Histone H4 lysine 20 monomethylation is not a mark of transcriptional silencers

Histone H4 lysine 20 monomethylation is not a mark of transcriptional silencers | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Contradictory Results Histone H4 lysine 20 monomethylation is not a mark of transcriptional silencers Julian A. Segert , View ORCID Profile Martha L. Bulyk doi: https://doi.org/10.1101/2025.01.09.632211 Julian A. Segert 1 Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School , Boston, MA 02115, USA 2 Program in Biological and Biomedical Sciences, Harvard University , Cambridge, MA 02138, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Martha L. Bulyk 1 Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School , Boston, MA 02115, USA 2 Program in Biological and Biomedical Sciences, Harvard University , Cambridge, MA 02138, USA 3 Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School , Boston, MA 02115, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Martha L. Bulyk For correspondence: mlbulyk{at}genetics.med.harvard.edu Abstract Full Text Info/History Metrics Preview PDF Abstract Transcriptional silencers are cis -regulatory elements that downregulate the expression of target genes. Although thousands of silencers have been identified experimentally, a predictive chromatin signature of silencers has not been found. H4K20me1 previously was reported to be highly enriched among human silencers, but our reanalysis of those data using an appropriate background revealed that the enrichment is only marginal. We generated H4K20me1 ChIP-seq profiles in Drosophila S2 cells, which similarly showed that H4K20me1 does not mark Drosophila silencers and instead is associated with active transcription. Silencers remain a poorly annotated, difficult to predict class of cis -regulatory elements whose specific chromatin features remain to be identified. Background Gene transcription is controlled by the combination of several classes of cis -regulatory elements, including promoters and enhancers. In addition to positive regulation, gene expression is controlled by negatively-acting regulatory elements known as transcriptional silencers. Silencers were first identified in Saccharomyces cerevisiae [ 1 ], and several decades later large-scale reporter assays identified large numbers of silencers in Drosophila [ 2 ], human cell lines [ 3 , 4 ], and cell lines and primary retina cells from mouse [ 5 , 6 ] and zebrafish [ 7 ]. While the prevalence and importance of silencers is now appreciated, the number of known silencers is still limited and their locations in the genome are difficult to predict. Enhancers can be predicted by the presence of histone modifications such as H3K27ac [ 8 ] and H3K4me1 [ 9 ], but histone modification(s) indicative of silencers remain unknown. A known chromatin mark of silencers would enable researchers to predict this class of regulatory elements in any model system and cell type by a high-throughput sequencing assay of the chromatin mark ( e.g. , ChIP-seq [ 10 ], CUT&Tag [ 11 ]). Silencers active in Drosophila embryonic mesoderm were found to be significantly enriched for H3K27me3, but this modification was neither sensitive nor specific in distinguishing silencers: many silencers had low levels of mesodermal H3K27me3 and many non-silencers had high levels [ 2 ]. Ngan et al. identified silencers corresponding to chromatin loops bound by PRC2, the complex that deposits H3K27me3 [ 5 ]. Although H3K27me3 is found at many silencers, it is not highly predictive since many silencers are not marked by this modification and large expanses of the genome are covered in broad H3K27me3 domains, making it difficult to identify active silencers from within regions of Polycomb-repressed chromatin. Large-scale screens for silencers (repressive ability of silencer elements or “ReSE”) in human cell lines reported that silencers are significantly enriched for methylated histone H4 lysine 20 (H4K20me) [ 4 ]. The input open chromatin screened by ReSE was obtained by formaldehyde-assisted isolation of regulatory elements (FAIRE) in K562 cells based on the assumption that silencers, like enhancers, are active cis -regulatory elements and therefore reside in open chromatin. The resulting FAIRE chromatin was then cloned into a reporter vector upstream of a toxic caspase 9 selection marker so that only cells with an active silencer survive screens that they then performed in K562 and HepG2 cells. The authors then performed an analysis for co-associated histone modifications using available ENCODE ChIP-seq peaks [ 12 ] and found that H4K20me was the most highly enriched mark in both cell lines [ 4 ], but the exact role of this modification remains unclear. We note that while their study refers to H4K20me generally and does not specify methyl form, the antibody used to generate the ENCODE ChIP-Seq data (Abcam ab9051) primarily detects monomethylation of H4K20me (H4K20me1)). Other studies have found H4K20me1 to be associated with both repressed and actively transcribed chromatin. The mammalian inactive X chromosome is covered by H4K20me1 following binding of the long noncoding RNA Xist that silences the X chromosome, although H4K20me1 was not found to be essential for silencing of genes on the X chromosome [ 13 ]. H4K20me1 is also found on the inactive X chromosome of C. elegans , which uses an orthogonal dosage compensation mechanism whereby expression of each X chromosome in XX animals is reduced by half to match the expression of XO animals. In worms, H4K20me1 is enriched on both X chromosomes by demethylation of H4K20me2 by the demethylase DPY-21 [ 14 ]. While loss of DPY-21 catalytic activity led to derepression and decompaction of the inactive X, it was not lethal, again indicating H4K20me1 is not essential for viability. H4K20me1 has been shown to directly recruit L3MBTL1 in vitro to promote chromatin compaction [ 15 ]. Nevertheless, the precise role of H4K20me1 in negative regulation of gene expression, particularly beyond X chromosome inactivation, remains unclear. Conversely, H4K20me1 marks actively transcribed genes along with H3K79me2 [ 16 ]. In addition to covering the transcribed gene body, H4K20me1 is commonly seen at promoters of expressed genes [ 17 ]. Since many silencers have been found to be bifunctional [ 2 , 5 ], acting as enhancers in alternate cellular contexts, we considered that H4K20me1’s associations with active and repressed chromatin suggest that it may be a reasonable candidate for a silencer mark, with H4K20me1 ChIP-Seq peaks corresponding to candidate silencers. However, the