Figures
Abstract
Background
Oligodendrocytes are specialized cells of the nervous system that produce the myelin sheaths surrounding the axons of neurons. Myelinating the axons increases the speed of nerve conduction and demyelination contributes to the pathology of neurodegenerative diseases such as multiple sclerosis. Oligodendrocyte differentiation is specified early in development by the expression of the basic-helix-loop-helix transcription factor Olig2 in the ventral region of the neural tube. Understanding how Olig2 expression is controlled is therefore essential for elucidating the mechanisms governing oligodendrocyte differentiation. A method is needed to identify potential regulatory sequences in the long stretches of adjacent non-coding DNA that flank Olig2.
Methodology/Principal Findings
We identified ten potential regulatory regions upstream of Olig2 based on a combination of bioinformatics metrics that included evolutionary conservation across multiple vertebrate genomes, the presence of potential transcription factor binding sites and the existence of ultraconserved elements. One of our computational predictions includes a region previously identified as the Olig2 basal promoter, suggesting that our criterion represented characteristics of known regulatory regions. In this study, we tested one candidate regulatory region for its ability to modulate the Olig2 basal promoter and found that it represses expression in undifferentiated embryonic stem cells.
Conclusions/Significance
The regulatory region we identified modifies the expression regulated by the Olig2 basal promoter in a manner consistent with our current understanding of Olig2 expression during oligodendrocyte differentiation. Our results support a model in which constitutive activation of Olig2 by its basal promoter is repressed in undifferentiated cells by upstream repressive elements until that repression is relieved during differentiation. We conclude that the potential regulatory elements presented in this study provide a good starting point for unraveling the cis-regulatory logic that governs Olig2 expression. Future studies of the functionality of the potential regulatory elements we present will help reveal the interactions that govern Olig2 expression during development.
Citation: Chen CTL, Gottlieb DI, Cohen BA (2008) Ultraconserved Elements in the Olig2 Promoter. PLoS ONE 3(12): e3946. https://doi.org/10.1371/journal.pone.0003946
Editor: Olaf Sporns, Indiana University, United States of America
Received: July 24, 2008; Accepted: November 13, 2008; Published: December 16, 2008
Copyright: © 2008 Chen et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by a grant from the National Science Foundation (MCB-0543156). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Oligodendrocytes are glial cells that myelinate axons, forming the myelin sheaths in the central nervous system. These myelin sheaths enhance the saltatory conduction by insulating the axons and forming the nodes of Ranvier (reviewed in [1], [2]). Damage to myelin sheaths can result in devastating neuronal diseases, such as multiple sclerosis [3]. Even though myelin is formed mostly during postnatal development in mammals, the specification of oligodendrocytes cell fate occurs early in development [4]. Numerous studies have shown that this specification of oligodendrocyte progenitors depends on a single gene, Olig2(NM_016967) [5], [6]. Olig2 is a basic-helix-loop-helix transcription factor and acts as a transcriptional repressor [7], [8]. It is structurally conserved from humans to zebrafish [6], [9]. Mice homozygous for Olig2 deletion do not form oligodendrocytes, and die on the day of birth [6], [10]. Olig2 misexpression has been associated with neuronal disorders, including schizophrenia [11], [12] and Alzheimer's disease [13]. Thus manipulating Olig2 expression could have therapeutic potential for some neurodegenerative diseases.
The expression of Olig2 is first detected in mice at E8.5 in the ventral portion of the mouse neural tube [6], [7]. This precedes the expression of early oligodendrocyte precursor markers such as platelet-derived growth factor receptor α, whose expression is first detected at E12.5 [7]. Olig2 expression is maintained in mature oligodendrocytes, but not in astrocytes, in the adult central nervous sytem [14]. The basal promoter of Olig2 has been located and is functional in cell types that do not express Olig2 [15]. A motor neuron-specific enhancer has also been located downstream of Olig2 based on transgenic mouse studies [16]. However, other factors involved in the molecular events that regulate Olig2 expression remain to be elucidated.
To further our understanding of the mechanisms by which Olig2 expression is regulated, we identified potential regulatory regions upstream of the Olig2 coding region using criteria such as clustering of potential transcription factor binding sites and sequence conservation. We then verified one of these predictions by testing its effect on the expression of an Olig2 reporter gene in mouse embryonic stem cells. Embryonic stem (ES) cells are an attractive tool for biomedical research since they have the potential to produce many different cell types, including neuronal precursors, in vitro [17]–[19]. Furthermore, the earliest stages of oligodendrocyte development in ES derived neuroepithelial cells follow a similar ordered sequence to that observed in vivo [15], [20]–[22]. ES cell derived oligodendrocytes also interact with host neurons and myelinate axons in the brain [23], [24]. By studying the effect of potential regulatory elements in both undifferentiated and differentiated states, we will be able to gain a better understanding of the regulation of Olig2. We suggest that bioinformatic identification of potential cis-regulatory elements coupled with rapid experimental verification in ES cells will provide a powerful combination for elucidating the transcriptional control of major developmental regulators.
Results
Potential regulatory regions identified computationally
The 150 kb sequence upstream of Olig2 region has been shown to be sufficient to drive normal expression of Olig2 [20]. We sought to identify the regulatory elements in this region, reasoning that potential regulatory elements were likely to share some of the following properties: high sequence conservation relative to orthologous sequences from other vertebrate genomes, stretches of sequence that are perfectly conserved between orthologous regions from mammalian genomes, and, high densities of potential transcription factor binding sites (TFBS) [25]–[30]. We therefore devised metrics to score these properties in the upstream region of Olig2.
