Dynamic reprogramming of chromatin accessibility during Drosophilaembryo development
- Sean Thomas†1,
- Xiao-Yong Li†2,
- Peter J Sabo1,
- Richard Sandstrom1,
- Robert E Thurman1,
- Theresa K Canfield1,
- Erika Giste1,
- William Fisher2,
- Ann Hammonds2,
- Susan E Celniker2,
- Mark D Biggin2 and
- John A Stamatoyannopoulos1Email author
© Thomas et al.; licensee BioMed Central Ltd. 2011
Received: 8 February 2011
Accepted: 11 May 2011
Published: 11 May 2011
The development of complex organisms is believed to involve progressive restrictions in cellular fate. Understanding the scope and features of chromatin dynamics during embryogenesis, and identifying regulatory elements important for directing developmental processes remain key goals of developmental biology.
We used in vivo DNaseI sensitivity to map the locations of regulatory elements, and explore the changing chromatin landscape during the first 11 hours of Drosophila embryonic development. We identified thousands of conserved, developmentally dynamic, distal DNaseI hypersensitive sites associated with spatial and temporal expression patterning of linked genes and with large regions of chromatin plasticity. We observed a nearly uniform balance between developmentally up- and down-regulated DNaseI hypersensitive sites. Analysis of promoter chromatin architecture revealed a novel role for classical core promoter sequence elements in directing temporally regulated chromatin remodeling. Another unexpected feature of the chromatin landscape was the presence of localized accessibility over many protein-coding regions, subsets of which were developmentally regulated or associated with the transcription of genes with prominent maternal RNA contributions in the blastoderm.
Our results provide a global view of the rich and dynamic chromatin landscape of early animal development, as well as novel insights into the organization of developmentally regulated chromatin features.
The progressive restriction of cellular fate is a hallmark of development and is believed to involve the sequential modification and perpetuation of chromatin states . However, it is currently unclear how this process unfolds at the level of chromatin structure, and whether early development is characterized chiefly by temporal restriction of a large potential pool of accessible chromatin elements or the progressive acquisition of potential manifested in the timed appearance of novel elements, or a combination thereof.
The Drosophila melanogaster embryo is one of the best characterized systems for addressing this challenge. During the first 11 hours of development, a single diploid cell, the fertilized egg (0 hours) undergoes nuclear division to form a blastoderm of approximately 6,000 undifferentiated cells (3 to 4 hours), followed by further division and differentiation into 40,000 cells organized into specific tissues such as nerve, muscle and epithelia (11 hours) [2, 3]. This morphological patterning is directed by a temporally ordered regulatory cascade [4–8]. Initiated by a few maternally supplied regulatory proteins, by the blastoderm stage some 40 or so sequence-specific transcription factors control the spatial and temporal expression of around a thousand genes [9–14]. By 11 hours, several hundred regulatory factors, many expressed in narrow subsets of cells, direct transcription of approximately 8,000 genes in patterns so intricate that they often change even between adjacent cells of the same cell type. An additional cohort of several hundred ubiquitously expressed transcription factors act throughout embryogenesis to facilitate the action of stage-selective regulators at promoters, enhancers, insulators and other cis-acting elements.
To understand the developmental control of transcription and morphogenesis, it is critical to identify the full set of sequence elements through which transcription factors and other genomic regulators act . The formation of active cis-regulatory complexes involves the dynamic interplay between sequence-specific DNA binding proteins and nucleosomes and chromatin organizing proteins [16–20]. Binding of multiple sequence-specific regulators within cis-regulatory regions results in markedly increased local chromatin accessibility to nucleases, both with respect to flanking genomic regions and to inactive genomic regions generally. For this reason, delineation of DNaseI hypersensitive sites (DHSs) has proven to be a particularly powerful strategy for mapping regulatory DNA in eukaryotic cells [21–24], and recent advances in sequencing technology have enabled DHS mapping at genome scale [25–29]. A salient advantage of this approach is that it permits precise delineation of potential regulatory DNA regions independent of a priori knowledge of the particular regulatory factor(s) that may be bound at any given region.
To map the occupancy patterns of specific regulators, chromatin immunoprecipitation (ChIP) has been applied to over 20 developmental transcription factors and RNA polymerase in the blastoderm embryo and, for several factors, at later stages of embryogenesis [30–36]. These studies collectively identify over 20,000 genomic regions occupied to varying degrees by at least one factor, with significant enrichment of known cis-regulatory modules (CRMs) among the most highly bound regions [30, 31, 33]. Recent studies have also mapped binding sites for CTCF and other insulator proteins in D. melanogaster embryos , as well as origin recognition complex (ORC) proteins in Drosophila Kc cells . Both of these features are associated with regions of active, accessible chromatin and nucleosome turnover. Analysis of 53 chromatin-associated proteins localized across the genome in Kc167 cells using DamID has distinguished five major chromatin states, including two active and three repressive states. Active states were enriched in actively transcribed genes, while one repressed state was particularly enriched in genes important for embryonic development.
Here we apply genome-scale, high-resolution mapping of in vivo DNaseI sensitivity to define the chromatin accessibility and regulatory DNA landscape of Drosophila early embryo development. We mapped DHSs across the D. melanogaster genome at five developmental stages (stages 5, 9, 10, 11 and 14) encompassing the transition from a pre-gastrulation (stage 5 blastoderm) to the largely differentiated tissues at stage 14, and in the widely used Kc167 cell line. Our results show that the chromatin landscapes of undifferentiated and more differentiated embryos are similar in terms of the number and distribution of chromatin accessibility and DHSs, with a largely balanced developmental acquisition and loss of DHSs and associated cis-regulatory potential. The dynamic chromatin landscape of development is characterized by focused temporally programmed changes occurring at the level of individual DHSs. This contrasts sharply with the wholesale changes in chromatin organization observed between embryos and a static cell line. We were able to associate thousands of developmentally patterned distal DHSs with distinct spatial and temporal expression patterns of linked genes as well as larger regions of chromatin plasticity. Analysis of chromatin remodeling at promoter regions revealed a novel role for classical core promoter sequence elements in directing temporally regulated chromatin architectures. An unexpected feature of the chromatin landscape was the presence of developmentally regulated, localized accessibility and weak DHSs over many protein-coding regions. Subsets of these regions are associated with blastoderm-stage transcription of genes that receive prominent maternal RNA contributions. The results collectively provide a global view of chromatin landscape dynamics during early animal development.
