Physical properties of naked DNA influence nucleosome positioning and correlate with transcription start and termination sites in yeast
- Özgen Deniz†1,
- Oscar Flores†1,
- Federica Battistini1,
- Alberto Pérez2,
- Montserrat Soler-López1 and
- Modesto Orozco1, 3, 4Email author
© Deniz et al; licensee BioMed Central Ltd. 2011
Received: 21 June 2011
Accepted: 7 October 2011
Published: 7 October 2011
In eukaryotic organisms, DNA is packaged into chromatin structure, where most of DNA is wrapped into nucleosomes. DNA compaction and nucleosome positioning have clear functional implications, since they modulate the accessibility of genomic regions to regulatory proteins. Despite the intensive research effort focused in this area, the rules defining nucleosome positioning and the location of DNA regulatory regions still remain elusive.
Naked (histone-free) and nucleosomal DNA from yeast were digested by microccocal nuclease (MNase) and sequenced genome-wide. MNase cutting preferences were determined for both naked and nucleosomal DNAs. Integration of their sequencing profiles with DNA conformational descriptors derived from atomistic molecular dynamic simulations enabled us to extract the physical properties of DNA on a genomic scale and to correlate them with chromatin structure and gene regulation. The local structure of DNA around regulatory regions was found to be unusually flexible and to display a unique pattern of nucleosome positioning. Ab initio physical descriptors derived from molecular dynamics were used to develop a computational method that accurately predicts nucleosome enriched and depleted regions.
Our experimental and computational analyses jointly demonstrate a clear correlation between sequence-dependent physical properties of naked DNA and regulatory signals in the chromatin structure. These results demonstrate that nucleosome positioning around TSS (Transcription Start Site) and TTS (Transcription Termination Site) (at least in yeast) is strongly dependent on DNA physical properties, which can define a basal regulatory mechanism of gene expression.
KeywordsDNA physical properties Molecular dynamics MNase digestion nucleosome positioning gene regulation chromatin structure
Genomic studies mostly provide one-dimensional information encoded in DNA, but we cannot ignore the fact that in eukaryotic organisms, DNA is packaged into chromatin structure, where DNA folds to a global compaction of at least 104. Genome homeostatic histone concentration ensures most of DNA to be wrapped into nucleosomes (~75-90%) , which are structural units of 145-147 base pairs (bp) long, where the interaction with regulatory proteins is severely handicapped. Nucleosomes are separated from each other by short linkers (around 20 bp long in yeast) where site-specific recognition by proteins is easier. Therefore, DNA compaction has clear functional implications, since it modulates the accessibility of genomic regions to regulatory proteins. Indeed, a close relationship was established between nucleosome positioning and important regulatory signals , such as proximal promoters [4, 5] and splicing sites . Further evidence on the connection between three-dimensional chromatin structure and function was obtained from genome-wide analysis of chromatin DNase I degradation profiles, which revealed a cross-link between DNase I hypersensitive sites and regulatory regions [7–9].
DNA underlying sequence has long been considered to be an important contributor to nucleosome assembly [10–13]. Crystal structures of nucleosome core particles revealed a lack of direct readout mechanisms between histones and DNA bases (the so-called base readout) [14–17] which led to the postulate that histone-DNA direct interactions are not the major determinant of nucleosome positioning . Accordingly, the DNA relative affinities for nucleosome formation (e.g. high-affinity Widom601 sequence)  should be based on an indirect readout mechanism, where the ability of a given DNA sequence to be deformed would account for the nucleosome assembly preferences [20–24]. Nevertheless, to which extent nucleosome positioning in vivo is really dictated by the DNA sequence is still an issue of strong discussion [25–27].
Our group and others have provided indirect evidence highlighting the connection between DNA physical properties and chromatin organization [28–30]. In particular, we have previously reported theoretical studies showing that human promoters display very unusual stiffness properties . These might affect DNA binding of regulatory proteins, either directly by hampering or favoring complex formation, or indirectly through the modulation of the chromatin structure and hence the DNA accessibility . Here, we have pursued this hypothesis by a genome-wide analysis of conformational properties across yeast naked DNA using micrococcal nuclease (MNase) degradation profiles as an experimental descriptor. We were able to characterize in detail, MNase preferences for naked DNA, extending fractional information derived from small-scale experiments. These preferences (at the tetramer level) correlate with ab initio physical descriptors derived from molecular dynamics (MD) simulations of short DNA oligonucleotides [32–35]. This finding confirms that MNase can signal genomic regions with unusual physical properties [36, 37]. Very interestingly, MNase-hypersensitive sites in naked DNA are mainly located around TSS and TTS, which supports experimentally our suggestion that those regulatory regions are signaled by physical properties. Moreover, the correlation of genome-wide nucleosome positioning profiles with MD-derived mesoscopic calculations evinces that the main mechanism by which physical properties influence gene regulation is through nucleosome positioning. Altogether, our experimental and computational integrative analysis demonstrates a clear relationship between sequence-dependent structural properties of naked DNA, accessible from first-principles simulations, and regulatory signals in chromatin structure.
