Title: "Differential DNA Methylation Detection in Plants: The Importance of Sequence Context"
Speaker Gayla R. Olbricht; Department of Mathematics and Statistics, Missouri University of Science and Technology, Rolla, MO

Place: LILLY Hall G126
Date: October 27, 2015; Tuesday
Time: 4:30pm

DNA methylation is an epigenetic modification that plays an important role in many biological processes. In mammals, DNA methylation primarily occurs when a methyl chemical group attaches to cytosine bases at CG sites, when a cytosine is followed by a guanine in the DNA sequence. In plants, DNA methylation can also occur when a cytosine and a guanine are separated by any of the other three bases (CHG sites) and also when neither of the two bases following a cytosine are guanine (CHH sites). Many statistical methods have been developed to estimate methylation levels and test differential methylation for whole genome bisulfite sequencing studies. However, most of these methods have been applied to human studies, where only CG sites are investigated. Many of these methods incorporate the observed correlation between methylation levels of neighboring cytosine sites. However, the possibility of methylation at any cytosine in plants and the differences in correlation of methylation levels between sequence contexts complicates the correlation structure. In this work, we investigate the importance of accounting for the sequence context in the correlation structure by comparing the performance of three existing statistical methods and explore the benefits considering the context to improve estimation of DNA methylation in plants.

Associated reading:
Tom Mayo, Gabriele Schweikert and Guido Sanguinetti. 2015. M3D: a kernel-based test for spatially correlated changes in methylation profiles. Bioinformatics. 31(6):809-816.

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