A role for MED14 and UVH6 in heterochromatin transcription upon destabilization of silencing

Abstract

Constitutive heterochromatin is associated with repressive epigenetic modifications of histones and DNA which silence transcription. Yet, particular mutations or environmental changes can destabilize heterochromatin-associated silencing without noticeable changes in repressive epigenetic marks. Factors allowing transcription in this nonpermissive chromatin context remain poorly known. Here, we show that the transcription factor IIH component UVH6 and the mediator subunit MED14 are both required for heat stress-induced transcriptional changes and release of heterochromatin transcriptional silencing in Arabidopsis thaliana. We find that MED14, but not UVH6, is required for transcription when heterochromatin silencing is destabilized in the absence of stress through mutating the MOM1 silencing factor. In this case, our results raise the possibility that transcription dependency over MED14 might require intact patterns of repressive epigenetic marks. We also uncover that MED14 regulates DNA methylation in non-CG contexts at a subset of RNA-directed DNA methylation target loci. These findings provide insight into the control of heterochromatin transcription upon silencing destabilization and identify MED14 as a regulator of DNA methylation.

Figure S1.. Heat stress–induced release of silencing does not require ARP6 and AtMORC6.

Transcript accumulation in rosette leaves from Col-0 WT, arp6-1, and atmorc6-3 mutants was quantified by RT-qPCR at five loci overexpressed in heat stress. Samples had been subjected to a control stress at 23°C or a heat stress treatment at 37°C. Data were normalized to the geometric mean of the reference genes AT5G12240 and ACT2. Values were further normalized to the mean of WT samples at 23°C. Error bars indicate standard errors of the mean across three biological replicates. For each locus, differences in mean at 37°C between the WT and the mutants was tested using unpaired two-tailed t test, but did not reveal any significant difference (P > 0.05).

Figure 1.. Heat stress releases heterochromatin silencing without altering DNA methylation.

(A) Scheme representing the method used to submit rosette leaves to a control stress (23°C) or a heat stress (37°C). The L5-GUS transgene is reactivated in leaves subjected to heat stress. GUS: β-glucuronidase. (B) RT-qPCR analysis of transcripts from MULE-AT2G15810 and the L5-GUS transgene in L5 transgenic plants at 23 or 37°C, normalized to the reference gene AT5G12240 and further normalized to the mean of L5 samples at 23°C. Error bars represent standard error of the mean across three biological replicates. (C) RT-qPCR analysis of transcripts from endogenous repeats in L5 transgenic plants at 23 or 37°C (Transcriptionally Silent Information [TSI]). Amplification of 18S rRNA was used as a loading control. PCR in the absence of reverse transcription (RT-) was performed to control for genomic DNA contamination. (D) (top) Transcriptional changes in WT plants subjected to heat stress represented along chromosomes by log2 ratios (37/23°C) of mean reads per kilobase per million mapped reads (RPKM) values calculated in 100 kb windows. (bottom) Density of TEs detected as significantly up-regulated in WT plants subjected to heat stress is plotted in red (left y axis) with total TE density in grey (right y axis), both calculated by 100-kb windows. Windows containing up-regulated ONSEN elements (AtCOPIA78) are marked with an asterisk. (E) Average cytosine methylation levels by 500-kb windows calculated in CG, CHG, and CHH contexts in a WT subjected to a control stress (23°C) or to heat stress (37°C). (F) PCGs or TEs up-regulated in heat-stressed WT plants were aligned at their 5′-end or 3′-end and average cytosine methylation levels in the indicated nucleotide contexts were calculated from 3 kb upstream to 3 kb downstream in a WT subjected to a control stress (23°C) or to heat stress (37°C). Upstream and downstream regions were divided in 100 bp bins, whereas annotations were divided in 40 bins of equal length.

Figure S2.. DNA methylation levels at 23 and 37°C.

