Zea mays) with 5-ethynyl-2’-deoxyuridine (EdU) and used flow sorting of nuclei to examine DNA replication timing (RT) during the transition from a mitotic cycle to an endocycle. Comparison of the sequence-based RT profiles showed that most regions of the maize genome replicate at the same time during S phase in mitotic and endocycling cells, despite the need to replicate twice as much DNA in the endocycle and the fact that endocycling is typically associated with cell differentiation. However, regions collectively corresponding to 2% of the genome displayed significant changes in timing between the two types of cell cycles. The majority of these regions are small with a median size of 135 kb, shift to a later RT in the endocycle, and are enriched for genes expressed in the root tip. We found larger regions that shifted RT in centromeres of seven of the ten maize chromosomes. These regions covered the majority of the previously defined functional centromere, which ranged between 1 and 2 Mb in size in the reference genome. They replicate mainly during mid S phase in mitotic cells but primarily in late S phase of the endocycle. In contrast, the immediately adjacent pericentromere sequences are primarily late replicating in both cell cycles. Analysis of CENH3 enrichment levels in 8C vs 2C nuclei suggested that there is only a partial replacement of CENH3 nucleosomes after endocycle replication is complete. The shift to later replication of centromeres and possible reduction in CENH3 enrichment after endocycle replication is consistent with a hypothesis that centromeres are inactivated when their function is no longer needed.Plant cells undergo two types of cell cycles–the mitotic cycle in which DNA replication is coupled to mitosis, and the endocycle in which DNA replication occurs in the absence of cell division. To investigate DNA replication programs in these two types of cell cycles, we pulse labeled intact root tips of maize  phase. In plants, it is unclear whether traditional and endocycle programs are the same, especially since endocycling cells are typically in the process of differentiation. Using root tips of maize, we found that in comparison to replication in the mitotic cell cycle, there is a small portion of the genome whose replication in the endocycle is shifted in time, usually to later in S phase. Some of these regions are scattered around the genome and mostly coincide with active genes. However, the most prominent shifts occur in centromeres. The shift to later replication in centromeres is noteworthy because they orchestrate the process of separating duplicated chromosomes into daughter cells, a function that is not needed in the endocycle. Zea mays) root, the first 1-mm primarily contains actively dividing mitotic cells )Arabidopsis cell suspensions [in vivo with the thymidine analog, 5-ethynyl-2’-deoxyuridine (EdU), and labeled nuclei are separated by flow cytometry into populations representing different stages of S phase. One key advantage of using EdU as the nucleotide analog instead of 5-bromo-2’deoxyuridine (BrdU), which has traditionally been used in replication timing by sequencing (Repli-seq) protocols [We developed a system to analyze DNA replication in maize roots , 20, usipensions . In thisrotocols , is the Cytological analysis of sorted, EdU-labeled nuclei showed that replication activities in early and mid S are more closely interspersed in the maize nucleus than in animal cells , 23. We Although replication in the first 1-mm of the root is mostly mitotic, with DNA contents of labeled nuclei ranging from 2C to 4C, flow cytometry profiles of nuclei derived from root tissue between 1 and 3-mm from the tip also included a substantial population of nuclei with DNA contents beyond 4C. Appearance of endopolyploid 8C) nuclei in this zone would be expected, as some 4C nuclei are known to enter the endocycle rather than undergo division , 8. CytoC nuclei Drosophila (reviewed in [Both under-replication and over-replication (amplification) have been observed in multiple animal systems during developmentally programmed endocycles, notably including iewed in ). In addiewed in –30.Arabidopsis showed that leaf nuclear DNA is evenly endoreduplicated in wild-type plants, although the same series of experiments clearly demonstrated selective over-replication in atxr5 and atxr6 mutants [Even though endopolyploidy is common in plants, there are very few reports dealing with over- or under-replication of specific sequences. Some orchids exhibit a phenomenon in which only a fraction of the genome is endoreplicated , 32, but mutants .To address the question of over- or under-replication and whether there are developmentally associated changes in RT programs in the maize root tip system, we performed a detailed comparison of RT dynamics in mitotic and endocycling cells. We found very little evidence for over- or under-replication in endocycling cells, consistent with the few previous reports on this topic from plant systems. We also found that the RT programs for the vast majority of the genome are very similar. However, we found significant changes in timing for a number of loci that together correspond to 2% of the genome. Most notably, we found major changes in the RT of centromeres, which replicate mainly during mid S phase in mitotic cells but primarily in late S phase of the endocycle.As reported previously and described in Methods, we used a 20-min pulse of the thymidine analog, EdU, to label newly replicated DNA in intact maize roots. This was followed by formaldehyde fixation and isolation of nuclei from defined segments of root tips . IncorpoThe flexibility of the EdU labeling and flow sorting system also allowed us to collect unlabeled nuclei, representing non S-phase cells with 2C, 4C and 8C DNA contents. These nuclei were used to characterize selected histone marks following mitotic or endocycle replication and to investigate the copy number of individual loci across the genome.Given the well documented examples of over- and under-replication during the endocycle in animal systems, we investigated whether there are local copy number differences in the maize genome after endocycle replication. To do this, we used the non S-phase 2C, 4C, and 8C nuclei populations described above, and carried out whole genome paired-end sequencing. To gain a better representation of the copy number of repeat regions in the genome, reads that could not be uniquely mapped to a single location were included, but we retained only the primary alignment location for each read pair. This approach was used exclusively for the copy number analysis, while all subsequent analyses included only uniquely mapping reads see . The datknob180 and TR-1 [CentC satellite repeats [CRM) families 1–4 [To further investigate whether there is complete replication of high-copy repeats that are not well represented in the genome assembly, we used BLAST software to query all reads, not just those that can be mapped to the genome, to determine the percentage of reads corresponding to each of several consensus sequences for high-copy repeats . Analyzeand TR-1 , 39, 5S and TR-1 , and cen repeats . We alsolies 1–4 –45. In aAs described above, we sorted endocycling nuclei from the S-phase populations in To compare the RT programs in endocycling and mitotic nuclei, we mapped our previous Repli-seq data for mitotic nuclei  and our Repliscan analysis pipeline [We used the pipeline  to generpipeline ). Normalpipeline , 48. TheDespite the global similarity of the RT programs of mitotic and endocycling cells, there are regions scattered around the maize genome that show a shift in RT. To identify regions with differences in RT (DRT), we first calculated the difference in normalized replication signal between the mitotic and endocycle data at each genomic location for the early, mid and late profiles separately ; S5 Fig.Regions of Altered Timing (RATs), we identified regions in which the DRT was ≥ 25% of the total difference range for a given S-phase fraction , and those in which the strongest replication signal occurs earlier in the mitotic cycle than in the endocycle (“Earlier-to-Later” shift). In addition, we separately characterized a subset of the Earlier-to-Later RATs that are located in functional centromeres (“Earlier-to-Later-CEN”) using centromere (CEN) coordinates from . Our strP value was calculated  and acetylation of H3 lysine 56 (H3K56ac) modifications tend to colocalize on active genes and are associated with earlier replicating regions, while trimethylation of H3 lysine 27 (H3K27me3) tends to be on repressed genes regardless of their RT . For eacWe also performed a