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. 2022 Sep 23;190(4):2797–2811. doi: 10.1093/plphys/kiac448

The chromatin accessibility landscape of pistils and anthers in rice

Guanqun Wang 1,2, Xiaozheng Li 3, Wei Shen 4, Man-Wah Li 5, Mingkun Huang 6, Jianhua Zhang 7,8,✉, Haoxuan Li 9,10,✉
PMCID: PMC9706442  PMID: 36149297

Abstract

Transcription activation is tightly associated with the openness of chromatin and allows direct contact between transcriptional regulators and their targeted DNA for gene expression. However, there are limited studies on the annotation of open chromatin regions (OCRs) in rice (Oryza sativa), especially those in reproductive organs. Here, we characterized OCRs in rice pistils and anthers with an assay for transposase-accessible chromatin using sequencing. Despite a large overlap, we found more OCRs in pistils than in anthers. These OCRs were enriched in gene transcription start sites (TSSs) and showed tight associations with gene expression. Transcription factor (TF) binding motifs were enriched at these OCRs as validated by TF chromatin immunoprecipitation followed by sequencing. Pistil-specific OCRs provided potential regulatory networks by binding directly to the targets, indicating that pistil-specific OCRs may be indicators of cis-regulatory elements in regulating pistil development, which are absent in anthers. We also found that open chromatin of pistils and anthers responded differently to low temperature (LT). These data offer a comprehensive overview of OCRs regulating reproductive organ development and LT responses in rice.

Chromatin accessibility, histone modification, and transcriptome data provide valuable resource for rice floral tissue development.

Introduction

Chromatin regions with open conformation for the binding of transcription factors (TFs) are open chromatin regions (OCRs). The binding of TFs to the cis-regulatory elements within the OCRs governs the expression of genes associated with the OCRs. Genome-wide open chromatin mapping enables the identification of the cis-regulatory elements both in genic and intergenic regions (Rodgers-Melnick et al., 2016; Maher et al., 2018; Yan et al., 2019; Han et al., 2020). Commonly used methods including assays of transposase accessible chromatin sequencing (ATAC-seq) have been successfully deployed to generate large-scale open chromatin maps in plants and provide details about gene regulation (Buenrostro et al., 2013; Potter et al., 2018; Klemm et al., 2019; Wang et al., 2020; Tian et al., 2021). While cis-regulatory elements within the OCRs are crucial for gene expression, emerging evidence has shown that manipulation of these cis-regulatory elements by genome editing could result in quantitative variation of desirable traits by altering gene expression (Swinnen et al., 2016; Hendelman et al., 2021; Wang et al., 2021a). Therefore, better understanding of genome-wide cis-regulatory elements is essential for crop improvement.

Rice (Oryza sativa) is one of the most important global crops. OCR maps mainly focus on the root (Zhang et al., 2021) and leaf (Lu et al., 2019). The anther and pistil are the reproductive organs of rice. They possess distinct architecture and are crucial for determining the yield. However, their OCR maps are still unavailable. Low temperature (LT) is an environmental cue that affects gene expression (Vyse et al., 2020). Specifically, LT can restore the fertility of thermo-sensitive sterile rice (Zhou et al., 2014; Fan et al., 2016; Yu et al., 2017), thus indicating its potential roles in regulating the gene expression responsible for reproductive organ development. Here, we plotted the OCR profiles of young panicle, anther, and pistil before flowering in rice using ATAC-seq. By integrating these results with those from RNA-seq, histone ChIP-seq, and TF ChIP-seq, we provide a comprehensive overview of the relationships among OCRs, gene expressions, and histone modifications. Importantly, we conducted in vivo ChIP-seq of pistil enriched TFs and found that TF binding sites (TFBSs) could be predicted by OCRs. The potential regulatory networks mediated by pistil-enriched TFs and its targets regulating pistil development were constructed. We also explored changes in chromatin accessibility of pistil and anther under LT conditions. Pistil and anther responded differently to LT, thus indicating tissue-specific changes of chromatin openness. In addition, we explored changes in chromatin status in a thermo-sensitive female sterility mutant at LT. These results indicate the potential regulatory role of OCRs in rice pistil and anther. The data can guide future studies on the manipulation of OCRs in reproductive tissues to improve rice farming.

Results

Genome-wide identification of OCRs in reproductive tissues of rice

To provide a comprehensive understanding of chromatin accessibility in reproductive tissues of rice, we constructed genome-wide, tissue-specific maps of OCRs of young panicles (2–5 mm in length), pistil, and anther of rice before flowering using ATAC-seq (Figure 1A;Supplemental Figure S1 and Supplemental Table S1). We identified 27,585 OCRs in pistil (Supplemental Table S2) and 18,874 OCRs in anther (Supplemental Table S3), with 12,725 OCRs shared between the two tissues (Figure 1B and Supplemental Table S4). The length of OCRs mainly fell between 100 and 900 base pairs (bp), and most were within 100–250 bp (Figure 1C). By plotting the positions of OCRs relative to nearby genes, we found that OCRs showed a similar distribution pattern in anther and pistil—these were mainly enriched at the gene transcription start sites (TSSs) (Figure 1D and Supplemental Figure S2A). We next assigned each OCR to the nearest gene based on the annotated TSSs. OCRs were classified into local OCRs and distal intergenic OCRs (distal OCRs). Local OCRs were OCRs with peaks located from 2 kilobase (kb) upstream of TSS, spanning the gene body, to 2 kb downstream of transcription termination site (TTS) (Supplemental Figure S2B). Peaks of distal OCRs were located outside these regions: the stretches of DNA beyond the 2 kb upstream of TSS, gene body and 2 kb downstream of TTS regions (Supplemental Figure S2B). Approximately, 77.71% of the OCRs in anther were local OCRs, with 59.78% located in the promoter (Supplemental Figure S2B). Here, 22.29% of the OCRs in anther were distal intergenic OCRs (Supplemental Figure S2B). Similarly, 75.36% and 24.64% of the OCRs in pistil were local OCRs, and distal intergenic OCRs, respectively (Supplemental Figure S2B). Given that pistil and anther originate from the panicle primordia during the reproductive stage, we compared the chromatin accessibility between the young panicle (2–5 mm) and mature floral tissues (pistil and anther) and then explored the OCR changes of reproductive organs over time. The OCR data of pistil and anther were merged as matured floral tissues in this analysis. The results showed that the OCR density of young panicles was lower than mature floral tissues (Figure 1E). Although we included 2 kb upstream of TSS in analysis, the core promoter region of average rice genes seems to be much narrower based on the distribution of OCRs (Figure 1E and Supplemental Figure S2A). These range from ∼500 bp upstream of TSS to 100 bp downstream of TSS. A large number of differential OCRs including 21,432 with reduced accessibility and 1,518 with increased accessibility were identified between young panicles and mature floral tissues by diffBind (Stark and Brown, 2011), thus suggesting stage-dependent chromatin accessibility in rice (Supplemental Figure S2C).

