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Proc Natl Acad Sci U S A. 2005 December 20; 102(51): 18479–18484. Published online 2005 December 9. doi: 10.1073/pnas.0507030102. | PMCID: PMC1317932 |
Copyright © 2005, The National Academy of Sciences Developmental Biology Mapping Dmef2-binding regulatory modules by using a ChIP-enriched in silico targets approach Guillaume Junion,* Teresa Jagla,* Sebastien Duplant,† Romain Tapin,* Jean-Philippe Da Ponte,* and Krzysztof Jagla*‡ *Institut National de la Santé et de la Recherche Médicale Unité 384, Faculté de Médecine, 28 Place Henri Dunant, 63000 Clermont-Ferrand, France; and †Soluscience S.A., 28 Place Henri Dunant, 63000 Clermont-Ferrand, France Received August 13, 2005; Accepted October 27, 2005. Mapping the regulatory modules to which transcription factors bind in vivo is a key step toward understanding of global gene expression programs. We have developed a chromatin immunoprecipitation (ChIP)-chip strategy for identifying factor-specific regulatory regions acting in vivo. This method, called the ChIP-enriched in silico targets (ChEST) approach, combines immunoprecipitation of cross-linked protein-DNA complexes (X-ChIP) with in silico prediction of targets and generation of computed DNA microarrays. We report the use of ChEST in Drosophila to identify several previously unknown targets of myocyte enhancer factor 2 (MEF2), a key regulator of myogenic differentiation. Our approach was validated by demonstrating that the identified sequences act as enhancers in vivo and are able to drive reporter gene expression specifically in MEF2-positive muscle cells. Presented here, the ChEST strategy was originally designed to identify regulatory modules in Drosophila, but it can be adapted for any sequenced and annotated genome. Keywords: Dmef2, transcription factor Mapping the interactions of regulatory proteins with their cognate target sequences in vivo is an important step toward building transcriptional regulatory networks. Several computational approaches have been developed to predict cis-regulatory modules (CRMs) in large and complex genomes ( 1- 11). Despite these advances, only a fraction of the predicted CRMs were found to act as bona fide enhancers ( 1). Thus, in silico targets need to be validated in an in vivo context where the recognition of DNA sequences by a given transcription factor (TF) is influenced by chromatin structure and interacting cofactors. The genomewide repertoire of motifs to which TFs bind in vivo can be revealed by formaldehyde cross-linking and chromatin immunoprecipitation (X-ChIP) using factor-specific antibodies ( 12- 14). However, the X-ChIP-based approaches ( 12- 14) are time-consuming because they involve cloning, sequencing, and mapping of immunoprecipitated DNA fragments. Easier access to CRMs is expected to be achieved by combining X-ChIP with genomic microarrays (ChIP-chip strategy). The ChIP-chip was first developed for yeast ( 15) and more recently adapted for TF targets in human cells. Three different types of human genomic microarrays have been used in ChIP-chip approaches: the arrays for human chromosomes 21 and 22 ( 16, 17), the CpG islands ( 18), and the selected core promoters ( 19). Although these efforts enabled the identification of in vivo-acting TF targets, the available CpG or core promoter arrays do not cover CRMs located in introns or distant from genes. Moreover, extending genomic arrays to cover the entire human genome and some model organisms significantly increases the costs of genomewide ChIP-chip approaches, making them unavailable to most researchers. To address these limitations, we developed a ChIP-enriched in silico targets (ChEST) strategy (), designed by combining in silico and in vivo approaches previously used separately for genomewide mapping of CRMs. ChEST involves a software-assisted prediction of TF-specific CRMs, which are spotted to produce a computed CRM microarray. In parallel, the in vivo pool of targets of a given TF is isolated by formaldehyde cross-linking/chromatin immunoprecipitation (X-ChIP) and used as a probe for hybridization with the array generated (). Here, we take advantage of genome scanning tools and annotations available for the fruit fly genome and demonstrate that ChEST allows rapid identification of in vivo TF targets in Drosophila (). Using the ChEST approach, we uncovered a large set of motifs to which binds the key myogenic factor