How to Isolate a Plant's Hypomethylome in One Shot

Abstract

Genome assembly remains a challenge for large and/or complex plant genomes due to their abundant repetitive regions resulting in studies focusing on gene space instead of the whole genome. Thus, DNA enrichment strategies facilitate the assembly by increasing the coverage and simultaneously reducing the complexity of the whole genome. In this paper we provide an easy, fast, and cost-effective variant of MRE-seq to obtain a plant's hypomethylome by an optimized methyl filtration protocol followed by next generation sequencing. The method is demonstrated on three plant species with knowingly large and/or complex (polyploid) genomes: Oryza sativa, Picea abies, and Crocus sativus. The identified hypomethylomes show clear enrichment for genes and their flanking regions and clear reduction of transposable elements. Additionally, genomic sequences around genes are captured including regulatory elements in introns and up- and downstream flanks. High similarity of the results obtained by a de novo assembly approach with a reference based mapping in rice supports the applicability for studying and understanding the genomes of nonmodel organisms. Hence we show the high potential of MRE-seq in a wide range of scenarios for the direct analysis of methylation differences, for example, between ecotypes, individuals, within or across species harbouring large, and complex genomes.

Figure 1

Genes and transposable elements identified in the rice genome with the methyl filtration technique. The regions comprised of at least five reads (left), and all regions (middle) show a clear depletion of transposable elements for AciI, Bsh1236I, and HpaII. On the right a representation of genes and transposable elements is given showing potential methylation sites within their gene space. All values are shown in percent based on the annotated 39.954 genes and 15.847 transposable elements.

Figure 2

Length distribution of genomic regions identified for AciI, HpaII, and the combined dataset in rice. The length distribution of hypomethylated regions identified with the three datasets up to the maximal length is shown as well as a closer view to the region between 0 and 2.000 bp, where an increase in length is visible for the combined dataset. Additionally, the amount of regions, the average and maximum length, and the average reads per region are given.

Figure 3

Overlap between the datasets in rice. The hypomethylated regions identified with the three datasets are compared focussing on genomic area, annotated gene models (including both genes and TEs and their surrounding +/− 1.000 bp regions), and genes and TEs separately. The total in each category is given in the table above while the overlap is visualized in the separate Venn diagrams.

Figure 4

Complementary identification of genomic regions in rice due to restriction site locations. A detailed representation of the mapping results is shown for both enzymes, AciI and HpaII. The identified regions around the displayed gene differ due to the lack of recognition sites for the other enzyme. On the right, an example for overlapping but expanded regions is given.

Figure 5

Genomic overview of hypomethylated regions in rice. The results of the de novo assembly and mapping approach are displayed for all three datasets (AciI, HpaII, and combined). In the upper panel the positions of the recognition sites are shown. The locations of annotated genes and TEs are depicted as well as the regions identified with the data of previous methylation studies (lower two tracks). The positions of the centromeric regions are also indicated and represented by green lines.

Figure 6

A simulation performed in rice to estimate the minimal coverage necessary to identify the hypomethylome of the whole genome was performed by randomly selecting reads from the combined dataset with 7x coverage to represent different coverage thresholds. The reads were allocated to the genome sequence and compared to the result of the complete dataset (100%) regarding genome area, gene space area, gene area, and exon area.

Figure 7

Reads located within the gene space (gene and surrounding +/− 1.000 bp regions) and the annotated TE (including surrounding +/− 1.000 bp regions) in Norway spruce. A clear enrichment of reads derived from gene regions and a clear depletion of reads derived from TE regions are shown.