most common form of H4K20 in the human and fly genomes is H4K20me2, comprising approximately 80% of histone tails, whereas H4K20me1 comprises approximately 10% of histone tails [ 18 , 19 ]. This presents technical difficulties for assaying H4K20me1 by ChIP-seq because even a small degree of cross-reactivity of antibody against H4K20me1 to the dimethyl form may greatly skew the results to H4K20me2, obscuring the signal due to H4K20me1. Here, we report an in-depth re-analysis of histone mark enrichment among the human silencers identified by Pang and Snyder [ 4 ]. Whereas the authors of that study [ 4 ] calculated enrichment as compared to random sampling of the human genome, we instead used elements that were tested but not found to act as silencers as a more appropriate background for calculating enrichment since this maintains the sequence biases inherent in generating the FAIRE open chromatin library used to screen for silencers in that study. In contrast to the high degree of enrichment reported by Pang and Snyder [ 4 ], the results of our re-analysis indicate that H4K20me1 is only marginally enriched among the Pang & Snyder human silencers. We confirmed the generality of the lack of notable enrichment among silencers in Drosophila , for which we generated H4K20me1 ChIP-seq data in Drosophila S2 cells using 3 different H4K20me1 antibodies. Silencers remain a poorly annotated class of cis -regulatory elements that cannot be reliably predicted by commonly assayed histone modifications. Results H4K20me1 is only marginally enriched among human K562 and HepG2 silencers The authors of the ReSE silencer screen reported that H4K20me-modified chromatin was significantly enriched among silencers from K562 and HepG2 cells. We noticed that in their analyses, Pang & Snyder calculated the significance of enrichment for any histone modification using a permutation test in which silencer coordinates were randomly shuffled across the genome. However, since the FAIRE fragments used to assemble the tested library are enriched for open chromatin, the use of random genomic regions as background is not appropriate ( Fig. 1A ). Download figure Open in new tab Figure 1. Silencers in human and fly cell lines are not enriched for H4K20me1. ( A ) Schematic of how FAIRE selection of an input library can create spurious enrichments. Top: all possible elements across the genome. Blue peaks represent histone modification ChIP-Seq peaks. Middle: selection of a subset of elements as selected by FAIRE for testing by ReSE enriches for histone modifications associated with open chromatin. Bottom: subset of tested elements that have significant silencer activity by MPRA. Proportion of elements overlapping the histone modification is unchanged compared to FAIRE elements but appears enriched compared to all possible genomic elements. ( B ) Venn diagram depicting the intersections between the FAIRE-selected ReSE library, ENCODE FAIRE-seq peaks from K562 cells and ENCODE ATAC-seq peaks from K562 cells. ( C ) Results of permutation test enrichment analysis for the K562 silencers. The background elements were randomly selected from tested non-silencer elements. Cover ratio denotes the fraction of silencer elements overlapping the indicated ChIP-Seq peak set. Fold enrichment represents the cover ratio of the foreground silencers over the background cover ratio of non-silencer elements. P -values were computed empirically by a permutation test and adjusted by Benjamini-Hochberg correction to calculate a false discovery rate (FDR). ( D ) AUROC curves showing histone modification enrichments for K562 silencers. AUROC curves were computed by iterating over silencer score quantile cutoffs from the set of all tested elements in 1 percentile increments. ( E ) Results of H4K20me1 permutation test enrichment for Drosophila S2 silencers. DLM3, Phaser, and Su(Hw) are subsets of “all” silencers that contain matches for the named motif ( e.g. , DLM3) and are not mutually exclusive. p -values were computed by permutation tests using random genomic regions. None of the classes were significantly enriched for H4K20me1 at P < 0.1. All: n = 347; DLM3: n = 267; SuHw: n = 175; Phaser: n = 15. Therefore, we then performed a similar permutation test except that to assemble a putative negative set we instead randomly sampled elements tested in the ReSE assay that were not found to exhibit silencer activity. The results revealed a strikingly different pattern of histone modification enrichment. In contrast to the results reported by Pang & Snyder [ 4 ], H4K20me1 was only moderately enriched ( q 0.05, fold enrichment = 0.958). Instead, the strongest enrichments corresponded to activation-associated marks, including H3K27ac (1.246 fold enrichment, q = 0), H3K4me1/2/3 (1.115, 1.237, 1.74 fold enrichments, q = 0.00017, 0, 0, respectively) and H3K9ac (1.232 fold enrichment, q = 0) ( Fig. 1B ). However, despite the statistical significance of these enrichments, the magnitude of these effects was very small, with none enriched more than 1.25-fold over background. For comparison, a similarly constructed STARR-seq assay that selected open chromatin as input, but measured enhancer activity, resulted in at least 5-10 fold enrichment of enhancer-associated marks [ 20 ]. Although Pang & Snyder noted small but significant enrichment for H3K9me3, we instead observed slight but not statistically significant ( q = 1.0 and 0.22, respectively) depletion of this mark among K562 and HepG2 silencers. It is important to note that ReSE employed a survival marker for detecting silencers so the assay is not able to differentiate between fragments with enhancer activity and fragments with no regulatory activity. This is likely why there are no strong depletions for marks commonly associated with enhancers. We observed very similar enrichments for silencers found by ReSE in HepG2 cells (Additional file 1: Fig. S1A ); nevertheless, use of a FAIRE library from K562 cells as input for the ReSE screen in HepG2 cells likely biased the set of identified HepG2 silencers, and thus potentially also the associated histone marks. Download figure Open in new tab Figure S1: HepG2 silencers are not enriched for H4K20me1. ( A ) The background elements were randomly selected from tested non-silencer elements. Cover ratio denotes the fraction of silencer elements overlapping the indicated peak set. Fold enrichment represents the cover ratio of the foreground silencers over the background cover ratio of non-silencer elements. P -values were computed empirically by a permutation test with 20,000 permutations