View Article Google Scholar 8. PLoS Biol 8: e View Article Google Scholar 9. B Emerging principles of regulatory evolution. View Article Google Scholar Nat Rev Genet 7: — Kellis M, Birren B. W, Lander E. S Proof and evolutionary analysis of ancient genome duplication in the yeast Saccharomyces cerevisiae. Nature — Conant G. C, Wolfe K. H Increased glycolytic flux as an outcome of whole-genome duplication in yeast. Mol Syst Biol 3: Kornberg R.
D, Lorch Y Twenty-five years of the nucleosome, fundamental particle of the eukaryote chromosome. Cell — Radman-Livaja M, Rando O.
J Nucleosome positioning: How is it established, and why does it matter? Dev Biol. Rando O. J, Chang H. Y Genome-wide views of chromatin structure. Annu Rev Biochem — Jiang C, Pugh B. F Nucleosome positioning and gene regulation: advances through genomics. Nat Rev Genet — L The role of chromatin during transcription. Venters B. J, Pugh B. F A canonical promoter organization of the transcription machinery and its regulators in the Saccharomyces genome. Genome Res — J, Friedman N High-resolution nucleosome mapping reveals transcription-dependent promoter packaging.
Genome Res. Drew H. R, Travers A. A DNA bending and its relation to nucleosome positioning. J Mol Biol — Kaplan N, Moore I. J, Tillo D, et al. Sekinger E. A, Moqtaderi Z, Struhl K Intrinsic histone-DNA interactions and low nucleosome density are important for preferential accessibility of promoter regions in yeast. Mol Cell — Yuan G. C, Liu Y. J, Dion M. F, Slack M. D, Wu L.
F, et al. P, Euskirchen G, Snyder M, et al. Nat Struct Mol Biol — Clapier C. R, Cairns B. R The biology of chromatin remodeling complexes. Whitehouse I, Rando O. Brem R. Lee S. I, Pe'er D, Dudley A. M, Church G. M, Koller D Identifying regulatory mechanisms using individual variation reveals key role for chromatin modification. A, Barkai N A yeast hybrid provides insight into the evolution of gene expression regulation.
Mol Syst Biol 4: K, Mieczkowski P, Kaplan N, et al. Lantermann A. C, Ekwall K, et al. Nature 54— Segal E, Widom J What controls nucleosome positions? Trends Genet — D, Stryer L Statistical distributions of nucleosomes: nonrandom locations by a stochastic mechanism.
Nucleic Acids Res — Mavrich T. N, Ioshikhes I. P, Venters B. J, Jiang C, Tomsho L. P, et al. Heus J. J, Zonneveld B. J, Bloom K. S, de Steensma H. Y, van den Berg J. A The nucleosome repeat length of Kluyveromyces lactis is 16 bp longer than that of Saccharomyces cerevisiae. Van Holde K. E Chromatin. New York: Springer-Verlag.. Sasaki S, Mello C. Warnecke T, Batada N. N, Hurst L. D The impact of the nucleosome code on protein-coding sequence evolution in yeast.
PLoS Genet 4: e Routh A, Sandin S, Rhodes D Nucleosome repeat length and linker histone stoichiometry determine chromatin fiber structure. Albert I, Mavrich T. N, Tomsho L. P, Qi J, Zanton S. J, et al. Z nucleosomes across the Saccharomyces cerevisiae genome. Choi J. K, Kim Y. J Intrinsic variability of gene expression encoded in nucleosome positioning sequences.
K, Sharon E, et al. PLoS Comput Biol 4: e Tirosh I, Barkai N Two strategies for gene regulation by promoter nucleosomes. MacKay V. L, Li X, Flory M. R, Turcott E, Law G. L, et al. Mol Cell Proteomics 3: — Kurtzman C. P, Fell J. W The yeasts: a taxonomic study.
Amsterdam; New York: Elsevier. Embo J — Kunkel G. R, Martinson H. G Nucleosomes will not form on double-stranded RNa or over poly dA. Nucleic Acids Res 9: — Hartley P.
D, Madhani H. D Mechanisms that specify promoter nucleosome location and identity. Yarragudi A, Parfrey L. W, Morse R. H Genome-wide analysis of transcriptional dependence and probable target sites for Abf1 and Rap1 in Saccharomyces cerevisiae.
