Single-allele analysis of transcription kinetics in …...3D-stacks of images from RNAFISH experiments (MS2- -Cy3 probe, pseudo-colored green) were collected and deconvolved. Transcription

nature | methods

Single-allele analysis of transcription kinetics in living mammalian cells Sharon Yunger, Liat Rosenfeld, Yuval Garini & Yaron Shav‐Tal

Supplementary figures and text:

Supplementary Figure 1 Inserting CCND1 into the Flp‐In system

Supplementary Figure 2 Generating a cell system expressing single CCND1‐MS2 alleles

Supplementary Figure 3 Detection of transcription sites and mRNPs in the stable clones

Supplementary Figure 4 Live‐cell imaging of CMVpr and CCND1pr driven transcription

Supplementary Figure 5 The CCND1pr cycles between “on” and “off” states

Supplementary Figure 6 Detection and quantification of mRNAs by RNA‐FISH

Supplementary Figure 7 Detection of replicated transcription sites

Supplementary Figure 8 Spatial localization of the active transcription sites

Supplementary Figure 9 The emerging of a second site in living cells

Supplementary Figure 10 Duplicated transcription sites in fixed and living cells

Supplementary Figure 11 RT‐PCR of reporter mRNA levels

Supplementary Table 1 Values of transcriptional kinetics extracted from the model.

Supplementary Table 2 Primers

Supplementary Discussion

Supplementary Note 1 The FRT system; The cyclin D1 gene; Extracting polymerase kinetics from FRAP data; Modeling the FRAP data

Note: Supplementary Videos 1–11 are available on the Nature Methods website.

1

Nature Methods: doi: 10.1038/nmeth.1482

4

Supplementary Figure 1 Inserting CCND1 into the Flp-In system

(a) Schematic representation of the FRT recombination process. The HA-CCND1-MS2 gene (cyan

box, named cyclin D1) under the control of the promoter (CMV, green box) was cloned into the


5

pCDNA5/FRT plasmid. Homologous recombination of the FRT sites (pink triangles) between the

above vector and the genomic site in the HEK 293-Flp-In cells (top, linear DNA), yields a

recombined genomic region in the HEK 293-Flp-In cells (bottom, linear recombined DNA)

containing a single copy of the gene of interest (cyclin D1, cyan box), an active hygromycin gene

(faint pink box), and an inactive lacZ-Zeocin gene (purple box). Flp-In cells contain Zeocin

resistance, while correct site-specific recombination yields the Zeocin gene inactive and in

conjunction induces hygromycin gene activity. For explanation on system see Supplementary

Note 1. We verified the loss of Zeocin resistance and the gain of hygromycin resistance after

recombination. This process was performed also for the CCND1 endogenous promoter.

(b) Sequencing of the genomic DNA region of recombination shows that the ATG start codon

(yellow) is in frame with the hygromycin gene (pink) driven by the SV40 promoter (cyan). FRT

site is in dark pink.

(c) PCR followed by sequencing of genomic shows that the cyclin D1 gene sequence (cyan) as

well as the BGH region (grey) were integrated upstream of the lacZ-Zeocin gene (purple).


6

Supplementary Figure 2 Generating a cell system expressing single CCND1-MS2 alleles.

The following controls were performed to verify that the CCND1-MS2 genes were integrated in

the correct FRT genomic location. (a) Loss of LacZ expression observed by X-gal staining (blue-

Flp-In cells, white- Flp-In/CCND1-MS2 cells). Scale bar, 10 µm. (b) PCR on genomic DNA showing

the correct integration of the gene in both clones compared to parental HEK-293 cells. Primers

spanned (top) the SV40pr - hygromycin region, (middle) the cyclin D1 – LacZ region, and

(bottom) control of genomic GAPDH. (c) RT-PCR showing hygromycin expression in CMVpr-


7

CCND1-MS2 and CCND1pr-CCND1-MS2 cells versus control HEK-293 cells. (d) Anti-HA

immunofluorescence showing the expression of the HA-cyclin D1 protein in CCND1pr-CCND1-

MS2 and CMVpr-CCND1-MS2 cells. Hoechst in blue. (e) Semi-quantitative RT-PCR showing the

levels of endogenous CCND1 (Endo) and exogenous CCND1-MS2 (Exo) expression in CCND1pr-

CCND1-MS2 cells during serum starvation (48 hr) and after serum stimulation (8 hr).

