GenoPipe: identifying the genotype of origin within (epi)genomic datasets.

Confidence in experimental results is critical for discovery. As the scale of data generation in genomics has grown exponentially, experimental error has likely kept pace despite the best efforts of many laboratories. Technical mistakes can and do occur at nearly every stage of a genomics assay (i.e. cell line contamination, reagent swapping, tube mislabelling, etc.) and are often difficult to identify post-execution. However, the DNA sequenced in genomic experiments contains certain markers (e.g. indels) encoded within and can often be ascertained forensically from experimental datasets. We developed the Genotype validation Pipeline (GenoPipe), a suite of heuristic tools that operate together directly on raw and aligned sequencing data from individual high-throughput sequencing experiments to characterize the underlying genome of the source material. We demonstrate how GenoPipe validates and rescues erroneously annotated experiments by identifying unique markers inherent to an organism's genome (i.e. epitope insertions, gene deletions and SNPs).

Joint sequence & chromatin neural networks characterize the differential abilities of Forkhead transcription factors to engage inaccessible chromatin.

The DNA-binding activities of transcription factors (TFs) are influenced by both intrinsic sequence preferences and extrinsic interactions with cell-specific chromatin landscapes and other regulatory proteins. Disentangling the roles of these binding determinants remains challenging. For example, the FoxA subfamily of Forkhead domain (Fox) TFs are known pioneer factors that can bind to relatively inaccessible sites during development. Yet FoxA TF binding also varies across cell types, pointing to a combination of intrinsic and extrinsic forces guiding their binding. While other Forkhead domain TFs are often assumed to have pioneering abilities, how sequence and chromatin features influence the binding of related Fox TFs has not been systematically characterized. Here, we present a principled approach to compare the relative contributions of intrinsic DNA sequence preference and cell-specific chromatin environments to a TF's DNA-binding activities. We apply our approach to investigate how a selection of Fox TFs (FoxA1, FoxC1, FoxG1, FoxL2, and FoxP3) vary in their binding specificity. We over-express the selected Fox TFs in mouse embryonic stem cells, which offer a platform to contrast each TF's binding activity within the same preexisting chromatin background. By applying a convolutional neural network to interpret the Fox TF binding patterns, we evaluate how sequence and preexisting chromatin features jointly contribute to induced TF binding. We demonstrate that Fox TFs bind different DNA targets, and drive differential gene expression patterns, even when induced in identical chromatin settings. Despite the association between Forkhead domains and pioneering activities, the selected Fox TFs display a wide range of affinities for preexiting chromatin states. Using sequence and chromatin feature attribution techniques to interpret the neural network predictions, we show that differential sequence preferences combined with differential abilities to engage relatively inaccessible chromatin together explain Fox TF binding patterns at individual sites and genome-wide.

An integrated SAGA and TFIID PIC assembly pathway selective for poised and induced promoters.

Genome-wide, little is understood about how proteins organize at inducible promoters before and after induction and to what extent inducible and constitutive architectures depend on cofactors. We report that sequence-specific transcription factors and their tethered cofactors (e.g., SAGA [Spt-Ada-Gcn5-acetyltransferase], Mediator, TUP, NuA4, SWI/SNF, and RPD3-L) are generally bound to promoters prior to induction ("poised"), rather than recruited upon induction, whereas induction recruits the preinitiation complex (PIC) to DNA. Through depletion and/or deletion experiments, we show that SAGA does not function at constitutive promoters, although a SAGA-independent Gcn5 acetylates +1 nucleosomes there. When inducible promoters are poised, SAGA catalyzes +1 nucleosome acetylation but not PIC assembly. When induced, SAGA catalyzes acetylation, deubiquitylation, and PIC assembly. Surprisingly, SAGA mediates induction by creating a PIC that allows TFIID (transcription factor II-D) to stably associate, rather than creating a completely TFIID-independent PIC, as generally thought. These findings suggest that inducible systems, where present, are integrated with constitutive systems.

PEGR: a flexible management platform for reproducible epigenomic and genomic research.

Reproducibility is a significant challenge in (epi)genomic research due to the complexity of experiments composed of traditional biochemistry and informatics. Recent advances have exacerbated this as high-throughput sequencing data is generated at an unprecedented pace. Here, we report the development of a Platform for Epi-Genomic Research (PEGR), a web-based project management platform that tracks and quality controls experiments from conception to publication-ready figures, compatible with multiple assays and bioinformatic pipelines. It supports rigor and reproducibility for biochemists working at the bench, while fully supporting reproducibility and reliability for bioinformaticians through integration with the Galaxy platform.

