Plasticity of DNA methylation in a nerve injury model of pain.

The response of the peripheral nervous system (PNS) to injury may go together with alterations in epigenetics, a conjecture that has not been subjected to a comprehensive, genome-wide test. Using reduced representation bisulfite sequencing, we report widespread remodeling of DNA methylation in the rat dorsal root ganglion (DRG) occurring within 24 h of peripheral nerve ligation, a neuropathy model of allodynia. Significant (P < 10(-4)) cytosine hyper- and hypo-methylation was found at thousands of CpG sites. Remodeling occurred outside of CpG islands. Changes affected genes with known roles in the PNS, yet methylome remodeling also involved genes that were not linked to neuroplasticity by prior evidence. Consistent with emerging models relying on genome-wide methylation and RNA-seq analysis of promoter regions and gene bodies, variation of methylation was not tightly linked with variation of gene expression. Furthermore, approximately 44% of the dynamically changed CpGs were located outside of genes. We compared their positions with the intergenic, tissue-specific differentially methylated CpGs (tDMCs) of an independent experimental set consisting of liver, spleen, L4 control DRG, and muscle. Dynamic changes affected those intergenic CpGs that were different between tissues (P < 10(-15)) and almost never the invariant portion of the methylome (those CpGs that were identical across all tissues). Our findings-obtained in mixed tissue-show that peripheral nerve injury leads to methylome remodeling in the DRG. Future studies may address which of the cell types found in the DRG, such as specific groups of neurons or non-neuronal cells are affected by which aspect of the observed methylome remodeling.

SERE: single-parameter quality control and sample comparison for RNA-Seq.

BACKGROUND: Assessing the reliability of experimental replicates (or global alterations corresponding to different experimental conditions) is a critical step in analyzing RNA-Seq data. Pearson's correlation coefficient r has been widely used in the RNA-Seq field even though its statistical characteristics may be poorly suited to the task. RESULTS: Here we present a single-parameter test procedure for count data, the Simple Error Ratio Estimate (SERE), that can determine whether two RNA-Seq libraries are faithful replicates or globally different. Benchmarking shows that the interpretation of SERE is unambiguous regardless of the total read count or the range of expression differences among bins (exons or genes), a score of 1 indicating faithful replication (i.e., samples are affected only by Poisson variation of individual counts), a score of 0 indicating data duplication, and scores >1 corresponding to true global differences between RNA-Seq libraries. On the contrary the interpretation of Pearson's r is generally ambiguous and highly dependent on sequencing depth and the range of expression levels inherent to the sample (difference between lowest and highest bin count). Cohen's simple Kappa results are also ambiguous and are highly dependent on the choice of bins. For quantifying global sample differences SERE performs similarly to a measure based on the negative binomial distribution yet is simpler to compute. CONCLUSIONS: SERE can therefore serve as a straightforward and reliable statistical procedure for the global assessment of pairs or large groups of RNA-Seq datasets by a single statistical parameter.