Transcriptional Dynamics and Chromatin Accessibility in the Regulation of Shade-Responsive Genes in Arabidopsis

  1. Sandi Paulisic
  2. Alessandra Boccaccini
  3. René Dreos
  4. Giovanna Ambrosini
  5. Nicolas Guex
  6. Ruben Maximilian Benstei
  7. Markus Schmid
  8. Christian Fankhauser

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Abstract

Open chromatin regions host DNA regulatory motifs that are accessible to transcription factors and the transcriptional machinery. In Arabidopsis, responses to light are heavily regulated at the transcriptional level. Shade, for example, can limit photosynthesis and is rapidly perceived by phytochromes as a reduction of red to far-red light ratio (LRFR). Under shade, phytochromes become inactive, enabling PHYTOCHROME INTERACTING FACTORs (PIFs), particularly PIF7, to promote genome-wide reprogramming essential for LRFR responses. An initial strong and fast regulation of shade-responsive genes is followed by attenuation of this response under prolonged shade. We wanted to determine whether the transcriptional response to shade depends on chromatin accessibility. For this, we used ATAC-seq to profile the chromatin of seedlings exposed to short (1h) and long (25h) simulated shade. We found that PIF7 binding sites were accessible for most early target genes before LRFR treatment. The transcription pattern of most acute shade-responsive genes correlated with a rapid increase in PIF levels and chromatin association at 1h, and its decrease at 25h of shade exposure. For a small subset of acutely responding genes, PIFs also modulate chromatin accessibility at their binding sites early and/or late in the response to shade. Our results suggest that in seedlings a state of open chromatin conformation allows PIFs to easily access and recognize their binding motifs, rapidly initiating gene expression triggered by shade. This transcriptional response primarily depends on a transient increase in PIF stability and gene occupancy, accompanied by changes in chromatin accessibility in a minority of genes.

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    Reply to the reviewers

    Manuscript number: RC-2025-02888

    Corresponding author(s): Christian, Fankhauser

    General Statements

    We were pleased to see that the three reviewers found our work interesting and provided supportive and constructive comments.

    Our answers to their comments and/or how we propose to address them in a revised manuscript are included in bold.

    1. Description of the planned revisions

    Reviewer #1 (Evidence, reproducibility and clarity (Required)):

    Summary: Plant systems sense shading by neighbors via the phytochrome signaling system. In the shade, PHYTOCHROME-INTERACTING FACTORS (PIFs) accumulate and are responsible for transcriptional reprogramming that enable plants to mobilize the "shade-avoidance response". Here, the authors have sought to examine the role of chromatin in modulating this response, specifically by examining whether "open" or "closed" chromatin regions spanning PIF target genes might explain the transcriptional output of these genes. They used a combination of ATAC-seq/CoP-qPCR (to detect open regions of chromatin), ChIP (to assay PIF binding) and RNA-seq (to measure transcript abundance) to understand how these processes may be mechanistically linked in Arabidopsis wild-type and pif mutant lines. They found that some chromatin accessibility changes do occur after LRFR (shade) treatment (32 regions after 1h and 61 after 25 h). While some of these overlap with PIF-binding sites, the authors found no correlation between open chromatin states and high levels of transcription. Because auxin is an important component of the shade-avoidance response and has been shown to control chromatin accessibility in other contexts, they examined whether auxin might be required for opening these regions of chromatin. They find that in an auxin biosynthesis mutant, there is a small subset of PIF target genes whose chromatin accessibility seems altered relative to the wild-type. Likewise, they found that chromatin accessibility for certain PIF targets is altered in phyB and pif mutant and propose that PIFs are necessary for changing the accessibility of chromatin in these genes. The authors thus propose that PIF occupancy of already open regions, rather than increased accessibility, underly the increase in transcript of abundance of these target genes in response to shade.

    Major comments: *• I find that the data generally support the hypothesis presented in the manuscript that chromatin accessibility alone does not predict transcription of PIF target genes in the shade. That said, I think that a paragraph from the discussion (lines 321-332) would benefit from some careful rephrasing. I think it is perfectly reasonable to propose that PIF occupancy is more predictive of shade-induced transcriptional output than chromatin accessibility, but I think that calling PIF occupancy "the key drivers" (line 323) or "the main driving force" (line 76) risks ignoring the observation that levels of PIF occupancy specifically do not predict expression levels of PIF target genes (Pfeiffer et al., 2014, Mol Plant). For PIL1 and HFR1, the authors have shown that PIF promoter occupancy and transcript levels are correlated, but the central finding of Pfeiffer et al. was that this pattern does not apply to the majority of PIF direct target genes. Finding factors (i.e. histone marks) that convert PIF-binding information into transcriptional output appears to have been the impetus for the experiments devised in Willige et al., 2021 and Calderon et al., 2022. It is great that the authors have outlined in the discussion that there are a number of factors that modulate PIF transcriptional activating activity but I think that the emphasis on PIF-binding explaining transcript abundance should be moderated in the text. *

    We appreciate the reviewers’ comments and will address it by introducing appropriate changes to the discussion. One element that should be pointed out is that the study of Willige et al., 2021 allows us to look at sites where PIF7 is recruited in response to the shade stimulus (a low R/FR treatment) and relate this to higher transcript abundance of the nearby genes. The study of Pfeiffer et al., 2014 which analyses PIF ChIP studies from several labs does not include this dynamic view of PIF recruitment in response to a stimulus. For example, this study re-analyses data from our lab, Hornitschek et al., 2012, in which we did PIF5 ChIP in low R/FR, but we did not compare that to high R/FR to enable an analysis of sites where we see recruitment of PIF5 in response to a shade cue. In the revised manuscript we will also include a new figure comparing PIF7 recruitment and changes in gene expression at direct PIF target genes.