Results and Discussion
Preferential MNase cut sites
Frequency of MNase-preferred tetramers at the cutting sites
3.01 × 10-4
1.01 × 10-4
6.03 × 10-4
2.01 × 10-4
Frequency of tetramers in MNase-digested LRs and CLRs
Common low regions (CLR)
9.05 × 10-4
7.54 × 10-3
7.04 × 10-4
3.22 × 10-3
4.62 × 10-3
4.22 × 10-3
5.53 × 10-3
3.62 × 10-3
1.30 × 10-2
3.44 × 10-2
Preferential MNase degraded regions
Upon an initial endonucleotic cleavage, MNase displays an exonuclease activity that continues with the degradation of DNA , leading to digested areas that we identified as low coverage regions (LRs) in our sequencing experiments (see Methods). Tetramer composition along naked DNA LRs was different from the one observed in the cutting sites, suggesting that the degradation of a particular fragment does not only depend on the existence of cleavage sites in its vicinity, but also on the differential sequence preferences of endo- and exo-nuclease activities. For example, d(AAAA·TTTT) was the most abundant tetramer in naked DNA LRs, nearly four times more frequent than expected (p < 10-8), while the same tetramer was rarely present at primary cutting sites (1/4 than expected, p < 10-7, Additional File 1: Table S1). Moreover, the tetramer composition was very similar in both naked and nucleosomal LRs and in the common low regions (CLRs) (definitions in Additional File 1: Additional Methods) indicating that sequence susceptibility for MNase degradation in nucleosomal DNA was not exclusively dependent on the chromatin structure, but was also related to the intrinsic properties of naked DNA (Table 2).
Low coverage regions and physical properties
Nucleosome positioning and gene structure
Physical properties, nucleosome positioning and regulatory regions
The analysis of MD-derived descriptors of naked DNA showed that key genomic regions, such as at TSSs and TTSs, were marked by unusual flexibility properties (Additional File 1: Figure S5) . Since those regions are strongly nucleosome depleted, we hypothesized that unusual physical properties might control nucleosome positioning in those regions, which in turn would affect the DNA accessibility to regulatory proteins and ultimately impact gene regulation. To verify this hypothesis, we computed the deformation energy required to wrap a DNA sequence around a histone octamer by using a simple elastic energy function based on the MD-derived physical descriptors (see Methods). Figure 2 clearly shows that CLRs, which are nucleosome depleted, correlate with high deformation energy confirming that in these regions it is more difficult to wrap DNA around a nucleosome core. It is interesting to note (Figure 2) that, often, 147 bps regions with high deformation energy contain a high flexible (4 mer) step, indicating that global concepts about the impact of point flexibility on chromatin organization needs to be considered with caution. Overall, results in Figure 2 strongly suggest that the properties that make a DNA segment a good substrate for MNase are also those that avoid DNA wrapping around a nucleosome. In fact, very encouragingly, deformation energies for wrapping a DNA around a nucleosome core particle can accurately predict in vivo nucleosome distribution around TSSs and TTSs in yeast (Additional File 1: Figure S6). These results suggest that, without dismissing the importance of cellular mechanisms for controlling chromatin structure, very important details of the nucleosome organization around TSS and TTS can be rationalized considering physical properties of the naked DNA sequence.
The molecular mechanisms that regulate gene expression in eukaryotic organisms are very diverse and complex. Considering the large amount of basal gene expression in cells, it is difficult to believe that regulation is entirely modulated by specific direct-readout mechanisms, where regulatory proteins would directly interact with DNA through hydrogen bonds in the major/minor grooves and compete with histones . Thus, a combination of direct and indirect readout mechanisms is required to achieve the correct interaction affinity and specificity . Direct mechanism can be very specific, but has implicitly a large energetic cost. Indirect mechanism is obviously less precise, but implies no energy cost for the cell and might be useful in cases where no specific regulation of the gene is needed.
Genome-wide sequencing of MNase treated nucleosomal DNA shows that key regulatory regions such as the start and the end of transcribed sites, which have been traditionally interpreted as nucleosome depletion sites, are actually signaled by a differential pattern of MNase susceptibility in naked DNA. This observation, which could initially raise some concerns, does not contradict previously reported nucleosome maps where MNase degradation was supposed to only reflect nucleosome positioning [10, 11, 43–50, 59–61]. Indeed, nucleosomal degradation profiles corrected with naked DNA data maintained major nucleosome positioning signals, such as nucleosome depletion upstream of TSS or downstream of TTS, thereby supporting previous MNase based nucleosome positioning conclusions [62, 63]. Nevertheless, our experiments with nucleosomal and naked DNA suggest caution in the interpretation of nucleosome positioning signals in regions with anomalous MNase degradation profile.
