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发表于 2012-5-17 17:06 |只看该作者 |倒序浏览 |打印

Real-time quantification of microRNAs by$ @: g' U! ~9 B( S" L/ H
stem–loop RT–PCR9 y3 ~6 A+ \2 y& A. d% K
Caifu Chen*, Dana A. Ridzon, Adam J. Broomer, Zhaohui Zhou, Danny H. Lee,% |: n% q$ r2 w; b( g
Julie T. Nguyen, Maura Barbisin, Nan Lan Xu, Vikram R. Mahuvakar, Mark R. Andersen,9 t) G( z! v- V. h
Kai Qin Lao, Kenneth J. Livak and Karl J. Guegler
Applied Biosystems, 850 Lincoln Centre Drive, Foster City, CA 94404, USA
Received May 24, 2005; Revised July 8, 2005; Accepted October 25, 2005. a- M+ X/ d0 S' u- M
ABSTRACT
A novel microRNA (miRNA) quantification method' f) g% d0 ~, n% ~8 r# [, _
has been developed using stem–loop RT followed! f: i/ y: y: `2 U  `/ |& x' i5 J4 B) w
by TaqMan PCR analysis. Stem–loop RT primers are
better than conventional ones in terms of RT efficiency
and specificity. TaqMan miRNA assays are specific0 t" [5 M1 l8 |
for mature miRNAs and discriminate among
related miRNAs that differ by as little as one nucleotide.  k: K* U. q7 |6 S# \% E, e
Furthermore, they are not affected by genomic7 h& z2 j  U/ ~( X& u: o
DNA contamination. Precise quantification is
achieved routinely with as little as 25 pg of total
RNA for most miRNAs. In fact, the high sensitivity,
specificity and precision of this method allows for; r5 _, [. Q  |2 a
direct analysis of a single cell without nucleic acid
purification. Like standard TaqMan gene expression
assays, TaqMan miRNA assays exhibit a dynamic2 ^" ?' r9 i% p, f
range of seven orders of magnitude. Quantification
of five miRNAs in seven mouse tissues showed variation9 o9 e, \9 R) _, k9 t6 l+ z8 A
from less than 10 to more than 30 000 copies per
cell. This method enables fast, accurate and sensitive
miRNA expression profiling and can identify and
monitor potential biomarkers specific to tissues or
diseases. Stem–loop RT–PCR can be used for the
quantification of other small RNA molecules such/ h( c* A& k  N9 s3 u1 O
as short interfering RNAs (siRNAs). Furthermore, the
concept of stem–loop RT primer design could be
applied in small RNA cloning and multiplex assays
for better specificity and efficiency.
INTRODUCTION
MicroRNAs (miRNAs) are naturally occurring, highly conserved2 _1 y. j' o5 S! j; g
families of transcripts (18–25 nt in length) that are1 v6 J$ e0 L8 W% ]" o) T
processed from larger hairpin precursors (1,2). miRNAs are
found in the genomes of animals (3–9) and plants (10–12). To
date, there are 1000 unique transcripts, including 326 human  w- F+ o$ R3 m4 B
miRNAs in the Sanger Center miRNA registry (13).