In order to identify regions upstream of Olig2 that are dense in potential TFBS, we removed 57 kb of repeated sequence, leaving 93 kb of sequence in the analysis. We used the program Patser [31], [32] to identify sequences that match the Position Weight Matrix (PWM) models of all known mammalian TFBS from TRANSFAC [33]. The TFBS density in 2 kb regions was defined as the total number of base pairs contained in TFBS. The top 6% of windows contain at least 230 bp of TFBS (Figure 1A and Figure S1).
Sequences upstream of Olig2 were scanned using Patser [31], [32] for any potential binding site for any of the mammalian transcription factors in TRANSFAC [33]. Total lengths of potential TFBS were summed up for each 2 kb window. B) Frequency distribution of percent identity in the Olig2 promoter. The average percent identity was calculated for every 2 kb window spanning the multiple alignments of sixteen species in the regions upstream of Olig2.
We located evolutionarily conserved regions by calculating the percent identity in all 2 kb regions spanning the Olig2 promoter using multiple alignments of seventeen species: mouse, rat, rabbit, human, chimp, macaque, dog, cow, armadillo, elephant, tenrec, opossum, chicken, frog, zebrafish, tetraodon and fugu. The average percent identity per 2 kb region is 35%. The top 8% of windows have an average percent identity of at least 75%. (Figure 1B and Figure S1).
We also searched for ultraconserved elements in regions upstream of Olig2. Ultraconserved elements were first defined as sequences at least 200 bp long that show perfect conservation in alignments of the human, mouse and rat reference genomes (perfect HMR conservation). They have been hypothesized to represent sequences under selection for specific functions [34], [35] . The 200 bp threshold used to define these elements is arbitrary and we therefore sought to determine empirically what the appropriate threshold length should be for defining a sequence as ultraconserved. To build an expected length distribution of segments with perfect conservation, we assumed that the identity of each base was independent of all other bases and randomly swapped the columns in alignments of non-coding portions of the three genomes. For each length, we tabulated the number of perfectly conserved sequences from the simulation and compared it to the observed number of segments in the actual alignments (Figure 2). A sequence with 38 bp of perfect HMR conservation was statistically significant (280 segments expected, 8031 observed, false positive rate<0.05). Using this threshold, we found sixteen such sequences upstream of Olig2 (range 38–106 bp) (Table 1 and Figure S1).
The expected length distribution was generated by randomizing the columns in the human, mouse, and rat multiple alignments containing only non-coding regions.
The analyses described above identified 2 kb sequence windows upstream of Olig2 that either contained a high density of potential TFBS, showed high conservation across many vertebrate genomes, or showed stretches of perfect HMR conservation. We combined these sets of sequences to identify potential regulatory regions (Table 2, Table S2). Some regions that did not included stretches of identical bases, but were otherwise highly conserved, were also included.
The Olig2 basal promoter has been shown to reside in the 2 kb region immediately upstream of the Olig2 exons [15], [20]. This region also appeared on our candidate list (mm8_chr16: 91,112,409 – 91, 114,408; Table 2), suggesting that our criterion represented characteristics of known regulatory regions. This 2 kb region contains 237 bases covered by potential TFBS, many of which were binding sites for Sp1. Sp1 is a transcription factor that activates gene expression [36], [37]. In addition, this region has 74.7% conservation across multiple species and includes a 61 bp sequence of perfect HMR conservation.
Another region on our candidate list (mm8_chr16: 91,080,626 – 91,082,625; Table 2) may contain a repressive element (DIG, unpublished data). This region shows 83.7% conservation across multiple genomes, the highest in the Olig2 promoter, and includes a 45 bp sequence of perfect HMR conservation. A recent study demonstrated that this region has different methylation patterns in ES cells and neuronal precursor cells [38]. Furthermore, this region contains numerous binding sites for Gut-Kruppel-Like Factor 4 (Gklf4). Recent studies have shown that Gklf4 is one of four transcription factors required to induce pluripotent stem cells from mouse fibroblasts [39]. There is also evidence that Gklf plays important roles in ES cells, such as in inhibiting myofibroblast differentiation [40] and regulating the expression of Lefty1 [41]. We therefore suspect that Gklf4 plays a similar role in regulating oligodendrocyte differentiation by repressing Olig2 expression in undifferentiated cells.
In addition, another region on our candidate list (mm8_chr16:91,061,447 – 91,063,446, Table 2) was shown to have different methylation patterns between ES cells and neuronal precursor cells [38]. This region contains three segments of perfect HMR conservation with a combined length of 121 bp. It has 75.2% identity across all genomes in the alignment and contains 221 bp of potential TFBS. We also speculate that this region contains sequences that regulate Olig2 expression.
Our top candidate for a new regulatory region (mm8_chr16: 91,028,363-91,030,362; Table 2) contained a sequence we designated as ULTRA (chr16 91,029,26-91, 029,835, Table S2). It contains 106 bp and 45 bp sequences of perfectly HMR conservation, which are separated by only a 1 base mismatch in the human genome. This region also has 80.3% conservation among the set of seventeen vertebrate genomes and was significantly enriched for potential TFBS. In addition, ULTRA shows 71% sequence similarity with another region (mm8_chr10:18,999,620-18,999,731) that also shows perfect identity among human, mouse, and rat genomes. This second region is located 46 kb upstream of Olig3, a paralogous gene of Olig2. The presences of these similar highly conserved elements in the promoters of two genes in the Olig family suggest that these elements play a role in Olig gene expression. We, therefore, tested whether ULTRA could influence the expression regulated by the Olig2 promoter in the current study.
