High Resolution Genome Wide Binding Event Finding and Motif Discovery Reveals Transcription Factor Spatial Binding Constraints

An essential component of genome function is the syntax of genomic regulatory elements that determine how diverse transcription factors interact to orchestrate a program of regulatory control. A precise characterization of in vivo spacing constraints between key transcription factors would reveal key aspects of this genomic regulatory language. To discover novel transcription factor spatial binding constraints in vivo, we developed a new integrative computational method, genome wide event finding and motif discovery (GEM). GEM resolves ChIP data into explanatory motifs and binding events at high spatial resolution by linking binding event discovery and motif discovery with positional priors in the context of a generative probabilistic model of ChIP data and genome sequence. GEM analysis of 63 transcription factors in 214 ENCODE human ChIP-Seq experiments recovers more known factor motifs than other contemporary methods, and discovers six new motifs for factors with unknown binding specificity. GEM's adaptive learning of binding-event read distributions allows it to further improve upon previous methods for processing ChIP-Seq and ChIP-exo data to yield unsurpassed spatial resolution and discovery of closely spaced binding events of the same factor. In a systematic analysis of in vivo sequence-specific transcription factor binding using GEM, we have found hundreds of spatial binding constraints between factors. GEM found 37 examples of factor binding constraints in mouse ES cells, including strong distance-specific constraints between Klf4 and other key regulatory factors. In human ENCODE data, GEM found 390 examples of spatially constrained pair-wise binding, including such novel pairs as c-Fos:c-Jun/USF1, CTCF/Egr1, and HNF4A/FOXA1. The discovery of new factor-factor spatial constraints in ChIP data is significant because it proposes testable models for regulatory factor interactions that will help elucidate genome function and the implementation of combinatorial control

Divergent wiring of repressive and active chromatin interactions between mouse embryonic and trophoblast lineages.

The establishment of the embryonic and trophoblast lineages is a developmental decision underpinned by dramatic differences in the epigenetic landscape of the two compartments. However, it remains unknown how epigenetic information and transcription factor networks map to the 3D arrangement of the genome, which in turn may mediate transcriptional divergence between the two cell lineages. Here, we perform promoter capture Hi-C experiments in mouse trophoblast (TSC) and embryonic (ESC) stem cells to understand how chromatin conformation relates to cell-specific transcriptional programmes. We find that key TSC genes that are kept repressed in ESCs exhibit interactions between H3K27me3-marked regions in ESCs that depend on Polycomb repressive complex 1. Interactions that are prominent in TSCs are enriched for enhancer-gene contacts involving key TSC transcription factors, as well as TET1, which helps to maintain the expression of TSC-relevant genes. Our work shows that the first developmental cell fate decision results in distinct chromatin conformation patterns establishing lineage-specific contexts involving both repressive and active interactions

Large-scale analysis of transcriptional cis-regulatory modules reveals both common features and distinct subclasses

Analysis of 280 experimentally-verified cis-regulatory modules from Drosophila reveal features both common to all and unique to distinct subclasses of modules

PeakRanger: A cloud-enabled peak caller for ChIP-seq data

Background: Chromatin immunoprecipitation (ChIP), coupled with massively parallel short-read sequencing (seq) is used to probe chromatin dynamics. Although there are many algorithms to call peaks from ChIP-seq datasets, most are tuned either to handle punctate sites, such as transcriptional factor binding sites, or broad regions, such as histone modification marks; few can do both. Other algorithms are limited in their configurability, performance on large data sets, and ability to distinguish closely-spaced peaks. Results: In this paper, we introduce PeakRanger, a peak caller software package that works equally well on punctate and broad sites, can resolve closely-spaced peaks, has excellent performance, and is easily customized. In addition, PeakRanger can be run in a parallel cloud computing environment to obtain extremely high performance on very large data sets. We present a series of benchmarks to evaluate PeakRanger against 10 other peak callers, and demonstrate the performance of PeakRanger on both real and synthetic data sets. We also present real world usages of PeakRanger, including peak-calling in the modENCODE project. Conclusions: Compared to other peak callers tested, PeakRanger offers improved resolution in distinguishing extremely closely-spaced peaks. PeakRanger has above-average spatial accuracy in terms of identifying the precise location of binding events. PeakRanger also has excellent sensitivity and specificity in all benchmarks evaluated. In addition, PeakRanger offers significant improvements in run time when running on a single processor system, and very marked improvements when allowed to take advantage of the MapReduce parallel environment offered by a cloud computing resource. PeakRanger can be downloaded at the official site of modENCODE project: http://www.modencode.org/software/ranger