Normalized with GAPDH. (f) Cell cycle analysis of the Flp-In cell lines. FACS analysis of the

parent cell line (HEK-293-Flp-In) and the two generated cell lines - CCND1pr-CCND1-MS2 and

CCMVpr-CCND1-MS2 cells, shows a similar cell cycle pattern. G1 - blue, S - green, G2 - orange.


8

Supplementary Figure 3 Detection of transcription sites and mRNPs in the stable clones.

(a) RNA-FISH with a Cy3-labeled probe against the MS2 region showing transcription sites

(green arrows) and cytoplasmic mRNAs in CMVpr-CCND1-MS2 and CCND1pr-CCND1-MS2 cells.


9

(b) RNA FISH with a Cy3-MS2 probe on the CMVpr-CCND1-MS2 (left) and CCND1pr-CCND1-MS2

(right) cell populations shows that active transcription sites were detected in 94% of the

CMVpr-CCND1-MS2 cells, while in CCND1pr-CCND1-MS2 cells only 43% of the population

showed active sites (histogram). Two independent experiments: CMVpr-CCND1-MS2 cells

n=400, CCND1pr-CCND1-MS2 cells n=425. Values are mean ± s.d.

(c) Frames from Supplementary Video 1 showing the release of an mRNP (red arrow) from a

transcription site in a CCND1pr-CCND1-MS2 cell. (d) Frames from Supplementary Video 1

showing an active transcription site and nucleolplasmic mRNPs in a CMVpr-CCND1-MS2 cell.

Scale bar = 5 µm.


10

Supplementary Figure 4 Live-cell imaging of CMVpr and CCND1pr-driven transcription.

Cells were imaged at different acquisition frequencies and the intensity of mRNA transcription

at the active genes was measured over time (see Fig. 1). (a-c) CMVpr-CCND1-MS2 cells. Imaging

frequency: left: every 300 msec; middle: 1 min; right: 20 min. (d-f) CCND1pr-CCND1-MS2 cells.

Imaging frequency: left: 3 min; middle: 1 min; right: 1 min. Scale bar, 5 µm. Frames from live-

cell movies in a-c correspond to the intensity profile plots in Fig. 1c. Frames from live-cell

movies in d and f correspond to the intensity profile plots in Fig. 1d (left and middle plots,

respectively).


11

Supplementary Figure 5 The CCND1 endogenous promoter cycles between “on” and “off”

states. Frames from Supplementary Movie 5 showing the cycling of the CCND1pr driven gene


12

over a period of more than 6 hours. Arrowheads point to the active state of the transcription

site. Scale bar = 5 µm. Plot shows the expression levels at the transcription site during the

movie.


13

Supplementary Figure 6 Detection and quantification of mRNAs by RNA-FISH.

3D-stacks of images from RNA-FISH experiments (MS2-Cy3 probe, pseudo-colored green) were

collected and deconvolved. Transcription sites (cyan arrows) and cytoplasmic mRNAs were

identified (white spheres, middle image). DNA (Hoechst) is pseudo-colored red. The intensities


14

in each volume were measured. Total cell volumes are shown for: (a) CMVpr-CCND1-MS2 cell,

(b) CCND1pr-CCND1-MS2 cell. Left- deconvolved RNA-FISH (green) and DNA. Middle- Detection

of total mRNA particles (white). Right- 3D projections of cell volumes: Top- particle

identification (blue spheres) seen on top of the original FISH signal (green). Bottom- the

measured mRNA volumes seen as the object surface of each mRNP. Scale bar, 5 μm.

(c) Schematic presentation of the increase in fluorescence from the MS2 region and onwards

during transcription. This shows: 1) the region on which mRNAs were quantified by RNA-FISH,

and 2) the region in which fluorescence recovery is measured during FRAP experiments.


