Raja Jothi

Global analysis of the insulator binding protein CTCF in chromatin barrier regions reveals demarcation of active and repressive domains

Insulators are DNA elements that prevent inappropriate interactions between the neighboring regions of the genome. They can be functionally classified as either enhancer blockers or domain barriers. CTCF (CCCTC-binding factor) is the only known major insulator-binding protein in the vertebrates and has been shown to bind many enhancer-blocking elements. However, it is not clear whether it plays a role in chromatin domain barriers between active and repressive domains. Here, we used ChIP-seq to map the genome-wide binding sites of CTCF in three cell types and identified significant binding of CTCF to the boundaries of repressive chromatin domains marked by H3K27me3. Although we find an extensive overlapping of CTCF-binding sites across the three cell types, its association with the domain boundaries is cell-type-specific. We further show that the nucleosomes flanking CTCF-binding sites are well positioned. Interestingly, we found a complementary pattern between the repressive H3K27me3 and the active H2AK5ac regions, which are separated by CTCF. Our data indicate that CTCF may play important roles in the barrier activity of insulators, and this study provides a resource for further investigation of the CTCF function in organizing chromatin in the human genome.

Genome-wide identification of in vivo protein–DNA binding sites from ChIP-Seq data

ChIP-Seq, which combines chromatin immunoprecipitation (ChIP) with ultra high-throughput massively parallel sequencing, is increasingly being used for mapping protein–DNA interactions in-vivo on a genome scale. Typically, short sequence reads from ChIP-Seq are mapped to a reference genome for further analysis. Although genomic regions enriched with mapped reads could be inferred as approximate binding regions, short read lengths (∼25–50 nt) pose challenges for determining the exact binding sites within these regions. Here, we present SISSRs (Site Identification from Short Sequence Reads), a novel algorithm for precise identification of binding sites from short reads generated from ChIP-Seq experiments. The sensitivity and specificity of SISSRs are demonstrated by applying it on ChIP-Seq data for three widely studied and well-characterized human transcription factors: CTCF (CCCTC-binding factor), NRSF (neuron-restrictive silencer factor) and STAT1 (signal transducer and activator of transcription protein 1). We identified 26 814, 5813 and 73 956 binding sites for CTCF, NRSF and STAT1 proteins, respectively, which is 32, 299 and 78% more than that inferred previously for the respective proteins. Motif analysis revealed that an overwhelming majority of the identified binding sites contained the previously established consensus binding sequence for the respective proteins, thus attesting for SISSRs’ accuracy. SISSRs’ sensitivity and precision facilitated further analyses of ChIP-Seq data revealing interesting insights, which we believe will serve as guidance for designing ChIP-Seq experiments to map in vivo protein–DNA interactions. We also show that tag densities at the binding sites are a good indicator of protein–DNA binding affinity, which could be used to distinguish and characterize strong and weak binding sites. Using tag density as an indicator of DNA-binding affinity, we have identified core residues within the NRSF and CTCF binding sites that are critical for a stronger DNA binding.

An embryonic stem cell chromatin remodeling complex, esBAF, is an essential component of the core pluripotency transcriptional network

Distinctive SWI/SNF-like ATP-dependent chromatin remodeling esBAF complexes are indispensable for the maintenance and pluripotency of mouse embryonic stem (ES) cells [Ho L, et al. (2009) Proc Natl Acad Sci USA 10.1073/pnas.0812889106]. To understand the mechanism underlying the roles of these complexes in ES cells, we performed high-resolution genome-wide mapping of the core ATPase subunit, Brg, using ChIP-Seq technology. We find that esBAF, as represented by Brg, binds to genes encoding components of the core ES transcriptional circuitry, including Polycomb group proteins. esBAF colocalizes extensively with transcription factors Oct4, Sox2 and Nanog genome-wide, and shows distinct functional interactions with Oct4 and Sox2 at its target genes. Surprisingly, no significant colocalization of esBAF with PRC2 complexes, represented by Suz12, is observed. Lastly, esBAF colocalizes with Stat3 and Smad1 genome-wide, consistent with a direct and critical role in LIF and BMP signaling for maintaining self-renewal. Taken together, our studies indicate that esBAF is an essential component of the core pluripotency transcriptional network, and might also be a critical component of the LIF and BMP signaling pathways essential for maintenance of self-renewal and pluripotency.