Genome-wide promoter assembly in E. coli measured at single-base resolution.

When detected at single-base-pair resolution, the genome-wide location, occupancy level, and structural organization of DNA-binding proteins provide mechanistic insights into genome regulation. Here we use ChIP-exo to provide a near-base-pair resolution view of the epigenomic organization of the Escherichia coli transcription machinery and nucleoid structural proteins at the time when cells are growing exponentially and upon rapid reprogramming (acute heat shock). We examined the site specificity of three sigma factors (RpoD/σ70, RpoH/σ32, and RpoN/σ54), RNA polymerase (RNAP or RpoA, -B, -C), and two nucleoid proteins (Fis and IHF). We suggest that DNA shape at the flanks of cognate motifs helps drive site specificity. We find that although RNAP and sigma factors occupy active cognate promoters, RpoH and RpoN can occupy quiescent promoters without the presence of RNAP. Thus, promoter-bound sigma factors can be triggered to recruit RNAP by a mechanism that is distinct from an obligatory cycle of free sigma binding RNAP followed by promoter binding. These findings add new dimensions to how sigma factors achieve promoter specificity through DNA sequence and shape, and further define mechanistic steps in regulated genome-wide assembly of RNAP at promoters in E. coli.

STENCIL: A web templating engine for visualizing and sharing life science datasets.

The ability to aggregate experimental data analysis and results into a concise and interpretable format is a key step in evaluating the success of an experiment. This critical step determines baselines for reproducibility and is a key requirement for data dissemination. However, in practice it can be difficult to consolidate data analyses that encapsulates the broad range of datatypes available in the life sciences. We present STENCIL, a web templating engine designed to organize, visualize, and enable the sharing of interactive data visualizations. STENCIL leverages a flexible web framework for creating templates to render highly customizable visual front ends. This flexibility enables researchers to render small or large sets of experimental outcomes, producing high-quality downloadable and editable figures that retain their original relationship to the source data. REST API based back ends provide programmatic data access and supports easy data sharing. STENCIL is a lightweight tool that can stream data from Galaxy, a popular bioinformatic analysis web platform. STENCIL has been used to support the analysis and dissemination of two large scale genomic projects containing the complete data analysis for over 2,400 distinct datasets. Code and implementation details are available on GitHub: https://github.com/CEGRcode/stencil.

A ChIP-exo screen of 887 Protein Capture Reagents Program transcription factor antibodies in human cells.

Antibodies offer a powerful means to interrogate specific proteins in a complex milieu. However, antibody availability and reliability can be problematic, whereas epitope tagging can be impractical in many cases. To address these limitations, the Protein Capture Reagents Program (PCRP) generated over a thousand renewable monoclonal antibodies (mAbs) against human presumptive chromatin proteins. However, these reagents have not been widely field-tested. We therefore performed a screen to test their ability to enrich genomic regions via chromatin immunoprecipitation (ChIP) and a variety of orthogonal assays. Eight hundred eighty-seven unique antibodies against 681 unique human transcription factors (TFs) were assayed by ultra-high-resolution ChIP-exo/seq, generating approximately 1200 ChIP-exo data sets, primarily in a single pass in one cell type (K562). Subsets of PCRP mAbs were further tested in ChIP-seq, CUT&RUN, STORM super-resolution microscopy, immunoblots, and protein binding microarray (PBM) experiments. About 5% of the tested antibodies displayed high-confidence target (i.e., cognate antigen) enrichment across at least one assay and are strong candidates for additional validation. An additional 34% produced ChIP-exo data that were distinct from background and thus warrant further testing. The remaining 61% were not substantially different from background, and likely require consideration of a much broader survey of cell types and/or assay optimizations. We show and discuss the metrics and challenges to antibody validation in chromatin-based assays.

A high-resolution protein architecture of the budding yeast genome.

