Inheritance patterns and stability of DNA methylation variation in maize near-isogenic lines

玉米近等基因系DNA甲基化变异的遗传模式和稳定性

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Abstract

DNA methylation is a chromatin modification that contributes to epigenetic regulation of gene expression. The inheritance patterns and trans-generational stability of 962 differentially methylated regions (DMRs) were assessed in a panel of 71 near-isogenic lines (NILs) derived from maize (Zea mays) inbred lines B73 and Mo17. The majority of DMRs exhibit inheritance patterns that would be expected for local (cis) inheritance of DNA methylation variation such that DNA methylation level was coupled to local genotype. There are few examples of DNA methylation that exhibit trans-acting control or paramutation-like patterns. The cis-inherited DMRs provide an opportunity to study the stability of inheritance for DNA methylation variation. There was very little evidence for alterations of DNA methylation levels at these DMRs during the generations of the NIL population development. DNA methylation level was associated with local genotypes in nearly all of the >30,000 potential cases of inheritance. The majority of the DMRs were not associated with small RNAs. Together, our results suggest that a significant portion of DNA methylation variation in maize exhibits locally (cis) inherited patterns, is highly stable, and does not require active programming by small RNAs for maintenance. DNA methylation may contribute to heritable epigenetic information in many eukaryotic genomes. In this study, we have documented the inheritance patterns and trans-generational stability for nearly 1000 DNA methylation variants in a segregating maize population. At most loci studied, the DNA methylation differences are locally inherited and are not influenced by the other allele or other genomic regions. The inheritance of DNA methylation levels across generations is quite robust with almost no examples of unstable inheritance, suggesting that DNA methylation differences can be quite stably inherited, even in segregating populations.

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