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. 2024 Jun 28;10(26):eadn4149.
doi: 10.1126/sciadv.adn4149. Epub 2024 Jun 26.

H3K9 methylation regulates heterochromatin silencing through incoherent feedforward loops

Kannosuke Yabe  1 , Asuka Kamio  1 , Satoyo Oya  1 , Tetsuji Kakutani  1 , Mami Hirayama  1 , Yuriko Tanaka  1 , Soichi Inagaki  1
Affiliations

H3K9 methylation regulates heterochromatin silencing through incoherent feedforward loops

Kannosuke Yabe et al. Sci Adv. .

Abstract

Histone H3 lysine-9 methylation (H3K9me) is a hallmark of the condensed and transcriptionally silent heterochromatin. It remains unclear how H3K9me controls transcription silencing and how cells delimit H3K9me domains to avoid silencing essential genes. Here, using Arabidopsis genetic systems that induce H3K9me2 in genes and transposons de novo, we show that H3K9me2 accumulation paradoxically also causes the deposition of the euchromatic mark H3K36me3 by a SET domain methyltransferase, ASHH3. ASHH3-induced H3K36me3 confers anti-silencing by preventing the demethylation of H3K4me1 by LDL2, which mediates transcriptional silencing downstream of H3K9me2. These results demonstrate that H3K9me2 not only facilitates but orchestrates silencing by actuating antagonistic silencing and anti-silencing pathways, providing insights into the molecular basis underlying proper partitioning of chromatin domains and the creation of metastable epigenetic variation.

