• We are sorry, but NCBI web applications do not support your browser and may not function properly. More information
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Nat Biotechnol. Author manuscript; available in PMC Nov 1, 2010.
Published in final edited form as:
PMCID: PMC2908494

Dynamic single cell imaging of direct reprogramming reveals an early specifying event


Generation of induced pluripotent stem cells is a reproducible but inefficient procedure. While genomic approaches have previously been used to study reprogramming, they average measurements across a large population of cells, the majority of which fail to induce pluripotency. Here, we used high-resolution, live time–lapse imaging to trace the reprogramming process from single donor cells to pluripotency factor positive colonies. Tracing back successfully reprogrammed colonies, we calculate a normalized cell-of-origin reprogramming efficiency that is limited to the pool of responding cells that form colonies. Our data provided a detailed physical description of the specific characteristics of reprogramming populations and reveal a robust, sequential trajectory from a somatic morphology and proliferative index to those of pluripotent cells, suggestive of an early specifying event. Our results clarify and expand previously proposed theoretical models, and provide important new insights into the still poorly defined process of direct reprogramming.

Ectopic expression of Oct4 and Sox2 in combination with both Klf4 and c-Myc (OSKM) 1, Klf4 alone 2,3, Lin28 and Nanog 4 or Esrrb 5 is sufficient to reprogram somatic cells to a pluripotent state. These induced pluripotent stem (iPS) cells exhibit many of the molecular and functional characteristics of embryonic stem (ES) cells 6. While iPS cell technology has progressed dramatically within the past three years (reviewed in 7), the extended latency and low efficiency of reprogramming events within induced populations obscure efforts to characterize the underlying mechanism 8. One simple model suggests that progressive proliferation allows for the accumulation of factor-mediated stochastic events that lead select members through a path towards pluripotency. In an alternative model, the likelihood of iPS cell colony formation is specified at an earlier time, after which the resulting path is more defined 8,9,10. Population-level measurements typically done in reprogramming studies cannot distinguish between these stochastic or more sequential events.

To study reprogramming at the single cell level, we developed a live cell, high throughput imaging system based on previously characterized, clonally inducible murine embryonic fibroblast (MEFs) 11 (Supplementary Fig. 1,2). High-resolution transmitted light images (Fig. 1a, upper panels) taken along a 12-day time course from the initial fibroblasts to the final iPS cell colonies show that even at low starting cell densities it is virtually impossible to accurately follow the progeny of a single cell over the course of days. To facilitate tracking of individual cells, we transduced MEFs with one of several lentiviral vectors encoding different fluorescent proteins and seeded them at variable densities into unlabeled populations (Fig. 1a; lower panels and Supplementary Movie 1).

Figure 1
Continuous single cell imaging allows tracking of reprogramming cells

Our system allows us to trace multiple discrete reprogramming “lineages” from parental fibroblast to terminal iPS cell colony. We acquired images over complete 12 or 14 day experiments at 0.25–0.5 day intervals across a connected spatial range to provide a representative global field at a sufficient resolution for tracing lineage identity from any starting cell (Fig. 1b). To provide information for multiple distinctly labeled lineages at every site over time, we acquired information at each position in phase contrast and for up to four fluorescent wavelengths (Fig. 1b). We generated over 500,000 images covering a total of over 80 imaged plates for the subsequent analysis. We scored positive reprogramming events from terminal acquisitions (at day 12 or 14) via stringent Nanog and E-Cadherin (Cdh1) immunostaining, and traced them retroactively to their first progenitor at t=0 days. Using multi wavelength overlays (Fig. 1d, lower panels and Supplementary Movie 1) we can readily distinguish initial MEFs and track the resulting iPS cell colonies in the global field (Fig. 1b; upper right corner, Fig. 1d; lower panels and Supplementary Movie 1). We measured the reprogramming efficiencies as the fraction of double positive colonies from the starting cell numbers for each distinct wavelength (e.g., a representative Cdh1 stain on day 12.5; Fig. 1c). Overall reprogramming efficiency fell within 0–33%, an expected variability given the low starting numbers of labeled cells (50–200). The mean efficiency of 3.7% across all examined experiments (n=40) and the downstream characterization of isolated lines (Supplementary Fig. 2,3) show that our system is consistent with other studies 11,12,13.