    • I think that the hypothesis could be further supported by incorporating the previously published ChIP-seq data on PIF1, PIF3 and PIF5 binding. Given these data are published/publicly available, I think it would be helpful to note which of the 72 DARs are bound by PIF1, PIF3 and/or PIF5. Especially so given that PIF5 (Lorrain et al., 2008, Plant J) and PIF1/PIF3 (Leivar et al., 2012, Plant Cell) contribute at least in some capacity to transcriptional regulation in response to shade. At the very least, it might help explain some of the observed increases in nucleosome accessibility observed for genes that don't have PIF4 or PIF7-binding.* This is a thoughtful suggestion. Our choice to focus on PIF7 target genes is dictated by two reasons. First, the finding that amongst all tested PIFs, PIF7 is the major contributor to the control of low R/FR (neighbor proximity) induced responses in seedlings (e.g. Li et al., 2012; de Wit et al., 2016; Willige et al., 2021). In addition, the PIF7 ChIP-seq and gene expression data from the Willige et al., 2021 paper was obtained using growth conditions very similar to the ones we used, hence allowing us to compare it to our data. As the reviewer suggests, other PIFs also contribute to the low R/FR response and hence looking at ChIP-seq for those PIFs in publicly available data is also informative. One limitation of this data is that ChIP-seq was not always done in seedlings grown in conditions directly comparable to the conditions we used (except for PIF5, see above). Nevertheless, we have performed this analysis with the available data suggested by the reviewer and intend to include the results in the revised version of the manuscript, presumably updated Figure 4B.

    • In the manuscript, there are several instances where separate col-0 (wild type) controls have been used for identical experiments. Specifically, qPCR (Fig 3C, Fig S7C/D and Fig S8C/D), CoP-qPCR (Fig 5B/5C and Fig S8E/F) and hypocotyl measurements (Fig S7A/B and Fig S8A/B). In the cases of the hypocotyl measurements, there appear to be hardly any differences between col-0 controls indicating the measurements can be confidently compared between genotypes.

    We appreciate this comment but to be comprehensive, we like to include a Col-0 control for each experiment (whenever possible) and hence also include the data when available.

    • In some cases of qPCR and CoP-qPCR experiments however, the differences in values obtained from col-0 samples that underwent identical experimental treatments appear to vary significantly. In Figure 3C for example, the overall trend for PIL1 expression in col-0 is the same (e.g. HRFR levels are low, LRFR1 levels are much higher and LRFR25 levels drop down to some intermediate level) but the expression levels themselves appear to differ almost two-fold for the LRFR 1h timepoint (~110 on the left panel vs ~60 for the right panel). Given the size of the error bars, it appears that these data represent the mean from only one biological replicate. PIL1 expression levels at LRFR 1h as reported in Fig S7C and D also show similar ~2-fold differences.* This is a good comment. Having looked at PIL1 gene induction by low R/FR in dozens of similar experiments made us realize that indeed while the PIL1 induction is always massive, the extent is somewhat variable. Based on the data that we have (including from RNA-seq) we are convinced that this is due to the very low level of expression of PIL1 in high R/FR conditions. Given that induction by low R/FR is expressed as fold increase relative to baseline high R/FR expression, small changes in the lowly expressed PIL1 in high R/FR leads to seemingly significant differences in its induction by low R/FR across experiments.

    All qPCR data is represented by three biological replicates, and the variation between them per experiment is low, which is reflected in the size of the SD error bars. Data on technical and biological replicates in each panel will be clearly indicated in the revised figure legends.

    • I would recommend that the authors explicitly describe the number of biological replicates used for each experiment in the methods section. If indeed these experiments were only performed once, I think the authors should be very careful in the language used in describing their conclusions and in assigning statistical significance. One possibility that could also be helpful would be normalizing LRFR 1h and LRFR 25h values to HRFR values and plotting these data somewhere in the supplemental data. If, for example, the relative levels of PIL1 are different between replicates but the fold-induction between HRFR and LRFR 1h are the same, this would at least allay any concerns that the experimental treatments were not the same. I understand that doing so precludes comparison between genotypes, but I do think it's important to show that at least the control data are comparable between experiments.

    All qPCR and CoP-qPCR experiments have been performed with three 3 biological replicates as described in Materials and Methods section, and these are represented in the Figures. Relative gene expression in the qPCR experiments was normalized to two housekeeping genes YLS8 and UBC21 and afterwards to one biological replicate of Col-0 control in HRFR. As indicated for the previous comment information about replicates will be included in the updated figure legends.

    • Similarly, for the CoP-qPCR experiments presented in Fig 5B and 5C, the col-0 values for region P2 between Fig 5B and 5C shows that while HRFR and LRFR 1h look comparable, the values presented for LRFR 25h are quite different.

    This comment of the reviewer prompted us to propose a different way of representing the data that is clearer (new Figure 5B and 5C). We believe that this facilitates the comparison between the genotypes. Enrichment over the input was calculated for the chromatin accessibility of each region. Chromatin accessibility was further normalized against two open control regions on the promoters of ACT2 (AT3G18780, region chr3:6474579: 6474676) and RNA polymerase II transcription elongation factor (AT1G71080 region chr1:26811833:26811945). The difference between previous representation is that the regions are not additionally subtracted to Col-0 in HRFR. We will update the Materials and Methods and figure legend sections with this information.

    Minor comments: • Presentation of Supplemental Figure 7A/7B and Supplemental Figure 8A/8B could be changed to make the data more clear (i.e. side-by-side rather than superimposed).

    We propose changing the presentation of the hypocotyl length data to show the values for days side-by-side as the Reviewer suggests.

    • I think that the paragraph introducing auxin (lines 25-37) could be reduced to 1-2 sentences and merged into a separate introductory paragraph given that the SAV3 work makes up a relatively minor component of the manuscript.

    We agree with the reviewer and will reduce the paragraph about auxin and merge it with the previous paragraph about transcription.

      • For Figure 3A, I would strongly encourage the authors to show some of the raw western blot data for PIF4, PIF5 and PIF7 protein abundance (and loading control), not just the normalized values. This could be put into supplemental data, but I think it should accompany the manuscript.

    We agree that presenting the raw data that was used for quantification is important. We will include the western blots used for quantifying PIF4, PIF5 and PIF7 protein abundance (and loading control DET3). This information will presumably be included to the Supplementary Figure 3C (figure number to be confirmed once we decide on all new data to be presented).