gene ontology (GO) analysis for the genes found in non-CEN RATs to ask if there are functional annotations enriched in genes that shift RT. For this analysis, we focused on the genes that we identified as expressed in the root tip . We founP value threshold of 0.001, although one TE superfamily, RLG/Gypsy, is very close to the threshold for being called significantly depleted in Earlier-to-Later RATs . InCentC; , which wUpon inspecting the RT profiles for each of the complex CENs we found the strongest replication signals occurring mainly in mid S in mitotic cells, but changing to primarily late S in endocycling cells. It is also noteworthy that though replication occurs mainly in mid S in mitotic cells, there are some distinct peaks of early replication inside or directly adjacent to the called centromere  were previously characterized as “simple” because they mainly contain large arrays of the C repeat , 57. In ng cells , while sng cells .Because of the issues with computationally identifying continuous RATs we chose to focus the following set of analyses on the entire CENH3-binding region of each chromosome (excluding blacklist regions). We calculated the difference in early, mid and late replication signal (endocycle minus mitotic) from RT profiles by averaging across 100-kb static windows. For comparison, we also calculated the replication signal differences in pericentromeres, which were arbitrarily defined as the ± 1 Mb flanking the CENH3 region. We inspected all RT differences in the centromeres and pericentromeres by not requiring that the DRT be compensated by an opposite shift in the other S-phase fractions. Early and mid replication signals across the complex centromeres decrease and late replication signals increase in endocycling cells, reflecting a large shift toward late replication. The DRT values for the late profile in centromeres and pericentromeres are shown in CentC repeats  as wellfamilies , 58, 59. binding , 58. In CRM families, CRM1 and CRM2, are similar  and repressive (H3K27me3) histone H3 post-translational modifications to look for epigenetic changes in centromeres after endocycle replication. It was previously reported that some H3K4me3 and H3K27me3 peaks of enrichment occur in the centromere, mainly associated with genes . We askeWe also investigated the levels of dimethylation of histone H3 lysine 9 (H3K9me2) enrichment in each centromere after mitotic and endocycle replication. Previous work indicated there is a depletion of H3K9me2 in centromeres relative to adjacent pericentromeres , 62, whiUnlike the canonical histone H3, CENH3 is not replaced in a replication dependent manner in higher eukaryotes, resulting in a dilution of CENH3 relative to centromeric DNA during S phase , 65. NewArabidopsis endopolyploid nuclei showing the CENH3 signal does not increase in parallel with the total DNA content or the signal for 180-bp centromeric repeats [Because mitosis does not occur in the endocycle and centromere function is presumably not required, we speculated that CENH3 might remain at low levels following DNA replication in endocycling cells. This hypothesis is supported by cytological studies of  repeats , 69. To  repeats  for ChIP repeats .To compare total CENH3 content of entire centromeres at different ploidy levels, we calculated the percent of total CENH3 reads found in a given centromere and made a ratio to the percent of total reads from the corresponding input DNA in that centromere separately for each biological replicate, as described above for H3K9me2. The CENH3 average fold enrichment relative to total DNA content is similar for 2C and 4C nuclei in each of the complex centromeres , with anThe maize root tip includes a naturally occurring developmental gradient, with cells in the meristem region (ca. 0–1 mm) primarily undergoing mitotic cell cycles, while a subpopulation of cells in the transition zone (ca. 1–3 mm) enters a developmentally programmed endocycle prior to further differentiation , 9. Evenin vivo EdU labeling of intact root tips and two-color fluorescence activated nuclei sorting. By doing so, we avoided potential artefacts caused by cell synchronization [We generated whole genome Repli-seq data for root cell nuclei undergoing DNA replication in either the mitotic cycle or the endocycle, making use of nization  and chronization –77). We nization . An addiDrosophila follicle cells which found no regions of differential RT between mitotic and endocycling cells [The current study sought to investigate whether the mitotic RT program is maintained as endocycling cells transition from 4C to 8C, despite the need to replicate twice as much DNA and the initiation of various root cell differentiation pathways. Extending our previous cytological observation that spatiotemporal patterns of replication are similar in mitotic and endocycling cells , we founng cells . Additiong cells , howeverDrosophila endocycles  between the two types of cell cycles. Approximately 11% of the genome showed compensated DRT at a stringency level of ≥ 10% difference in replication signal see . Howeverper se. Research in metazoans has revealed ~8–20% of their genomes can shift RT between cell types [Drosophila genome, regions that show RT shifts between cell types are more similar in size to the maize non-centromeric RATs [The first 1-mm of the maize root contains the meristem and precursors for at least ten different cell types. Only some of these cell types enter the endocycle prior to cell elongation . If therll types , 81–83. ll types ). These The vast majority of the non-centromeric RATs involved RT shifts from Earlier-to-Later, with a significant enrichment for genes expressed in the root tip, but not for non-expressed genes (FPKM < 1). This result suggests the possibility that RT shifts may be related to shifts in gene expression. Unfortunately, we have been unable to follow transcriptional changes in endocycling nuclei directly, as we have so far not been able to isolate RNA of sufficient quality to characterize transcripts from fixed, sorted nuclei. However, our analysis of activating and repressive histone modifications uncovered only minor changes in the enrichment and location of these marks within RAT genes after endocycle replication. The lack of notable changes in the proportion of RAT genes bearing H3K56ac and H3K4me3 modifications after the endocycle suggests that these histone marks are permissive to changes in RT. Nonetheless, the direction of the change in H3K4me3 enrichment on genes in Earlier-to-Later RATs after endocycle replication  is consiIn the case of centromeres, it is easy to imagine that the large shifts to later replication are related specifically to endocycling, because endocycling cells presumably no longer require functional centromeres. Though often broken by unmappable and multi-mapping (“blacklist”) regions in the genome assembly, centromeric RATs when combined across blacklist regions are much larger in size (0.9–2 Mb) than the non-centromeric RATs and cover the majority of each of the seven complex centromeres . These sCentC repeats within them–undergo a shift to late replication in the endocycle. As a result, the RT of the complex centromeres in the endocycle becomes much more similar to that of the immediately adjacent pericentromeric regions, which replicate primarily in late S phase in both mitotic and endocycling cells. Late replication of pericentromeres is expected based on our previous cytological observations in mitotic and endocycling nuclei [These analyses revealed several features shared by the RT programs of the seven complex maize centromeres. For example, in mitotic cells there are a few distinct peaks of early replication  wouCentC arrays [CentC satellite repeats in all centromeres, which showed that, as a group, these repeats consistently shift RT from mid to late. Another piece of evidence comes from our analysis of complex centromeres, which showed that the magnitude of the RT change tapers off toward the outer edges of the functional centromere. One can speculate that the simple centromere assemblies are comprised mostly of the sequences at the edges of the actual centromere, which would still be anchored to nonrepetitive regions in the genome assembly. As in complex centromeres, these edge sequences might have a smaller RT shift than internal sequences. Future cytological experiments, using a combination of flow sorted, EdU-labeled nuclei and techniques for identifying maize chromosomes [Unlike complex centromeres, the three simple centromeres of maize show less drastic RT changes that occur over smaller regions. These simple centromeres are not as well assembled as the