Phillip Rosenbaum

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.

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.

La méthylation de l'ADN et les modifications post-traductionnelles des histones sont des éléments de régulation nécessaires pour le développement normal et la bonne fonction des cellules. On sait que les modifications d'histones déterminent partiellement la localisation des ADN méthyltransférases (DNMT). Par exemple, le domaine PWWP des DNMTs de novo (DNMT3A, DNMT3B) interagit normalement avec la méthylation de la lysine 36 de l'histone H3 (H3K36) pour guider la localisation des DNMTs. Les îlots CpG (CGI) sont généralement pauvres en H3K36me2/3 et enrichis de marques répressives associées aux complexes répressifs PRC1 (H2AK119ub) et PRC2 (H3K27me3). Malgré l'antagonisme entre H3K27me3 et H3K36me2/3, nous avons observé au cours du développement, de la différenciation et de la progression du cancer que certaines régions du génome enrichies en H3K27me3 acquièrent la méthylation de novo. Ceci suggère que les DNMTs de novo pourraient être recrutés par un mécanisme autre que l'interaction entre le domaine PWWP et la méthylation H3K36. Des mutations dans le domaine PWWP de DNMT3A ont été liées au paragangliome et au nanisme microcéphalique, et il a été démontré que ces mutants PWWP se localisent dans les régions régulées par Polycomb, ce qui entraîne une hyperméthylation de ces régions. Nous avons étudié la possibilité que les marques déposées par PRC recrutent le mutant DNMT3A, et avons constaté que ces mutants s'enrichissent dans les régions contenant H2AK119ub, mais sont indifférents aux niveaux de H3K27me3 catalysé par PRC2. Sur la base de la protéomique in vitro, nous observons également des preuves d'une interaction directe entre DNMT3A et H2AK119ub. Surtout, nous notons également que les régions enrichies en H2AK119ub qui attirent le DNMT3A muté PWWP gagnent la méthylation de l'ADN. Parmi ces régions hyperméthylées, on trouve un sous-ensemble de CGI marqués avec H2AK119ub. L'enrichissement du mutant PWWP DNMT3A dans ces CGI est associé à l'hyperméthylation de l'ADN, ce qui implique que la dérégulation des mécanismes distincts de recrutement du DNMT3A peut contribuer à la méthylation aberrante de CGI dans le cancer et d'autres maladies