    • Lines 145-147 "we observed a strong correlation between PIF4 protein levels (Figure 3A) and PIL1 promoter occupancy (Figure 3B), and a similar behavior was seen with PIF7 (Figure 3B)." According to Fig 3A, there is no statistically significant increase in PIF7 abundance after 1h shade. There is an apparent increase in PIF7 promoter occupancy, but the variation appears too large for it to be statistically significant. I agree that qualitatively there is a correlation for PIF4 but I think the description of the behavior of PIF7 should be rephrased.

    __As suggested by the reviewer, we will rephrase this paragraph to more accurately account for our data and also what was reported by others (e.g. Willige et al, 2021, in Li et al, 2012) regarding the regulation PIF7 levels and phosphorylation in response to a low R/FR treatment. __

    • There appear to be issues in the coloring of the labels (light blue dots vs dark blue dots) for the PIF7 panels of Fig 3B and Supplemental Fig 3B.*

    We thank the reviewer for pointing this out. This will be clarified by appropriate changes in the figure to avoid confusion in the revised version of Figure 3B.

    Reviewer #1 (Significance (Required)):

    This authors here have sought to examine the possibility that the transcriptional responses to shade mediated by the phy-PIF system might involve large-scale opening or closing of chromatin regions. This is an important and unanswered question in the field despite several studies that have looked at the role of histone variants (H2A.Z) and modifications (H3K4me3 and H3K9ac) in modulating PIF transcriptional activating activity. The authors have shown that, at least in the case of the transcriptional response to shade mediated by PIF7 (and to an extent PIF4), large-scale changes in chromatin accessibility are not occurring in response to shade treatment.

    The results presented in this study support the hypothesis that large-scale changes in chromatin accessibility may have already occurred before plants see shade. This opens the possibility that perhaps the initial perception of light by etiolated (dark-grown seedlings) might trigger changes in chromatin accessibility, opening up chromatin in regions encoding "shade-specific" genes and/or closing chromatin in regions encoding "dark-specific" genes.

    The audience for this particular manuscript encompasses a fairly broad group of biologists interested in understanding how environmental stimuli can trigger changes in chromatin reorganization and transcription. The results here are important in that they rule out chromatin accessibility changes as underlying the changes in transcription between the short-term and long-term shade responses. They also reveal that there are a few cases in which chromatin accessibility does change in a statistically-significant manner in response to shade. These regions, and the molecular players which regulate their accessibility, merit further exploration.

    Reviewer #2 (Evidence, reproducibility and clarity (Required)):

    The study by Paulisic et al. explores the variations in chromatin accessibility landscape induced by plant exposure to light with low red/far-red ratios (LRFR), which mimicks neighbor shade perception. The authors further compare these changes with the genome association of PIF4 and PIF7 transcription factors - two major actors of gene expression regulation in response to LRFR. While this is not highlighted in the main text, the analyses of chromatin accessibility are performed on INTACT-mediated nucleus sorting, presumably to ensure proper and clean isolation of nuclei.

    Major comments

    • Why is the experimental setup exposing plants to darkness overnight? Does this affect the response to LRFR, by a kind of reset of phytochrome signaling? I guess this choice was made to maintain a strong circadian rhythm. Yet, given that PIF genes are clock-regulated, I am afraid that this choice complicates data interpretation concerning the specific effects of LRFR exposure.

    There appears to be some confusion which prompts us to better explain our protocol both by changing Figure 1A (that outlines the experimental conditions) and in the text.

    Seedlings are grown in long day conditions because this is more physiologically relevant than growing them in constant light, which is a rather unnatural condition.

    The reviewer is correct that PIF transcription is under circadian control and the shade avoidance response is gated by the circadian clock (e.g. Salter et al., 2003). To prevent conflating circadian and light quality effects, all samples that are compared are harvested at the same ZT (circadian time – hours after dawn). This allows us to focus our analysis on light quality effects specifically. We are therefore convinced that our protocol does not complicate the interpretation of the LRFR effects reported here.

    • As a result of this setup, the 1h exposure to LRFR immediately follows HRFR while the 3h final LRFR exposure of the « 25h LRFR » samples immediately follows a long period of darkness. Can this explain why in several instances (e.g., at the ATHB2 gene) 1h LRFR seems to have stronger effects than 25h LRFR on chromatin accessibility?* Please check the explanation above. Both samples are harvested at the same ZT (ZT3, meaning 3 hours after dawn). The 1h LRFR seedlings went through the night, had 2 hours of HRFR then 1h of LRFR. The 25h are harvested at the very same ZT, meaning 3h after dawn. Importantly, the HRFR control was also harvested at ZT3, meaning 3h after dawn. As indicated above this protocol allows us to focus on the light quality effects by comparing samples that are all harvested at the same ZT.

    We expect that the changes in Fig. 1A and associated text changes will clarify this issue.

    • Lane 42 cites the work by Calderon et al 2022 as « Transcript levels of these genes increase before the H3K4me3 levels, implying that H3K4me3 increases as a consequence of active transcription ». Despite this previous study being reviewed and published, such a strong conclusion should be taken cautiously, and I disagree with it. The study by Calderon et al compares RNA-seq with ChIP-seq data, two methodologies with very different sensitivity, especially when employing bulk cells/whole seedlings as starting materials. For example, a gene strongly induced in a few cells will give a good Log2FC in RNA-seq data analysis (as new transcripts are produced after a low level of transcripts before shade) but, even though its chromatin variations would follow the same temporality or would even precede gene induction, this would be invisible in bulk ChIP-seq data analysis (which averages the signal of all cells together). I understand the rationale for relying on the conclusions made in an excellent lab with strong expertise in light signaling, but I recommend being cautious when relying on these conclusions to interpret new data.* We agree with this comment, and we will change the text to reflect this.
    • The problem is that the same issue holds true when comparing ATAC-seq and RNA-seq data. ATAC signals reflect average levels over all cells while RNA-seq data can be influenced by a few cell highly expressing a given gene. Even though authors carefully sorted nuclei using an INTACT approach, this should be discussed, in particular when gene clusters (such as cluster C-D) show no match between chromatin accessibility and transcript level variations. In this regard, is PIF7 expressed in many cells or a small niche of cells upon LRFR exposure? The conclusions on its role in chromatin accessibility, analyzed here as mean levels of many different seedling cells, could be affected by PIF7 activity pattern (e.g., at lane 293).* This is a good comment. PIF7 is expressed in the cotyledons and leaves in LD conditions (Kidokoro et al, 2009, Galvao et al, 2019), and few available scRNA-seq datasets indicate an enrichment of PIF7 in the epidermis (Kim et al, 2021, Lopez-Anido et al, 2021). LRFR exposure only mildly represses PIF7 expression as seen in Figure 3A and also in our bulk RNA-seq study (Table S4). We will discuss this potential limitation to our study in a revised version of the manuscript.
    • Lane 89, the conclusion linking DNA methylation and DNA accessibility is unclear to me, this may be rephrased. Also, it should be noted that in gene-rich regions, most DNA methylation is located along the body of moderately to highly transcribing genes (gene-body methylation) while promoters of active and inactive genes are most frequently un-methylated.* We will rephrase to better reflect the presence or absence of DNA methylation on promoter regions of shade regulated genes that contain accessible sites.