Badis G, Chan E. Zhu C, Byers K. J, McCord R. P, Shi Z, Berger M. Harbison C. T, Gordon D. B, Lee T. I, Rinaldi N. J, Macisaac K. D, et al. Nature 99— Tanay A, Regev A, Shamir R Conservation and evolvability in regulatory networks: the evolution of ribosomal regulation in yeast. P, Spellman P. T, Kao C. B, et al. Mol Biol Cell — Lam F. H, Steger D. J, O'Shea E. K Chromatin decouples promoter threshold from dynamic range.
Lomvardas S, Thanos D Modifying gene expression programs by altering core promoter chromatin architecture. MacIsaac K. D, Wang T, Gordon D. B, Gifford D. K, Stormo G. BMC Bioinformatics 7: Eukaryot Cell 7: — Williams R. M, Primig M, Washburn B. K, Winzeler E. A, Bellis M, et al. A, et al. Tillo D, Hughes T. BMC Bioinformatics Kent W.
Nucleic Acids Res 29— Harris M. Nucleic Acids Res D—D Mewes H. Together, this estimate and the total free energy of binding inferred from the restriction enzyme assay suggest that each contact patch provides around 6 k B T of favorable energy. This calculation neglects effects of DNA sequence: flexible DNA is expected to be easier to bend into the distorted shape found in nucleosomal crystal structures.
This effect is counteracted by the concomitant loss of DNA conformational entropy, which is correlated with DNA flexibility [ 16 ]. Thus more flexible sequences are easier to bend but at the same time lose more entropy upon nucleosome formation.
Moreover, intrinsic DNA curvature and bending anisotropy may make it easier for some DNA sequences to adopt the nucleosomal shape. Taken together, these contributions determine which DNA sequences are best and worst nucleosome formers. The nucleosome used in those experiments was assembled on the so-called sequence selected in vitro for high affinity [ 18 ].
Because the range of free energies of nucleosome formation is 7. The difference between the high-affinity sequence and DNA sequences from chicken genome is smaller yet at 5. The relatively low sequence specificity is consistent with the fact that nucleosomes can form on any DNA segment of sufficient length, fulfilling their role as a universal compaction factor of eukaryotic DNA.
Furthermore, in vitro nucleosome mobility can be suppressed by adding linker histones H1 or H5 to the system [ 22 ]. Linker histones make a separate histone class; they likely bind both nucleosomal and linker DNA, stabilizing the entire histone—DNA complex [ 23 , 24 ].
Note, however, that this cost is less than that entailed by complete nucleosome unfolding and assembly at a new position. Because spontaneous nucleosome repositioning activated by thermal fluctuations is too slow and random to be of much biological significance, cells depend on ATP-dependent chromatin remodelers to catalyze the repositioning reaction. Chromatin remodelers are multi-subunit proteins capable of translocating nucleosomes along the DNA, evicting nucleosomes or changing the nucleosome histone composition i.
In principle, the energy of ATP hydrolysis is sufficient to keep the entire population of genomic nucleosomes out of equilibrium. Interestingly, even with perfect efficiency a remodeler will take several seconds to unfold or reposition a single nucleosome, consuming several ATPs in the process; waiting times, which depend on the remodeler-to-nucleosome ratio, may be an order-of-magnitude greater still. Transient DNA unwrapping induced by thermal fluctuations has been observed in vitro , through competitive protein binding to nucleosomal DNA and fluorescence resonance energy transfer measurements [ 32—34 ].
In these and other studies, nucleosome unwrapping as opposed to relatively costly nucleosome repositioning has been thought to assist binding of nucleosomal DNA by transcription factors TFs.
However, until recently its significance in genome-wide chromatin organization has been unclear. Large-scale mapping of nucleosomes assembled in vitro on genomic or synthetic DNA, or extracted from living cells has become a standard technique for studying chromatin structure. Typically, chromatin is treated with micrococcal nuclease MNase —an endo-exonuclease that preferentially digests non-nucleosomal DNA optionally, nucleosomes are folmaldehyde-crosslinked on the DNA before the MNase treatment.
The mononucleosomal band is excised and sequenced using one of the next-generation sequencing technologies. High-throughput sequencing results in a collection of relatively short, 35—95 bp reads either single- or paired-end , which are mapped to the reference genome for recent reviews, see [ 35 , 36 ].
