Improved genome-wide localization by ChIP-chip using double-round T7 RNA polymerase-based amplification

Chromatin immunoprecipitation combined with DNA microarrays (ChIP-chip) is a powerful technique to detect in vivo protein–DNA interactions. Due to low yields, ChIP assays of transcription factors generally require amplification of immunoprecipitated genomic DNA. Here, we present an adapted linear amplification method that involves two rounds of T7 RNA polymerase amplification (double-T7). Using this we could successfully amplify as little as 0.4 ng of ChIP DNA to sufficient amounts for microarray analysis. In addition, we compared the double-T7 method to the ligation-mediated polymerase chain reaction (LM-PCR) method in a ChIP-chip of the yeast transcription factor Gsm1p. The double-T7 protocol showed lower noise levels and stronger binding signals compared to LM-PCR. Both LM-PCR and double-T7 identified strongly bound genomic regions, but the double-T7 method increased sensitivity and specificity to allow detection of weaker binding sites

The Inheritance of Histone Modifications Depends upon the Location in the Chromosome in Saccharomyces cerevisiae

Histone modifications are important epigenetic features of chromatin that must be replicated faithfully. However, the molecular mechanisms required to duplicate and maintain histone modification patterns in chromatin remain to be determined. Here, we show that the introduction of histone modifications into newly deposited nucleosomes depends upon their location in the chromosome. In Saccharomyces cerevisiae, newly deposited nucleosomes consisting of newly synthesized histone H3-H4 tetramers are distributed throughout the entire chromosome. Methylation of lysine 4 on histone H3 (H3-K4), a hallmark of euchromatin, is introduced into these newly deposited nucleosomes, regardless of whether the neighboring preexisting nucleosomes harbor the K4 mutation in histone H3. Furthermore, if the heterochromatin-binding protein Sir3 is unavailable during DNA replication, histone H3-K4 methylation is introduced onto newly deposited nucleosomes in telomeric heterochromatin. Thus, a conservative distribution model most accurately explains the inheritance of histone modifications because the location of histones within euchromatin or heterochromatin determines which histone modifications are introduced

Genic and Global Functions for Paf1C in Chromatin Modification and Gene Expression in Arabidopsis

In budding yeast, intragenic histone modification is linked with transcriptional elongation through the conserved regulator Paf1C. To investigate Paf1C-related function in higher eukaryotes, we analyzed the effects of loss of Paf1C on histone H3 density and patterns of H3 methylated at K4, K27, and K36 in Arabidopsis genes, and integrated this with existing gene expression data. Loss of Paf1C did not change global abundance of H3K4me3 or H3K36me2 within chromatin, but instead led to a 3′ shift in the distribution of H3K4me3 and a 5′ shift in the distribution of H3K36me2 within genes. We found that genes regulated by plant Paf1C showed strong enrichment for both H3K4me3 and H3K27me3 and also showed a high degree of tissue-specific expression. At the Paf1C- and PcG-regulated gene FLC, transcriptional silencing and loss of H3K4me3 and H3K36me2 were accompanied by expansion of H3K27me3 into the promoter and transcriptional start regions and further enrichment of H3K27me3 within the transcribed region. These results highlight both genic and global functions for plant Paf1C in histone modification and gene expression, and link transcriptional activity with cellular memory

Mapping Dynamic Histone Acetylation Patterns to Gene Expression in Nanog-depleted Murine Embryonic Stem Cells

Embryonic stem cells (ESC) have the potential to self-renew indefinitely and to differentiate into any of the three germ layers. The molecular mechanisms for self-renewal, maintenance of pluripotency and lineage specification are poorly understood, but recent results point to a key role for epigenetic mechanisms. In this study, we focus on quantifying the impact of histone 3 acetylation (H3K9,14ac) on gene expression in murine embryonic stem cells. We analyze genome-wide histone acetylation patterns and gene expression profiles measured over the first five days of cell differentiation triggered by silencing Nanog, a key transcription factor in ESC regulation. We explore the temporal and spatial dynamics of histone acetylation data and its correlation with gene expression using supervised and unsupervised statistical models. On a genome-wide scale, changes in acetylation are significantly correlated to changes in mRNA expression and, surprisingly, this coherence increases over time. We quantify the predictive power of histone acetylation for gene expression changes in a balanced cross-validation procedure. In an in-depth study we focus on genes central to the regulatory network of Mouse ESC, including those identified in a recent genome-wide RNAi screen and in the PluriNet, a computationally derived stem cell signature. We find that compared to the rest of the genome, ESC-specific genes show significantly more acetylation signal and a much stronger decrease in acetylation over time, which is often not reflected in an concordant expression change. These results shed light on the complexity of the relationship between histone acetylation and gene expression and are a step forward to dissect the multilayer regulatory mechanisms that determine stem cell fate.Comment: accepted at PLoS Computational Biolog

