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DNA methylation and gene expression in Mimulus guttatus

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 generat...

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Detalles Bibliográficos
Autores principales: Colicchio, Jack M., Miura, Fumihito, Kelly, John K., Ito, Takashi, Hileman, Lena C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4492170/
https://www.ncbi.nlm.nih.gov/pubmed/26148779
http://dx.doi.org/10.1186/s12864-015-1668-0
Descripción
Sumario: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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-1668-0) contains supplementary material, which is available to authorized users.