miRNAs regulate gene expression by catalyzing the cleavage
of messenger RNA (mRNA) (14–19) or repressing mRNA
translation (19–21). They are believed to be critical in cell
development, differentiation and communication (2). Specific
roles include the regulation of cell proliferation and metabolism
(22), developmental timing (23,24), cell death (25),
haematopoiesis (26), neuron development (27), human
tumorigenesis (28) and DNA methylation and chromatin
modification (29).; I* u2 H9 r: o3 @# X7 n# p/ n
Although miRNAs represent a relatively abundant class of
transcripts, their expression levels vary greatly among species6 T# p9 J6 `* ~1 @
and tissues (30). Less abundant miRNAs routinely escape
detection with technologies such as cloning, northern hybridization
(31) and microarray analysis (32,33). Here, we present
a novel real-time quantification method for accurate and sensitive
detection of miRNAs and other small RNAs. This method
expands the real-time PCR technology for detecting gene
expression changes from macromolecules (e.g. mRNAs) to
micro molecules (e.g. miRNAs).' l9 D# {; Q" A3 G) v) `* N
MATERIALS AND METHODS7 M8 W$ m" u8 d" D# z
Targets, primers and probes (Supplementary Data)
Seventeen miRNA genes were selected from the Sanger
Center miRNA Registry at http://www.sanger.ac.uk/Software/2 K5 P9 w4 G: m! \1 Y1 V/ O' j) [
Rfam/mirna/index.shtml. All TaqMan miRNA assays are2 q: i; v: R9 V
available through Applied Biosystems (P/N: 4365409). Standard
TaqMan assays for pri-miRNA precursors, pri-let-7a-3: g6 D9 H# Y; _' a
and pri-miR-26b and pre-miRNA precursor pre-miR-30a were
designed using PrimerExpress software (Applied Biosystems,6 i3 }  g/ b* U( o- F3 X
Foster City, CA). All sequences are available in the' l) I  @+ v. ^* ?# K& V
section of the Supplementary Data. Synthetic miRNA oligonucleotides$ y: I- T- @+ Y2 a  l
were purchased from Integrated DNA Technologies) J# G0 ~" B9 K( y. g0 g) R" S
Tissue RNA samples, cells, cell lysates and
total RNA preparation
Mouse total RNA samples from brain, heart, liver, lung,$ E+ t: {+ O2 c- n
thymus, ovary and embryo at day 10–12 were purchased
from Ambion (P/N: 7810, 7812, 7814, 7816, 7818, 7824,) _# r- H; F' B( U3 g& q% T2 C# B
7826 and 7968). Ambion’s mouse total RNAs are derived; z( e* Z" y# x" F% D' e- B& G
from Swiss Webster mice. All RNA samples were normalized/ ~' q' V* n% h9 x
based on the TaqMan Gene Expression Assays for human or8 a2 k8 K4 F, i1 D2 Y
mouse glyceraldehyde-3-phosphate dehydrogenase (GAPDH)
endogenous controls (P/N: 4310884E and 4352339E, Applied8 @, @4 S5 J8 Y3 s2 N
Biosystems).1 o& E) X* w" R4 d+ W9 n7 T0 }
Two cell lines, HepG2 and OP9, were cultured using
Gibco MEM (P/N: 12492–021, Invitrogen, Carlsbad, CA)9 s$ r0 Q1 D! L
supplemented with 10% fetal bovine serum (FBS) (P/N:: O7 I0 R4 K) d, e; {$ N& A9 l. O
SH30070.01, HyClone, Logan, UT). Trypsinized cells were( A; x2 |( B( L" X/ _
counted with a hemocytometer. Approximately 2.8 · 106$ y/ g; N% M$ e5 S
suspended cells were pelleted by centrifugation (Allegra 6,. V, t: ~' j6 n' j. \4 e
Beckman Coulter, Fullerton, CA) at 1500 r.p.m. for 5 min,
washed with 1 ml Dulbecco’s phosphate-buffered saline (PBS)
without MgCl2 and CaCl2 (P/N: 14190078, Invitrogen, Carlsbad,
CA). The cell pellets were re-suspended in 140 ml PBS6 P8 D6 T2 z' C  O$ N" _2 ?
and processed with three different sample preparation methods.