of the background set and FDR corrected by Benjamini-Hochberg. ( B ) AUROC-based enrichment scores for HepG2 cell line analogous to figure 2 . AUROC curves are computed by iterating over silencer score quantile cutoffs from the set of all tested elements in 1 percentile increments. Next, to evaluate the predictive accuracy of each of the histone modifications in distinguishing silencers versus non-silencers, we analyzed the K562 and HepG2 silencers by the area under receiver operating characteristic curve (AUROC) (see the “Methods” section), which assessed performance across all possible threshold scores for calling silencers from the ReSE data. For the background in this AUROC analysis, as above, we used randomly sampled elements tested in the ReSE assay that were not found to exhibit silencer activity. The AUROC results were overall consistent with those from our permutation tests: the strongest, albeit modest, enrichments were for enhancer-associated marks, including H3K4me1/2/3 and H3K9ac (AUROC = 0.601, 0.643, 0.636 and 0.628, respectively; Fig. 2C ), while H3K9me3 was slightly depleted (AUROC = 0.490). We obtained similar results for silencers found by ReSE in HepG2 cells, with an even more pronounced depletion of H3K9me3 among the HepG2 silencers (AUROC = 0.417; Additional file 1: Fig. S1B ). Download figure Open in new tab Figure 2. H4K20me1 marks actively transcribed genes in Drosophila S2 cells. A) Upset plot of genomic annotations for Drosophila S2 cell H4K20me1 ChIP-Seq peaks using Ensembl gene annotations for dm3. B) Summary of antibody specificity as measured by SNAP-ChIP spike-in mononucleosomes. Columns represent individual ChIP-seq libraries, rows represent all histone modifications present in the panel. Values denote percentages of barcode reads mapped to each modification within a library. Abcam 9051: Abcam ab9051; AM: Active Motif AB_2615074; Thermo: Thermo Fisher MA5-18067. C) Venn diagram comparing IDR reproducible peaks in S2 cells from the three H4K20me1 antibodies (as in C) ) used in this study. D) Average peak density of H4K20me1 consensus ChIP-Seq peaks over genes. E) Boxplot of gene expression level in transcripts per million by H4K20me1 consensus peak overlap status. P -value is computed using a Wilcoxon rank sum test. Gene expression data from [ 33 ]. F) Top 10 enriched GO annotations among genes that are covered by H4K20me1 peaks in S2 cells. GeneRatio refers to the proportion of genes in the list that have the indicated GO annotation. Because the input library was obtained by FAIRE, we reasoned that FAIRE data from ENCODE for K562 cells [ 12 ] might serve as an alternate background set (without the more stringent selection of a putative negative set) in these histone mark enrichment analyses. The resulting profile of histone modifications enriched among the K562 silencers was vastly different using the ENCODE FAIRE sequences as background rather than the putative non-silencers from the ReSE screen. Here, only H3K27me3 was significantly enriched ( q < 0.05), with the magnitude of the enrichment again very small (Additional file 1: Fig. S2A ). Only 13% of ReSE input fragments overlapped ENCODE FAIRE peaks from K562 cells, while many more sequences were present only in the ReSE input library or the ENCODE FAIRE data ( Fig. 1D ). The ReSE input library showed lower overlap with HepG2 FAIRE-seq peaks (7.5%), as expected since the ReSE library was prepared from FAIRE sequences obtained from K562 cells. Similarly, analysis of the HepG2 silencers using the HepG2 FAIRE-seq peaks as background showed significant enrichments only for H3K27me3 and H3K9me3 (Additional file 1: Fig. S2B ). These results suggest that enrichment analyses of ReSE data should be performed for background sequences obtained from the same FAIRE experiments used to generate the ReSE input library to control for systematic biases across FAIRE datasets. Both the ReSE input library and the ENCODE FAIRE data showed only modest overlap with ENCODE ATAC-seq, despite both FAIRE and ATAC-Seq targeting open chromatin ( Fig. 1D ), consistent with prior studies that reported differences in open chromatin regions obtained by different chromatin accessibility profiling technologies [ 21 ]. Conservatively considering only ReSE library elements that overlapped with FAIRE-seq peaks to assemble a background set, enrichments for histone modifications showed even more modest effect sizes (fold enrichment 0.05 for all marks, Additional file 1: Fig. S2C ). Similarly, only 11% of silencers identified in HepG2 overlapped with ENCODE FAIRE peaks; restricting analyses to these regions did not substantially change the enrichment results (Additional file 1: Fig. S2D ). Download figure Open in new tab Figure S2: Silencers are not enriched for any histone marks when considering FAIRE-seq peaks as background. ( A ) Histone modifications enriched in ReSE K562 silencer elements using ENCODE FAIRE regions as background. Cover ratio denotes the fraction (0-1) of silencer elements overlapping the indicated peak set. Fold enrichment represents the cover ratio of the foreground silencers over the background cover ratio of non-silencer elements. P values are computed empirically by permutation test with 20,000 permutations of the background set and FDR corrected by Benjamini-Hochberg. Significant (FDR q < 0.05) enrichments are shown in red. ( B ) Histone modifications enriched in ReSE HepG2 silencer elements using ENCODE FAIRE regions as background, as in ( A ). ( C ) K562 silencers are not enriched for any histone mods when considering only elements that overlap K562 FAIRE-seq peaks. Cover ratio denotes the fraction (0-1) of silencer elements overlapping the indicated peak set. Fold enrichment represents the cover ratio of the foreground silencers over the background cover ratio of non-silencer elements. P -values were computed empirically by a permutation test with 20,000 permutations of the background set and FDR corrected by Benjamini-Hochberg. ( D ) Histone modification enrichments for ReSE HepG2 silencers, as in ( C ). Since the histone modifications that we found to be most enriched among the K562 or HepG2 silencers – H3K4me1/2/3 and H3K9ac – are marks associated with promoters [ 8 , 22 ], we reasoned that this enrichment could be driven by promoter competition [ 23 ] and thus excluded promoter regions from further analyses of silencer features [ 2 ]. Inspection of the distributions of the top 1,000 ENCODE ChIP-Seq peaks for the promoter-associated marks (H3K4me2/3 and H3K9ac) showed that these peaks are generally located within 5 kb of