CAGE peaks enriched in each of the 15 anatomical regions included in the study

For each peak we report the brain region where it is enriched, the corresponding gene symbol (according to rheMac8 Ensembl, and rheMac8 and hg38 projected RefSeq), normalized expression and enrichment score in the region of enrichment

Annotation of the CAGE peaks identified in the study with respect to CpG islands, TATA-box and repeats

For each of the macaque CAGE peaks identified in this study, we report whether they overlap a CpG island, if a TATA-box is present in their neighborhood and whether they overlap a repetitive element (in case of overlap with repeats, the family and class of the element overlapped are reported). NA indicates that there is no overlap for the corresponding feature

Genomic view of selected genes for comparison between manual and automation methods.

<p>CAGE mapped read counts were displayed as linear scale histogram on ACTB (A) and GAPDH (B) genes. The transcription initiation regions are magnified to demonstrate the tag density distribution is consistent between manual and automated libraries. Green and purple indicate plus and minus strands, respectively.</p

JQ1 affects BRD2-dependent and independent transcription regulation without disrupting H4-hyperacetylated chromatin states

<p>The bromodomain and extra-terminal domain (BET) proteins are promising drug targets for cancer and immune diseases. However, BET inhibition effects have been studied more in the context of bromodomain-containing protein 4 (BRD4) than BRD2, and the BET protein association to histone H4-hyperacetylated chromatin is not understood at the genome-wide level. Here, we report transcription start site (TSS)-resolution integrative analyses of ChIP-seq and transcriptome profiles in human non-small cell lung cancer (NSCLC) cell line H23. We show that di-acetylation at K5 and K8 of histone H4 (H4K5acK8ac) co-localizes with H3K27ac and BRD2 in the majority of active enhancers and promoters, where BRD2 has a stronger association with H4K5acK8ac than H3K27ac. Although BET inhibition by JQ1 led to complete reduction of BRD2 binding to chromatin, only local changes of H4K5acK8ac levels were observed, suggesting that recruitment of BRD2 does not influence global histone H4 hyperacetylation levels. This finding supports a model in which recruitment of BET proteins via histone H4 hyperacetylation is predominant over hyperacetylation of histone H4 by BET protein-associated acetyltransferases. In addition, we found that a remarkable number of BRD2-bound genes, including MYC and its downstream target genes, were transcriptionally upregulated upon JQ1 treatment. Using BRD2-enriched sites and transcriptional activity analysis, we identified candidate transcription factors potentially involved in the JQ1 response in BRD2-dependent and -independent manner.</p

Representative scatter plots demonstrating reproducibility between manual and automated workflows and reproducibility within batches and between batches using automation.

<p>A–C: shows scatterplots of TPM normalized gene expression for A, two technical replicates in the same batch; B: between technical replicates from different batches and; C: between manually and automatically prepared technical replicates. Finally D: shows the average correlation coefficient when comparing multiple replicates from automation and manual libraries. Error bars indicate the standard deviation.</p

Evaluation of replicate THP-1 CAGE libraries.

<p>The quality control values for all replicate THP-1 CAGE libraries and sequencing/mapping evaluation are listed. All values are averages with standard deviations. The Ct values of ACTB and 18S rRNA are representatives of non-capped and capped transcripts. The primers were designed at near 5′ end of each transcript. The promoter ratio and rRNA ratio are the rates of reads mapped at 5′ end per total filtered reads. The detail information is shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0030809#pone.0030809.s005" target="_blank">Table S2</a>.</p

Additional file 1 of Defining super-enhancers by highly ranked histone H4 multi-acetylation levels identifies transcription factors associated with glioblastoma stem-like properties

