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. 2018 Feb;16(2):672-687.
doi: 10.1111/pbi.12820. Epub 2017 Sep 22.

Single-base Methylome Analysis Reveals Dynamic Epigenomic Differences Associated With Water Deficit in Apple

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Free PMC article

Single-base Methylome Analysis Reveals Dynamic Epigenomic Differences Associated With Water Deficit in Apple

Jidi Xu et al. Plant Biotechnol J. .
Free PMC article

Abstract

Cytosine methylation is an essential feature of epigenetic regulation and is involved in various biological processes. Although cytosine methylation has been analysed at the genomic scale for several plant species, there is a general lack of understanding of the dynamics of global and genic DNA methylation in plants growing in environments challenged with biotic and abiotic stresses. In this study, we mapped cytosine methylation at single-base resolution in the genome of commercial apple (Malus x domestica), and analysed changes in methylation patterns associated with water deficit in representative drought-sensitive and drought-tolerant cultivars. We found that the apple genome exhibits ~54%, ~38% and ~8.5% methylation at CG, CHG and CHH sequence contexts, respectively. We additionally documented changes in gene expression associated with water deficit in an attempt to link methylation and gene expression changes. Global methylation and transcription analysis revealed that promoter-unmethylated genes showed higher expression levels than promoter-methylated genes. Gene body methylation appears to be positively correlated with gene expression. Water deficit stress was associated with changes in methylation at a multitude of genes, including those encoding transcription factors (TFs) and transposable elements (TEs). These results present a methylome map of the apple genome and reveal widespread DNA methylation alterations in response to water deficit stress. These data will be helpful for understanding potential linkages between DNA methylation and gene expression in plants growing in natural environments and challenged with abiotic and biotic stresses.

Keywords: apple; epigenetics; gene expression; methylomes; transcriptome; water deficit.