Dmef2 ( 20, 21). We opted to use Dmef2 for the following reasons: ( i) it is expressed in all differentiating muscle and cardiac cell precursors, which represent a large proportion of cells in the embryo, thus creating favorable conditions for ChIP; ( ii) Dmef2-dependent enhancers have already been reported ( 22- 26), making it possible to use them as a positive control; and ( iii) Dmef2 is a key regulator of myogenic differentiation, and identifying its direct targets is of prime importance. In Silico Prediction of CRMs and Generation of Computed CRM Array. Custom-developed scanning/filtering scafi software ( www.soluscience.fr/dup_soft) was used for in silico CRM prediction. scafi uses fly enhancer ( www.flyenhancer.org) as its scanning engine. Scanning parameters for Dmef2 CRMs are shown in Table 1. The three previously reported in vivo Dmef2-binding sites identified in the vicinity of Paramyosin/b3-tubulin, Actin 57B, and Dmef2 (auto-regulation) ( 22- 25) were combined with different numbers of E-box/E-box related sequences ( 27) in a short genomic window (see above). This led to the prediction of >1,200 Dmef2-dependent CRMs. We did not use for scanning the fourth previously identified Dmef2-binding site ( 26) composed of AT only and located upstream of Tropomyosin. The subsequent filtering steps (for details, see Fig. 5, which is published as supporting information on the PNAS web site) were based on the distance of predicted CRMs in relation to adjacent genes [available at www.flyenhancer.org ( 28)] and on the annotations of potential target genes [available at flybase ( http://flybase.bio.indiana.edu) and the Berkeley Drosophila Genome Project in situ database ( www.fruitfly.org)]. Only CRMs located within 12 kb of genes annotated as having mesodermal function and/or expressed in the mesoderm or in a subset of mesodermal cells were selected, meaning that the CRMs laying in the vicinity of genes of unknown function and expression were rejected (for details of selection, see Fig. 5). In general, a wide range of scanning and filtering conditions can be applied. A large number of CRMs will be predicted by increasing the size of the genomic window in which the search for regulatory motifs is performed and by reducing the number and the complexity of motifs. Conversely, searching for relatively long motifs in a genomic window of restricted size will result in the prediction of a comparatively lower number of CRMs. Filtering parameters are also fully flexible, enabling a defined combination of functional criteria to be used for the final CRM selection. This selection is possible because the relevant information about the CRMs and the adjacent genes is stored in a database that is automatically generated by scafi software during the initial scanning step. The stringent scanning/filtering conditions applied here (see Fig. 5) have led to the selection of 99 potential Dmef2-dependent CRMs. Selected CRMs were amplified by PCR using genomic DNA as a template. Each PCR fragment was purified, and DNA concentration was measured. The PCR products (200 ng of each) were spotted twice on Nylon membranes (Hybond N+) by using a dot blot apparatus and fixed on the membrane by using a UV cross-linker. Alternatively, instead of PCR fragments, the pool of predicted CRMs can be printed on glass microarrays as long 50- to 60-nt oligos (data not shown). X-ChIP. One gram of embryos of stage 11-15 were dechorionated, washed in PBS/0.01% Triton X-100, and cross-linked for 15 min at room temperature with a mixture of 10 ml of 1.8% Formaldehyde, 50 mM Hepes, 1 mM EDTA, 0.5 mM EGTA, 100 mM NaCl (pH 8.0), and 30 ml of n-heptane. After centrifugation, embryos were washed with 50 ml of PBS, 0.125 M glycine, and 0.01% Triton X-100 to stop the reaction. After settling, embryos were homogenized in 10 ml of solution 1 (0.3 M sucrose/10 mM Hepes/10 mM KCl/1.5 mM MgCl2/0.1 mM EGTA/0.5 mM DTT/2 mM AEBSF/1 μg/ml leupeptin) by using a Dounce homogenizer (B type), and lysate was centrifuged at 500 × g for 1 min at 4°C. Supernatant was collected and centrifuged at 1,000 × g for 10 min at 4°C to obtain nuclei that then were resuspended in 2 ml of solution 1 and purified on a sucrose gradient at 13,000 rpm for 30 min at 4°C in an SW41 rotor (Beckman). The pellet containing protein-DNA complexes was washed with 2 ml of solution 2 (10 mM Hepes/10 mM KCl/2 mM MgCl2/0.5 mM DTT/2 mM AEBSF/1μg/ml leupeptin) and then dissolved