complex centromeres , 57, andC arrays , 57, theomosomes , 107 couDrosophila cell types in metaphase to G1; reviewed in [The centromere-specific histone variant, CENH3  plays an important role in recruiting kinetochore proteins –55. In miewed in , 70). Thiewed in . In our Drosophila midgut cells found that CENP-A is required in post-mitotic and differentiated cells, and proposed that the loading of CENP-A in endocycling cells is essential for maintaining chromosome cohesion [It is unlikely that endocycling cells will ever re-enter the mitotic cycle , 110, ancohesion . This poCentromeres are considered to be epigenetically specified, as there are no unique sequences in the functional centromere that are not also found in the adjacent pericentromere . WAn interesting question for future investigation is whether changes in chromatin conformation or 3D positioning in the nucleus are associated with the large shift in centromeric RT. In mammals, RT is considered a functional readout of large-scale chromatin structure , 26, 82,CentC satellite repeats as well as CRM retroelements, and there is evidence that centromere transcripts are involved in the function of the kinetochore complex and centromere chromatin organization [Additionally, we speculate that centromere transcription could play a role in the shift to later replication of centromeres in the endocycle. Non-coding transcription has been reported to occur in centromeres across a wide range of eukaryotes, and has also been found to be essential for centromere function  were germinated on damp paper towels and grown for three days. Seedling roots were labeled by immersion in sterile water containing 25 μM EdU (Life Technologies) for 20 min, using growth and experimental conditions described previously [Seeds of eviously , 19, 20.Details of the flow sorting for Repli-seq analysis were described previously , 20. BriFor ChIP-seq experiments, roots were labeled with EdU, and nuclei were isolated from 0–3 mm (H3K27me3 and H3K4me3) or 0–5 mm (H3K56ac) root segments and conjugated to AF-488 as described above. The 2C, 4C and 8C unlabeled, non S-phase populations of nuclei were sorted into 2× extraction buffer 2 (EB2)  using thFor endocycle Repli-seq samples, reversal of formaldehyde cross links, nuclear DNA purification and isolation, DNA shearing, EdU/AF-488 DNA immunoprecipitation with an anti-Alexa Fluor 488 antibody , and DNA fragment purification were performed as described in Wear et al. .Zea mays anti-CENH3 antibody at a 1:250 dilution (gift from R.K. Dawe) [ChIP procedures were performed as in Wear et al.  except tK. Dawe) , anti-H3For Repli-seq and ChIP-seq samples, the final purified DNA was used to construct paired-end libraries as described . After aftp://ftp.ensemblgenomes.org/pub/plants/release-33/gff3/zea_mays/) using BWA-MEM v0.7.12 with default parameters [http://broadinstitute.github.io/picard/) and SAMtools [Trimming and quality control of 100-bp paired-end Repli-seq reads were carried out as described previously , and rearameters . RedundaSAMtools . ProperlSAMtools  for downSAMtools , but to SAMtools  to a totRepliscan [Repliscan default parameters described in [-w 3000). Additionally, we customized the cutoff for reducing type one errors which excluded genomic windows with extremely low coverage in the 2C reference sample. To identify these low read mapping windows, which we labeled “blacklist”, Repliscan natural log-transformed the read counts from the pre-replicative 2C reference sample and windows with read counts in the lower 2.5% tail of a fitted normal distribution were excluded from all samples (parameter—pcut 2.5–100). The upper 2.5% tail containing extremely high coverage windows or “spikes” was not removed at this step, because we found that these data spikes were adequately normalized in the subsequent step of dividing each 3-kb window in the S-phase samples by the 2C reference data–which also normalized for sequencing biases and collapsed repeats  [The difference between normalized replication signal profiles of mitotic and endocycle Repli-seq data for early, mid, and late S was calculated in 3-kb windows, and the maximum negative and positive differences were then calculated for each chromosome and averaged. Regions showing a DRT of ≥ 25%  or ≥ 10%  of the total range of differences in each profile were identified ; S5 Fig -d 6000) . This in-d 6000) ). There ChIP-seq reads for H3K27me3, H3K4me3, H3K56ac (100-bp paired-end reads), H3K9me2 and CENH3 (150-bp paired-end reads) were trimmed, mapped to maize B73 RefGen_v4.33, and filtered to retain only properly-paired, uniquely-mapped reads (MAPQ score > 10) as described above for Repli-seq reads. The 2C ChIP and input data for H3K27me3, H3K4me3, H3K56ac is from , while tFor visualization of CENH3 localization in 2C, 4C and 8C nuclei, read counts for individual biological replicates of CENH3 or input samples were scaled to 1× genome coverage using the reads per genomic content (RPGC) method. Biological replicate data had good agreement , and diftp://ftp.ensemblgenomes.org/pub/plants/release-33/gff3/zea_mays/). The updated B73 Refgen_v4 TEv2 disjoined annotation [http://mcstitzer.github.io/maize_TEs. Coordinates for mapped CentC satellite repeat regions are described in Gent et al. [The maize filtered gene set Zm00001d.2 annotation from B73 RefGen_v4  was downnotation  was downt et al. . The per-wa -wb) in the BEDtools suite [-u).We tested the association of various genomic features with the non-CEN RAT categories by determining the overlap of a particular feature with each RAT type. The coordinates for genomic features  were intersected with RAT coordinate intervals using intersectBED  in the BEDtools suite [CRM element spanned more than one of the 3-kb windows, the replication signals were averaged using mergeBED (parameter -o mean) to compute a single value for the entire gene or element.For comparison to CEN regions (coordinates from ), pericels suite . Only elS1 Text(DOCX)Click here for additional data file.S1 FigMaize root tip nuclei were isolated from the 1–3 mm root region and sorted on a BD InFlux flow sorter. A small sample from each of the three S-phase sort gates was re-analyzed to determine the purity of the sorted nuclei. Histograms of relative DNA content (DAPI fluorescence) from re-analyzed sorted nuclei are overlaid for early (E), mid (M), and late (L) S-phase gates from the endocycle arc to show the separation between sorted samples. Similar separation was found for sorted early, mid and late nuclei from the mitotic cycle . The hi(PDF)Click here for additional data file.S2 FigA and B) Histograms of the normalized read frequency ratios, calculated in 5-kb static windows, for 2C/4C (A) and 8C/4C (B) nuclei. The black dashed lines indicate the overall mean and the red dashed lines indicate ± 2 S. D. from the mean. (C) The 8C/4C read frequency ratios plotted as a function of genomic location, which shows that the values outside ± 2 S. D. all occur as singleton 5-kb windows. (D and E) We used consensus sequences for 45S rDNA and knob180 (D), and for 5S rDNA, TR-1, CentC and CRM1–4 families (E) to individually query all of the trimmed whole genome sequence reads using BLAST software and a non-stringent E value to allow for variants of each repeat (knob180 and CRM2) is not statistically significant.Whole genome sequence data from sorted non S-phase 2C, 4C and 8C nuclei were used to assess copy number per DNA content across the genome. To better represent the copy number of repeat regions, the primary alignment location for each read pair–even those that map to multiple locations–were included in the analysis. (h repeat . The mea(PDF)Click here for additional data file.S3 FigA and B) Read densities were calculated in 3-kb windows for the 2C reference (A) and each S-phase sample . After excluding blacklist regions (e.g. unmappable and multi-mapping regions), reads were scaled for overall sequence depth in each sample. (C) Scaled reads in each S-phase sample were normalized by making a ratio to 2C reference scaled reads in each 3-kb window. (D) Replication signal profiles were smoothed using a Haar wavelet transform to remove noise without altering peak boundaries.An example region from CEN 10 is shown to illustrate that the pre-replicative 2C reference data effectively normalizes spikes of signal in the S-phase data. ((PDF)Click here for additional data file.S4 FigA and B) Biological replicates (BR) of early (E), mid (M) and late (L) Repli-seq data for the mitotic cycle  and endocycle  was analyzed independently using Repliscan [C) The Pearson’s correlation coefficients for E, M, L data between mitotic cycle and endocycle.