transcription start sites (TSSs) (Additional file 1: Fig. S3A-C ). Therefore, to focus our analysis of potential silencer marks beyond those whose silencing activity is likely due to promoter competition, we omitted from further analysis all ReSE library elements within 5 kb of a TSS. Although both the statistical significance and fold enrichment for H3K4me2/3 were diminished, the degree of those reductions was small and H3K4me2/3 remained among the most highly enriched marks among the K562 silencers (Additional file 1: Fig. S3D-E ). Download figure Open in new tab Figure S3: Removing TSS-overlapping elements has a marginal effect on histone enrichments. (A-C) Heatmaps showing the distributions of top 1000 peaks for ( a ) H3K4me3, ( B ) H3K4me2 and ( C ) H3K9ac in K562 cells. ( D ) Enrichment values for K562 silencer elements after subtracting all tested elements within 5 kb of a TSS. Cover ratio denotes the fraction (0-1) of silencer elements overlapping the indicated peak set. Fold enrichment represents the cover ratio of the foreground silencers over the background cover ratio of non-silencer elements. P -values are computed empirically by a permutation test with 20,000 permutations of the background set and FDR corrected by Benjamini-Hochberg. Significant (FDR < 0.05) enrichments are shown in red. ( E ) AUROC curves for K562 silencers after subtracting all tested elements within 5 kb of a TSS. Drosophila S2 cell silencers are not enriched for H4K20me1 To validate the findings from human cell lines in an orthologous system, we next looked to silencers in Drosophila melanogaster. To date, the largest set of silencers identified in Drosophila was found using a STARR-seq-based screen in S2 cells [ 24 ]. This screen identified 837 active silencer elements, many of which contain known DNA binding site motifs for the transcriptional repressors Phaser or Su(Hw) or the uncharacterized motif DLM3 [ 25 ]. Because H4K20me1 ChIP-seq data for S2 cells were not publicly available, we generated ChIP-seq data in S2 cells using three antibodies against H4K20me1 and one antibody against H3K27me3 as a positive control (see the “Methods” section). The H3K27me3 ChIP-seq peaks had strong overlap with previously published H3K27me3 ChIP-seq data for S2 cells [ 26 ] (Additional file 1: Fig. S4 ), which suggests the ChIP-seq experiments worked successfully. To directly assay the specificity of each antibody, we utilized SNAP-ChIP spike-in mononucleosomes, a panel of modified mononucleosomes with DNA barcodes representing specific modifications [ 27 ]. SNAP-ChIP spike-in mononucleosomes showed that all three H4K20me1 antibodies enriched H4K20me1 nucleosomes with low cross-reactivity (∼0.6 to 3.5%) with the di- or tri-methylated forms (H4K20me2/3), although one of the antibodies (Abcam 9051) exhibited substantial cross-reactivity (>55%) with other monomethylated lysines, particularly H3K27me1 ( Fig. 2A ). This cross-reactivity suggests that many peaks in prior ChIP-seq datasets generated using this antibody, including the ENCODE ChIP-seq data for K562 and HepG2 [ 12 ] used to analyze the ReSE silencer data by Pang and Snyder [ 4 ] and by us in this study, may not actually be due to H4K20me1. Download figure Open in new tab Figure S4. Venn diagram of overlap between newly generated H3K27me3 peaks (“H3K27me3 IDR”) with H3K27me3 peaks from Brown et al. , Science Advances (2024). Elements were considered overlapping if they overlapped by at least 1 bp. IDR analysis showed good reproducibility (36.7% - 50.1% of peaks replicated at IDR < 0.05, Additional file 1: Table S2 ) between replicate ChIP-Seq experiments (Additional file 1: Fig. S6 ). Furthermore, the sets of IDR peaks resulting from each of the three antibodies were largely overlapping ( Fig. 2B ). Abcam 9051 had the largest number of peaks not found using the other antibodies, most likely because of the high cross-reactivity of this antibody. We merged the peaks found in common by all three H4K20me1 antibodies into a high-confidence consensus set of 3036 H4K20me1 peaks (see the “Methods” section) with an average peak width of 9 kb. 1486/3036 (49%) of these H4K20me1 consensus peaks overlapped peaks identified by ChIP-chip experiments by modENCODE [ 28 ] (Additional file 1: Fig. S6A ). This moderate degree of overlap may be due to technical differences between the ChIP-Seq and ChIP-chip experiments and associated peak calling algorithms. The strongest modENCODE ChIP-chip peaks showed the greatest ChIP-Seq peak signal (CPM) from the overlapping H4K20me1 consensus ChIP-Seq peaks (Additional file 1: Fig. S6B ), suggesting that the weaker modENCODE peaks may have been more likely to be due to antibody cross-reactivity. H4K20me1 peaks covered a smaller proportion of the Drosophila genome overall (∼17% of mappable dm3 genome) compared to K562 (∼28% of mappable hg19 genome). This is most likely the result of our more stringently requiring H4K20me1 peaks in S2 cells to have been found using three different antibodies, but might also reflect broad, species-specific differences. Download figure Open in new tab Figure S5. Plots of IDR peak reproducibility between ChIP-seq replicates for each of the antibodies against histone modifications used in ChIP-Seq assays in Drosophila S2 cells in this study. Scatterplots depict IDR for ( a ) Abcam 9051 H4K20me1, ( b ) Active Motif H4K20me1, ( c ) Thermo H4K20me1, and ( d ) Epicypher H3K27me3. Black dots represent reproducible peaks and red dots are not considered reproducible. All plots were generated by the IDR software. Download figure Open in new tab Figure S6. S2 cell ChIP-seq corresponds to modENCODE ChIP-chip. A ) Venn diagram of overlaps (at least 1 bp) between modENCODE ChIP-chip peaks for H4K20me1 and the consensus set of H4K20me1 ChIP-Seq peaks generated in this study. B ) Heatmap showing the CPM normalized coverage of H4K20me1 ChIP-seq reads over the 4796 modENCODE ChIP-chip peaks. Abcam 9051: Abcam ab9051; AM: Active Motif AB_2615074; Thermo: Thermo Fisher MA5-18067. Regions are sorted in descending order by statistical significance reported in the modENCODE ChIP-chip dataset from modENCODE Consortium, Science (2010). View this table: View inline View popup Download powerpoint Table S1. Sequencing statistics for ChIP-seq and corresponding input libraries. All reads are paired-end 2 x 150 bp reads sequenced in the same run. Duplication percentage was calculated by Picard MarkDuplicates. Percentage mapped and mapq scores are given by Bowtie2 using dm3 as the reference genome. View this table: View inline View popup Download powerpoint Table S2. Peak