In the end, this procedure yields a nucleosome density profile—the number of nucleosomes starting at each genomic bp. With single-end nucleosome maps, the actual length of mapped DNA fragments is unknown and commonly assumed to be equal to the canonical nucleosome length of bp [ 37 ].
This approach neglects nucleosome unwrapping as well as under- or overdigestion of nucleosomal DNA by MNase. These difficulties were overcome in a recent experiment in which both nucleosome dyad positions and distances between dyads of neighboring nucleosomes were mapped with high precision in S. In this so-called chemical method, mutant H4 histones S47C were modified by covalent attachment of a sulfhydryl-reactive copper-chelating label to the cysteines.
With the addition of copper and hydrogen peroxide, a localized cloud of hydroxyl radicals was produced, which cleaved the DNA backbone at specific sites flanking nucleosome dyads.
The cleavage products that corresponded to DNA fragments linking neighboring nucleosomes were then size-selected on an agarose gel, purified, sequenced using paired-end reads and mapped to the S. As a result, each read marks a dyad position, and each mate pair yields a measurement of the distance between dyads of neighboring nucleosomes positioned on the same chromosome and in the same cell.
If DNA cuts at both sites are equally likely, averaging over hydroxyl cleavage preferences shows that the average interdyad distances are 5 bp longer than the average distances between adjacent hydroxyl cut sites [ 42 ].
Large-scale nucleosome positioning data obtained by MNase or chemical mapping can be used to predict nucleosome energetics. Sequence reads mapped to genomic coordinates produce one-dimensional nucleosome density profiles, in which nucleosome-enriched regions and nucleosome-depleted regions NDRs are marked with more and fewer reads, respectively. These density profiles can be used to infer sequence-dependent nucleosome formation energies, in a rigorous procedure that uses exact results from physics of one-dimensional liquids, and is capable of disentangling steric exclusion between neighboring nucleosomes from intrinsic histone—DNA sequence preferences [ 42 , 43 ].
The earlier version of this work, which used single-end data sets, had to assume bp canonical nucleosome length. These predictions, based on maps of nucleosomes assembled in vitro on genomic DNA, supplemented direct measurements of histone—DNA interaction energies available only for a handful of sequences [ 19 ]. More recently, with the advent of paired-end nucleosome maps and high-resolution chemical mapping, it has become possible to model energetics of nucleosome unwrapping using genome-scale data [ 42 ].
An important feature of the chemical mapping approach is that in addition to single-nucleosome positions it provides information about distances between neighboring nucleosomes. Before this work, inter-nucleosome distances were commonly estimated using a nucleosome ladder on an agarose gel Figure 1 B. This method yields an average nucleosome repeat length of — bp [ 3 ]; as MNase concentration increases, the distances become shorter owing to more extensive digestion at DNA fragment ends.
Moreover, the histogram of distances between adjacent hydroxyl cut sites exhibits prominent oscillations consistent with the 10—11 bp periodic model of DNA unwrapping based on nucleosome crystal structures Figure 1 D [ 42 ]. The model, which yields an energy profile averaged over sequence-dependent effects, is obtained by a parametric fit to the 1. When distances between neighboring dyads are averaged over all yeast genes aligned by their transcription start sites TSS , a prominent oscillatory pattern emerges Figure 1 E.
Thus, many yeast nucleosomes are crowded and partially unwrapped, as illustrated in the right panel of Figure 1 A. Chromatin organization, gene transcription and remodeler activity in S. A Heatmap of nucleosome dyad counts in S. Genes are sorted as in A. Pol II and Mediator: wild-type yeast in glucose; Msn2: wild-type yeast 20 min after a glucose-to-glycerol switch; Chd1, Isw1, Isw2: wild-type yeast grown in yeast extract peptone dextrose YPD medium [ 48 ].
Distributions of average occupancies over all yeast genes were converted into z -scores, and the color scheme in each vertical bar was set so that genes in the bottom 5 percentile negative z -scores are green, genes in the top 5 percentile positive z -scores are red and genes with zero z -scores are white. C Left panel: average nucleosome dyad density in the most transcribed genes orange, solid and in the rest of the yeast genes blue, dotted. Dots mark peaks of nucleosome dyad density in the coding region.
Right panel: linear fit to the positions of the nucleosome density peaks shown in the left panel. Changes in gene expression during the specific developmental stages of an organism or cell coincide with fluctuations in the levels of each of the specific protein complexes involved in chromatin remodeling Struhl, Histone modification can open chromatin, thus permitting selective binding of transcription factors that, in turn, recruit RNA polymerase II Turner, Varying levels and types of histone modifications have been shown to correlate with levels of chromatin activation.