However, upon retroactive tracing, we found that only a subset of iPS cell colonies (termed “primary”) could be traced to a source MEF at t=0 days (Fig. 2a; yellow arrowheads). Another subset of smaller and more symmetrical colonies consistently appeared later between days 6–12 days and upon close inspection could not be traced to an original fibroblast (Fig. 2a, b and Supplementary Fig. 4; red arrowheads and Supplementary Movie 2). Moreover, these late colonies appear to emerge in the inspected position as complete iPS cells, with characteristic small size, round shape, rapid self-renewal and compacted colony growth. We concluded that they likely arise from single cells or small compacted clusters that had reprogrammed at an ectopic site outside the inspected region and are likely secondary events or “satellites” that do not uniquely correspond to a single responding lineage (Fig. 2a, b and Supplementary Fig. 4, 5). As such, these secondary satellites inherently confound true calculations of reprogramming efficiency. We therefore defined a normalized efficiency in which reprogramming events are counted only if they can be traced to their originating fibroblast, and in which satellites were excluded. This normalized efficiency ranged between 0–8% primary colonies per representative wavelength with a mean of 1.15% across all experiments (Fig. 2c and Supplementary Fig. 3).

Figure 2
Progressive accumulation of secondary, non-unique “satellite” colonies skew interpretation of reprogramming data

The distinction between primary and satellite colonies allowed us to reappraise calculated reprogramming efficiencies over time. Surprisingly, primary colonies arise rapidly and reach a stable number within the first 8 days of reprogramming. Furthermore, in many instances, single originating cells were found to separate into distinct sub-populations that uniquely and independently gave rise to iPS cell colonies at the same time (Fig. 2d and Supplementary Movie 3). Conversely, satellites appear later and continue to increase, likely an effect of the progressive growth of iPS colonies each of which can expand clonally over time (Fig. 2e), increasing the likelihood that cells will detach from a primary colony and form a satellite elsewhere. These observations suggest that during the initial two-week period, only a select number of cells are capable of reaching the iPS cell state and do so within a defined temporal window shortly after factor induction. The ability to distinguish primary from satellite colonies can thus impact current models of reprogramming that may have previously included artifacts scored as de novo events (Fig. 2e).

Several distinct cell types arose after induction based on broad morphological and proliferative characteristics. As expected, most cells fail to initiate reprogramming, and generally resemble the initial somatic fibroblast population (Fig. 3a; t=0 days) and respond with either arrested/apoptotic (A) or slow dividing (SD) behaviors, consistent with time series data and Annexin V staining (Fig. 3a; A and SD panels, and Supplementary Movies 4a and b). In addition, we observe a fast dividing fibroblast (FD) population at a much lower frequency (~1% of the starting fibroblasts). These cells exhibited a higher proliferative rate than normal fibroblasts and initially showed a large decrease in size, but retained mesenchymal characteristics (Fig. 3a; FD panel and Supplementary Movie 4c).

Figure 3
Unique fates of induced fibroblasts reveal a conserved trajectory for reprogramming cells

In contrast, when we traced primary iPS cell colonies back to their original source cell, we found that these lineages belong within a unique class of small and fast dividing cells that is established early upon induction (Fig 3a; iPS panel, and Supplementary Movie 4d). Based on gross morphological examination, within a few divisions, these cells become significantly smaller than the starting fibroblast population and exhibit a heightened proliferative rate. To quantify these observations we examined 19 representative primary colonies and traced them back to a starting MEF at t=0 days (Supplementary Fig. 6). The cells that lead to iPS cell colonies had an increased proliferative rate (generation time 12.2±2.8 hrs) after the first division, and grew exponentially over the next several days at a rate similar to that observed for murine ES cells (11–16 hrs) 14, and much faster than that of somatic murine cells such as MEFs (18–22 hrs) 15 or of the induced population as a whole (Fig. 3b). The fast proliferative trait was conferred equally to both daughter cells as early as the first division (Supplementary Fig. 7a, and Supplementary Movie 1).