15

Supplementary Figure 7 Detection of replicated transcription sites.

(a) Two adjacent GFP-MS2 labeled transcription sites observed in living cells. Scale bar, 5 µm.

(b) FACS analysis showing synchronization of cells to G1/S by thymidine or to S phase after

etoposide treatment. G1 - blue, S - green, G2 - orange (n=4 repeats). (c) Synchronization to late-

S phase led to a 17% increase in cells showing two active transcription sites (n=300). Values are

mean ± s.d. (d) Frames from a time-lapse movie of mitosis (Supplemental Movie 7) showing

duplicated transcription sites before mitosis (left, and inset), the cell during metaphase with no

transcription sites (middle), and daughter cells with single transcription sites (right).


16


17

Supplementary Figure 8 Spatial localization of the active transcription sites.

(a) 3D time-projection of an active transcription site (red) in relation to the nuclear periphery

(green shell) shows that transcription sites usually had peripheral localization. Right– original

movie time projection (1 hr movie).

(b) Single or double active transcription sites (green) did not localize with nuclear speckles (red,

SC-35), or with (c) nucleoli (red, fibrillarin), or with Cajal bodies (arrow) detected with the

fibrillarin staining. Scale bar = 5 µm.

(d) Diffusion analysis portrays the dynamics of the mRNA associated with the transcription site

before and after duplication (n=16 and 12 for single and double sites, respectively). Colors

represent the time scale. The motion of actively transcribing single genes was diffusive

(diffusion coefficients measured were D=(2.3±1.7)*10-4 μm2/sec, similar to1) and after

duplication an increase in transcription site mobility was observed (D=(3.9±2.4)*10-4 μm2/sec).

Two tailed t-test (t= 2.739, (df=26), p-value=0.011). (Supplementary Video 8).


18


19

Supplementary Figure 9 The emerging of a second site in living cells.

(a) The kinetics of the transcriptional activation of the second site appearance in a CMVpr-

CCND1-MS2 cell (Supplementary Video 9, 49 min movie). Scale bar = 5 µm. Top – frames from

movie. Bottom – close up of the transcription sites (grey levels pseudo-colored using ImageJ

‘fire’ look-up table).

(b) The kinetics of the transcriptional activation of the second site appearance in a CCND1pr-

CCND1-MS2 cell (image sequence - 18 min).

(c) Time projection of the two sites from (a). At first one site is seen, later on the emergence of

the second site is detected (arrow). Right – 3D volume of the nucleus.


20

Supplementary Figure 10 Duplicated transcription sites in fixed and living cells.

Imaging the appearance of a second transcription site in living cells CMVpr-CCND1-MS2 cells

were imaged (a) every 10 min, for a total time of 230 min; and (b) every 8 min, total 176 min.

Single transcription sites could be followed for up to 3 hours before the appearance of the

duplicated site. Scale bar = 5 µm. (c) Signal intensity of a replicated transcription site (two

arrows), a single transcription site (one arrow, and cellular mRNAs using RNA-FISH. Right –

enlargement of the transcription sites. Scale bar, 5 µm.


21

Supplementary Figure 11 RT-PCR of reporter mRNA levels.

(a) Cells expressing the CCND1pr-driven CCND1-MS2 gene were synchronized to either G1/S (2

mM thymidine) or to late-S phase (1 mM etoposide). The different sub-populations are marked

in the plots. (b) Semi-quantitative RT-PCR of the CCND1-MS2 and endogenous CCND1 mRNA

levels in untreated, G1/S and late-S cells. The levels were normalized to GAPDH.


22

Supplementary Table 1 Values of transcriptional kinetics extracted from the model.

Values of the transcriptional kinetics measured from actively transcribing single alleles as

extracted from the model (Supplementary Note).

