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The organization of nucleosomes around splice sites.

ABSTRACT: The occupancy of nucleosomes along chromosome is a key factor for gene regulation. However, except promoter regions, genome-wide properties and functions of nucleosome organization remain unclear in mammalian genomes. Using the computational model of Increment of Diversity with Quadratic Discriminant (IDQD) trained from the microarray data, the nucleosome occupancy score (NOScore) was defined and applied to splice junction regions of constitutive, cassette exon, alternative 3' and 5' splicing events in the human genome. We found an interesting relation between NOScore and RNA splicing: exon regions have higher NOScores compared with their flanking intron sequences in both constitutive and alternative splicing events, indicating the stronger nucleosome occupation potential of exon regions. In addition, NOScore valleys present at approximately 25 bp upstream of the acceptor site in all splicing events. By defining folding diversity-to-energy ratio to describe RNA structural flexibility, we demonstrated that primary RNA transcripts from nucleosome occupancy regions are relatively rigid and those from nucleosome depleted regions are relatively flexible. The negative correlation between nucleosome occupation/depletion of DNA sequence and structural flexibility/rigidity of its primary transcript around splice junctions may provide clues to the deeper understanding of the unexpected role for nucleosome organization in the regulation of RNA splicing.

SUBMITTER: Chen W

PROVIDER: S-EPMC2875036 | biostudies-literature | 2010 May

REPOSITORIES: biostudies-literature

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The organization of nucleosomes around splice sites.

Chen Wei W Luo Liaofu L Zhang Lirong L

Nucleic acids research 20100121 9

The occupancy of nucleosomes along chromosome is a key factor for gene regulation. However, except promoter regions, genome-wide properties and functions of nucleosome organization remain unclear in mammalian genomes. Using the computational model of Increment of Diversity with Quadratic Discriminant (IDQD) trained from the microarray data, the nucleosome occupancy score (NOScore) was defined and applied to splice junction regions of constitutive, cassette exon, alternative 3' and 5' splicing ev ...[more]

PMID: 20097656

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Project description:BackgroundThe association between M segment splicing and pathogenicity remains ambiguous in human influenza A viruses. In this study, we aimed to investigate M splicing in various human influenza A viruses and characterize its physiological roles by applying the splicing inhibitor, herboxidiene.MethodsWe examined the M splicing of human H1N1 and H3N2 viruses by comparing three H1N1 and H3N2 strains, respectively, through reverse transcriptase-polymerase chain reaction (RT-PCR) analyses. We randomly selected M sequences of human H1N1, H2N2, and H3N2 viruses isolated from 1933 to 2020 and examined their phylogenetic relationships. Next, we determined the effects of single nucleotide variations on M splicing by generating mutant viruses harboring the 55C/T variant through reverse genetics. To confirm the importance of M2 splicing in the replication of H1N1 and H3N2, we treated infected cells with splicing inhibitor herboxidiene and analyzed the viral growth using plaque assay. To explore the physiological role of the various levels of M2 protein in pathogenicity, we challenged C57BL/6 mice with the H1N1 WSN wild-type strain, mutant H1N1 (55T), and chimeric viruses including H1N1 + H3wt and H1N1 + H3mut. One-tailed paired t-test was used for virus titer calculation and multiple comparisons between groups were performed using two-way analysis of variance.ResultsM sequence splice site analysis revealed an evolutionarily conserved single nucleotide variant C55T in H3N2, which impaired M2 expression and was accompanied by collinear M1 and mRNA3 production. Aberrant M2 splicing resulted from splice-site selection rather than a general defect in the splicing process. The C55T substitution significantly reduced both M2 mRNA and protein levels regardless of the virus subtype. Consequently, herboxidiene treatment dramatically decreased both the H1N1 and H3N2 virus titers. However, a lower M2 expression only attenuated H1N1 virus replication and in vivo pathogenicity. This attenuated phenotype was restored by M replacement of H3N2 M in a chimeric H1N1 virus, despite low M2 levels.ConclusionsThe discrepancy in M2-dependence emphasizes the importance of M2 in human influenza A virus pathogenicity, which leads to subtype-specific evolution. Our findings provide insights into virus adaptation processes in humans and highlights splicing regulation as a potential antiviral target.

Project description:The eukaryotic genome, first packed into nucleosomes of about 150 bp around the histone core, is organized into euchromatin and heterochromatin, corresponding to the A and B compartments, respectively. Here, we asked if individual nucleosomes in vivo know where to go. That is, do mono-nucleosomes by themselves contain A/B compartment information, associated with transcription activity, in their biophysical properties? We purified native mono-nucleosomes to high monodispersity and used physiological concentrations of biological polyamines to determine their condensability. The chromosomal regions known to partition into A compartments have low condensability and vice versa. In silico chromatin polymer simulations using condensability as the only input showed that biophysical information needed to form compartments is all contained in single native nucleosomes and no other factors are needed. Condensability is also strongly anticorrelated with gene expression, and especially so near the promoter region and in a cell type dependent manner. Therefore, individual nucleosomes in the promoter know whether the gene is on or off, and that information is contained in their biophysical properties. Comparison with genetic and epigenetic features suggest that nucleosome condensability is a very meaningful axis onto which to project the high dimensional cellular chromatin state. Analysis of condensability using various condensing agents including those that are protein-based suggests that genome organization principle encoded into individual nucleosomes is electrostatic in nature. Polyamine depletion in mouse T cells, by either knocking out ornithine decarboxylase (ODC) or inhibiting ODC, results in hyperpolarized condensability, suggesting that when cells cannot rely on polyamines to translate biophysical properties of nucleosomes to control gene expression and 3D genome organization, they accentuate condensability contrast, which may explain dysfunction known to occur with polyamine deficiency.

Project description:In computational methods, position weight matrices (PWMs) are commonly applied for transcription factor binding site (TFBS) prediction. Although these matrices are more accurate than simple consensus sequences to predict actual binding sites, they usually produce a large number of false positive (FP) predictions and so are impoverished sources of information. Several studies have employed additional sources of information such as sequence conservation or the vicinity to transcription start sites to distinguish true binding regions from random ones. Recently, the spatial distribution of modified nucleosomes has been shown to be associated with different promoter architectures. These aligned patterns can facilitate DNA accessibility for transcription factors. We hypothesize that using data from these aligned and periodic patterns can improve the performance of binding region prediction. In this study, we propose two effective features, "modified nucleosomes neighboring" and "modified nucleosomes occupancy", to decrease FP in binding site discovery. Based on these features, we designed a logistic regression classifier which estimates the probability of a region as a TFBS. Our model learned each feature based on Sp1 binding sites on Chromosome 1 and was tested on the other chromosomes in human CD4+T cells. In this work, we investigated 21 histone modifications and found that only 8 out of 21 marks are strongly correlated with transcription factor binding regions. To prove that these features are not specific to Sp1, we combined the logistic regression classifier with the PWM, and created a new model to search TFBSs on the genome. We tested the model using transcription factors MAZ, PU.1 and ELF1 and compared the results to those using only the PWM. The results show that our model can predict Transcription factor binding regions more successfully. The relative simplicity of the model and capability of integrating other features make it a superior method for TFBS prediction.

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The organization of nucleosomes around splice sites.

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The organization of nucleosomes around splice sites.

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