H3K36 dimethylation shapes the epigenetic interaction landscape by directing repressive chromatin modifications in embryonic stem cells.

Epigenetic modifications on the chromatin do not occur in isolation. Chromatin-associated proteins and their modification products form a highly interconnected network, and disturbing one component may rearrange the entire system. We see this increasingly clearly in epigenetically dysregulated cancers. It is important to understand the rules governing epigenetic interactions. Here, we use the mouse embryonic stem cell (mESC) model to describe in detail the relationships within the H3K27-H3K36-DNA methylation subnetwork. In particular, we focus on the major epigenetic reorganization caused by deletion of the histone 3 lysine 36 methyltransferase NSD1, which in mESCs deposits nearly all of the intergenic H3K36me2. Although disturbing the H3K27 and DNA methylation (DNAme) components also affects this network to a certain extent, the removal of H3K36me2 has the most drastic effect on the epigenetic landscape, resulting in full intergenic spread of H3K27me3 and a substantial decrease in DNAme. By profiling DNMT3A and CHH methylation (mCHH), we show that H3K36me2 loss upon Nsd1-KO leads to a massive redistribution of DNMT3A and mCHH away from intergenic regions and toward active gene bodies, suggesting that DNAme reduction is at least in part caused by redistribution of de novo methylation. Additionally, we show that pervasive acetylation of H3K27 is regulated by the interplay of H3K36 and H3K27 methylation. Our analysis highlights the importance of H3K36me2 as a major determinant of the developmental epigenome and provides a framework for further consolidating our knowledge of epigenetic networks.

Two competing mechanisms of DNMT3A recruitment regulate the dynamics of de novo DNA methylation at PRC1-targeted CpG islands.

Precise deposition of CpG methylation is critical for mammalian development and tissue homeostasis and is often dysregulated in human diseases. The localization of de novo DNA methyltransferase DNMT3A is facilitated by its PWWP domain recognizing histone H3 lysine 36 (H3K36) methylation1,2 and is normally depleted at CpG islands (CGIs)3. However, methylation of CGIs regulated by Polycomb repressive complexes (PRCs) has also been observed4-8. Here, we report that DNMT3A PWWP domain mutations identified in paragangliomas9 and microcephalic dwarfism10 promote aberrant localization of DNMT3A to CGIs in a PRC1-dependent manner. DNMT3A PWWP mutants accumulate at regions containing PRC1-mediated formation of monoubiquitylated histone H2A lysine 119 (H2AK119ub), irrespective of the amounts of PRC2-catalyzed formation of trimethylated histone H3 lysine 27 (H3K27me3). DNMT3A interacts with H2AK119ub-modified nucleosomes through a putative amino-terminal ubiquitin-dependent recruitment region, providing an alternative form of DNMT3A genomic targeting that is augmented by the loss of PWWP reader function. Ablation of PRC1 abrogates localization of DNMT3A PWWP mutants to CGIs and prevents aberrant DNA hypermethylation. Our study implies that a balance between DNMT3A recruitment by distinct reader domains guides de novo CpG methylation and may underlie the abnormal DNA methylation landscapes observed in select human cancer subtypes and developmental disorders.

Closing the Yield Gap for Cannabis: A Meta-Analysis of Factors Determining Cannabis Yield.

Until recently, the commercial production of Cannabis sativa was restricted to varieties that yielded high-quality fiber while producing low levels of the psychoactive cannabinoid tetrahydrocannabinol (THC). In the last few years, a number of jurisdictions have legalized the production of medical and/or recreational cannabis with higher levels of THC, and other jurisdictions seem poised to follow suit. Consequently, demand for industrial-scale production of high yield cannabis with consistent cannabinoid profiles is expected to increase. In this paper we highlight that currently, projected annual production of cannabis is based largely on facility size, not yield per square meter. This meta-analysis of cannabis yields reported in scientific literature aimed to identify the main factors contributing to cannabis yield per plant, per square meter, and per W of lighting electricity. In line with previous research we found that variety, plant density, light intensity and fertilization influence cannabis yield and cannabinoid content; we also identified pot size, light type and duration of the flowering period as predictors of yield and THC accumulation. We provide insight into the critical role of light intensity, quality, and photoperiod in determining cannabis yields, with particular focus on the potential for light-emitting diodes (LEDs) to improve growth and reduce energy requirements. We propose that the vast amount of genomics data currently available for cannabis can be used to better understand the effect of genotype on yield. Finally, we describe diversification that is likely to emerge in cannabis growing systems and examine the potential role of plant-growth promoting rhizobacteria (PGPR) for growth promotion, regulation of cannabinoid biosynthesis, and biocontrol.