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Background The analysis of chromatin binding patterns of proteins in different biological states is a main application of chromatin immunoprecipitation followed by sequencing (ChIP-seq). A large number of algorithms and computational tools for quantitative comparison of ChIP-seq datasets exist, but their performance is strongly dependent on the parameters of the biological system under investigation. Thus, a systematic assessment of available computational tools for differential ChIP-seq analysis is required to guide the optimal selection of analysis tools based on the present biological scenario. Results We created standardized reference datasets by in silico simulation and sub-sampling of genuine ChIP-seq data to represent different biological scenarios and binding profiles. Using these data, we evaluated the performance of 33 computational tools and approaches for differential ChIP-seq analysis. Tool performance was strongly dependent on peak size and shape as well as on the scenario of biological regulation. Conclusions Our analysis provides unbiased guidelines for the optimized choice of software tools in differential ChIP-seq analysis.

Summary The first gapless, telomere‐to‐telomere (T2T) sequence assemblies of plant chromosomes were reported recently. However, sequence assemblies of most plant genomes remain fragmented. Only recent breakthroughs in accurate long‐read sequencing have made it possible to achieve highly contiguous sequence assemblies with a few tens of contigs per chromosome, that is a number small enough to allow for a systematic inquiry into the causes of the remaining sequence gaps and the approaches and resources needed to close them. Here, we analyse sequence gaps in the current reference genome sequence of barley cv. Morex (MorexV3). Optical map and sequence raw data, complemented by ChIP‐seq data for centromeric histone variant CENH3, were used to estimate the abundance of centromeric, ribosomal DNA, and subtelomeric repeats in the barley genome. These estimates were compared with copy numbers in the MorexV3 pseudomolecule sequence. We found that almost all centromeric sequences and 45S ribosomal DNA repeat arrays were absent from the MorexV3 pseudomolecules and that the majority of sequence gaps can be attributed to assembly breakdown in long stretches of satellite repeats. However, missing sequences cannot fully account for the difference between assembly size and flow cytometric genome size estimates. We discuss the prospects of gap closure with ultra‐long sequence reads.

We used ChIP‐Seq to map ERα‐binding sites and to profile changes in RNA polymerase II (RNAPII) occupancy in MCF‐7 cells in response to estradiol (E2), tamoxifen or fulvestrant. We identify 10 205 high confidence ERα‐binding sites in response to E2 of which 68% contain an estrogen response element (ERE) and only 7% contain a FOXA1 motif. Remarkably, 596 genes change significantly in RNAPII occupancy (59% up and 41% down) already after 1 h of E2 exposure. Although promoter proximal enrichment of RNAPII (PPEP) occurs frequently in MCF‐7 cells (17%), it is only observed on a minority of E2‐regulated genes (4%). Tamoxifen and fulvestrant partially reduce ERα DNA binding and prevent RNAPII loading on the promoter and coding body on E2‐upregulated genes. Both ligands act differently on E2‐downregulated genes: tamoxifen acts as an agonist thus downregulating these genes, whereas fulvestrant antagonizes E2‐induced repression and often increases RNAPII occupancy. Furthermore, our data identify genes preferentially regulated by tamoxifen but not by E2 or fulvestrant. Thus (partial) antagonist loaded ERα acts mechanistically different on E2‐activated and E2‐repressed genes.

Summary FOXO transcription factors (FOXOs) are central regulators of lifespan across species, yet they also have cell-specific functions, including adult stem cell homeostasis and immune function. Direct targets of FOXOs have been identified genome-wide in several species and cell types. However, whether FOXO targets are specific to cell types and species or conserved across cell types and throughout evolution remains uncharacterized. Here, we perform a meta-analysis of direct FOXO targets across tissues and organisms, using data from mammals as well as Caenorhabditis elegans and Drosophila. We show that FOXOs bind cell type-specific targets, which have functions related to that particular cell. Interestingly, FOXOs also share targets across different tissues in mammals, and the function and even the identity of these shared mammalian targets are conserved in invertebrates. Evolutionarily conserved targets show enrichment for growth factor signaling, metabolism, stress resistance, and proteostasis, suggesting an ancestral, conserved role in the regulation of these processes. We also identify candidate cofactors at conserved FOXO targets that change in expression with age, including CREB and ETS family factors. This meta-analysis provides insight into the evolution of the FOXO network and highlights downstream genes and cofactors that may be particularly important for FOXO's conserved function in adult homeostasis and longevity.

