基于ChIP-seq的差异组蛋白修饰区域的筛选

组蛋白修饰是在基因组水平上起到重要调控作用的表观遗传修饰,随着ChIP-Seq的广泛使用,高通量数据的积累,为从全基因组研究组蛋白修饰模式奠定了基础。但目前缺乏在多样本间筛选疾病相关的调控区域的方法,因而本文开发了一种多细胞系的差异筛选算法来识别差异组蛋白修饰区域。本文通过窗口移动法来估计组蛋白修饰水平,并根据信息熵理论定量各个细胞系之间的差异。基于随机背景来确定差异显著性阈值。利用此算法来筛选人类全基因组9个细胞系间H3K4me3差异的区域,结果显示这些区域显著富集在基因启动子上和其他重要的染色质状态上,且与先前人们发现的活性启动子染色质状态显著重叠。通过文献挖掘进一步证实了与白血病相关的基因组标记。这些结果表明基于熵的策略可有效地挖掘多细胞系间以及与疾病相关的差异组蛋白修饰。     

An HMM approach to genome-wide identification of differential histone modification sites from ChIP-seq data

MOTIVATION: Epigenetic modifications are one of the critical factors to regulate gene expression and genome function. Among different epigenetic modifications, the differential histone modification sites (DHMSs) are of great interest to study the dynamic nature of epigenetic and gene expression regulations among various cell types, stages or environmental responses. To capture the histone modifications at whole genome scale, ChIP-seq technology is becoming a robust and comprehensive approach. Thus the DHMSs are potentially identifiable by comparing two ChIP-seq libraries. However, little has been addressed on this issue in literature. RESULTS: Aiming at identifying DHMSs, we propose an approach called ChIPDiff for the genome-wide comparison of histone modification sites identified by ChIP-seq. Based on the observations of ChIP fragment counts, the proposed approach employs a hidden Markov model (HMM) to infer the states of histone modification changes at each genomic location. We evaluated the performance of ChIPDiff by comparing the H3K27me3 modification sites between mouse embryonic stem cell (ESC) and neural progenitor cell (NPC). We demonstrated that the H3K27me3 DHMSs identified by our approach are of high sensitivity, specificity and technical reproducibility. ChIPDiff was further applied to uncover the differential H3K4me3 and H3K36me3 sites between different cell states. Interesting biological discoveries were achieved from such comparison in our study.     

Proliferating cell nuclear antigen associates with histone deacetylase activity, integrating DNA replication and chromatin modification

Faithful inheritance of the chromatin structure is essential for maintaining the gene expression integrity of a cell. Histone modification by acetylation and deacetylation is a critical control of chromatin structure. In this study, we test the hypothesis that histone deacetylase 1 (HDAC1) is physically associated with a basic component of the DNA replication machinery as a mechanism of coordinating histone deacetylation and DNA synthesis. Proliferating cell nuclear antigen (PCNA) is a sliding clamp that serves as a loading platform for many proteins involved in DNA replication and DNA repair. We show that PCNA interacts with HDAC1 in human cells and in vitro and that a considerable fraction of PCNA and HDAC1 colocalize in the cell nucleus. PCNA associates with histone deacetylase activity that is completely abolished in the presence of the HDAC inhibitor trichostatin A. Trichostatin A treatment arrests cells at the G(2)-M phase of the cell cycle, which is consistent with the hypothesis that the proper formation of the chromatin after DNA replication may be important in signaling the progression through the cell cycle. Our results strengthen the role of PCNA as a factor coordinating DNA replication and epigenetic inheritance.     

Computational study of associations between histone modification and protein-DNA binding in yeast genome by integrating diverse information

Background

Several tools are available to identify miRNAs from deep-sequencing data, however, only a few of them, like miRDeep, can identify novel miRNAs and are also available as a standalone application. Given the difference between plant and animal miRNAs, particularly in terms of distribution of hairpin length and the nature of complementarity with its duplex partner (or miRNA star), the underlying (statistical) features of miRDeep and other tools, using similar features, are likely to get affected.