Developmental profiling of chromatin accessibility and DHSs
Landscape of Drosophila embryo DNase I hypersensitive sites
Consensus DHSs (FDR 1%)
Percentage of genome
Balanced developmental restriction and expansion of accessible chromatin
Replicate DNaseI sensitivity measurements from pooled nuclei from each stage were highly reproducible (mean genome-wide correlation for raw tag density R = 0.96; Figure 1c). DNaseI cleavage densities from immediately adjacent stages were also highly concordant, with monotonic decay of correlation between progressively more distant stages (Figure 1c). At the level of DHSs, we observed both strong persistence of DHSs between successive stages, and the appearance of new DHSs (Figure 1d). Of the detected DHSs within stage 14 chromatin, 54.7% were carried forward from stage 5, with the remainder (45%) having originated in stages 9 (4.5%), 10 (6.4%), 11 (9.6%), and 14 (24.5%) (Figure 1d). As such, the developmental restriction of cis-regulatory regions marked by DHSs appears to be largely balanced by the synchronous appearance of new elements.
Genomic distribution and relationship with genic and functional genomic annotations
To assess how comprehensively the chromatin accessibility data illuminated well-documented embryonic regulatory DNA regions, we analyzed 60 previously described experimentally validated CRMs active within blastoderm embryos and known to be bound by multiple transcription factors [33, 35, 41, 42]; 100% of these elements displayed significantly increased chromatin accessibility in stage 5 embryos. We obtained analogous results in a distinct set of CRMs identified initially using ChIP-chip data and tested in transgenic embryos (W. Fisher, A. Hammonds, X.-Y. Li, M.B. Eisen, M.D. Biggin and S.E. Celniker, in preparation). Of the 42 elements active in in vivo transgenic promoter experiments at stage 5, 100% exhibited high accessibility in stage 5 chromatin. Additionally, of the 45 CRMs active in vivo at stage 14, 70% showed significantly increased accessibility in stage 14 chromatin - a surprisingly high percentage in view of the fact that many later elements are active in only a small fraction of the cells of the embryo (W. Fisher, A. Hammonds, X.-Y. Li, M.B. Eisen, M.D. Biggin and S.E. Celniker, in preparation). The P-values for each of these associations are very low (P < 1e-16) using either the genome structure correction method or a binomial model.
To determine the genomic distribution of DHSs relative to genic annotations, we computed the proportions of DHSs around annotated transcription start sites (TSSs; from -60 to +40), and within 5' and 3' UTRs, protein coding exons, introns, and intergenic regions (Figure 2b). Overall, approximately 12% of DHSs were localized around TSSs, while 31% were found in introns, and 29% in more distal intergenic regions (Figure 2b). DHSs exhibited strong enrichment relative to random expectation around TSSs and 5' UTRs, moderate enrichment over protein coding exons, and relative depletion in intronic and intergenic regions (Figure 2b).
Distinct combinations of motifs predict early and late promoter accessibility patterns
Evidence has recently emerged that suggests a more complicated and active role for core promoter elements in regulated gene expression . We therefore examined the relationship between core promoter structure (as reflected in the pattern of core promoter motifs) and developmental alterations in core promoter remodeling/accessibility, which is a prerequisite for (though does not necessitate) transcriptional activity. Prior functional studies have extensively characterized several critical core promoter elements, including TATA, the initiator (INR), the downstream promoter element (DPE), and the DNA replication-related element (DRE or DREF) . In addition, six novel core promoter motifs have been defined on the basis of intra-genomic TSS comparisons and evolutionary conservation , of which one, MTE (motif ten element), was subsequently shown to facilitate INR-mediated transcription .
We therefore first determined the presence (or absence) of the aforementioned ten motifs within the core promoter regions (-60 to +40) defined relative to the annotated TSSs of all Drosophila genes. We then related the patterns of core promoter motif occurrence with developmental patterning of chromatin accessibility. This revealed a striking and nearly mutually exclusive relationship between specific sets of core promoter motifs and genes that exhibit constitutive or early promoter chromatin accessibility versus those with late-peaking accessibility (Figure 2c). Genes with either constitutive or early peaking accessibility are significantly enriched for DRE and motifs 1 and 7 (from Ohler et al. ), whereas genes with late-peaking accessibility are highly enriched for INR, DPE, and MTE motifs.
Changes in promoter motif composition are also accompanied by clear alterations in chromatin structure. While most promoters show a single accessibility peak centered just upstream of the TSS, others with specific motif combinations displayed more complex structures. For example, a subset of early accessible promoters with DRE and Ohler motifs 1 and 7 exhibit a prominent 'camelback' morphology, with a trough located approximately 150 bp upstream of the TSS (Figure 2d). By contrast, promoters with late-onset accessibility and enriched in INR, MTE, and, to a lesser extent, DPE, show single accessibility peaks more closely apposed to the TSS. Taken together, these findings suggest a prominent and previously unappreciated role for the core promoter in developmental patterning of promoter chromatin remodeling.
Developmentally regulated accessibility at protein-coding exons
We noted that a subset of DHSs overlapped coding exons, prompting us to explore this relationship more fully. In total, we identified 10,056 DHSs that overlapped the protein coding portions of exons in one or more developmental stages (Figure 2b). These elements were predominantly only weakly accessible, with mean DNaseI cleavage density approximately 2.5-fold lower than the mean for all other DHSs, and four-fold lower than average DHSs upstream of TSSs. This finding parallels prior observations of low-level regulatory factor occupancy over protein coding exons . Chromatin accessibility over coding exons displayed prominent developmental regulation, of similar magnitude to DHSs in other genomic regions (Figure S2 in Additional file 1).
We also observed systematic skewing of chromatin accessibility toward the 5' ends of exons and over immediately adjacent 5'-upstream intronic regions. The degree of 5' skewing was strongly correlated with RNA polymerase II occupancy over the exon as measured by ChIP-chip (Figure S3 in Additional file 1). The occurrence of peak DNaseI sensitivity immediately upstream of exons suggests that peri-exonic accessibility patterns may, in fact, reflect the actuation of nearby upstream intronic cis-regulatory elements.
Maternally loaded exons and blastoderm chromatin accessibility patterns
To visualize peri-exonic chromatin accessibility more clearly, we identified all exons of at least 320 bp in length with at least 300 bp of uninterrupted intronic sequence both 5' and 3' to the up- and down-stream intron-exon boundaries (n = 4,575 exons). We then computed chromatin accessibility over each peri-exonic region, and clustered these values into four groups reflecting increasing intensity and extent of exonic and exon-proximal accessibility (Figure S4 in Additional file 1). Surprisingly, these accessibility patterns were strongly correlated with the number of exons in each cluster that exhibited elevated RNA abundance (signal >50) between 0 and 2 hours of embryonic development . At this early time point prior to the onset of zygotic transcription, most RNA signal is expected to derive from maternally contributed transcripts . Increased blastoderm chromatin accessibility around maternally loaded exons suggests that these regions may be programmed for rapid early activation following the dissipation of maternal transcripts.