in 3 ml of sonication buffer (50 mM Hepes/140 mM NaCl/1 mM EDTA/1% Triton X-100/0.1% Na-deoxycholate/0.1% SDS). Sonication was performed in conditions adapted to obtain DNA fragments of 200-1500 bp (Branson B-15 sonifier, output control 4, duty cycle percentage 60, with 15 pulses of 1 s repeated 12 times). After centrifugation for 15 min at 11,000 × g, clarified supernatant containing fragmented chromatin was collected and used for immunoprecipitation. Chromatin was first preincubated with protein A Sepharose 2 h at 4°C to eliminate nonspecific binding to the resin. Pretreated chromatin was incubated overnight at 4°C in the presence of Dmef2 antibody or in the presence of nonimmune serum and then for 4 h at 4°C with 100 μl of protein A Sepharose. Protein-DNA complexes were washed two times with sonication buffer, three times with 50 mM Tris (pH 7.5)/0.5 M LiCl/0.1% SDS/2% Nonidet P-40, and three times with 50 mM Tris (pH 7.5)/50 mM NaCl. Elution was performed at 65°C with 200 μl of 50 mM Tris (pH 8.0)/1 mM EDTA/1% SDS. Probe Synthesis and Hybridization. The Dmef2-bound DNA fragments were purified from the immunoprecipitated protein-DNA complexes and amplified by using a linker-ligation-PCR protocol ( 37). The size and quantity of DNA fragments was evaluated, and DNA was radiolabeled by using a random priming kit (RadPrime, Invitrogen). Probes were normalized according to the radioactivity incorporated. Prehybrization (8 h) and hybridization (overnight) were performed in 6× SSC/5× Denhardt's/0.5% SDS/100 μg/ml salmon sperm DNA at 65°C. All washes were carried out at 65°C for 30 min, the first in 2× SSC/0.1% SDS, the second in 0.5× SSC/0.1% SDS, and the third in 0.1× SSC/0.1% SDS. The ChEST Strategy and Its Application for TF Targets in Drosophila. To predict Dmef2-dependent CRMs, we first scanned the Drosophila genome for modules containing one of the three previously described in vivo-acting Dmef2 binding sites (Figs. and 5). Because muscle differentiation events are controlled by the synergistic action of MADS-box (Mef2 family) and E-box (Twist and MyoD bHLH family) factors ( 29) we searched for modules containing Mef2- and E-box-binding sites (; see Materials and Methods for scanning conditions). This scanning procedure led to the identification of ≈1,243 potential Dmef2-binding CRMs, from which 99 modules were selected (Fig. 5 and Tables 2 and 3, which is published as supporting information on the PNAS web site), amplified, and spotted to produce a computed Dmef2-CRM array (). Three of four previously described Dmef2-CRMs ( 22- 25), located in the vicinity of Paramyosin, Act57B, and Dmef2, were identified during genome scanning and selected for spotting as positive control. The fourth in vivo-acting Dmef2-CRM located close to b3-tubulin ( 25) did not come out from the screen because of the high number of E-box sites used as the scanning criterion (see Material and Methods). The CRMs located in the vicinity of genes that are not expressed in the mesoderm or genes of unknown expression and function (some of CGs) were rejected (see Materials and Methods and Fig. 5 for filtering conditions). In parallel, X-ChIP was used to isolate DNA fragments to which Dmef2 binds in vivo. ChIP-DNA immunoprecipitated either with Dmef2 antibody or with nonimmune serum was then labeled and used to probe the Dmef2-CRM array. The three previously described in vivo-acting CRMs were found enriched in ChIP-DNA immunoprecipitated with Dmef2 antibody (). Importantly, numerous other in silico-identified Dmef2-CRMs were enriched in ChIP-DNA [see (Example of results) and Table 2], thus demonstrating the efficacy of the ChEST method. | Table 2.ChEST-identified Dmef2 CRMs and adjacent target genes |
Dmef2 Targets Revealed by ChEST. The evolutionarily conserved family of Mef2 transcription factors plays a central role in the activation and maintenance of the myogenic differentiation program in Drosophila and is also involved in muscle and heart development in vertebrates ( 30). Although certain Mef2-regulated genes have been identified ( 22- 26), many more targets need to be identified before Mef2 can be placed in a network of muscle transcriptional regulation. We used ChEST to identify an additional set of direct Mef2 target genes in Drosophila. Of the 99 in silico-predicted Dmef2-CRMs (Tables 2 and 3), 62 were enriched in the DNA immunoprecipitated with anti-Dmef2 antibody (see Table 2). The CRM-associated