Additional file 1: Figure S1. Identification of regions that bind H4K5acK8ac preferentially over H3K27ac. Figure S2. Effect of JQ1 on genome-wide enrichment of BRD4, H3K27ac, and H4K5acK8ac across glial cell lines. Figure S3. Effect of H4K5acK8ac level in regulatory elements on changes in gene expression upon JQ1 treatment in three glial cell lines. Figure S4. Effect of JQ1 on specific genes and various biological pathways and molecular functions across the three glial cell lines. Figure S5. Defining super-enhancers (SEs) by H4K5acK8ac enrichment ranking in 0316-GSC, U87, and C13NJ cells. Figure S6. CRISPR-Cas9–mediated genome editing strategy of H4K5acK8ac-preferred super-enhancers (SEs) in 0316-GSC cells. Figure S7. CRISPR-Cas9–mediated genome editing of HOXA7 super-enhancers (SEs) in 0316-GSC cells. Figure S8. CRISPR-Cas9–mediated genome editing of H3K27ac-preferred super-enhancers (SEs) in 0316-GSC cells. Figure S9. Source data for cropped gel images

Additional file 2 of Defining super-enhancers by highly ranked histone H4 multi-acetylation levels identifies transcription factors associated with glioblastoma stem-like properties

Additional file 2: Table S1. Pairwise interactions among ChIP-seq peaks across three cell lines (Excel). Table S2. H4K5acK8ac- and H3K27ac-preferred promoters and enhancers that were differentially expressed upon JQ1 treatment in 0316-GSC cells (Excel). Table S3. Gene set enrichment analysis of genes differentially expressed between JQ1 and DMSO (vehicle control) treatment in three cell lines (Excel). Table S4. Cellular and molecular categorization of genes with H4K5acK8ac- or H3K27ac-preferred promoters or SEs in 0316-GSC cells (Excel). Table S5. Genes associated with H4K5acK8ac- and H3K27ac-preferred SEs across the three cell lines (Excel). Table S6. List of all primers and gRNAs used in this study (Excel)

Systematic analysis of transcription start sites in avian development

<div><p>Cap Analysis of Gene Expression (CAGE) in combination with single-molecule sequencing technology allows precision mapping of transcription start sites (TSSs) and genome-wide capture of promoter activities in differentiated and steady state cell populations. Much less is known about whether TSS profiling can characterize diverse and non-steady state cell populations, such as the approximately 400 transitory and heterogeneous cell types that arise during ontogeny of vertebrate animals. To gain such insight, we used the chick model and performed CAGE-based TSS analysis on embryonic samples covering the full 3-week developmental period. In total, 31,863 robust TSS peaks (>1 tag per million [TPM]) were mapped to the latest chicken genome assembly, of which 34% to 46% were active in any given developmental stage. ZENBU, a web-based, open-source platform, was used for interactive data exploration. TSSs of genes critical for lineage differentiation could be precisely mapped and their activities tracked throughout development, suggesting that non-steady state and heterogeneous cell populations are amenable to CAGE-based transcriptional analysis. Our study also uncovered a large set of extremely stable housekeeping TSSs and many novel stage-specific ones. We furthermore demonstrated that TSS mapping could expedite motif-based promoter analysis for regulatory modules associated with stage-specific and housekeeping genes. Finally, using <i>Brachyury</i> as an example, we provide evidence that precise TSS mapping in combination with Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)-on technology enables us, for the first time, to efficiently target endogenous avian genes for transcriptional activation. Taken together, our results represent the first report of genome-wide TSS mapping in birds and the first systematic developmental TSS analysis in any amniote species (birds and mammals). By facilitating promoter-based molecular analysis and genetic manipulation, our work also underscores the value of avian models in unravelling the complex regulatory mechanism of cell lineage specification during amniote development.</p></div

Expression profiles of stage- and cell type–specific transcription start sites (TSSs).

<p>Cap Analysis of Gene Expression (CAGE) TSSs associated with pluripotency and germ layer–specific genes show distinct expression patterns during development. Pluripotency-related genes (<i>NANOG</i>, <i>POU5F3</i>, <i>MYC</i>, <i>EOMES</i>) show early stage–specific expression. Ectoderm-, mesoderm-, and endoderm-related genes show opposite expression patterns, being activated at later stages of development. X-axis represents developmental stages; y-axis represents tag per million (TPM) expression values on a logarithmic scale. Numerical values for this plot can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2002887#pbio.2002887.s022" target="_blank">S1 Data</a>.</p