Extensive plasticity of chromatin domains between embryos and static cell lines
Stereotyped temporal patterns of chromatin accessibility at regulatory DNA
Many DHSs are characterized by significant stage-to-stage variability in DNaseI sensitivity, and show graded, monotonic increases or decreases in accessibility along a temporal axis (Figure 1; Figure S1 in Additional file 1). For example, the blastoderm-specific CRM marked by a DHS downstream of ftz  is accessible at stage 5 but not stages 9, 10, 11 and 14 (Figure 1). Also, neuronal enhancer active in late embryogenesis  first becomes accessible at stage 11 (Figure 1).
Number of developmentally dynamic elements belonging to different temporal pattern classes
Temporal pattern class
Number of DDEs
Percentage of totala
Stage 5 specific
Stage 9 specific
Stage 10 specific
Stage 11 specific
Stage 14 specific
Developmentally dynamic elements are conserved and cluster into dynamic domains
By clustering DDEs along the genome, we delineated 890 developmentally dynamic domains (DDDs) comprising significant clusters of DDEs with shared temporal profiles (Additional file 4). These domains ranged in size from 10 kb to 70 kb (mean 27 kb), and collectively encompassed 11.6% of the euchromatic genome (including DDEs as well as the intervening inaccessible regions). It is notable that some DDDs contain not only a cluster of DDEs with similar temporal profiles, but may also encompass interspersed constitutive elements that do not show temporal bias, or, more rarely, isolated elements that may show a temporal bias differing from the domain as a whole.
Developmentally dynamic domains mark developmental regulatory genes
We next examined how DDDs were distributed with respect to genes, and specifically if there were particular classes of genes that were enriched within DDDs generally (that is, irrespective of the particular temporal profile of the DDE). We observed a striking relationship between domains with high DDE density and genes encoding transcription factors, transcriptional co-factors, signal transducers, or other regulatory genes (Figure 5a). We also observed a specific concentration of developmental regulators (versus generic transcriptional regulators) within such DDDs. For example, the 200 domains with the highest density of DDEs contain, among other regulators, 28 transcription factors, of which 24 are well-studied developmental regulators. We also observed a quantitative relationship between DDE density and transcription factors, with lower DDE density associated with a lower proportion of transcription factors among the overlapped genes (Figure S6 in Additional file 1).
These results indicate that DDEs are enriched in CRMs important for controlling the regulators important for development, and suggest that the DDEs within high-density domains may encode CRMs controlling many developmental regulators. This indication is further supported by the observation that 85% of a set of 53 spatially patterned CRMs active at diverse points across embryogenesis (including many late elements; W. Fisher, A. Hammonds, X.-Y. Li, M.B. Eisen, M.D. Biggin and S.E. Celniker, unpublished data) coincide with a DDE, in spite of the fact that DDEs cover only 1.5% of the genome. Surprisingly, the few remaining regions with high DDE density that were not associated with transcriptional regulators were mainly associated instead with genes of unknown function, including many regions among the top 10% in DDE density. This suggests that these genes may, in fact, encode as-yet-uncharacterized developmental regulators.
Spatio-temporal gene expression patterns parallel developmentally dynamic chromatin
Not all of the approximately 300 BDGP gene expression annotation terms are significantly enriched in the accessibility clusters. Largely late tissue-specific expression terms are missed. This is not unexpected, however, as in stage 14 embryos there are many more tissues/annotation terms and these typically each represent a smaller percentage of the embryo. Thus, these terms are less likely to be captured as statistically significant in our analysis. We suggest our DDE clusters could represent a broad temporal mode of control, one that is in addition to the fine-grained tissue patterning captured in the BDGP's annotations. In which case, in the late embryo in particular, each DDE cluster could include genes that are each expressed in different tissues, but which share a common temporal control mechanism.
A longstanding question surrounding animal development is whether the transition from an undifferentiated pregastrula to a late embryo entails the sequential restriction or an expansion of the cis-regulatory landscape. We have mapped millions of individual in vivo DNaseI cleavages to produce the first genome-wide maps of the Drosophila chromatin accessibility landscape during development from an undifferentiated blastoderm to a highly differentiated late embryo. DHSs are the sine qua non of active cis-regulatory elements, and the fact that 100% of well-defined blastoderm and 75% of later stage cis-regulatory modules coincide with DNaseI-accessible elements suggests that a reasonably comprehensive mapping of accessible regulatory DNA regions active during the surveyed stages has been obtained. This is further supported by the extensive overlap of DHSs with mapped occupancy sites for blastoderm transcriptional regulators , the insulator factor CTCF, and DNA replication origins marked by the ORC complex.
The very high proportion of Kc167 DHSs localized within active chromatin domains defined by occupancy patterns of dozens of chromatin proteins  contrasts sharply with the >50% of embryonic DHSs that map within genomic domains designated as repressive in Kc cells. The presence of wholesale differences in chromatin compartmentalization between embryos and static cell lines highlights the dynamism of the chromatin landscape across developmental or differentiation gradients.
During early development, chromatin dynamics are exemplified by the widespread developmental patterning of DHSs, which appears to be largely balanced between the extinction of DHSs formed in earlier stages, and the timed appearance of new sites during the progress of development (Figure 1b). DDEs are: (i) evolutionarily conserved; (ii) clustered along the genome; (iii) particularly enriched around genes encoding transcriptional regulators; and (iv) associated with specific spatiotemporal expression programs. In the case of promoters, we identified specific sequence features associated with temporal down- versus up-regulation of chromatin accessibility. Unexpectedly, localized and developmentally regulated chromatin accessibility was also found over protein-coding sequences (albeit weakly), where it closely paralleled both RNA polymerase II occupancy as well as RNA abundance measured prior to the onset of zygotic transcription (0 to 2 hours). The observed blastoderm chromatin patterns may therefore reflect 'programming' of genes or protein-exons for rapid transcription activation coinciding with the dissipation of maternal RNA contributions.
Developmentally dynamic elements and domains
Developmental patterning of DHSs is highly stereotyped, with large cohorts of genomically dispersed sites displaying almost identical patterns of quantitative change during development. These cohorts are frequently associated with genes that fall into specific combinations of spatial and temporal expression classes. This suggests that the collective action of diverse developmental regulators results in limited complexity at the level of chromatin accessibility, which likely results from shared aspects of regulation among similarly behaved DHSs.
It has long been known that small groups of neighboring genes, such as the Bithorax and Antennapedia complexes [4, 52], exhibit temporally correlated expression. More recent work has shown that clustering of genes with related gene expression patterns is common and is also associated with clustered binding of chromatin organizing proteins, patterns of histone modification and the tendency of regions to be physically close to one another in the nucleus [53–56]. The clustering of DDEs showing similar temporal patterns into 10- to 70-kb domains thus likely reflects the coordinate regulation of individual genes by groups of different CRMs with similar temporal activity profiles.