CMVpr CCND1pr

mRNA per cell 114+40 41+30

mRNA per site 14+4 7+4

Polymerase spacing (nt) 237 335

Polymerase firing (sec) 22 52

Transcription rate (kb/min) 0.31-0.78


23

Supplementary Table 2 Primer and adaptor list

Primers and adaptors used:

Adaptor 1 5’-GGCCTGACGCGTTCGCGAGAGCTCAACCGGT

CCTGCAGGATGTACCCATACGATGTTCCAGATT

ACGCTGCATGTACAAGCGGCCGCACTCGAGACCCGGGA-

3’

Adaptor 2 5’-AGCTGATAGGATCCAGCTAGCAGATCTTCATTCT

CCTTGTTGTTGGTTGTTTTTTCCTTTGCTCTTTCCGC

CTTCCATCTCTGAA-3’

Adaptor 3 5’-AATTCTGCAGATATCCAGCACAGTGGCCT

GACGCGTTCGCGAGAGCTCAAGATCTAAATAGGAT

CCGGTACCATAATAAAGCTTAAACCGGTCCTGCAGG-3’

D1-sense 5’-ATAGCGGCCGCATGGAACACCAGCTCCT-3’

D1-antisense 5’-TATCTCGAGGACGCCTCCTTTGTGTTAATGCC-3’

D1-3'UTR-sense 5’-GTCACCTAGCAAGCTGCCGAAC-3’

D1-3’UTR-antisense 5’-TATCTCGAGCCTCCGAGCACAGGATGAC-3’

Hygromycin-sense 5’-GACGTCTGTCGAGAAGTTTCTG-3’

Hygromycin-antisense 5’-CTGTTATGCGGCCATTGTCC-3’

SV40-promoter-sense 5’-CCAGTTCCGCCCATTCTCC-3’

Lac-Zeocin-antisense 5’-GTAACCGTGCATCTGCCAGTTTG-3’


24

Supplementary Discussion

Gene active phases alternating between inactive periods as seen with the endogenous CCND1

promoter are termed transcriptional pulses or bursts. These have been described by

microscopy assays that typically examined the levels of the final protein product2-4 or by

counting of mRNAs in fixed cells5,6. Two live-cell studies have shown gene active periods to

range on the short minute range, 5-6 minutes in E.coli7 and the social amoeba Dictyostelium8. In

this study we show that a "transcriptional burst" in mammalian cells manifests on the long-

minute range, within a time-window that permits the recruitment and gradual buildup of

several polymerases on the gene, per event of gene activation. This would result in the

downstream long-range buildup of protein as seen in the 5 hour oscillation period of the p53

product9. Our data show that several polymerases are recruited to the gene during a

transcriptional burst. Previous measurements using RNA-FISH to count polymerase numbers

and their spacing on genes have quantified 30 transcripts on the β-actin gene following serum-

induction (~170 bp spacing)10, 14 and 23 polymerases per highly active s36 and s38 chorion

genes in Drosophila (~100 bp spacing)11, and 11 polymerases on the Dictyostelium dscA gene

(~120 bp spacing)8. Our quantifications show that the CMV promoter and the endogenous

promoter have distinct recruitment capabilities, 7±4 mRNAs for CCND1pr-CCND1-MS2 and

14±4 mRNAs for CMVpr-CCND1-MS2 sites, which confirm the distinct variation in kinetics for

both promoters seen in the live-cell movies. This analysis also showed that the elongation rates

measured on our genes were ~0.8 kb/min, a value which is lower than the current

measurements from living cells (2-4 kb/min)12-14. The latter studies have used tandem arrays

containing many genes to perform these measurements, and thereby could extract elongation


25

rates as well as pausing and termination values. This was possible since the polymerases on

some genes in the array were elongating whereas others were stalled. However, it is not

possible to distinguish between these processes using the single-gene approach since so few

polymerases are on the genes. Therefore, our value probably reflects a global number

encompassing elongation, pausing and termination.

Transcription was followed in real-time through the cell cycle. Surprisingly, a second

transcription site emerged from the “mother site” after replication. Transcriptional activity

from both sister chromatids persisted until cell division, yet promoter potency and polymerase

recruitment were drastically reduced as shown by mRNA quantification and FRAP experiments.

