BTN Protocol Guide-08

Bio-Rad Laboratories
| PCR
Life Science Group
Real-Time PCR
2000 Alfred Nobel Drive
Hercules, CA 94547
1-800-4BIORAD (1-800-424-6723)
For Product Technical Support: lsg_techserv_us@bio-rad.com
For Literature Request: lsg_literature_request@bio-rad.com
www.discover.bio-rad.com
Normalization Methods for qPCR
Real-time PCR has been used for gene expression analysis for over a housekeeping genes may be expressed at variable levels within an
decade (Heid et al. 1996, Higuchi et al. 1992). Most gene expression experimental system.
assays are based on comparing two or more samples, and require
uniform sampling conditions for valid comparisons. Many factors A more accurate normalization strategy has been proposed by
can contribute to variability in sample analysis, making experimental Vandesompele et al. (2002). They proposed selecting a set of genes
results difﬁ cult to reproduce. Variability is most often related to that display minimal variation across the treatment, determining the
events upstream of the qPCR assay—namely, the quantity and geometric mean, and normalizing the target gene(s) to this geometric
quality of the extracted sample and reverse-transcription efﬁ ciency mean. Figure 3 shows the expression levels of four genes in HeLa
(Fleige and Pfafﬂ 2006). Two methods of sample normalization for cells across ﬁ ve treatments, as calculated by multiple reference
accurate comparison between genes of interest are normalizing to gene normalization.
input RNA and normalizing to a reference gene.
Summary
Normalization to Input RNA
Proper normalization is essential for accurate gene expression
Normalization to input RNA implies starting with the same amount
studies. To simplify data analysis, iQTM5 and MyiQTM real-time PCR
and quality of material in each sample. We monitored the expression
detection systems have analysis software that permits normalization
of four genes in HeLa cells subjected to different treatments. Standard
to a standardized input amount, a single reference gene, or the
curves were used to determine individual ampliﬁ cation efﬁ ciencies.
geometric mean of multiple reference genes. Additionally, the
No
The
rm
rela
a
tive
liza
expression
tion M
of
e
the
th
four
ods
genes
for
across
qPC
trea
R
tments was
software can consider individual assay efﬁ ciencies, and combine
in Figure 2, which shows an analysis from the same input RNA, of
normalized to the amount of input RNA (Figure 1).
multiple datasets for a complete gene study.
three common reference genes. Although equal starting amounts
Rea
Normalization to a Single Reference Gene
l-time PCR has been used for gene expression analysis for of R
References
NA were used, the expression levels of the three genes varied
ove
or Multiple Reference Genes
r a decade (Heid et al. 1996, Higuchi et al. 1992). Most gene con
1
s
.
id
Fl
e
e
r
ig
a
e
b
,
l
S
y,
.
d
an
e
d
pe
P
n
fa
d
ff
i
l
n
,
g
M

.
o
W
n
.

,
t
R
re
N
a
A
tm
in
e
te
n
g
t
r
.
i

t
T
y
h
a
e
nd
se
th
d
e
a
e
t
f
a
fe
i
c
n
t
d
o
i
n
ca
th
t
e
e
r
t
e
h
a
a
l-
t
time
expression assays are based on comparing two or more samples, genesq RcTo-nPsCiR depreerdfo rtmao bnece h, oMuosl. eAksepeepcitns gM ged. en2e7s, 1m2a6y– 1b3e9 e(2x0p0re6s).
Although normalizing to input RNA ensures that equivalent amounts
sed at
and require uniform sampling conditions for valid comparisons. var
2.
iab
H
le
ei

d,
lev
C
e
.A
ls
.

e
w
t
i
a
th
l.,
in
R

e
a
a
n
l

t
e
im
xp
e
e
q
r
u
im
an
e
tit
n
a
t
t
a
iv
l
e
s
P
y
C
s
R
te
,
m
Ge
.
nome Res. 6, 986–994
of RNA are compared, it cannot compensate for variations in reverse
Man
transcription
y factors can
efﬁ
co
cienc
ntribu
y
t
.
e
Therefore,
to variability in sample analysis,
(1996).
researchers often normalize
3. Higuchi, R. et al., Kinetic PCR analysis: real-time monitoring of DNA
mak
target
ing ex
gene
perim
expression
ental resul
levels
ts difﬁ
to
cul
tha
t to
t
r
of
ep
a
ro
reference
duce. Var
gene.
iabilit

