Picking ChIP-seq peak detectors for analyzing chromatin modification experiments

Numerous algorithms have been developed to analyze ChIP-Seq data. However, the complexity of analyzing diverse patterns of ChIP-Seq signals, especially for epigenetic marks, still calls for the development of new algorithms and objective comparisons of existing methods. We developed Qeseq, an algorithm to detect regions of increased ChIP read density relative to background. Qeseq employs critical novel elements, such as iterative recalibration and neighbor joining of reads to identify enriched regions of any length. To objectively assess its performance relative to other 14 ChIP-Seq peak finders, we designed a novel protocol based on Validation Discriminant Analysis (VDA) to optimally select validation sites and generated two validation datasets, which are the most comprehensive to date for algorithmic benchmarking of key epigenetic marks. In addition, we systematically explored a total of 315 diverse parameter configurations from these algorithms and found that typically optimal parameters in one dataset do not generalize to other datasets. Nevertheless, default parameters show the most stable performance, suggesting that they should be used. This study also provides a reproducible and generalizable methodology for unbiased comparative analysis of high-throughput sequencing tools that can facilitate future algorithmic development

Detecting broad domains and narrow peaks in ChIP-seq data with hiddenDomains

Abstract Background Correctly identifying genomic regions enriched with histone modifications and transcription factors is key to understanding their regulatory and developmental roles. Conceptually, these regions are divided into two categories, narrow peaks and broad domains, and different algorithms are used to identify each one. Datasets that span these two categories are often analyzed with a single program for peak calling combined with an ad hoc method for domains. Results We developed hiddenDomains, which identifies both peaks and domains, and compare it to the leading algorithms using H3K27me3, H3K36me3, GABP, ESR1 and FOXA ChIP-seq datasets. The output from the programs was compared to qPCR-validated enriched and depleted sites, predicted transcription factor binding sites, and highly-transcribed gene bodies. With every method, hiddenDomains, performed as well as, if not better than algorithms dedicated to a specific type of analysis. Conclusions hiddenDomains performs as well as the best domain and peak calling algorithms, making it ideal for analyzing ChIP-seq datasets, especially those that contain a mixture of peaks and domains

Making waves: collaboration in the time of SARS-CoV-2 - rapid development of an international co-operation and wastewater surveillance database to support public health decision-making

The presence of SARS-CoV-2 RNA in wastewater was first reported in March 2020. Over the subsequent months, the potential for wastewater surveillance to contribute to COVID-19 mitigation programmes has been the focus of intense national and international research activities, gaining the attention of policy makers and the public. As a new application of an established methodology, focused collaboration between public health practitioners and wastewater researchers is essential to developing a common understanding on how, when and where the outputs of this non-invasive community-level approach can deliver actionable outcomes for public health authorities. Within this context, the NORMAN SCORE "SARS-CoV-2 in sewage" database provides a platform for rapid, open access data sharing, validated by the uploading of 276 data sets from nine countries to-date. Through offering direct access to underpinning meta-data sets (and describing its use in data interpretation), the NORMAN SCORE database is a resource for the development of recommendations on minimum data requirements for wastewater pathogen surveillance. It is also a tool to engage public health practitioners in discussions on use of the approach, providing an opportunity to build mutual understanding of the demand and supply for data and facilitate the translation of this promising research application into public health practice. [Abstract copyright: Copyright © 2021 Elsevier Ltd. All rights reserved.

The Mammalian Sin3 Proteins Are Required for Muscle Development and Sarcomere Specification▿ †

The highly related mammalian Sin3A and Sin3B proteins provide a versatile platform for chromatin-modifying activities. Sin3-containing complexes play a role in gene repression through deacetylation of nucleosomes. Here, we explore a role for Sin3 in myogenesis by examining the phenotypes resulting from acute somatic deletion of both isoforms in vivo and from primary myotubes in vitro. Myotubes ablated for Sin3A alone, but not Sin3B, displayed gross defects in sarcomere structure that were considerably enhanced upon simultaneous ablation of both isoforms. Massively parallel sequencing of Sin3A- and Sin3B-bound genomic loci revealed a subset of target genes directly involved in sarcomere function that are positively regulated by Sin3A and Sin3B proteins. Both proteins were coordinately recruited to a substantial number of genes. Interestingly, depletion of Sin3B led to compensatory increases in Sin3A recruitment at certain target loci, but Sin3B was never found to compensate for Sin3A loss. Thus, our analyses describe a novel transcriptional role for Sin3A and Sin3B proteins associated with maintenance of differentiated muscle cells

Genome-wide remodeling of the epigenetic landscape during myogenic differentiation

We have examined changes in the chromatin landscape during muscle differentiation by mapping the genome-wide location of ten key histone marks and transcription factors in mouse myoblasts and terminally differentiated myotubes, providing an exceptionally rich dataset that has enabled discovery of key epigenetic changes underlying myogenesis. Using this compendium, we focused on a well-known repressive mark, histone H3 lysine 27 trimethylation, and identified novel regulatory elements flanking the myogenin gene that function as a key differentiation-dependent switch during myogenesis. Next, we examined the role of Polycomb-mediated H3K27 methylation in gene repression by systematically ablating components of both PRC1 and PRC2 complexes. Surprisingly, we found mechanistic differences between transient and permanent repression of muscle differentiation and lineage commitment genes and observed that the loss of PRC1 and PRC2 components produced opposing differentiation defects. These phenotypes illustrate striking differences as compared to embryonic stem cell differentiation and suggest that PRC1 and PRC2 do not operate sequentially in muscle cells. Our studies of PRC1 occupancy also suggested a “fail-safe” mechanism, whereby PRC1/Bmi1 concentrates at genes specifying nonmuscle lineages, helping to retain H3K27me3 in the face of declining Ezh2-mediated methyltransferase activity in differentiated cells

Making Waves: Collaboration in the time of SARS-CoV-2 - rapid development of an international co-operation and wastewater surveillance database to support public health decision-making

The presence of SARS-CoV-2 RNA in wastewater was first reported in March 2020. Over the subsequent months, the potential for wastewater surveillance to contribute to COVID-19 mitigation programmes has been the focus of intense national and international research activities, gaining the attention of policy makers and the public. As a new application of an established methodology, focused collaboration between public health practitioners and wastewater researchers is essential to developing a common understanding on how, when and where the outputs of this non-invasive community-level approach can deliver actionable outcomes for public health authorities. Within this context, the NORMAN SCORE “SARS-CoV-2 in sewage” database provides a platform for rapid, open access data sharing, validated by the uploading of 276 data sets from nine countries to-date. Through offering direct access to underpinning meta-data sets (and describing its use in data interpretation), the NORMAN SCORE database is a resource for the development of recommendations on minimum data requirements for wastewater pathogen surveillance. It is also a tool to engage public health practitioners in discussions on use of the approach, providing an opportunity to build mutual understanding of the demand and supply for data and facilitate the translation of this promising research application into public health practice. © 2021 Elsevier Lt