For example, one group of researchers used antibody-based immunoprecipitation studies to determine that acetylation of histone H3 and methylation at lysine residue K4 appeared to coincide with each other. They also coincided during transcriptional activation in chicken embryos, while methylation at lysine residue K9 marked inactive chromatin.
Another means by which transcription is controlled is through methylation of the DNA strand itself. Not to be confused with histone methylation, methylation of the DNA strand involves cytosine bases of eukaryotic DNA being converted to 5-methylcytosine, resulting in the repression of transcription, particularly in vertebrates and plants. The altered cytosine residues are usually immediately adjacent to a guanine nucleotide , resulting in two methylated cytosine residues set diagonally to one another on opposing DNA strands Figure 3.
When methylation affects CpG islands, methyl-binding proteins trigger a silencing cascade activity illustrated by green stars whereby histone H3K9 is sequentially deaceylated and then methylated, allowing heterochromatin protein 1 HP1 to bind; eventually resulting in closed chromatin bottom right.
This results in faithful replication of methylation patterns bottom left and the maintenance of silencing. Adult patterns of methylation are erased by epigenetic reprogramming in early embryogenesis top left. CpG island methylator phenotype in cancer. Nature Review Cancer 4, Heavily methylated regions of DNA with elevated concentrations of these so-called CpG groups are often found near transcription start sites. In an interestingly coordinated process, proteins that bind to methylated DNA also form complexes with proteins involved in deacetylation of histones.
Therefore, when the DNA is in a methylated state, nearby histones are deacetylated, resulting in compact, semipermanently silent chromatin. Likewise, demethylated DNA does not draw deacetylating enzymes to the histones, but it often attracts histone acetyltransferases, allowing histones to remain acetylated and promoting transcription. Storage of eukaryotic DNA in small, compact nuclei requires that this DNA be tightly coiled and compacted in the form of chromatin. However, the structure of chromatin also appears to serve a second, possibly more important role, in that it gives eukaryotic cells the capability to exert complex levels of control over gene expression.
As described throughout this article, chromatin and the DNA sequences it contains are constantly undergoing modifications, thereby periodically exposing different regions of DNA to transcription factors and RNA polymerases. The cumulative effects of these changes are various states of transcriptional control and the ability of eukaryotic cells to turn genes on and off as needed.
This complexity provides eukaryotes with a means of making the most of a relatively small number of genes. However, much research remains to be performed before investigators precisely understand how the many mechanisms of chromatin remodeling operate, as well as how they work together to result in the complex patterns of gene expression characteristic of eukaryotic cells.
Cosgrove, M. Regulated nucleosome mobility and the histone code. Nature Structural and Molecular Biology 11 , — link to article. Issa, J. Nature Reviews Cancer 4 , — link to article.
Lall, S. Primers on chromatin. Nature Structural and Molecular Biology 14 , — link to article. Li, B. Preferential occupancy of histone variant H2AZ at inactive promoters influences local histone modifications and chromatin remodeling.
Proceedings of the National Academy of Sciences , — Saha, A. Chromatin remodelling: The industrial revolution of DNA around histones. Nature Reviews Molecular Cell Biology 7 , — link to article. Strahl, B. Nature , 41—45 doi Struhl, K. Fundamentally different logic of gene regulation in eukaryotes and prokaryotes.
Cell 98 , 1—4 Turner, B. Reading signals on the nucleosome with a new nomenclature for modified histones. Nature Structural and Molecular Biology 12 , — link to article. Wu, W. Nature Structural and Molecular Biology 12 , — doi Zhang, Y. Transcription regulation by histone methylation: interplay between different covalent modifications of the core histone tails.
Genes and Development 15 , Atavism: Embryology, Development and Evolution. Gene Interaction and Disease. Genetic Control of Aging and Life Span. Boxes represent the histone fold domain and orange lines represent site-specific sequence variations.
Histones that are in different shades of the same color are from the same histone family but have large differences in sequence [ 5 ].
Clark and Felsenfeld first used staphylococcal nuclease to digest chromatin in and found that some regions were sensitive to nuclease while some were insensitive; insensitive regions were homogeneous, suggesting it contains subunits. Then Hewish and Burgoyun Researchers in previous study digested the nuclei with endogenous nuclease and isolated DNA from the nucleus. As a result, a series of DNA fragments were found, which corresponded to a basic unit of about bp, indicating that histones bind to DNA in a regular manner which results in only certain restricted regions are sensitive to nuclease.
