specifically
to their own complementary spotted
cDNA
Fluorescence is read using laser
technology
Layout of a microarray experiment
1) Get the cells
2) Isolate RNA
3) Make fluorescent
cDNA
4) Hybridize
5) Laser read out
6) Analyze image
Next slide shows data of one
single actual microarray
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Normalized expression shown for both
channels.
Each reporter is shown with a single dot.
Red dots are controls
Note the GEM barcode (QC)
Note the slight error in linear
normalization (low expressed genes are
higher in Cy5 channel)
Next slide shows same data
after processing
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Controls removed
Bad spots (<40% average area)
removed
Low signals (<2.5 Signal/Background)
removed
All reporters with <1.7 fold change
removed (only changing spots shown)
Final slide shows information
for one single reporter
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This signifies one single spot
It is a known gene:
an UDP glucuronyltransferase
Raw data and fold change are
shown
Microarrays can detect
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Differences in mRNA expression (that’s
what they were made for)
– Can compare the individual to “the
population”
– Or “the exposed group” with the “control
group”
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Gene deletions
SNP’s (single nucleotide point mutations)
We could now
Isolate mRNA from an individuals
white blood cells.
 Run a 10,000 gene mRNA
expression array
 Put the results on a personal
microchip or CD-ROM
 And know his vulnerabilities
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And we could
Sell the results to his insurance
company…
Are you ready?
Are you ready to hop on the
genomics wagon?
It may be a bit awkward
But you will have to…
Hop, Step and … Jump
Slides will be made available at:
http://www.BiGCaT.nl