esBAF facilitates pluripotency by conditioning the genome for LIF/STAT3 signalling and by regulating polycomb function

Signalling by the cytokine LIF and its downstream transcription factor, STAT3, prevents differentiation of pluripotent embryonic stem cells (ESCs). This contrasts with most cell types where STAT3 signalling induces differentiation. We find that STAT3 binding across the pluripotent genome is dependent on Brg1, the ATPase subunit of a specialized chromatin remodelling complex (esBAF) found in ESCs. Brg1 is required to establish chromatin accessibility at STAT3 binding targets, preparing these sites to respond to LIF signalling. Brg1 deletion leads to rapid polycomb (PcG) binding and H3K27me3-mediated silencing of many Brg1-activated targets genome wide, including the target genes of the LIF signalling pathway. Hence, one crucial role of Brg1 in ESCs involves its ability to potentiate LIF signalling by opposing PcG. Contrary to expectations, Brg1 also facilitates PcG function at classical PcG targets, including all four Hox loci, reinforcing their repression in ESCs. Therefore, esBAF does not simply antagonize PcG. Rather, the two chromatin regulators act both antagonistically and synergistically with the common goal of supporting pluripotency.

Chromatin poises miRNA- and protein-coding genes for expression

Chromatin modifications have been implicated in the regulation of gene expression. While association of certain modifications with expressed or silent genes has been established, it remains unclear how changes in chromatin environment relate to changes in gene expression. In this article, we used ChIP-seq (chromatin immunoprecipitation with massively parallel sequencing) to analyze the genome-wide changes in chromatin modifications during activation of total human CD4(+) T cells by T-cell receptor (TCR) signaling. Surprisingly, we found that the chromatin modification patterns at many induced and silenced genes are relatively stable during the short-term activation of resting T cells. Active chromatin modifications were already in place for a majority of inducible protein-coding genes, even while the genes were silent in resting cells. Similarly, genes that were silenced upon T-cell activation retained positive chromatin modifications even after being silenced. To investigate if these observations are also valid for miRNA-coding genes, we systematically identified promoters for known miRNA genes using epigenetic marks and profiled their expression patterns using deep sequencing. We found that chromatin modifications can poise miRNA-coding genes as well. Our data suggest that miRNA- and protein-coding genes share similar mechanisms of regulation by chromatin modifications, which poise inducible genes for activation in response to environmental stimuli.

DOMINE: a comprehensive collection of known and predicted domain-domain interactions

DOMINE is a comprehensive collection of known and predicted domain–domain interactions (DDIs) compiled from 15 different sources. The updated DOMINE includes 2285 new domain–domain interactions (DDIs) inferred from experimentally characterized high-resolution three-dimensional structures, and about 3500 novel predictions by five computational approaches published over the last 3 years. These additions bring the total number of unique DDIs in the updated version to 26 219 among 5140 unique Pfam domains, a 23% increase compared to 20 513 unique DDIs among 4346 unique domains in the previous version. The updated version now contains 6634 known DDIs, and features a new classification scheme to assign confidence levels to predicted DDIs. DOMINE will serve as a valuable resource to those studying protein and domain interactions. Most importantly, DOMINE will not only serve as an excellent reference to bench scientists testing for new interactions but also to bioinformaticans seeking to predict novel protein–protein interactions based on the DDIs. The contents of the DOMINE are available at http://domine.utdallas.edu.

Genomic analysis reveals a tight link between transcription factor dynamics and regulatory network architecture.

Although several studies have provided important insights into the general principles of biological networks, the link between network organization and the genome‐scale dynamics of the underlying entities (genes, mRNAs, and proteins) and its role in systems behavior remain unclear. Here we show that transcription factor (TF) dynamics and regulatory network organization are tightly linked. By classifying TFs in the yeast regulatory network into three hierarchical layers (top, core, and bottom) and integrating diverse genome‐scale datasets, we find that the TFs have static and dynamic properties that are similar within a layer and different across layers. At the protein level, the top‐layer TFs are relatively abundant, long‐lived, and noisy compared with the core‐ and bottom‐layer TFs. Although variability in expression of top‐layer TFs might confer a selective advantage, as this permits at least some members in a clonal cell population to initiate a response to changing conditions, tight regulation of the core‐ and bottom‐layer TFs may minimize noise propagation and ensure fidelity in regulation. We propose that the interplay between network organization and TF dynamics could permit differential utilization of the same underlying network by distinct members of a clonal cell population.