Still, these quantifications show that the combination of replicated alleles produced similar

amounts of transcripts as the one-allele state, hence indicating fine-tuning of mRNA levels

generated in concurrence with the cell cycle stage. The changes in promoter potency could be

due to alterations in chromatin structure and modifications following replication. The similar

transcriptional kinetics observed on both sister chromatids provide confirmation for the

inheritance of transcriptional potential during replication as suggested by McKnight and Miller

for replicated Drosophila sister chromatids15.


26

Supplementary Notes

The FRT system

The Flp-In System (Invitrogen) streamlines the generation of stable mammalian expression cell

lines by taking advantage of an S. cerevisiae-derived DNA recombination system. The

recombination system uses a recombinase (Flp) and site-specific recombination to facilitate the

integration of a single gene of interest into a specific Flp Recombination Target (FRT) site in the

genome of mammalian cells. Since the integration site is identical, isogenic cell lines with

different inserted genes can be obtained. Using antibiotic resistance it is possible to screen for

positive cell clones. The obtained cell lines contain a single-copy of the integrated gene in the

same genomic locus, allowing direct comparison between different gene-constructs.

Following is the order of steps for stable cell line generation and options of screening. Three

different vectors are used:

1) The pFRT/lacZeo target site vector was used to generate a Flp-In™293-FRT cell line

(Invitrogene). The vector contains a lacZ-Zeocin fusion gene that confers Zeocin antibiotic

resistance to the cells. An FRT site has been inserted just downstream of the ATG initiation

codon of lacZ-Zeocin. The FRT site serves as the binding and cleavage site for the Flp

recombinase.

2) The pcDNA5/FRT expression vector into which HA-CCND1-MS2 was cloned. The vector also

contains the hygromycin resistance gene with an FRT site embedded in the 5′ coding region.

However, the hygromycin gene lacks a promoter and the ATG initiation codon, and therefore

cannot express.

3) The pOG44 plasmid which constitutively expresses the Flp recombinase.


27

Upon co-transfection of the pOG44 plasmid and the pcDNA5/FRT-HA-CCND1-MS2 vector, the

Flp recombinase mediates a homologous recombination event between the FRT sites such that

the pcDNA5/FRT construct is inserted into the genome of the HEK-293-Flp-In cells at the

integrated FRT site. This brings the SV40 promoter and the ATG initiation codon (from

pFRT/lacZeo) into proximity and frame with the hygromycin gene, and inactivates the lacZ-

Zeocin fusion gene. Thus, stable Flp-In expression cell lines can be selected for hygromycin

resistance, Zeocin sensitivity, lack of β-galactosidase activity, and expression of the

recombinant protein of interest (Supplementary Figs. 1 & 2).

The cyclin D1 gene

Cyclin D1 is a major player in the control of the cell cycle16,17. D-type cyclins control the passage

of cells through the G1 phase, ultimately allowing entry into S phase18. They function through

the activation of cdk4/6, which in turn causes the initial inactivation of Rb by

phospohorylation19. Given the central role of cyclin D1 in the cell cycle, its expression is

regulated at several levels, including mRNA transcription, mRNA stability, translational control

and protein turnover. Among the dozen known human cyclin genes, only CCND1 has been

convincingly implicated in oncogenesis20 and its overexpression was shown to cause mammary

cancer in transgenic mice21. The CCND1 mRNA contains a large 3’UTR that might be involved in

transcriptional regulation. A large number of transcription factor binding sites have been

identified in the promoter region17,22,23. For instance, a study that followed Pol II recruitment to

the D1 promoter in the presence of a mutated transcription factor showed by ChIP that Pol II

recruitment was modified along the gene when the mutated transcription factor was present24.


