Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Aug 7;11(8):jkab190.
doi: 10.1093/g3journal/jkab190.

Stability of DNA methylation and chromatin accessibility in structurally diverse maize genomes

Affiliations

Stability of DNA methylation and chromatin accessibility in structurally diverse maize genomes

Jaclyn M Noshay et al. G3 (Bethesda). .

Abstract

Accessible chromatin and unmethylated DNA are associated with many genes and cis-regulatory elements. Attempts to understand natural variation for accessible chromatin regions (ACRs) and unmethylated regions (UMRs) often rely upon alignments to a single reference genome. This limits the ability to assess regions that are absent in the reference genome assembly and monitor how nearby structural variants influence variation in chromatin state. In this study, de novo genome assemblies for four maize inbreds (B73, Mo17, Oh43, and W22) are utilized to assess chromatin accessibility and DNA methylation patterns in a pan-genome context. A more complete set of UMRs and ACRs can be identified when chromatin data are aligned to the matched genome rather than a single reference genome. While there are UMRs and ACRs present within genomic regions that are not shared between genotypes, these features are 6- to 12-fold enriched within regions between genomes. Characterization of UMRs present within shared genomic regions reveals that most UMRs maintain the unmethylated state in other genotypes with only ∼5% being polymorphic between genotypes. However, the majority (71%) of UMRs that are shared between genotypes only exhibit partial overlaps suggesting that the boundaries between methylated and unmethylated DNA are dynamic. This instability is not solely due to sequence variation as these partially overlapping UMRs are frequently found within genomic regions that lack sequence variation. The ability to compare chromatin properties among individuals with structural variation enables pan-epigenome analyses to study the sources of variation for accessible chromatin and unmethylated DNA.

