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Tuesday June 07, 11:00 AM - 3:00 PM

Variation in epigenetic state correlates with gene expression across nine inbred strains of mice


Authors:
Anna Tyler; Catrina Spruce; Robyn Ball; Wendy Pitman; Vivek Philip; J. Matthew Mahoney; Mary Ann Handel; Gary Churchill; Jennifer Trowbridge; Michael Stitzel; Kenneth Paigen; Petko Petkov; Gregory Carter

Affiliation: The Jackson Laboratory

Keywords:
Other (epigenetics)

It is well established that epigenetic features, such as histone modifications and DNA methylation, are associated gene expression across cell types. However, it is not well known how variation in genotype affects epigenetic state, or to what extent such variation contributes to variation in gene expression across genetically distinct individuals. Here we investigated the relationship between heritable epigenetic variation and gene expression in hepatocytes across nine inbred mouse strains. Eight of the inbred strains were founders of the diversity outbred (DO) mice, and the ninth was DBA/2J, which, along with C57Bl6/J, is one of the founders of the BxD recombinant inbred panel of mice. We surveyed four histone modifications, H3K4me1, H3K4me3, H3K27me3 and H3K27ac, as well as DNA methylation. We used ChromHMM to identify 14 chromatin states representing distinct combinations of the four measured histone modifications. We found that variation in chromatin state mirrored genetic variation across the inbred strains. Furthermore, epigenetic variation was correlated with gene expression across strains. The correspondence between epigenetic state and gene expression was replicated in an independent population of DO mice in which we imputed local epigenetic state. In contrast, we found that DNA methylation did not vary across inbred strains and was not correlated with variation in expression in DO mice. This work suggests that chromatin state is highly influenced by local genotype and may be a primary mode through which expression quantitative trait loci (eQTLs) are mediated. We further demonstrate that the mid-range resolution of chromatin states, between that of SNPs and haplotypes paired with gene expression, is useful for annotation of functional regions of the mouse genome. Finally, we provide, to our knowledge, the first data resource to document variation in chromatin state across genetically distinct individuals.