The high correlation of MNase degradation profiles of nucleosomal and naked DNA and with unusual stiffness properties indicates that (without dismissing the importance of the cellular machinery for control of chromatin structure) intrinsic physical properties of naked DNA determine major nucleosome location signals in yeast, especially those at TSS and TTS. This hypothesis is indirectly supported by very recent studies , where nucleosome positioning signals are clearly identified after genome-wide nucleosome reconstitution in vitro.
Essential regions for gene regulation like TSSs and TTSs are characterized by unusual physical properties that disfavor positioning of nucleosomes and therefore expose DNA to interaction with regulatory proteins. This property of regulatory regions is quite general across the genome. The genes with well-defined CLRs at regulatory regions did not differ from those with more diffuse signals in terms of Gene Ontology analysis , promoter architecture, transcription rate or their dependence on regulatory proteins. Accordingly, we can infer that unusual physical properties are perhaps a general property of gene regulatory regions that can confer a basal mechanism of gene regulation. Furthermore, we speculate that additional specific signals were evolutionarily conferred to enable proteins to directly read DNA sequences in those genes that might require a finer regulatory mechanism.
All conclusions drawn here have been derived from the analysis of yeast genome and thus concerns exist whether they can be validated for higher eukaryotes with a different sequence composition at regulatory regions. Therefore, we compared the sequence-dependent physical properties of the Drosophila melongaster genome with the high-resolution genomic nucleosome map available . The comparative analysis is shown in Additional File 1: Figure S7, which revealed that coverage and stiffness profiles at TSS are conserved between such distant organisms like yeast and fruit fly . Extension of conclusions to vertebrates is more complex, due to the higher impacts of epigenetic factors. Nevertheless unusual physical properties are also remarkable in human promoters . All these findings prompt us to believe in the general conclusion that nucleosome-depleted and enriched regions are signalled by unusual physical properties, which define the core of an evolutionarily conserved mechanism of gene regulation.
DNA sample preparation
Both nucleosomal and genomic (histone-free) DNA were isolated from Saccharomyces cerevisiae BY4741 strain, (an outline of the experimental procedure is presented in Figure 1, adapted from a previously described procedure) . For nucleosomal DNA preparation, exponentially growing yeast cells were first cross-linked with formaldehyde, spheroplasted with zymolase and finally subjected to a MNase partial digestion to generate core nucleosomes containing DNA fragments of around 147 bp (see Additional File 1: Additional Methods). Agarose gel electrophoresis confirmed that more than 90% of the isolated DNA corresponded to mono-nucleosomal fragments (Additional File 1: Figure S8). Naked DNA was prepared from overnight grown culture by spheroplasting the cells with zymolase and subsequently incubated with SDS and RNase for an efficient protein and RNA depletion. DNA samples were analyzed by fluorometry and UV spectrophotometry to ensure that proteins and RNA were completely removed from the DNA (Additional File 1: Figure S8). The purified DNA was then sheared following two different approaches (MNase digestion and sonication) that yielded fragments of approximately 150 bp in both cases (additional details in Additional File 1: Additional Methods). To guarantee that results were not dependent on MNase concentration, experiments were repeated using two MNase concentrations (0.04 and 0.12 U) (data not shown, but available upon request). The original, the corrected degradation maps and MNase cutting preferences did not show any differeces between the two MNase concentrations. Accordingly in this study only the data obtained with high MNase concentration are reported. These degradation conditions ensure that in nucleosomal DNA experiments only the linker DNA is digested, most of the degraded sample corresponds to mononucleosomes, and integrity of DNA bound to histones is preserved.
Cleaved DNA samples were sequenced on the Illumina/Solexa Genome Analyzer (GA) IIx to generate reads of 54 bp length. Data were processed with standard GA base calling pipeline to convert initial raw images into sequences. All sequencing experiments were done in duplicates. Pooled data highly converged, as the reproducibility of individual experiments was very large in all cases (Additional File 1: Additional Methods). Reads are available in Short Read Archive of NCBI under Accession Number SRA030453.
Mapping reads to genome
GA reads were aligned to the Saccharomyces cerevisae reference genome using the Bowtie software , allowing up to three mismatches per read. Short reads with multiple alignments were mapped to all possible places, thus avoiding the generation of artificial depleted regions. Largely over-represented reads were eliminated to reduce PCR amplification artifacts. Coverage values were calculated for each position on the genome, normalized and converted to reads per million (r.p.m.) (Additional File 1: Additional Methods).