y
The ideal
A mor
a
e
m

p
a
l
c
if
c
ic
u
a
r
ti
a
o
t
n
e
r

e
n
a
o
c
r
t
m
ion
a
s
li
,
z
B
a
i
t
o
i
t
o
e
n
c

hn
st
o
r
l
a
o
t
g
e
y
g
1
y
1

,
h
1
a
0
s
2
b
6
e
–
e
10
n
3
p
0
ro
(1
p
9
o
9
s
3
e
).
d
is m
reference
ost often
gene
relate
does
d to
not
eve
var
nts
y
u
as
ps
a
tr
function
eam of t
of
he
trea
qPC
tment
R ass
or
ay
condition;
by V
4.
a
T
n
h
d
e
e
ll
s
in
o
,
m
O.
p
et
le
a

l.
e
,
t
H
a
o
l
u
.
s
(
e
2
ke
0
e
0
p
2
in
).
g
T
g
h
e
e
n
y
es
p
a
r
s
op
in
o
te
s
r
e
n
d
al
s
s
e
ta
le
nd
c
a
ti
r
n
d
g
s:
a
u

s
s
e
e
a
t
nd
—
ho
na
wever
mely,
,
t

h
it
e
is
q
often
uantit
difﬁ
y an
cult
d qu
to
al
identify
ity of the
a
e
gene
xtrac
meeting
ted sam
this
ple
criterion
of genlimesit st, hJa. tB dioistepclhnayo ml. 75ini, m2a91l –va29ri5 at(i1o9n9 a9c).ross the treatment,
and(Thellin reverseet -traal.n s1999).criptio nThis efﬁcis ienillustracy (Fleted ige in anFdigure Pfafﬂ2, 2 0which 06). shows det
5
e
.
rm
Va
i
n
n
d
in
es
g
o

m
th
p
e
e

l
g
e,
e
J
o
.
m
et
e
a
tr
l.
i
,
c
A
m
cc
e
u
a
ra
n
te
, a
n
n
or
d
ma
no
liz
r
a
m
tio
a
n
liz
o
i
f
n
r
g
e

a
t
l
h
-t
e
im
t
e
ar
q
g
u
e
a
t
ntitative
Two
an
me
analysis
thods of
from
sam
the
ple
same
norma
input
lizatio
RNA,
n for

of
ac
three
curate
common
compari
reference
son gene(
R
s
T
)
-
t
P
o
C
t
R
hi
d
s
a

t
g
a
e
b
o
y
m
g
e
eo
tr
m
ic
e

t
m
ric
e
a
a
v
n
e
.
r

a
F
g
i
i
g
n
u
g
r
o
e
f
3
m

u
s
l
h
tip
o
l
w
e
s
in

t
t
e
h
r
e
na
e
l
x
co
p
n
re
tr
s
ol
s
g
io
e
n
nes,
betw
genes.
een g

e
Although
nes of int
equal
erest a
starting
re norm
amounts
alizing to
of
inp
RNA
ut RN
were
A and
used, the
Genome Biol. 3, RESEARCH0034, Epub Jun 18 (2002).
levels of four genes in HeLa cells across ﬁve treatments, as
norm
expression
alizing to
levels
a refer
of
en
the
ce
three
gene.
genes varied considerably, depending
calculated by multiple reference gene normalization.
on treatment. These data indicate that genes considered to be
5 1.4 8
Annexin
18S GADPH �-Tubulin Annexin
CAPZB 1.2 CAPZB
4
Coﬁlin Coﬁlin
6
Destrin Destrin
s
s
io
n
1.0
3
0.8

e
x
p
r
e
s
s
io
n
4
2

f
o
ld

e
x
p
r
e
0.6
e

f
o
ld

e
x
p
r
e
s
s
io
n
a
t
iv
e
e
la
t
iv
e

f
o
ld
e
l
0.4 e
la
t
iv
R R R
2
1
0.2
0 0.0 0
GFP Act8 Act9 Lipid (-) control GFP Act8 Act9 Lipid (-) control GFP Act8 Act9 Lipid (-) control
Condition Condition Condition
F
F
ig
ig
.
.
1
1
.
.

G
G
e
e
n
n
e
e
e
e
x
x
p
p
re
re
ss
s
i
s
o
i
n
o

n
a

n
a
a
n
l
a
ys
ly
is
s

i
o
s
f

o
fo
f
u
fo
r
u
g
r
e
g
n
e
e
n
s
es F
F
i
i
g
g
.
.
2
2.
. G
G
e
e
n
n
e
e
e
e
x
x
p
p
r
r
e
e
s
s
s
s
i
i
o
o
n
n
o
o
f
f
t
t
h
hr
re
e
e
e
r
r
e
e
f
f
e
e
r
r
e
e
n
n
c
ce
e F
Fi
i
g
g
.
. 3
3
.
.
G
G
e
e
n
n
e
e
e
e
x
x
p
p
r
re
e
s
s
s
s
i
i
o
o
n
n
a
a
n
n
a
a
l
l
y
y
s
s
i
i
s
s
o
o
f
f
f
f
o
o
u
u
r
r
aaccrroosss f ifviev ec conodnidtiiotinosn nso nrmoramliazelidz etdo tinoi tiinailt iaaml ount ggeeness nnoorrmmaalliized d too iinput t amount t of f RNA.. genes s across s ffiive e connddititioionns sn noormarmalilzizeed d to
o
a
f
m
st
o
a
u
r
n
tin
t
g
o