(epliscan . The agr(PDF)Click here for additional data file.S5 FigDifferences in replication timing (DRT) signal were calculated by subtracting the mitotic signal from the endocycle signal for early (E), mid (M) and late (L) S-phase fractions in each 3-kb window across the genome. The distributions of DRT signal values are represented as violin plots for each chromosome. Median values are indicated by colored squares and 1.5 x IQR of the distribution is indicated by colored whisker lines. Dashed lines indicate the thresholds used in subsequent steps for identifying RATs Click here for additional data file.S6 FigA–F) Example regions on chromosomes 1 (A), 3 (B), 4 (C), 5 (D), 6 (E) and 7 (F) that include RATs. See main text A, B, C and F), or in which the change in one S-phase fraction was not compensated by an opposite change in at least one other S-phase fraction (boxes labeled “b” in panels C and D).((PDF)Click here for additional data file.S7 FigA–C) The distributions of fold enrichment values for H3K56ac (A), H3K4me3 (B) and H3K27me3 (C) peaks in expressed and non-expressed genes  may be associated with increases in peak enrichment we observed near the 3' end of some genes. (D) The count and percentage of expressed and non-expressed genes with each histone modification shown in the boxplots in panels A–C. The 8C/2C ratio of genes with each mark is also shown to demonstrate there is very little change in the number of genes with each mark. The total number of expressed and non-expressed genes in each RAT or random category are shown at the bottom for reference.To assess whether changes in selected histone modifications related to gene transcription and chromatin accessibility occur in RATs, ChIP-seq data was generated for H3K56ac and H3K4me3 (active transcription and early replication) and H3K27me (repressive transcription and facultative heterochromatin) from sorted non S-phase 2C, 4C and 8C nuclei. Click here for additional data file.S8 FigUsing the Plant GO slim ontology subset, we identified 44 significant GO terms in the biological process (P), molecular function (F), and cellular component (C) GO categories that were enriched in expressed genes  in Earli(PDF)Click here for additional data file.S9 FigA and B) and Later-to-Earlier (C and D) non-CEN RATs and corresponding 1000 randomly shuffled sets  or less than (down arrow) the observed value. No overlap was observed between Later-to-Earlier RATs and the RIT/LINE RTE superfamily, thus no P value was calculated.The percent coverage of all TEs and individual TE superfamilies annotated in the B73 RefGen_v4 genome was calculated for Earlier-to-Later (sets see . The obs(PDF)Click here for additional data file.S10 FigA) The distributions of percent AT content, calculated in 3-kb static windows, for Later-to-Earlier and Earlier-to-Later non-CEN RATs and the corresponding random shuffle sets are plotted as boxplots. Values outside the boxplot whiskers (1.5 x IQR) are represented as grey dots. The dashed line indicates the genome wide median value.((PDF)Click here for additional data file.S11 FigThe average percentage of centromeric reads that map to unique locations is shown for each Repli-seq sample. Black dots represent the individual values for biological replicates.(PDF)Click here for additional data file.S12 Fig5-Mb regions are shown for complex CENs 2, 3, 4, 5, and 8 and simple CEN 7. See main text (PDF)Click here for additional data file.S13 FigA and D), mid (B and E) and late (C and F) RT profiles for each centromere and corresponding pericentromere (± 1 Mb) in 100-kb static windows. In panels D, E, and F asterisks indicate DRT values from windows where an Earlier-to-Later-CEN RAT extends past the called CEN boundary [DRT values (endocycle minus mitotic) were calculated from early (boundary  into the(PDF)Click here for additional data file.S14 FigA–E) The distributions of replication signals in early (E), mid (M), and late (L) during mitotic and endocycle S phases for all 3-kb windows (A), annotated genes (B), CRM1 elements (C), CRM2 elements (D), and mapped CentC repeats (E) in centromeres and pericentromeres (± 1 Mb). All elements within centromeres and pericentromeres are included, not just those that cover at least half of a 3-kb window, as in ((PDF)Click here for additional data file.S15 FigA–C) The fold enrichment values for peaks in expressed and non-expressed genes for H3K56ac (A), H3K4me3 (B) and H3K27me3 (C) in 2C, 4C and 8C nuclei. Red lines indicate the median value. (D) The number of expressed and non-expressed genes with each mark in 2C, 4C and 8C nuclei.ChIP-seq data were generated for H3K56ac, H3K4me3 (active transcription) and H3K27me (repressive transcription) from 2C, 4C and 8C nuclei. ((PDF)Click here for additional data file.S16 FigA and B) using coordinates from [C and D) and dividing by the percent of total input reads corresponding to that centromere or pericentromere. Black dots represent the individual values from biological replicates.We used the ChIP-seq datasets from 2C, 4C and 8C nuclei to estimate the H3K9me2 average fold enrichment relative to DNA content by calculating the percent of total H3K9me2 reads found in a given centromere (tes from  or peric(PDF)Click here for additional data file.S17 FigA) CENH3 localization patterns for 2C, 4C and 8C nuclei for CEN 1–CEN 8. (B) CENH3 average fold enrichment relative to DNA content for complex and simple centromeres. See main text ((PDF)Click here for additional data file.S18 FigZea mays anti-CENH3 antibody (A) and anti-H3K9me2 antibody (B). Black dots in panel A represent the individual values from two biological replicates. Positive control primer sets (CRM2 and Copia retrotransposons) and negative control primer sets (18S rDNA and Actin1 UTR) were used. The no antibody control (NoAB) values are too small to see on the graph. See The percentage of input (% IP) was calculated for various antibody dilutions and primer sets for the (PDF)Click here for additional data file.S1 TableThe difference in replication signal between mitotic and endocycle profiles (endocycle minus mitotic) was calculated for each 3-kb window across the genome. The maximum negative difference value, which indicates a higher signal in the mitotic cycle, and the maximum positive difference value, which indicates a higher signal in the endocycle, are shown for early and late profiles. The average total difference range between these two values was used to calculate percentage thresholds for identifying RATs (see (DOCX)Click here for additional data file.S2 TableThe thresholds from (DOCX)Click here for additional data file.S3 TableThe percent of RATs that contain genes, the total number of genes and expressed genes and the mean gene count per RAT are shown.(DOCX)Click here for additional data file.S4 TableWe calculated the total number of 3-kb windows in complex centromeres and pericentromeres (± 1 Mb), as well as the number of windows that show DRT values that are compensated (threshold ≥ 10%) by equal and opposite shifts in the other two S-phase fractions.(DOCX)Click here for additional data file.S5 TableCENH3 fold enrichment relative to DNA content and the ratio of enrichments between 4C and 2C and 8C and 2C are shown for each centromere. Fold enrichment values are the mean ± S. D. of three biological replicates for 2C and 8C and two biological replicates of 4C. See main text (DOCX)Click here for additional data file.S1 Spreadsheet(XLSX)Click here for additional data file.S2 Spreadsheet(XLSX)Click here for additional data file.S3 Spreadsheet(XLSX)Click here for additional data file.