An Integrated Model of Multiple-Condition ChIP-Seq Data Reveals Predeterminants of Cdx2 Binding

Regulatory proteins can bind to different sets of genomic targets in various cell types or conditions. To reliably characterize such condition-specific regulatory binding we introduce MultiGPS, an integrated machine learning approach for the analysis of multiple related ChIP-seq experiments. MultiGPS is based on a generalized Expectation Maximization framework that shares information across multiple experiments for binding event discovery. We demonstrate that our framework enables the simultaneous modeling of sparse condition-specific binding changes, sequence dependence, and replicate-specific noise sources. MultiGPS encourages consistency in reported binding event locations across multiple-condition ChIP-seq datasets and provides accurate estimation of ChIP enrichment levels at each event. MultiGPS's multi-experiment modeling approach thus provides a reliable platform for detecting differential binding enrichment across experimental conditions. We demonstrate the advantages of MultiGPS with an analysis of Cdx2 binding in three distinct developmental contexts. By accurately characterizing condition-specific Cdx2 binding, MultiGPS enables novel insight into the mechanistic basis of Cdx2 site selectivity. Specifically, the condition-specific Cdx2 sites characterized by MultiGPS are highly associated with pre-existing genomic context, suggesting that such sites are pre-determined by cell-specific regulatory architecture. However, MultiGPS-defined condition-independent sites are not predicted by pre-existing regulatory signals, suggesting that Cdx2 can bind to a subset of locations regardless of genomic environment. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2–5.National Science Foundation (U.S.) (Graduate Research Fellowship under Grant 0645960)National Institutes of Health (U.S.) (grant P01 NS055923)Pennsylvania State University. Center for Eukaryotic Gene Regulatio

N-Linked Glycosylation Regulates CD22 Organization and Function

The organization and clustering of cell surface proteins plays a critical role in controlling receptor signaling; however, the biophysical mechanisms regulating these parameters are not well understood. Elucidating these mechanisms is highly significant to our understanding of immune function in health and disease, given the importance of B cell receptor (BCR) signaling in directing B cells to produce antibodies for the clearance of pathogens, and the potential deleterious effects of dysregulated BCR signaling, such as in B cell malignancies or autoimmune disease. One of main inhibitory co-receptors on B cells is CD22, a sialic-acid binding protein, which interacts homotypically with other sialylated CD22 molecules, as well as heterotypically with IgM and CD45. Although the importance of CD22 in attenuating BCR signaling is well established, we still do not fully understand what mediates CD22 organization and association to BCRs. CD22 is highly glycosylated, containing 12 N-linked glycosylation sites on its extracellular domain, the function of which remain to be resolved. We were interested in how these glycosylation sites mediate homotypic vs. heterotypic interactions. To this end, we mutated five out of the six N-linked glycosylation residues on CD22 localized closest to the sialic acid binding site. Glycan site N101 was not mutated as this resulted in lack of CD22 expression. We used dual-color super-resolution imaging to investigate the impact of altered glycosylation of CD22 on the nanoscale organization of CD22 and its association with BCR. We show that mutation of these five glycosylation sites increased the clustering tendency of CD22 and resulted in higher density CD22 nanoclusters. Consistent with these findings of altered CD22 organization, we found that mutation of N-glycan sites attenuated CD22 phosphorylation upon BCR stimulation, and consequently, increased BCR signaling. Importantly, we identified that these sites may be ligands for the soluble secreted lectin, galectin-9, and are necessary for galectin-9 mediated inhibition of BCR signaling. Taken together, these findings implicate N-linked glycosylation in the organization and function of CD22, likely through regulating heterotypic interactions between CD22 and its binding partners