Figure 1.

Figure 1

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Characterization of OCRs in reproductive tissues of rice. A, Pistil and anther before flowering were dissected for all experiments. Scale Bar, 0.5 mm. B, A modest proportion of OCRs overlapped between pistil and anther. C, Length distribution of ATAC-seq peaks (bp) in anther and pistil. D, ATAC intensity of anther in the genome. E, Comparison of ATAC density between young panicles and mature floral organs (merged pistil and anther). F, The percentages of distal- and local OCRs that associated with expressed transcripts in pistil and anther. G, Expression levels of genes associated with both local OCR and distal OCR were significantly higher than those with only distal OCR or local OCR in pistil. Sample size (n) was indicated. Boxplots show the median (horizontal line). Upper and lower quartiles were the box limits. The outlier is the data point that is located outside the whiskers of the box plot. The P-value was calculated by Wilcoxon test.

Distal OCRs are another important category of OCRs because they are widely used for the prediction of putative enhancers in plants (Zhu et al., 2015; Oka et al., 2017). To explore the association between OCRs and expression levels of its most proximal genes, we performed the RNA-seq of pistil and anther. We then calculated the proportion of distal and local OCRs associated with their nearest transcribed genes. About 13.29% and 15.91% distal OCRs associated with transcribed genes in pistil and anther, respectively (Figure 1F). In contrast, 64.73% and 73.25% local OCRs in anther and pistil, respectively, were associated with transcribed genes (Figure 1F). Genes that associated with both distal and local OCRs tended to have higher expressions than those associated with either local or distal OCRs (Figure 1G). Moreover, genes that associated with only distal OCRs showed the lowest expression levels. This finding was consistent with that identified in maize (Zea mays) and soybean (Glycine max), thus indicating that distal OCRs might serve as putative enhancers for gene expression in plants (Sun et al., 2020; Huang et al., 2021).

OCRs association with differential gene expression

We identified 5,193 genes enriched in anther and 3,904 genes enriched in pistil (FPKM fold change > 2, P-value < 0.01) (Figure 2A and Supplemental Table S5). The anther-enriched genes were significantly enriched in various pathways such as starch and sucrose metabolism and biosynthesis of secondary metabolites, as annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis (Supplemental Figure S3A). In addition, we noted that 38 anther-enriched genes were enriched in the plant hormone signal transduction pathway including genes involved in jasmonic acid-related pathways such as JAR1 (LOC_Os05g50890) (Figure 2B), and genes involved in the auxin-responsive pathways. In contrast, the pistil-enriched genes were classified into very different pathways such as ribosome biogenesis in eukaryotes, photosynthesis-antenna proteins, and DNA replication (Supplemental Figure S3B), which is consistent with the fact that ribosomal proteins were significantly associated to the female fertility (Weijers et al., 2001; Nishimura et al., 2005; Imai et al., 2008; Szakonyi and Byrne, 2011; Zsögön et al., 2014). In addition, 23 pistil-enriched genes were also enriched in the plant hormone signal transduction pathway including auxin, brassinosteroid, abscisic acid (ABA), ethylene-related pathways, and amino acid transporter protein. For example, the gene SMALL AUXIN UPREGULATED RNA 25 (OsSAUR25, LOC_Os06g45950) encodes an auxin-responsive SAUR protein, and the product of LIKE AUXIN 5 (LOC_Os11g06820) enables auxin transport (Figure 2C). This suggested that the hormonal responses in anther and pistil were quite different. We further explored how the chromatin accessibility associated with anther- or pistil-enriched genes (Figure 2D). The results showed that anther-enriched genes exhibited higher chromatin accessibility near TSSs in anther than in pistil. In contrast, only a slight increase of chromatin openness was detected in pistil-enriched genes in pistil compared with anther (Figure 2D).

Figure 2.

Figure 2

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The correlation between OCRs and gene expression in pistil and anther. A, M-versus-A plot of DEGs between pistil and anther, Anther enriched genes were marked with blue dots; pistil enriched genes were marked with red dots; the gray dots marked the non-DEGs. DEGs were defined with the following criteria: P-value < 0.01, fold change > 2. B and C, Example of anther enriched gene (B) and pistil enriched gene (C) showed in genome browser tracks. D, ATAC-seq signal intensities in ±2 kb around the TSSs of anther enriched genes (left panel) and pistil enriched genes (right panel). E, Overlapping of promoter DOCRs (differential OCRs) with DEGs between pistil and anther. F, Heatmap of the overlapped genes in (E) presented with both ATAC-seq signal intensities (upper panel) and transcript levels (lower panel). G, A modest correlation between the DEGs and DOCRs was observed between pistil and anther. H, Significantly enriched GO terms of the uniquely expressed genes in pistil. I, Venn diagram showing the association between the uniquely expressed genes and the unique promoter (here referring to 2 kb upstream of TSS) OCRs in pistil and anther.

To further understand variation in chromatin accessibility between pistil and anther, we identified differential enrichment of OCRs (DOCRs) that were differentially enriched between samples. If an OCR showed differential ATAC-seq signals greater than two-fold (false discovery rate [FDR] < 0.01) in anther or pistil, then it was considered as a DOCR. Overall, we identified 3,629 DOCRs in 2-kb upstream of TSSs, 1,310 DOCRs in distal intergenic, 34 DOCRs in 2-kb downstream of TTSs, and 134 DOCRs in the gene body. Given that gene expression is strongly associated with chromatin accessibility, we assigned the DOCRs in the 2-kb upstream of TSSs to 3,392 genes expressed in anther and pistil (Supplemental Table S6). Of these DOCRs-associated genes, 1,114 genes were differentially expressed (Figure 2E). The ATAC-seq intensity of these genes showed a significant and positive correlation with the gene expression (Figure 2, F and G). Genes uniquely expressed in pistil (pistil-unique genes) were significantly enriched in gene ontology (GO), for example, reproductive development pathway, anatomical structural morphogenesis, nucleic acid metabolic process, and reproductive structure development (Figure 2H). In contrast, genes uniquely expressed in anther (anther-unique genes) were mainly enriched in transporter activity. To determine how chromatin accessibility was associated with the unique differentially expressed genes (DEGs), we compared the unique DOCRs that occurred in the anther and pistil with those unique DEGs. We found 175 pistil-unique genes associated with the pistil-unique OCRs, but only 47 anther-unique genes overlapped with the anther-unique OCRs (Figure 2I).

