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1.
Genome Biol ; 23(1): 99, 2022 04 19.
Artigo em Inglês | MEDLINE | ID: mdl-35440038

RESUMO

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.


Assuntos
Epigenômica , Genômica , Biologia Computacional , Genoma , Reprodutibilidade dos Testes , Software
2.
PLoS Comput Biol ; 18(2): e1009859, 2022 02.
Artigo em Inglês | MEDLINE | ID: mdl-35139076

RESUMO

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.


Assuntos
Genômica , Software , Biologia Computacional , Genômica/métodos , Disseminação de Informação , Internet , Reprodutibilidade dos Testes
3.
Genome Res ; 31(9): 1663-1679, 2021 09.
Artigo em Inglês | MEDLINE | ID: mdl-34426512

RESUMO

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.


Assuntos
Sequenciamento de Cromatina por Imunoprecipitação , Fatores de Transcrição , Sítios de Ligação , Imunoprecipitação da Cromatina , Humanos , Indicadores e Reagentes , Reprodutibilidade dos Testes , Fatores de Transcrição/metabolismo
4.
Nature ; 592(7853): 309-314, 2021 04.
Artigo em Inglês | MEDLINE | ID: mdl-33692541

RESUMO

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.


Assuntos
Proteínas Fúngicas/genética , Proteínas Fúngicas/metabolismo , Genoma Fúngico/genética , Complexos Multiproteicos/genética , Saccharomyces cerevisiae/genética , Saccharomyces cerevisiae/metabolismo , Fatores de Transcrição/genética , Coenzimas/metabolismo , Complexos Multiproteicos/metabolismo , Regiões Promotoras Genéticas , RNA Polimerase I/metabolismo , RNA Polimerase II/metabolismo , RNA Polimerase III/metabolismo , Proteína de Ligação a TATA-Box/genética , Proteína de Ligação a TATA-Box/metabolismo , Fator de Transcrição TFIIB/genética , Fator de Transcrição TFIIB/metabolismo , Fator de Transcrição TFIID , Fatores de Transcrição/metabolismo
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