f
R
s
N
ta
A
r
.
t

i
G
n
F
g
P
R
,
N
Ac
A
t
.
8
G
, A
FP
c
,
t

9
A
,
c
t
t
r
8
e
,
a
A
te
c
d
t9
w
, t
i
r
t
e
h
a

ted t
th
o
e
th
g
e
e

o
g
m
eo
e
m
tri
e
c
tr
a
ic
v

e
a
r
v
a
e
g
r
e
ag
o
e
f

t
o
h
f
e
th
thr
e
e
th
e
re
re
e
ference
with corresponding siRNA; Lipid, treated with lipid reference genes.
c
r
o
e
r
a
r
g
e
e
s
n
p
t
o
;
n
(-
d
)
i
c
n
o
g
n
s
tr
iR
ol
N
, t
A
re
;
a
li
t
p
e
i
d
d

,
w
t
i
r
t
e
h
a
b
te
u
d
ff

e
w
r
i
o
th
n

l
l
y
ip
.
i

d genes.
reagent; (-) control, treated with buffer only.
Normalization to Input RNA Summary
Normalization to input RNA implies starting with the same
Protocol Guide ı 2008 View entire
P
protocol
roper no
online
rmaliz
at
at
www
ion i
.biotechniques.com/protocol
s essential for accurate ge
ı
n
BioT
e ex
echniques
pression
ı 63
amount and quality of material in each sample. We monitored studies. To simplify data analysis, iQ™5 and MyiQ™ real-time
the expression of four genes in HeLa cells subjected to different PCR detection systems have analysis software that permits
BioRad RealTime Protocol.indd 63
treatments. Standard curves were used to determine individual normalization to a standardized input amount, a single referenc
10/26/07 12:00:23 PM
e
ampliﬁcation efﬁciencies. The relative expression of the four gene, or the geometric mean of multiple reference genes.
genes across treatments was normalized to the amount of input Additionally, the software can consider individual assay efﬁciencies,
RNA (Figure 1). and combine multiple datasets for a complete gene study.
Normalization to a Single Reference Gene References
or Multiple Reference Genes
Fleige S and Pfafﬂ MW, RNA integrity and the effect on the real-time qRT-PCR performance,
Mol Aspects Med 27, 126–139 (2006)
Although normalizing to input RNA ensures that equivalent
Heid CA et al., Real time quantitative PCR, Genome Res 6, 986–994 (1996)
amounts of RNA are compared, it cannot compensate for
Higuchi R et al., Kinetic PCR analysis: real-time monitoring of DNA ampliﬁcation reactions,
variations in reverse transcription efﬁciency. Therefore, researchers Biotechnology 11, 1026–1030 (1993)
often normalize target gene expression levels to that of a reference Thellin O et al., Housekeeping genes as internal standards: use and limits, J Biotechnol 75,
gene. The ideal reference gene does not vary as a function of
291–295 (1999)
treatment or condition; however, it is often difﬁcult to identify a
Vandesompele J et al., Accurate normalization of real-time quantitative RT-PCR data by
geometric averaging of multiple internal control genes, Genome Biol 3, RESEARCH0034,
gene meeting this criterion (Thellin et al. 1999). This is illustrated Epub Jun 18 (2002)
Page 1 | Page 2 | Page 3 | Page 4 | Page 5 | Page 6 | Page 7 | Page 8 | Page 9 | Page 10 | Page 11 | Page 12 | Page 13 | Page 14 | Page 15 | Page 16 | Page 17 | Page 18 | Page 19 | Page 20 | Page 21 | Page 22 | Page 23 | Page 24 | Page 25 | Page 26 | Page 27 | Page 28 | Page 29 | Page 30 | Page 31 | Page 32 | Page 33 | Page 34 | Page 35 | Page 36 | Page 37 | Page 38 | Page 39 | Page 40 | Page 41 | Page 42 | Page 43 | Page 44 | Page 45 | Page 46 | Page 47 | Page 48 | Page 49 | Page 50 | Page 51 | Page 52 | Page 53 | Page 54 | Page 55 | Page 56 | Page 57 | Page 58 | Page 59 | Page 60 | Page 61 | Page 62 | Page 63 | Page 64 | Page 65 | Page 66 | Page 67 | Page 68 | Page 69 | Page 70 | Page 71 | Page 72 | Page 73 | Page 74 | Page 75 | Page 76