ULTRA represses Olig2 basal promoter regulated expression in embryonic stem cells
We constructed three plasmids (P-plasmid, UP-plasmid, PGK-plasmid) to test the regulatory activity of ULTRA (Methods). All three constructs all included a neomycin cassette, which confers resistance to G418, and the coding region of green fluorescent protein (GFP), but differed in the sequences upstream of GFP. The Olig2 basal promoter sequence was placed upstream of GFP in P-plasmid. The UP-plasmid is identical to the P-plasmid except that the ULTRA sequence is included directly upstream of the Olig2 basal promoter, and is designed to test whether the ULTRA region can modulate the activity of the Olig2 basal promoter. The phosphoglycerate kinase promoter was placed upstream of GFP in PGK-plasmid to serve as a positive control.
The three constructs were separately transfected into mouse ES cells and random integration events were selected for using G418. The resulting cell lines were designated P-clones, UP-clones, and PGK-clones. Polymerase chain reaction (PCR) was used to verify that the complete sequences including the promoter and the GFP were integrated into the genome (data not shown). We kept only clones with intact target sequences, resulting in 28 P-clones 48 UP-clones and 26 PGK-clones. These clones were grown on STO feeder cells and then assayed by flow cytometry to measure GFP expression. To distinguish ES cells from these STO cells in each culture, we incubated all cells with a monoclonal antibody to mouse SSEA-1 (Stage-specific embryonic antigen-1), which is expressed on the surface of ES cells, but not on STO cells. The binding events of SSEA-1 antibody were detected using an anti-mouse secondary antibody conjugated to Alexa Fluor 555. The fluorescent levels of GFP and the Alexa Fluor 555 antibodies for each clone, along with the sizes of individual cells, were simultaneously detected on a flow cytometer. We included four wells of STO cells and four wells of ES cells as controls. These controls were used to build a statistical model to distinguish ES cells from non-ES cells in PGK-clones. We built a logistic regression model to predict cell type (ES vs non-ES) with three variables: antibody fluorescence, cell granularity measured by side scatter values, and the plate in which the clone was located. With this model, we first assessed the GFP expression of PGK-clones. The GFP expressions of PGK-clones range from 87.76 to 656.90 arbitrary fluorescent units (AFU) after adjusting for background fluorescence, indicating that the GFP sequence was functional and that integration sites in the genome indeed influence expression. We chose one PGK-clone with the smallest standard deviation in GFP expression to include on plates containing the P- and UP-clones. This PGK-clone serves as a technical positive control for each plate. We also used a similar logistic regression to differentiate between ES and non-ES cells in P- and UP-clones. With this model, a threshold of 0.48 was used to differentiate between ES and non-ES cells. This threshold correctly predicted 92% ES cells and 97% of STO cells in the control wells. This model was applied to all P- and UP-clones and only cells deemed to be ES cells were kept for further analysis. After removing all the non-ES cells from each clone, the average number of cells per P-clone is 151,217 cells, ranging from 58,770 to 196,069 cells. The number of cells per UP-clone ranged from 47,182 to 193,392 cells with an average of 134,618 cells per clone. The mean GFP expression for P-clones was 335 AFU, whereas the mean GFP value for UP-clones was 258 AFU, after correcting for background fluorescence (Figure 3). The reduction in GFP expression in the UP-clones relative to the P-clones was statistically significant (P value<0.05, Wilcoxon rank sum test), suggesting that ULTRA represses the expression driven by the Olig2 basal promoter.
P- and UP-clones were created by transfecting ES cells using two different constructs: one with a basal Olig2 promoter upstream of GFP and the other with ULTRA placed in front of the Olig2 promoter and GFP. Integration events were selected by applying neomycin. Clones were expanded and analyzed for GFP expression by flow cytometry. The distributions of fluorescence intensity for P- and UP-clones were statistically different (P-value<0.05, Wilcoxon rank sum test).
ULTRA does not affect Olig2 basal promoter regulated expression in differentiated neural precursor cells
We investigated the possibility that this ULTRA also affects expression driven by the Olig2 basal promoter in differentiated cells. We differentiated all 76 ES clones into neural precursor cells by treating them with retinoic acid and a Sonic Hedgehog agonist. 25 P-clones and 46 UP-clones survived differentiation. Differentiation induces Olig2 expression and differentiated cells were selected based on labeling with Olig2 antibodies. We assayed GFP fluorescence and Olig2 staining for each clone using a flow cytometer. We defined differentiated cells from each clone as those with higher Olig2 antibody fluorescence values than the undifferentiated ES cells. We computed their average GFP expression of each differentiated clone by subtracting the background fluorescence determined from the control wells on the same plate. The mean GFP expression for P-clones was 70.3 AFU and for UP-clones was 66.2 AFU (Figure 4). The difference in GFP was not statistically significant (P value >0.05, Wilcoxon rank sum test), indicating that ULTRA does not affect the expression driven by the Olig2 basal promoter in neuronal precursors.
ES cells were grown in suspension to form embryonic bodies and retinoic acid and Shh agonist Hh-Ag 1.4 were added to the medium after 2 days. Differentiated cells were detected using Olig2 antibodies. The distributions of differentiated P- and UP-clones were not statistically different (P value >0.05, Wilcoxon rank sum test).