A notable feature of the data is the decline in the total number of 1% FDR DHSs detected during embryogenesis (from approximately 30,000 in stage 5 to approximately 20,000 in stage 14; Table 1), which is paralleled by a substantial increase in the appearance of stage-specific elements. Indeed, stage 14 elements account for 75% of stage-specific DDEs. The appearance of novel elements at stage 14 is consistent with the emergence of specialized cell populations and the dramatic increase in spatially and temporally patterned gene expression at this stage versus blastoderm [10, 11, 13, 14]. Because our DNaseI experiments measured average accessibility for the whole embryo, it is likely that we have failed to detect some elements that are accessible in only a very small percentage of the cells. However, it seems unlikely that this technical failure is the sole explanation. Instead, other biological explanations are suggested by observing the fate of chromatin accessibility at stage 5 DHSs as development progresses. A large fraction of stage 5 DHSs exhibits gradually fading accessibility, as illustrated in Figures 1, 4c, and 5c, rather than suffering a rapid decline. One interpretation of this pattern is that the regulatory factors required for the maintenance of accessibility are diminishing in abundance. However, the number of sites affected is quite large, and is balanced by a large number of unaffected sites that would have been expected to be affected if general transcriptional factors were involved. Another explanation is that diminishing accessibility of stage 5 DHSs is a consequence of sequential cellular restriction of elements that may be accessible in early stages, but only destined for functional activity at later stages. Indeed, such pre-potentiation of chromatin accessibility at cis-regulatory DNA prior to the actual function of an element in control of transcription has long been described [16–20], suggesting that this is at least part of the reason why there are similar numbers of accessible regions in early and late embryos despite the fact that the total fraction of active CRMs is much higher later.
Developmentally patterned accessibility over promoter regions
Our results suggest that localized developmental patterning of chromatin accessibility at promoter elements is related, at least in part, to the structure of the core promoter. The core promoter is a universal mediator of transcription initiation by RNA polymerase II in eukaryotic cells, and has traditionally been regarded as a downstream target of cell- or condition-specific regulatory signals rather than as an intrinsic determinant of such regulation . However, limited evidence from select genes is emerging that suggests a more complicated and active role for core promoter elements in regulated gene expression . Prior functional studies have extensively characterized several critical core promoter elements including TATA, INR, DPE, and DRE/DREF . In addition, six novel core promoter motifs have been defined on the basis of intra-genomic TSS comparisons and evolutionary conservation , of which one (MTE) was subsequently shown to facilitate INR-mediated transcription . We found that distinct complements of these core promoter elements were associated with early (DRE/r1/r7) or late (INR/DPE/MTE) appearance of chromatin remodeling over the promoter region, and with the presence of distinct promoter chromatin accessibility morphologies. These results highlight broader effects of core promoter architectures, exposing a novel connection between core promoter architecture and the regulation of promoter chromatin remodeling.
The dynamic chromatin accessibility landscape of Drosophila early development exposed by our studies should provide a rich resource for future analyses. We have highlighted thousands of novel elements that appear to have the properties of cis-regulatory DNA, and which can be further explored both experimentally and computationally. The connection between the developmental timing of promoter chromatin remodeling and core promoter architecture identifies potential roles of previously unassigned motifs, and suggests links between established elements that can be tested experimentally. The correlation between peri-exonic chromatin accessibility patterns and pre-zygotic RNA abundance suggests a novel avenue for exploring the transition from maternal to zygotic transcription. Finally, the dramatic differences in chromatin compartmentalization between early embryos and model cell lines highlights the essential plasticity of the chromatin landscape.
Materials and methods
Nuclear isolation and DNaseI digestion
Nuclei from D. melanogaster embryos were isolated as described previously  and treated with DNAse I as previously described with some modifications. Briefly, the embryos were collected in population cages for 1 hour and allowed to develop to stage 5 (2 hours 10 minutes), 9 (3 hours 20 minutes), 10 (4 hours), 11 (5 hours 40 minutes), or 14 (9 hours 50 minutes) as desired at standard conditions. The embryos were dechorionated and homogenized in 5 ml cold buffer A (15 mM Tris HCl, pH 8.0, 15 mM NaCl, 60 mM KCl, 1 mM EDTA, 0.5 mM EGTA, 0.5 mM spermidine) containing 0.5 mM spermine, 0.5 mM dithiothreitol, and 1 mM phenylmethanesulfonylfluoride, for each gram of embryos by using a motor-driven dounce homogenizer. The homogenate was passed through Miracloth, and further homogenized using a dounce homogenizer with pestle B, for five to six strokes, and then 10% NP-40 was added drop-wise to a final concentration of 0.5% with gentle mixing. The nuclei samples were centrifuged in 1.5 ml aliquots in a micro-centrifuge at 3,000 rpm for 3 minutes at 4°C, and the nuclei pellet was washed with buffer A.
Kc167 cells were cultured in Schneider's medium supplemented with 10% heat-inactivated fetal bovine serum at 25°C in a humidified incubator. To isolate nuclei from Kc167 cells, cells were resuspended in buffer A with 0.025% IGEPAL for 5.5 minutes, the nuclei were pelleted in a micro-centrifuge at 3,000 rpm for 3 minutes at 4°C, and the nuclei pellet was washed with buffer A.
Nuclei from embryos and Kc167 cells were purified and treated with DNaseI as previously described  with some modifications. After being resuspended in a small volume of buffer A, the number of nuclei was determined, and 50 × 106 to 70 × 106 of the pooled nuclei were used in each DNAse I digestion reaction. The DNAse I digestion was carried out by incubating the nuclei with the indicated amount of DNAse I in 2.5-ml pre-equilibrated digestion buffer (buffer A plus 75 mM NaCl and 6 mM CaCl2) for 3 minutes at 37°C, and the reactions were stopped by the addition of 2.5 ml of the stop solution containing 50 mM Tris HCl, pH 8.0, 100 mM NaCl, 0.1% SDS, and 100 mM EDTA. The samples were then treated with Proteinase K, and extracted once with phenol/chloroform. Next, the DNA in the samples was fractionated through a sucrose gradient, and fragments ranging from 100 to 400 bp in size were isolated and an Illumina Genome Analyzer I was used to generate sequence tags for each sample. As described previously , the sequencing tags were used to map an average of 13.4 million DNAse I cleavage events per sample to D. melanogaster genomic sequence. The pairs of replica samples used to analyze stages 5, 9, 11 and 14 were taken from the same collections of staged embryos (one collection per stage), and the samples were divided in two after nuclei were purified but prior to DNaseI digestion. For stage 10, the replica samples were derived from different embryos collected on different days.