Histone modification in anther and pistil

Genes enriched in the H3K4me3 modification are often associated with an increase in expression level (van Dijk et al., 2010; Zong et al., 2013). OCRs characterized by H3K4me3 are indicative of active transcription and are enriched in local OCRs (Lu et al., 2019). To determine the importance of active histone modification on controlling the gene expression in anther and pistil, we performed the H3K4me3 ChIP-seq of anther (Supplemental Table S7 and Supplemental Figure S4) and pistil (Supplemental Table S8 and Supplemental Figure S4). We then profiled the association between H3K4me3 modification and gene expression. The results suggest that the enrichment of H3K4me3 in the gene body regions, especially the regions immediately downstream of TSS, was positively associated with the expression level (Figure 3, A and B). The transcription activity of genes marked by H3K4me3 within 1-kb upstream of TSS was significantly higher than that of genes with the summits located downstream of TSS (Figure 3C).

Figure 3.

Figure 3

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Histone modification associated with gene expression and open chromatin in pistil and anther. A and B, H3K4me3 modification is positively correlated with the gene expression in anther (A) and pistil (B); gene expression was divided into five groups from the lowest expression to highest expression. C, Boxplots showing expression levels of genes association in different regions of the genome structure. Sample size (n) was indicated. Boxplots show the median (horizontal line). Upper and lower quartiles were the box limits. The outlier is the data point that is located outside the whiskers of the box plot. D, Transcriptional levels of genes enriched with H3K4me3 modification in anther compared with pistil. Genes in anther showed higher expression levels than that of pistil (upper panel); Genes with enriched H3K4me3 signal in pistil showed higher levels than the relative transcript levels in anther (lower panel). Each red dot refers to one gene. The red violin refers to genes in anther, and blue violin refers to gene in pistil. E, The transcription activity of genes associated with both H3K4me3 and OCR, genes associated with none H3K4me3 modified OCR, and genes associated with only H3K4me3 modification. Sample size (n) was indicated. Boxplots show the median (horizontal line). Upper and lower quartiles were the box limits. The outlier is the data point that is located outside the whiskers of the box plot. F, IGV showing the tissue-unique expressed genes that associated with signals of ATAC and H3K4me3, including an amino acid transporter (LOC_Os06g36210) in anther (left panel) and an sex determination protein (LOC_Os07g40250) in pistil (right panel). The relative gene expression was showed. The P-value was calculated by Wilcoxon test.

To clarify the extent to which H3K4me3 modifications affect the gene expression, we examined the transcript levels of genes with differential H3K4me3 modifications between anther and pistil. As expected, H3K4me3 modifications enriched in anther displayed increased gene expression levels versus pistil and vice versa for pistil (Figure 3D). We then compared the differential H3K4me3 peak summit between pistil and anther. Most differential summits (75.4%, 6,533/8,666) were located 2-kb upstream of TSS while 7.9% (685/8,666) differential peaks were centered from TSS to ATG, and 10.4% (899/866) of the differential peaks were centered from ATG to TTS.

GO enrichment analyses of these differential H3K4me3-associated genes showed several significantly enriched GO terms including regulation of biological process, establishment of localization, transporter activity, transcription regulator activity, and electron carrier activity. As shown in previous studies, OCRs could be associated with gene-activating histone marks. We identified the OCRs modified by H3K4me3 and found that genes associated with H3K4me3 OCRs had significantly higher expression than those genes with only OCRs or genes with only H3K4me3 (Figure 3E). This highly suggested that OCRs modified by H3K4me3 enhanced transcription activation. We also found positive associations between differential OCRs and differential H3K4me3 modifications, such as tissue-unique expressed genes including an amino acid transporter (LOC_Os06g36210) in anther (Figure 3F) and a sex determination protein (LOC_Os07g40250) in pistil (Figure 3F).

Conserved TF binding motifs within OCRs

OCRs with specific sequence allow docking of TF to regulate gene expression (Friman et al., 2019). We sought to examine the potential TF binding motifs in the OCRs of anther and pistil. We first identified the top five most enriched TF binding motifs within OCRs of anther and pistil (Supplemental Figure S5, A and B). Four of these enriched motifs at these OCRs were shared between anther and pistil (Supplemental Figure S5, A and B). Next, we asked about the accuracy of the predicted TFBSs. To answer this, we then retrieved the ChIP-seq predicted target genes of an anther enriched NAC2 (LOC_Os04g38720) and a pistil enriched bZIP23 (LOC_Os02g52780) and overlapped them with the OCR associated genes (Brooks et al., 2021). Of the 614 and 4,197 high confident target genes bound by NAC2 and bZIP23, respectively, we noticed that about 24% targeted genes of NAC2 overlapped with OCR-associated genes in anther, and 71% of bZIP23 targeted genes overlapped with OCRs associated genes in pistil (Figure 4A). This indicated that these overlapped OCRs might be the regulatory regions of the two TFs present in anther and pistil.

Figure 4.

Figure 4

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TF motifs enriched at OCRs and the dynamic TF binding to OCRs contributes to differential gene expression between anther and pistil. A, Percentages of target genes of two previously reported TF (an anther enriched gene and a pistil enriched gene) overlapped with the OCRs in pistil and anther respectively. B, Percentages of TFBSs for nine pistil enriched TFs identified by in vivo ChIP-seq using rice protoplasts that overlap with OCRs in pistil. C, In vivo ChIP-seq signal enriched at the OCRs peak summit. Regions of ±2 kb from peak summits were showed. D, FPKM value of the pistil enriched TFs belonging to SPL and GRF families. E, Pistil specific OCRs in gene of SPL3 (left) and SPL14 (right). F, A proposed network of three TFs, SPL3, SPL4, and SPL14 from SPL family, and their potentially targets involved in auxin biosynthesis, transport and response. Red circle: auxin biosynthesis; pink circle: auxin transport; gray circle: auxin response. Arrow: transactive control. G, A proposed network of GRF2 and GRF3 and their potential targets. GRF family mainly plays negative roles in regulating genes responsible for the starch and sugar metabolism pathway, and sugar transport. Arrow: transactive control. Blunt arrow: suppress.

Pistil-specific OCRs could be indicators of cis-regulatory elements in regulating pistil development

Given the limited information of TF-target interactions in rice, we determined the TFBSs of nine pistil-enriched TFs by conducting in vivo ChIP-seq using rice protoplasts. We found that 32%–68% ChIP-seq identified TFBSs overlapped with pistil OCRs (Figure 4B). The peak summits of the nine TF ChIP-seq were observed to be enriched at the OCR peak centers (Figure 4C), thus revealing that TF access could be predicted by OCRs. Of the nine pistil-enriched TFs, SQUAMOSA-PROMOTER BINDING PROTEIN-LIKE 3 (SPL3), SPL14, GROWTH-REGULATING FACTOR 3 (GRF2), and GRF3 were associated with pistil-unique OCRs, thus indicating their unique regulatory roles in mediating the pistil development (Figure 4, D and E and Supplemental Figure S6).