    • Figure 3B shows a few ChIP-qPCR results with important conclusions. Why not sequencing the ChIPped DNA to obtain a genome-wide view of the PIF4-PIF7 relationships at chromatin, and also consequently a more robust genome-wide normalization?

    Several studies have shown that in the conditions that we studied here: transfer of seedlings from high R/FR (simulated sun) to low R/FR (neighbor proximity), amongst all PIFs, PIF7 is the one that plays the most dominant function (e.g. Li et al., 2012; de Wit et al., 2016; Willige et al., 2021). PIF4 and PIF5 also contribute but to a lesser extent. Given that Willige et al., 2021 did extensive ChIP-seq studies for PIF7 using similar conditions to the ones we used, we decided to rely on their data (that we re-analyzed), rather than performing our own PIF7 ChIP-seq analysis. While also performing a ChIP-seq analysis for PIF4 in similar conditions might be useful (this data is not available as far as we know), we are not convinced that doing that experiment would substantially modify the message. In the revised version we will also include analysis of the data from Pfeiffer et al., 2014, which comprises a ChIP-seq. dataset for PIF5 (the closest paralog of PIF4) initially performed by Hornitschek et al., in 2012 in low R/FR conditions (see comment to reviewer 1 above). For new ChIP-seq, we would have to make this experiment from scratch with substantially more material than what we used for the targeted ChIP-qPCR analyses. We thus do not feel that such an investment (time and money) is warranted.

      • Given the known functional interaction between PIF7 and INO80, it would be relevant to test whether changes in chromatin accessibility at ATHB2 and other genes are affected in ino80 mutant seedlings.* __We agree with the reviewer that this is potentially an interesting experiment. This will allow us to determine whether the nucleosome histone composition has an influence on nucleosome positioning at selected shade-regulated genes (e.g. ATHB2). We note that according to available data, the effect of INO80 would be expected once PIF7 started transcribing shade-induced genes. We therefore propose comparing the WT with an ino80 mutant for their seedling growth phenotype, expression of selected shade marker gene (e.g. ATHB2) and chromatin accessibility before (high R/FR) and after low R/FR treatment at selected shade marker genes. This will allow us to determine whether INO80 influences chromatin accessibility prior to a low R/FR treatment and/or once the treatment started. Our plan is to include this data in a revised version of the manuscript. __
    • On the same line, it would be interesting to test whether PIF7 target regions with pre-existing accessible chromatin would exist in ino80 mutant plants. In other words, testing a model in which chromatin remodeling by INO80 defines accessibility under HRFR to enable rapid PIF recruitment and DNA binding upon LRFR exposure.*

    See our answer just above.

    Minor comments

    *• In Figure 1C, it seems that PIF7 target genes do not match the set of LRFR-downregulated genes (even less than at random). Why not exclude these 4 genes from the analyses? *

    This is correct. There are indeed only 4 downregulated PIF7 target genes as we define them. Removing these genes from the analyses does not change our interpretation of the data and hence for completeness we propose keeping them in a revised version of the manuscript

    • Figure 3A shows the quantification of protein blots, but I did not find the corresponding images. These should be shown in the figure or as a supplementary figure with proper controls.

    We will include the raw Westen blots used for quantification of PIF4, PIF5 and PIF7 in the revised version of the manuscript

      • Lane 102, it is unclear why PIF7 target genes were defined as the -3kb/TSS domains while Arabidopsis intergenic regions are on average much shorter. Gene regulatory regions, or promoters, are typically called within -1kb/TSS regions to avoid annotating a ChIP peak to the upstream gene or TE. A better proxy of PIF7 typical binding sites in gene regulatory regions could be determined by analysing the mean distance between PIF7 peak coordinates and the closest TSS. Typically, a gene meta-plot would give this information.* We agree that the majority of PIF7 binding peaks are close to the 5’ of the TSS based on the PIF7 binding distribution meta-plot. But several known PIF binding sites are actually further upstream than 1kb 5’ of the TSS (e.g. ATHB2 and HFR1). However, we re-analyzed the data using your suggestion with -2kb/TSS and -1kb/TSS and while the number of target genes is reduced, it does not change our conclusions about PIF7 binding sites being located on accessible chromatin regions. Importantly, some well characterized LRFR induced genes such as HFR1 would not be annotated correctly if only peaks closest to the gene TSS were taken into account, without flanking genes. In this case only the neighboring AT1G02350 would be annotated, hence missing some important PIF7 target genes. Taking this into consideration we will not modify this part of the analysis in a revised manuscript.
    • Figure 4B, what's represented in the ATAC-seq heatmap: does a positive z-score represent high accessibility?*

    On the ATAC-seq heatmap we have represented z-scores of the average CPM (counts per million) for accessible chromatin regions. Z-scores are calculated by subtracting the average CPM from the median of averaged CPMs for each accessible chromatin region and then divided by the standard deviation (SD) of those averaged CPMs across all groups per accessible region (in our case a group is an average of three biological replicates for either HRFR, 1h or 25h of LRFR). In that sense, z-score indicates a change in accessibility, where higher z-score indicates opening of the region and lower z-score indicates a region becoming more closed when compared among the three light treatments (HRFR, 1h or 25h of LRFR). We will make sure that this is clear in the revised manuscript. Reviewer #2 (Significance (Required)):

    Contradicting the naive hypothesis that PIFs may target shade-inducible genes to « open » chromatin of shade-inducible genes with the help of chromatin remodelers, such as INO80, the study highlights that PIF7 typically associates with pre-existing accessible chromatin states. Thus, even though this is not stated, results from this study indicate that PIF7 is not a pioneer transcription factor. The data seem very robust, and while some conclusions need clarification, it should be of great interest to the community of scientists studying plant light signaling and shade responses.