28

Yet, the kinetics of CCND1 mRNA expression have not been analyzed as such, since most

attention has focused on cyclin D1 protein levels. In one study, CCND1 mRNA levels were

measured during the cell cycle using RNA-FISH, and concluded that CCND1 mRNA levels were

generally higher during G1 phase than during S and G2 phases25. This in agreement with our

quantifications of the number of mRNAs transcribed during different phases of the cell cycle

(Figs. 2 & 3). Interestingly in the above mentioned study, when a nuclear run-on assay was

performed on cells which were synchronized by serum starvation it was hard to detect any

major differences in CCND1 mRNA expression. This was seen also in RT-PCR (Supplementary

Fig. 11). This highlights the strength of single-cell analysis and quantification that can detect

differences in transcription on the single cell and single-allele level, versus biochemical

extractions of large cell populations that average out the differences within the cell

population26. In another study, RNA-FISH was used to analyze the percentage of cells with

active CCND1 transcription sites in cancerous cell lines27. This showed that only ~30% of cells

had active CCND1 transcription site similar to the data we present in Supplementary Fig. 3.

Extracting polymerase kinetics from FRAP data

RNA polymerase II elongation kinetics measured by FRAP analysis were previously described in

two studies utilizing this in vivo elongation assay12,14. In this assay, the GFP-MS2 signal at the

active transcription sites is photobleached and the recovery is monitored over time

(fluorescence recovery after photobleaching, FRAP)28. The recovering signal at the transcription

site consists of mRNA synthesis and mRNA release from the site. Specifically, the fluorescence

recovery signifies the generation of new MS2 stem-loops in the nascent mRNAs and their


29

binding by fluorescent GFP-MS2 proteins entering from the surrounding nucleoplasm. In other

words, the recovery rates are proportional to the rates of Pol II elongation as the polymerase

moves through the MS2 region. These numbers can then be extracted from the FRAP curves as

explained in Supplementary Note. It should be noted that in this assay the elongation kinetics

are being measured only throughout the MS2 region since this is the only region in which

fluorescent molecules are added sequentially to the nascent transcript (see Supplementary Fig.

6c).

Modeling the FRAP data

We used a model based on a rate-equation to describe the elongation of mRNA on the CCND1-

MS2 genes and the subsequent release of a complete transcript. The model is based on a few

basic assumptions and leads to a rather simple rate-equation:

dn/dt = ke-koffn

that describes the rate of change of the total number of nucleotides that contribute to the

buildup of fluorescence at the transcription site during active transcription. n is the number of

nucleotides to which GFP-MS2 proteins are attached (through the MS2 stem loops). ke is the

rate at which MS2-nucleotides are added to the transcript, and therefore it is also the rate at

which the fluorescence increases. koff is the average fraction of MS2-nucleotides that leave the

transcription site per time unit with the release of a mature transcript, and results in a

reduction in the fluorescence intensity. Therefore koffn is the number of MS2-nucleotides that

leaves the transcription site.


30

Summarizing these two assumptions we find that the fluorescent intensity is determined by

two processes:

1. The synthesis of the MS2 region which adds nucleotides and leads to the increase in

the fluorescent signal on the site (Supplementary Fig. 5c). This is the term + ke in the

equation.

2. The release of complete fluorescent transcripts, which reduces the number of MS2-

nucleotides and hence reduces the fluorescent signal, - koffn.

The diffusion coefficient of released transcripts was previously found to be 0.04 µm2/sec 29,30

which means that a transcript will leave the FRAP spot size (r=0.3 µm) in approximately 375

msec and therefore does not affect time-lapse measurements which are performed at

significantly longer time scales.

The above equation has an analytical solution:

n(t) = (1-e-kofft)

Note that this solution is normalized, which means that it approaches the value n = 1 after a

long time. We fitted the solution to the normalized FRAP data (Fig. 1c) and extracted koff. We

extracted a value of 2.83*10-3 [sec-1] for the CMVpr-CCND1-MS2 cells and 1.44*10-3 [sec-1] for

the CCND1pr-CCND1-MS2 cells. We also tried to fit the data with a two-exponential model, but

it did not improve the results and gave similar residual values to those obtained with a single

exponential fit.

In the steady state case (dn/dt = 0) meaning that the number of nucleotide at the site

remains constant over time and therefore the rate equation becomes koffn = ke.


