Paternally Acting Canonical RNA-Directed DNA Methylation Pathway Genes Sensitize Arabidopsis Endosperm to Paternal Genome Dosage

Abstract

Seed development is sensitive to parental dosage, with excess maternal or paternal genomes creating reciprocal phenotypes. Paternal genomic excess frequently results in extensive endosperm proliferation without cellularization and seed abortion. We previously showed that loss of the RNA polymerase IV gene NUCLEAR RNA POLYMERASE D1 (NRPD1) in tetraploid fathers represses seed abortion in paternal excess crosses. Here, we show genetically that RNA-directed DNA methylation (RdDM) pathway activity in the paternal parent is sufficient to determine the viability of paternal excess Arabidopsis (Arabidopsis thaliana) seeds. We compared transcriptomes, DNA methylation, and small RNAs from the endosperm of seeds from balanced crosses (diploid × diploid) and lethal (diploid × tetraploid) and viable paternal excess crosses (diploid × tetraploid nrpd1). Endosperms from both lethal and viable paternal excess seeds share widespread transcriptional and DNA methylation changes at genes and transposable elements. Interploidy seed abortion is thus unlikely to be caused by transposable elements or imprinted gene misregulation, and its repression by the loss of paternal RdDM is associated with only modest gene expression changes. Finally, using allele-specific transcription data, we present evidence for a transcriptional buffering system that increases the expression of maternal alleles and represses paternal alleles in response to excess paternal genomic dosage. These findings prompt reconsideration of models for dosage sensitivity in endosperm.

Figure 1.

Loss of Paternal RdDM Genes but Not RDR6 Represses Seed Abortion in Paternal Excess Crosses. (A) Each circle represents the seed abortion rate in one cross and represents multiple siliques from a single inflorescence. (B) Each circle represents the percent of seeds that failed to germinate from each scored collection of seeds. Failure to germinate was defined as the inability to produce either a radicle or a hypocotyl. Bars show median and interquartile range. * at the bottom represents statistically significant difference (P < 0.05) in comparisons between the indicated cross and the cross between wild-type (WT) diploid (2n) Col-0 mothers and wild-type tetraploid (4n) Col-0 fathers. * at the top represents statistically significant differences (P < 0.05) between the indicated crosses. Statistical significance calculated by Wilcoxon test.

Figure 2.

Lethal and Viable Paternal Excess Endosperms Are Transcriptionally More Similar to Each Other Than to Balanced Endosperm. (A) PCA plot of read counts for genes from biological replicate mRNA-Seq samples. (B) Plot of the number of genes differentially expressed in comparisons of balanced endosperm with both lethal (purple) and viable (yellow) ♂ excess endosperm. Only 614 genes were differentially expressed between viable and lethal ♂ excess endosperm (gray). (C) Correction value in viable paternal excess endosperm for each gene that was called as being significantly differentially expressed in comparisons of balanced and lethal ♂ excess endosperm. The value was calculated as ). A value of 100% indicates that the gene, which was misregulated in lethal ♂ excess, was not differentially expressed in viable ♂ excess relative to balanced endosperm. A value of 0% represents similar misregulation in both lethal and viable ♂ excess relative to balanced endosperm. Fold change values and significance for fold change for (B) and (C) were calculated using Cuffdiff. Boxplot is a Tukey plot. (D) Lethal paternal excess endosperm was enriched for chalazal endosperm gene expression; viable paternal excess endosperm showed both chalazal and peripheral markers. Tissue enrichment for each biological replicate is shown.

Figure 3.

Imprinted Genes and Transposons Are Misregulated in Both Lethal and Viable Paternal Excess Endosperm. (A) to (C) Expression of Col-Ler imprinted genes in endosperm. FPKM is normalized expression; statistical significance of difference in abundance was calculated by Cuffdiff. q < 0.05 is represented by black circles. q > 0.05 is represented by gray circles. (D) to (F) Expression from transposable elements is elevated in lethal and viable ♂ excess endosperm. RNA-Seq reads were mapped to consensus sequences from Repbase. Black circles represent TEs with significant differences in transcript abundances according to DEGseq, q < 0.05. Gray circles represent TEs without significant differences in transcript abundances.

Figure 4.

Canonical RdDM Pathway Function in Endosperm Is Affected by Paternal Excess. (A) Genes encoding RdDM components are downregulated in lethal and viable ♂ excess endosperm. ROS1 expression is a readout of RdDM activity and reflects differential activity of RdDM. * represents statistically significantly different gene expression, q < 0.05. (B) Small RNA production is impacted in paternal excess endosperm. Nucleotide (nt) size profiles of sRNA reads mapped to the TAIR10 genome for three replicates of balanced endosperm and two replicates each of lethal and viable paternal excess endosperm. (C) CHH methylation losses in paternal excess endosperm. Venn diagrams show the intersections of CHH DMRs obtained from comparisons of balanced (Bal), lethal, and viable paternal excess endosperm. Lethal and viable paternal excess endosperms share a significant proportion of regions that are hypomethylated relative to balanced endosperm. A smaller subset of DMRs lost more methylation in lethal relative to viable endosperm. (D) Loss of CHH methylation is associated with the loss of 24-nucleotide (nt) sRNAs. Venn diagrams show the relationship between changes in sRNA abundance and CHH methylation levels. A subset of CHH DMRs is associated with the loss of sRNAs. A smaller subset is associated with gains in 24-nt sRNAs. Significance of overlaps was calculated using the Fisher test option from Bedtools.

Figure 5.

Allelic Contributions to Expression Differences between Balanced and Lethal Paternal Excess Endosperm. (A) Paternal fraction in genic transcripts. Boxplot represents all genes with at least 50 allele-specific reads in the indicated genotypes. Number of genes in balanced, 10,388; lethal ♂ excess, 11,709; viable ♂ excess, 11,430. For balanced endosperm, a total of five replicate libraries were analyzed (Erdmann et al., 2017). (B) Paternal excess endosperm transcriptome is maternally skewed. Frequency distribution plot of % paternal deviation for each gene. Paternal deviation was calculated for genes with at least 50 allele-specific reads in each pair of genotypes being compared. Number of genes in lethal ♂ excess - balanced, 9,550; viable ♂ excess - balanced, 9,639; viable ♂ excess - lethal ♂ excess, 10,919. (C) Decreased paternal allele contribution at a larger proportion of genes with decreased expression in lethal paternal excess compared with balanced. n = 1910 genes. Impacts of allele-specific changes on gene expression for two examples, WOX8 and AT2G01580, are shown. (D) Increased maternal allele activation at a larger proportion of genes with increased expression in lethal paternal excess. n = 1608 genes. Impacts of allele-specific changes on gene expression for two examples, SDG21 and HEXO3, are shown. Genes analyzed in (C) and (D) were detected as having significantly different expression levels by Cuffdiff. A gene with an allelic shift of at least 20% was considered to have a modified allelic balance. Boxplots represent median values for paternal deviation from genomic expectation. For gene-specific histograms, the maternal allele is shown in red and the paternal allele is shown in blue. (E) sRNA populations are increasingly maternally biased in paternal excess endosperm. The paternal fraction of sRNA populations from viable paternal excess endosperm is intermediate between lethal paternal excess and balanced endosperm. Data from three replicates of balanced endosperm and two replicates each of lethal and viable paternal excess endosperm are plotted. sRNA reads mapped to the TAIR10 genome were first split based on size and then into Col and Ler reads using single nucleotide polymorphisms. % of paternal reads and deviation from genomic expectation at each size were calculated.