Delineation of DNAse I accessible regions and DNase hypersensitive sites
To identify regions of enriched accessibility, the number of tags within a 250-bp scanning window was compared to the expected number of tags based on a binomial model of the surrounding 50 kb to determine an enrichment z-score. Accessible regions were defined as collections of adjacent tags with z-scores greater than T where the number of background (random) regions with z ≥ T represent 1% of the number of experimental regions with z ≥T (that is, a 1% FDR control).
DNAse I tag density genome-wide was calculated by dividing the genome into 20-bp bins and adding the number of tags within a 150-bp window around each bin. The density scores were then used to identify peaks in accessibility within accessible regions, with each 150-bp peak being designated a DHS. The peak detection method allowed multiple DHSs per accessible region.
For each stage of embryonic development examined, two replicates were performed and the accessible regions for each replicate were intersected to yield a set of 'replicate-concordant' accessible regions (Tables S1 and S2 in Additional file 1). These represent very conservatively defined sets of accessible regions that were found in both replicates. The DHSs from each replicate were retained if they overlapped a DHS from another replicate by 75 bp or more (Table 1; Additional file 2). The union of non-intersecting DHSs from each stage constitute the final DHS list.
Conservation of DDEs relative to random genomic locations
Using the 12-way phastcon conservation scores  the average conservation score across each DDE (that did not overlap a coding sequence) was calculated, and then the total distribution of scores was determined. An equal number of random non-coding sequence positions were selected with equal sizes to the DDE pool and the average conservations were calculated to build the distribution of conservation at random genomic locations.
Identification of developmentally dynamic elements
Rank expectation was developed as a general method of identifying statistically significant differences between two matching whole-genome datasets (S. Thomas, S. Neph, A. Reynolds, J.A. Stamatoyannopoulos, manuscript in preparation). To identify all locations in dataset A that show increased signal over dataset B, the 20-bp bin scores in B are first ranked from low to high. Then A is sorted by the order of elements obtained from sorting B to achieve A'. That is to say that if the 675th bin in B has the lowest value in the entire dataset, then the 675th bin of A will be listed the first bin in A'. If A and B represent close replicates, then all of the re-ranked bins in A' will have neighbors with approximately equal scores; however, if there is a large difference at a particular site where the signal at B is low and the signal at A is high, then that location will appear out of place in A'. The probability that the score at a bin is drawn from the same distribution as its neighbors is determined from the Gaussian z-score from a local window of scores around each bin in A', since the median absolute variation (mad) around the median in these local windows can be approximated by a normal distribution. Rank expectation was performed on each replicate and in each polarity of comparison. Because two replicates of each stage were performed, for each location there were four measurements indicating whether or not it showed significant enrichment in a given stage over another stage. A bin was said to show 'consistent enrichment' if three or more of these measurements indicated enrichment after controlling for multiple testing using a Benjamini-Hochberg FDR control . Finally, the pairwise enrichment comparisons were tabulated and bins that displayed specific temporal patterns were identified. Bins that showed stage 5-specific chromatin structure, for example, were easily identified from the data as showing consistent enrichment in stage 5 over all other stages examined. Individual 20-bp bins that exhibited change and were adjacent to neighboring bins with similar patterns were merged together to form larger regions defined as DDEs.
Identification of developmentally dynamic domains
The number of base pairs covered by all DDEs within 10 kb of each 20-bp genomic bin was calculated. A resampling method was used to assess the statistical significance of peaks in DDE density. For each resample, a binomial model was used to draw a number of DDEs that randomly mapped to a particular 10-kb window of the genome. For each randomly mapped DDE a size was drawn from the density of DDE sizes and the DDE density was calculated for the hypothetical window. Ten million bootstraps were used to estimate the probabilities associated with DDE density scores. Peaks in DDE density with probabilities beyond the significance threshold set by Benjamini-Hochberg FDR control  at α = 0.05 were defined as DDDs (Additional file 4). The nearest gene to each domain was identified and any relevant gene ontology categories for those genes were identified.
Likewise, the DDE density was calculated for each TSS in the genome . The genes were ranked by DDE density scores and broken into 200-gene bins. The percentage of genes in each bin that were transcription factors was then calculated.
Analysis of similarly-patterned DDEs
Thus, if a particular site shows stage 5-specific chromatin, the resulting score would be a large positive number, and if the site was constitutive, then ρi would approach 0.
To determine the degree to which neighboring DDE tended to have similar patterns of accessibility through development, the ρi from adjacent DDEs were compared using a binomial model. If both DDEs exhibited early or late patterns, that constituted a successful Bernoulli trial. The number of observed successes between adjacent DDEs was compared to the binomial distribution to determine a probability of seeing that number of successes randomly. DDEs were then compared to their neighbor's neighbor (two DDEs away) and then to DDEs separated by three DDEs, and so on, all under the background binomial model assuming equal probability of success or failure.
Overlap of DNAse accessible regions and DDEs with active CRMs
We analyzed a set of 53 CRMs that were initially identified based on ChIP-chip data and subsequently shown to be active at different stages of embryogenesis (W. Fisher, A. Hammonds, X.-Y. Li, M.B. Eisen, M.D. Biggin and S.E. Celniker, unpublished data). The overlap between these sequences and DHSs and DDEs was determined as the number of CRMs that overlapped an accessible region or a DDE by at least 1 bp, divided by the total number of CRMs active at any analyzed stage. The statistical significance of this association was measured using the Genome Structure Correction tool  and by a binomial model in R .
Correlating DDEs with spatio-temporal expression patterns of nearby genes
The 64 clusters of DDEs were mapped to the nearest gene, and the BDGP mRNA in situ expression terms for all of the unique genes were identified . For each of the approximately 300 expression terms a hypergeometric model was used to determine the probability of choosing 'b' genes with that pattern given that there are 'B' total genes with that pattern out of 'N' total genes in the genome and that 'n' genes were drawn without replacement.
Analysis of core promoter elements
The peak DNAse I cleavage density was calculated for the core promoters (-60 to +40) of each gene from the release 4.3 version of the D. melanogaster genome obtained from FlyBase . Using the motif scanning tool FIMO from the MEME package , the sequences of the -60 to +40 promoter regions were then scanned for the presence (P < 0.0005) of one or more of the ten motifs previously found at core promoters . Promoters were then clustered (k-means) into ten groups comprising similar accessibility profiles. These groups formed three meta-clusters: one exhibiting constitutive accessibility (41% of TSSs); a second with down-regulated accessibility (44%); and a third with up-regulated accessibility (15%). For each cluster, and for each of the ten motifs, the percentage of promoters with the given motif was calculated in order to gauge differences in motif enrichment between clusters.