Nucleosome calling and MNase bias correction
Nucleosomes were defined as regions flanking ±74 bases the peaks detected in the coverage maps. Peak detection was performed using a recently published algorithm nucleR (Additional File 1: Additional Methods). Correction of nucleosomal digestion profiles was done by using the degradation profiles obtained for naked DNA as background (Additional File 1: Additional Methods).
Identification of cut sites and low coverage regions
MNase cut sites were extracted from mapped reads, taking two bases upstream and the two bases downstream of every read end. Low coverage regions (LRs) account for regions were MNase degradation has been especially extensive. Low coverage regions (LRs) were detected in both nucleosomal and naked DNA as genomic segments with non-zero coverage below certain thresholds (Additional File 1: Additional Methods).
Derivation of physical descriptors
Parameters describing the equilibrium geometry and deformability of naked DNA were derived from long atomistic MD simulations of a reduced number of short oligonucleotides (displaying all unique dinucleotide or tetranucleotide steps) in solvent water by using a newly developed force-field . Base pair and base step structures of DNA can be described as a set of three translations (shift, slide and rise) and three rotations (tilt, roll and twist), while the deformability along those directions can be described by their associated stiffness constants (K i ), considering the equilibrium conformation as the origin of energies following the approach suggested by Lankas and others [34, 32, 42, 41]. In brief, the covariance matrix defining the deformability of helical parameters of a given DNA segment (for example a dinucleotide step) is computed from the ensemble of molecular dynamics simulations and inverted to determine 6 × 6 stiffness matrix for each fragment (for example each of the ten unique dinucleotide steps, or the ten dinucleotide steps adapted to all tetramer environments). Pure stiffness constant associated to individual helical deformations (ktilt, kroll, kshift, ktilt, krise and kslide) are taken from the diagonal of the matrix. Ktotal is obtained as the product of the six pure stiffness constants and gives a rough global estimate of the flexibility of each base pair step (Additional File 1: Additional Methods)
Calculation of nucleosome deformation energy
The energetic cost of wrapping a 147 bp DNA fragment was determined by using an harmonic approach: E = 0.5 XT Θ X; where Θ is the stiffness matrix derived from MD simulations; X (or XT) is the deformation vector (or its transposed), given by translating a relaxed DNA fiber into the coiled nucleosome core DNA conformation as described for averaging and smoothing of X-ray structures (Additional File 1: Additional Methods). Note that no training is performed and therefore deformation energies are fully ab initio descriptors. The scripts used to perform deformation energy calculations are available upon request to the authors.
List of abbreviations
- DNase I:
DNA nuclease I
low coverage region
common low coverage region
transcription start site
transcription termination site
We thank D. Rossell and E. Planet for their support in pre-processing the high-throughput sequencing data and F. Azorín for assistance in the experimental assays. This work was supported by the Spanish Ministry of Science and Innovation (BIO2009-10964 and Consolider E-Science), Instituto de Salud Carlos III (INB-Genoma España and COMBIOMED RETICS) and Fundación Marcelino Botín. AP is an EMBO fellowship holder (ALTF 1107). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
- Gilbert N, Boyle S, Fiegler H, Woodfine K, Carter NP, Bickmore WA: Chromatin architecture of the human genome: gene-rich domains are enriched in open chromatin fibers. Cell. 2004, 118: 555-566. 10.1016/j.cell.2004.08.011.View ArticlePubMedGoogle Scholar
- Holde Kvan, Zlatanova J: Unusual DNA structures, chromatin and transcription. BioEssays : news and reviews in molecular, cellular and developmental biology. 1994, 16: 59-68.View ArticleGoogle Scholar