(A) PCGs and TEs were aligned at their 5′-end or 3′-end and average cytosine methylation levels in the indicated nucleotide contexts were calculated from 3 kb upstream to 3 kb downstream in WT subjected to a control stress (23°C) or to heat stress (37°C). Upstream and downstream regions were divided in 100 bp bins, whereas annotations were divided in 40 bins of equal length. (B) Average cytosine methylation levels at PCGs or TEs up-regulated or down-regulated in heat-stressed WT plants were calculated and represented as in (A).

Figure 2.. Mutants for UVH6 and MED14 are impaired in heat stress–induced release of silencing.

(A) Heat stress—induced activation of the L5-GUS transgene in rosette leaves of WT (L5 background) and mutants after 24 h at 23°C or 37°C detected by histochemical β-glucuronidase (GUS) staining. (B) RT-qPCR analysis of transcripts from the L5-GUS transgene in rosette leaves of WT and mutants, normalized to the reference gene AT5G12240 and further normalized to the mean of WT samples at 23°C. Error bars represent standard error of the mean across three biological replicates. (C) RT-PCR analysis of transcripts from endogenous repeats. Amplification of 18S rRNAs was used as a loading control. PCR in the absence of reverse transcription (RT-) was performed to control for genomic DNA contamination. (D) Representative pictures of 16-d-old seedlings of the indicated genotypes grown in soil and in long day conditions. Scale bar: 1 cm. (E) Heat survival assays. 7-d-old seedlings of the indicated genotypes were subjected to a 37°C heat stress for 24 h or 48 h and returned to standard conditions for 9 d. Pictures are representative of five replicates for the 24 h stress and two replicates for the 48 h stress. (F) Heat stress–induced activation of the L5-GUS transgene in rosette leaves of the indicated genotypes after 24 h at 37°C detected by GUS staining. (G) Top: Gene models for MED14 and UVH6, to scale. Punctual mutations (in orange) and their corresponding amino acid changes are indicated by vertical lines, their position relative to the transcriptional start site (+1) is given. Insertional T-DNA mutations are indicated by triangles. Location of the med14-1 mutation is reported according to Autran et al (2002). Bottom: Representation of MED14 and UVH6 proteins and their domains. The relative length of MED14 and UVH6 are not to scale. Point mutations and their corresponding amino acid changes are indicated by vertical lines. In MED14, LXXLL motifs have been indicated by black boxes. In UVH6, helicase motifs I, Ia, II, III, IV, V, and VI are indicated by transparent white boxes, respectively, from left to right. The positions of the domains were inferred from studies in other model organisms (see the Materials and Methods section). HD, helicase domain; KID, knob interaction domain; RM, repeat motif; TID, tail interaction domain.

Figure S3.. Mapping of zen mutations, and late flowering phenotype of zen1 mutants.

(A) Histochemical β-glucuronidase (GUS) staining of heat-stressed rosette leaves from a complementation test between zen1 and zen2 mutants. WT in L5 background. (B) Late flowering phenotype of zen1 mutants as shown by late emergence of floral buds (left) and increased leaf number at bolting (right) in zen1 mutants. Histograms (right) represent average leaf number and error bars indicate standard deviations from two plants. (C, D) Segregants with a suppressor phenotype in an F2 population from a mutant (Col-0) × Ler-0 cross were sequenced in bulk. Y-axis indicates single-nucleotide polymorphism frequencies along 20-kb windows. The SNP-depleted chromosomal region encompasses homozygous candidate mutations, as indicated by an orange rectangle. (C) zen1 mapping (D) zen2 mapping.

Figure S4.. Amino acid sequence alignment of UVH6 orthologs.

Protein sequence alignment of UVH6/XPD orthologs from Saccharomyces cerevisiae (Sc_RAD3), Homo sapiens (Hs_XPD), and A. thaliana UVH6 (At_UVH6). The alignment was performed with Clustal Omega (v1.2.4). UVH6 point mutations and their corresponding amino acid changes are indicated.