Analysis of peri-exonic chromatin accessibility patterns
The peak DNAse I cleavage density was calculated for each 20-bp increment within a 300-bp window around each DHS exon obtained from the release 4.3 version of the D. melanogaster genome . The density values were aligned by direction of transcription through the exon and were then aligned separately by the 5' exon boundary and the 3' exon boundary. The total list of exons was then filtered to identify the approximately 4,500 exons whose nearest exon was at least 300 bp away from both the 5' and 3' boundary and whose total exon length was greater than 600 bp. To characterize differences in transcription among exons with different DNAse I cleavage patterns, the DNAse I cleavage densities across the 5' exon boundaries were separated into four kmeans-derived clusters. The average expression  over each exon between 0 and 2 hours was calculated. Within each cluster, the percentage of exons with elevated expression (signal >25) was calculated.
All sequence data have been deposited in the NCBI Short Read Archive (SRA) under the following accession numbers: [SRA:SRP002474.1, SRA:SRX020691.4, SRA:SRX020692.1, SRA:SRX020693.1, SRA:SRX020694.1, SRA:SRX020695.1, SRA:SRX020696.1, SRA:SRX020697.1, SRA:SRX020698.1, SRA:SRX020699.1, SRA:SRX020700.1, SRA:SRX041410].
Berkeley Drosophila Genome Project
developmentally dynamic domain
developmentally dynamic element
DNase I hypersensitive site
downstream promoter element
DNA replication-related element
false discovery rate
origin recognition complex
transcription start site
This work is part of collaboration between the Berkeley Drosophila Transcription Network Project (BDTNP) and the Stamatoyannopoulos lab at UW. Special thanks to Brendan Henry for technical assistance during analysis and to the members of the BDTNP for thoughtful comments on, and support of, this project. This work was funded by the US National Institutes of Health (NIH) under grants GM704403 (to MDB, SC, and MBE), R01GM71923 (JAS), and T90 HG 004007-04 (ST). Work at Lawrence Berkeley National Laboratory was conducted under Department of Energy contract DE-AC02-05CH11231.
- Graf T, Enver T: Forcing cells to change lineages. Nature. 2009, 462: 587-594. 10.1038/nature08533.PubMedView ArticleGoogle Scholar
- Campos-Ortega JA, aH V: The Embryonic Development of Drosophila melanogaster. 1997, Berlin: Springer-Verlag, SecondView ArticleGoogle Scholar
- Weigmann K, Klapper R, Strasser T, Rickert C, Technau G, Jackle H, Janning W, Klambt C: FlyMove--a new way to look at development of Drosophila. Trends Genet. 2003, 19: 310-311. 10.1016/S0168-9525(03)00050-7.PubMedView ArticleGoogle Scholar
- Lewis EB: A gene complex controlling segmentation in Drosophila. Nature. 1978, 276: 565-570. 10.1038/276565a0.PubMedView ArticleGoogle Scholar
- Nusslein-Volhard C, Wieschaus E: Mutations affecting segment number and polarity in Drosophila. Nature. 1980, 287: 795-801. 10.1038/287795a0.PubMedView ArticleGoogle Scholar
- Rivera-Pomar R, Jackle H: From gradients to stripes in Drosophila embryogenesis: filling in the gaps. Trends Genet. 1996, 12: 478-483. 10.1016/0168-9525(96)10044-5.PubMedView ArticleGoogle Scholar
- St Johnston D, Nusslein-Volhard C: The origin of pattern and polarity in the Drosophila embryo. Cell. 1992, 68: 201-219. 10.1016/0092-8674(92)90466-P.PubMedView ArticleGoogle Scholar
- Stathopoulos A, Levine M: Genomic regulatory networks and animal development. Dev Cell. 2005, 9: 449-462. 10.1016/j.devcel.2005.09.005.PubMedView ArticleGoogle Scholar
- Adryan B, Teichmann SA: The developmental expression dynamics of Drosophila melanogaster transcription factors. Genome Biol. 2010, 11: R40-10.1186/gb-2010-11-4-r40.PubMedPubMed CentralView ArticleGoogle Scholar
- Anderson KV, Lengyel JA: Changing rates of DNA and RNA synthesis in Drosophila embryos. Dev Biol. 1981, 82: 127-138. 10.1016/0012-1606(81)90434-6.PubMedView ArticleGoogle Scholar
- Liang Z, Biggin MD: Eve and ftz regulate a wide array of genes in blastoderm embryos: the selector homeoproteins directly or indirectly regulate most genes in Drosophila. Development. 1998, 125: 4471-4482.PubMedGoogle Scholar
- Manak JR, Dike S, Sementchenko V, Kapranov P, Biemar F, Long J, Cheng J, Bell I, Ghosh S, Piccolboni A, Gingeras TR: Biological function of unannotated transcription during the early development of Drosophila melanogaster. Nat Genet. 2006, 38: 1151-1158. 10.1038/ng1875.PubMedView ArticleGoogle Scholar
- Tomancak P, Beaton A, Weiszmann R, Kwan E, Shu S, Lewis SE, Richards S, Ashburner M, Hartenstein V, Celniker SE, Rubin GM: Systematic determination of patterns of gene expression during Drosophila embryogenesis. Genome Biol. 2002, 3: RESEARCH0088-PubMedPubMed CentralView ArticleGoogle Scholar
- Tomancak P, Berman BP, Beaton A, Weiszmann R, Kwan E, Hartenstein V, Celniker SE, Rubin GM: Global analysis of patterns of gene expression during Drosophila embryogenesis. Genome Biol. 2007, 8: R145-10.1186/gb-2007-8-7-r145.PubMedPubMed CentralView ArticleGoogle Scholar
- Biggin MD, Tjian R: Transcriptional regulation in Drosophila: the post-genome challenge. Funct Integr Genomics. 2001, 1: 223-234. 10.1007/s101420000021.PubMedView ArticleGoogle Scholar
- Boeger H, Griesenbeck J, Kornberg RD: Nucleosome retention and the stochastic nature of promoter chromatin remodeling for transcription. Cell. 2008, 133: 716-726. 10.1016/j.cell.2008.02.051.PubMedPubMed CentralView ArticleGoogle Scholar
- Felsenfeld G, Groudine M: Controlling the double helix. Nature. 2003, 421: 448-453. 10.1038/nature01411.PubMedView ArticleGoogle Scholar