With the first method, a 50 ml sample (106 cells) was
mixed with an equal amount of Nucleic Acid Purification5 u7 j4 K* A0 S  [6 B3 w4 H
Lysis Solution (P/N: 4305895; Applied Biosystems) by pipetting
up and down 10 times, and then spun briefly. The lysate
was diluted 1/10 with 1 U/ml RNase inhibitor solution (P/N:$ J5 t/ L" ]' z: {
N8080119; Applied Biosystems) before adding the solution to' ~* H- [* m$ m5 k" R
an RT reaction. In the second method, a 50 ml sample (1063 h/ K0 `% R, m% |9 v9 Z
cells) was used to purify total RNA using the mirVana
miRNA Isolation Kit (P/N: 1560, Ambion, Austin, TX)' t& h) k1 M+ i/ c6 d/ O
according to the manufacturer’s protocol. Purified total/ ~; I8 o# e' u+ `) c5 x
RNA was eluted in 100 ml of elution buffer. The third method. U; N" I1 H2 g+ j) T/ l
involved diluting cells 1/2 with 1· PBS, heating at 95C for 54 e; o  b. u) e; ~- X% z
min, and immediately chilling on ice before aliquotting directly- M6 h: O* V% N. N
into RT reactions.. g( a8 O8 H% Y0 q9 i
miRNA detection using mirVana miRNA
detection kit
Solution hybridization-based miRNA analysis was carried out* n5 m- F6 h$ j% I- ^3 W
using the mirVana miRNA Detection Kit (Cat. #: 1552,' a/ d( f% x! Y
Ambion) according to the manufacturer’s protocol. RNA
probes were synthesized by IDT. The radioisotope labeled0 V- i% Q3 W! `- z* C
RNA fragments were detected and quantitated with a Cyclone! L6 O$ x& s( s% M3 z: D
Storage Phosphor System (PerkinElmer, Boston, MA).* x, b( T) ?8 l. ^" a/ w
Reverse transcriptase reactions
Reverse transcriptase reactions contained RNA samples. F- f$ s( g6 X1 M( F) u  v
including purified total RNA, cell lysate, or heat-treated
cells, 50 nM stem–loop RT primer (P/N: 4365386 and
4365387, Applied Biosystems), 1· RT buffer (P/N:7 T0 H" c1 Z  A1 y, Y# X
4319981, Applied Biosystems), 0.25 mM each of dNTPs,
3.33 U/ml MultiScribe reverse transcriptase (P/N: 4319983,
Applied Biosystems) and 0.25 U/ml RNase inhibitor (P/N:
N8080119; Applied Biosystems). The 7.5 ml reactions were' m% H; y5 n) ?
incubated in an Applied Biosystems 9700 Thermocycler in a
96- or 384-well plate for 30 min at 16C, 30 min at 42C, 5 min2 T# T& z: c" o  I2 T
at 85C and then held at 4C. All Reverse transcriptase reactions,8 {8 u' r% m9 r" S
including no-template controls and RT minus controls,4 w0 \! D  q5 n) j  j8 X* n( ~% j' r) N
were run in duplicate.
