Lineage relationship of CD8^＋ T cell subsets is revealed by progressive changes in the epigenetic landscape

To better elucidate epigenetic mechanisms that correlate with the dynamic gene expression program observed upon T-cell differentiation, we investigated the genomic landscape of histone modifications in naive and memory CD8＋ T cells. Using a ChlP-Seq approach coupled with global gene expression profiling, we generated genome-wide histone H3 lysine 4 （H3K4me3） and H3 lysine 27 （H3K27me3） trimethylation maps in naive, T memory stem cells, central memory cells, and effector memory cells in order to gain insight into how histone architecture is remodeled during T cell differentiation. We show that H3K4me3 histone modifications are associated with activation of genes, while H3K27me3 is negatively correlated with gene expression at canonical loci and enhancers associated with T-cell metabolism, effector function, and memory. Our results also reveal histone modifications and gene expression signatures that distinguish the recently identified T memory stem cells from other CD8＋ T-cell subsets. Taken together, our results suggest that CD8＋ lymphocytes undergo chromatin remodeling in a progressive fashion. These findings have major implications for our understanding of peripheral T-cell ontogeny and the formation of immunological memory.

RECOGNICER:A coarse-graining approach for identifying broad domains from ChIP-seq data

Background:Histone modifications are major factors that define chromatin states and have functions in regulating gene expression in eukaryotic cells.Chromatin immunoprecipitation coupled with high-throughput sequencing(ChIP-seq)technique has been widely used for profiling the genome-wide distribution of chromatin-associating protein factors.Some histone modifications,such as H3K27me3 and H3K9me3,usually mark broad domains in the genome ranging from kilobases(kb)to megabases(Mb)long,resulting in diffuse patterns in the ChIP-seq data that are challenging for signal separation.While most existing ChIP-seq peak-calling algorithms are based on local statistical models without account of multi-scale features,a principled method to identify scale-free board domains has been lacking.Methods:Here we present RECOGNICER(Recursive coarse-graining identification for ChIP-seq enriched regions),a computational method for identifying ChIP-seq enriched domains on a large range of scales.The algorithm is based on a coarse-graining approach,which uses recursive block transformations to determine spatial clustering of local enriched elements across multiple length scales.Results:We apply RECOGNICER to call H3K27me3 domains from ChIP-seq data,and validate the results based on H3K27me3's association with repressive gene expression.We show that RECOGNICER outperforms existing ChIP-seq broad domain calling tools in identifying more whole domains than separated pieces.Conclusion:RECOGNICER can be a useful bioinformatics tool for next-generation sequencing data analysis in epigenomics research.