The proper regulation of transcription is essential for maintaining genome integrity and executing other downstream cellular functions^1,2. Here we identify a stable association between the genome-stability regulator sensor of single-stranded DNA (SOSS)³ and the transcription regulator Integrator-PP2A (INTAC)^4–6. Through SSB1-mediated recognition of single-stranded DNA, SOSS–INTAC stimulates promoter-proximal termination of transcription and attenuates R-loops associated with paused RNA polymerase II to prevent R-loop-induced genome instability. SOSS–INTAC-dependent attenuation of R-loops is enhanced by the ability of SSB1 to form liquid-like condensates. Deletion of NABP2 (encoding SSB1) or introduction of cancer-associated mutations into its intrinsically disordered region leads to a pervasive accumulation of R-loops, highlighting a genome surveillance function of SOSS–INTAC that enables timely termination of transcription at promoters to constrain R-loop accumulation and ensure genome stability.

The major enhancer regulator lysine-specific histone demethylase 1A (LSD1) is required for mammalian embryogenesis and is implicated in human congenital diseases and multiple types of cancer; however, the underlying mechanisms remain enigmatic. Here, we dissect the role of LSD1 and its demethylase activity in gene regulation and cell fate transition. Surprisingly, the catalytic inactivation of LSD1 has a mild impact on gene expression and cellular differentiation whereas the loss of LSD1 protein de-represses enhancers globally and impairs cell fate transition. LSD1 deletion increases H3K27ac levels and P300 occupancy at LSD1-targeted enhancers. The gain of H3K27ac catalyzed by P300/CBP, not the loss of CoREST complex components from chromatin, contributes to the transcription de-repression of LSD1 targets and differentiation defects caused by LSD1 loss. Together, our study demonstrates a demethylase-independent role of LSD1 in regulating enhancers and cell fate transition, providing insight into treating diseases driven by LSD1 mutations and misregulation.

Downscaling satellite‐based precipitation to fine scales is crucial for deepening our understanding of global hydrologic cycles and water‐related issues. In this study, a novel approach that integrates precipitation zoning with random forest regression is proposed for the spatial downscaling of satellite‐based precipitation. Precipitation zoning is delineated through iterative rotated empirical orthogonal function (REOF) analyses of ground‐ and satellite‐based precipitation observations. Random forest regression is applied to link the satellite‐based precipitation to 1‐km‐resolution predictors such as latitude (Lat), longitude (Lon), elevation, aspect, slope, and the normalized difference vegetation index (NDVI). The accuracy of the resultant downscaled precipitation is evaluated based on five statistical evaluation indices. The performance of the proposed approach is exemplified in the Lancang–Mekong River basin, taking Tropical Rainfall Measuring Mission (TRMM) 3B43 and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN–CDR) products acquired in 2001 (wet year), 2005 (normal year), and 2009 (dry year) as the databases. The results show that seven precipitation subregions can be roughly distinguished in the study basin. Zoning‐based downscaling outperforms non‐zoning‐based downscaling in terms of accuracy, resulting in statistically significant reductions in root mean square error (RMSE) and mean absolute error (MAE) of 1–17% across the entire basin. Among the selected predictors, the variables Lat and Lon are the most important for precipitation estimation, whereas the remaining variables have lesser and subregion‐dependent importance. The proposed approach is promising for generating high‐spatial‐resolution precipitation data in regions with sparse ground‐based observations and differentiated climatic regimes.

Metazoan nucleosomes harboring H3K79 methylation (H3K79me) deposited by the methyltransferase DOT1L (disruptor of telomeric silencing 1-like) decorate actively transcribed genes. While DOT1L regulates transcription and the pathogenesis of leukemia and neurological disorders, the role of H3K79me remains elusive. Here, we reveal a functional synergism between H3K79me and H3K36 trimethylation (H3K36me3) in regulating gene expression and cellular differentiation. Simultaneous catalytic inactivation of DOT1L and the H3K36 methyltransferase SETD2 (SET domain containing 2) leads to hyperactive transcription and failures in neural differentiation. H3K79me/H3K36me3 loss causes increased transcription elongation, gained chromatin accessibility at a group of enhancers, and increased recruitment of TEAD4 (TEA domain transcription factor 4) and its coactivator YAP1 (Yes-associated protein 1) to these enhancers. Furthermore, YAP-TEAD inhibition restores the expression levels of genes hyperactivated by H3K79me/H3K36me3 loss. Together, we demonstrate a synergism of H3K79me and H3K36me3 in regulating transcription and cell fate transition, unveil the underlying mechanisms, and provide insight into targeting diseases driven by misregulation/mutations of DOT1L and/or SETD2.