Discussion
Despite mounting evidence that the regulation of Olig2 at the level of transcription plays an important role in glial cell fate specification, we know little about the regulation of Olig2. Here we presented a preliminary study aimed at identifying cis-regulatory regions that control Olig2 expression. Since distal cis-regulatory elements in vertebrates can be located far from the gene [42], we scanned the 150 kb of Olig2 upstream sequence and identified ten regions containing potential regulatory elements which might play a role in controlling Olig2 gene expression. Here we verified one candidate region in mouse ES cells and neuronal precursor cells. Our results indicate that this region contains sequences that repress Olig2 expression in undifferentiated cells. In neuronal precursor cells, this region does not appear to repress Olig2 expression. This element may play an important role in keeping Olig2 expression off in undifferentiated ES cells. Future studies, such as deleting this region from its native locus, are needed to further elucidate the molecular roles of this region.
Our results suggest a model by which Olig2, a key developmental transcription factor, is expressed only in cells developing along the neural lineage. The basal promoter of Olig2 shows constitutive activity in both undifferentiated ES cells and neuronal precursors [15], [20], indicating that the basal promoter alone cannot explain Olig2 expression. The expression of Olig2 is likely repressed in undifferentiated cells through the concerted action of upstream repressive elements including the ULTRA and, possibly, two other regions [38]. This repression is then relieved as cells develop along the neuronal lineage allowing Olig2 expression. The predictions of this model are testable and provide a framework for further studies of Olig2 expression regulation.
The recent discovery of ultraconserved elements [34] has generated a debate on the extent to which sequence conservation reflects functional importance. Ultraconserved elements are more conserved than coding sequences, thus prompting the suggestions that they encode essential functions. Here we used an empirically defined threshold to identify elements with perfect identity that we would not expect to arise randomly throughout evolution. The ULTRA region we tested in this study contains two such elements, but the region only has a mild repressive effect on expression. These results are in agreement with our previous study, which demonstrated that selection on these elements with contiguous identity is only weakly purifying [35].
We identified ten potential regulatory regions of Olig2 using a combination of sequence conservation across seventeen vertebrate genomes and TFBS density, and perfect HMR conservation. Only one of these candidate regions, the Olig2 basal promoter, had previous, direct experimental support to suggest that it regulates Olig2 expression [15], [20]. Two candidate regions have methylation profiles that suggest a regulatory role. Here we present direct evidence that a fourth candidate region, ULTRA, modifies the expression regulated by the Olig2 basal promoter in a manner consistent with our current understanding of Olig2 expression during oligodendrocyte differentiation. This study provides a basis for studying Olig2 regulation on the molecular level. We anticipate that further studies on our predicted regulatory regions will continue to unravel the regulatory interactions governing the timing and location of Olig2 expression during development.
Materials and Methods
Computational Predictions of Regulatory Elements
We predicted regulatory elements using three criteria: density of potential transcription factor binding sites (TFBS), sequence conservation across multiple genomes, and stretches of sequences with perfect conservation in human, mouse, and rat reference genomes.
The 150 kb sequence upstream of the mouse Olig2 gene was downloaded from the UCSC Genome Browser with nucleotides in repeat regions masked (mm8_90,964,409-91,114,408) [47]. We used Patser [31], [32] to scan this region for any potential binding site for any of the 263 mammalian transcription factors in TRANSFAC [33]. The numbers of potential sites overlapping each nucleotide position were summed up for individual bases and then the density of potential binding sites for each 2 kb window along the 150 kb upstream of the Olig2 coding sequences by adding up the number of sites at each base in the window.
To identify highly conserved regions, multiple sequence alignments with seventeen species spanning 150 kb upstream regions of Olig2 were downloaded from the UCSC Genome Browser [47]. The seventeen species include mouse, rat, rabbit, human, chimp, macaque, dog, cow, armadillo, elephant, tenrec, opossum, chicken, frog, zebrafish, tetraodon and fugu. To narrow down the conserved regions in this set of alignments, the percent identity for each base found in the mouse genome was calculated using the following scoring scheme: a percent identity of zero was assigned to a base if fewer than three species, other than mouse, contained a nucleotide in that position; otherwise, the percent identity is calculated by dividing the total number of species having the major allele by the total number of species having a non-gap base in that position. We then calculate the average percent identity for overlapping windows of 2 kb along the Olig2 promoter.
The third criterion we used to predict the regulatory elements is the presence of sequences with uninterrupted perfect identity across human, mouse and rat, so-called ultraconserved elements. We empirically determined the length threshold for a significant run of perfectly conserved adjacent residues across human, mouse and rat genomes. We used the same human-mouse-rat alignments that Bejerano et al. [34] used in first identifying the ultraconserved elements to generate the empirical length distribution. We removed all exonic sequences from the alignments and then randomized non-gapped columns in each alignment. After each round of randomization, the frequencies of lengths of perfectly matched sequences were recorded. Ten complete randomizations were done across all alignable regions of the three genomes and the resulting frequencies were averaged to create the empirical length distribution of perfectly conserved sequences. We selected the threshold length, 38 bp, by using a false positive rate of 0.05 derived from comparing the expected distribution with the observed. A false positive rate was calculated as the number of expected segments divided by the number of observed segments of the same length. We then scanned the 150 kb upstream sequence of Olig2 for any identical sequence across human, mouse, and rat genomes whose length was equal or greater than the threshold length.