    Reviewer #3 (Evidence, reproducibility and clarity (Required)):

    In their manuscript, Paulisic et al. investigate whether the transcriptional response of Arabidopsis seedlings to shade depends on chromatin accessibility, with a specific focus on PIF7-regulated genes. To this end, they perform ATAC-seq and RNA-seq, along with other experiments, on seedlings exposed to short and long shade and correlate the results with previously reported PIF7 and PIF4 ChIP-seq data. Based on their findings, they propose that shade-mediated transcriptional regulation may not require extensive remodeling of DNA accessibility. Specifically, they suggest that the open chromatin conformation allows PIFs to easily access and recognize their binding motifs, rapidly initiating gene expression in response to shade. This transcriptional response primarily depends on a transient increase in PIF stability and gene occupancy, with changes in chromatin accessibility occurring in only a small number of genes.

    Major comments:

    • I have one issue that, in my opinion, requires more attention. To define the PIF7 target genes, which were later used to estimate whether PIF7 binds to open or closed chromatin and affects DNA accessibility after its binding, the authors compared the 4h LRFR data point from Willige et al. (2021) ChIP-seq with their 1h RNA-seq data point. This comparison might have missed early genes where PIF7 binds before the 1h time point but is no longer present on DNA at 4h. I understand the decision to choose the 4h Willige et al. ChIP-seq data point, performed under LD conditions, as it matches the data in this study, rather than the 5min-30min data points, which were conducted in constant light. However, if possible, it would be interesting to also compare the RNA-seq data with the early PIF7 binding genes to assess how many additional PIF7 target genes could be identified based on that comparison and whether this might alter the conclusions. If the authors do not agree with this point, it should at least be emphasized that the ChIP-seq data and the RNA-seq/ATAC-seq data were performed under different LRFR conditions (R/FR 0.6 vs. 0.1), which may lead to the misidentification of PIF7 target genes in the manuscript.*

    1) This is an interesting suggestion, we therefore reanalyzed 5, 10 and 30 min ChIP-seq timepoints from Willige et al, 2021 and compared them to 4h of LRFR (ZT4). We have crossed these lists of potential PIF7 targets with our 1h LRFR PIF457 dependent genes based on our RNA-seq. While some PIF7 targets appear only in early time points 5-10 min of LRFR exposure, overall, the number and composition of PIF7 target genes is rather constant across these timepoints. We propose to include these additional analyses in a revised version of the manuscript as a supplemental figure. However, these additional analyses do not influence our general conclusions.

    2) The comment regarding the R/FR ratio is important. We will point this out although the conditions used by Willige et al., 2021 and the ones we used are similar, they are not exactly the same in terms of R/FR ratio. Importantly, in both studies the early transcriptional response largely depends on the same PIFs, many of the same response genes are induced (e.g. PIL1, AtHB2, HFR1, YUC8, YUC9 and many others) and the physiological response (hypocotyl elongation) is similar. This shows that this low R/FR response yields robust responses.

    Minor comments: • In Fig. 1D, please describe the meaning of the blue shaded areas and the blue lines under the ATAC-seq peaks, as they do not always correlate.

    The shaded areas and the bars define the extension of the ATAC-seq accessible chromatin peaks. We will add the meaning of the shaded areas and the blue bars in the Figure legend and correct the colors in a revised manuscript

    • In Fig. 1E, it could be helpful to note that the 257 peaks in the right bar correspond to the peaks associated with the 177 genes in the left bar.* We will update Figure 1E and Figure legends for better understanding as the Reviewer suggested.
    • In lines 116, 119, and 122, I believe it should read "Fig. 2" instead of "Fig. 2A."* We thank the Reviewer for noticing the error that we will correct.
    • Lines 138-139: "PIF7 total protein levels were overall more stable, and only a mild and non-significant increase of PIF7 levels was seen at 1 h of LRFR." Since PIF7 usually appears as two bands in HRFR and only one band in LRFR, how was the protein level of PIF7 quantified in Fig. 3A? Additionally, I was wondering about the authors' thoughts on the discrepancy with Willige et al. (2021, Extended Data Fig. 1d), where PIF7 abundance seems to increased after 30 min and 2 h of LRFR.* PIF7 protein levels were quantified by considering both the upper and the lower band in HRFR (total PIF7) and normalizing its levels to DET3 loading control. We still observe an increase in the total PIF7 protein levels at 1h of LRFR, however this change was not statistically significant in these experiments. In our conditions as in Willige et al, 2021, the increase in PIF7 protein levels to short term shade seems consistent as is the pronounced shift or disappearance of the upper band (phosphorylated form) on the Western blots (raw data will be available in the revised manuscript). We will introduce text changes referring to the phosphorylation status of PIF7 in our conditions.

    • Line 150: "... many early PIF target genes (Figure 3C)." Since only PIL1 is shown in Fig. 3C, I would recommend revising this sentence. Alternatively, the data could be presented, as in Fig. 2, for all the PIF7 target genes with transient expression patterns.

    We will introduce changes in the text to reflect that we only show PIL1 in the main Figure 3C.

    • Line 204: I'm not sure if Supplementary Fig. 7C-D is correct here. If it is, could the order of the figures be changed so that Supplementary Fig. 7C-D becomes Supplementary Fig. 7A-B?*

    The order of the panels A-B in the Supplementary Figure 7 follows the order of the text in the manuscript and is mentioned before panels C-D. It refers to the sentence “Overexpression of phyB resulted in a strong repression of hypocotyl elongation in both HRFR and LRFR, while the absence of phyB promoted hypocotyl elongation (Supplementary Figure 7A-B).”