PCR
Real-time PCR was performed using a standard TaqMan) w' h4 ~  Z; c' K6 G2 [8 h# Z
PCR kit protocol on an Applied Biosystems 7900HT Sequence9 f6 r- t* n- }: i! u' N9 q" l
Detection System (P/N: 4329002, Applied Biosystems). The
10 ml PCR included 0.67 ml RT product, 1· TaqMan Universal
PCR Master Mix (P/N: 4324018, Applied Biosystems),0 l! k8 @1 q" M! T# c
0.2 mM TaqMan probe, 1.5 mM forward primer and 0.7 mM
reverse primer. The reactions were incubated in a 384-well/ r/ H, a" [2 ?4 o- j' w* H4 \
plate at 95C for 10 min, followed by 40 cycles of 95C for 15 s& ]# e* b4 @- v% R0 S+ J
and 60C for 1 min. All reactions were run in triplicate. The6 Y# |) y- Y4 s$ ?+ j7 J7 O
threshold cycle (CT) is defined as the fractional cycle number
at which the fluorescence passes the fixed threshold. TaqMan8 \) @1 I$ E/ r. U" i% r' u
CT values were converted into absolute copy numbers using a/ \: J. m! A# [% L; C1 a
standard curve from synthetic lin-4 miRNA.8 Z: x; g9 y. \# v9 S; }
The method for real-time quantification of pri-miRNA- }$ R3 R! ~( Y/ S( @) t' E: F
precursors, let-7a-3 and miR-26b, and pre-miRNA precursor
miR-30a was described elsewhere (34).2 B+ h7 q/ ?9 ^) f" Z) y& b7 P& F/ G
RESULTS
We proposed a new real-time RT–PCR scheme for miRNA
quantification (Figure 1). It included two steps: RT and realtime
PCR. First, the stem–loop RT primer is hybridized to a
miRNA molecule and then reverse transcribed with a Multi-
Scribe reverse transcriptase. Next, the RT products are quantified5 R) R/ j% R  C9 W3 h' Y( A2 t  F
using conventional TaqMan PCR., b/ ^0 Z. g; Z
Figure 1. Schematic description of TaqMan miRNA assays, TaqMan-based$ B' T  p/ r# t2 o% [# w( I& c
real-time quantification of miRNAs includes two steps, stem–loop RT and realtime
PCR. Stem–loop RT primers bind to at the 30 portion of miRNA molecules
and are reverse transcribed with reverse transcriptase. Then, the RT product is
quantified using conventional TaqMan PCR that includes miRNA-specific
forward primer, reverse primer and a dye-labeled TaqMan probes. The purpose7 b' v! _. b; A) {7 D2 ?: x
of tailed forward primer at 50 is to increase its melting temperature (Tm)
depending on the sequence composition of miRNA molecules.The dynamic range and sensitivity of the miRNA quantification
scheme were first evaluated using a synthetic cel-lin-4
target. Synthetic RNA was quantified based on the A260 value
and diluted over seven orders of magnitude. The cel-lin-42 t: A. L& l1 \; b. E
TaqMan miRNA assay showed excellent linearity between- P' j( y. c# W
the log of target input and CT value, demonstrating that the
assay has a dynamic range of at least 7 logs and is capable of+ r! h' Y; K/ H0 j' l1 ]# `' d0 W
detecting as few as seven copies in the PCR reaction (Figure 2).
Eight additional miRNA assays were also validated using4 q: V/ G& b9 }5 q: z7 w. K& u
mouse lung total RNA. The RNA input ranged from 0.025 to
250 ng (Figure 3). The CT values correlated to the RNA input
(R2 > 0.994) over four orders of magnitude. A negative control
assay, cel-miR-2, did not give a detectable signal, even in( b% l, ]! G4 `9 T( g
reactions with 250 ng mouse total RNA.  P$ e7 y6 ]$ m( i4 P6 q" U2 c- I
The expression profile of five miRNAs was determined in1 W) Y  V' R" L
seven different mouse tissues to create a miRNA expression
map. The copy number per cell was calculated based on the
input total RNA (assuming 15 pg/cell) and the standard curve) x6 B1 b* @5 Z# N( t: c
of synthetic lin-4 target. Several interesting observations were
made from this expression map. First, miRNAs are very
abundant, averaging 2390 copies per cell in these tissues.- o( y$ D. ^3 p5 ?* J: x
The level of expression ranged from less than 10 to 32 0902 r2 t% ^5 X4 C% F7 g
copies per cell. Of the 12 miRNAs, miR-16 and miR-323 were! N' ?1 d1 C: Z7 K- L# ^8 B- S
the most and least abundant miRNAs, respectively, across all
tissues. In addition, each tissue had a distinctive signature of
miRNA expression. The overall level of miRNA expression9 c1 J, o" {7 e' r/ ?9 }$ {6 i. d
was highest in mouse lung and lowest in embryos. Finally, the
dynamic range of miRNA expression varied greatly from less
than 5-fold (let-7a) to more than 2000-fold (miR-323) among3 G% ?1 s4 B* P7 M4 A3 S
these seven tissues (Table 1).