Kornberg and Thomas then digested the chromatin with a small cellulase in and centrifuged it to obtain monomers, dimers, trimers, and tetramers. Using electron microscopy, the monomer was observed as a 10 nm body, and the dimer was two associated bodies. Through all kinds of experiments, it was found that the structure of the nucleosome core is relatively invariant from yeast to metazoans [ 11 , 12 ] containing a bp DNA wrapped around a histone protein octamer.
In , Yuan et al. However, the study of the location of nucleosomes is quite time-consuming and costly if using experiments alone, so the researchers began to build nucleosome positioning prediction model based on the existing experimental data [ 14 ]. In yeast genome, Segal et al. Since that, many nucleosome prediction models were developed. Generally, nucleosome positioning can divide into two parts: rotational positioning and translational positioning.
The first one is to describe the side of the DNA helix that faces the histones and the next one is to determine the nucleosome midpoint with regard to the DNA sequence.
It is possible to calculate average nucleosome positioning levels on a given region of DNA in a population of cells. Illustration of the concepts of nucleosome positioning and nucleosome occupancy. A We use fraction of cells from the population in which that basepair is in the middle of a bp nucleosome representing the nucleosome positioning along every basepair in the genome.
The left figure exhibit perfect-positioning region, where the nucleosome center is located at the same basepair all over population cells; the other two showed partial-positioning and no-positioning region. Early in , the 10—11 bp periodicities were reported [ 17 ]. In addition to 3-bp periodicity, which is due to the fact that three consecutive bases encode one type of amino acids, the genomic DNA exhibits 10—11 bp periodicities.
The 10—11 bp periodicities in complete genomes reflect protein structure and DNA folding [ 17 ]. On the other hand, the 10—11 bp periodicities have an intimate association with nucleosome positioning. To sharply bent and tightly wrapped around a histone protein octamer, DNA sequence has intrinsic bias.
The position of certain dinucleotides, such as AA, TA, and TT in minor grooves facing toward every 10 bp and GG in minor grooves facing away from the histone octamer favors these Figure 5 distortions [ 15 ].
For the naked DNA, which is entirely devoid of nucleosomes, the oscillatory pattern in cleavage profile was disappeared in digesting [ 18 ]. All of these strongly suggested the role of the 10—11 bp periodicities of the specific dinucleotides in positioning nucleosomes. Based on the features of DNA sequences, many models are developed to predict nucleosomes Table 2. Illustration of nucleosome sequence preferences [ 16 ].
We assessed the roles of the 10—11 bp periodicities for different kinds of dinucleotides [ 20 ]. Near the transcription start site, the signals reveal a similar feature that the nucleosome organization exhibits Figure 6. But, it seems that the species do not share the same dinucleotides patterns. Furthermore, the dinucleotides patterns are dominant at the specific region of genome, indicating their diverse roles in forming and organizing nucleosomes. The 10—11 bp periodicities signals of the dinucleotides patterns around TSSs of eight species human, mouse, chicken, worm, fly, fugu, lancelet, and yeast [ 20 ].
In Table 2 , the models for both nucleosome prediction and nucleosome sequencing data processing are listed. Chromatin remodeling complex helps cell to establish the access of genomic DNA for transcription factors. The complexes have two major groups, namely covalent histone-modifying complexes and ATP-dependent chromatin remodeling complexes [ 53 ]. They work in a different way. Covalent histone-modifying complexes modify the histone including acetylation, methylation, and phosphorylation which can change the interaction between histone and DNA; for example, methylation of specific lysine residues in H3 and H4 causes further condensation of DNA around histones, making it hard to bind transcription factor or other proteins.
A typical nucleosome distribution around TSS is shown in Figure 7 [ 56 ]. Nucleosomes are depleted around TSSs, resulting in a nucleosome-free region NFR that is flanked by two well-positioned nucleosomes whereas the nucleosomes downstream of the TSS are equally spaced in a nucleosome array. Z and H3. These may help to the nucleosome eviction when transcription is needed.