To explore the regulatory roles of the pistil-enriched SPL genes, the TIP model (Landt et al., 2012) was used to associate the binding sites of SPL3, SPL4, and SPL14 with target genes (Supplemental Tables S9–S11). We identified 2,246–6,070 potential target genes of the three SPLs including 522 target genes shared among them. We also found 460, 673, and 240 targets of SPL3, SPL4, and SPL14, respectively. These were differentially expressed between pistil and anther. The differentially expressed target genes of each SPL were significantly enriched in different KEGG pathways. For example, differentially expressed targets of SPL3 were significantly enriched in pathway of zeatin biosynthesis, biosynthesis of secondary metabolites, and ubiquinone and other terpenoid–quinone biosynthesis. Differentially expressed SPL4 targets were enriched in pathways of glutathione metabolism, monoterpenoid biosynthesis, and flavonoid biosynthesis. SPL14 targets were enriched in pathways of fatty acid elongation; cutin, suberine, and wax biosynthesis; and photosynthesis. Plant hormone signal transduction pathways were commonly enriched although not significantly. Importantly, we found that DEGs (between pistil and anther) involved in auxin biosynthesis, transport, and signaling were potentially bound by these three SPLs, thus suggesting the essential roles of auxin-related signaling in modulating pistil development. We thereby constructed a proposed regulatory network comprising of three SPL genes and their potential targets in auxin pathways that are differentially expressed between anther and pistil (Figure 4F). Coincidently, all targets were up regulated in pistil, indicating that SPL3, SPL4, and SPL14 were the positive regulatory factors in mediating the female organ development.

In another two TFs (GRF2 and GRF3), we noticed that some of their target genes were involved in the carbohydrate metabolic pathways such as sugar transport and starch synthesis. While GRF2 and GRF3 were upregulated in pistil, their target genes were downregulated. This suggested that GRF2 and GRF3 might be negatively regulating sugar transporter and starch biosynthesis in pistil (Figure 4G). In summary, our proposed TF-target interactions based on the TF-associated pistil-specific OCRs could provide rich and in depth understanding of the pistil development, which was absent in anther.

Anther and pistil responded differently to LT

To investigate the LT responsive changes in chromatin accessibility, we constructed ATAC-seq of pistil and anther under LT treatments (Supplemental Tables S12–S13). By calculating the proportion of OCRs distributed in different gene structures, we noticed an increase of proximal OCRs (including 2-kb upstream of TSS and 2-kb downstream of TTS). These are accompanied by a reduction of distal OCRs in anther treated with LT, while less fluctuation in LT-treated pistil (Supplemental Figure S7A). In total, we identified 2,943 LT-responsive OCRs in anther and 1,033 LT-responsive OCRs in pistil (Supplemental Figure S7B). Larger number of differential peaks was detected in the anther than in pistil under LT (Figure 5, A and B and Supplemental Tables S14 and S15). Given that DOCRs within the 2-kb upstream to TSS would potentially affect gene expression, we collected the DOCRs in 2-kb upstream of TSS, and found 1,115 and 281 LT-induced OCRs in anther and pistil, respectively (Figure 5C). In addition, most of the LT-responsive OCRs were tissue-specific (Figure 5C). LT-induced OCRs in anther were significantly enriched in GO terms such as response to ABA, response to osmotic stress, and response to salicylic acid. In contrast, GO terms of multiple RNA metabolic processes such as production of small RNA involved in gene silencing and dsRNA processing were highly enriched in LT-treated pistil, suggesting key roles of small RNA in regulating female organ development in response to LT (Figure 5D). These results revealed distinct chromatin accessibility changes in response to LT between anther and pistil.

Figure 5.

Figure 5

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Chromatin accessibility changes in a tissue-specific manner in response to LT. A and B, Volcano plot showing the LT induced (red) and decreased (yellow) OCRs in anther (A) and pistil (B). Numbers of DOCRs were showed in the figures. nodiff (gray in color), no difference between two samples. C, Venn diagram showing the LT induced and reduced OCRs located in the 2 kb upstream of TSS (here referred to 2 kb promoter OCRs) shared between anther and pistil (left panel), and showing the LT induced and reduced genes in the transcriptional level shared between anther and pistil (right panel). D, Functional annotation of LT induced promoter OCRs in pistil (left) and anther (right) using GO enrichment. E, PCA of RNA-seq data. Each dot represents one sample. Dots in different colors represent different samples. F, Percentages of LT induced promoter OCRs associated with the upregulated genes under LT condition, and the percentages of the LT decreased promoter OCRs associated with the downregulated genes under LT condition in anther and pistil, respectively. G, H3K4me3 modification intensity of the upregulated genes induced by LT in anther (left panel) and pistil (right panel). NT, normal temperature. LT-induced genes showed higher H3K4me3 modification signals in the gene body regions. H, Top five enriched motifs detected in OCRs induced by LT in anther and pistil, respectively.

To further characterize the LT-induced OCRs within 2 kb upstream of TSS, we conducted RNA-seq of the corresponding samples treated with LT. Principal component analysis (PCA) of the DEGs successfully clustered the replicates of the untreated and treated anther and pistil into four groups (Figure 5E and Supplemental Tables S16 and S17). The greater distance between anther and LT-treated anther than that between pistil and LT-treated pistil in the PCA plot was consistent with the observation that there was a larger number of DEGs in anther in response to LT than in pistil (Figure 5E and Supplemental Tables S16 and S17). To understand the extent to which LT-induced OCRs affect gene expression, we examined the overlap between DOCRs in 2-kb upstream of TSS and DEGs. However, we only detected 0.57%–2.55% DOCRs in 2-kb upstream of TSS overlapping with the DEGs (Figure 5F).

Histone modification plays an important role in epigenetic regulation of gene expressions in response to environmental stress including at LT (Zeng et al., 2019). Here, we examined the changes of H3K4me3 modifications in anther and pistil in response to LT (Supplemental Tables S18 and S19). In total, 3,611 differential H3K4me3 modifications (including 1,660 LT-reduced and 1,951 LT-induced) were detected in LT-treated pistil, while much fewer differential H3K4me3 modifications (including 146 LT reduced and 248 LT induced) in anther under LT conditions. Obviously, the gene body regions of upregulated genes both in LT-treated anther and pistil were enriched with H3K4me3 modifications (Figure 5G). We also noticed divergently enriched motifs detected within OCRs induced by LT between anther and pistil, which pinpointed the reproductive tissue-specific regulatory network in response to LT (Figure 5H).