To assess the need for RNA isolation, we added cell lysates
directly to miRNA assays. The equivalent of 2.5–2500 cells
were added directly to 7.5 ml RT reactions. When detected,
the CT values correlated (R2 > 0.998) to the number of cells inthe RT reactions over at least three orders of magnitude+ t9 ?* x/ G- o; }6 Q$ r, T
(Figure 4).
The effect of non-specific genomic DNA on TaqMan  V" R+ i" E' V. d9 n
miRNA assays was also tested for 12 assays. Results showed
no difference in CT values in the presence or absence of 5 ng of
human genomic DNA added to the RT reactions, suggesting
that the assays are highly specific for RNA targets (data not
shown). Based on this observation, we added heat-treated cells! ?* q; P3 f8 ]* a7 q  I  D( O& H
directly to miRNA quantification assays. Figure 5 illustrates' t! t# B4 ^6 D/ a7 @
the comparison of miRNA quantification using purified totalRNA, cell lysates and heat-treated cells derived from an equal
number of HepG2 cells. Adding heat-treated cells directly to
the miRNA assays produced the lowest CT values, and good
concordance was observed among all three different sample
preparation methods.4 x; s1 b. {; f: S! F9 n
The reproducibility of TaqMan miRNA assays was
examined by performing12 miRNA assays with 16 replicates8 c0 `/ _$ E4 W
performed by two independent operators (data not shown)., ~1 l+ g) ^7 v4 w
The standard deviation of the CTs averaged 0.1, demonstrating
the high precision of the assays.
Solution hybridization-based miRNA northern analysis was
used as an independent technology to compare with TaqMan
miRNA assays (Figure 6). We observed that hybridizationbased/ z1 E/ ~9 b; I# k: U+ i
miRNA analyses were less reproducible and that concordance
with TaqMan assays varied from target to target.9 g. ~% k4 `- o9 o' r
There was a general concordance between the two methods* p2 B( V7 v* Z+ W2 O# i& b" \
(R2 ¼ 0.916) for miR-16 across five mouse tissue samples.( F9 l2 {+ G/ O  X% O& H
However, correlations were relatively low for less abundant
miRNAs, such as miR-30 (R2 ¼ 0.751).
Hybridization methods can lack specificity for the mature
miRNAs. We investigated the ability of the TaqMan miRNA
assays to differentiate between the mature miRNAs and their
longer precursors, using synthetic targets for pri-miRNA precursors,
pri-miR-26b and pri-let-7a and pre-miRNA precursor
pre-miR-30a (Table 2). TaqMan assays designed to detect
either precursors or mature miRNAs were tested with synthetic+ S3 @- h  M# h7 N2 |
targets averaging 1.5 · 108 copies per RT reaction (1.3 · 107
copies per PCR). TaqMan miRNA analyses with only primiRNA
precursor molecules produced CT values at least
11 cycles higher than analyses with mature miRNA ones.
This result implies that if mature miRNA and precursor
were at an equal concentration, the latter would contribute
<0.05% background signal to the assay of mature target.& M+ K! {7 J# R' P
For pre-miR-30a where the mature miRNA miR-30a-3p is
located at the 30 end of the pre-miR-30a sequence, a differenceof 8.4 CT was observed. The results showed that TaqMan; g# e; Z- Q0 p8 B* V0 O- d" K
miRNA assays are specific to mature miRNAs. However,
the assay specificity is better if the miRNA is located at the
50 strand of the pre-miRNA precursor. Experiments analyzing
total RNA instead of synthetic targets indicated that the precursors$ j) m9 T0 j: W# {( I( m
are at least two orders of magnitude less abundant than
mature miRNAs, based on CT differences of 7 or more for
miR-26b-1 and let-7a-2 precursors. Considered together, these3 R  S5 M. K7 s7 v& {- q
results suggest that the TaqMan miRNA assays are highly
specific for the mature miRNAs.