iPS cell forming populations were also distinct in cell area and shape. Lineages that form iPS cell colonies exhibit a sequential reduction in cellular area over time (when normalized by the number of divisions), and acquire a new, stably maintained size concurrent with their increased proliferative rate within 3–4 divisions (Fig. 3c, Supplementary Fig. 7b). The narrow size range of these smaller cells is unique compared to the variability in initial fibroblasts or within FD cells. iPS cells also exhibit changes in eccentricity, or cell shape, and their intercellular characteristics suggest an enhanced clustering compared to the original MEFs (Supplementary Fig. 7c, d). Moreover, as the number of cells descending from an individual MEF increases, multiple progenitors confer these morphological and proliferative characteristics on all their progeny cells. The apparent symmetry by which these traits are inherited indicates a fundamental change in the homeostatic principles governing somatic MEFs that can occur as early as the first division (Fig. 1d, ,3c,3c, Supplementary Movies 1,3,4d, Supplementary Fig. 7). These results suggest that establishing rapid divisions, in which size decreases, is not only an essential trait needed to establish iPS cells, but one that emerges early and precedes subsequent, more frequent, and possibly less stochastic events.

Recent reports have suggested that p53 and downstream pathways can significantly enhance murine and human reprogramming efficiency 16,17,18,19,20,21. Given our ability to monitor the reprogramming process, we directly investigated the effect that p53 plays at the single cell level. We substituted one of our labeled fluorescent populations with one infected by a lentiviral vector co-expressing constitutive EGFP and an shRNA targeting the canonical tumor suppressor p53 (Fig. 4a and Supplementary Fig. 8) 22. We found a notable (4.1-fold) increase in the number of cells that initiated and maintained a heightened proliferative rate, size reduction, and cluster formation compared to the internal fluorescently labeled (but no shRNA) controls (Fig. 4a, b). On day 14, our terminal image acquisition for this experiment, we stained for Nanog, E-Cadherin, and Alkaline Phosphatase (AP) in all imaged wells (Fig. 4a; right panels). While p53 knockdown apparently expanded the global population of responding cells, many led to aberrant colonies, thus resulting in no increase or even a reduction in the overall reprogramming efficiency when normalized against single cells at the time of induction. In particular, when we characterized the ratio of aberrant (non reprogrammed) to fully reprogrammed colonies, we found a higher fraction of aberrant colonies in p53-depleted cells compared to control populations (Fig. 4a–c, Supplementary Movie 5). Interestingly, we found that the early response within p53 KD cells (time of first division 1.30+-0.19 days (n=11)) that led to these pluripotency marker-negative colonies was comparable to the normal responding populations that form marker-positive iPS cells (Fig. 4d, e, Supplementary Movie 5 and Supplementary Fig. 8). However, at later time points we observed a greater variability in proliferation and terminal size (Supplementary Movie 5). Given the finite number of p53 depleted cells per population in this experimental setting, and their discrete, fibroblast-of-origin dependent normalization, we conclude that the progenitor pool can be expanded by this perturbation, but this expansion does not necessarily improve the fraction of cells that can form complete, molecularly defined iPS cell colonies within the described temporal window.

Figure 4
Effects of p53 knockdown on single cells during the reprogramming process

Previous reports in which p53 has been globally depleted and shown to improve reprogramming efficiency rely on counting iPS cell colonies at a (static) terminal time point. They are thus incapable of discerning the subset of somatic cells that respond positively to factor induction or of measuring the co-occurring accumulation of aberrant colony morphologies 16,19,20. Conversely, our results suggest a model where early loss of p53 may derail cells with an otherwise established stochiometry of OSKM factors from the normal reprogramming trajectory or stabilize an intermediate state that would otherwise lead sequentially to the formation of complete iPS cells 16,19,20.

As reprogramming lineages continued into intermediate points within the timeline, it became increasingly difficult to identify or segment all cells in a responding population. Nevertheless, distinct events within the timeline could still be identified and attributed to unique lineages. We scored the analyzed colonies for compaction events by which cells exhibited enhanced intercellular binding and through which final iPS cell colonies emerged. These consistently arose between days 4 and 8 from the rapidly-dividing, size-reduced cells with similar latency (Supplementary Figure 9, Supplementary Movie 6) 11,13,23.