- Henikoff S: Nucleosome destabilization in the epigenetic regulation of gene expression. Nat Rev Genet. 2008, 9: 15-26.PubMedView ArticleGoogle Scholar
- John S, Sabo PJ, Johnson TA, Sung MH, Biddie SC, Lightman SL, Voss TC, Davis SR, Meltzer PS, Stamatoyannopoulos JA, Hager GL: Interaction of the glucocorticoid receptor with the chromatin landscape. Mol Cell. 2008, 29: 611-624. 10.1016/j.molcel.2008.02.010.PubMedView ArticleGoogle Scholar
- Wallrath LL, Lu Q, Granok H, Elgin SC: Architectural variations of inducible eukaryotic promoters: preset and remodeling chromatin structures. Bioessays. 1994, 16: 165-170. 10.1002/bies.950160306.PubMedView ArticleGoogle Scholar
- Gross DS, Garrard WT: Nuclease hypersensitive sites in chromatin. Annu Rev Biochem. 1988, 57: 159-197. 10.1146/annurev.bi.57.070188.001111.PubMedView ArticleGoogle Scholar
- Keene MA, Corces V, Lowenhaupt K, Elgin SC: DNase I hypersensitive sites in Drosophila chromatin occur at the 5' ends of regions of transcription. Proc Natl Acad Sci USA. 1981, 78: 143-146. 10.1073/pnas.78.1.143.PubMedPubMed CentralView ArticleGoogle Scholar
- Li Q, Peterson KR, Fang X, Stamatoyannopoulos G: Locus control regions. Blood. 2002, 100: 3077-3086. 10.1182/blood-2002-04-1104.PubMedPubMed CentralView ArticleGoogle Scholar
- Wu C: The 5' ends of Drosophila heat shock genes in chromatin are hypersensitive to DNase I. Nature. 1980, 286: 854-860. 10.1038/286854a0.PubMedView ArticleGoogle Scholar
- Birney E, Stamatoyannopoulos JA, Dutta A, Guigo R, Gingeras TR, Margulies EH, Weng Z, Snyder M, Dermitzakis ET, Thurman RE, et al: Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project. Nature. 2007, 447: 799-816. 10.1038/nature05874.PubMedView ArticleGoogle Scholar
- Boyle AP, Davis S, Shulha HP, Meltzer P, Margulies EH, Weng Z, Furey TS, Crawford GE: High-resolution mapping and characterization of open chromatin across the genome. Cell. 2008, 132: 311-322. 10.1016/j.cell.2007.12.014.PubMedPubMed CentralView ArticleGoogle Scholar
- Hesselberth JR, Chen X, Zhang Z, Sabo PJ, Sandstrom R, Reynolds AP, Thurman RE, Neph S, Kuehn MS, Noble WS, et al: Global mapping of protein-DNA interactions in vivo by digital genomic footprinting. Nat Methods. 2009, 6: 283-289. 10.1038/nmeth.1313.PubMedPubMed CentralView ArticleGoogle Scholar
- Sabo PJ, Hawrylycz M, Wallace JC, Humbert R, Yu M, Shafer A, Kawamoto J, Hall R, Mack J, Dorschner MO, et al: Discovery of functional noncoding elements by digital analysis of chromatin structure. Proc Natl Acad Sci USA. 2004, 101: 16837-16842. 10.1073/pnas.0407387101.PubMedPubMed CentralView ArticleGoogle Scholar
- Sekimata M, Perez-Melgosa M, Miller SA, Weinmann AS, Sabo PJ, Sandstrom R, Dorschner MO, Stamatoyannopoulos JA, Wilson CB: CCCTC-binding factor and the transcription factor T-bet orchestrate T helper 1 cell-specific structure and function at the interferon-gamma locus. Immunity. 2009, 31: 551-564. 10.1016/j.immuni.2009.08.021.PubMedPubMed CentralView ArticleGoogle Scholar
- Bradley RK, Li XY, Trapnell C, Davidson S, Pachter L, Chu HC, Tonkin LA, Biggin MD, Eisen MB: Binding site turnover produces pervasive quantitative changes in transcription factor binding between closely related Drosophila species. PLoS Biol. 2010, 8: e1000343-10.1371/journal.pbio.1000343.PubMedPubMed CentralView ArticleGoogle Scholar
- Li XY, MacArthur S, Bourgon R, Nix D, Pollard DA, Iyer VN, Hechmer A, Simirenko L, Stapleton M, Luengo Hendriks CL, et al: Transcription factors bind thousands of active and inactive regions in the Drosophila blastoderm. PLoS Biol. 2008, 6: e27-10.1371/journal.pbio.0060027.PubMedPubMed CentralView ArticleGoogle Scholar
- Li XY, Thomas S, Sabo PJ, Eisen MB, Stamatoyannopoulos JA, Biggin MD: The role of chromatin accessibility in directing the widespread, overlapping patterns of Drosophila transcription factor binding. Genome Biol. 2011, 12: R34-10.1186/gb-2011-12-4-r34.PubMedPubMed CentralView ArticleGoogle Scholar
- Macarthur S, Li XY, Li J, Brown JB, Chu HC, Zeng L, Grondona BP, Hechmer A, Simirenko L, Keranen SV, et al: Developmental roles of 21 Drosophila transcription factors are determined by quantitative differences in binding to an overlapping set of thousands of genomic regions. Genome Biol. 2009, 10: R80-10.1186/gb-2009-10-7-r80.PubMedPubMed CentralView ArticleGoogle Scholar
- Sandmann T, Girardot C, Brehme M, Tongprasit W, Stolc V, Furlong EE: A core transcriptional network for early mesoderm development in Drosophila melanogaster. Genes Dev. 2007, 21: 436-449. 10.1101/gad.1509007.PubMedPubMed CentralView ArticleGoogle Scholar
- Zeitlinger J, Zinzen RP, Stark A, Kellis M, Zhang H, Young RA, Levine M: Whole-genome ChIP-chip analysis of Dorsal, Twist, and Snail suggests integration of diverse patterning processes in the Drosophila embryo. Genes Dev. 2007, 21: 385-390. 10.1101/gad.1509607.PubMedPubMed CentralView ArticleGoogle Scholar
- Zinzen RP, Girardot C, Gagneur J, Braun M, Furlong EE: Combinatorial binding predicts spatio-temporal cis-regulatory activity. Nature. 2009, 462: 65-70. 10.1038/nature08531.PubMedView ArticleGoogle Scholar
- Negre N, Brown CD, Shah PK, Kheradpour P, Morrison CA, Henikoff JG, Feng X, Ahmad K, Russell S, White RA, et al: A comprehensive map of insulator elements for the Drosophila genome. PLoS Genet. 6: e1000814-
- MacAlpine HK, Gordan R, Powell SK, Hartemink AJ, MacAlpine DM: Drosophila ORC localizes to open chromatin and marks sites of cohesin complex loading. Genome Res. 20: 201-211.