Keywords: DNA methylation; chromatin accessibility; comparative epigenomics.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Identification of UMRs and ACRs in maize genotypes. (A) The number of UMRs defined based on samples aligned to B73v4 (green) and their own genome assembly (orange). (B) The location of UMRs and ACRs in the genome based on gene annotations was classified as overlapping genes (green), within 2 kb of a gene (orange) and >2 kb from a gene (purple). (C) The number of ACRs defined based on the merged replicates for each genotype aligned to their respective genome assemblies. (D) Overlap between the B73 UMRs and ACRs defined based on alignments to the B73v4 genome. The number in parentheses indicates ACRs that are defined as methylated as opposed to missing data. (E–H) Accessibility is often present only for a portion of the UMR. Several B73 UMRs are shown along with ATAC-seq data. IGV (Robinson et al. 2011) snapshots of the B73 genome showing ACRs within UMR space. Tracks include B73 gene and TE annotations, B73 methylation per cytosine in all contexts (CG: blue, CHG: red, CHH: yellow), B73 UMRs (black), B73 ACRs (blue), and B73 ATAC-seq coverage (grey).
Figure 2
Figure 2
Defining shared and nonshared regions between genome assemblies. (A) Schematic representation of B73-based 100 bp bins defined as shared or nonshared in Mo17 and W22 (gray shaded regions) based on chromosomal alignments. The 100 bp bins in W22 or Mo17 could be defined by 100 bp increments within that genome sequence or based on coordinate matches to the B73 genome and these are shown as the W22 (blue) or Mo17 (purple) coordinate bins or the B73-based coordinates (grey). The black hash or the light to dark color change indicates the 100 bp bin boundaries. (B) The proportion of the B73 genome that is defined as shared or nonshared with Mo17, W22, and Oh43 based on chromosome-level sequence alignments. (C) The number of B73 100 bp bins that are unique to B73 (0 shared genotypes), shared with one other genotype assessed (1), shared with two other genotypes assessed (2) or shared across all 4 genotypes including B73, Mo17, Oh43, and W22 (3). Genotype labels correspond to the genotypes which share 100 bp bins with B73.
Figure 3
Figure 3
Presence of ACRs and UMRs within shared and nonshared genomic regions. (A) An IGV (Robinson et al. 2011) representation of a 49 kb segment on chromosome 9 (upper panel) of the B73 genome assembly. Tracks show B73 methylation levels in all contexts (CG-blue, CHG-red, and CHH-yellow), B73 UMRs and ACRs, Mo17 shared sequence (green), W22 shared sequence (blue), Oh43 shared sequence (purple), and B73 gene and TE annotations (grey). The lower panel shows a closer view of a 10 kb region of the bz1 locus to see the detail. (B) The B73 genome was compared to Mo17, Oh43, or W22 to define regions that are shared or nonshared in each contrast. The proportion of the shared or nonshared space that is classified as UMR or ACR was determined for each of the pairwise contrasts.
Figure 4
Figure 4
Stability of UMRs in shared sequence. (A) A flowchart on how B73 UMRs are classified is shown. The numbers in parenthesis indicate the average number of regions classified in that group based on comparisons to the other genotypes. The proportion of B73 UMRs that are shared or nonshared (purple) based on sequence with the respective genome assembly. Shared regions are further classified as B73-only (green) for UMRs that lack data in the other genotype, identical (yellow) for UMRs that maintain an unmethylated state in the same region, partially overlapping (pink) for UMRs that maintain an unmethylated state but have different UMR boundaries across genotypes or polymorphic (blue) for UMRs that change to a methylated state in the other genome. The colors in A are identical to those in C. (B) A genome browser view of the several regions in the B73 genome to illustrate examples of identical, partially overlapping and polymorphic UMRs. A track of DNA methylation in all contexts (CG-blue, CHG-red, CHH-yellow) is shown for B73 and Mo17 (both aligned to B73v4) with UMRs defined below in black (B73) and blue (Mo17). B73 UMRs are defined as identical (yellow), partial overlap (pink), or polymorphic (blue). (C) The proportion of B73 UMRs that are classified in each group defined in A are shown for both aUMRs and iUMRs based on comparison to each of the other three genotypes. (D) The proportion of B73 aUMRs or iUMRs that are classified as ACR only (not unmethylated) in the other genotype (purple), aUMR in the other genotype (blue), iUMR in the other genotype (yellow), or methylated and inaccessible in the other genotype (burgundy) are shown for comparisons to each of the other genotypes
Figure 5
Figure 5
Characteristics of polymorphic UMRs. All B73 UMRs classified as polymorphic (shown in Figure 4A) were assessed based on the type of methylation present in the methylated genotype. The classification is based on which type of methylation state is most common among the 100 bp bins of the UMR. (A) A genome browser view of a region on chromosome 5 of the B73 genome. A track of B73 methylation in all contexts (CG-blue, CHG-red, CHH-yellow) is shown with UMRs defined below in black. Regions with shared sequence with W22 are shown in red and the W22 methylation track (aligned to the B73v4 assembly) with corresponding UMR classification as overlapping (purple) or polymorphic (red). Three separate snapshots are shown with the type of methylation found in W22 for the variable UMR noted below (CG only, CG/CHG, or CHH). (B) The percent of all B73 UMRs classified as polymorphic that change to CG only (light blue), CG/CHG (dark blue), or CHH (green) methylation in the other genotype was calculated. (C) UMRs were defined as containing an ACR in both genotypes (Stable ACR: blue), in one genotype (B73 only ACR: green, NonB73 ACR: orange), or lacking an ACR in both genotypes (No ACR: red). The proportion of each category of B73 UMR (overlapping and polymorphic) that is defined by ACR presence or absence is shown for each genotype. (D) The proportion of UMRs that are found within 200 bp of an annotated gene TSS that are defined as differentially expressed (DE), expressed in both genotypes or not expressed is shown for each genotype. Genes were classified as differentially expressed (log2 fold change > 2 and P-value < 0.05) with the higher expression level observed in B73 (green) or the nonB73 genotype (orange) or as nondifferentially expressed (FPKM > 1, pink) or not expressed (silent: purple).
Figure 6
Figure 6
Many DMTs are due to partially overlapping UMRs. (A) IGV (Robinson et al., 2011) view of DMTs. Tracks show B73 gene and TE annotations, B73 and Mo17 single cytosine methylation in all contexts (CG: blue, CHG: red, CHH: yellow), B73 UMRs and classification relative to Mo17 (identical: blue, partial: green, polymorphic: red), and DMTs defined by a low level of B73 CG methylation and high level of Mo17 CG methylation. (B) The proportion of B73 DMTs that are associated with partially overlapping UMRs (green) or polymorphic UMRs (orange) is shown. (C) The proportion of B73 UMRs, genome-wide (control) or in IBS regions, that are shared or nonshared (purple) based on sequence with the respective genome assembly. Shared regions are further classified as missing data (orange) for UMRs that lack data in the other genome, identical (blue) for UMRs that maintain an unmethylated state in the same region, partially overlapping (green) for UMRs that maintain an unmethylated state but have different UMR boundaries across genotypes or polymorphic (red) for UMRs that change to a methylated state in the other genome.

Similar articles

Cited by

References

    1. Anders S, Pyl PT, Huber W.. 2015. HTSeq–a Python framework to work with high-throughput sequencing data. Bioinformatics. 31:166–169. - PMC - PubMed
    1. Anderson SN, Stitzer MC, Brohammer AB, Zhou P, Noshay JM, et al.2019. Transposable Elements Contribute to Dynamic Genome Content in Maize. Plant Journal. 100:1052–1065. - PubMed
    1. Anderson SN, Zynda G, Song J, Han Z, Vaughn M, et al.2018. Subtle perturbations of the maize methylome reveal genes and transposons silenced :by Chromomethylase or RNA-directed DNA Methylation Pathways. G3 (Bethesda). 8:1921–1932. - PMC - PubMed
    1. Baucom RS, Estill JC, Chaparro C, Upshaw N, Jogi A, et al.2009. Exceptional diversity, non-random distribution, and rapid evolution of retroelements in the B73 maize genome. PLoS Genet. 5:e1000732. - PMC - PubMed
    1. Buenrostro JD, Giresi PG, Zaba LC, Chang HY, Greenleaf WJ.. 2013. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat Methods. 10:1213–1218. - PMC - PubMed

Publication types

LinkOut - more resources