      • Line 208: "In all three cases...". Please clarify what the three cases refer to.* We will change the text to more explicitly refer to the differentially accessible regions (DARs) of the genes ATHB2 and HFR1 shown in Figure 5A.
    • Line 231: Should Fig. 5C also be cited here in addition to Supplementary Fig. 7?* We will add the reference to Figure 5C that was missing.

    *• In Supplementary Table 3, more information is needed. For example, it could mention: "This data is presented in Fig. 3 and is based on datasets from ChIP-seq, RNA-seq, etc."

    The table will be updated with more information as suggested by the Reviewer.

    • In the figure legend of Fig. 4B, please check the use of "( )".*

    We will correct the error and include the references inside the parenthesis.

    Reviewer #3 (Significance (Required)):

    Paulisic et al. present novel discoveries in the field of light signaling and shade avoidance. Their findings extend our understanding of how DNA organization, prior to shade, affects PIF binding and how PIF binding remodels DNA accessibility. The data presented support the conclusions well and are backed by sufficient experimental evidence.

    2. Description of the revisions that have already been incorporated in the transferred manuscript

    The manuscript has not been modified yet.

    3. Description of analyses that authors prefer not to carry out

    Reviewer 2 asked for new ChIP-seq analyses for PIF7 and PIF4. For reasons that we outlined above, we believe that such analyses are not required, and we currently do not intend performing these experiments.

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    Referee #3

    Evidence, reproducibility and clarity

    In their manuscript, Paulisic et al. investigate whether the transcriptional response of Arabidopsis seedlings to shade depends on chromatin accessibility, with a specific focus on PIF7-regulated genes. To this end, they perform ATAC-seq and RNA-seq, along with other experiments, on seedlings exposed to short and long shade and correlate the results with previously reported PIF7 and PIF4 ChIP-seq data. Based on their findings, they propose that shade-mediated transcriptional regulation may not require extensive remodeling of DNA accessibility. Specifically, they suggest that the open chromatin conformation allows PIFs to easily access and recognize their binding motifs, rapidly initiating gene expression in response to shade. This transcriptional response primarily depends on a transient increase in PIF stability and gene occupancy, with changes in chromatin accessibility occurring in only a small number of genes.

    Major comments:

    I have one issue that, in my opinion, requires more attention. To define the PIF7 target genes, which were later used to estimate whether PIF7 binds to open or closed chromatin and affects DNA accessibility after its binding, the authors compared the 4h LRFR data point from Willige et al. (2021) ChIP-seq with their 1h RNA-seq data point. This comparison might have missed early genes where PIF7 binds before the 1h time point but is no longer present on DNA at 4h. I understand the decision to choose the 4h Willige et al. ChIP-seq data point, performed under LD conditions, as it matches the data in this study, rather than the 5min-30min data points, which were conducted in constant light. However, if possible, it would be interesting to also compare the RNA-seq data with the early PIF7 binding genes to assess how many additional PIF7 target genes could be identified based on that comparison and whether this might alter the conclusions. If the authors do not agree with this point, it should at least be emphasized that the ChIP-seq data and the RNA-seq/ATAC-seq data were performed under different LRFR conditions (R/FR 0.6 vs. 0.1), which may lead to the misidentification of PIF7 target genes in the manuscript.

    Minor comments:

    • In Fig. 1D, please describe the meaning of the blue shaded areas and the blue lines under the ATAC-seq peaks, as they do not always correlate.
    • In Fig. 1E, it could be helpful to note that the 257 peaks in the right bar correspond to the peaks associated with the 177 genes in the left bar.
    • In lines 116, 119, and 122, I believe it should read "Fig. 2" instead of "Fig. 2A."

    Lines 138-139: "PIF7 total protein levels were overall more stable, and only a mild and non-significant increase of PIF7 levels was seen at 1 h of LRFR."

    Since PIF7 usually appears as two bands in HRFR and only one band in LRFR, how was the protein level of PIF7 quantified in Fig. 3A? Additionally, I was wondering about the authors' thoughts on the discrepancy with Willige et al. (2021, Extended Data Fig. 1d), where PIF7 abundance seems to increased after 30 min and 2 h of LRFR. Line 150: "... many early PIF target genes (Figure 3C)." Since only PIL1 is shown in Fig. 3C, I would recommend revising this sentence. Alternatively, the data could be presented, as in Fig. 2, for all the PIF7 target genes with transient expression patterns.

    • Line 204: I'm not sure if Supplementary Fig. 7C-D is correct here. If it is, could the order of the figures be changed so that Supplementary Fig. 7C-D becomes Supplementary Fig. 7A-B?
    • Line 208: "In all three cases...". Please clarify what the three cases refer to.
    • Line 231: Should Fig. 5C also be cited here in addition to Supplementary Fig. 7?
    • In Supplementary Table 3, more information is needed. For example, it could mention: "This data is presented in Fig. 3 and is based on datasets from ChIP-seq, RNA-seq, etc."
    • In the figure legend of Fig. 4B, please check the use of "( )".

    Significance

    Paulisic et al. present novel discoveries in the field of light signaling and shade avoidance. Their findings extend our understanding of how DNA organization, prior to shade, affects PIF binding and how PIF binding remodels DNA accessibility. The data presented support the conclusions well and are backed by sufficient experimental evidence.

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    Referee #2

    Evidence, reproducibility and clarity

    The study by Paulisic et al. explores the variations in chromatin accessibility landscape induced by plant exposure to light with low red/far-red ratios (LRFR), which mimicks neighbor shade perception. The authors further compare these changes with the genome association of PIF4 and PIF7 transcription factors - two major actors of gene expression regulation in response to LRFR. While this is not highlighted in the main text, the analyses of chromatin accessibility are performed on INTACT-mediated nucleus sorting, presumably to ensure proper and clean isolation of nuclei.