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Figures

Fig. 1.
Fig. 1.. H3K36, as a putative anti-silencer, is induced by H3K9me2/mCH.
(A) Hypothetical factors that modulate silencing triggered by H3K9me2/mCH. (B) Screening for other chromatin features that are correlated with the loss of H3K4me1 triggered by H3K9me2/mCH in ibm1. Pearson’s R2 (coefficient of determination) values for factors positively correlated with the loss of H3K4me1 (silencer candidates) and −R2 values for factors negatively correlated with the loss of H3K4me1 (anti-silencer candidates) are shown. (C) Correlations between H3K36me3 levels (20) (left) and H2Bub levels (44) (right) and the “decrease in H3K4me1 in ibm1” (see Materials and Methods) are shown as scatter plots, linear regression lines, and Pearson’s R2. Each dot represents a gene that accumulates H3K9me2 in ibm1. n = 3395. (D) Intragenic patterns of H3K36me3 and H2Bub in WT around genes categorized by H3K9me2 and H3K4me1 changes in ibm1. Among 3395 genes that accumulate H3K9me2 in ibm1 (“H3K9me2 up”), 722 genes showed clear decreases in H3K4me1 (“H3K4me1 down”), but others did not (“H3K4me1-stay”) (18). (E) H3K36me3 [reads per kilobases per million mapped reads (RPKM)] in ibm1 and ldl2 for all genes (blue) and genes accumulating H3K9me2 in ibm1 (red). (F) Intragenic patterns of H3K36me3 (top) and H3K4me1 (bottom) around genes categorized by H3K9me2 and H3K36me3 changes in ibm1. (G and H) H3K36me3 (G) and H3K4me1 (H) levels (RPKM) in WT and mutants. Each circle represents each gene in gene groups categorized by H3K9me2 and H3K36me3 changes in ibm1 [same as (F)]. In the boxplots, the centerline corresponds to the median, the notch represents the 95% confidence interval of the median, the upper and lower limits of the box correspond to the upper and lower quartiles, and the whiskers indicate the data range within 1.5× of the interquartile range (IQR). The P values are based on paired t tests.
Fig. 2.
Fig. 2.. ASHH3 mediates H3K9me2/mCH-triggered H3K36me3 to prevent the loss of H3K4me1.
(A) Model depicting the H3K36me3 promotion by H3K9me2/mCH, which prevents the H3K4me1 loss by LDL2. (B) Four-week-old WT, ashh3, ibm1, and ibm1 ashh3 plants. (C and D) Kernel density plots showing the log2 ratio of RPKM [H3K36me3 (C) and H3K4me1 (D)] between indicated samples. Gene categories are the same as Fig. 1 (F to H); “H3K9me2 up H3K36me3 up (164),” “H3K9me2 up H3K36me3 down (445),” and “H3K9me2 up H3K36me3 stay (2785).” (E) Browser views of H3K9me2, H3K4me1, and H3K36me3 in ibm1 and ashh3 around genes that have increased H3K9me2 and H3K36me3 in ibm1. (F) Scatter plots comparing H3K4me1 changes (left) and H3K36me3 changes (right), with mRNA changes between WT and mutants. Dots represent expressed genes with increased H3K9me2 in 1G ibm1 (352 genes). Lines represent linear regression and shaded areas represent 95% confidence intervals. Spearman’s correlation coefficient ρ is shown for each WT-mutant comparison. *: 0.01 < P value < 0.05; ***P value < 0.0001. (G) FLAG-ASHH3 localization in WT and ibm1 plants around genes with increased H3K9me2 and H3K36me3 in ibm1 [shown in (E)]. WT on top is the nontransgenic negative control. (H) Average profiles of FLAG-ASHH3 and H3K9me2 around genes categorized as (C) (top) and heatmaps around genes in “H3K9me2 up H3K36me3 up” category, sorted by FLAG-ASHH3 level in ibm1 (bottom). (I) Difference of FLAG-ASHH3 signal between WT and ibm1 in two independent transgenic lines, TG1 and TG2. Blue dots indicate all genes and red dots indicate 497 genes with more ASHH3 accumulation in ibm1 than in WT. (J) Enrichment analysis of the genes with ASHH3 accumulation in ibm1 (I) in genes categorized by H3K9me2 and H3K36me3 changes in ibm1. The color indicates the P value of the hypergeometric test. (K) Pattern of FLAG-ASHH3 and H3K36me3 in WT around 2029 ASHH3-bound genes and other protein-coding genes (PCGs).
Fig. 3.
Fig. 3.. LDL2 facilitates TE silencing by removing H3K4me1.
(A) A model depicting the H3K9me2/mCH-promoted H3K36me3 by ASHH3, which prevents the loss of H3K4me1 mediated by LDL2. Transcribed sequences are targeted by IBM1 for H3K9 demethylation (14). Therefore, the antagonistic actions of LDL2 and ASHH3 are predicted to affect H3K9me2/mCH dynamics through feedback regulation. (B) Experimental design for analyzing the function of LDL2 in TE silencing. (C) Effects of ldl2 mutation on mCHG (left) and mCHH (right) establishment in sxc (x axis) and cxs (y axis). Each dot represents a TE-encoded gene (“TE gene”; n = 3728), and red dots represent “LDL2-regulated TE genes” (n = 194), which show lower mCHG in sxc ldl2 and cxs ldl2 than in sxc LDL2 and cxs LDL2, respectively (see Materials and Methods). Averages of biological replicates are plotted. (D) Averaged profiles of mCHG and mCHH in WT and four F1 lines around all TE genes (left) and LDL2-regulated TE genes (right). (E and F) H3K9me2 (E) and H3K4me1 (F) patterns in WT and four F1 lines around all TE genes (top) and LDL2-regulated TE genes (bottom). (G) mRNA levels [log2 of transcripts per million (TPM) + 0.05] of LDL2-regulated TE genes in WT, parental mutant plants, and F1 plants. Each circle represents each TE gene. In the boxplots, the centerline corresponds to the median, the notch represents the 95% confidence interval of the median, the upper and lower limits of the box correspond to the upper and lower quartiles, and the whiskers indicate the data range within 1.5× of the IQR. The P values are based on paired t tests. n.s., not significant.
Fig. 4.
Fig. 4.. ASHH3 counteracts the silencing of several TEs.
(A) Experimental design for analyzing the function of ASHH3 in TE silencing. (B) Effects of ashh3 mutation on mCHG (left) and mCHH (right) establishment in sxc (x axis) and cxs (y axis). Each dot represents a TE gene (n = 3551), and red dots represent ASHH3-regulated TE genes (n = 14), which show higher mCHG in sxc ashh3 and cxs ashh3 than in sxc ASHH3 and cxs ASHH3, respectively (see methods). Averages of biological replicates are plotted. (C and D) Averaged profiles of mCHG (C) and mCHH (D) in WT and four F1 lines around all TE genes (left) and ASHH3-regulated TE genes (right). (E to G) H3K9me2 (E), H3K36me3 (F), and H3K4me1 (G) patterns in WT and four F1 lines around all TE genes (top) and ASHH3-regulated TE genes (bottom). (H) Volcano plot of mRNA-seq comparing TPM of cxs ashh3 and cxs ASHH3. Blue dotted lines represent FDR = 0.05. Blue dots represent all genes including protein-coding genes and TE genes (n = 33,603), and red dots represent ASHH3-regulated TE genes.
Fig. 5.
Fig. 5.. A model of the mechanism that partitions epigenetic marks by counteracting LDL2 and ASHH3.
When H3K9me2/mCH accumulates in the transcribed region of genes or TEs, genes/TEs with high levels of H3K36me3 are kept in active chromatin status by the concerted functions of ASHH3 and IBM1 (left). Meanwhile, genes/TEs with lower levels of H3K36me3 cannot attract ASHH3, and thus silencing is established through the removal of H3K4me1 by LDL2 (right).
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