The genome-wide architecture of chromatin-associated proteins that maintains chromosome integrity and gene regulation is not well defined. Here we use chromatin immunoprecipitation, exonuclease digestion and DNA sequencing (ChIP-exo/seq)1,2 to define this architecture in Saccharomyces cerevisiae. We identify 21 meta-assemblages consisting of roughly 400 different proteins that are related to DNA replication, centromeres, subtelomeres, transposons and transcription by RNA polymerase (Pol) I, II and III. Replication proteins engulf a nucleosome, centromeres lack a nucleosome, and repressive proteins encompass three nucleosomes at subtelomeric X-elements. We find that most promoters associated with Pol II evolved to lack a regulatory region, having only a core promoter. These constitutive promoters comprise a short nucleosome-free region (NFR) adjacent to a +1 nucleosome, which together bind the transcription-initiation factor TFIID to form a preinitiation complex. Positioned insulators protect core promoters from upstream events. A small fraction of promoters evolved an architecture for inducibility, whereby sequence-specific transcription factors (ssTFs) create a nucleosome-depleted region (NDR) that is distinct from an NFR. We describe structural interactions among ssTFs, their cognate cofactors and the genome. These interactions include the nucleosomal and transcriptional regulators RPD3-L, SAGA, NuA4, Tup1, Mediator and SWI-SNF. Surprisingly, we do not detect interactions between ssTFs and TFIID, suggesting that such interactions do not stably occur. Our model for gene induction involves ssTFs, cofactors and general factors such as TBP and TFIIB, but not TFIID. By contrast, constitutive transcription involves TFIID but not ssTFs engaged with their cofactors. From this, we define a highly integrated network of gene regulation by ssTFs.

Acute stress drives global repression through two independent RNA polymerase II stalling events in Saccharomyces.

In multicellular eukaryotes, RNA polymerase (Pol) II pauses transcription ~30-50 bp after initiation. While the budding yeast Saccharomyces has its transcription mechanisms mostly conserved with other eukaryotes, it appears to lack this fundamental promoter-proximal pausing. However, we now report that nearly all yeast genes, including constitutive and inducible genes, manifest two distinct transcriptional stall sites that are brought on by acute environmental signaling (e.g., peroxide stress). Pol II first stalls at the pre-initiation stage before promoter clearance, but after DNA melting and factor acquisition, and may involve inhibited dephosphorylation. The second stall occurs at the +2 nucleosome. It acquires most, but not all, elongation factor interactions. Its regulation may include Bur1/Spt4/5. Our results suggest that a double Pol II stall is a mechanism to downregulate essentially all genes in concert.

Universal promoter scanning by Pol II during transcription initiation in Saccharomyces cerevisiae.

BACKGROUND: The majority of eukaryotic promoters utilize multiple transcription start sites (TSSs). How multiple TSSs are specified at individual promoters across eukaryotes is not understood for most species. In Saccharomyces cerevisiae, a pre-initiation complex (PIC) comprised of Pol II and conserved general transcription factors (GTFs) assembles and opens DNA upstream of TSSs. Evidence from model promoters indicates that the PIC scans from upstream to downstream to identify TSSs. Prior results suggest that TSS distributions at promoters where scanning occurs shift in a polar fashion upon alteration in Pol II catalytic activity or GTF function. RESULTS: To determine the extent of promoter scanning across promoter classes in S. cerevisiae, we perturb Pol II catalytic activity and GTF function and analyze their effects on TSS usage genome-wide. We find that alterations to Pol II, TFIIB, or TFIIF function widely alter the initiation landscape consistent with promoter scanning operating at all yeast promoters, regardless of promoter class. Promoter architecture, however, can determine the extent of promoter sensitivity to altered Pol II activity in ways that are predicted by a scanning model. CONCLUSIONS: Our observations coupled with previous data validate key predictions of the scanning model for Pol II initiation in yeast, which we term the shooting gallery. In this model, Pol II catalytic activity and the rate and processivity of Pol II scanning together with promoter sequence determine the distribution of TSSs and their usage.

Characterizing protein-DNA binding event subtypes in ChIP-exo data.

MOTIVATION: Regulatory proteins associate with the genome either by directly binding cognate DNA motifs or via protein-protein interactions with other regulators. Each recruitment mechanism may be associated with distinct motifs and may also result in distinct characteristic patterns in high-resolution protein-DNA binding assays. For example, the ChIP-exo protocol precisely characterizes protein-DNA crosslinking patterns by combining chromatin immunoprecipitation (ChIP) with 5' → 3' exonuclease digestion. Since different regulatory complexes will result in different protein-DNA crosslinking signatures, analysis of ChIP-exo tag enrichment patterns should enable detection of multiple protein-DNA binding modes for a given regulatory protein. However, current ChIP-exo analysis methods either treat all binding events as being of a uniform type or rely on motifs to cluster binding events into subtypes. RESULTS: To systematically detect multiple protein-DNA interaction modes in a single ChIP-exo experiment, we introduce the ChIP-exo mixture model (ChExMix). ChExMix probabilistically models the genomic locations and subtype memberships of binding events using both ChIP-exo tag distribution patterns and DNA motifs. We demonstrate that ChExMix achieves accurate detection and classification of binding event subtypes using in silico mixed ChIP-exo data. We further demonstrate the unique analysis abilities of ChExMix using a collection of ChIP-exo experiments that profile the binding of key transcription factors in MCF-7 cells. In these data, ChExMix identifies possible recruitment mechanisms of FoxA1 and ERα, thus demonstrating that ChExMix can effectively stratify ChIP-exo binding events into biologically meaningful subtypes. AVAILABILITY AND IMPLEMENTATION: ChExMix is available from https://github.com/seqcode/chexmix. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Simplified ChIP-exo assays.