Wood-degrading fungi in the phylum Basidiomycota play a crucial role in nutrient recycling by breaking down all components of wood. Fungi have evolved transcriptional networks that regulate expression of wood-degrading enzymes, allowing them to prioritize one nutrient source over another. Wood-decaying fungi of the class Agaricomycetes (phylum Basidiomycota) are saprotrophs that break down lignocellulose and play an important role in nutrient recycling. They secrete a wide range of extracellular plant cell wall degrading enzymes that break down cellulose, hemicellulose, and lignin, the main building blocks of plant biomass. Although the production of these enzymes is regulated mainly at the transcriptional level, no activating regulators have been identified in any wood-decaying fungus in the class Agaricomycetes. We studied the regulation of cellulase expression in the wood-decaying fungus Schizophyllum commune . Comparative genomics and transcriptomics on two wild isolates revealed a Zn 2 Cys 6 -type transcription factor gene ( roc1 ) that was highly upregulated during growth on cellulose, compared to glucose. It is only conserved in the class Agaricomycetes. A roc1 knockout strain showed an inability to grow on medium with cellulose as sole carbon source, and growth on cellobiose and xylan (other components of wood) was inhibited. Growth on non-wood-related carbon sources was not inhibited. Cellulase gene expression and enzyme activity were reduced in the Δ roc1 strain. ChIP-Seq identified 1474 binding sites of the Roc1 transcription factor. Promoters of genes involved in lignocellulose degradation were enriched with these binding sites, especially those of LPMO (lytic polysaccharide monooxygenase) CAZymes, indicating that Roc1 directly regulates these genes. A conserved motif was identified as the binding site of Roc1, which was confirmed by a functional promoter analysis. Together, Roc1 is a key regulator of cellulose degradation and the first identified in wood-decaying fungi in the phylum Basidiomycota. IMPORTANCE Wood-degrading fungi in the phylum Basidiomycota play a crucial role in nutrient recycling by breaking down all components of wood. Fungi have evolved transcriptional networks that regulate expression of wood-degrading enzymes, allowing them to prioritize one nutrient source over another. However, to date all these transcription factors have been identified in the phylum Ascomycota, which is only distantly related to the phylum Basidiomycota. Here, we identified the transcription factor Roc1 as a key regulator of cellulose degradation in the mushroom-forming and wood-degrading fungus Schizophyllum commune . Roc1 is highly conserved in the phylum Basidiomycota. Using comparative genomics, transcriptomics, ChIP-Seq and promoter analysis we have identified direct targets of Roc1, as well as other aspects of the transcriptional response to cellulose.

Members of the large ETS family of transcription factors (TFs) have highly similar DNA‐binding domains (DBDs)—yet they have diverse functions and activities in physiology and oncogenesis. Some differences in DNA‐binding preferences within this family have been described, but they have not been analysed systematically, and their contributions to targeting remain largely uncharacterized. We report here the DNA‐binding profiles for all human and mouse ETS factors, which we generated using two different methods: a high‐throughput microwell‐based TF DNA‐binding specificity assay, and protein‐binding microarrays (PBMs). Both approaches reveal that the ETS‐binding profiles cluster into four distinct classes, and that all ETS factors linked to cancer, ERG, ETV1, ETV4 and FLI1, fall into just one of these classes. We identify amino‐acid residues that are critical for the differences in specificity between all the classes, and confirm the specificities in vivo using chromatin immunoprecipitation followed by sequencing (ChIP‐seq) for a member of each class. The results indicate that even relatively small differences in in vitro binding specificity of a TF contribute to site selectivity in vivo.