    Major comments

    • Why is the experimental setup exposing plants to darkness overnight? Does this affect the response to LRFR, by a kind of reset of phytochrome signaling? I guess this choice was made to maintain a strong circadian rhythm. Yet, given that PIF genes are clock-regulated, I am afraid that this choice complicates data interpretation concerning the specific effects of LRFR exposure.
    • As a result of this setup, the 1h exposure to LRFR immediately follows HRFR while the 3h final LRFR exposure of the « 25h LRFR » samples immediately follows a long period of darkness. Can this explain why in several instances (e.g., at the ATHB2 gene) 1h LRFR seems to have stronger effects than 25h LRFR on chromatin accessibility?
    • Lane 42 cites the work by Calderon et al 2022 as « Transcript levels of these genes increase before the H3K4me3 levels, implying that H3K4me3 increases as a consequence of active transcription ». Despite this previous study being reviewed and published, such a strong conclusion should be taken cautiously, and I disagree with it. The study by Calderon et al compares RNA-seq with ChIP-seq data, two methodologies with very different sensitivity, especially when employing bulk cells/whole seedlings as starting materials. For example, a gene strongly induced in a few cells will give a good Log2FC in RNA-seq data analysis (as new transcripts are produced after a low level of transcripts before shade) but, even though its chromatin variations would follow the same temporality or would even precede gene induction, this would be invisible in bulk ChIP-seq data analysis (which averages the signal of all cells together). I understand the rationale for relying on the conclusions made in an excellent lab with strong expertise in light signaling, but I recommend being cautious when relying on these conclusions to interpret new data.
    • The problem is that the same issue holds true when comparing ATAC-seq and RNA-seq data. ATAC signals reflect average levels over all cells while RNA-seq data can be influenced by a few cell highly expressing a given gene. Even though authors carefully sorted nuclei using an INTACT approach, this should be discussed, in particular when gene clusters (such as cluster C-D) show no match between chromatin accessibility and transcript level variations. In this regard, is PIF7 expressed in many cells or a small niche of cells upon LRFR exposure? The conclusions on its role in chromatin accessibility, analyzed here as mean levels of many different seedling cells, could be affected by PIF7 activity pattern (e.g., at lane 293).
    • Lane 89, the conclusion linking DNA methylation and DNA accessibility is unclear to me, this may be rephrased. Also, it should be noted that in gene-rich regions, most DNA methylation is located along the body of moderately to highly transcribing genes (gene-body methylation) while promoters of active and inactive genes are most frequently un-methylated.
    • Figure 3B shows a few ChIP-qPCR results with important conclusions. Why not sequencing the ChIPped DNA to obtain a genome-wide view of the PIF4-PIF7 relationships at chromatin, and also consequently a more robust genome-wide normalization?
    • Given the known functional interaction between PIF7 and INO80, it would be relevant to test whether changes in chromatin accessibility at ATHB2 and other genes are affected in ino80 mutant seedlings.
    • On the same line, it would be interesting to test whether PIF7 target regions with pre-existing accessible chromatin would exist in ino80 mutant plants. In other words, testing a model in which chromatin remodeling by INO80 defines accessibility under HRFR to enable rapid PIF recruitment and DNA binding upon LRFR exposure.

    Minor comments

    • In Figure 1C, it seems that PIF7 target genes do not match the set of LRFR-downregulated genes (even less than at random). Why not exclude these 4 genes from the analyses?
    • Figure 3A shows the quantification of protein blots, but I did not find the corresponding images. These should be shown in the figure or as a supplementary figure with proper controls.
    • Lane 102, it is unclear why PIF7 target genes were defined as the -3kb/TSS domains while Arabidopsis intergenic regions are on average much shorter. Gene regulatory regions, or promoters, are typically called within -1kb/TSS regions to avoid annotating a ChIP peak to the upstream gene or TE. A better proxy of PIF7 typical binding sites in gene regulatory regions could be determined by analysing the mean distance between PIF7 peak coordinates and the closest TSS. Typically, a gene meta-plot would give this information.
    • Figure 4B, what's represented in the ATAC-seq heatmap: does a positive z-score represent high accessibility?

    Significance

    Contradicting the naive hypothesis that PIFs may target shade-inducible genes to « open » chromatin of shade-inducible genes with the help of chromatin remodelers, such as INO80, the study highlights that PIF7 typically associates with pre-existing accessible chromatin states. Thus, even though this is not stated, results from this study indicate that PIF7 is not a pioneer transcription factor. The data seem very robust, and while some conclusions need clarification, it should be of great interest to the community of scientists studying plant light signaling and shade responses.

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    Referee #1

    Evidence, reproducibility and clarity

    Summary:

    Plant systems sense shading by neighbors via the phytochrome signaling system. In the shade, PHYTOCHROME-INTERACTING FACTORS (PIFs) accumulate and are responsible for transcriptional reprogramming that enable plants to mobilize the "shade-avoidance response". Here, the authors have sought to examine the role of chromatin in modulating this response, specifically by examining whether "open" or "closed" chromatin regions spanning PIF target genes might explain the transcriptional output of these genes. They used a combination of ATAC-seq/CoP-qPCR (to detect open regions of chromatin), ChIP (to assay PIF binding) and RNA-seq (to measure transcript abundance) to understand how these processes may be mechanistically linked in Arabidopsis wild-type and pif mutant lines. They found that some chromatin accessibility changes do occur after LRFR (shade) treatment (32 regions after 1h and 61 after 25 h). While some of these overlap with PIF-binding sites, the authors found no correlation between open chromatin states and high levels of transcription. Because auxin is an important component of the shade-avoidance response and has been shown to control chromatin accessibility in other contexts, they examined whether auxin might be required for opening these regions of chromatin. They find that in an auxin biosynthesis mutant, there is a small subset of PIF target genes whose chromatin accessibility seems altered relative to the wild-type. Likewise, they found that chromatin accessibility for certain PIF targets is altered in phyB and pif mutant and propose that PIFs are necessary for changing the accessibility of chromatin in these genes. The authors thus propose that PIF occupancy of already open regions, rather than increased accessibility, underly the increase in transcript of abundance of these target genes in response to shade.