Results

The potential effects on features, such as minimum free energy, stability of secondary structures, excision length, etc., were examined, and the parameters of those displaying sizable changes were estimated for plant specific miRNAs. We found most of these features acquired a new set of values or distributions for plant specific miRNAs. While the length of conserved positions (nucleus) in mature miRNAs were relatively longer in plants, the difference in distribution of minimum free energy, between real and background hairpins, was marginal. However, the choice of source (species) of background sequences was found to affect both the minimum free energy and miRNA hairpin stability. The new parameters were tested on an Illumina dataset from maize seedlings, and the results were compared with those obtained using default parameters. The newly parameterized model was found to have much improved specificity and sensitivity over its default counterpart.

Conclusions

In summary, the present study reports behavior of few general and tool-specific statistical features for improving the prediction accuracy of plant miRNAs from deep-sequencing data.     

Scaling up population dynamics: integrating theory and data

How to scale up from local-scale interactions to regional-scale dynamics is a critical issue in field ecology. We show how to implement a systematic approach to the problem of scaling up, using scale transition theory. Scale transition theory shows that dynamics on larger spatial scales differ from predictions based on the local dynamics alone because of an interaction between local-scale nonlinear dynamics and spatial variation in density or the environment. Based on this theory, a systematic approach to scaling up has four steps: (1) derive a model to translate the effects of local dynamics to the regional scale, and to identify key interactions between nonlinearity and spatial variation, (2) measure local-scale model parameters to determine nonlinearities at local scales, (3) measure spatial variation, and (4) combine nonlinearity and variation measures to obtain the scale transition. We illustrate the approach, with an example from benthic stream ecology of caddisflies living in riffles. By sampling from a simulated system, we show how collecting the appropriate data at local (riffle) scales to measure nonlinearities, combined with measures of spatial variation, leads to the correct inference for dynamics at the larger scale of the stream. The approach provides a way to investigate the mechanisms and consequences of changes in population dynamics with spatial scale using a relatively small amount of field data.     

Epigenetic histone modification by butyrate downregulates KIT and attenuates mast cell function

Short-chain fatty acid butyrate is produced from the bacterial fermentation of indigestible fiber in the intestinal lumen, and it has been shown to attenuate lung inflammation in murine asthma models. Mast cells (MCs) are initiators of inflammatory response to allergens, and they play an important role in asthma. MC survival and proliferation is regulated by its growth factor stem cell factor (SCF), which acts through the receptor, KIT. It has previously been shown that butyrate attenuates the activation of MCs by allergen stimulation. However, how butyrate mechanistically influences SCF signalling to impact MC function remains unknown. Here, we report that butyrate treatment triggered the modification of MC histones via butyrylation and acetylation, and inhibition of histone deacetylase (HDAC) activity. Further, butyrate treatment caused downregulation of SCF receptor KIT and associated phosphorylation, leading to significant attenuation of SCF-mediated MC proliferation, and pro-inflammatory cytokine secretion. Mechanistically, butyrate inhibited MC function by suppressing KIT and downstream p38 and Erk phosphorylation, and it mediated these effects via modification of histones, acting as an HDAC inhibitor and not via its traditional GPR41 (FFAR3) or GPR43 (FFAR2) butyrate receptors. In agreement, the pharmacological inhibition of Class I HDAC (HDAC1/3) mirrored butyrate's effects, suggesting that butyrate impacts MC function by HDAC1/3 inhibition. Taken together, butyrate epigenetically modifies histones and downregulates the SCF/KIT/p38/Erk signalling axis, leading to the attenuation of MC function, validating its ability to suppress MC-mediated inflammation. Therefore, butyrate supplementations could offer a potential treatment strategy for allergy and asthma via epigenetic alterations in MCs.