Skeletal muscle differentiation is orchestrated by a network of transcription factors, epigenetic regulators, and non‐coding RNAs. The transcription factor Yin Yang 1 (YY1) silences multiple target genes in myoblasts (MBs) by recruiting Ezh2 (Enhancer of Zeste Homologue2). To elucidate genome‐wide YY1 binding in MBs, we performed chromatin immunoprecipitation (ChIP)‐seq and found 1820 specific binding sites in MBs with a large portion residing in intergenic regions. Detailed analysis demonstrated that YY1 acts as an activator for many loci in addition to its known repressor function. No significant co‐occupancy was found between YY1 and Ezh2, suggesting an additional Ezh2‐independent function for YY1 in MBs. Further analysis of intergenic binding sites showed that YY1 potentially regulates dozens of large intergenic non‐coding RNAs (lincRNAs), whose function in myogenesis is underexplored. We characterized a novel muscle‐associated lincRNA (Yam‐1) that is positively regulated by YY1. Yam‐1 is downregulated upon differentiation and acts as an inhibitor of myogenesis. We demonstrated that Yam‐1 functions through in cis regulation of miR‐715, which in turn targets Wnt7b. Our findings not only provide the first genome‐wide picture of YY1 association in muscle cells, but also uncover the functional role of lincRNA Yam‐1. In addition to its role in gene silencing, the transcription factor YY1 can act as a positive regulator of numerous intergenic long non‐coding RNAs in myoblasts. One of these lncRNAs, Yam‐1, inhibits myogenesis by reducing miR‐715 levels in cis .

Adipogenesis is tightly controlled by a complex network of transcription factors acting at different stages of differentiation. Peroxisome proliferator‐activated receptor γ (PPARγ) and CCAAT/enhancer‐binding protein (C/EBP) family members are key regulators of this process. We have employed DNase I hypersensitive site analysis to investigate the genome‐wide changes in chromatin structure that accompany the binding of adipogenic transcription factors. These analyses revealed a dramatic and dynamic modulation of the chromatin landscape during the first hours of adipocyte differentiation that coincides with cooperative binding of multiple early transcription factors (including glucocorticoid receptor, retinoid X receptor, Stat5a, C/EBPβ and ‐δ) to transcription factor ‘hotspots’. Our results demonstrate that C/EBPβ marks a large number of these transcription factor ‘hotspots’ before induction of differentiation and chromatin remodelling and is required for their establishment. Furthermore, a subset of early remodelled C/EBP‐binding sites persists throughout differentiation and is later occupied by PPARγ, indicating that early C/EBP family members, in addition to their well‐established role in activation of PPARγ transcription, may act as pioneering factors for PPARγ binding. Adipogenesis is a tightly controlled differentiation process regulated by a complex transcriptional network. Here, DNase I hypersensitive site analysis, DHSseq, reveals the genome‐wide changes in chromatin structure that occur during adipogenesis and identifies sites that are bound by multiple transcription factors.

Vernalization, the requirement of plants for long-term exposure to low environmental temperature for flowering, is an epigenetic phenomenon. Histone modification regulation has been revealed in vernalization, but is limited to key genes. Now, we know that VRN1 is epigenetically critical for monocots. Genome-wide analysis is still unavailable, however. We performed chromatin immunoprecipitation-sequencing for H3K4me3/H3K27me3 in Brachypodium distachyon to obtain a global view of histone modifications in vernalization on a genome-wide scale and for different pathways/genes. Our data showed that H3K4me3 and H3K27me3 play distinct roles in vernalization. Unlike H3K4me3, H3K27me3 exhibited regional regulation, showed main regulation targets in vernalization and contributed to epigenetic memory. For genes in four flowering regulation pathways, only FT2(functional ortholog of VRN3 in B. distachyon) and VRN1 showed coordinated changes in H3K4me3/H3K27me3. The epigenetic response at VRN3 was weaker under short-day than under long-day conditions. VRN3 was revealed as an epigenetic regulation point integrating vernalization and day length signals. We globally identified genes maintaining vernalization-induced epigenetic changes. Most of these genes showed dose-dependent vernalization responses, revealing a quantitative ‘recording system’ for vernalization. Our studies shed light on the epigenetic role of VRN3 and H3K4me3/H3K27me3 in vernalization and reveal genes underlying epigenetic memory, laying the foundation for further study.

The expression level of a gene is often used as a proxy for determining whether the protein or RNA product is functional in a cell or tissue. Therefore, it is of fundamental importance to understand the global distribution of gene expression levels, and to be able to interpret it mechanistically and functionally. Here we use RNA sequencing (RNA‐seq) of mouse Th2 cells, coupled with a range of other techniques, to show that all genes can be separated, based on their expression abundance, into two distinct groups: one group comprised of lowly expressed and putatively non‐functional mRNAs, and the other of highly expressed mRNAs with active chromatin marks at their promoters. These observations are confirmed in many other microarray and RNA‐seq data sets of metazoan cell types. The authors show that genes can be separated into distinct low or high expression abundance groups. Histone marks reveal that this switch‐like transition from low to high expression goes hand‐in‐hand with a change in chromatin status.