Chromatin accessibility changes of thermo-sensitive female sterility mutant

Thermo-sensitive female sterility is a desirable genetic resource that can help with mechanized hybrid rice production. We identified one spontaneous mutant originating from the rice cultivar of 4,266 (hereafter referring as wild type [WT]) during paddy field production, which displayed the complete seed set failure under high temperature (>25°C) (Figure 6A; Li et al., 2022). The pollen activity was normal in mutant (Li et al., 2022). The embryo sac of the mutant was normal as WT at 0 days after pollination (DAP) (Figure 6A), but the embryogenesis of the mutant indicated a failed embryo at 4 DAP. In contrast, the embryo of WT was visible (Figure 6A). These results suggested that the mutant was female sterile. We next applied LT (23°C) treatment to the mutant during the entire growing season. Surprisingly, the mutant’s fertility was restored with partially filled hulls (Figure 6B), suggesting that the mutant was thermo-sensitive female sterility (Li et al., 2022).

Figure 6.

Figure 6

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Identification of thermo-sensitive female sterility mutant and its open chromatin changes in pistil. A, Phenotype of thermo-sensitive female sterility mutant. Embryo sac and embryo development after pollination; pollen grain activity stained by I2-KI; Mature panicles after grain filling of the WT, mutant, and mutant under LT. Scale bars in embryo sac, 50 μm; Scale bars in pollen grain, 100 μm. A, antipodal cells; PN, polar nuclei; E, egg; S, synergids; Em, embryo. B, Panicles of WT, mutant and mutant under LT (mutant-LT). Scale bars, 1.5 cm. C, Proportion of OCRs distributed in different gene structures. distal intergenic: outside genic regions. gene body. proximal: including 2 kb pair upstream of TSS, and 2 kb downstream of TTS. D, Examples of DOCRs associated with DEGs between WT pistil and mutant pistil showing in the IGV. E, Venn diagram showing the shared DEGs between mutant pistil versus mutant pistil LT and WT pistil versus mutant pistil. F, Pearson correlation analysis of the 726 shared DEGs among the three samples with two biological replicates. The number from 0 to 1 represents the increasing correlations. Higher correlations between the mutant pistil LT and WT pistil (0.71–0.73) than the comparison of mutant pistil versus WT pistil (0.32–0.39) was observed. G, GO analysis of the 726 shared DEGs using the agriGO (http://systemsbiology.cau.edu.cn/agriGOv2/). H, Heatmap showing the expression pattern of differentially expressed TFs among the 726 shared DEGs.

We are curious about the chromatin accessibility changes of the mutant pistil, and thus ATAC-seq of the pistil in the mutant (mutant_pistil) was conducted. We found that the mutant showed slightly reduced proximal OCRs along with the increased distal OCRs (Figure 6C). A total of 2,007 increased and 180 decreased peaks were identified in mutant compared with the WT (Fold change > 2, FDR < 0.05; Supplemental Figure S8A). Then, we asked to what extent of the DOCRs affected the gene expression levels in the mutant (Supplemental Figure S8B). We found 1,386 DEGs between WT and mutant among which only 113 DEGs were associated with the DOCRs in proximal regions such as OsbHLH006 (LOC_Os04g23550) (Figure 6D). In addition, we also found five DEGs associated with OCRs in both distal and proximal regions, and five DEGs only associated with distal OCRs.

We are also curious about how the LT reconstructed the gene expression profiles in the mutant. This may relate to the partially restored female fertility. To address this, we conducted the RNA-seq of mutants under LT (Supplemental Figure S8B). The DEGs between mutant_pistil and WT_pistil (Cluster 1), and between mutant_pistil_LT and_mutant_pistil (Cluster 2) were identified. Those 726 DEGs shared between cluster 1 and cluster 2 were picked up, which might be important in regulating female fertility under LT (Figure 6E). We then calculated the expression correlation of these shared DEGs between different comparisons and found that the correlation index between mutant_pistil_LT and WT_pistil was higher than that of the comparison between mutant_pistil and WT_pistil (Figure 6F), suggesting that LT partially restored female fertility of the mutant by restoring the gene expression pattern of the mutant to a status similar to WT versus mutants under normal temperature. The above shared 726 DEGs were significantly enriched in terms of oxidation reduction and cell wall macromolecular metabolism process (Figure 6G).

TFs usually act as gene expression activators or repressors to modulate plant development. The shared differentially expressed TFs probably contributed to the restored female fertility under LT. In total, 65 TFs were identified among the shared DEGs, and these belongs to 13 TF families, including WRKY, NAC, and ERF (Supplemental Figure S8C). To our surprise, reduced enrichment of the above TFs was identified in the female-fertile plants (Figure 6H). It possibly suggested a relatively weaker regulatory network for the normal female organ development under normal temperature. Finally, few H3K4me3 modifications overlapped with the corresponding DEGs (Supplemental Figure S8D). These results provided insights into chromatin feature changes in thermo-sensitive female sterility rice.

Discussion

The divergent architecture of female and male tissues is probably the consequence of tissue-dependent gene regulation in which different cellular contexts provide unique sets of co-regulators and chromatin accessibility in preparation for fertilization and embryogenesis. In plants, the OCR landscape has been well investigated in Arabidopsis, maize, and soybean (Parvathaneni et al., 2020; Sun et al., 2020; Huang et al., 2021, 2022; Wang et al., 2021b). Specifically, the chromatin openness of maize reproductive tissues has been well studied (Sun et al., 2020). However, it remains unclear in pistil and anther of rice. Here, the complex integrative analysis of ATAC-seq, RNA-seq, and ChIP-seq (including both H3K4me3 and TFs) datasets were conducted to address knowledge gaps regarding the development of reproductive tissues of rice: (1) What is the chromatin accessibility identity of pistil and anther? (2) How does the chromatin accessibility change in pistil and anther in response to LT treatment? and (3) What are the chromatin accessibility signatures of the thermo-sensitive female sterility mutant?

We adopted ATAC-seq to annotate accessible chromatin of pistil and anther in rice. More OCRs were identified in pistil than in anthers (Figure 1B), which is similar to the case in maize, that is, the ear had more OCRs than tassel (Sun et al., 2020). Moreover, the significant increased expression levels of genes associated with both local and distal OCRs compared with the association with either distal or local OCRs suggested distal enhancer-like feature of distal OCRs in rice, which is consistent with the observation in soybean (Huang et al., 2021). By integrating ATAC-seq with transcriptome data, we observed a modest correlation between the DEGs and changes in local OCRs upon comparison of anther and pistil (Figure 2, F and G). Collectively, the results show that the correlation of gene expression abundance and degree of local chromatin accessibility plays important roles in the morphological identity and development of pistil and anther.