calling statistics from Drosophila H4K20me1 ChIP-seq libraries. MACS2 peaks for each library were called using the default q value cutoff of 0.05, whereas idr peaks were called using a more relaxed P -value cutoff of 0.01 for each replicate. Fraction of reads in peaks (FRiP) was computed using the q < 0.05 peaks for each library individually. IDR peaks are only listed for replicate 1 but apply to replicates 1 and 2 together. Abcam 9051: Abcam ab9051; AM: Active Motif AB_2615074; Thermo: Thermo Fisher MA5-18067. View this table: View inline View popup Download powerpoint Table S3: UCSC Genome Browser accession numbers for K562 and HepG2 histone ChIP-seq peaks. Using our high-confidence consensus set of H4K20me1 ChIP-Seq peaks from S2 cells, we analyzed the set of 837 S2 silencers for enrichment of H4K20me1 ChIP-Seq peaks. In contrast to the FAIRE-enriched library used as input in ReSE, the S2 silencer screen was constructed using random fragments covering the entire Drosophila genome; therefore, we used random D. melanogaster genomic sequences as a proxy for an input library [ 24 ]. We found that the S2 silencers as a whole were not enriched for H4K20me1 peaks ( Fig. 1E ). We next analyzed each of the 3 classes of silencers, as defined according to their repressor motif matches (DLM3, Phaser, Su(Hw)), for enrichment of H4K20me1 to test if this histone modification marks a specific class of silencers. None of these 3 silencer classes were significantly enriched for H4K20me1 ( P < 0.05 after Benjamini-Hochberg correction to adjust for multiple hypothesis testing). As an alternative approach for calculating enrichment, we generated a background set matched for genomic sequence composition using GENRE [ 29 ]. We found that silencers had a comparable degree of enrichment for H4K20me1 using GENRE background compared to random background (Additional file 1: Fig. S7 ). Notably, the cover ratio of H4K20me1 over S2 silencers (0.09) was lower than that observed in human K562 and HepG2 cells (0.50 and 0.40 respectively). Download figure Open in new tab Figure S7. H4K20me1 fold enrichment values for Drosophila S2 silencers as compared to GENRE background regions. Background cover ratio is computed as the average of 100 GENRE backgrounds. H4K20me1 is associated with active transcription in S2 cells Genomic annotations of H4K20me1 peaks in S2 cells showed these regions are primarily genic and cover both introns and exons ( Fig. 2C ). Peaks were generally within 1 kb of a TSS (Additional file 1: Fig. S8 ). Only 4 peaks were annotated as “distal intergenic”, and inspection of these loci showed that they often included lncRNAs that were not included in the Flybase gene annotation file but are presumably transcribed. ENCODE H4K20me1 peaks in a human cell line (K562) showed broadly similar distributions across different genomic regions when considering the much larger genome and longer intronic spans of human genes (Additional file 1: Fig. S9 ). In both Drosophila S2 cells and human K562 cells, the profile of H4K20me1 over gene bodies shows a dip directly over TSSs before sharply increasing and slowly attenuating over the length of the gene body, consistent with a prior study of H4K20me1 in human cell lines ( Fig. 2D and Additional file 1: Fig. S9 ) [ 16 ]. Download figure Open in new tab Figure S8. H4K20me1 ChIP-Seq peaks in S2 cells are close to TSSs. H4K20me1 consensus peaks were assigned to the closest TSS in Flybase annotation v.5.57. Download figure Open in new tab Figure S9. H420me1 peaks in human cell lines are primarily genic. ( A, B ) Upset plot of annotations for ENCODE H4K20me1 peaks from A) K562 and ( B ) HepG2 using Ensembl gene annotations for hg19. ( C, D ) Distribution of distances to TSS for ENCODE H4K20me1 peaks in ( C ) K562 and ( D ) HepG2. ( E, F ) Aggregate peak profile of ENCODE H4K20me1 peaks in ( E ) K562 and ( F ) HepG2 over genes. Since H4K20me1 previously was found to be enriched over transcribed genes in mammalian cells and Drosophila [ 16 , 30 – 32 ], we integrated RNA-seq expression data from S2 cells into our analysis to inspect H4K20me1 for potential association with gene expression levels [ 33 ]. We found that genes overlapping S2 cell H4K20me1 ChIP-Seq peaks were on average more highly expressed in S2 cells than were genes that did not overlap H4K20me1 ChIP-Seq peaks ( P < 2.2 x 10 -16 ) ( Fig. 2E ). Analysis of Gene Ontology (GO) annotation terms assigned to H4K20me1 intersecting genes showed enrichment for developmental categories, including “instar larval or pupal morphogenesis”, “imaginal disc morphogenesis” and “wing disc development” ( Fig. 2F ), consistent with the stem cell origins of S2 cells [ 34 ]. Several GO categories related to negative regulation were enriched, including “negative regulation of response to stimulus”, “negative regulation of signaling” and “negative regulation of cell communication”, suggesting that many H4K20me1 marked genes are involved in regulating cellular responses. Profiles of H4K20me1 have been seen to closely match those of H3K36me3, another mark of actively transcribed gene bodies, in human cell lines [ 16 ]. We analyzed publicly available H3K36me3 ChIP-seq peaks from S2 cells [ 26 ] and found that 60% of H4K20me1 ChIP-Seq peaks overlapped with H3K36me3 peaks (Additional file 1: Fig. S10A ), demonstrating the evolutionary conservation of the co-association of these marks with expressed genes. The distribution of these H3K36me3 peaks was strikingly similar to that of H4K20me1 in terms of distance to TSS, genomic annotation, and aggregate peak profile over gene bodies (Additional file 1: Fig. S10B-D ). Overall, we found that the distribution and associations of H4K20me1 in S2 cells is similar to known H4K20me1 patterns in other systems. Download figure Open in new tab Figure S10. H3K36me3 has a distribution similar to that of H4K20me1 in Drosophila S2 cells. ( A ) Venn diagram of peak overlap between S2 H4K20me1 peaks and H3K36me3 peaks. ( B ) Distribution of distances to nearest TSS for H3K36me3 peaks. ( C ) Upset plot of genomic annotations for H3K36me3 peaks. ( D ) Aggregate peak profile of H3K36me3 over genes. H3K36me3 peaks are from Brown et al. , Science Advances (2024). Discussion Human transcriptional silencers were reported previously to be enriched for H4K20me1 [ 4 ], but our re-analyses of those human silencer data using appropriate background sets to assess enrichment, combined with analysis of Drosophila S2 cell silencer data with H4K20me1 ChIP-Seq profiles generated for this study, reveal that H4K20me1 is not actually a silencer mark in