ChIP-seq and ChIP-exo identify where proteins bind along any genome in vivo. Although ChIP-seq is widely adopted in academic research, it has inherently high noise. In contrast, ChIP-exo has relatively low noise and achieves near-base pair resolution. Consequently, and unlike other genomic assays, ChIP-exo provides structural information on genome-wide binding proteins. Construction of ChIP-exo libraries is technically difficult. Here we describe greatly simplified ChIP-exo methods, each with use-specific advantages. This is achieved through assay optimization and use of Tn5 tagmentation and/or single-stranded DNA ligation. Greater library yields, lower processing time, and lower costs are achieved. In comparing assays, we reveal substantial limitations in other ChIP-based assays. Importantly, the new ChIP-exo assays allow high-resolution detection of some protein-DNA interactions in organs and in as few as 27,000 cells. It is suitable for high-throughput parallelization. The simplicity of ChIP-exo now makes it a highly appropriate substitute for ChIP-seq, and for broader adoption.

Genome-wide determinants of sequence-specific DNA binding of general regulatory factors.

General regulatory factors (GRFs), such as Reb1, Abf1, Rap1, Mcm1, and Cbf1, positionally organize yeast chromatin through interactions with a core consensus DNA sequence. It is assumed that sequence recognition via direct base readout suffices for specificity and that spurious nonfunctional sites are rendered inaccessible by chromatin. We tested these assumptions through genome-wide mapping of GRFs in vivo and in purified biochemical systems at near-base pair (bp) resolution using several ChIP-exo-based assays. We find that computationally predicted DNA shape features (e.g., minor groove width, helix twist, base roll, and propeller twist) that are not defined by a unique consensus sequence are embedded in the nonunique portions of GRF motifs and contribute critically to sequence-specific binding. This dual source specificity occurs at GRF sites in promoter regions where chromatin organization starts. Outside of promoter regions, strong consensus sites lack the shape component and consequently lack an intrinsic ability to bind cognate GRFs, without regard to influences from chromatin. However, sites having a weak consensus and low intrinsic affinity do exist in these regions but are rendered inaccessible in a chromatin environment. Thus, GRF site-specificity is achieved through integration of favorable DNA sequence and shape readouts in promoter regions and by chromatin-based exclusion from fortuitous weak sites within gene bodies. This study further revealed a severe G/C nucleotide cross-linking selectivity inherent in all formaldehyde-based ChIP assays, which includes ChIP-seq. However, for most tested proteins, G/C selectivity did not appreciably affect binding site detection, although it does place limits on the quantitativeness of occupancy levels.

Understanding nucleosome dynamics and their links to gene expression and DNA replication.

Advances in genomics technology have provided the means to probe myriad chromatin interactions at unprecedented spatial and temporal resolution. This has led to a profound understanding of nucleosome organization within the genome, revealing that nucleosomes are highly dynamic. Nucleosome dynamics are governed by a complex interplay of histone composition, histone post-translational modifications, nucleosome occupancy and positioning within chromatin, which are influenced by numerous regulatory factors, including general regulatory factors, chromatin remodellers, chaperones and polymerases. It is now known that these dynamics regulate diverse cellular processes ranging from gene transcription to DNA replication and repair.

Genome-wide uniformity of human 'open' pre-initiation complexes.

Transcription of protein-coding and noncoding DNA occurs pervasively throughout the mammalian genome. Their sites of initiation are generally inferred from transcript 5' ends and are thought to be either locally dispersed or focused. How these two modes of initiation relate is unclear. Here, we apply permanganate treatment and chromatin immunoprecipitation (PIP-seq) of initiation factors to identify the precise location of melted DNA separately associated with the preinitiation complex (PIC) and the adjacent paused complex (PC). This approach revealed the two known modes of transcription initiation. However, in contrast to prevailing views, they co-occurred within the same promoter region: initiation originating from a focused PIC, and broad nucleosome-linked initiation. PIP-seq allowed transcriptional orientation of Pol II to be determined, which may be useful near promoters where sufficient sense/anti-sense transcript mapping information is lacking. PIP-seq detected divergently oriented Pol II at both coding and noncoding promoters, as well as at enhancers. Their occupancy levels were not necessarily coupled in the two orientations. DNA sequence and shape analysis of initiation complex sites suggest that both sequence and shape contribute to specificity, but in a context-restricted manner. That is, initiation sites have the locally "best" initiator (INR) sequence and/or shape. These findings reveal a common core to pervasive Pol II initiation throughout the human genome.