    Major comments:

    I find that the data generally support the hypothesis presented in the manuscript that chromatin accessibility alone does not predict transcription of PIF target genes in the shade. That said, I think that a paragraph from the discussion (lines 321-332) would benefit from some careful rephrasing. I think it is perfectly reasonable to propose that PIF occupancy is more predictive of shade-induced transcriptional output than chromatin accessibility, but I think that calling PIF occupancy "the key drivers" (line 323) or "the main driving force" (line 76) risks ignoring the observation that levels of PIF occupancy specifically do not predict expression levels of PIF target genes (Pfeiffer et al., 2014, Mol Plant). For PIL1 and HFR1, the authors have shown that PIF promoter occupancy and transcript levels are correlated, but the central finding of Pfeiffer et al. was that this pattern does not apply to the majority of PIF direct target genes. Finding factors (i.e. histone marks) that convert PIF-binding information into transcriptional output appears to have been the impetus for the experiments devised in Willige et al., 2021 and Calderon et al., 2022. It is great that the authors have outlined in the discussion that there are a number of factors that modulate PIF transcriptional activating activity but I think that the emphasis on PIF-binding explaining transcript abundance should be moderated in the text.

    I think that the hypothesis could be further supported by incorporating the previously published ChIP-seq data on PIF1, PIF3 and PIF5 binding. Given these data are published/publicly available, I think it would be helpful to note which of the 72 DARs are bound by PIF1, PIF3 and/or PIF5. Especially so given that PIF5 (Lorrain et al., 2008, Plant J) and PIF1/PIF3 (Leivar et al., 2012, Plant Cell) contribute at least in some capacity to transcriptional regulation in response to shade. At the very least, it might help explain some of the observed increases in nucleosome accessibility observed for genes that don't have PIF4 or PIF7-binding.

    In the manuscript, there are several instances where separate col-0 (wild type) controls have been used for identical experiments. Specifically, qPCR (Fig 3C, Fig S7C/D and Fig S8C/D), CoP-qPCR (Fig 5B/5C and Fig S8E/F) and hypocotyl measurements (Fig S7A/B and Fig S8A/B). In the cases of the hypocotyl measurements, there appear to be hardly any differences between col-0 controls indicating the measurements can be confidently compared between genotypes.

    In some cases of qPCR and CoP-qPCR experiments however, the differences in values obtained from col-0 samples that underwent identical experimental treatments appear to vary significantly. In Figure 3C for example, the overall trend for PIL1 expression in col-0 is the same (e.g. HRFR levels are low, LRFR1 levels are much higher and LRFR25 levels drop down to some intermediate level) but the expression levels themselves appear to differ almost two-fold for the LRFR 1h timepoint (~110 on the left panel vs ~60 for the right panel). Given the size of the error bars, it appears that these data represent the mean from only one biological replicate. PIL1 expression levels at LRFR 1h as reported in Fig S7C and D also show similar ~2-fold differences.

    I would recommend that the authors explicitly describe the number of biological replicates used for each experiment in the methods section. If indeed these experiments were only performed once, I think the authors should be very careful in the language used in describing their conclusions and in assigning statistical significance. One possibility that could also be helpful would be normalizing LRFR 1h and LRFR 25h values to HRFR values and plotting these data somewhere in the supplemental data. If, for example, the relative levels of PIL1 are different between replicates but the fold-induction between HRFR and LRFR 1h are the same, this would at least allay any concerns that the experimental treatments were not the same. I understand that doing so precludes comparison between genotypes, but I do think it's important to show that at least the control data are comparable between experiments.

    Similarly, for the CoP-qPCR experiments presented in Fig 5B and 5C, the col-0 values for region P2 between Fig 5B and 5C shows that while HRFR and LRFR 1h look comparable, the values presented for LRFR 25h are quite different.

    Minor comments:

    Presentation of Supplemental Figure 7A/7B and Supplemental Figure 8A/8B could be changed to make the data more clear (i.e. side-by-side rather than superimposed).

    I think that the paragraph introducing auxin (lines 25-37) could be reduced to 1-2 sentences and merged into a separate introductory paragraph given that the SAV3 work makes up a relatively minor component of the manuscript.

    For Figure 3A, I would strongly encourage the authors to show some of the raw western blot data for PIF4, PIF5 and PIF7 protein abundance (and loading control), not just the normalized values. This could be put into supplemental data, but I think it should accompany the manuscript.

    Lines 145-147 "we observed a strong correlation between PIF4 protein levels (Figure 3A) and PIL1 promoter occupancy (Figure 3B), and a similar behavior was seen with PIF7 (Figure 3B)." According to Fig 3A, there is no statistically significant increase in PIF7 abundance after 1h shade. There is an apparent increase in PIF7 promoter occupancy, but the variation appears too large for it to be statistically significant. I agree that qualitatively there is a correlation for PIF4 but I think the description of the behavior of PIF7 should be rephrased.

    There appear to be issues in the coloring of the labels (light blue dots vs dark blue dots) for the PIF7 panels of Fig 3B and Supplemental Fig 3B.

    Significance

    This authors here have sought to examine the possibility that the transcriptional responses to shade mediated by the phy-PIF system might involve large-scale opening or closing of chromatin regions. This is an important and unanswered question in the field despite several studies that have looked at the role of histone variants (H2A.Z) and modifications (H3K4me3 and H3K9ac) in modulating PIF transcriptional activating activity. The authors have shown that, at least in the case of the transcriptional response to shade mediated by PIF7 (and to an extent PIF4), large-scale changes in chromatin accessibility are not occurring in response to shade treatment.

    The results presented in this study support the hypothesis that large-scale changes in chromatin accessibility may have already occurred before plants see shade. This opens the possibility that perhaps the initial perception of light by etiolated (dark-grown seedlings) might trigger changes in chromatin accessibility, opening up chromatin in regions encoding "shade-specific" genes and/or closing chromatin in regions encoding "dark-specific" genes.

    The audience for this particular manuscript encompasses a fairly broad group of biologists interested in understanding how environmental stimuli can trigger changes in chromatin reorganization and transcription. The results here are important in that they rule out chromatin accessibility changes as underlying the changes in transcription between the short-term and long-term shade responses. They also reveal that there are a few cases in which chromatin accessibility does change in a statistically-significant manner in response to shade. These regions, and the molecular players which regulate their accessibility, merit further exploration.

    My fields of expertise are photobiology, photosynthesis and early seedling development.

  5. Version published to 10.1101/2025.01.23.634457 on bioRxiv