All
experimental
work
starts
in
principle
with a
question.
This
also
applies
to
the
field
of
molecular
biology. A
molecular
scientist
is
using a
certain
technique
to
answer a
specific
question
such
as,
“Does
the
cell
produce
more
of a
given
protein
when
treated
in a
certain
way?
”
Questions
in
molecular
biology
are
indeed
regularly
focused
on
specific
proteins
or
genes,
often
because
the
applied
technique
cannot
measure
more.
Gene
expression
studies
that
make
use
of
microarrays
also
start
with a
biological
question.
The
largest
difference
to
many
other
molecular
biology
approaches
is,
however,
the
type
of
question
that
is
being
asked.
Scientists
will
typically
not
run
arrays
to
find
out
whether
the
expression
of a
specific
messenger
RNA
is
altered
in a
certain
condition.
More
often
they
will
focus
their
question
on
the
treatment
or
the
condition
of
interest.
Centering
the
question
on a
biological
phenomenon
or a
treatment
has
the
advantage
of
allowing
the
researcher
to
discover
hitherto
unknown
alterations.
On
the
other
hand,
it
poses
the
problem
that
one
needs
to
define
when
an“interesting”
alteration
occurs.
1.1
Why
gene
expression?
1.1.1
Biotechnological
advancements
Research
evolves
and
advances
not
only
through
the
compilation
of
knowledge
but
also
through
the
development
of
new
technologies.
Traditionally,
researchers
were
able
to
measure
only a
relatively
small
number
of
genes
at a
time.
The
emergence
of
microarrays
see
BioBox
1.1
now
allows
scientists
to
analyze
the
expression
of
many
genes
in a
single
experiment
quickly
and
efficiently.
1.1.2
Biological
relevance
Living
organisms
contain
information
on
how
to
develop
its
form
and
structure
and
how
to
build
the
tools
that
are
responsible
for
all
biological
processes
that
need
to
be
carried
out
by
the
organism.
This
information ?
the
genetic
content ?
is
encoded
in
information
units
referred
to
as
genes.
The
whole
set
of
genes
of
an
organism
is
referred
to
as
its
genome.
The
vast
majority
of
genomes
are
encoded
in
the
sequence
of
chemical
building
blocks
made
from
deoxyribonucleic
acid
DNA
and a
smaller
number
of
genomes
are
composed
of
ribonucleic
acid
RNA
,
e.g.
,
for
certain
types
of
viruses.
The
genetic
information
is
encoded
in a
specific
sequence
made
from
four
different
nucleotide
bases:
adenine,
cytosine,
guanine
and
thymine. A
slighlty
different
composition
of
building
blocks
is
present
in
mRNA
where
the
base
thymine
is
replaced
by
uracil.
Genetic
information
encoding
the
building
plan
for
proteins
is
transferred
from
DNA
to
mRNA
to
proteins.
The
gene
sequence
can
range
in
length
typically
between
hundreds
and
thousands
of
nucleotides
up
to
even
millions
of
bases.
The
number
of
genes
that
contain
protein-coding
information
is
expected
to
be
between
25,000
to
30,000
when
looking
at
the
human
genome. A
protein
is
made
by
constructing a
string
of
protein
building
blocks
amino
acids
.
The
order
of
the
amino
acids
in a
protein
matches
the
sequence
of
the
nucleotides
in
the
gene.
In
other
words,
messenger
RNA
interconnects
DNA
and
protein,
and
also
has
some
important
practical
advantages
compared
to
both
DNA
and
proteins
see
BioBox
1.2
.
Increasing
our
knowlegde
about
the
dynamics
of
the
genome
as
manifested
in
the
alterations
in
gene
expression
of a
cell
upon
treatment,
disease,
development
or
other
external
stimuli,
should
enable
us
to
transform
this
knowledge
into
better
tools
for
the
diagnosis
and
treatment
of
diseases.
DNA
is
made
of
two
strands
forming
together a
chemical
structure
that
is
called
“double
helix.
”
The
two
strands
are
connected
with
one
another
via
pairs
of
bases
that
form
hydrogen
bonds
between
both
strands.
Such
pairing
of
so-called
“complementary”
bases
occurs
only
between
certain
pairs.
tiontakesplacewheneverthecelldrawninlightredneedstomakeaproteindrawnaschainofreddots,and3mRNAtoproteinstranslationistheactualproteinsynthesisstepintheribosomesdrawningreen.Besidesthesegeneraltransfersthatoccurnormallyinmostcells,therearealsosomespecialinformationtransfersthatareknowntooccurinsomevirusesorinalaboratoryexperimentalsetting.
BioBox
1.2:
Central
dogma
of
molecular
biology
..........................................
Hydrogen
bonds
can
be
formed
between
cytosine
and
guanine
or
between
adenine
and
thymine.
The
pairing
of
the
two
strands
occurs
in a
process
called
“hybridization.
”
Compared
to
DNA,
mRNA
is
more
dynamic
and
less
redundant.
The
information
that
is
encoded
in
the
DNA
is
made
available
for
processing
in a
step
called
“gene
expression”
or
“transcription.
”
Gene
expression
is a
highly
complex
and
tightly
regulated
process
by
which a
working
copy
of
the
original
sequence
information
is
made.
This
allows a
cell
to
respond
dynamically
both
to
environmental
stimuli
and
to
its
own
changing
needs,
while
DNA
is
relatively
invariable.
