The genome-wide protein architecture of chromatin that maintains chromosome integrity and gene regulation is ill-defined. Here we use ChIP-exo/seq 1 , 2 to define this structure in Saccharomyces . We identified 21 ensembles consisting of ~400 different proteins related to DNA replication, centromeres, subtelomeres, transposons, and RNA polymerase (Pol) I, II, and III transcription. Replication proteins engulfed a nucleosome, centromeres lacked a nucleosome, and repressive proteins encompassed three nucleosomes at subtelomeric X-elements. We find that most Pol II promoters evolved to lack a regulatory region, having only a core promoter. These constitutive promoters comprised a short nucleosome-free region (NFR) adjacent to a +1 nucleosome, which together bound TFIID to form a preinitiation complex (PIC). Positioned insulators protected core promoters from upstream events. A small fraction of promoters were architected for inducibility, wherein sequence-specific transcription factors (TFs) create a nucleosome-depleted region (NDR) that is distinct from NFRs. We describe TF structural interactions with the genome and cognate cofactors, including nucleosomal and transcriptional regulators RPD3-L, SAGA, NuA4, Tup1, Mediator, and SWI-SNF. Surprisingly, we do not detect TF-TFIID interactions, suggesting that they do not stably occur. Our model for gene induction involves TFs, cofactors, and general factors like TBP and TFIIB, but not TFIID. However, constitutive transcription involves TFIID but not TFs and cofactors. From this we define a highly integrated network of TF-regulated transcription.

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.

51Antibodies offer a powerful means to interrogate specific proteins in a complex milieu, 52 and where epitope tagging is impractical. However, antibody availability and reliability are 53 problematic. The Protein Capture Reagents Program (PCRP) generated over a thousand 54 renewable monoclonal antibodies against human-presumptive chromatin proteins in an effort to 55 improve reliability. However, these reagents have not been widely field-tested. We therefore 56 screened their ability in a variety of assays. 887 unique antibodies against 681 unique chromatin 57 proteins, of which 605 are putative sequence-specific transcription factors (TFs), were assayed 58 by ChIP-exo. Subsets were further tested in ChIP-seq, CUT&RUN, STORM super-resolution 59 microscopy, immunoblots, and protein binding microarray (PBM) experiments. At least 6% of 60 the tested antibodies were validated for use in ChIP-based assays by the most stringent of our 61criteria. An additional 34% produced data suggesting they warranted further testing for clearer 62 validation. We demonstrate and discuss the metrics and limitations to antibody validation in 63 chromatin-based assays. 64 65

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 challenge as high-throughput sequencing data is generated at an unprecedented pace. Here we report on our 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 wet bench, while continuing to fully support reproducibility and reliability for bioinformaticians through integration with the Galaxy platform.

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

Regulatory proteins can employ multiple direct and indirect modes of interaction with the genome. The ChIP-exo mixture model (ChExMix) provides a principled approach to detecting multiple protein-DNA interaction modes in a single ChIP-exo experiment. ChExMix discovers and characterizes binding event subtypes in ChIP-exo data by leveraging both protein-DNA cross-linking signatures and DNA motifs. In this study, we present a summary of the major features and applications of ChExMix. We demonstrate that ChExMix does not require high-resolution protein-DNA binding assay data to detect binding event subtypes. Specifically, we apply ChExMix to analyze 393 ChIP-seq data profiles in K562 cells. Similar binding event subtypes are discovered across multiple proteins, suggesting the existence of colocalized regulatory protein modules that are recruited to DNA through a particular sequence-specific transcription factor. Our results thus suggest that ChExMix can characterize protein-DNA binding interaction modes using data from multiple types of protein-DNA interaction assays.

Genome browsers have become an intuitive and critical tool to visualize and analyze genomic features and data. Conventional genome browsers display data/annotations on a single reference genome/assembly; there are also genomic alignment viewer/browsers that help users visualize alignment, mismatch, and rearrangement between syntenic regions. However, there is a growing need for a comparative epigenome browser that can display genomic and epigenomic datasets across different species and enable users to compare them between syntenic regions. Here, we present the WashU Comparative Epigenome Browser. It allows users to load functional genomic datasets/annotations mapped to different genomes and display them over syntenic regions simultaneously. The browser also displays genetic differences between the genomes from single nucleotide variants (SNVs) to structural variants (SVs) to visualize the association between epigenomic differences and genetic differences. Instead of anchoring all datasets to the reference genome coordinates, it creates independent coordinates of different genome assemblies to faithfully present features and data mapped to different genomes. It uses a simple, intuitive genome-align track to illustrate the syntenic relationship between different species. It extends the widely used WashU Epigenome Browser infrastructure and can be expanded to support multiple species. This new browser function will greatly facilitate comparative genomic/epigenomic research, as well as support the recent growing needs to directly compare and benchmark the T2T CHM13 assembly and other human genome assemblies.

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.