Biology subjects

Sanbonmatsu, K. Y.

Publications and source records attributed to Sanbonmatsu, K. Y..

3 recordsLinked to original sources

bioRxiv2023

Vaccinia virus infection induces concurrent alterations in host chromatin architecture, accessibility, and gene expression

Genomic DNA folds into complex configurations that produce particular local and global structures thought to profoundly impact genome function. To understand the dynamic nature of this relationship, we investigated the extent of host chromatin structural and functional changes in response to a viral agent. We performed comprehensive assessments of host architecture (Hi-C), accessibility (ATAC-seq), and gene expression (RNA-seq) in a paired manner in response to attenuated vaccinia (smallpox) virus. Over time, infection significantly increased long-range intra-chromosomal interactions and decreased chromatin accessibility. Fine-scale accessibility changes were independent of broad-scale chromatin compartment exchange, which increased (up to 12% of the genome) over time, underscoring potential independent mechanisms for global and local chromatin reorganization. The majority of differentially expressed genes, including those downregulated in immune responses, had concurrent alterations in local accessibility and loop domain restructuring. Increased B compartmentalization, intra-chromosomal interactions, and decreased inter-chromosomal interactions and chromatin accessibility together indicate that infection converts the host genome into a more condensed state with nearly equal bidirectional differential gene expression. These changes in host chromatin features may have implications for developing efficacious anti-viral countermeasures. Overall, our empirical data provides evidence of orchestrated concurrent alterations in chromatin architecture, accessibility, and gene expression in response to infection, further reinforcing the notion of coordinated structure-function dynamics of the genome.

genomics↗

bioRxiv2023

Activation of automethylated PRC2 by dimerization on chromatin

Polycomb Repressive Complex 2 (PRC2) is an epigenetic regulator that trimethylates lysine 27 of histone 3 (H3K27me3) and is essential for embryonic development and cellular differentiation. H3K27me3 is associated with transcriptionally repressed chromatin and is established when PRC2 is allosterically activated upon methyl-lysine binding by the regulatory subunit EED. Automethylation of the catalytic subunit EZH2 stimulates its activity by an unknown mechanism. Here, we show that PRC2 forms a dimer on chromatin in which an inactive, automethylated PRC2 protomer is the allosteric activator of a second PRC2 that is poised to methylate H3 of a substrate nucleosome. Functional assays support our model of allosteric trans-autoactivation via EED, suggesting a novel mechanism mediating context- dependent activation of PRC2. Our work showcases the molecular mechanism of auto- modification coupled dimerization in the regulation of chromatin modifying complexes.

biochemistry↗

bioRxiv2023

Improved Quality Metrics for Association and Reproducibility in Chromatin Accessibility Data Using Mutual Information

BackgroundCorrelation metrics are widely utilized in genomics analysis and often implemented with little regard to assumptions of normality, homoscedasticity, and independence of values. This is especially true when comparing values between replicated sequencing experiments that probe chromatin accessibility, such as assays for transposase-accessible chromatin via sequencing (ATAC-seq). Such data can possess several regions across the human genome with little to no sequencing depth and are thus non-normal with a large portion of zero values. Despite distributed use in the epigenomics field, few studies have evaluated and benchmarked how correlation and association statistics behave across ATAC-seq experiments with known differences or the effects of removing specific outliers from the data. Here, we developed a computational simulation of ATAC-seq data to elucidate the behavior of correlation statistics and to compare their accuracy under set conditions of reproducibility. ResultsUsing these simulations, we monitored the behavior of several correlation statistics, including the Pearsons R and Spearmans{rho} coefficients as well as Kendalls{tau} and Top-Down correlation. We also test the behavior of association measures, including the coefficient of determination R2, Kendalls W, and normalized mutual information. Our experiments reveal an insensitivity of most statistics, including Spearmans{rho} , Kendalls{tau} , and Kendalls W, to increasing differences between simulated ATAC-seq replicates. The removal of co-zeros (regions lacking mapped sequenced reads) between simulated experiments greatly improves the estimates of correlation and association. After removing co-zeros, the R2 coefficient and normalized mutual information display the best performance, having a closer one-to-one relationship with the known portion of shared, enhanced loci between simulated replicates. When comparing values between experimental ATAC-seq data using a random forest model, mutual information best predicts ATAC-seq replicate relationships. ConclusionsCollectively, this study demonstrates how measures of correlation and association can behave in epigenomics experiments. We provide improved strategies for quantifying relationships in these increasingly prevalent and important chromatin accessibility assays.

bioinformatics↗