OCRs usually harbor conserved cis-regulatory elements, such as TF-binding motifs, in either the promoter or the distal region (Parvathaneni et al., 2020). We identified several TFs with pistil preferential expression and identified their genome-wide binding sites through ChIP-seq. We found that TFs binding sites were enriched at OCRs, thus indicating that OCRs could be used to predict TF access in rice. The preferentially expressed TFs in pistil may lead to distinct regulatory networks, which subsequently results in the identity of pistil. We thus constructed a regulatory network of genes involved in auxin biosynthesis, transport, and response. These were potentially targeted by SPLs and have value in auxin signaling mediated rice pistil development.

Chromatin is a dynamic structure that could change in response to environmental cues. It is essential in modulating transcriptional responses (Potter et al., 2018). Here we offer a global view of the chromatin openness in pistil and anther, respectively, in response to LT. We observed a tissue-specific open chromatin pattern induced by LT with few LT-induced OCRs shared between pistil and anther. Fewer changes in chromatin openness of pistil indicated that pistil was more stable than anther in response to LT. This was further supported by fewer DEGs number in pistil treated with LT than in anther.

Our study suggests association of the open chromatin with gene expression. There were still expressed genes that lacked association with OCRs in both pistil and anther. This is consistent with the results of recent studies in Arabidopsis (Potter et al., 2018) and maize (Sun et al., 2020). The possible reason could be that the open chromatin identified from a heterogeneous cell population are too rough to identify these chromatin changes, and thus identifying chromatin alterations at single-cell resolution using single nuclei ATAC may help solve the problem (Marand et al., 2021).

Conclusions

Alternation of gene function may be caused by mutations in coding regions and in cis-regulatory regions. Recent studies have demonstrated that variations in cis-regulatory regions such as promoters, result in quantitative variation of desirable traits in crop domestication and improvement both in tomato and rice through altered gene expression (Hendelman et al., 2021; Wang et al., 2021b; Song et al., 2022). In contrast to the coding region mutations, dissecting the functional sequence of cis-regulatory variations is even more challenging because of the large number of cis-regulatory elements surrounding the genes. Therefore, deciphering or predicting the rice cis-regulatory elements genome-wide based on sequence conservation, TF binding, and chromatin accessibility is crucial for rice improvement.

Materials and methods

Plant materials and sampling

Rice (O. sativa) variety of “4266” containing 70% indica and 30% japonica backgrounds were examined under natural field conditions and grown at the gene garden of The Chinese University of Hong Kong, Hong Kong, China (April–July 2020). For LT (23°C, 13-h light) conditions, the plants were grown in the growth chamber at The Chinese University of Hong Kong, Hong Kong, China (April–July 2020). Young panicles between 2 and 5 mm in length, pistil, and anther before flowering were sampled for further experiments. Specifically, pistil and anther in the same spikelet that had not yet flowered after heading were collected. Tweezers were used to expose and collect the young panicles, pistil, and anther during the sampling process. The female-sterility mutant was a spontaneous mutation identified from the 4,266 plants during paddy field production.

ATAC-seq and data analysis

Freshly collected young panicle, pistil, and anther were immediately chopped with two biological replicates using a razor blade for 5 min in 100 μL lysis buffer (20 mM MES, pH 5.7, 0.6 M Mannitol, 10 mM MgCl2, 10 mM KCl, 0.1% [v/v] 2-mercaptoethanol, and 0.2% [v/v] Triton X-100, 1× protease inhibitor [PI]) on ice (two biological replicates were performed). Thereafter the chopped slurry was carefully washed in a 1.5 mL microcentrifuge tube with 1 mL lysis buffer. The tube was chilled on ice with gentle shaking for 10 min. The mixture was filtered through a 40-μm filter into a new tube, followed by centrifugation at 500 g for 8 min (4°C). Then, we discarded the supernatant, and resuspended the precipitation with 150 µL wash buffer (20 mM Tris–HCl pH 7.8, 10 mM MgCl2, 60 mM KAc pH 5.6). Part of the nuclei was stained with trypan blue and loaded on a flow cytometer to determine the number of nuclei (50,000 nuclei per reaction). The above-washed nuclei were then tagged with TS-Tn5 at 37°C for 30 min following the kit’s instructions (Vazyme, Nanjing, China; TD501). After tagging, the integration products were purified using DNA Purification Kit (ZYMO, Irvine, California, USA; D4004) and then amplified using Q5 high fidelity DNA polymerase (New England Biolabs, Ipswich, Massachusetts, USA; M0491S) for 10–15 cycles using index provided in TruePrep Index Kit V2 for Illumina kit (TD202). PCR cycle was determined as previously reported (Buenrostro et al., 2013). Amplified libraries were purified with AMPure beads (Beckman Coulter, Brea, California, USA; Cat No./ID: A63880). The libraries were sequenced on Illumina HiSeq X Ten with paired-end reads of 150 bp.

ATAC-seq reads were aligned to O. sativa (MSU7.0) reference genome using Bowtie 2 (version 2.3.2.) (Langmead and Salzberg, 2012). For paired-end 150 bp reads, 100 bp sequences at the 3′-end of the reads were trimmed with the parameter “-3 100.” We used SAMtools (version 1.9) (Li et al., 2009) to filter the low quality and duplicated reads using the parameters “-F 4 -q 20.” The bigwig files were generated by deepTools (version 2.5.3) (Ramírez et al., 2016) with the command “bamCoverage –normalizeUsingRPKM.” For ATAC peak calling, the MACS2 parameters were “-g 2e8 –nomodel –extsize 70 –shift -35 -q 0.01.” We determined the peaks with high reproducibility scores shared between the two biological replicates by using the irreproducibility discovery rate (IDR). The differential binding events were identified using the R package “DiffBind.” All OCRs were then divided into local OCRs and distal OCRs. A gene that has the shortest distance between its TSS and distal OCR is considered as the “most proximal gene” of the distal OCR (Zhu et al., 2015), which were defined as distal OCR-associated genes.

RNA-seq and data analysis

Total RNA was isolated from pistil and anther with two biological replicates using Plant RNA Extraction Kit (Qiagen, Hilden, Germany; Cat, No. 74904) following the manufacturer’s instructions, and genomic DNA was removed with the RNase-free DNase Set (Qiagen; Cat. No. 79254). Messenger RNAs were isolated with Oligo d(T)25 Magnetic Beads (New England Biolabs; Cat. S1419S) and used for preparing the Illumina library. The libraries were sequenced on an Illumina HiSeq X Ten with paired-end reads of 150-bp.