Furthermore,
as
mRNA
constitutes
only
the
expressed
part
of
the
DNA,
it
focuses
more
directly
on
processes
underlying
biological
activity.
This
filtering
is
convenient
as
the
functionality
of
most
DNA
sequences
is
irrelevant
for
the
study
at
hand.
Compared
to
proteins,
mRNA
is
much
more
measurable.
Proteins
are
3D
conglomerates
of
multiple
molecules
and
cannot
benefit
from
the
hybridising
nature
of
the
base
pairs
in
the
2D,
single
molecule,
structure
of
mRNA
and
DNA.
Furthermore,
proteins
are
very
unstable
due
to
denaturation,
and
cannot
be
preserved
even
with
very
laborious
methods
for
sample
extraction
and
storage.
When
using
microarrays
to
study
alterations
in
gene
expression,
people
normally
will
only
want
to
study
the
types
of
RNA
that
code
for
proteins
?
the
messenger
RNA
mRNA
.
It
is
however
important
to
keep
in
mind
that
RNAnot
only
contains
mRNA?acopyofa
section
of
the
genomic
DNA
carrying
the
information
of
how
to
build
proteins.
Besides
the
code
for
the
synthesis
of
ribosomal
RNA,
there
are
other
non-coding
genes
that,
e.g.
,
contain
information
for
the
synthesis
of
RNA
molecules.
These
RNAs
have
different
functions
that
range
from
enzymatic
activities
to
regulating
transcription
of
mRNAs
and
translation
of
mRNA
sequences
to
proteins.
The
numbers
of
these
functional
RNAs
that
are
encoded
in
the
genome
are
not
known.
Initial
studies
looking
at
the
overall
transcriptional
activity
along
the
DNA
are
predicting
that
the
number
will
most
likely
be
larger
than
the
number
of
protein-coding
genes.
People
used
to
say
that a
large
portion
of
the
genomic
information
encoded
in
the
DNA
are
useless
“junk
DNA”
.
Over
the
last
years
scientific
evidence
has
accumulated
that a
large
proportion
of
the
genome
is
being
transcribed
into
RNAs
of
which a
small
portion
constitutes
messenger
RNAs.
All
these
other
non-coding
RNAs
are
divided
into
two
main
groups
depending
on
their
size.
While
short
RNAs
are
defined
to
have
sizes
below
200
bases,
the
long
RNAs
are
thought
to
be
mere
precursors
for
the
generation
of
small
RNAs,
of
which
the
function
is
currently
still
unknown ?
in
contrast
to
the
known
small
RNAs
such
as
microRNAs
or
siRNAs[6]
see
BioBox
1.3
for
an
overview
of
different
types
of
RNA
.
Microarrays
are
also
being
made
to
study
differences
in
abundance
of
these
kinds
of
RNA.
..........................................
In
this
book
we
will
focus
on
studying
mRNA.
However,
most
likely
many
remarks
given
on
the
experimental
design
and
the
data
analysis
will
apply
to
the
study
of
small
RNA
as
well.
1.2
Research
question
The
key
to
optimal
data
analysis
lies
in a
clear
formulation
of
the
research
question.
Being
aware
of
having
to
define
what
one
considers
to
be a
“relevant”
finding
in
the
data
analysis
step
will
help
in
asking
the
right
question
and
in
designing
the
experiment
properly
so
that
the
question
can
really
be
answered. A
well-thought-out
and
focused
research
question
leads
directly
into
hypotheses,
which
are
both
testable
and
measurable
by
proposed
experiments.
Furthermore, a
well-formulated
hypothesis
helps
to
choose
the
most
appropriate
test
statistic
out
of
the
plethora
of
available
statistical
procedures
and
helps
to
set
up
the
design
of
the
study
in a
carefully
considered
manner.
To
formulate
the
right
question,
one
needs
to
disentangle
the
research
topic
into
testable
hypotheses
and
to
put
it
in a
wider
framework
to
reflect
on
potentially
confounding
factors.
Some
of
the
most
commonly
used
study
designs
in
microarray
research
will
be
introduced
here
by
means
of
real-life
examples.
For
each
type
of
study,
research
questions
are
formulated
and
example
datasets
described.
These
datasets
will
be
used
troughout
the
book
to
illustrate
some
technical
and
statistical
issues.
1.2.1
Correlational
vs.
experimental
research
Microarray
research
can
either
be
correlational
or
experimental.
In
correlational
research,
scientists
generally
do
not
apply a
treatment
or
stimulus
to
provoke
an
effect
on,
e.g.
,
gene
expression
influence
variables
,
but
measure
them
and
look
for
correlations
with
mRNA
see
StatsBox
1.1
. A
typical
example
are
cohort
studies,
where
individuals
of
populations
with
specific
characteristics
like
diseased
patients
and
healthy
controls
are
sampled
and
analysed.
In
experimental
research,
scientists
manipulate
certain
variables
e.g.
,
apply a
compound
to a
cell
line
and
then
measure
the
effects
of
this
manipulation
on
mRNA.
Experiments
are
designed
studies
where
individuals
are
assigned
to
specifically
chosen
conditions,
and
mRNA
is
afterwards
collected
and
compared.
It
is
important
to
comprehend
that
only
experimental
data
can
conclusively
demonstrate
causal
relations
between
variables.
For
example,
if
we
found
that a
certain
treatment A
affects
the
expression
levels
of
gene
X,
then
we
can
conclude
that
treatment A
influences
the
expression
of
gene
X.
Data
from
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