MicroRNA (miRNA) biogenesis is known to be modulated by a variety of RNA-binding proteins (RBPs), but in most cases, individual RBPs appear to influence the processing of a small subset of target miRNAs. Here, we report that the RNA-binding NONO-PSF heterodimer binds a large number of expressed pri-miRNAs in HeLa cells to globally enhance pri-miRNA processing by the Drosha-DGCR8 Microprocessor. NONO and PSF are key components of paraspeckles organized by the long noncoding RNA (lncRNA) NEAT1. We further demonstrate that NEAT1 also has a profound effect on global pri-miRNA processing. Mechanistic dissection reveals that NEAT1 broadly interacts with the NONO-PSF heterodimer as well as many other RBPs and that multiple RNA segments in NEAT1, including a 'pseudo pri-miRNA' near its 3' end, help attract the Microprocessor. These findings suggest a 'bird nest' model in which an lncRNA orchestrates efficient processing of potentially an entire class of small noncoding RNAs in the nucleus.

Snow and frozen soil are important factors that influence terrestrial water and energy balances through snowpack accumulation and melt and soil freeze-thaw. In this study, a new land surface model (LSM) with coupled snow and frozen soil physics was developed based on a hydrologically improved LSM (HydroSiB2). First, an energy-balance-based three-layer snow model was incorporated into HydroSiB2 (hereafter HydroSiB2-S) to provide an improved description of the internal processes of the snow pack. Second, a universal and simplified soil model was coupled with HydroSiB2-S to depict soil water freezing and thawing (hereafter HydroSiB2-SF). In order to avoid the instability caused by the uncertainty in estimating water phase changes, enthalpy was adopted as a prognostic variable instead of snow/soil temperature in the energy balance equation of the snow/frozen soil module. The newly developed models were then carefully evaluated at two typical sites of the Tibetan Plateau (TP) (one snow covered and the other snow free, both with underlying frozen soil). At the snow-covered site in northeastern TP (DY), HydroSiB2-SF demonstrated significant improvements over HydroSiB2-F (same as HydroSiB2-SF but using the original single-layer snow module of HydroSiB2), showing the importance of snow internal processes in three-layer snow parameterization. At the snow-free site in southwestern TP (Ngari), HydroSiB2-SF reasonably simulated soil water phase changes while HydroSiB2-S did not, indicating the crucial role of frozen soil parameterization in depicting the soil thermal and water dynamics. Finally, HydroSiB2-SF proved to be capable of simulating upward moisture fluxes toward the freezing front from the underlying soil layers in winter.