Nowadays, the use of MSCs has attracted considerable attention in the global science and technology field, with the self-renewal and multidirectional differentiation potential for diabetes, obesity treatment, bone repair, nerve repair, myocardial repair, and so on. Epigenetics plays an important role in the regulation of mesenchymal stem cell differentiation, which has become a research hotspot in the medical field. This review focuses on the role of lysine acetylation modification on the determination of MSC differentiation direction. During this progress, the recruitment of lysine acetyltransferases (KATs) and lysine deacetylases (KDACs) is the crux of transcriptional mechanisms in the dynamic regulation of key genes controlling MSC multidirectional differentiation. Mesenchymal stem cells (MSCs), a kind of adult stem cell with multidirectional differentiation potential, can differentiate into many mesodermal lineages, including adipocytes, osteoblasts, chondrocytes, muscle cells, and nerve cells –4. BasedPrecise control of proteins is essential to organism function. Lysine acetylation is one of the major protein modifications after translation, which has multiple effects on protein and metabolic components . It can Lysine acetylation is a reversible process of transferring acetyl group from acetyl coenzyme A to the E-amino side chain of lysine . Lysine Acetylation of histones or nonhistones is mainly reversibly regulated by lysine acetyltransferase (KAT) and lysine deacetylase (KDAC), which are sometimes referred as histone acetyltransferase (HAT) and deacetylase (HDAC). KAT can relax the structure of nucleosomes, promoting the expression of transcription factors and synergy. Transcription factors can contact with DNA molecules to activate transcription of specific genes. Deacetylation is the process in which KDACs make the promoter barely access to transcriptional regulatory elements to inhibit transcription followed by gene inactivation .α-tubulin N-acetyltransferase 1 (TAT1/ATAT1), establishment of cohesion 1 homologue 1 (ESCO1) and ESCO2, and histone acetyltransferase 1 (HAT1/KAT1), and there is no homology. Besides TAT1, all classical KATs are mainly localized in the nucleus acetylating histones and nonhistones.At present, it shows that 13 KATs have been identified in the human proteome , and most of them can be classified into three families: GCN5, p300, and MYST19 . In addi+-dependent sirtuin deacetylases [The deacetylation of proteins is catalyzed by deacetylase. At present, 18 kinds of KDACs have been found in human proteome. According to the homology of KDAC domain, it can be divided into four types: class I KDACs , class II KDACs , class III KDACs (SirT 1-7), and class IV  , 26. Claetylases . Zinc-deAbout 70% of the known acetylation sites of KATs are the targets of CBP and/or p300. Acetylation in most of the acetylated proteins is catalyzed by five KATs  . SimilarAcetyl coenzyme A  is a key metabolite of cell function, including energy production in mitochondria and lipid biosynthesis in the cytoplasm. Acetylation is directly related to the level of ACA. The specific production of ACA in cells can locally affect the acetylation of proteins. For example, nuclear ACLY, ACSS2, and PDC regulate histone acetylation by locally producing ACA and thereby affecting gene transcription . In yeasProtein acetylation is associated with many cellular processes and human diseases. Line mutations in several KATs and KDACs, such as KAT6A, SMC3 (coding chromosome protein 3), and HDAC8 , are related to developmental retardation, abnormalities, and mental disabilities , 35. StuPrior to the discovery of KDAC, histone deacetylase inhibitors (HDACi) also advanced protein acetylation , 42. SodIn vivo, HDACi can reduce the invasiveness, angiogenesis, and metastasis of tumors, thus inhibiting the development of tumors. In contrast, CBP, KAT inhibitors discovered recently, and A485, p300 inhibitor, showed antiproliferative effects on lineage-specific tumor cell lines [HDACi equally promote the acetylation of nonhistone proteins, which can determine the interactions, localization, and stability of these proteins . At the ll lines .Mesenchymal stem cells (MSCs) are pluripotent progenitor cells that have the potential to differentiate into multiple mesodermal lineages, including adipocytes, osteoblasts, and chondrocytes. During aging and osteoporosis, adipogenesis is superior to osteogenesis, which means that under these conditions, the balance of MSC differentiation is dysregulated. Numerous transcription factors are involved in the lineage selection and terminal differentiation of MSCs.Lysine acetylation regulation is involved in many cell differentiation processes. It is also one of the major regulatory mechanisms of epigenetic regulation of MSCs to adipose differentiation and osteogenic differentiation . HistoneLysine acetylation modification and its modified enzyme are basically involved in the epigenetic regulation of lipogenesis –53. Lysihdac3 knockout or the expression of hdac1 interfered with siRNA [Pretreatment with HDAC inhibitors VPA and sodium butyrate (NaBu) inhibited the adipogenic differentiation of human umbilical cord blood and adipose-derived mesenchymal stem cells ; HDAC inth siRNA –58. In ath siRNA . HDAC9 hth siRNA , 60, 61.γ (PPARγ), CCAAT/enhancer-binding proteins (C/EBPs), adipocyte assay and differentiation-dependent factor 1/sterol response element-binding protein 1c (ADD1/SREBP1c) are key regulators of mammalian adipocyte differentiation and also participate in the spectrum selection and terminal differentiation of MSCs [γ and C/EBPα is accomplished by the interaction of transcription factors, coactivators, and coinhibitors. Among them, lysine acetylation and deacetylation play an important role by genetic regulation. Zhang et al. (2012) detected the distribution patterns of acetylation modification of five key adipose formation regulatory genes, Pref-1, C/EBPβ, C/EBPα, PPARγ2, and aP2, during the adipogenesis of C3H 10T1/2 mouse mesenchymal stem cells (MSCs) and 3T3-L1 preadipocytes, in order to determine the role of acetylation modification of lysine and its “division of labor” in adipocyte differentiation. The results showed that the detected lysine acetylation modification was globally stable throughout the adipogenesis process but showed a unique and highly dynamic distribution pattern for specific genes. For example, PPARα 2 and aP2 genes in MSCs showed increased histone acetylation in the tails of H3 and H4 during adipogenesis, and increased histone acetylation levels activate the transcription of PPARα 2 and aP2 genes [γ and inhibiting its target genes when food is restricted [γ acetylation, thereby increasing C/EBPα expression and promoting the development of lipogenesis [γ, thereby enhancing its transcriptional processes [Multiple transcription factors are involved in the lineage selection and terminal differentiation of MSCs. Peroxisome proliferator-activated receptor  of MSCs , 63. StuP2 genes . In addistricted –71. Convogenesis . In addirocesses , 74. Morrocesses . And HDArocesses –78. Interocesses .The degree of histone acetylation of related regulatory genes may reflect the maintenance and differentiation status of MSCs . The aceIn the current study, class I HDAC1, HDAC2, HDAC3, and HDAC8 and class III SIRT1 and SIRT3 played an important role in the differentiation direction of BMMSCs –89. In tβ-catenin to accumulate in the nucleus [κB [SIRT1 can directly regulate the factor Sox2 to maintain the self-renewal and pluripotency of BMMSCs. The decrease of its activity reduces the expression of Sox2, which leads to the degradation of self-renewal and differentiation ability of BMMSCs. The activated SIRT1 can dose-dependently promote the ability of BMMSCs to clone and differentiate into osteogenic adipogenic differentiation . Similar nucleus . In addileus [κB .Histone deacetylase inhibitors have a strong influence on the differentiation of BMMSCs. Treatment of BMMSCs with histone deacetylase inhibitors VPA and NaBu increased histone H3 and H4 acetylation levels and significantly promoted liver-specific gene expression, suggesting that the agent promotes the differentiation of BMMSCs into the liver by inhibiting deacetylase . At the In vitro, chondrogenic differentiation of hBMMSCs significantly increased the level of chromatin marker H3K9ac at the promoter and 5′ end regions of the gene [In addition, Tan et al. studied the H3K9ac modification of the gene promoter region of hBMMSCs at the genome-wide level. The results showed that the modification of H3K9 in the promoter region of hBMMSCs correlated well with mRNA expression. Functional analysis showed self-renewal in hBMMSCs. Multiple key intracellular signal transduction pathways can be regulated by H3K9 modification . In the the gene . These rβ 1 (TGF-β 1)/SMAD pathway and Wnt/β-catenin pathway have been proved to be related to this process [In cartilage tissue regeneration medicine, lysine acetylation is involved in the regulation of chondrocyte differentiation and terminal differentiation of mesenchymal stem cells. Cartilage tissue is a vascularless tissue composed of chondrocyte and extracellular matrix. Hence, cartilage tissue has limited repair ability . Mesench process –107. Lys process –111. Hisβ-catenin to inhibit the expression of β-catenin gene but also degrade β-catenin through the interaction between the domain of deacetylase and the deacetylated β-catenin protein, which leads to the downregulation of the classical Wnt/β-catenin signaling pathway and promotion of the cartilage differentiation process of mouse mesenchymal stem cells induced by TGF-β 1 [β 1; meanwhile, HDAC4 can inhibit the expression of X hypertrophic phenotype X (SDSCs) [Histone modification plays an important role in regulating the early chondrogenic differentiation of mesenchymal stem cells . Coactiv TGF-β 1 . HDAC4 c (SDSCs) .