either human or fly. Our re-analyses demonstrate the importance of both selecting the appropriate background in enrichment analyses and considering the fold enrichment to evaluate the effect size of enrichment in addition to statistical significance. Although the enrichment of some histone modifications did reach statistical significance, their modest fold enrichments indicate that they are not reliable predictors. The ReSE library obtained by FAIRE in K562 cells [ 4 ], which was used as input in the human silencer screen that we re-analyzed, showed surprisingly low overlap with ENCODE FAIRE-seq peaks from the same cell line ( Fig. 1D ). However, only a small portion of reads (FAIRE fragments) in a FAIRE-Seq experiment are typically found within peaks [ 35 ], consistent with the fraction of FAIRE fragments from ReSE that were in FAIRE-seq peaks. ReSE [ 4 ], as well as several other silencer screens [ 2 , 3 , 36 ], selected for open chromatin based on the assumption that silencers are located within accessible chromatin, as are transcriptional enhancers. The result that most K562 and HepG2 silencers were not found within open chromatin according to FAIRE-Seq data challenges this assumption and suggests that human silencers either do not reside preferentially in open chromatin or alternatively that they require only very short stretches of open chromatin that may not be detected by genomic assays such as FAIRE-Seq. Such a chromatin state is consistent with findings from the recent Drosophila S2 cell silencer screen, which found that that Drosophila S2 silencers reside within phased nucleosomes that appear to be within inaccessible chromatin according to DNase I hypersensitivity peaks but often contained very short regions of chromatin accessibility that were sufficient for just a single transcription factor to bind [ 24 ]. Our results highlight persistent problems with antibody specificity. While the H3K27me3 antibody was highly specific, the H4K20me1 antibodies showed cross-reactivity. This was particularly problematic for Abcam 9051, which had affinity for other monomethylated lysines, especially H3K27me1. This cross-reactivity could create confounding artifacts in interpreting results from ChIP-Seq and other experiments using this antibody, since H3K27me1 is related to the facultative heterochromatin mark H3K27me3 and is also deposited by PRC2 [ 37 ]. This antibody has been discontinued but was widely used in many previous studies, including by ENCODE and modENCODE. Because ChIP-seq studies rarely include direct assays for antibody specificity such as the barcoded mononucleosomes used here, antibody cross-reactivity often goes unnoticed. The functional role(s) of H4K20me1 remains unclear. The loss of H4K20me1 results in reduced viability [ 33 ] or reduced efficiency of X chromosome inactivation [ 13 ], suggesting that H4K20me1 may contribute to robustness of gene regulatory programs. While it has been found to localize on regions of heterochromatin [ 13 , 15 , 38 ], our results from H4K20me1 ChIP-Seq in S2 cells support prior studies in human cells that found it associated with actively transcribed genes [ 16 , 31 , 39 ]. Our data showed association almost exclusively with active chromatin, but we note that many of the previous associations with repressed chromatin, such as the mammalian inactive X chromosome [ 13 ] or polytene chromosomes [ 38 ], are not present in S2 cells. H4K20me1 is also associated with the repression of repetitive elements in mammals [ 40 , 41 ], but Drosophila primarily use small RNA pathways to silence repetitive elements [ 42 ], for which we did not find an association with H4K20me1. Conclusions Our results expand upon a recent study in Drosophila S2 cells that likewise found that transcriptional silencers do not correspond to any known chromatin signatures [ 24 ]. Despite the number of functionally identified silencers in fly or human now numbering in the thousands [ 3 – 5 , 24 ], they remain poorly characterized and difficult to predict. Silencers might be specifically marked by a histone modification that is not commonly profiled or for which ChIP-grade antibodies do not exist currently. Mass spectrometry has identified over 500 histone post-translational modifications [ 43 ], only a small fraction of which have been assayed by ChIP-seq or similar assays. The functional associations of many of these understudied modifications, particularly those other than methyl or acetyl groups, have started to be appreciated only recently [ 44 , 45 ]. Broader profiling of histone modifications may reveal a silencer chromatin signature. Several distinct subclasses of silencers may exist, each of which are characterized by a different chromatin signature such that there is no universal silencer mark [ 46 ]. Finally, it is possible that unlike transcriptional enhancers, silencers as a broad class of cis -regulatory elements have no characteristic histone mark(s) and can only be predicted by the binding of particular transcriptional (co-)repressors. Determining the chromatin features of silencers will be important for the prediction of transcriptional silencers for genome annotation and understanding gene regulatory mechanisms. Methods S2 cell culture S2-DRSC cells were purchased from the Drosophila Genomics Resource Center (DGRC Stock Number: 181). S2 cells were cultured in Schneider’s medium (Thermo Fisher 21720024) supplemented with 10% fetal bovine serum (FBS) and penicillin-streptomycin at ambient temperature (22 °C). Cell counts were determined using a Countess II with Trypan blue staining. ChIP-seq We performed ChIP-seq experiments in S2 cells closely following previously published protocols [ 47 ]. Briefly, we used 100 µg of sheared DNA per ChIP reaction with SNAP-ChIP K-MetStat spike-in mononucleosomes. We used the following H4K20me1 antibodies: Abcam ab9051, used widely by ENCODE and modENCODE as well as [ 32 ]; Active Motif AB_2615074, which was not used in a published ChIP-seq study to our knowledge; and Thermo Fisher MA5-18067, which was recently used in CUT&RUN experiments in Drosophila [ 48 ]. As a positive control, we performed ChIP in parallel for H3K27me3 using a well characterized H3K27me3 antibody (Epicypher 13-0055). ChIP-seq reads were mapped to dm3 using Bowtie2 [ 49 ] and peaks were called using MACS2 [ 50 ]. We used the IDR framework [ 51 ] to find peaks that are reproducible between replicates. SNAP-ChIP spike-in analysis We identified SNAP-ChIP barcodes in each library using a custom Python script based on Epicypher’s provided script. Counts were summed across the two