The top candidate regions with potential regulatory functions were selected such that they contained perfectly matched sequences, were highly conserved among all species in the alignment and had dense transcription factor binding sites. Regions were also considered as candidates when they included high numbers of binding sites and were highly conserved only. In total, ten regions of 2 kb each were identified as potential regulatory regions.
Construction of Enhancer Plasmids
We chose one computational prediction to validate experimentally in mouse embryonic stem (ES) cells: mm8_chr16: 91,028,363 — 91,030,36. To test whether this region contained any element that has enhancer activity, the most conserved sequence within this region, mm8_chr16: 91,029,261 — 91, 029,835 (designated ULTRA), was chosen to test for its activity in ES cells. We constructed three plasmids from the pEGFP plasmid (Clontech): a plasmid with a native promoter from the Olig2 locus in front of the green fluorescence protein (GFP) gene (P-plasmid), a plasmid with ULTRA cloned in front of the native promoter, followed by the GFP gene (UP-plasmid), and a plasmid with the phosphoglycerate kinase as promoter in front of the GFP gene (PGK-plasmid).
The P-plasmid was constructed by cloning the 2 kb sequence in front of the first exon of Olig2 (mm8_chr16:91,112,391 — 91,114,400) upstream of the GFP gene on the pEGFP plasmid. This sequence was shown to contain the Olig2 basal promoter [15], [20]. The sequence was amplified from the mouse genome using primers listed in Table S1. The polymerase chain reaction (PCR) products and the pEGFP plasmid were both digested with BamHI and Sal1 restriction enzymes. Ligation was carried out at 16°C for one hour. The UP-plasmid was constructed by inserting the ULTRA upstream of the 2 kb segment. The ULTRA was amplified from the mouse genome using appropriate primers (Table S1). The PCR product and the P-plasmid were then digested with BglII and HindIII restriction enzyme and ligated at 16°C for one hour. The PGK-plasmid was constructed by putting the phosphoglycerate kinase as a promoter upstream of GFP. The phosphoglycerate kinsase sequence was digested from pBC293 (Cohen Lab, Washington University) using EcoRI and BglII restriction enzymes. The pEGFP vector was then digested with these two enzymes and the ligation reaction was carried out at 16°C in one hour. Transformation of E. coli was selected with 30 mg/mL kanamycin.
Embryonic stem cell culture and transfection
The ES cells used in this study were the mouse RW4 line and were cultured in conditions previously described [20]. About 5 ug of P-plasmid, UP-plasmid, and PGK-plasmid were used in independent electroporations to created P-clones, UP-clones and PGK-clones. Electroporations were carried out using program A-013 on a Nucleofector II device (Amaxa Inc.) with the provided ES cell electroporation solution. Electroporated cells were transferred to a 100 mm gelatinized dish with 10 mL of complete medium (CM) (DMEM+10% fetal bovine serum, 10% newborn calf serum and nucleoside supplement) with 1000 U/mL leukemia inhibitory factor (LIF), 0.1 mM β-mercaptoethanol [22]. 50 uL of 250 ug/mL of G418 (GIBCO) was added to the tranfected cells to select for cells with a stably integrated transgene. After eight days, clones resistant to G418 were transferred into 96-well plate wells with about 30,000 STO cells as feeder layers. STO cells had been irradiated with 3500 rads to prevent replication. ES cell clones were then cultured and expanded in CM as described until each clone could be maintained and harvested from a well on a six-well plate [20].
PCR verification of integration events
The cells were washed with Dulbecco's solution A (PBS), dissociated with 380 uL 0.25% Trypsin-EDTA (GIBCO), and harvested from six-well plates. DNA was extracted from cells using a DNA purification kit (5 PRIME ArchivePure, Fisher Scientific). To verify the complete sequence from the beginning of the promoter to the end of the GFP gene on the P-plasmid was integrated into the genome, two separate PCR reactions were performed using two primer pairs (Table S1). Similarly, UP-clones and PGK-clones were verified via PCR reactions (Table S1).
Plate layout and antibody staining
Each clone was placed into a well on a 96-well plate and GFP expression in clones was assessed by flow cytometry. To control for plate-to-plate variation, four sets of three wells each (A1–A3, A10–A12, H1–H3, H10–H12) were used as control wells on each 96-well plate. Each set of three control wells contained either STO cells, RW4 cells, or PGK-clone cells, in that order. The PGK-clone was used as a positive control. Each clone with approximately four to five million cells were washed with PBS, dissociated with 380 uL 0.25% Trypsin-EDTA, and recovered with 1.6 mL CM. Each clone was then spun down at 1200rpm for 5 min, resuspended in 100 uL PBS, and transferred into a well on a 96-well plate. Each clone was washed with 100 uL PBS twice. The cells were then incubated at 4°C with 50 uL of unconjugated mouse SSEA-1(Stage-specific embryonic antigen-1) antibodies for 20 minutes (Millipore, 1:50 dilution). SSEA-1 is present only on the cell surface of ES cells, but not STO cells. After incubation, the cells were washed twice with 100 uL PBS. We then stained with 50 uL of anti-mouse IgM antibodies (Invitrogen, 1:100 dilution) for 20 minutes at 4°C. These secondary antibodies were conjugated to Alexa Fluor 555. The cells were washed twice with 100 uL PBS and then resuspended in 150 uL of PBS for fluorescence analysis on a flow cytometer.