Computational Analysis of Whole-Genome Differential Allelic Expression Data in Human

Allelic imbalance (AI) is a phenomenon where the two alleles of a given gene are expressed at different levels in a given cell, either because of epigenetic inactivation of one of the two alleles, or because of genetic variation in regulatory regions. Recently, Bing et al. have described the use of genotyping arrays to assay AI at a high resolution (∼750,000 SNPs across the autosomes). In this paper, we investigate computational approaches to analyze this data and identify genomic regions with AI in an unbiased and robust statistical manner. We propose two families of approaches: (i) a statistical approach based on z-score computations, and (ii) a family of machine learning approaches based on Hidden Markov Models. Each method is evaluated using previously published experimental data sets as well as with permutation testing. When applied to whole genome data from 53 HapMap samples, our approaches reveal that allelic imbalance is widespread (most expressed genes show evidence of AI in at least one of our 53 samples) and that most AI regions in a given individual are also found in at least a few other individuals. While many AI regions identified in the genome correspond to known protein-coding transcripts, others overlap with recently discovered long non-coding RNAs. We also observe that genomic regions with AI not only include complete transcripts with consistent differential expression levels, but also more complex patterns of allelic expression such as alternative promoters and alternative 3′ end. The approaches developed not only shed light on the incidence and mechanisms of allelic expression, but will also help towards mapping the genetic causes of allelic expression and identify cases where this variation may be linked to diseases

ChromaSig: A Probabilistic Approach to Finding Common Chromatin Signatures in the Human Genome

Computational methods to identify functional genomic elements using genetic information have been very successful in determining gene structure and in identifying a handful of cis-regulatory elements. But the vast majority of regulatory elements have yet to be discovered, and it has become increasingly apparent that their discovery will not come from using genetic information alone. Recently, high-throughput technologies have enabled the creation of information-rich epigenetic maps, most notably for histone modifications. However, tools that search for functional elements using this epigenetic information have been lacking. Here, we describe an unsupervised learning method called ChromaSig to find, in an unbiased fashion, commonly occurring chromatin signatures in both tiling microarray and sequencing data. Applying this algorithm to nine chromatin marks across a 1% sampling of the human genome in HeLa cells, we recover eight clusters of distinct chromatin signatures, five of which correspond to known patterns associated with transcriptional promoters and enhancers. Interestingly, we observe that the distinct chromatin signatures found at enhancers mark distinct functional classes of enhancers in terms of transcription factor and coactivator binding. In addition, we identify three clusters of novel chromatin signatures that contain evolutionarily conserved sequences and potential cis-regulatory elements. Applying ChromaSig to a panel of 21 chromatin marks mapped genomewide by ChIP-Seq reveals 16 classes of genomic elements marked by distinct chromatin signatures. Interestingly, four classes containing enrichment for repressive histone modifications appear to be locally heterochromatic sites and are enriched in quickly evolving regions of the genome. The utility of this approach in uncovering novel, functionally significant genomic elements will aid future efforts of genome annotation via chromatin modifications

An NF-Y-Dependent Switch of Positive and Negative Histone Methyl Marks on CCAAT Promoters

Background: Histone tails have a plethora of different post-translational modifications, which are located differently in ‘‘open’ ’ and ‘‘closed’ ’ parts of genomes. H3K4me3/H3K79me2 and H4K20me3 are among the histone marks associated with the early establishment of active and inactive chromatin, respectively. One of the most widespread promoter elements is the CCAAT box, bound by the NF-Y trimer. Two of NF-Y subunits have an H2A-H2B-like structure. Principal findings: We established the causal relationship between NF-Y binding and positioning of methyl marks, by ChIP analysis of mouse and human cells infected with a dominant negative NF-YA: a parallel decrease in NF-Y binding, H3K4me3, H3K79me2 and transcription was observed in promoters that are dependent upon NF-Y. On the contrary, changes in the levels of H3K9-14ac were more subtle. Components of the H3K4 methylating MLL complex are not recruited in the absence of NF-Y. As for repressed promoters, NF-Y removal leads to a decrease in the H4K20me3 mark and deposition of H3K4me3. Conclusions: Two relevant findings are reported: (i) NF-Y gains access to its genomic locations independently from the presence of methyl histone marks, either positive or negative; (ii) NF-Y binding has profound positive or negative consequences on the deposition of histone methyl marks. Therefore NF-Y is a fundamental switch at the heart of decisio