- Jiang C, Pugh BF: Nucleosome positioning and gene regulation: advances through genomics. Nature reviews Genetics. 2009, 10: 161-72.View ArticlePubMedPubMed CentralGoogle Scholar
- Lodhi N, Ranjan A, Singh M, Srivastava R, Singh SP, Chaturvedi CP, Ansari SA, Sawant SV, Tuli R: Interactions between upstream and core promoter sequences determine gene expression and nucleosome positioning in tobacco PR-1a promoter. Biochimica et biophysica acta. 2008, 1779: 634-44.View ArticlePubMedGoogle Scholar
- Choi JK, Kim Y-J: Intrinsic variability of gene expression encoded in nucleosome positioning sequences. Nature genetics. 2009, 41: 498-503. 10.1038/ng.319.View ArticlePubMedGoogle Scholar
- Schwartz S, Ast G: Chromatin density and splicing destiny: on the cross-talk between chromatin structure and splicing. The EMBO journal. 2010, 29: 1629-1636. 10.1038/emboj.2010.71.View ArticlePubMedPubMed CentralGoogle 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: 311-22. 10.1016/j.cell.2007.12.014.View ArticlePubMedPubMed CentralGoogle Scholar
- Ling G, Sugathan A, Mazor T, Fraenkel E, Waxman DJ: Unbiased, Genome-wide in vivo Mapping of Transcriptional Regulatory Elements Reveals Sex Differences in Chromatin Structure Associated with Sex-specific Liver Gene Expression. Molecular and cellular biology. 2010, MCB.00601-10-Google Scholar
- Micheli E, Martufi M, Cacchione S, Santis PDe, Savino M: Self-organization of G-quadruplex structures in the hTERT core promoter stabilized by polyaminic side chain perylene derivatives. Biophysical chemistry. 2010Google Scholar
- Ioshikhes IP, Albert I, Zanton SJ, Pugh BF: Nucleosome positions predicted through comparative genomics. Nature genetics. 2006, 38: 1210-5. 10.1038/ng1878.View ArticlePubMedGoogle Scholar
- Kaplan N, Moore IK, Fondufe-Mittendorf Y, Gossett AJ, Tillo D, Field Y, LeProust EM, Hughes TR, Lieb JD, Widom J, Segal E: The DNA-encoded nucleosome organization of a eukaryotic genome. Nature. 2009, 458: 362-6. 10.1038/nature07667.View ArticlePubMedGoogle Scholar
- Chung H-R, Vingron M: Sequence-dependent nucleosome positioning. Journal of molecular biology. 2009, 386: 1411-22. 10.1016/j.jmb.2008.11.049.View ArticlePubMedGoogle Scholar
- Cui F, Zhurkin VB: Structure-based analysis of DNA sequence patterns guiding nucleosome positioning in vitro. Journal of biomolecular structure & dynamics. 2010, 27: 821-41.View ArticleGoogle Scholar
- Luger K, Mäder AW, Richmond RK, Sargent DF, Richmond TJ: Crystal structure of the nucleosome core particle at 2.8 A resolution. Nature. 1997, 389: 251-60. 10.1038/38444.View ArticlePubMedGoogle Scholar
- Richmond TJ, Davey CA: The structure of DNA in the nucleosome core. Nature. 2003, 423: 145-50. 10.1038/nature01595.View ArticlePubMedGoogle Scholar
- Hall MA, Shundrovsky A, Bai L, Fulbright RM, Lis JT, Wang MD: High-resolution dynamic mapping of histone-DNA interactions in a nucleosome. Nature structural & molecular biology. 2009, 16: 124-9. 10.1038/nsmb.1526.View ArticleGoogle Scholar
- Makde RD, England JR, Yennawar HP, Tan S: Structure of RCC1 chromatin factor bound to the nucleosome core particle. Nature. 2010, 467: 562-566. 10.1038/nature09321.View ArticlePubMedPubMed CentralGoogle Scholar
- Zhang Y, Moqtaderi Z, Rattner BP, Euskirchen G, Snyder M, Kadonaga JT, Liu XS, Struhl K: Intrinsic histone-DNA interactions are not the major determinant of nucleosome positions in vivo. Nature structural & molecular biology. 2009, 16: 847-52. 10.1038/nsmb.1636.View ArticleGoogle Scholar
- Lowary PT, Widom J: New DNA sequence rules for high affinity binding to histone octamer and sequence-directed nucleosome positioning. Journal of molecular biology. 1998, 276: 19-42. 10.1006/jmbi.1997.1494.View ArticlePubMedGoogle Scholar
- Tolstorukov MY, Colasanti AV, McCandlish DM, Olson WK, Zhurkin VB: A novel roll-and-slide mechanism of DNA folding in chromatin: implications for nucleosome positioning. Journal of molecular biology. 2007, 371: 725-38. 10.1016/j.jmb.2007.05.048.View ArticlePubMedPubMed CentralGoogle Scholar