β-catenin induces an imbalance in cartilage homeostasis [In vitro chondrogenesis experiments using C3H10T1/2 cells showed that mRNA and protein levels of β-catenin were inhibited during chondrogenesis, while expression levels of HDAC1 was elevated. The opposite expression pattern between β-catenin and HDAC1 suggests that there may be novel regulatory mechanisms involved in cartilage formation between these two factors [Cartilage damage is usually accompanied by the occurrence of bone lesions. Multiple local factors are involved in regulating the physiological remodeling of cartilage, and the loss of balance of these factors may result in higher cartilage catabolism. Molecules of the Wnt pathway have become key regulators of bone and cartilage. Activation of Wnt/eostasis , 118. In factors .Lysine acetylation regulation is involved in many cell development and differentiation processes.α [α promoter region prevents binding of PPARγ with HDAC1 binding to this region further, reducing histone acetylation levels, and PPARγ establishes DNA methylation in the promoter region of C/EBPα and the bridge of histone acetylation [In the complex and delicate internal environment of organisms, epigenetic regulation often does not work in a single way. Different histone modifications can interact with each other and play a synergistic role. Histone modification can also be coupled with DNA methylation to produce complex epigenetic effects. The network regulation pattern of epigenetic modification is also involved in the fine regulation of adipogenic differentiation of MSCs. The balance between osteogenic and adipogenic differentiation of MSCs is regulated by DNA methylation and histone acetylation in the promoter region of C/EBPα , 120. Attylation .RUNX2 was upregulated in BMMSCs during osteogenic differentiation, and both transcriptional activation-related H3K9ac and H3K4me3 modification levels and recruitment in the RUNX2 promoter region were elevated, while H3K9me3 modification levels associated with transcriptional repression were observed in the RUNX2 promoter region. The recruitment was reduced, and the degree of DNA methylation in the RUNX2 promoter region was reduced . These fin vivo generation of models to specifically study stem cells and their molecular regulatory mechanisms of adult origin, as well as the lack of stem cell-specific inducible targeting strains and conventional methods for epigenetic analysis from very small amounts and powerful calculation methods to understand the large amount of data generated.Epigenetic modulators affect the function of adult tissue stem cells primarily by modulating the function of tissue-specific master regulators. However, for us, it is still far away to understand the specific role of individual epigenetic factors; more importantly, their combined activity in adult stem cells and their communication is unclear. We face many technical challenges, such as In recent years, a variety of epigenetic modifications have been found to participate in the differentiation of MSCs. Based on these modifications, drugs have been developed to effectively regulate these modifications, providing precise differentiation conditions for MSCs and enabling MSCs to differentiate in a controllable and predictable direction. At present, some small-molecule drugs that can regulate stem cell differentiation and proliferation are in the stage of detection and development, which can participate in various aspects of regulatory programming and development signaling pathways . These rIn conclusion, the regulation of lysine acetylation plays an important role in the process of MSC adipogenesis and differentiation, but the specific mechanism is not yet fully understood, and a new regulatory modification network needs to be found. Further research in this field will provide clues for the fate of MSC differentiation and will have broad application prospects in clinical tissue engineering and cell therapy.


Arabidopsis PcG mutants, we show that PcG function regulates chromatin accessibility. We find that H2AK121ub is associated with a less accessible but still permissive chromatin at transcriptional regulation hotspots. Accessibility is further reduced by EMF1 acting in collaboration with PRC2 activity. Consequently, H2AK121ub/H3K27me3 marks are linked to inaccessible although responsive chromatin. In contrast, only-H3K27me3-marked chromatin is less responsive, indicating that H2AK121ub-marked hotspots are required for transcriptional responses. Nevertheless, despite the loss of PcG activities leads to increased chromatin accessibility, this is not necessarily accompanied by transcriptional activation, indicating that accessible chromatin is not always predictive of gene expression.Although it is well established that the Polycomb Group (PcG) complexes maintain gene repression through the incorporation of H2AK121ub and H3K27me3, little is known about the effect of these modifications on chromatin accessibility, which is fundamental to understand PcG function. Here, by integrating chromatin accessibility, histone marks and expression analyses in different  Polycomb Group complexes maintain gene repression through the incorporation of H2AK121ub and H3K27me3. Here, the authors show that H2AK121ub marks less accessible but transcriptionally permissive chromatin, while H3K27me3 enforces a repressed transcriptionally less-permissive state. While PcG repressive complex 1 (PRC1) has histone 2A E3 ubiquitin ligase activity8, PRC2 has histone 3 lysine 27 (H3K27) trimethyltransferase activity12. Nevertheless, despite the important role of these chromatin marks in regulating transcription in eukaryotes, their effect on chromatin is not yet clear. Several pieces of evidence suggested that animal PcG proteins mediate chromatin compaction15. However, a recent report proposed that although PcG occupied promoters exhibit reduced accessibility, this does not rely on PcG proteins. Instead, PRC1 plays a role in increasing nucleosome occupancy and decreasing nucleosomal spacing16.PcG complexes maintain gene repression by incorporating histone modifications within chromatinArabidopsis thaliana (Arabidopsis), the composition of PcG complexes is still a matter of debate. While PRC2 core components are well conserved to their animal counterparts and the catalytic activity is mainly carried out by the EZ homologs CURLY LEAF (CLF) and SWINGER (SWN) during sporophyte development17, the identity of PRC1 is less clear. Despite the H2A monoubiquitination module is formed by the Polycomb Group ring finger (PCGF) and RING1 homologs BMI1  and RING1 (A or B)18, association of the plant-specific proteins EMBRYONIC FLOWER 1 (EMF1) and LIKE-HETEROCHROMATIN PROTEIN 1 (LHP1) to this complex has turned to be controversial. EMF1 was proposed to be a PRC1 component due to its ability to in vitro mediate chromatin compaction as Drosophila melanogaster (Drosophila) PRC1 component Posterior Sex Combs (Psc) does20. However, recent data showed that EMF1 co-purifies with PRC2 (refs. 23) and is required for H3K27me3 marking25. Likewise, LHP1 was proposed to perform similar function to Drosophila PRC1 component Polycomb (Pc)27; however, LHP1 also co-purifies with PRC2 (refs. 23) and is involved in maintenance/spreading of H3K27me3 (ref. 21) but dispensable for H2AK121ub marking28. Thus, these two proteins actually seem to be PRC2-associated component.In 28. Accordingly, H3K27me3 marks usually cover the complete gene region, whereas H2AK121ub marks are enriched at the region surrounding the transcriptional start site (TSS)28. In addition, there are also genes marked with only-H2AK121ub or H3K27me3 (ref. 28) , indicating that these marks may play independent roles.Interestingly, although H2AK121ub and H3K27me3 marks often co-localize at genes (H2AK121ub/H3K27me3-marked genes), H3K27me3-marked peaks are generally much longer than that of H2AK121ubArabidopsis have been linked to regions displaying locally reduced DNA accessibility29. According to this, the promoters of expressed genes display high chromatin accessibility and are depleted of H3K27me3 marks31. However, it is not clear whether H3K27me3 has a direct role in regulating chromatin accessibility. On the other hand, the role of PRC1-mediated H2AK121ub is far from clear. Although several data support a repressive role of this modification28, it has been proposed to be associated with gene responsiveness and its repressive function seems to require PRC2 recruitment32. In