Figure S5.. Identification of the uvh6-4 mutation.

(A) Heat stress–induced activation of the L5-GUS transgene in rosette leaves of WT (L5 background) and mutants after 24 h at 37°C was detected by β-glucuronidase (GUS) staining. (B) RT-qPCR analysis of transcripts from L5-GUS and MULE, normalized to the reference gene AT5G12240 and further normalized to the mean of WT samples at 23°C. Errors bars represent standard error of the mean across two biological replicates. Statistically significant differences between means of uvh6-3 and uvh6-4 samples at 37°C were tested using unpaired unilateral t tests (*P < 0.05, **P < 0.005). (C) Representative pictures of 16-d-old seedlings of the indicated genotypes grown in soil and in long day conditions. Scale bar: 1 cm.

Figure 3.. Transcriptomic analysis of med14 and uvh6 mutants at 23°C.

(A) Number of PCGs and TEs detected as DEGs in med14-3, uvh6-3 and uvh6-4 relative to the WT at 23°C. (B) Venn diagrams showing the extent of the overlap between up-regulated and down-regulated loci determined in med14-3 and uvh6-4.

Figure S6.. Analysis of uvh6 mutants at 23°C and in response to UV irradiation.

(A) Reads per kilobase per million mapped reads (RPKM) values in the WT (L5 background) and uvh6-3 mutants of loci significantly up-regulated and down-regulated in uvh6-4 at 23°C. Statistical differences between distributions in WT and uvh6-3 were tested using unpaired two-sided Mann–Whitney tests. (B) UV survival assays. 7-d-old seedlings of the indicated genotypes were UV irradiated at 10 kJ/m² and returned to standard conditions with 24 h of dark followed by 5 d recovery in light.

Figure 4.. Transcriptomic analysis of med14 and uvh6 mutants at 37°C.

(A) Transcriptional changes in WT (L5 background) plants subjected to heat stress (top), in med14-3 at 37°C (middle) and uvh6-3 at 37°C (bottom) relative to the WT at 37°C, represented along the chromosome five by log₂ ratios of mean reads per kilobase per million mapped reads (RPKM) values calculated in 100 kb windows. (B) Number of PCGs and TEs detected as DEGs in med14-3 at 37°C and uvh6-3 at 37°C relative to the WT at 37°C. (C) Venn diagrams showing the extent of the overlap between up-regulated and down-regulated loci determined in med14-3 at 37°C and uvh6-3 at 37°C. (D) Log₂ fold change values at 37°C versus 23°C in med14-3 (left) and uvh6-3 (right) plotted against the log₂ fold change values at 37°C versus 23°C in the WT (x axis), considering TEs up-regulated in heat-stressed WT plants.

Figure S7.. Chromosome-wide transcriptional changes in med14 and uvh6 mutants at 37°C.

Transcriptional changes in WT (L5 background) plants subjected to heat stress (top), in med14-3 at 37°C (middle) and uvh6-3 at 37°C (bottom) relative to WT at 37°C, represented along chromosomes one to four by log₂ ratios of mean RPKM values in 100 kb windows.

Figure S8.. Impact of med14 and uvh6 mutations on heat-induced transcriptional changes.

(A, B) Reads per kilobase per million mapped reads (RPKM) log₂ values in the WT (L5 background) at 37°C, med14-3 at 37°C (left), and uvh6-3 at 37°C (right) of PCGs up-regulated (A) or down-regulated (B) in heat-stressed WT plants. (C) RPKM log₂-fold change (log₂FC) values of DEGs, including PCGs and TEs, in med14-3 at 37°C (left) and uvh6-3 at 37°C (right). DEGs were calculated relative to WT plants at 37°C.

Figure S9.. Enrichment in transcription factor binding sites and distribution of TE superfamilies at MED14- and UVH6-dependent loci.