redundant barcodes used for each modification, the two FASTQ files for each paired-end read library, and the two replicate libraries for each antibody. Statistical analysis Enrichment of histone marks among genomic regions For re-analysis of human datasets [ 4 ], enrichments were calculated using ChIP-seq data generated by ENCODE. Unless otherwise stated, all coordinates are in hg19. To match reference data used previously [ 4 ], processed bed files for broad peaks were downloaded from the UCSC Genome Browser. Reference peaks for H3K27me3 and H3K36me3 in S2 cells were downloaded from GEO: GSE245077 [ 26 ] and lifted over to dm3 coordinates. RNA-seq expression data for S2 cells were downloaded from SRA PRJNA937779 [ 33 ]. AUROC analysis of histone mark enrichment among silencers Silencer reporter activities for all tested human elements in ReSE were obtained from the authors of [ 4 ]. We performed receiver operating characteristic curve (AUROC) analysis to determine the sensitivity and specificity with which the silencer activity of an element is predicted by overlap (at least 1 bp) with a ChIP-seq peak for a particular histone modification. The entire tested library was sorted by fold enrichment and the cutoff values for every percentile were calculated. Then, for every percentile threshold, elements with fold enrichment greater than the threshold were considered silencers and those below the threshold considered non-silencers. The true positive (TP) elements were counted as those library elements above the silencer threshold and overlapping a ChIP-seq peak, false positives (FP) were above the silencer threshold but not overlapping a peak. True negatives (TN) were below the silencer threshold and not overlapping a peak, and false negatives (FN) were below threshold but overlapping a ChIP peak. The true positive rate (TPR) is TP/(TP+FN) and the false positive rate (FPR) is FP/(TN+FP). We computed the area under the AUROC ( i.e. , the area under the curve of TPR as a function of FPR) by the AUC function of DescTools using the “trapezoid” method. Analysis of cover ratios of histone marks among human silencers Cover ratio was defined as the fraction of foreground elements that overlap ChIP-Seq peaks [ 4 ]. We defined the fold enrichment as the ratio of the foreground cover ratio over the mean cover ratio of permuted background sets. Permutation tests were performed by comparing the fraction of elements overlapping annotated peaks in foreground (silencer) versus background (non-silencer) sets. For histone modification enrichment analyses in ReSE datasets, we defined the background as the set of elements tested in the screen that were not called as silencers. Because the Drosophila S2 STARR-seq screen had much broader coverage across the genome in the input library, we defined the background as the entire D. melanogaster genome, excluding unmappable blacklisted regions. P -values of histone mark enrichment were computed as the fraction of permuted background sets that had a higher cover ratio than the foreground set. All permutation tests were performed using 20,000 permutations to mirror the analyses performed by Pang and Snyder [ 4 ]. Analysis of S2 cell RNA-seq expression data We downloaded a table of TPM normalized read counts from an S2 RNA-seq experiment [ 33 ]. We classified genes as H4K20me1+ if they intersected an H4K20me1 consensus peak by at least 1 bp and H4K20me1-if they did not. The statistical significance of differences between the distributions of TPMs among H4K20me1+ versus H4K20me1-genes was determined by a Student’s t-test. Additional method details For additional methods, please see Additional file 2: Supplemental Methods. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials Accession numbers of histone modification ChIP-Seq datasets for human cell lines from the UCSC Genome Browser analyzed in this study are listed in Table S3 . Histone modification ChIP-Seq and RNA-Seq datasets for Drosophila S2 cells analyzed in this study were obtained from the NCBI Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/ ) under accession number GSE245077 and the Sequence Read Archive (SRA) under accession number PRJNA937779, respectively. Genomic coordinates of S2 silencers were obtained from [ 24 ] under GEO accession number GSE254776. The raw sequencing data from H4K20me1 ChIP-Seq for S2 cells generated in this study have been deposited in GEO under accession number GSE284058. The results of all statistical tests appear in Additional file 3: Table S4-13. Original code is available from Github ( https://github.com/jsegert1/H4K20me1-manuscript ). Competing interests The authors declare they have no competing interests. Funding This project was supported in part by fellowship F31 GM145107 from the U.S. National Institutes of Health to J.A.S., grants R01 HG009723 and R56 HG009723 from the U.S. National Institutes of Health to M.L.B., and a grant from the Brigham Research Institute Fund to Sustain Research Excellence to M.L.B. Authors’ contributions J.A.S. and M.L.B. designed research; J.A.S. performed experiments and data analysis; M.L.B. supervised research; J.A.S. and M.L.B. wrote the paper. The authors read and approved the final manuscript. Supplemental methods S2 cell collection and chromatin shearing Cells were harvested by use of a plastic cell scraper, tapping the flask, and repeated pipetting of media. Approximately 2 x 10 7 cells were used per chromatin immunoprecipitation (ChIP) reaction, although the final amount was determined by micrograms of DNA and not input cell number as this reduced variability from automated cell counting and variable efficiency of sonication. Cells were pelleted by centrifugation at 1000 x g for 5 minutes and washed twice with 1X PBS (Gibco 10010023). They were then crosslinked with 1% formaldehyde (Electron Microscopy Science 15710) in PBS at room temperature for 10 minutes with shaking. Crosslinking was quenched by the addition of 2.5 M glycine to a final concentration of 125 mM and incubated at room temperature for 5 minutes. Cells were washed twice with cold PBS and finally resuspended in PBS + complete protease inhibitor cocktail EDTA-free (Millipore Sigma 11873580001) and divided into aliquots of ∼1 x 10 8 cells in microcentrifuge tubes. These were pelleted again at 1000 x g for 5 minutes, the supernatant was aspirated off, and the pellets were frozen at -80 °C for future processing. Two replicates were collected and fixed in different batches on different days. To shear chromatin, cell pellets were thawed on ice and resuspended in cell lysis buffer and incubated