any case, nothing is known about a possible role of H2AK121ub in regulating chromatin accessibility in plants.H3K27me3 marks in Arabidopsis PcG mutants, we show that H2AK121ub marks associate with a less accessible but permissive chromatin at transcriptional regulation hotspots, which are sites enriched for the binding of transcription factors (TFs). Chromatin accessibility can be further reduced by EMF1 and PRC2 activity. However, while H2AK121ub/H3K27me3-mediated inaccessible chromatin is still transcriptionally responsive, only-H3K27me3 marked chromatin is less responsive.In this work, by integrating chromatin accessibility, histone marks, and expression analyses in different bmi1abc, clf28swn7, and emf1-2 severe mutants33 that cannot undergo the transition from embryonic to vegetative development after germination in the aerial part of the seedling. However, unlike bmi1abc and clf28swn7, which in addition have a stunted root displaying embryonic traits, emf1-2 is able to develop a WT-like root  in wild-type Col-0 (WT) and different PcG mutants at 10 days after germination (DAG). We selected ring1ab, and lhp1 clustered together, whereas clf28swn7 and emf1-2 on one side, and bmi1abc on the other, constituted two distant and distinct clusters, indicating differences between them  of ATAC-seq data revealed that WT,  WT Fig. . Consens WT Fig. . Accordi WT Fig. . We then WT Fig. . Interesp value <10−4; Fig. 39. According to this, a high number of transcriptional regulation hotspots that were inaccessible in WT became accessible in one or more mutants -binding sites . We redefined H2AK121ub/H3K27me3, only-H3K27me3, and only-H2AK121ub marked genes as those genes displaying the corresponding modification/s in one of the two WT datasets, resulting in similar gene lists than the ones previously published28 (see “Methods” section).To investigate the role of H3K27me3 and H2AK121ub marks in regulating chromatin accessibility, we next analyzed the signal levels of these modifications at H2AK121ub/H3K27me3, only-H3K27me3, and only-H2AK121ub marked genes in the different mutants Fig. . For thiclf28swn7 and significantly decreased in bmi1abc compared to WT as previously described28  is most probably due to the presence of RING1 activity in this knockdown mutant. All together, these data indicate that all these proteins are required for appropriate H3K27me3 marking at H2AK121ub/H3K27me3 genes. On the contrary, average global H3K27me3 levels at only-H3K27me3 genes were significantly affected in clf28swn7 and lhp1 but not in strong bmi1abc, weak ring1ab, and unexpectedly emf1-2  analysis of genes with increased H3K27me3 levels in emf1-2 showed an enrichment in processes involved in photosynthesis and response to light, corresponding to genes marked with H3K27me3 in both WT and emf1-2 roots . Interestingly, average expression levels of only-H2AK121ub genes are higher than H2AK121ub/H3K27me3 or only-H3K27me3 (ref. 28), which may argue against a repressive role of this modification. In line with this, a recent report proposed that H2AK121ub at H2AK121ub/H3K27me3-marked genes does not play a repressive role by itself, as despite it allows recruitment of PRC2, and thus gene repression, the removal of H2AK121ub at these genes seems to prevent gene reactivation by interfering with active H3K27me3 demethylation32. However, we found that the expression levels of only-H2AK121ub-marked genes were significantly lower than non-PcG active genes, supporting that this modification may play a role in modulating gene expression.While the association of PRC2 marking and gene repression is widely accepted in plants, PRC1-mediated H2AK121ub has been recently proposed to be associated with gene responsiveness45. Therefore, to understand PcG function it is fundamental to determine whether PRC1, PRC2, or their respective hallmarks play a role in regulating chromatin accessibility. Our data revealed that indeed PcG activities regulate chromatin accessibility. We found that reduced levels of H2AK121ub led to increased chromatin accessibility, whereas increased levels of this modification caused the opposite effect, supporting a role of this modification in regulating chromatin accessibility. It might be argued that the BMI1 proteins rather than H2AK121ub marks are the ones responsible for this effect. However, this role is supported by the fact that accessibility changes associated with the levels of H2AK121ub are observed in clf28swn7. In this mutant, the expression of BMI1s is not altered and the recruitment of the BMI1s should not be affected, as PRC1 recruitment is independent of PRC2. In any case, our data cannot rule out the possibility of a direct implication of BMI1 proteins in regulating chromatin accessibility instead of H2AK121ub.Nevertheless, although it is true that inaccessible chromatin is refractory to gene expression, chromatin accessibility by itself does not impose a transcriptional state32.We also found that H2AK121ub associates with transcriptional regulation hotspots, which are sites enriched for the binding of a wide variety of TFs, and thus, required for transcriptional responses. Hence, we propose that H2AK121ub marks help to create a less accessible although still permissive chromatin at these regulatory hotspots Fig. . This is25. Accordingly, loss of EMF1 function affected H3K27me3 levels but not H2AK121ub. However, emf1-2 ChIP-seq results showed that not all H3K27me3-marked genes display reduced levels. Furthermore, emf1-2 phenotype suggests that EMF1 is dispensable for H3K27me3 marking at root tissue. Interestingly, a recent phylogenetic analysis of EMF1 showed that ancestral EMF1 gene duplicated twice resulting in three orthologous groups that, next to EMF1, contain three novel outparalogs46. This finding rises the possibility that these paralogs display EMF1-like functions in different tissues or in the regulation of different subsets of genes.In addition, our results indicate that chromatin accessibility can be further reduced by EMF1. This plant-specific protein has been shown to associate with PRC2 and to be required for H3K27me3 markingemf1-2 displayed higher chromatin accessibility than clf28swn7, indicating that EMF1 acting upstream H3K27me3 marking plays an important role in regulating chromatin accessibility. Interestingly, EMF1 has the ability to in vitro mediate chromatin compaction20. Local and/or higher order chromatin compaction affects chromatin accessibility45. Furthermore, local chromatin compaction has been shown to precede the establishment of H3K27me3 in mouse embryonic stem cells47, which supports the connection between EMF1 and PRC2 activity. EMF1 ability to in vitro compact chromatin is shared with Drosophila PRC1 component Psc20, which combines BMI1 and EMF1 functions in a single polypeptide48, and with vertebrate Cbx2 (ref. 13), which is one of the Pc homologs49, indicating that, unlike in animals, EMF1 function in plants is associated to PRC2.In any case, we found that the H3K27me3-marked genes that lose H3K27me3 in Based on our results, we also propose that chromatin at H2AK121ub/H3K27me3-marked genes associates with inaccessible but responsive chromatin, most likely due to the presence of H2AK121ub-marked transcriptional regulation hotspots, which may be important to allow gene reprogramming Fig. . Convers16. We found this result surprising, as one would have predicted that these effects would yield at least locally increased chromatin accessibility. In any case, under our experimental conditions and integrating chromatin accessibility, histone marks levels, and expression data in different PcG mutants, we were able to show that the loss of PcG activities in Arabidopsis leads to increased chromatin accessibility at PcG targets. Furthermore, our findings indicate that this increased chromatin accessibility is not caused by gene expression, which explains the lack of transcriptional activation of many PcG target genes that lose PcG marks in mutant plants43.In vertebrate, a recent report showed that despite PcG target promoters exhibit reduced chromatin accessibility, removal of PRC1, but not PRC2, causes reduced nucleosome occupancy and increase nucleosome spacing without affecting chromatin accessibilityArabidopsis thaliana WT Col-0, bmi1abc8, clf28swn7 (ref. 33), emf1-2 (ref. 50), lhp1 (ref. 51), and ring1ab34 mutants were grown under long-day condition (16 h of light/8 h of dark) at 22 °C on MS agar plates containing 1% sucrose and 0.7% agar.52. Briefly, nuclei from 10-day-old whole seedlings were separated from other cellular debris by passing the nuclei suspension through a sucrose cushion during centrifugation. After