RNA-seq reads were trimmed by seqtk with parameters “trimfq -e 100” and then mapped to rice reference genome using Hisat2 with default parameters (Tu et al., 2020). Reads were counted by “HTseq-count” (version 0.11.0, https://htseq.readthedocs.io/en/release_0.11.1/) with parameters “–format=bam –stranded=no –type=mRNA –idattr=Parent.” FPKM values were calculated by Cufflinks (Trapnell et al., 2012) with “–multi-read-correct –min-isoform-fraction 0.2 –max-intron-length 10000 –max-multiread-fraction 0.5.” Differential gene expression was performed using R package DESeq2 (Love et al., 2014). Genes were considered to be differentially expressed if they showed at least two-fold difference with an adjusted P-value < 0.01.

Histone ChIP-seq and data analysis

Rice anther and pistil with two biological replicates were cross-linked with 1% (w/v) formaldehyde in PBS buffer for 30 min, and glycine was added (final concentration is 0.1 M) to stop the reaction. The cross-linked samples were then blot dried by tissue paper and ground into fine powder in liquid nitrogen. The fine powder was then added with 10 ml nuclei isolation buffer 1 (10 mM Tris–HCl, pH 8.0, 1 mM EDTA, 0.25 M sucrose, 1% [v/v] Triton X-100, PI) in a 15 mL tube. The mixture was then shaken at 80 rpm on ice for 10 min, and filtered through a 40-μm filter. The filtered supernatant was then centrifuged for 10 min at 6,000 g (4°C) to obtain the precipitation. The precipitate was then resuspended with buffer 2 (10 mM Tris–HCl, pH 8.0, 1 mM EDTA, 1% (v/v) Triton X-100, 1× PI) followed by centrifuging for 10 min at 6,000 g (4°C). We removed the supernatant and resuspended it in buffer 2 again, followed by the centrifuging to obtain the precipitation. Next, 100 µL of sonication buffer (10 mM Tris–HCl, PH 8.0, 1 mM EDTA, 0.2% [w/v] SDS, 1× PI) was added to precipitate and mixed well for sonication (30 cycles of 30-s on, 30-s off on a Diagenode Bioruptor). Tubes were centrifuged at 10,000 g for 5 min and supernatants were transferred to new tubes. At this point, ChIP input aliquots were collected.

Dynabeads Protein A (Thermo Fisher Scientific, Waltham, Massachusetts, USA; cat. no. 10002D) were washed with low salt buffer (10 mM Tris–HCl, pH 8.0, 1 mM EDTA, 150 mM NaCl, 1% [v/v] Triton X-100, 1× PI) and then rotated with antibodies (Anti-Trimethyl-Histone H3 [Lys4] Rabbit Monoclonal Antibody [RM340] Cat No 31-1226-00) at a concentration of 2 μg antibody per 100 μL of ChIP dilution buffer overnight at 4°C. After binding, the beads were washed with low salt buffer (10 mM Tris–HCl, pH 8.0, 1 mM EDTA, 150 mM NaCl, 1% [v/v] Triton X-100, 1× PI), high salt buffer (10 mM Tris–HCl pH 8.0, 1 mM EDTA, 500 mM NaCl, 0.5% [v/v] Triton X-100, 1× PI),, and 10 mM Tris–HCl (pH 8.0) twice. The immunoprecipitated DNA was tagged with TS-Tn5 (Vazyme; TD-501) at 37°C for 30 min as previously described (Schmidl et al., 2015). They were then washed with low salt buffer, high salt buffer, and 10 mM Tris–HCl. After being reverse-crosslinked and treated with proteinase K in accordance with the referenced protocol (Schmidl et al., 2015), DNA was purified with DNA recovery beads. The recovered DNA was then amplified following 72°C for 2 min, 98°C for 30 s, then 10–15 cycles of 98°C for 15 s, 63°C for 30 s, 72°C for 30 s and once at 72°C for 1 min using TruePrep Index Kit V2 for Illumina (Vazyme; cat.no.TD202). PCR products were purified with AMPure beads to remove primers. The libraries were then sequenced on Illumina X Ten platforms in PE150 mode.

ChIP-seq reads were aligned to the O. sativa (MSU7.0) reference genome using Bowtie 2 (version 2.3.2.) (Langmead and Salzberg, 2012). For paired-end 150 bp reads, the 100 bp sequences at the 3′ end of the reads were trimmed with the parameter “-3 100.” We used SAMtools (version 1.9) (Li et al., 2009) to filter the low quality and duplicated reads using the parameters “-F 4 -q 20.” The bigwig files were generated by deepTools (version 2.5.3) (Ramírez et al., 2016) with the command “bamCoverage –normalizeUsingRPKM.” We applied MACS2 with parameters “-g 2e8 –nomodel -q 0.01” to call peaks that were normalized with the input control.

Plasmid construction for the ChIP-seq of TF

The open-reading frame of TFs was amplified and then cloned into pENTR11 (Thermo fisher; A10467). Primers were listed in Supplemental Table S20. The LR recombination reaction used the gateway system was performed with the binary vector of pMDC43.gb confused with GFP at the N-terminus of the TF, which was driven by a CaMV 35S promoter.

Rice protoplast transfection for ChIP-seq of TFs

Protoplast was isolated from 8-day-old rice seedlings. Stem and leaf sheath tissues were cut into ∼0.5 mm strips, which were immediately transferred into enzymatic digestion buffer (20 mM MES pH 5.7, 10 mM CaCl2, 0.4 M Mannitol, 1.5% [w/v] Cellulase RS [Yakult], 0.4% [w/v] Macerozyme R-10 [Yakult], 0.1% [w/v] BSA, 20 mM KCl) in the dark with gentle shaking for 4 h. The protoplasts were collected by filtration through a 40-μm nylon meshes and centrifuged for 10 min at 100 g. The W5 solution (2 mM MES pH 5.7, 5 mM KCl, 5 mM NaCl, 125 mM CaCl2) was added to resuspend the protoplasts. The protoplasts were centrifuged at 100 g and resuspended in MMG solution (4 mM MES pH 5.7, 0.4 M Mannitol, 15 mM MgCl2). The constructed plasmids (50 μg plasmid incubated with 106 protoplasts [∼1 mL volume]) were transiently transformed into the protoplast with two biological replicates as described previously (Wang et al., 2021c, 2021d). After incubation for 16–24 h, the protoplasts were observed by confocal microscopy for GFP fluorescence (imaged with 488 and 555 nm laser excitation, and emission fluorescence was captured by 500–520 and 560–580 nm band-pass emission filters, respectively) to check the protein expression status.