Analysis of GFP Expression in undifferentiated cells by flow cytometry
Linear and log values of fluorescence level at 510 nm (GFP fluorescence) and 565 nm (fluorescence of Alexa Fluor 555 antibodies), as well as forward scatter (FS) and side scatter (SS) values were obtained for each cell using a Beckmann-Coulter Cytomics FC500 MPL with a 488-nm laser. The Alexa Fluor 555 antibodies bind to SSEA-1 primary antibodies, which recognize the antigens that are present only on the surface of ES cells. To select only the undifferentiated ES cells from each well, the fluorescence values of antibodies gathered from the RW4 cells and STO cells in all the control wells were used to construct a logistic regression model, which gives the probability of a cell being an ES cell. With the assumption that majority of the RW4 cells were undifferentiated and STO cells were not ES cells, we expected the RW4 cells and STO cells to show different distributions of antibody fluorescence values. We chose the best model, based on the lowest Akaike information criterion (AIC) [48], to predict the membership of each cell (a ES cell or non-ES cell). Parameters tested in the model included: Plate effect, log(antibody fluorescence), log(FS), log(SS), antibody fluorescence, FS, and SS values. We conducted leave-one-out cross validations to assess the sensitivity and specificity of the model. Sensitivity was defined as the number of correctly predicted ES cells divided by the total number of true ES cells. Specificity was defined as the number of correctly predicted non-ES cells divided by the total number of true non-ES cells. We chose a threshold value for selecting ES cells based on the sum of sensitivity and specificity values. To investigate whether the location of each clone on a plate affects the fluorescence levels of cells, models built using only three sets of the STO-RW4 control wells were used to predict the cell types of cells in the set of control wells that were not included in the models. The sensitivity and specificity of the predictions were then compared among the four different sets of wells. The appropriate logistic regression model was used to select the undifferentiated cells from each clone on the plates. To test whether there is a difference in the distribution of mean GFP fluorescence levels among P-and UP-clones, the Wilcoxon rank sum test was used.
Differentiation of ES cells
ES cells were treated with a protocol that induces ventral neural cell fates. ES cells are first scrapped off the bottom of flasks and cultured for two days in M-DFK5 medium [20]. After two days, embryonic bodies were plated in a 24-well plate in the same media in the presence of 2 µM retinoic acid (Sigma) and 30 nM of Shh agonist Hh-Ag 1.4 (Curis) for 4 days.
Plate layout and antibody staining
We reserved four sets of three wells on each plate to serve as controls. Each set of control wells contained a well of undifferentiated RW4 cells, differentiated RW4 cells, and differentiated TG25 ES cells. TG25 cells carry a GFP knock-in at the Olig2 genes; GFP in the cells is turned on when they were differentiated [49], thus serving as a positive control. The cells were moved from 24-well plates to 96-well plates prior to staining by using the procedures described earlier. After washing with PBS twice, we fixed the cells with 4% paraformaldehyde for 30 minutes at room temperature. We then permeated the cells with 0.1% triton-X for 10 minutes and blocked the cells with bovine serum albumin for 30 minutes. Cells were washed with PBS between each step. We stained the cells with Olig2-antibodies (Chemicon, 1:100 dilution) for 30 minutes at 4°C. The second staining was done using the Alexa Fluor 555 goat anti-rabbit IgG (H+L) antibody (Invitrogen, 1:100 dilution) and incubated for 30 minutes at 4°C. These conjugated secondary antibodies bind to Olig2-antiboies. After staining, the cells were then resuspended in 150 uL of PBS for fluorescence analysis on a flow cytometer.
Analysis of GFP Expressions in differentiated cells by flow cytometry
To select only the differentiated cells from each well, the fluorescence values of Alexa Fluor 555 antibodies emitted from the undifferentiated and differentiated RW4 cells on each place were used. The mean and standard deviation of the antibody fluorescence from the undifferentiated RW4 cells were calculated. The 95% confidence intervals were used as a threshold to distinguish differentiated cells from undifferentiated cells. Any cell with a fluorescence value higher than the 95% upper bound was deemed differentiated. This threshold was applied to all clones on a plate and GFP fluorescence was calculated for the differentiated cells only. The average GFP values for the differentiated RW4 cells were subtracted from the GFP values for each clone on the same plate to control for plate-to-plate variation. We used the Wilcoxon rank sum test to test for differences in the distribution of mean GFP fluorescence levels among P-and UP-clones.
Supporting Information
Figure S1.
Potential transcriptional factor binding sites (TFBS) density, conservation level and perfectly conserved human-mouse-rat sequences in Olig2 promoter. The locations of potential TFBS were identified using the program Patser [31], [32] and all known mammalian transcriptional factor matrices in TRANSFAC [33]. The level of conservation was calculated using multiple alignments of seventeen vertebrate genomes. Sequences with at least 38 bp of contiguous perfect conservation across the human, mouse, and rat genomes were also located in the Olig2 promoter. Bases are colored according to the level of conservation and the number of potential TFBS located. Bases with high sequence conservation or contain high number of potential TFBS are represented by darker blue whereas bases with low sequence conservation or contain low number of potential TFBS are represented by lighter blue. Candidate regions with regulatory potentials are indicated with red boxes.
https://doi.org/10.1371/journal.pone.0003946.s001
(1.55 MB TIF)
Table S2.
Sequence of the candidate region.
https://doi.org/10.1371/journal.pone.0003946.s003
(0.09 MB DOC)
Acknowledgments
We thank Deany Delaney for technical advice, Daniel Chen for help on plasmid constructions, Steve Johnson for providing the pEGFP plamid, Gil Bejerano for first showing us the presence of the sequence homologous to ULTRA upstream of Olig3, and members of the Cohen Lab for advice and discussion.