- De Santis P, Morosetti S, Scipioni A: Prediction of nucleosome positioning in genomes: limits and perspectives of physical and bioinformatic approaches. Journal of biomolecular structure & dynamics. 2010, 27: 747-64.View ArticleGoogle Scholar
- Trifonov EN, Sussman JL: The pitch of chromatin DNA is reflected in its nucleotide sequence. Proceedings of the National Academy of Sciences of the United States of America. 1980, 77: 3816-20. 10.1073/pnas.77.7.3816.View ArticlePubMedPubMed CentralGoogle Scholar
- Xu F, Olson WK: DNA architecture, deformability, and nucleosome positioning. Journal of biomolecular structure & dynamics. 2010, 27: 725-39.View ArticleGoogle Scholar
- Rohs R, West SM, Sosinsky A, Liu P, Mann RS, Honig B: The role of DNA shape in protein-DNA recognition. Nature. 2009, 461: 1248-53. 10.1038/nature08473.View ArticlePubMedPubMed CentralGoogle Scholar
- Travers A, Hiriart E, Churcher M, Caserta M, Di Mauro E: The DNA sequence-dependence of nucleosome positioning in vivo and in vitro. Journal of biomolecular structure & dynamics. 2010, 27: 713-24.View ArticleGoogle Scholar
- Arya G, Maitra A, Grigoryev SA: A structural perspective on the where, how, why, and what of nucleosome positioning. Journal of biomolecular structure & dynamics. 2010, 27: 803-20.View ArticleGoogle Scholar
- Trifonov EN: Nucleosome positioning by sequence, state of the art and apparent finale. Journal of biomolecular structure & dynamics. 2010, 27: 741-6.View ArticleGoogle Scholar
- Abeel T, Saeys Y, Bonnet E, Rouzé P, Van de Peer Y: Generic eukaryotic core promoter prediction using structural features of DNA. Genome research. 2008, 18: 310-23. 10.1101/gr.6991408.View ArticlePubMedPubMed CentralGoogle Scholar
- Goñi JR, Fenollosa C, Pérez A, Torrents D, Orozco M: DNAlive: a tool for the physical analysis of DNA at the genomic scale. Bioinformatics (Oxford, England). 2008, 24: 1731-2. 10.1093/bioinformatics/btn259.View ArticleGoogle Scholar
- Miele V, Vaillant C, D Aubenton-Carafa Y, Thermes C, Grange T: DNA physical properties determine nucleosome occupancy from yeast to fly. Nucleic acids research. 2008, 36: 3746-56. 10.1093/nar/gkn262.View ArticlePubMedPubMed CentralGoogle Scholar
- Goñi JR, Pérez A, Torrents D, Orozco M: Determining promoter location based on DNA structure first-principles calculations. Genome biology. 2007, 8: R263-10.1186/gb-2007-8-12-r263.View ArticlePubMedPubMed CentralGoogle Scholar
- Lankas F, Sponer J, Langowski J, Cheatham TE: DNA basepair step deformability inferred from molecular dynamics simulations. Biophysical journal. 2003, 85: 2872-83. 10.1016/S0006-3495(03)74710-9.View ArticlePubMedPubMed CentralGoogle Scholar
- Morozov AV, Fortney K, Gaykalova DA, Studitsky VM, Widom J, Siggia ED: Using DNA mechanics to predict in vitro nucleosome positions and formation energies. Nucleic acids research. 2009, 37: 4707-22. 10.1093/nar/gkp475.View ArticlePubMedPubMed CentralGoogle Scholar
- Olson WK: DNA sequence-dependent deformability deduced from protein-DNA crystal complexes. Proceedings of the National Academy of Sciences. 1998, 95: 11163-11168. 10.1073/pnas.95.19.11163.View ArticleGoogle Scholar
- Araúzo-Bravo MJ, Fujii S, Kono H, Ahmad S, Sarai A: Sequence-dependent conformational energy of DNA derived from molecular dynamics simulations: toward understanding the indirect readout mechanism in protein-DNA recognition. Journal of the American Chemical Society. 2005, 127: 16074-89. 10.1021/ja053241l.View ArticlePubMedGoogle Scholar
- Yamasaki S, Terada T, Shimizu K, Kono H, Sarai A: A generalized conformational energy function of DNA derived from molecular dynamics simulations. Nucleic acids research. 2009, 37: e135-10.1093/nar/gkp718.View ArticlePubMedPubMed CentralGoogle Scholar
- Fujii S, Kono H, Takenaka S, Go N, Sarai A: Sequence-dependent DNA deformability studied using molecular dynamics simulations. Nucleic acids research. 2007, 35: 6063-74. 10.1093/nar/gkm627.View ArticlePubMedPubMed CentralGoogle Scholar