Dmef2 targets included genes expressed in all muscle cell types, in which Dmef2 has previously been reported to function ( 20, 21). In addition to expected candidates encoding fusion (Lmd, Hibris) and structural (Ket, Pod1) muscle proteins, a large number of CRM-associated Dmef2 target genes coded for TFs and signal transduction proteins. For example, CRMs upstream of Fz2 and within the introns of Ci and Pan indicate a potential role of Dmef2 in transcriptional regulation of genes transducing to the mesodermal cells ectodermal Wg and Hh signals, whereas CRMs within the introns of If and Pka-C3 suggest that by regulating transcription of these genes Dmef2 is involved in the attachment of muscle fibers and in fiber contraction, respectively. In some cases (e.g., Kettin, NetB, N-cad), several Dmef2-dependent CRMs were mapped in the vicinity of the same gene ( Table 2), highlighting the complexity of transcriptional regulation in which Dmef2 is involved. Analysis of the position of CRMs in relation to adjacent genes () revealed that the majority of ChIP-enriched modules are located upstream (42%) or within the introns (39%) of target genes. In these two categories, the most frequent positions of Dmef2-CRMs appear between 1 and 5 kb upstream of the gene and within the first intron. Given the restrictive in silico scanning and filtering conditions (narrow scanning window, rejection of CRMs laying close to functionally unknown genes), and given the selected developmental stages (embryos from stage 11 to stage 15) used for ChIP, the ChEST-identified genes are unlikely to represent the totality of direct Dmef2 targets. ChEST-Identified CRMs Act as Enhancers in Vivo. To determine whether the ChEST-identified DNA fragments are able to act as regulatory modules in vivo, we tested 10 Dmef2-CRMs by reporter gene transgenesis. Nine of 10 CRMs were found to drive reporter gene expression in Dmef2-positive muscle cells (). In all transgenic Drosophila lines, lacZ reporter expression at least partially reproduced endogenous gene expression (), indicating that the identified CRMs were bona fide enhancers of adjacent genes. For example, the Ket-1, Ket-2, and Ket-3 CRMs laying in the vicinity of the kettin gene ( 31), which encodes a giant muscle protein required for the formation and maintenance of normal sarcomere structure, were found to drive lacZ expression in distinct subsets of differentiating body wall muscles (). These data indicate that the pan-muscular expression of kettin is regulated in a muscle-type-specific manner, and by multiple Dmef2-binding enhancers. Interestingly, four other analyzed CRMs ( Table 2 and Fig. 6, which is published as supporting information on the PNAS web site) located within the introns of N-cad and acon and upstream of fz2, sfl, and Meso18E also drive lacZ expression in discrete subsets of somatic muscle precursors (). The muscle-type-restricted activity of these modules suggests that both CRM regulators (Dmef2, E-box factors) and their target genes are involved in different aspects of muscle precursors diversification, including muscle fiber shape and axial positioning. Alternatively, the observed muscle-type-specific expression of lacZ may result from the limited size (250-300 bp) of genomic sequences tested. In embryos carrying a Dmef2-dependent CRM found in the intron of If (Fig. 6), lacZ expression is detected in a group of ventrolateral muscles (). This lacZ pattern correlates with distribution of endogenous If, which accumulates at the extremities of ventrolateral muscle fibers () and is required for their correct epidermal insertion. The reduced level of target gene expression in Dmef2 mutant embryos () provides an additional support for Dmef2-dependent in vivo regulation of ChEST-identified CRMs. Advantages and Limitations of ChEST. Compared with other genomewide ChIP-chip approaches ( 15- 19), ChEST does not require access to the whole-genome tiling arrays. It is dedicated to the identification of a subset of factor-specific CRMs that can be predicted by using computer-assisted methods. Depending on the TF and the organism concerned, the predictability of CRMs may represent a limiting factor. Here, we used ChEST to identify Dmef2-regulated CRMs in Drosophila. Because Dmef2 binds to long, well characterized DNA sequences and the Drosophila genome is well adapted to CRM prediction (rich in annotations), this approach created an attractive framework for