FGF signaling and cell state transitions during organogenesis

Organogenesis is a complex choreography of morphogenetic processes, patterns and dynamic shape changes as well as the specification of cell fates. Although several molecular actors and context-specific mechanisms have already been identified, our general understanding of the fundamental principles that govern the formation of organs is far from comprehensive. The application of the concept of ‘rebuild it to understand it’ from synthetic biology represents a promising alternative to the classical approach of ‘break it to understand it’ in order to distill biological understanding from complex developmental processes. According to this ‘rebuilding’ concept, in this study we sought to develop an experimental approach to induce the formation of organs from progenitor cells ‘on demand’ and to investigate the minimum requirements for such a process. The zebrafish lateral line chain cells are a powerful in vivo model for our study because they are a group of naïve multipotent progenitor cells that display mesenchyme-like features. In order to bring these cells to form organs, we used the well-known role of the FGF signaling pathway as a driver of organogenesis in the lateral line and developed an inducible and constitutively active form of the fibroblast growth factor receptor 1a (chemoFGFR). The cell-autonomous induction of this chemoFGFR in chain cells effectively triggered the formation of fully mature organs and thus enabled spatial and temporal control of the organogenesis process. Next, we asked what it takes to form an organ de novo. We used a combination of real-time microscopy, single cell tracking, polarity quantification, and mosaic analysis to study the cell behaviors that result from chemoFGFR induction. The picture that emerges from these analyses is that de novo organs form through a genetically encoded self-assembly process that is based on the pattern of chemoFGFR induction. In this scenario, cells expressing chemoFGFR aggregate into clusters and epithelialize as they sort out of non-expressing cells. We found that this sorting process occurs through cell rearrangement and slithering, which involves an extensive remodeling of the cell-cell contacts. Chain cells that do not express chemoFGFR can envelop these chemoFGFR expressing cell clusters and form a rim at the cluster periphery. This multi-stage process leads to the establishment of the inside-outside pattern of de novo organs, which is used as a blueprint for cell differentiation. In summary, in this study we provide insights into the mechanisms involved in the self-assembly of organs from a naïve population of progenitor cells

Discovery of non-directional and directional pioneer transcription factors by modeling DNase profile magnitude and shape

Here we describe Protein Interaction Quantitation (PIQ), a computational method that models the magnitude and shape of genome-wide DNase profiles to facilitate the identification of transcription factor (TF) binding sites. Through the use of machine learning techniques, PIQ identified binding sites for >700 TFs from one DNase-seq experiment with accuracy comparable to ChIP-seq for motif-associated TFs (median AUC=0.93 across 303 TFs). We applied PIQ to analyze DNase-seq data from mouse embryonic stem cells differentiating into pre-pancreatic and intestinal endoderm. We identified (n=120) and experimentally validated eight ‘pioneer’ TF families that dynamically open chromatin, enabling other TFs to bind to adjacent DNA. Four pioneer TF families only open chromatin in one direction from their motifs. Furthermore, we identified a class of ‘settler’ TFs whose genomic binding is principally governed by proximity to open chromatin. Our results support a model of hierarchical TF binding in which directional and non-directional pioneer activity shapes the chromatin landscape for population by settler TFs

TCR Signaling Emerges from the Sum of Many Parts

“How does T cell receptor signaling begin?” Answering this question requires an understanding of how the parts of the molecular machinery that mediates this process fit and work together. Ultimately this molecular architecture must (i) trigger the relay of information from the TCR-pMHC interface to the signaling substrates of the CD3 molecules and (ii) bring the kinases that modify these substrates in close proximity to interact, initiate, and sustain signaling. In this contribution we will discuss advances of the last decade that have increased our understanding of the complex machinery and interactions that underlie this type of signaling