Previous studies propose several models for reprogramming 9,10, most recently a ‘stochastic one-step model’ 10, where reprogramming of a given cell type under a given condition can occur stochastically in one step throughout the time line of the experiment at a uniform intrinsic probability per cell that depends only on the derivation conditions. We tested the fit of a ‘stochastic one-step model’ when limited to the iPS cell lineages alone, using colony compaction times as determinants for reprogramming and found a rate on the order of 0.001 per cell per day (Supplementary Fig. 9e, purple curve). Our rate is markedly higher than the kinetics found when tracing reprogramming events that occur after a standard 14 day time period 10. Furthermore, colony compaction times show a similar or better fit to a normal distribution that is more consistent with a sequential model, where a series of steps in a lineage leads to successful reprogramming (Supplementary Fig. 9e). The immediate induction of these responses and the consistent subsequent events are in line with both an “elite” deterministic model (where the subset of reprogramming lineages is determined early) and a stochastic model that assumes a stepwise acquisition of traits in which early choices play a dominant role (Supplementary Figure 9). The highly synchronized and reproducible nature of these events further argues against a model with multiple stochastic rate-limiting steps.

In conclusion, our high resolution data lead to several new insights including: (1) an accurate measure of reprogramming efficiency that is normalized according to a colony’s cell of origin and may be used to characterize molecular strategies for enhanced iPS cell generation (2) the identification of iPS cell forming characteristics by proliferation, size, and morphology that precede terminal pluripotency and (3) a more refined interpretation of proposed theoretical models within a practical framework. The observed de-coupling of cell size and proliferation in reprogramming cells is a radical departure from the fibroblast cell cycle, and suggests that overcoming this cell size checkpoint is an important early step in reprogramming. Normal fibroblasts maintain tight control over their cell size that is retained after mitosis during the prolonged G1 phase of the somatic cell cycle 24. The fact that all tracked cells that successfully reprogram show immediate initiation of increased proliferation and cell size reduction suggests that ectopic factor expression allows these cells to overcome those checkpoints early as a necessary step (Fig. 3b, c). However, the fact that alternative fates, such as the observed fast dividing (FD) cells and p53 KD cells, show a similar initial response (Fig. 3 and and4)4) suggests that increased proliferation and size-reduction is not itself sufficient or is even an intermediate state that can be itself stabilized to the detriment of iPS cell generation. Furthermore, while successful reprogramming may be initiated early, it nonetheless requires the continued expression of the factors as demonstrated by previous doxycycline withdrawal experiments 13,23.

The low efficiency of reprogramming emphasizes that population-based measurements are not perfectly suited to dissect its molecular mechanism. Unfortunately, the identification of physical parameters unique to responding populations does not yet explain the nature by which these decisions are made. More nuanced strategies for isolating or expanding this small responding population will be needed in order to completely understand the stages inherent within the gradual re-acquisition of pluripotency as well as their mediating factors. We propose as one possible mechanism that the preliminary response may rely on a unique coupling of somatic silencing as mediated by Oct4/Sox2 and the acquisition of ES-like biosynthesis and cell cycle as mediated by the Myc oncogene, a predominant transcription factor with abundant somatic targets. A complete understanding of the changes that occur within the cells that transition to pluripotency will be necessary for safer and more efficient generation of iPS cells that will eventually unlock their tremendous potential for regenerative medicine.

Materials and Methods

Generation of Fluorescently-Labeled Inducible Fibroblast Lines

E13.5 doxycycline-inducible fibroblasts were generated as described previously and passed twice before infection with a FUW lentivirus 12 in which GFP, YFP, RFP or a CFP-B actin fusion protein (Evrogen) was cloned via PCR amplified EcoRI sites. Fibroblast cultures infected with one respective fluorescent protein were expanded for at least one additional passage before serum starvation and seeding at unique representations within control, uninfected inducible MEFs that were passaged in parallel. MEFs were cultured under serum starvation conditions until the onset of imaging at which point they were switched into standard mouse ES medium supplemented with 2 μg/ml doxycycline (Sigma). This protocol ensured a uniform initial response to ectopic factor induction from a globally stable somatic population arrested in G1 and facilitated the tracking of single cells. Cells were kept on Dox for the duration of all imaging experiments. Isolated iPS cell lines were expanded without Dox and characterized by immunostaining and via blastocyst injection. Primers for real time are as described in 12 and 21 and conducted using an SuperScript® II Reverse Transcriptase (Invitrogen), Power SYBR® Green PCR Master Mix (Applied Biosystems) and a 384 well 7900 RT-PCR Machine (Applied Biosystems).