Figures

Figure 1
Figure 1
Relative expression analysis of genes encoding homologs of DNA methyltransferase and demethylases under drought stress for 2, 4, 6 or 8 days using real‐time PCR. Transcripts of Malus elongation factor 1 alpha gene (EF‐1α, DQ341381) were used as an endogenous control to normalize expression in different samples. Bars represented means ± SD from three biological replicates. Each biological replicate was performed with independent RNA extractions and two technical replicates. Significant differences calculated from the three biological replicates were indicated by *(P value < 0.05) and **(P value < 0.01).
Figure 2
Figure 2
The apple epigenome. (a) Relative proportions of mCs in three sequence contexts (CG, CHG and CHH) in apple, tomato, Arabidopsis and rice. (b) Circos plots of chromosomes in apple genome. Track order: density plot of 5mC in CG, CHG and CHH contexts; density of transposable elements (TEs); gene density of each chromosome. (c) Distributions of 5‐methylcytosine density on chromosome 1. Q_C, ‘Qinguan’ control; Q_WD, ‘Qinguan’ water deficit.
Figure 3
Figure 3
DNA methylation patterns in different genomic regions. (a) Percentage of methylation levels of promoter, transposable element (TE), coding genes with 5′UTR, exon, intron, CDS, 3′UTR regions. (b) Distributions of DNA methylation levels among gene features, including promoter, 5′UTR, exon, intron, 3′UTR and downstream 2 kb. (c) Percentage of methylation levels among TE regions and their 2‐kb upstream and downstream regions.
Figure 4
Figure 4
Relationship between DNA methylation and gene expression. (a) Distributions of methylation levels within gene bodies partitioned by different expression levels: 1st_quintile is the lowest and 5th_quintile is the highest; genes with FPKM value <0.1 were considered nonexpressed (none). (b) Expression profiles of methylated genes compared with unmethylated genes. Methylated genes were further divided into quintiles based on promoter, gene body and transcriptional termination region (TTR) methylation levels: 1st_quintile is the lowest and 5th_quintile is the highest.
Figure 5
Figure 5
Methylation patterns of transposable elements in the apple genome. (a) Numbers of different types of TEs in apple genome. (b) Percentage of methylation levels of different types of TEs in ‘Qinguan’ and ‘Honeycrisp’. (c) Methylation patterns of different types of TEs with different length. TEs divided into quintiles based on their length: 1st_quintile is the shortest and 5th_quintile is the longest length of TEs. Q_C, ‘Qinguan’ control; H_C, ‘Honeycrisp’ control.
Figure 6
Figure 6
Differential methylome analysis under water deficit stress. (a) Numbers of differentially methylated regions (DMR), genes (DMGs) and TEs. (b) Venn diagram of hyper/hypomethylated genes among ‘Qinguan’ and ‘Honeycrisp’ under water deficit stress. (c) Heat maps of methylation levels within CG, CHG and CHH DMRs, respectively; (d) KEGG pathway enrichment of hypermethylated and hypomethylated genes in two cultivars under water deficit. The size of the circle represents gene numbers, and the colour represents the q‐value. Q_WDvsQ_C, ‘Qinguan’ water deficit versus ‘Qinguan’ control; H_WDvsH_C, ‘Honeycrisp’ water deficit versus ‘Honeycrisp’ control.
Figure 7
Figure 7
Assignment of differentially methylated genes among ‘Qinguan’ (a) and ‘Honeycrisp’ (b) under water deficit in Mapman bins. The red and blue squares indicated the hyper‐ and hypomethylated genes. (c) Venn map of differentially methylated transcriptional factors (TFs); (d) IGV software depicts the demethylation of OCP3 promoter region induced by water deficit stress in ‘Honeycrisp’; (e) the methylation difference of MdOCP3 in ‘Honeycrisp’ under water deficit; (f) expression analysis of MdOCP3 in ‘Qinguan’ and ‘Honeycrisp’ under water deficit. Q_WDvsQ_C, ‘Qinguan’ water deficit versus ‘Qinguan’ control; H_WDvsH_C, ‘Honeycrisp’ water deficit versus ‘Honeycrisp’ control. Significant differences calculated from the three replicates were indicated by ** (P value < 0.01).
Figure 8
Figure 8
(a) Numbers of differentially methylated TEs in ‘Qinguan’ or ‘Honeycrisp’ under water deficit; (b) heat maps of differentially methylated TEs; (c) IGV snapshots of five representative hypo‐ and hypermethylated TEs in ‘Qinguan’ and ‘Honeycrisp’ under water deficit. Q_WDvsQ_C, ‘Qinguan’ water deficit versus ‘Qinguan’ control; H_WDvsH_C, ‘Honeycrisp’ water deficit versus ‘Honeycrisp’ control.
Figure 9
Figure 9
(a) Heap maps of differentially expressed genes (DEGs). Venn diagram of DMGs (differentially methylated genes) and DEGs in QWDvsQC (b) and HWDvsHC (c). (d) Differential expression levels of all genes (red box), hypermethylated genes (green box) and hypomethylated genes (blue box) are displayed as boxplots (boxes represent the quartiles; whiskers mark data within 1.5 interquartile ranges of the quartile; Wilcoxon P values are reported). QWDvsQC, ‘Qinguan’ water deficit versus ‘Qinguan’ control; HWDvsHC, ‘Honeycrisp’ water deficit versus ‘Honeycrisp’ control.
Figure 10
Figure 10
Differential methylation analysis between ‘Qinguan’ (‘QG’) and ‘Honeycrisp’ (‘HC’). (a) Numbers of DMR genes in different gene features among HCvsQC (‘HC’ control versus ‘QG’ control); (b) Venn maps of DMR genes and DEGs; (c) differential expression levels of all genes, hypomethylated genes and hypermethylated genes are displayed as boxplots among HCvsQC and HWDvsQWD (‘HC’ water deficit versus ‘QG’ water deficit; Wilcoxon P values are reported).

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