analysis and contributed to a high percentage (63%) of ChIP-enriched CRMs ( Table 2). The fact that 37% of in silico-selected Dmef2-CRMs have not been found as significantly enriched in ChIP material (Table 3) results from one of the following reasons or from a combination of these reasons: ( i) inefficient ChIP due to restricted expression of target genes (13 CRMs listed in Table 3 lie close to genes expressed in a short time window or in a subset of mesodermal cells); ( ii) inefficient ChIP due to chromatin conformation; and/or ( iii) false positives generated during the computer-assisted genome scanning (see Table 3 for additional information). To test ChEST in more challenging conditions, we applied it for mapping CRMs to which bind two other myogenic factors, Lame duck (Lmd) ( 32) and Ladybird early (Lbe) ( 33) (G.J., unpublished data). Compared with Dmef2, Lmd and Lbe are expressed in a progressively more restricted subset of cells in the embryo, and their in vivo binding sites have not yet been identified, meaning only the in vitro consensus binding sequences can be used for CRM prediction. In such suboptimal conditions, the efficacy of ChEST dropped from 63% (Dmef2) to 34% of ChIP-enriched CRMs for Lmd and <20% for Lbe (data not shown). Thus, in Drosophila, ChEST can also be used (with a lower efficacy) for mapping CRMs to which bind transcription factors recognizing short and/or in vitro-only characterized DNA sequences. Furthermore, because the genome annotations for several invertebrate and vertebrate organisms are rapidly progressing, we expect ChEST to be easily adapted to other systems. Otherwise, targets for the evolutionarily conserved TFs can be identified in Drosophila and then validated in other organisms. One possible application of ChEST in the future is to use it in cell- or tissue-culture systems to follow the repertoire of target CRMs for TFs involved in important biological processes, including human pathologies. ChEST-Revealed Dmef2 Targets Confirm Previously Described, and Suggest Novel, Dmef2 Functions. Drosophila Dmef2 is required for the terminal differentiation of skeletal, visceral, and cardiac musculature ( 20, 21) but seems not to be involved in early myogenic events such as muscle specification and diversification ( 34). It directs mesodermal cell differentiation programs by regulating transcriptional activity of genes associated with these processes. Here, among the identified Dmef2-binding CRMs, we found those that map in the vicinity of ket, Tm1, Act87E, and Pod1 genes encoding muscle structural proteins and a few others located close to Lmd, N-cad, NetB, Hibris, Sema-5c, If, dei, and Flw genes implicated in cell adhesion/fusion or muscle attachment, thus supporting previously described muscle differentiation functions of Dmef2. The identification of Lmd, Hibris, and N-cad CRMs is consistent with the involvement of Dmef2 in myoblast fusion processes, which are affected in Dmef2 mutant embryos ( 20, 21). Furthermore, the presence of Dmef2-dependent CRMs close to NetB, which is involved in the attraction of motoneurons, suggests that the Dmef2-dependent formation of presynaptic active zones ( 35) may involve NetB. However, in addition to these novel but anticipated Dmef2 targets, our data indicate that Dmef2 also contributes to the transcriptional regulation of genes implicated in muscle specification and diversification. Candidates that indicate an early myogenic role of Dmef2 include components of the Wg, Hh, and RTK signaling pathways ( Ci, Pan, GATAe, AbdA, Jeb, Sfl, Fz2, ttk, argos, stumps, Concertina, and Src42A) that play key roles in the specification of myogenic lineages and their subsequent diversification. The role of Dmef2 in the initial steps of myogenesis is in agreement with the early, twist-dependent phase of Dmef2 expression, and is further supported by the previously described regulation of early expression of Dmeso18E ( 36). Another unexpected group of potential transcriptional targets of Dmef2 corresponds to genes encoding proteins involved in ion transport, channel activity, and metabolism (e.g., Slo, Itp-r83A, NheII, and Acon). The regulation of this class of genes may reflect a role for Dmef2 in the transmission of neural stimulation and muscle contraction. The maintenance of Dmef2 expression in fully differentiated adult muscles is in agreement with such a function. 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