(A–C) TF binding sites showing significant enrichment at the indicated gene sets relative to random sets of the same number of genes (two-sided two proportion Z-test, P-value Bonferroni adjusted <0.05 and −log10 [P-value] >2). The number of genes containing binding sites for the corresponding TFs are indicated in white. TF binding site data were retrieved from published datasets (O’Malley et al, 2016). (D) Reads per kilobase per million mapped reads (RPKM) log₂ values in the WT (L5 background) at 37°C, med14-3 at 37°C (left) and uvh6-3 at 37°C (right) of TEs up-regulated in heat-stressed WT plants. (E) Relative frequency of TE superfamilies in the Arabidopsis genome (TAIR10, white) and the following datasets: TEs up-regulated in WT plants subjected to heat stress (red), among these, TEs down-regulated in med14-3 at 37°C (dark blue) or in uvh6-3 at 37°C (green) relative to the WT at 37°C.

Figure S10.. Genetic epistasis analysis of med14-3 and uvh6-3 mutations.

Accumulation of transcripts from six target loci was analyzed by RT-qPCR in WT (L5 background) control plants, med14-3, uvh6-3 mutants, and med14-3 uvh6-3 double mutants at 23 and 37°C. The primer pairs for the following targets potentially amplify multiples copies, indicated between brackets: ATCOPIA28 (AT1TE43225 and AT3TE51900) and ONSEN (AT3TE54550, AT3TE92525, AT5TE15240, AT1TE12295, AT1TE24850, AT1TE59755, and AT1TE71045). Data were normalized to the reference gene AT5G12240 and further normalized to the mean of WT samples at 23°C. Error bars illustrate standard errors of the mean across three biological replicates. For each temperature treatment, statistical differences between means of mutant conditions were tested using ANOVA followed by post hoc analysis using Tukey's honest significant difference test (*P < 0.05, **P < 0.005, ***P < 0.0001). see the Materials and Methods section. Data for the L5-GUS transgene was already displayed in Fig 2B.

Figure 5.. MED14 promotes transcript accumulation of heterochromatic loci.

(A) Venn diagrams showing the up-regulated TEs in ddm1 and mom1 and their overlap. (B) Reads per kilobase per million mapped reads (RPKM) values in WT (L5 background) and indicated mutants of TEs commonly up-regulated between ddm1 and mom1. Progenies from sister plants were identically colored. Statistical differences between distributions of single mutants (ddm1 and mom1) versus double mutants (med14 ddm1, uvh6 ddm1, med14 mom1, uvh6 mom1) were tested using unpaired two-sided Mann–Whitney tests. (C) Transcripts from TSI and MULE loci were analyzed by RT-qPCR in rosette leaves from indicated genotypes at control temperature (23°C). Data were normalized to the reference gene AT5G12240 and further normalized to the mean of WT samples at 23°C. Error bars illustrate standard errors of the mean across three biological replicates. Statistically significant differences between means of mom1, ddm1, met1, and combinations of these mutations with med14-3 were tested using unpaired bilateral t tests. (D) DNA methylation levels at the CG, CHG, and CHH contexts of TEs up-regulated in heat-stressed WT samples, distinguishing TEs down-regulated in med14-3 at 37°C from TEs not down-regulated in med14-3 at 37°C (relative to WT at 37°C), were calculated in WT samples subjected to a control stress at 23°C. Statistical differences between datasets were tested using unpaired two-sided Mann–Whitney tests. (E) DNA methylation levels at CG, CHG, and CHH contexts in WT at 23°C were calculated for the indicated groups of TEs. RPKM values at TEs were calculated using multi- and uniquely mapped reads in WT and med14-3 in control conditions (23°C) (see the Materials and Methods section), and TEs above one RPKM in WT were grouped according to their log₂ fold change in med14-3. Statistical differences between datasets were tested using unpaired two-sided Mann–Whitney tests.