- Sabo PJ, Kuehn MS, Thurman R, Johnson BE, Johnson EM, Cao H, Yu M, Rosenzweig E, Goldy J, Haydock A, et al: Genome-scale mapping of DNase I sensitivity in vivo using tiling DNA microarrays. Nat Methods. 2006, 3: 511-518. 10.1038/nmeth890.PubMedView ArticleGoogle Scholar
- Adams MD, Celniker SE, Holt RA, Evans CA, Gocayne JD, Amanatides PG, Scherer SE, Li PW, Hoskins RA, Galle RF, et al: The genome sequence of Drosophila melanogaster. Science. 2000, 287: 2185-2195. 10.1126/science.287.5461.2185.PubMedView ArticleGoogle Scholar
- Berman BP, Pfeiffer BD, Laverty TR, Salzberg SL, Rubin GM, Eisen MB, Celniker SE: Computational identification of developmental enhancers: conservation and function of transcription factor binding-site clusters in Drosophila melanogaster and Drosophila pseudoobscura. Genome Biol. 2004, 5: R61-10.1186/gb-2004-5-9-r61.PubMedPubMed CentralView ArticleGoogle Scholar
- Schroeder MD, Pearce M, Fak J, Fan H, Unnerstall U, Emberly E, Rajewsky N, Siggia ED, Gaul U: Transcriptional control in the segmentation gene network of Drosophila. PLoS Biol. 2004, 2: E271-10.1371/journal.pbio.0020271.PubMedPubMed CentralView ArticleGoogle Scholar
- Goodrich JA, Tjian R: Unexpected roles for core promoter recognition factors in cell-type-specific transcription and gene regulation. Nat Rev Genet. 11: 549-558.
- Ohler U, Liao GC, Niemann H, Rubin GM: Computational analysis of core promoters in the Drosophila genome. Genome Biol. 2002, 3: RESEARCH0087-PubMedPubMed CentralView ArticleGoogle Scholar
- Lim CY, Santoso B, Boulay T, Dong E, Ohler U, Kadonaga JT: The MTE, a new core promoter element for transcription by RNA polymerase II. Genes Dev. 2004, 18: 1606-1617. 10.1101/gad.1193404.PubMedPubMed CentralView ArticleGoogle Scholar
- Schier AF: The maternal-zygotic transition: death and birth of RNAs. Science. 2007, 316: 406-407. 10.1126/science.1140693.PubMedView ArticleGoogle Scholar
- Kharchenko PV, Alekseyenko AA, Schwartz YB, Minoda A, Riddle NC, Ernst J, Sabo PJ, Larschan E, Gorchakov AA, Gu T, et al: Comprehensive analysis of the chromatin landscape in Drosophila melanogaster. Nature. 471: 480-485.
- Filion GJ, van Bemmel JG, Braunschweig U, Talhout W, Kind J, Ward LD, Brugman W, de Castro IJ, Kerkhoven RM, Bussemaker HJ, van Steensel B: Systematic Protein Location Mapping Reveals Five Principal Chromatin Types in Drosophila Cells. Cell. 143: 212-224.
- Calhoun VC, Levine M: Long-range enhancer-promoter interactions in the Scr-Antp interval of the Drosophila Antennapedia complex. Proc Natl Acad Sci USA. 2003, 100: 9878-9883. 10.1073/pnas.1233791100.PubMedPubMed CentralView ArticleGoogle Scholar
- Hiromi Y, Kuroiwa A, Gehring WJ: Control elements of the Drosophila segmentation gene fushi tarazu. Cell. 1985, 43: 603-613. 10.1016/0092-8674(85)90232-6.PubMedView ArticleGoogle Scholar
- Hon G, Ren B, Wang W: ChromaSig: a probabilistic approach to finding common chromatin signatures in the human genome. PLoS Comput Biol. 2008, 4: e1000201-10.1371/journal.pcbi.1000201.PubMedPubMed CentralView ArticleGoogle Scholar
- McGinnis W, Krumlauf R: Homeobox genes and axial patterning. Cell. 1992, 68: 283-302. 10.1016/0092-8674(92)90471-N.PubMedView ArticleGoogle Scholar
- de Wit E, Braunschweig U, Greil F, Bussemaker HJ, van Steensel B: Global chromatin domain organization of the Drosophila genome. PLoS Genet. 2008, 4: e1000045-10.1371/journal.pgen.1000045.PubMedPubMed CentralView ArticleGoogle Scholar
- Dekker J: Gene regulation in the third dimension. Science. 2008, 319: 1793-1794. 10.1126/science.1152850.PubMedPubMed CentralView ArticleGoogle Scholar
- Fullwood MJ, Liu MH, Pan YF, Liu J, Xu H, Mohamed YB, Orlov YL, Velkov S, Ho A, Mei PH, et al: An oestrogen-receptor-alpha-bound human chromatin interactome. Nature. 2009, 462: 58-64. 10.1038/nature08497.PubMedPubMed CentralView ArticleGoogle Scholar
- Spellman PT, Rubin GM: Evidence for large domains of similarly expressed genes in the Drosophila genome. J Biol. 2002, 1: 5-10.1186/1475-4924-1-5.PubMedPubMed CentralView ArticleGoogle Scholar
- Thomas MC, Chiang CM: The general transcription machinery and general cofactors. Crit Rev Biochem Mol Biol. 2006, 41: 105-178. 10.1080/10409230600648736.PubMedView ArticleGoogle Scholar
- Carr A, Biggin MD: Accessibility of transcriptionally inactive genes is specifically reduced at homeoprotein-DNA binding sites in Drosophila. Nucleic Acids Res. 2000, 28: 2839-2846. 10.1093/nar/28.14.2839.PubMedPubMed CentralView ArticleGoogle Scholar
- Siepel A, Bejerano G, Pedersen JS, Hinrichs AS, Hou M, Rosenbloom K, Clawson H, Spieth J, Hillier LW, Richards S, et al: Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome Res. 2005, 15: 1034-1050. 10.1101/gr.3715005.PubMedPubMed CentralView ArticleGoogle Scholar
- Benjamini Y, Hochberg Y: Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society Series B (Methodological). 1995, 57: 289-300.Google Scholar
- Drysdale RA, Crosby MA: FlyBase: genes and gene models. Nucleic Acids Res. 2005, 33: D390-395.PubMedPubMed CentralView ArticleGoogle Scholar
- R-Development-Core-Team: R: A Language and Environment for Statistical Computing. 2009, Vienna, Austria: R Foundation for Statistical ComputingGoogle Scholar
- Tweedie S, Ashburner M, Falls K, Leyland P, McQuilton P, Marygold S, Millburn G, Osumi-Sutherland D, Schroeder A, Seal R, Zhang H: FlyBase: enhancing Drosophila Gene Ontology annotations. Nucleic Acids Res. 2009, 37: D555-559. 10.1093/nar/gkn788.PubMedPubMed CentralView ArticleGoogle Scholar
- Bailey TL, Boden M, Buske FA, Frith M, Grant CE, Clementi L, Ren J, Li WW, Noble WS: MEME SUITE: tools for motif discovery and searching. Nucleic Acids Res. 2009, 37: W202-208. 10.1093/nar/gkp335.PubMedPubMed CentralView ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.