Dissecting Nucleosome Free Regions by a Segmental Semi-Markov Model

BACKGROUND: Nucleosome free regions (NFRs) play important roles in diverse biological processes including gene regulation. A genome-wide quantitative portrait of each individual NFR, with their starting and ending positions, lengths, and degrees of nucleosome depletion is critical for revealing the heterogeneity of gene regulation and chromatin organization. By averaging nucleosome occupancy levels, previous studies have identified the presence of NFRs in the promoter regions across many genes. However, evaluation of the quantitative characteristics of individual NFRs requires an NFR calling method. METHODOLOGY: In this study, we propose a statistical method to identify the patterns of NFRs from a genome-wide measurement of nucleosome occupancy. This method is based on an appropriately designed segmental semi-Markov model, which can capture each NFR pattern and output its quantitative characterizations. Our results show that the majority of the NFRs are located in intergenic regions or promoters with a length of about 400-600bp and varying degrees of nucleosome depletion. Our quantitative NFR mapping allows for an investigation of the relative impacts of transcription machinery and DNA sequence in evicting histones from NFRs. We show that while both factors have significant overall effects, their specific contributions vary across different subtypes of NFRs. CONCLUSION: The emphasis of our approach on the variation rather than the consensus of nucleosome free regions sets the tone for enabling the exploration of many subtler dynamic aspects of chromatin biology

The Set2/Rpd3S Pathway Suppresses Cryptic Transcription without Regard to Gene Length or Transcription Frequency

In cells lacking the histone methyltransferase Set2, initiation of RNA polymerase II transcription occurs inappropriately within the protein-coding regions of genes, rather than being restricted to the proximal promoter. It was previously reported that this “cryptic” transcription occurs preferentially in long genes, and in genes that are infrequently transcribed. Here, we mapped the transcripts produced in an S. cerevisiae strain lacking Set2, and applied rigorous statistical methods to identify sites of cryptic transcription at high resolution. We find that suppression of cryptic transcription occurs independent of gene length or transcriptional frequency. Our conclusions differ with those reported previously because we obtained a higher-resolution dataset, we accounted for the fact that gene length and transcriptional frequency are not independent variables, and we accounted for several ascertainment biases that make cryptic transcription easier to detect in long, infrequently transcribed genes. These new results and conclusions have implications for many commonly used genomic analysis approaches, and for the evolution of high-fidelity RNA polymerase II transcriptional initiation in eukaryotes

Critical Role of TCF-1 in Repression of the IL-17 Gene

Overwhelming activation of IL-17, a gene involved in inflammation, leads to exaggerated Th17 responses associated with numerous autoimmune conditions, such as experimental autoimmune encephalomyelitis (EAE). Here we show that TCF-1 is a critical factor to repress IL-17 gene locus by chromatin modifications during T cell development. Deletion of TCF-1 resulted in increased IL-17 gene expression both in thymus and peripheral T cells, which led to enhanced Th17 differentiation. As a result, TCF-1-/- mice were susceptible to Th17-dependent EAE induction. Rag1-/- mice reconstituted with TCF-1-/- T cells were also susceptible to EAE, indicating TCF-1 is intrinsically required to repress IL-17. However, expression of wild-type TCF-1 or dominant negative TCF-1 did not interfere with Th17 differentiation in mature T cells. Furthermore, expression of TCF-1 in TCF-1-/- T cells could not restore Th17 differentiation to wild-type levels, indicating that TCF-1 cannot affect IL-17 production at the mature T cell stage. This is also supported by the normal up-regulation or activation in mature TCF-1-/- T cells of factors known to regulate Th17 differentiation, including RORγt and Stat3. We observed hyperacetylation together with trimethylation of Lys-4 at the IL-17 locus in TCF-1-/- thymocytes, two epigenetic modifications indicating an open active state of the gene. Such epigenetic modifications were preserved even when TCF-1-/- T cells migrated out of thymus. Therefore, TCF-1 mediates an active process to repress IL-17 gene expression via epigenetic modifications during T cell development. This TCF-1-mediated repression of IL-17 is critical for peripheral T cells to generate balanced immune responses