- Flick JT, Eissenberg JC, Elgin SC: Micrococcal nuclease as a DNA structural probe: its recognition sequences, their genomic distribution and correlation with DNA structure determinants. Journal of molecular biology. 1986, 190: 619-33. 10.1016/0022-2836(86)90247-0.View ArticlePubMedGoogle Scholar
- Hörz W, Altenburger W: Sequence specific cleavage of DNA by micrococcal nuclease. Nucleic acids research. 1981, 9: 2643-58. 10.1093/nar/9.12.2643.View ArticlePubMedPubMed CentralGoogle Scholar
- Alexander M, Heppel LA, Hurwitz J: The purification and properties of micrococcal nuclease. The Journal of biological chemistry. 1961, 236: 3014-9.PubMedGoogle Scholar
- Pérez A, Lankas F, Luque FJ, Orozco M: Towards a molecular dynamics consensus view of B-DNA flexibility. Nucleic acids research. 2008, 36: 2379-94. 10.1093/nar/gkn082.View ArticlePubMedPubMed CentralGoogle Scholar
- Lavery R, Zakrzewska K, Beveridge D, Bishop TC, Case DA, Cheatham T, Dixit S, Jayaram B, Lankas F, Laughton C, Maddocks JH, Michon A, Osman R, Orozco M, Perez A, Singh T, Spackova N, Sponer J: A systematic molecular dynamics study of nearest-neighbor effects on base pair and base pair step conformations and fluctuations in B-DNA. Nucleic acids research. 2010, 38: 299-313. 10.1093/nar/gkp834.View ArticlePubMedGoogle Scholar
- Ozsolak F, Song JS, Liu XS, Fisher DE: High-throughput mapping of the chromatin structure of human promoters. Nature biotechnology. 2007, 25: 244-8. 10.1038/nbt1279.View ArticlePubMedGoogle Scholar
- Field Y, Kaplan N, Fondufe-Mittendorf Y, Moore IK, Sharon E, Lubling Y, Widom J, Segal E: Distinct modes of regulation by chromatin encoded through nucleosome positioning signals. PLoS computational biology. 2008, 4: e1000216-10.1371/journal.pcbi.1000216.View ArticlePubMedPubMed CentralGoogle Scholar
- Bai L, Morozov AV: Gene regulation by nucleosome positioning. Trends in genetics TIG. 2010, 26: 476-83. 10.1016/j.tig.2010.08.003.View ArticleGoogle Scholar
- Mavrich TN, Ioshikhes IP, Venters BJ, Jiang C, Tomsho LP, Qi J, Schuster SC, Albert I, Pugh BF: A barrier nucleosome model for statistical positioning of nucleosomes throughout the yeast genome. Genome research. 2008, 18: 1073-83. 10.1101/gr.078261.108.View ArticlePubMedPubMed CentralGoogle Scholar
- Segal E, Fondufe-Mittendorf Y, Chen L, Thåström A, Field Y, Moore IK, Wang J-PZ, Widom J: A genomic code for nucleosome positioning. Nature. 2006, 442: 772-8. 10.1038/nature04979.View ArticlePubMedPubMed CentralGoogle Scholar
- Lee W, Tillo D, Bray N, Morse RH, Davis RW, Hughes TR, Nislow C: A high-resolution atlas of nucleosome occupancy in yeast. Nature genetics. 2007, 39: 1235-44. 10.1038/ng2117.View ArticlePubMedGoogle Scholar
- Albert I, Mavrich TN, Tomsho LP, Qi J, Zanton SJ, Schuster SC, Pugh BF: Translational and rotational settings of H2A.Z nucleosomes across the Saccharomyces cerevisiae genome. Nature. 2007, 446: 572-6. 10.1038/nature05632.View ArticlePubMedGoogle Scholar
- Yuan G-C, Liu Y-J, Dion MF, Slack MD, Wu LF, Altschuler SJ, Rando OJ: Genome-scale identification of nucleosome positions in S. cerevisiae. Science (New York, N.Y.). 2005, 309: 626-30. 10.1126/science.1112178.View ArticleGoogle Scholar
- Yuan GC, Liu YJ, Dion MF, Slack MD, Wu LF, Altschuler SJ, Rando OJ: Genome-scale identification of nucleosome positions in S. cerevisiae. Science (New York, N.Y.). 2005, 309: 626-3010. 10.1126/science.1112178. 1126/science.1112178View ArticleGoogle Scholar
- Lee W, Tillo D, Bray N, Morse RH, Davis RW, Hughes TR, Nislow C: A high-resolution atlas of nucleosome occupancy in yeast. Nature genetics. 2007, 39: 1235-4410.1038/ng2117Google Scholar
- Field Y, Kaplan N, Fondufe-Mittendorf Y, Moore IK, Sharon E, Lubling Y, Widom J, Segal E: Distinct modes of regulation by chromatin encoded through nucleosome positioning signals. PLoS computational biology. 2008, 4: e100021610-1371/journal.pcbi.1000216View ArticleGoogle Scholar
- Albert I, Mavrich TN, Tomsho LP, Qi J, Zanton SJ, Schuster SC, Pugh BF: Translational and rotational settings of H2A.Z nucleosomes across the Saccharomyces cerevisiae genome. Nature. 2007, 446: 572-610.1038/nature05632. 10.1038/nature05632.View ArticlePubMedGoogle Scholar
