Nitrogen (N) is a macronutrient that boosts carbon (C) metabolism and plant growth leading to biomass accumulation. The molecular connection between nitrogen utilization efficiency (NUE) and biomass production remains unclear. Here, via quantitative trait loci analysis and map-based cloning, we reveal that natural variation at the MYB61 locus leads to differences in N use and cellulose biogenesis between indica and japonica subspecies of rice. MYB61, a transcriptional factor that regulates cellulose synthesis, is directly regulated by a known NUE regulator GROWTH-REGULATING FACTOR4 (GRF4), which coordinates cellulosic biomass production and N utilization. The variation at MYB61 has been selected during indica and japonica domestication. The indica allele of MYB61 displays robust transcription resulting in higher NUE and increased grain yield at reduced N supply than that of japonica. Our study hence unravels how C metabolism is linked to N uptake and may provide an opportunity to reduce N use for sustainable agriculture.Chromatin-associated RNA (caRNA) has been proposed as a type of epigenomic modifier. Here, we test whether environmental stress can induce cellular dysfunction through modulating RNA-chromatin interactions. We induce endothelial cell (EC) dysfunction with high glucose and TNFα (H + T), that mimic the common stress in diabetes mellitus. We characterize the H + T-induced changes in gene expression by single cell (sc)RNA-seq, DNA interactions by Hi-C, and RNA-chromatin interactions by iMARGI. H + T induce inter-chromosomal RNA-chromatin interactions, particularly among the super enhancers. To test the causal relationship between H + T-induced RNA-chromatin interactions and the expression of EC dysfunction-related genes, we suppress the LINC00607 RNA. This suppression attenuates the expression of SERPINE1, a critical pro-inflammatory and pro-fibrotic gene. Furthermore, the changes of the co-expression gene network between diabetic and healthy donor-derived ECs corroborate the H + T-induced RNA-chromatin interactions. Taken together, caRNA-mediated dysregulation of gene expression modulates EC dysfunction, a crucial mechanism underlying numerous diseases.Legumes utilize a shoot-mediated signaling system to maintain a mutualistic relationship with nitrogen-fixing bacteria in root nodules. In Lotus japonicus, shoot-to-root transfer of microRNA miR2111 that targets TOO MUCH LOVE, a nodulation suppressor in roots, has been proposed to explain the mechanism underlying nodulation control from shoots. see more However, the role of shoot-accumulating miR2111s for the systemic regulation of nodulation was not clearly shown. Here, we find L. japonicus has seven miR2111 loci, including those mapped through RNA-seq. MIR2111-5 expression in leaves is the highest among miR2111 loci and repressed after rhizobial infection depending on a shoot-acting HYPERNODULATION ABERRANT ROOT FORMATION1 (HAR1) receptor. MIR2111-5 knockout mutants show significantly decreased nodule numbers and miR2111 levels. Furthermore, grafting experiments using transformants demonstrate scions with altered miR2111 levels influence nodule numbers in rootstocks in a dose-dependent manner. Therefore, miR2111 accumulation in leaves through MIR2111-5 expression is required for HAR1-dependent systemic optimization of nodule number.Cryo-electron microscopy (cryoEM) is becoming the preferred method for resolving protein structures. Low signal-to-noise ratio (SNR) in cryoEM images reduces the confidence and throughput of structure determination during several steps of data processing, resulting in impediments such as missing particle orientations. Denoising cryoEM images can not only improve downstream analysis but also accelerate the time-consuming data collection process by allowing lower electron dose micrographs to be used for analysis. Here, we present Topaz-Denoise, a deep learning method for reliably and rapidly increasing the SNR of cryoEM images and cryoET tomograms. By training on a dataset composed of thousands of micrographs collected across a wide range of imaging conditions, we are able to learn models capturing the complexity of the cryoEM image formation process. The general model we present is able to denoise new datasets without additional training. Denoising with this model improves micrograph interpretability and allows us to solve 3D single particle structures of clustered protocadherin, an elongated particle with previously elusive views. We then show that low dose collection, enabled by Topaz-Denoise, improves downstream analysis in addition to reducing data collection time. We also present a general 3D denoising model for cryoET. Topaz-Denoise and pre-trained general models are now included in Topaz. We expect that Topaz-Denoise will be of broad utility to the cryoEM community for improving micrograph and tomogram interpretability and accelerating analysis.During neuronal differentiation, the transcriptional profile and the epigenetic context of neural committed cells is subject to significant rearrangements, but a systematic quantification of global histone modification changes is still missing. Here, we show that H3K79me2 increases and H3K27ac decreases globally during in-vitro neuronal differentiation of murine embryonic stem cells. DOT1L mediates all three degrees of methylation of H3K79 and its enzymatic activity is critical to modulate cellular differentiation and reprogramming. In this context, we find that inhibition of DOT1L in neural progenitor cells biases the transcriptional state towards neuronal differentiation, resulting in transcriptional upregulation of genes marked with H3K27me3 on the promoter region. We further show that DOT1L inhibition affects accessibility of SOX2-bound enhancers and impairs SOX2 binding in neural progenitors. Our work provides evidence that DOT1L activity gates differentiation of progenitors by allowing SOX2-dependent transcription of stemness programs.For over ten years, China has been the largest vehicle market in the world. In order to address energy security and air quality concerns, China issued the Dual Credit policy to improve vehicle efficiency and accelerate New Energy Vehicle adoption. In this paper, a market-penetration model is combined with a vehicle fleet model to assess implications on greenhouse gas (GHG) emissions and energy demand. Here we use this integrated modeling framework to study several scenarios, including hypothetical policy tweaks, oil price, battery cost and charging infrastructure for the Chinese passenger vehicle fleet. The model shows that the total GHGs of the Chinese passenger vehicle fleet are expected to peak in 2032 under the Dual Credit policy. A significant reduction in GHG emissions is possible if more efficient internal combustion engines continue to be part of the technology mix in the short term with more New Energy Vehicle penetration in the long term.