The ability of the TaqMan miRNA assays to discriminate
miRNAs that differ by as little as a single nucleotide was tested5 ^/ F# H6 I! j1 M8 Q: D  R
with the five synthetic miRNAs of let-7a, let-7b, let-7c, let-7d4 |9 I) \6 z8 p
and let-7e (Figure 7). Each miRNA assay was examined
against each miRNA. Relative detection efficiency was calculated
from CT differences between perfectly matched and' l* j6 z" M; [# h
mismatched targets, assuming 100% efficiency for the perfect& |* o+ p. B- T
match. Very low levels of non-specific signal were observed,' F8 v( t4 D0 h. a
ranging from zero to 0.3% for miRNAs with 2–3 mismatched, j& |& o) q3 T7 Y4 V! S
bases and only 0.1–3.7% for the miRNAs that differed by a; C  |( D9 V0 D$ M
single nucleotide. Most cross-reactions resulted from G–T
mismatches during the RT reaction (let-7a assay versus let-0 |; B7 b  F1 t- H
7c target etc.). Only the targeted miRNA was detected if more
than three mismatched bases between any two miRNAs were& w# @7 W/ \# M  ~# H$ M! X
present.
We compared the discrimination ability of the TaqMan$ I* c, B9 |8 q6 f& W/ s+ G
miRNA assays to that of solution-based hybridization analysis
(Figure 8). In our hands, the hybridization method discriminated# f' ~9 t' ^+ ^1 v0 R  |1 y
well between let-7a and let-7b. However, poor or no
discrimination was observed among let-7a, let-7c and let-( v; Z& V! p) t' ?6 _
7d, which differ by 1–3 nt.5 }8 s0 L3 N" a; d$ d) k4 e
We speculated that stem–loop primers might provide better: U+ T, z! s4 P
RT efficiency and specificity than linear ones. Base stacking of! p( P9 q/ q1 z
the stemmight enhance the thermal stability of the RNA–DNA
heteroduplex. Furthermore, spatial constraint of the stem–loop' D# ]3 v; g  D
would likely improve the assay specificity in comparison to1 Z5 e/ p  V8 _7 t3 r8 r
conventional linear RT primers. We compared the sensitivity$ @/ {% R' p: t" R
and specificity of the stem–loop and linear RT primers using# ~/ |0 `( H) k! g* a1 u
synthetic miRNAs for let-7a (Figure 9). We observed several
advantages for the stem–loop RT. First, in the presence of the) k9 @- n* x  `/ N
synthetic let-7a target, the CT values between linear and stem–
loop RT methods differed by 7, indicating that the efficiency of
stem–loop RT was at least 100 times higher. Secondly, stem–9 j- n. `( K8 M; i/ F% Q
loop RT discriminated better between miRNAs that differ by
two bases based on DCT values. Finally, the stem–loop RT was
at least 100 times better able to discriminate between the0 y. c' q' w- q6 S
mature miRNA and its precursor, based on the DCT (precursor( E0 p# K! C3 Y7 {/ t" t! V  J
versus mature) of 7.
DISCUSSION0 q6 L3 g; ^4 p, ?