Z and less methylation and acetylation. In a barrier model for nucleosome organization, the nucleosome distribution is largely a consequence of statistical packing principles. The consensus distribution of nucleosomes gray ovals around all yeast genes is shown, aligned by the beginning and end of every gene. The resulting two plots were fused in the genic region.
The peaks and valleys represent similar positioning relative to the transcription start site TSS. The green-blue shading in the plot represents the transitions observed in nucleosome composition and phasing green represents high H2A. Z levels, acetylation, H3K4 methylation and phasing, whereas blue represents low levels of these modifications. Each of these components has different contribution in nucleosome positioning.
Interestingly, these components can affect each other thus resulting in different positioning pattern in a more complex way. The DNA sequence is critical for rotational positioning along the DNA helix, and it is also an important determinant for nucleosome occupancy. In particular, poly dA:dT and poly dG:dC tracts are intrinsically inhibitory to nucleosome formation, whereas non-homopolymeric GC-rich regions favor nucleosome formation.
Determinants of nucleosome positioning. Gray circles indicate nucleosomes. Micrococcal nuclease MNase , one kind of glycolprotein of Staphylococcus aureus , has capacity of digesting the naked DNA. MNase, firstly, induces single-strand breaks, and then cleaves the complementary strand near the first break [ 58 , 59 ].
Taking this advantage, a high throughput sequencing technique MNase-seq is developed to probe nucleosome positions in a genome-wide manner. MNase cleavage favors AT-rich region in limiting enzyme concentrations. The opening chromatin region is mainly the regulatory sites in gene transcription. Thus, the opening region may alter in different cells types. This can be reflected in DHSs.
The change of DHSs often associates one or more nucleosomes loss or formation [ 60 ]. DNase I hypersensitive sites within chromatin [ 60 ]. DNase-seq has been widely used in probing cell-specific chromatin accessibility. The rotational localization of individual nucleosomes is based on the inherent preference of DNA enzyme I cleavage of DNA at about 10 bp per nucleosome [ 61 ].
By coupling bioinformatics analysis, DNase-seq can be used in studying TF occupancy at nucleotide resolution in a qualitative and quantitative manner [ 62 ].
In DNase-seq, many cells and many sample preparations and enzyme titration steps are required [ 63 ]. ATAC-seq is an assay for transposase-accessible chromatin with high throughput sequencing [ 64 ]. Moreover, its procedure only involves two steps. Therefore, it is able to study multiple aspects of chromatin architecture simultaneously at high resolution, including nucleosomes, chromatin accessibility [ 64 ].
Chromatin immunoprecipitation followed by sequencing ChIP-seq sequences the interest DNA fragments that are separated and collected from the immunoprecipitation [ 66 ]. Figure 10 shows a general procedure of a ChIP experiment [ 66 ]. This procedure includes the DNA-protein crosslinking with formaldehyde, sonication, immunoprecipitation, reversed crosslinking, and sequencing [ 66 ]. Using antibody of the histones, such as histone H3, ChIP-seq is immediately able to determine nucleosome positions.
In addition to the techniques mentioned above, there are other techniques often used, such as Formaldehyde-assisted isolation of regulatory elements FAIRE-seq and ChIP-exo. Sequencing provides information for regions of DNA that are not occupied by histones [ 67 ]. The nucleotides of the exonuclease-treated ends are determined using DNA sequencing. At the present, nucleosome sequencing dataset are mainly from MNase-seq. A general analysis workflow includes data quality control, mapping, making nucleosome profile, determining nucleosome position, comparing between cell types, and associating with other omics-data expression data to find biological meanings.
Sequencing quality control QC is to check the reads quality fraction of mapped reads and depth of coverage. Tools BWA and Bowtie are widely used in reads alignments. During the alignment process, multiple-mapping reads and duplication reads are often filtered so as to remove overrepresented regions of the genome due to technical bias [ 60 ]. Reads filtering can be performed with SAMtools or Picard tools. Data visualization helps to observe the reads distribution at specific locus.
In IGV, the multiple types of annotation data are integrated, including gene information, epigenetic and expression data, single-nucleotide polymorphisms SNPs , repeat elements and functional information from the ENCODE, and other research projects. With respect to nucleosomes sequencing data, there are two basic tasks in analysis.
One is to calculate the nucleosome profile reads coverage both along the genomic coordinate and near the regulatory sites for instance the TSSs. The other task is to infer the precise nucleosomes positions dyad position using the nucleosome profile so as to identify the nucleosome alteration among different cell types.
0コメント