centrifugation, the contaminating organelles and debris are visible at the top of the tube and nuclei at the bottom. Next, 30,000 nuclei were counted and resuspended in 50 μL transposition reaction mix using the TruePrepTM DNA Library Prep Kit V2 for Illumina® . Reactions were incubated for 30 min at 37 °C before isolation DNA using the VAHTSTM DNA Clean Beads . Two independent biological replicates were processed for next-generation sequencing library preparation. Libraries were prepared by PCR amplification using two index (i5 and i7) Illumina barcodes  with 13 cycles. Libraries were purified with a VAHTSTM DNA Clean Beads. ATAC libraries were sequenced on Illumina Hiseq-Xten PE150 by generating 2 × 150-bp paired-end reads.Nuclei isolation of ATAC-seq experiments were performed as previously described following the sucrose sedimentation protocol53. The organelle genomes were excluded from the TAIR10 Arabidopsis reference genome before reads were mapped using bowtie. PCR duplicates were discarded from the mapped reads using Picard . Regions with an artifactual massive amount of unique mapped reads were identified. Specifically, 91 regions were collected into a list of blacklisted genomic regions (Supplementary Data lm (linear model) function in R. The overall significance of the regression analysis was carried out using the F-test.We obtained around 45 million paired-end reads for each independent biological replicates of the different genotypes. Quality trimming and adapters removal were performed using Trimmomatic54 was used to study the location of THS around the TSS. The percentages of consensus THSs located nearby histone marks were determined using different functions from deepTools.The bioconductor R package ChipseekeRArabidopsis thaliana  have been determined in this study by reanalyzing in a uniform manner 100 independent ChIP-seq datasets previously published covering most TF families in bmi1abc, clf28swn7, and WT at 7 DAG, and H2AK121ub data of lhp1 at 7 DAG were previously generated28. H2AK121ub and H3K27me3 ChIP-seq data of WT, ring1ab, emf1-2, and H3K27me3 data of lhp1 at 10 DAG were generated for this work.H2AK121ub and H3K27me3 ChIP-seq data of 55. In brief, whole seedlings were fixed in 1% formaldehyde. Chromatin was extracted from fixed tissue and fragmented using a Bioruptor® Pico (Diagenode) in fragments of 200–500 bp. The sheared chromatin was immunoprecipitated overnight using the following antibodies: Anti-H2Aub  and anti-H3K27me3 . Immunocomplexes were captures using Protein A Sepharose beads CL-4B . After washing the Protein-A beads, chromatin was eluted and the crosslinking was reversed overnight at 65 °C. The DNA from the immunoprecipitated chromatin was treated with RNase and proteinase K and purified by phenol–chloroform extraction followed by ethanol precipitation. For ChIP-seq, two immunoprecipitations from independent biological replicates were processed for next-generation sequencing library preparation. All libraries were prepared with end repair, A-tailing and ligation of Illumina-compatible adapters using the Ovation® Ultralow Library Systems (NuGEN). The ligated product was amplified with 14 cycles of PCR. DNA of a size range between 200 and 600 bp was purified from an agarose gel. Amplification was confirmed by testing an aliquot of the library before and after amplification by qPCR. Libraries were sequenced on Illumina Hiseq-Xten PE150 by generating 2 ×  150-bp paired-end reads.ChIP-seq experiments were performed as previously described56 was used to map reads to the TAIR10 Arabidopsis reference genome. The tool boxes for the analysis of high-throughput sequencing data deepTools57 and samtools58 were used to generate bigwig files storing H3K27me3 and H2AK121ub genome-wide signal levels measured as CPM (counts per million). Specifically, the function bamCoverage was used to compute normalized signal levels using the parameter –normalizeUsing CPM. Mark peaks were detected using MACS2 (ref. 59) with default parameters for each individual replicate of the WT genotype. Specifically, the function bamCoverage was used to compute normalized signal levels using the parameter –normalizeUsing CPM. Mark peaks were detected using MACS2 (ref. 59) with default parameters for each individual replicate of the WT genotype. A specific input for each of the two datasets was considered, namely an input for the previously published data corresponding to 7 DAG and another specific input for the data generated in this study from 10 DAG seedlings. The final set of mark peaks were defined as the intersection of the ones detected for each replicate and the combination obtained from the 7 DAG and 10 DAG WT data using bedtools60. Target genes were associated to mark peaks using the bioconductor R package ChIPpeakAnno61 when an overlap was detected with either the gene body or promoter defined as the region 750 bp upstream from the TSS. A matrix was constructed were rows represented marked genes and columns the different genotype samples. For each marked gene a signal level in each one of the genotype samples under study was computed as the average signal across the corresponding histone mark peak. In order to remove noisy peaks, we filtered out genes with signals below 3 CPM, approximately corresponding to the 5% lower percentile of the signal distribution. After log2 transformation of the filtered matrix the bioconductor R package limma62 was used to identify significantly reduced or increased histone mark signal levels in the different mutants when compared to the WT.Each sample for the different genotypes generated approximately 12 million paired-end reads. Bowtie69. The statistical significance of differences in metagene plots were assessed using the non-parametric Mann–Whitney–Wilcoxon test implemented in the Wilcox.test funcion in R. Similarly, the identification of binding sites for the TFs under analysis was performed using bowtie for read mapping and macs2 for peak calling.Metagene plots were generated with a custom R script available from our github repository (10.5281/zenodo.4304639)63. In brief, 10-day-old WT seedlings were fixed in 1% formaldehyde. Chromatin was extracted from fixed tissue and fragmented using a Bioruptor® Pico (Diagenode) in fragments of 500–1000 bp. ChIP was first performed with anti-H3K27me3 . Immunocomplexes were captures using Protein A Sepharose beads CL-4B . After washing the Protein-A beads, one fraction was processed as in a conventional ChIP assay in order to revert the crosslinking and purify the DNA, and another fraction was used to elute the immunoprecipitated protein–DNA complexes in Re-ChIP elution buffer  by incubation for 30 min at 37 °C. The eluate was diluted 20 times with ChIP dilution buffer supplemented with 50 μg of BSA and protease inhibitor. Then, the second ChIP was performed with anti-H2Aub . Immunocomplexes were captures using Protein A Sepharose beads CL-4B . After washing the Protein-A beads, chromatin was eluted, de-crosslinked, and the DNA was extracted. The DNA obtained in the two sequential ChIPs were used as PCR template to amplify PLT5, SOC1, and AG using specific primers  from 10-day-old whole seedlings following the manufacturer´s instructions. Three independent biological replicates were processed for next-generation sequencing library preparation. Libraries were prepared using 1 μg of total RNA with the VAHTSTM Total RNA-seq (H/M/R) Library Prep Kit for Illumina®  according to the manufacturer’s instructions. Libraries were sequenced on Illumina Hiseq-Xten PE150 by generating 2 × 150-bp paired-end reads.Total RNA was extracted using E.Z.N.A.Arabidopsis reference genome was carried out using HISAT2 (ref. 64). Transcript assembly and gene expression estimation measured as FPKM (fragments per kilobase of exon and million of mapped reads) were computed using Stringtie65 and the bioconductor R package ballgown66. Differential gene expression analysis was performed using the bioconductor R package limma62. Specifically, a log2 fold-change of ±1 and a p value of 0.05 was used to determine activated, repressed, and unaltered genes. GO enrichment analysis was performed over the different gene sets of interest using the bioconductor R package clusterProfiler67. PCA was carried out using the R package FactoMineR v2.3 (ref. 68).Each independent biological replicate of the different genotypes generated approximately 20 million paired-end reads. Quality control was performed using FASTQC. Read mapping to the TAIR10 Further information on research design is available in the Supplementary InformationPeer Review FileReporting SummaryDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4