Image Acquisition, Immunohistochemistry, and iPS cell Colony Scoring

Inducible MEFs were plated in 12 well plates at low densities and imaged using a IX-71 microscope (Olympus) and motorized Prior XY stage (Supplementary Fig. 10). Images were taken within a connected 4×4 or 5×5 spatial range at 10x magnification and in up to 4 fluorescent wavelengths using Metamorph Advanced High Though-put Screening software (Metamorph). Acquisitions were taken with manual oversight every 6 to 12 hours for 10–14 days to minimize the exposure of induction plates to atmospheric conditions and temperature. At the end of a given imaging experiment, plates were fixed in 4% Paraformaldehyde and immunostained for (Abcam or Convance) and/or E-cadherin (Abcam) at 1:500 dilution and detected using Alexa488 or Alexa594 conjugated secondary Antibodies (Jackson Immunoresearch). Additional Immunostaining for line characterization used Oct4 (Abcam), Stella (Millipore), and SSEA1 (Santa Cruz) primary antibodies. Alkaline Phosphatase was detected using a standard AP staining kit (Stemgent) with 8 and 40 minutes (see Supplementary Figure 8) sequential incubations that provided a precise gauge of stain sensitivity. Without analyzing time-lapse information, colonies were scored in efficiency calculations if they demonstrated uniform signal positivity and appeared distinct from other colonies (see Figure 1c) as a standard metric.

Image Analysis

A semi-automated cell segmentation pipeline using the CellProfiler package 25 was employed on images from the fluorescent channels for the period in which cells were discernable by eye (around 4 days for proliferative cells). The package then calculated morphological attributes (such as area and eccentricity) for each cell. Further analysis was done in Matlab. Manual analysis such as time of compaction, or assigning of morphological attributes (SD, FD, iPS, A), used time-lapse images of entire 4×4 or 5×5 global fluorescent overlays across the entire experimental timeline. Sites of interest (predominantly those containing iPS colonies) were scored and tracked retrospectively to the earliest point in which a parent cell could be observed. Primary colonies were scored as those with initial fibroblast origins whereas secondary events were scored if no discernable origin could be found. Primary colonies were catalogued according to their initial response, the time of compaction as measured by the earliest instance in which cells demonstrated compact ES-like colony growth, and pluripotency marker staining. Satellites were scored for marker positivity and for the earliest time in which they were observed. Colonies and other morphologies for CellProfiler analysis were annotated during this manual analysis and stacks of phase contrast and respective wavelengths of interest were generated (Supplementary Figure 10). Movies were constructed using basic ImageJ software with StackCombiner and MtrackerJ plug-ins (ImageJ). For the characterization of the satellite colony appearance, a bounding rectangle was manually determined for each of the analyzed satellite and primary iPS cell lineages. Total fluorescent intensity in the rectangle was summed for each time point.

Modeling and Statistical Analysis

We tested a one-step stochastic model 10 where the probability of a given cell to reprogram at time t is proportional to ekt. Assuming average proliferation time of τ, and neglecting cell death events, the model implies the probability of a lineage to have any reprogramming cell by time t is:


Colony compaction times were fit to this model to find the optimal k using τ=12h, as well as to a Gaussian distribution model. Maximum likelihood estimator was used to fit parameters, and a likelihood ratio test was used to compare the fit of the models.

Supplementary Material

Suppl Figures

S.Movie 1

S.Movie 2

S.Movie 3

S.Movie 4a

S.Movie 4b

S.Movie 4c

S.Movie 4d

S.Movie 5

S.Movie 6

S.Movie 7


We thank Anne Carpenter and Mark Bray from the Broad Imaging Platform for help with the initial CellProfiler image analysis pipeline. We thank Eric S. Lander and Christoph Bock for critical reading of the manuscript as well as Matt Thomson, Max Staller, Alejandro De Los Angelos, and Julia Dennett for technical assistance and intellectual input. IN was supported by a Merck postdoctoral fellowship and an Alon fellowship. AR was supported by a Career Award at the Scientific Interface from the Burroughs Wellcome Fund, an NIH Pioneer Award, and the Sloan Foundation. A.R. is an Early Career Scientist of the Howard Hughes Medical Institute and an Investigator of the Merkin Foundation for Stem Cell Research at the Broad Institute. AM was supported by the Pew Charitable Trust and a New Investigator grant by the Massachusetts Life Science Center (MLSC). This work was funded by the Pew and MLSC.


Author contributions

ZDS, IN, AR and AM conceived the experiments and wrote the manuscript. ZDS generated all reagents and performed the experiments. ZDS and IN performed the analysis.