Since the discovery of miRNAs, remarkable advances in the
characterization of these gene families have delineated the! s. D6 |) E3 Q2 w' n: k
mechanism for their functions in gene regulation (35). As a, Z+ i& ~- ?+ N; K) f6 T" ]" U
result, extensive surveys have begun to identify miRNA biomarkers
specific for tissue types or disease status. These studies4 I7 o+ v) t7 A
will benefit from methods that allow for both accurate
identification and quantification of miRNAs.$ R2 `& m9 s7 j8 \; i1 h7 O) B
Current methods for detection and quantification of miRNAs
are largely based on cloning, northern blotting (5), or- H! c8 \% D$ J# n
primer extension (36). Although microarrays could improve
the throughput of miRNA profiling, the method is relatively! Z/ A7 V) S4 X9 y
limited in terms of sensitivity and specificity (32,33). Low" ~3 C( a  Z4 @4 h: F" |2 E" |
sensitivity becomes a problem for miRNA quantification
because it is difficult to amplify these short RNA targets.5 W8 K6 a, o' Z2 D' F
Furthermore, low specificity may lead to false positive signalfrom closely related miRNAs, precursors and genomic
sequences. More recently, a modified Invader assay has
been reported for the quantification of several miRNAs$ i6 J6 {# ?: ~7 h
(37). However, Invader assays have limited specificity and
sensitivity, requiring at least 50 ng total RNA, or 10003 k# o+ `: s6 W. H- w
lysed cells, per assay.
Real-time PCR is the gold standard for gene expression
quantification (38,39). It has been a long challenge for scientists6 p- s8 y  b' C2 y
to design a conventional PCR assay from miRNAs averaging) |4 N$ j7 w4 c% p( K
22 nt in length. We developed a novel scheme to
design TaqMan PCR assays that specifically quantify
miRNA expression levels with superior performance over
existing conventional detection methods. We have designed
and validated assays for 222 human miRNAs (Chen et al.,0 W, Y1 F) f$ f
unpublished data). These assays combine the power of PCR" j, j( Y5 b  |" k/ ^1 o
for exquisite sensitivity, real-time monitoring for a large" ?8 T: A6 n  _
dynamic range and TaqMan assay reporters to increase the4 M7 q6 V2 R3 }  Z  y9 b
specificity. In our hands, miRNA precursors were at least 2000, T/ |- P2 ]9 G6 O- s* b
times less effective targets than mature miRNAs (Table 2).
Because these assays are insensitive to precursors or genomic) g3 c+ ~3 k1 {
DNA, we were able to add heat-treated cells directly to the
assays, eliminating the need for sample preparation. For
applications where both mature miRNAs and their precursors
need to be assayed, conventional TaqMan assays can be used
in parallel to specifically detected precursors.
We observed the better specificity and sensitivity of stem–/ j, a$ J1 N& w: `
loop RT primers than conventional linear ones likely due to the
base stacking and spatial constraint of the stem–loop structure  K9 }2 E; i) O; B/ e
(Figure 9). The base stacking could improve the thermal stability
and extend the effective footprint of RT primer/RNA4 c4 k$ \$ K: U( t
duplex that may be required for effective RT from relatively; y# G2 w& ^0 T$ S4 R9 a
shorter RT primers. The spatial constraint of the stem–loop0 P; Z3 {( x1 ^" j
structure may prevent it from binding double-strand genomic
DNA molecules and, therefore, eliminate the need of TaqMan- w1 T+ X( U( V/ P9 G- X
miRNA assays for RNA sample preparation. Stem–loop) y5 q" h- J. [9 y; T
RT primers can potentially be used for multiplex RT reactions. j* U7 ?+ H, f: i- Y
and small RNA cloning for possibly better efficiency and& C: x4 m7 k% Z. g- x* ~0 r
specificity.7 |- U4 w9 \7 F# }+ x( P  M" f
There is an increasing need for sensitive and specific whole
miRNA profiling. The ability to effectively profile miRNAs
could lead to the discoveries of disease- or tissue-specific
miRNA biomarkers, as well as contribute to the understanding7 {( Y3 p. U% ?6 [. ?
of how miRNAs regulate stem cell differentiation. Our stem–/ S- z/ {! Q2 \) S
loop RT–PCR method should provide a practical solution for3 j: A+ `9 {' d8 d* M7 V
these studies. We are currently developing multiplex  ^# }" X; b: S, W6 z. A' {
approaches that should further increase the utility of this
method.

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