Integrating Genome-Wide Methylome and Gen Expression Data in Plant Genomes

Integrating genome-wide methylome and gen expression data in plant genomes

Mon-Ray Shao, Vikas Shedge, Robersy Sanchez, Xiaodong Yang, Sally Mackenzie

Beadle Center for Genetics Research, University of Nebraska, Lincoln, NE 68588

Genome-wide methylome analysis in plants conducted by bisulfite sequencing produces a highly heterogenous dataset that is difficult to associate with gene expression changes. Part of the data heterogeneity is dynamic DNA methylation behavior that serves to stabilize DNA, but which confounds analysis of methylation signal deriving from experimental treatment. We have conducted genome-wide bisulfite sequencing together with RNAseq in Arabidopsis and tomato lines that have undergone epigenetic reprogramming by suppression of the gene MSH1. We have developed a strategy for data analysis that permits more robust discrimination of signal to noise in methylome data, and integrated these data with transcriptome analysis to identify genes that display altered gene expression in association with intragenic DNA methylation changes. These analyses were also invaluable in detection of methylation changes that were aberrant in pattern, revealing them to be the consequence of germplasm contamination. We will present the various methodologies we have employed for mining these large datasets.