1. Takahashi K, Yamanaka S. Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell. 2006;126:663–676. [PubMed]
2. Nakagawa M, et al. Generation of induced pluripotent stem cells without Myc from mouse and human fibroblasts. Nat Biotechnol. 2008;26:101–106. [PubMed]
3. Wernig M, Meissner A, Cassady JP, Jaenisch R. C-Myc is dispensable for direct reprogramming of mouse fibroblasts. Cell stem cell. 2007 [PubMed]
4. Yu J, et al. Induced pluripotent stem cell lines derived from human somatic cells. Science. 2007;318:1917–1920. [PubMed]
5. Feng B, et al. Reprogramming of fibroblasts into induced pluripotent stem cells with orphan nuclear receptor Esrrb. Nat Cell Biol. 2009;11:197–203. [PubMed]
6. Maherali N, et al. Global epigenetic remodeling in directly reprogrammed fibroblasts. Cell Stem Cells. 2007:55–70. [PubMed]
7. Amabile G, Meissner A. Induced pluripotent stem cells: current progress and potential for regenerative medicine. Trends in molecular medicine. 2009;15:59–68. [PubMed]
8. Jaenisch R, Young R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell. 2008;132:567–582. [PubMed]
9. Yamanaka S. Elite and stochastic models for induced pluripotent stem cell generation. Nature. 2009;460:49–52. [PubMed]
10. Hanna J, et al. Direct cell reprogramming is a stochastic process amenable to acceleration. Nature. 2009;462:595–601. [PMC free article] [PubMed]
11. Mikkelsen TS, et al. Dissecting direct reprogramming through integrative genomic analysis. Nature. 2008;454:49–55. [PMC free article] [PubMed]
12. Wernig M, et al. A drug-inducible transgenic system for direct reprogramming of multiple somatic cell types. Nat Biotechnol. 2008;26:916–924. [PMC free article] [PubMed]
13. Stadtfeld M, Maherali N, Breault D, Hochedlinger K. Defining molecular cornerstones during fibroblast to iPS cell reprogramming in mouse. Cell stem cell. 2008;2:230–240. [PMC free article] [PubMed]
14. Orford KW, Scadden DT. Deconstructing stem cell self-renewal: genetic insights into cell-cycle regulation. Nat Rev Genet. 2008;9:115–128. [PubMed]
15. Kamijo T, et al. Tumor suppression at the mouse INK4a locus mediated by the alternative reading frame product p19ARF. Cell. 1997;91:649–659. [PubMed]
16. Hong H, et al. Suppression of induced pluripotent stem cell generation by the p53-p21 pathway. Nature. 2009;460:1132–1135. [PMC free article] [PubMed]
17. Kawamura T, et al. Linking the p53 tumour suppressor pathway to somatic cell reprogramming. Nature. 2009;460:1140–1144. [PMC free article] [PubMed]
18. Li H, et al. The Ink4/Arf locus is a barrier for iPS cell reprogramming. Nature. 2009;460:1136–1139. [PMC free article] [PubMed]
19. Marion RM, et al. A p53-mediated DNA damage response limits reprogramming to ensure iPS cell genomic integrity. Nature. 2009;460:1149–1153. [PMC free article] [PubMed]
20. Utikal J, et al. Immortalization eliminates a roadblock during cellular reprogramming into iPS cells. Nature. 2009;460:1145–1148. [PMC free article] [PubMed]
21. Banito A, et al. Senescence impairs successful reprogramming to pluripotent stem cells. Genes Dev. 2009;23:2134–2139. [PMC free article] [PubMed]
22. Ventura A, et al. Cre-lox-regulated conditional RNA interference from transgenes. Proc Natl Acad Sci U S A. 2004;101:10380–10385. [PMC free article] [PubMed]
23. Brambrink T, et al. Sequential expression of pluripotency markers during direct reprogramming of mouse somatic cells. Cell stem cell. 2008;2:151–159. [PMC free article] [PubMed]
24. Singh AM, Dalton S. The cell cycle and Myc intersect with mechanisms that regulate pluripotency and reprogramming. Cell stem cell. 2009;5:141–149. [PMC free article] [PubMed]
25. D’Amour KA, et al. Production of pancreatic hormone-expressing endocrine cells from human embryonic stem cells. Nat Biotechnol. 2006;24:1392–1401. [PubMed]
PubReader format: click here to try


Related citations in PubMed

See reviews...See all...

Cited by other articles in PMC

See all...


Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...