for 10 minutes. Samples were centrifuged at 4000 x g for 5 minutes and then resuspended in 1mL nuclear lysis buffer. Samples were sonicated in a Bioruptor Plus (Diagenode) at high power for 30 seconds on and 30 seconds off. The number of cycles was chosen to fragment DNA with a peak of fragments ∼200 - 600 bp. In our case, 60 cycles were needed, but the exact number will vary depending on many factors and should be determined empirically by testing many iterations. To measure DNA concentration, a 100 µL aliquot was decrosslinked by adding 38 uL decrosslinking buffer (2 M NaCl, 0.1M EDTA, 0.4M Tris pH 7.5 [ 1 ]) and incubating overnight at 65 °C followed by incubation with 2 µL proteinase K (Thermo Fisher 25530049) at 50 °C for 2 hours. DNA was extracted by phenol-chloroform purification and then precipitated with ethanol and linear acrylamide (Thermo Fisher AM9520) as a carrier. DNA pellets were reconstituted in 100 µL water and quantified by Qubit HS dsDNA kits (Invitrogen Q33231). ChIP-seq To evaluate antibody specificity, 10 µL SNAP-ChIP K-MetStat mononucleosomes (Epicypher 19-1001) were spiked into each replicate chromatin prep before aliquoting into individual ChIP reactions. 100 µL input chromatin (“Input”) was reserved and sequenced as background. To dilute the concentration of sodium dodecyl sulfate (SDS) in the nuclear lysis buffer prior to ChIP, sonicated chromatin was diluted 1:5 with IP dilution buffer (16.7 mM Tris pH 8.0, 1.2 mM EDTA, 167 mM NaCl, 1.1% Triton X-100, 0.01% SDS) [ 1 ]. 100 µg chromatin as measured from the decrosslinked sample was aliquoted to each ChIP reaction. ChIP was performed using several different antibodies against H4K20me1 to check for consistency of ChIP signal and ensure high quality data. The H4K20me1 antibodies used were: Abcam ab9051, used widely by ENCODE and modENCODE as well as [ 2 ] Active Motif AB_2615074, which has not been used in a published ChIP-seq study to our knowledge; and Thermo Fisher MA5-18067, which was recently used in CUT&RUN experiments in Drosophila [ 3 ]. As a positive control, ChIP was performed in parallel for H3K27me3 using a well characterized H3K27me3 antibody (Epicypher 13-0055). Chromatin was first pre-cleared by incubation with 20 uL unblocked Magna ChIP Protein A+G beads (Sigma Aldrich 16-663). Beads were washed once in IP dilution buffer for 2 hours with rotation before adding to chromatin. The beads were then immobilized with a magnet and the precleared chromatin was moved to new tubes and then incubated with 5ug antibody (see above) overnight at 4C with rotation. In parallel, beads for ChIP were blocked overnight in 1 mg/mL BSA (NEB B9200S) in IP dilution buffer at 4C. Beads were washed once with IP dilution buffer before 20uL beads were added to each sample and then incubated for 2 hours at 4C. Washes and elution were performed as previously described [ 1 ]. Briefly, beads were washed 6 times with low salt buffer (0.1% SDS, 1% Triton X-100, 2 mM EDTA, 20 mM Tris pH 8.0, 150 mM NaCl), once with high salt buffer (0.1% SDS, 1% Triton X-100, 2 mM EDTA, 20 mM Tris pH 8.0, 500 mM NaCl), and once with TE pH 8.0 (Invitrogen AM9849) before elution with 250 µL elution buffer (0.1M NaHC03, 1% SDS). Eluted DNA was decrosslinked by overnight incubation with decrosslinking buffer at 65 °C and purified using Monarch PCR and DNA Cleanup Kit (New England Biolab T1030S). DNA was quantified using Qubit HS dsDNA and High Sensitivity D5000 DNA ScreenTape assays (Agilent). Generation and QC of sequencing libraries Sequencing libraries were generated using NEBNext Ultra II (E7645S) with NEBNext multiplex oligos for Illumina (E7335S). The number of PCR cycles was selected according to manufacturer’s recommendations for the mass of DNA in each library. Input, H4K20me1 libraries using Abcam 9051 antibodies, and H3K27me3 libraries were amplified with 3 cycles of PCR, while H4K20me1 libraries using the Active Motif or Thermo antibodies required 6 cycles of PCR. QC of sequencing libraries was performed using Qubit High Sensitivity dsDNA assays for DNA concentration and High Sensitivity D1000 and D5000 DNA ScreenTape assays (Agilent) for fragment length distributions. Since the libraries generated using the Active Motif or Thermo H4K20me1 antibodies skewed towards larger fragment sizes, we size-selected them with SPRISelect beads (Beckman Coulter B23317) prior to sequencing, using a right-side size selection with 0.4x bead ratio to remove large fragments. Libraries were paired-end sequenced 2 x 150bp on an Illumina HiSeq 2500. Sequencing statistics are provided in Additional file 4: Table S3 . ChIP-seq data processing Trim galore (v. 0.6.6) [ 4 ] was used to remove adaptor sequences and bases with sequencing quality below 30. Reads were then mapped to dm3 using bowtie2 (v. 2.5.1) [ 5 ] with the settings “--sensitive-local --no-discordant --no-mixed”. PCR duplicates were called using Picard MarkDuplicates. Libraries were filtered for alignments above mapq 30. Peak calling was performed using MACS2 [ 6 ] (v. 2.1.1.20160309) with the corresponding input reads as control and the settings “--broad -g dm -f BAMPE”. Following ENCODE guidelines [ 7 ], we used the irreproducible discovery rate (IDR) framework [ 8 ] to identify peaks that are consistent between the two replicate samples that used the same antibody. For calling peaks found to be reproducible by IDR analysis, a more relaxed threshold of “-p 1e3” was used to call peaks in each library before running IDR [ 8 ] (v. 2.0.2). A summary of peak counts is provided in Additional file 5: Table S4. High confidence “consensus” H4K20me1 peaks used for downstream analyses were determined by concatenating the sets of IDR reproducible peaks and retaining only those peaks that were common across all three peak sets from the three H4K20me1 antibodies that we used. Consensus peaks were then merged to remove redundancies and overlapping peaks were collapsed into continuous regions. Peaks were annotated using the annotatePeak function of ChIPSeeker (v.1.38.0) [ 9 ] with the reference annotation packages TxDb.Hsapiens.UCSC.hg19.knownGene (v.3.2.2) for humans and Flybase (v5.7) for Drosophila . Bed files of H4K20me1 ChIP-seq peaks in K562 and HepG2 used for genomic annotation were downloaded from ENCODE (accessions ENCFF139CKE and ENCFF869HGO respectively). The TSS region was set to 250bp downstream and 50bp upstream for Drosophila and 500bp downstream and 500bp upstream for human. Names of H4K20me1 intersecting genes were determined according to org.Dm.eg.db (v.3.19.0). 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