Iron-responsive chromatin remodelling and MAPK signalling enhance adhesion in Candida albicans.

Recent cumulative data show that various transcription factors are recruited to the chromatin in an iron-responsive manner to affect diverse cellular functions in the pathogenic fungus Candida albicans. Here we identified groups of iron-responsive genes in C. albicans by chromatin remodelling analysis at gene promoters, using micrococcal nuclease (MNase) digestion followed by deep sequencing. Chromatin in the promoter regions of iron uptake and utilization genes showed repressed and active configuration, respectively, under iron-replete conditions. GO Term enrichment analysis of genes with differentially remodelled chromatin, in respective promoter locales, suggested that many genes involved in adhesion are also iron-responsive. C. albicans was observed to be more self-adherent (twofold increase) and formed higher biofilm mass (77% increase) in the presence of iron. Furthermore, we identified various known and novel adhesion-related genes with iron-dependent active chromatin profiles that are indicative of potential upregulation under iron-replete conditions. Transcription factor Cph1 that is activated upon Cek1 phosphorylation also showed an active chromatin profile under iron-replete conditions and cells showed iron-responsive Cek1 MAPK phosphorylation in the presence of iron. Thus, iron affects diverse biological functions by modulating chromatin profiles of large gene sets and by signalling through Cek1 MAPK in C. albicans.

An integrative approach to understanding the combinatorial histone code at functional elements.

SUMMARY: The rapid advancement of genomic technology has revealed the enormous complexity and combinatorial nature of chromatin modifications. To facilitate interpretation of the combinatorial nature of chromatin, we have developed a novel method to integrate all chromatin datasets into distinct nucleosome types (nucleosome alphabet). We have applied this approach to Saccharomyces cerevisiae, generating a nucleosome alphabet, which forms chromatin motifs when mapped back to the genome. By applying novel chromatin alignment and global word search approaches, we have defined distinctive chromatin motifs for introns, origins of replication, tRNAs, antisense transcripts, double-strand-break hotspots and DNase hypersensitive sites, and can distinguish genes by expression level. We have also uncovered strong associations between transcription factor binding and specific types of nucleosomes. Our results demonstrate the uses and functionality of defining a chromatin alphabet and provide a unique and novel framework for exploring chromatin architecture. CONTACT: mjbuck@buffalo.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Chromatin architectures at fission yeast transcriptional promoters and replication origins.

We have used micrococcal nuclease (MNase) digestion followed by deep sequencing in order to obtain a higher resolution map than previously available of nucleosome positions in the fission yeast, Schizosaccharomyces pombe. Our data confirm an unusually short average nucleosome repeat length, ∼152 bp, in fission yeast and that transcriptional start sites (TSSs) are associated with nucleosome-depleted regions (NDRs), ordered nucleosome arrays downstream and less regularly spaced upstream nucleosomes. In addition, we found enrichments for associated function in four of eight groups of genes clustered according to chromatin configurations near TSSs. At replication origins, our data revealed asymmetric localization of pre-replication complex (pre-RC) proteins within large NDRs-a feature that is conserved in fission and budding yeast and is therefore likely to be conserved in other eukaryotic organisms.

ArchTEx: accurate extraction and visualization of next-generation sequence data.

MOTIVATION: The extension of mapped sequence tags is a common step in the analysis of single-end next-generation sequencing (NGS) data from protein localization and chromatin studies. The optimal extension can vary depending on experimental and technical conditions. Improper extension of sequence tags can obscure or mislead the interpretation of NGS results. We present an algorithm, ArchTEx (Architectural Tag Extender), which identifies the optimal extension of sequence tags based on the maximum correlation between forward and reverse tags and extracts and visualizes sites of interest using the predicted extension. AVAILABILITY AND IMPLEMENTATION: ArchTEx requires Java 1.6 or newer. Source code and the compiled program are freely available at http://sourceforge.net/projects/archtex/ CONTACT: mjbuck@buffalo.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.