Author Contributions
Conceived and designed the experiments: CTLC DG BAC. Performed the experiments: CTLC. Analyzed the data: CTLC. Contributed reagents/materials/analysis tools: CTLC DG BAC. Wrote the paper: CTLC DG BAC.
References
- 1. Girault JA, Oguievetskaia K, Carnaud M, Denisenko-Nehrbass N, Goutebroze L (2003) Transmembrane scaffolding proteins in the formation and stability of nodes of Ranvier. Biol Cell 95: 447–452.
- 2. Hildebrand C, Remahl S, Persson H, Bjartmar C (1993) Myelinated nerve fibres in the CNS. Prog Neurobiol 40: 319–384.
- 3. Kuhlmann T, Miron V, Cuo Q, Wegner C, Antel J, et al. (2008) Differentiation block of oligodendroglial progenitor cells as a cause for remyelination failure in chronic multiple sclerosis. Brain.
- 4. Sugimori M, Nagao M, Parras CM, Nakatani H, Lebel M, et al. (2008) Ascl1 is required for oligodendrocyte development in the spinal cord. Development 135: 1271–1281.
- 5. Ligon KL, Fancy SP, Franklin RJ, Rowitch DH (2006) Olig gene function in CNS development and disease. Glia 54: 1–10.
- 6. Lu QR, Sun T, Zhu Z, Ma N, Garcia M, et al. (2002) Common developmental requirement for Olig function indicates a motor neuron/oligodendrocyte connection. Cell 109: 75–86.
- 7. Lu QR, Yuk D, Alberta JA, Zhu Z, Pawlitzky I, et al. (2000) Sonic hedgehog–regulated oligodendrocyte lineage genes encoding bHLH proteins in the mammalian central nervous system. Neuron 25: 317–329.
- 8. Novitch BG, Chen AI, Jessell TM (2001) Coordinate regulation of motor neuron subtype identity and pan-neuronal properties by the bHLH repressor Olig2. Neuron 31: 773–789.
- 9. Park HC, Shin J, Roberts RK, Appel B (2007) An olig2 reporter gene marks oligodendrocyte precursors in the postembryonic spinal cord of zebrafish. Dev Dyn 236: 3402–3407.
- 10. Takebayashi H, Nabeshima Y, Yoshida S, Chisaka O, Ikenaka K, et al. (2002) The basic helix-loop-helix factor olig2 is essential for the development of motoneuron and oligodendrocyte lineages. Curr Biol 12: 1157–1163.
- 11. Huang K, Tang W, Tang R, Xu Z, He Z, et al. (2008) Positive association between OLIG2 and schizophrenia in the Chinese Han population. Hum Genet 122: 659–660.
- 12. Georgieva L, Moskvina V, Peirce T, Norton N, Bray NJ, et al. (2006) Convergent evidence that oligodendrocyte lineage transcription factor 2 (OLIG2) and interacting genes influence susceptibility to schizophrenia. Proc Natl Acad Sci U S A 103: 12469–12474.
- 13. Uchida Y, Nakano S, Gomi F, Takahashi H (2007) Differential regulation of basic helix-loop-helix factors Mash1 and Olig2 by beta-amyloid accelerates both differentiation and death of cultured neural stem/progenitor cells. J Biol Chem 282: 19700–19709.
- 14. Lu QR, Park JK, Noll E, Chan JA, Alberta J, et al. (2001) Oligodendrocyte lineage genes (OLIG) as molecular markers for human glial brain tumors. Proc Natl Acad Sci U S A 98: 10851–10856.
- 15.
Zhang X, Horrell S, Delaney D, Gottlieb D (2008) ES Cells as a Platform for Analyzing Neural Gene Transcription. Stem Cells.
- 16. Sun T, Hafler BP, Kaing S, Kitada M, Ligon KL, et al. (2006) Evidence for motoneuron lineage-specific regulation of Olig2 in the vertebrate neural tube. Dev Biol 292: 152–164.
- 17. Bain G, Ray WJ, Yao M, Gottlieb DI (1996) Retinoic acid promotes neural and represses mesodermal gene expression in mouse embryonic stem cells in culture. Biochem Biophys Res Commun 223: 691–694.
- 18. Du ZW, Zhang SC (2004) Neural differentiation from embryonic stem cells: which way? Stem Cells Dev 13: 372–381.
- 19. Yao M, Bain G, Gottlieb DI (1995) Neuronal differentiation of P19 embryonal carcinoma cells in defined media. J Neurosci Res 41: 792–804.
- 20. Xian HQ, Werth K, Gottlieb DI (2005) Promoter analysis in ES cell-derived neural cells. Biochem Biophys Res Commun 327: 155–162.
- 21. Billon N, Jolicoeur C, Ying QL, Smith A, Raff M (2002) Normal timing of oligodendrocyte development from genetically engineered, lineage-selectable mouse ES cells. J Cell Sci 115: 3657–3665.
- 22. Bain G, Kitchens D, Yao M, Huettner JE, Gottlieb DI (1995) Embryonic stem cells express neuronal properties in vitro. Dev Biol 168: 342–357.
- 23. Liu S, Qu Y, Stewart TJ, Howard MJ, Chakrabortty S, et al. (2000) Embryonic stem cells differentiate into oligodendrocytes and myelinate in culture and after spinal cord transplantation. Proc Natl Acad Sci U S A 97: 6126–6131.