Figure S11.. MED14 preferentially targets loci with high levels of DNA methylation to promote transcript accumulation.

(A, B) Reads per kilobase per million mapped reads (RPKM) values in WT (L5 background) and the indicated mutants of TEs up-regulated in ddm1 (A) or mom1 (B). Sister plants were identically colored. Statistical differences between distributions of single mutants (ddm1 and mom1) versus double mutants (med14 ddm1, uvh6 ddm1, med14 mom1, and uvh6 mom1) were tested using unpaired two-sided Mann–Whitney tests. (C) TEs commonly up-regulated in ddm1 and mom1 were aligned at their 5′-end or 3′-end, and average cytosine methylation levels in the indicated nucleotide contexts were calculated from 3 kb upstream to 3 kb downstream in WT, ddm1, and mom1. The upstream and downstream regions were divided in 100-bp bins, whereas annotations were divided in 40 bins of equal length. (D, E) DNA methylation levels in a WT at 23 or 37°C in the CG, CHG, and CHH contexts were calculated for TEs up-regulated in heat-stressed WT samples, distinguishing TEs down-regulated (blue) from TEs not down-regulated (grey) in med14-3 (D) or uvh6-3 (E) at 37°C relative to the WT at 37°C.

Figure S12.. MED14 contributes a layer of silencing at the L5-GUS transgene and some endogenous TEs.

(A) Histochemical GUS staining of 13-d-old leaves (first pair) (top) and the genome-browser view of the RNA-seq data showing GUS transcript accumulation (bottom) in the indicated mutants. (B, C) The genome-browser views of RNA-seq data at selected TEs.

Figure 6.. MED14 controls DNA methylation at CHG and CHH sites.

(A) Kernel density plot of DNA methylation differences between med14-3 and WT (L5 background) at CG, CHG, and CHH contexts. (B) Number of 100-bp differentially methylated regions (DMRs) detected in med14-3 at CG, CHG, and CHH contexts with a minimum DNA methylation difference of 0.4, 0.2, and 0.2, respectively. (C) Chromosomal density of hypo-CHG (blue) and hypo-CHH DMRs (red) identified in med14-3 (top) with total TE density in grey (bottom), both calculated by 100-kb windows on chromosome 3. (D) DNA methylation levels in the CHH context in the indicated genotypes at med14-3 hypo-CHH DMRs. (E) DNA methylation levels in the CHH context in the indicated genotypes at 1,200 randomly selected regions of 100 bp.

Figure S13.. Effect of the med14-3 mutation on DNA methylation rates.

(A) TEs localized in chromosome arms or pericentromeres were aligned at their 5′-end or 3′-end, and average cytosine methylation levels in the indicated nucleotide contexts were calculated from 3 kb upstream to 3 kb downstream in WT (L5 background) and med14-3. Upstream and downstream regions were divided in 100-bp bins, whereas annotations were divided in 40 bins of equal length. (B) Average DNA methylation levels were calculated at PCGs as in (A). (C) DNA methylation levels in the CG, CHG, and CHH contexts in WT and med14-3 at med14-3 hypo-CHG differentially methylated regions (DMRs) (left) and med14-3 hypo-CHH DMRs (right).

Figure S14.. Overlap between med14 and RdDM mutants differentially methylated region.

(A) DNA methylation levels in the CHG context in WT (L5 background) and nrpb2-3 at med14-3 hypo-CHG differentially methylated regions (DMRs) (left) and med14-3 hypo-CHH DMRs (right). Two replicates (A, B) are shown for each genotype. (B) DNA methylation levels in the CHG context in the indicated genotypes at med14-3 hypo-CHG DMRs. (C) DNA methylation levels in the CHH context in WT and med14-3 at hypo-CHH DMRs identified in drm1/2, nrpd1, and nrpe1. Statistically significant differences between distributions in WT and med14-3 were tested using unpaired two-sided Mann–Whitney tests.