Interplay between gene expression noise and regulatory network architecture

Complex regulatory networks orchestrate most cellular processes in biological systems. Genes in such networks are subject to expression noise, resulting in isogenic cell populations exhibiting cell-to-cell variation in protein levels. Increasing evidence suggests that cells have evolved regulatory strategies to limit, tolerate or amplify expression noise. In this context, fundamental questions arise: how can the architecture of gene regulatory networks generate, make use of or be constrained by expression noise? Here, we discuss the interplay between expression noise and gene regulatory network at different levels of organization, ranging from a single regulatory interaction to entire regulatory networks. We then consider how this interplay impacts a variety of phenomena, such as pathogenicity, disease, adaptation to changing environments, differential cell-fate outcome and incomplete or partial penetrance effects. Finally, we highlight recent technological developments that permit measurements at the single-cell level, and discuss directions for future research.

Acute depletion of Tet1-dependent 5-hydroxymethylcytosine levels impairs LIF/Stat3 signaling and results in loss of embryonic stem cell identity

The TET family of FE(II) and 2-oxoglutarate-dependent enzymes (Tet1/2/3) promote DNA demethylation by converting 5-methylcytosine to 5-hydroxymethylcytosine (5hmC), which they further oxidize into 5-formylcytosine and 5-carboxylcytosine. Tet1 is robustly expressed in mouse embryonic stem cells (mESCs) and has been implicated in mESC maintenance. Here we demonstrate that, unlike genetic deletion, RNAi-mediated depletion of Tet1 in mESCs led to a significant reduction in 5hmC and loss of mESC identity. The differentiation phenotype due to Tet1 depletion positively correlated with the extent of 5hmC loss. Meta-analyses of genomic data sets suggested interaction between Tet1 and leukemia inhibitory factor (LIF) signaling. LIF signaling is known to promote self-renewal and pluripotency in mESCs partly by opposing MAPK/ERK-mediated differentiation. Withdrawal of LIF leads to differentiation of mESCs. We discovered that Tet1 depletion impaired LIF-dependent Stat3-mediated gene activation by affecting Stat3s ability to bind to its target sites on chromatin. Nanog overexpression or inhibition of MAPK/ERK signaling, both known to maintain mESCs in the absence of LIF, rescued Tet1 depletion, further supporting the dependence of LIF/Stat3 signaling on Tet1. These data support the conclusion that analysis of mESCs in the hours/days immediately following efficient Tet1 depletion reveals Tet1s normal physiological role in maintaining the pluripotent state that may be subject to homeostatic compensation in genetic models.

Diverse stresses dramatically alter genome-wide p53 binding and transactivation landscape in human cancer cells

The effects of diverse stresses on promoter selectivity and transcription regulation by the tumor suppressor p53 are poorly understood. We have taken a comprehensive approach to characterizing the human p53 network that includes p53 levels, binding, expression and chromatin changes under diverse stresses. Human osteosarcoma U2OS cells treated with anti-cancer drugs Doxorubicin (DXR) or Nutlin-3 (Nutlin) led to strikingly different p53 gene binding patterns based on chromatin immunoprecipitation with high-throughput sequencing experiments. Although two contiguous RRRCWWGYYY decamers is the consensus binding motif, p53 can bind a single decamer and function in vivo. Although the number of sites bound by p53 was six times greater for Nutlin than DXR, expression changes induced by Nutlin were much less dramatic compared with DXR. Unexpectedly, the solvent dimethylsulphoxide (DMSO) alone induced p53 binding to many sites common to DXR; however, this binding had no effect on target gene expression. Together, these data imply a two-stage mechanism for p53 transactivation where p53 binding only constitutes the first stage. Furthermore, both p53 binding and transactivation were associated with increased active histone modification histone H3 lysine 4 trimethylation. We discovered 149 putative new p53 target genes including several that are relevant to tumor suppression, revealing potential new targets for cancer therapy and expanding our understanding of the p53 regulatory network.