TF ChIP-seq and data analysis

The protoplasts that showed GFP fluorescence (>50% transformation rate) were collected for cross-linking by 1% (w/v) formaldehyde in PBS buffer for 5 min on ice. They were subsequently added with glycine (at a final concentration of 0.1 M) to stop the fixation by further incubating on ice for 5 min. The methods for the nuclei isolation, protein binding, and library construction were similar to the histone ChIP-seq described above. The anti-GFP antibody was ordered from Takara, Shiga, Japan (Cat No. 632381).

The method for ChIP-seq reads mapping and trimming were same as histone ChIP-seq described above. The SPP peak caller from PhantomPeakQualTools (version 1.14) (Landt et al., 2012) was used to access regions with high signal-to-noise ratio with parameters “-npeak = 300000 -savp -savr”; each replicate had a corresponding input as control. IDR (version 2.0.3) (Li et al., 2011) was used with “–idr-threshold 0.01” to obtain reproducible peaks from replicates. TIP (Cheng et al., 2011) model was applied to associate peak to target genes.

Motif analysis

The MEME suite software package was used for motif analysis using the default parameters (Bailey et al., 2009). The rice (O. sativa “Nipponbare”) TF motif position weight matrix was downloaded from PlantPAN version 3.0. Differential OCRs under LT treatment were used for the analysis of LT responsive motif.

GO analysis

Functional GO enrichment analysis was performed by web-based toolkit for the agricultural community agriGO version 2.038 (http://systemsbiology.cau.edu.cn/agriGOv2/). GO terms with a FDR < 0.05 were considered significantly enriched.

Statistical analysis

The P-value was calculated by the Wilcoxon test.

Accession numbers

All sequencing data generated in this study are available at Sequence Read Archive under accession number PRJNA751145.

Supplemental data

The following materials are available in the online version of this article.

Supplemental Figure S1. Reproducibility analysis between replicates of all the ATAC-seq datasets.

Supplemental Figure S2. OCRs in pistil and distribution of transcript levels (FPKM) in pistil and anther.

Supplemental Figure S3. KEGG analysis of the DEGs between anther and pistil.

Supplemental Figure S4. Reproducibility analysis between replicates of all the H3k4me3 ChIP-seq datasets.

Supplemental Figure S5. TF binding motifs predicted at OCRs.

Supplemental Figure S6. Integrative genomics viewer (IGV) showing the pistil-enriched OCRs in SPL4, and pistil-specific OCRs in GRF2 and GRF3.

Supplemental Figure S7. Anther and pistil showed different response to LT.

Supplemental Figure S8. Gene expression changes of thermo-sensitive female sterility mutant under normal and LT.

Supplemental Table S1. Sequencing data summary of ATAC-seq of pistil and anther.

Supplemental Table S2. Annotation of ATAC-seq peaks in pistil of rice.

Supplemental Table S3. Annotation of ATAC-seq peaks in anther of rice.

Supplemental Table S4 . OCRs comparison between pistil and anther.

Supplemental Table S5. DEGs between pistil and anther.

Supplemental Table S6. DOCRs associated with the promoter between anther and pistil.

Supplemental Table S7. H3K4me3 peaks identified in anther.

Supplemental Table S8. H3K4me3 peaks identified in pistil.

Supplemental Table S9. Binding sites of SPL3 associated to the promoter (2-kb upstream of TSS) region.

Supplemental Table S10. Binding sites of SPL4 associated to the promoter (2-kb upstream of TSS) region.

Supplemental Table S11. Binding sites of SPL14 associated to the promoter (2-kb upstream of TSS) region.

Supplemental Table S12. Annotation of ATAC-seq peaks in pistil of rice responded to LT.

Supplemental Table S13. Annotation of ATAC-seq peaks in anther of rice responded to LT.

Supplemental Table S14. DOCRs of anther in response to LT associated with the promoter.

Supplemental Table S15. DOCRs of pistil in response to LT associated with the promoter.

Supplemental Table S16. DEGs of anther in response to LT.

Supplemental Table S17. DEGs of pistil in response to LT.

Supplemental Table S18. H3K4me3 peaks identified in anther in response to LT.

Supplemental Table S19. H3K4me3 peaks identified in pistil in response to LT.

Supplemental Table S20. Primers for plasmid construction used in the TF ChIP-seq.

Supplementary Material

kiac448_Supplementary_Data
Click here for additional data file. (18.4MB, zip)

Acknowledgments

We thank Qianwen Wang for some scientific advice.

Funding

This work was supported by the Hong Kong Research Grant Council (AoE/M-05/12, AoE/M-403/16, GRF14122415, 14160516, 14177617, 12100318, 1210321, and 12103220) and the National Key Research and Development Program of China (2018YFA0902500), and the Shenzhen Science and Technology Research Funding (JCYJ20180305124041430).

Conflict of interest statement. The authors declare that they have no competing interests.

Contributor Information

Guanqun Wang, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen 518000, China; State Key Laboratory of Agrobiotechnology, School of Life Sciences, The Chinese University of Hong Kong, Shatin 999077, Hong Kong.

Xiaozheng Li, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen 518000, China.

Wei Shen, State Key Laboratory of Agrobiotechnology, School of Life Sciences, The Chinese University of Hong Kong, Shatin 999077, Hong Kong.

Man-Wah Li, State Key Laboratory of Agrobiotechnology, School of Life Sciences, The Chinese University of Hong Kong, Shatin 999077, Hong Kong.

Mingkun Huang, Lushan Botanical Garden Jiangxi Province, Chinese Academy of Sciences, Jiujiang 332900, China.

Jianhua Zhang, State Key Laboratory of Agrobiotechnology, School of Life Sciences, The Chinese University of Hong Kong, Shatin 999077, Hong Kong; Department of Biology, Hong Kong Baptist University, Kowloon 999077, Hong Kong.

Haoxuan Li, State Key Laboratory of Agrobiotechnology, School of Life Sciences, The Chinese University of Hong Kong, Shatin 999077, Hong Kong; Department of Biology, Hong Kong Baptist University, Kowloon 999077, Hong Kong.

 

These authors contributed equally (G.W., X.L., and W.S.)

J.Z. and H.L. conceived the research. G.W. and H.L. performed all the experiments and analyzed all the sequencing data. H.L. and W.S. plotted the figures. G.W. and X.L. wrote the manuscript. H.L., M.-W.L., and G.W. revised the manuscript. All authors read and approved the final manuscript.

The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (https://academic.oup.com/plphys/pages/general-instructions) is: Zhang Jianhua (jzhang@hkbu.edu.hk).

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