- Kaplan N, Moore IK, Fondufe-Mittendorf Y, Gossett AJ, Tillo D, Field Y, LeProust EM, Hughes TR, Lieb JD, Widom J, Segal E: The DNA-encoded nucleosome organization of a eukaryotic genome. Nature. 2009, 458: 362-610. 10.1038/nature07667. 1038/nature07667View ArticlePubMedGoogle Scholar
- Chung H-R, Dunkel I, Heise F, Linke C, Krobitsch S, Ehrenhofer-Murray AE, Sperling SR, Vingron M: The effect of micrococcal nuclease digestion on nucleosome positioning data. PloS one. 2010, 5: e1575410-1371/journal.pone.0015754Google Scholar
- Rando OJ, Ahmad K: Rules and regulation in the primary structure of chromatin. Current opinion in cell biology. 2007, 19: 250-6. 10.1016/j.ceb.2007.04.006.View ArticlePubMedGoogle Scholar
- Rohs R, Jin X, West SM, Joshi R, Honig B, Mann RS: Origins of specificity in protein-DNA recognition. Annual review of biochemistry. 2010, 79: 233-69. 10.1146/annurev-biochem-060408-091030.View ArticlePubMedPubMed CentralGoogle Scholar
- Peckham HE, Thurman RE, Fu Y, Stamatoyannopoulos JA, Noble WS, Struhl K, Weng Z: Nucleosome positioning signals in genomic DNA. Genome research. 2007, 17: 1170-7. 10.1101/gr.6101007.View ArticlePubMedPubMed CentralGoogle Scholar
- Weiner A, Hughes A, Yassour M, Rando OJ, Friedman N: High-resolution nucleosome mapping reveals transcription-dependent promoter packaging. Genome research. 2010, 20: 90-100. 10.1101/gr.098509.109.View ArticlePubMedPubMed CentralGoogle Scholar
- Locke G, Tolkunov D, Moqtaderi Z, Struhl K, Morozov AV: High-throughput sequencing reveals a simple model of nucleosome energetics. Proceedings of the National Academy of Sciences. 2010, 1003838107-Google Scholar
- Segal E, Widom J: From DNA sequence to transcriptional behaviour: a quantitative approach. Nature reviews Genetics. 2009, 10: 443-56.View ArticlePubMedPubMed CentralGoogle Scholar
- Fan X, Moqtaderi Z, Jin Y, Zhang Y, Liu XS, Struhl K: Nucleosome depletion at yeast terminators is not intrinsic and can occur by a transcriptional mechanism linked to 3'-end formation. Proceedings of the National Academy of Sciences of the United States of America. 2010, 107: 17945-50. 10.1073/pnas.1012674107.View ArticlePubMedPubMed CentralGoogle Scholar
- Zhang Z, Wippo CJ, Wal M, Ward E, Korber P, Pugh BF: A Packing Mechanism for Nucleosome Organization Reconstituted Across a Eukaryotic Genome. Science. 2011, 332: 977-98010. 10.1126/science.1200508. 1126/science.1200508View ArticlePubMedPubMed CentralGoogle Scholar
- Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G: Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nature genetics. 2000, 25: 25-9. 10.1038/75556.View ArticlePubMedPubMed CentralGoogle Scholar
- Mavrich TN, Jiang C, Ioshikhes IP, Li X, Venters BJ, Zanton SJ, Tomsho LP, Qi J, Glaser RL, Schuster SC, Gilmour DS, Albert I, Pugh BF: Nucleosome organization in the Drosophila genome. Nature. 2008, 453: 358-62. 10.1038/nature06929.View ArticlePubMedPubMed CentralGoogle Scholar
- Mavrich TN, Jiang C, Ioshikhes IP, Li X, Venters BJ, Zanton SJ, Tomsho LP, Qi J, Glaser RL, Schuster SC, Gilmour DS, Albert I, Pugh BF: Nucleosome organization in the Drosophila genome. Nature. 2008, 453: 358-6210. 10.1038/nature06929. 1038/nature06929View ArticlePubMedPubMed CentralGoogle Scholar
- Langmead B, Trapnell C, Pop M, Salzberg SL: Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome biology. 2009, 10: R25-10.1186/gb-2009-10-3-r25.View ArticlePubMedPubMed CentralGoogle Scholar
- Flores O, Orozco M: nucleR: a package for non-parametric nucleosome positioning. Bioinformatics (Oxford, England). 2011, 27: 2149-215010. 10.1093/bioinformatics/btr345. 1093/bioinformatics/btr345View ArticleGoogle Scholar
- Pérez A, Marchán I, Svozil D, Sponer J, Cheatham TE, Laughton CA, Orozco M: Refinement of the AMBER force field for nucleic acids: improving the description of alpha/gamma conformers. Biophysical journal. 2007, 92: 3817-29. 10.1529/biophysj.106.097782.View ArticlePubMedPubMed CentralGoogle Scholar
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