31

The total number of MS2-nucleotides n at the transcription site depends on the total

number of polymerases moving through the MS2 region and onwards. Note that ke in the above

equation describes the addition rate of all MS2-nucleotides that are being transcribed by all the

polymerases that are moving through the MS2 region. This leads to ke = ke*·p = koff ·Σini where

ke* is the transcription rate of a single polymerase, p is the number of polymerases that are

currently transcribing the MS2 region, ni is the number of MS2-nucleotides on each polymerase,

and the sum is for all the polymerases at the transcription site.

Taking the quantified number of mRNAs in each cell (Fig. 2c) and assuming that the

polymerases are equally distributed along the transcription unit, the total number of

polymerases can be determined. The mRNA number and the knowledge that the MS2 region in

each RNA is 1308 nucleotides long, leads to an estimation of the total number of transcripts

containing MS2-nucleotides at the site. Deploying the polymerases through the gene with a

constant spacing and considering the constraint from the above number, the transcription rate

for a single polymerase in each cell type could be extracted. Using statistical analysis (Matlab),

the range of transcription rates were determined and found to be 0.31-0.78 kb/min.


32

References

1. J. R. Chubb, S. Boyle, P. Perry, and W. A. Bickmore, Curr. Biol. 12, 439-445 (2002). 2. A. Sigal et al., Nature 444, 643-646 (2006). 3. J. Yu et al., Science 311, 1600-1603 (2006). 4. L. Cai, C. K. Dalal, and M. B. Elowitz, Nature 455, 485-490 (2008). 5. A. Raj et al., PLoS Biol 4, e309 (2006). 6. D. Zenklusen, D. R. Larson, and R. H. Singer, Nat Struct Mol Biol 15, 1263-1271 (2008). 7. I. Golding, J. Paulsson, S. M. Zawilski, and E. C. Cox, Cell 123, 1025-1036 (2005). 8. J. R. Chubb, T. Trcek, S. M. Shenoy, and R. H. Singer, Curr. Biol. 16, 1018-1025 (2006). 9. G. Lahav et al., Nat Genet 36, 147-150 (2004). 10. A. M. Femino, F. S. Fay, K. Fogarty, and R. H. Singer, Science 280, 585-590 (1998). 11. Y. N. Osheim, O. L. Miller, Jr., and A. L. Beyer, Cell 43, 143-151 (1985). 12. X. Darzacq et al., Nat Struct Mol Biol 14, 796-806 (2007). 13. Y. Ben-Ari et al., J. Cell Sci. 123, 1761-1774 (2010). 14. S. Boireau et al., J Cell Biol 179, 291-304 (2007). 15. S. L. McKnight and O. L. Miller, Jr., Cell 17, 551-563 (1979). 16. D. G. Johnson and C. L. Walker, Annu Rev Pharmacol Toxicol 39, 295-312 (1999). 17. R. G. Pestell et al., Endocr Rev 20, 501-534 (1999). 18. C. J. Sherr, Cell 79, 551-555 (1994). 19. R. A. Weinberg, Cell 81, 323-330 (1995). 20. S. Bates and G. Peters, Semin Cancer Biol 6, 73-82 (1995). 21. T. C. Wang et al., Nature 369, 669-671 (1994). 22. O. Coqueret, Gene 299, 35-55 (2002). 23. E. A. Klein and R. K. Assoian, J. Cell Sci. 121, 3853-3857 (2008). 24. G. Sanchez et al., Proc. Natl. Acad. Sci. U S A 105, 6004-6009 (2008). 25. Y. Guo, D. W. Stacey, and M. Hitomi, Oncogene 21, 7545-7556 (2002). 26. D. R. Larson, R. H. Singer, and D. Zenklusen, Trends Cell Biol. (2009). 27. S. Maier et al., J Cell Physiol 218, 638-642 (2009). 28. A. I. Lamond and J. R. Swedlow, Nat Struct Mol Biol 14, 788-790 (2007). 29. Y. Shav-Tal et al., Science 304, 1797-1800 (2004). 30. D. Y. Vargas et al., Proc. Natl. Acad. Sci. U S A 102, 17008-17013 (2005).


Documents

Single-allele analysis of transcription kinetics in …...3D-stacks of images from RNAFISH experiments (MS2- -Cy3 probe, pseudo-colored green) were collected and deconvolved. Transcription