- 24. Brustle O, Jones KN, Learish RD, Karram K, Choudhary K, et al. (1999) Embryonic stem cell-derived glial precursors: a source of myelinating transplants. Science 285: 754–756.
- 25. Murakami K, Kojima T, Sakaki Y (2004) Assessment of clusters of transcription factor binding sites in relationship to human promoter, CpG islands and gene expression. BMC Genomics 5: 16.
- 26. Donaldson IJ, Chapman M, Kinston S, Landry JR, Knezevic K, et al. (2005) Genome-wide identification of cis-regulatory sequences controlling blood and endothelial development. Hum Mol Genet 14: 595–601.
- 27. Bauer DC, Bailey TL (2008) Studying the functional conservation of cis-regulatory modules and their transcriptional output. BMC Bioinformatics 9: 220.
- 28. Sandelin A, Bailey P, Bruce S, Engstrom PG, Klos JM, et al. (2004) Arrays of ultraconserved non-coding regions span the loci of key developmental genes in vertebrate genomes. BMC Genomics 5: 99.
- 29. Woolfe A, Goodson M, Goode DK, Snell P, McEwen GK, et al. (2005) Highly conserved non-coding sequences are associated with vertebrate development. PLoS Biol 3: e7.
- 30. Thomas JW, Touchman JW, Blakesley RW, Bouffard GG, Beckstrom-Sternberg SM, et al. (2003) Comparative analyses of multi-species sequences from targeted genomic regions. Nature 424: 788–793.
- 31. Hertz GZ, Hartzell GW 3rd, Stormo GD (1990) Identification of consensus patterns in unaligned DNA sequences known to be functionally related. Comput Appl Biosci 6: 81–92.
- 32. Hertz GZ, Stormo GD (1999) Identifying DNA and protein patterns with statistically significant alignments of multiple sequences. Bioinformatics 15: 563–577.
- 33. Matys V, Fricke E, Geffers R, Gossling E, Haubrock M, et al. (2003) TRANSFAC: transcriptional regulation, from patterns to profiles. Nucleic Acids Res 31: 374–378.
- 34. Bejerano G, Pheasant M, Makunin I, Stephen S, Kent WJ, et al. (2004) Ultraconserved elements in the human genome. Science 304: 1321–1325.
- 35. Chen CT, Wang JC, Cohen BA (2007) The strength of selection on ultraconserved elements in the human genome. Am J Hum Genet 80: 692–704.
- 36. Kyo S, Takakura M, Taira T, Kanaya T, Itoh H, et al. (2000) Sp1 cooperates with c-Myc to activate transcription of the human telomerase reverse transcriptase gene (hTERT). Nucl Acids Res 28: 669–677.
- 37. Rosmarin AG, Luo M, Caprio DG, Shang J, Simkevich CP (1998) Sp1 Cooperates with the ets Transcription Factor, GABP, to Activate the CD18 (beta 2 Leukocyte Integrin) Promoter. J Biol Chem 273: 13097–13103.
- 38.
Meissner A, Mikkelsen TS, Gu H, Wernig M, Hanna J, et al. (2008) Genome-scale DNA methylation maps of pluripotent and differentiated cells. Nature.
- 39. Takahashi K, Yamanaka S (2006) Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell 126: 663–676.
- 40. Hu B, Wu Z, Liu T, Ullenbruch MR, Jin H, et al. (2007) Gut-enriched Kruppel-like factor interaction with Smad3 inhibits myofibroblast differentiation. Am J Respir Cell Mol Biol 36: 78–84.
- 41. Nakatake Y, Fukui N, Iwamatsu Y, Masui S, Takahashi K, et al. (2006) Klf4 cooperates with Oct3/4 and Sox2 to activate the Lefty1 core promoter in embryonic stem cells. Mol Cell Biol 26: 7772–7782.
- 42. Vavouri T, McEwen GK, Woolfe A, Gilks WR, Elgar G (2006) Defining a genomic radius for long-range enhancer action: duplicated conserved non-coding elements hold the key. Trends Genet 22: 5–10.
- 43. Takebayashi H, Yoshida S, Sugimori M, Kosako H, Kominami R, et al. (2000) Dynamic expression of basic helix-loop-helix Olig family members: implication of Olig2 in neuron and oligodendrocyte differentiation and identification of a new member, Olig3. Mech Dev 99: 143–148.
- 44. Takebayashi H, Ohtsuki T, Uchida T, Kawamoto S, Okubo K, et al. (2002) Non-overlapping expression of Olig3 and Olig2 in the embryonic neural tube. Mech Dev 113: 169–174.
- 45. Li H, Lu Y, Smith HK, Richardson WD (2007) Olig1 and Sox10 interact synergistically to drive myelin basic protein transcription in oligodendrocytes. J Neurosci 27: 14375–14382.
- 46. Bronchain OJ, Pollet N, Ymlahi-Ouazzani Q, Dhorne-Pollet S, Helbling JC, et al. (2007) The olig family: phylogenetic analysis and early gene expression in Xenopus tropicalis. Dev Genes Evol 217: 485–497.
- 47. Karolchik D, Baertsch R, Diekhans M, Furey TS, Hinrichs A, et al. (2003) The UCSC Genome Browser Database. Nucleic Acids Res 31: 51–54.
- 48. Akaike H (1974) A new look at th estatistical model identification. IEEE Transactions on Automatic Control 19: 716–723.
- 49. Xian HQ, McNichols E, St Clair A, Gottlieb DI (2003) A subset of ES-cell-derived neural cells marked by gene targeting. Stem Cells 21: 41–49.