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DNA methylation and gene expression in Mimulus guttatus.

Colicchio JM, Miura F, Kelly JK, Ito T, Hileman LC - BMC Genomics (2015)

Bottom Line: Additionally, we find that DNA methylation is significantly depleted near gene transcriptional start sites, which may explain the recently discovered elevated rate of recombination in these same regions.Using a model-based approach, we demonstrate that methylation patterns are an important predictor of variation in gene expression.This model provides a novel approach for differential methylation analysis that generates distinct and testable hypotheses regarding gene expression.

View Article: PubMed Central - PubMed

Affiliation: Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, KS, 66045, USA. Colicchio@ku.edu.

ABSTRACT

Background: The presence of methyl groups on cytosine nucleotides across an organism's genome (methylation) is a major regulator of genome stability, crossing over, and gene regulation. The capacity for DNA methylation to be altered by environmental conditions, and potentially passed between generations, makes it a prime candidate for transgenerational epigenetic inheritance. Here we conduct the first analysis of the Mimulus guttatus methylome, with a focus on the relationship between DNA methylation and gene expression.

Results: We present a whole genome methylome for the inbred line Iron Mountain 62 (IM62). DNA methylation varies across chromosomes, genomic regions, and genes. We develop a model that predicts gene expression based on DNA methylation (R(2) = 0.2). Post hoc analysis of this model confirms prior relationships, and identifies novel relationships between methylation and gene expression. Additionally, we find that DNA methylation is significantly depleted near gene transcriptional start sites, which may explain the recently discovered elevated rate of recombination in these same regions.

Conclusions: The establishment here of a reference methylome will be a useful resource for the continued advancement of M. guttatus as a model system. Using a model-based approach, we demonstrate that methylation patterns are an important predictor of variation in gene expression. This model provides a novel approach for differential methylation analysis that generates distinct and testable hypotheses regarding gene expression.

No MeSH data available.


Interspecific comparison of plant DNA methylation levels. A comparison of global DNA methylation levels in CG (red), CHG (green), and CHH (blue) sequence contexts found in Mimulus guttatus compared with those of Arabidopsis thaliana [66], Glycine max [52], Brachypodium distachyiom [27], Oryza sativa [20], Solanum lycopersicum [22], and Zea mays [26]
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Fig1: Interspecific comparison of plant DNA methylation levels. A comparison of global DNA methylation levels in CG (red), CHG (green), and CHH (blue) sequence contexts found in Mimulus guttatus compared with those of Arabidopsis thaliana [66], Glycine max [52], Brachypodium distachyiom [27], Oryza sativa [20], Solanum lycopersicum [22], and Zea mays [26]

Mentions: Of the 186 million reads generated, 126 million were mapped to the genome (67.7 % mapping, mean read depth = 19, median = 6). This proportion is typical for Mimulus genomic studies eg. [51] given the substantial proportion of the physical genome that is not contained in the v2 reference genome. Mapping to unmethylated lambda DNA confirmed that our PBAT treatment achieved 99.4 % conversion of unmethylated cytosines to thymine. Methylation is most common in a CG context (72 %), intermediate in a CHG context (36.5 %), and lowest in a CHH context (6.1 %) (Fig. 1), with 23 % of total cytosine’s being methylated. The percent of genome methylation found in M. guttatus is higher in all contexts than Oryza sativa [20], Arabiopsis thaliana [8], Brachypodium distachyiom [27], lower in all contexts than Solanum lycopersicum [22], and both higher or lower than Zea mays [26] and Glycine max [52] depending on context (Fig. 1). While CHH methylation levels are higher in M. guttatus than Z. mays and G. max, the opposite is true for CHG methylation. CG methylation is highest in Z. Mays, moderate in M. guttatus, and lowest in G. max (Fig. 1).Fig. 1


DNA methylation and gene expression in Mimulus guttatus.

Colicchio JM, Miura F, Kelly JK, Ito T, Hileman LC - BMC Genomics (2015)

Interspecific comparison of plant DNA methylation levels. A comparison of global DNA methylation levels in CG (red), CHG (green), and CHH (blue) sequence contexts found in Mimulus guttatus compared with those of Arabidopsis thaliana [66], Glycine max [52], Brachypodium distachyiom [27], Oryza sativa [20], Solanum lycopersicum [22], and Zea mays [26]
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4492170&req=5

Fig1: Interspecific comparison of plant DNA methylation levels. A comparison of global DNA methylation levels in CG (red), CHG (green), and CHH (blue) sequence contexts found in Mimulus guttatus compared with those of Arabidopsis thaliana [66], Glycine max [52], Brachypodium distachyiom [27], Oryza sativa [20], Solanum lycopersicum [22], and Zea mays [26]
Mentions: Of the 186 million reads generated, 126 million were mapped to the genome (67.7 % mapping, mean read depth = 19, median = 6). This proportion is typical for Mimulus genomic studies eg. [51] given the substantial proportion of the physical genome that is not contained in the v2 reference genome. Mapping to unmethylated lambda DNA confirmed that our PBAT treatment achieved 99.4 % conversion of unmethylated cytosines to thymine. Methylation is most common in a CG context (72 %), intermediate in a CHG context (36.5 %), and lowest in a CHH context (6.1 %) (Fig. 1), with 23 % of total cytosine’s being methylated. The percent of genome methylation found in M. guttatus is higher in all contexts than Oryza sativa [20], Arabiopsis thaliana [8], Brachypodium distachyiom [27], lower in all contexts than Solanum lycopersicum [22], and both higher or lower than Zea mays [26] and Glycine max [52] depending on context (Fig. 1). While CHH methylation levels are higher in M. guttatus than Z. mays and G. max, the opposite is true for CHG methylation. CG methylation is highest in Z. Mays, moderate in M. guttatus, and lowest in G. max (Fig. 1).Fig. 1

Bottom Line: Additionally, we find that DNA methylation is significantly depleted near gene transcriptional start sites, which may explain the recently discovered elevated rate of recombination in these same regions.Using a model-based approach, we demonstrate that methylation patterns are an important predictor of variation in gene expression.This model provides a novel approach for differential methylation analysis that generates distinct and testable hypotheses regarding gene expression.

View Article: PubMed Central - PubMed

Affiliation: Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, KS, 66045, USA. Colicchio@ku.edu.

ABSTRACT

Background: The presence of methyl groups on cytosine nucleotides across an organism's genome (methylation) is a major regulator of genome stability, crossing over, and gene regulation. The capacity for DNA methylation to be altered by environmental conditions, and potentially passed between generations, makes it a prime candidate for transgenerational epigenetic inheritance. Here we conduct the first analysis of the Mimulus guttatus methylome, with a focus on the relationship between DNA methylation and gene expression.

Results: We present a whole genome methylome for the inbred line Iron Mountain 62 (IM62). DNA methylation varies across chromosomes, genomic regions, and genes. We develop a model that predicts gene expression based on DNA methylation (R(2) = 0.2). Post hoc analysis of this model confirms prior relationships, and identifies novel relationships between methylation and gene expression. Additionally, we find that DNA methylation is significantly depleted near gene transcriptional start sites, which may explain the recently discovered elevated rate of recombination in these same regions.

Conclusions: The establishment here of a reference methylome will be a useful resource for the continued advancement of M. guttatus as a model system. Using a model-based approach, we demonstrate that methylation patterns are an important predictor of variation in gene expression. This model provides a novel approach for differential methylation analysis that generates distinct and testable hypotheses regarding gene expression.

No MeSH data available.