The Genomes of Oryza sativa: A History of Duplications

We report improved whole-genome shotgun sequences for the genomes of indica and japonica rice, both with multimegabase contiguity, or almost 1,000-fold improvement over the drafts of 2002. Tested against a nonredundant collection of 19,079 full-length cDNAs, 97.7% of the genes are aligned, without fragmentation, to the mapped super-scaffolds of one or the other genome. We introduce a gene identification procedure for plants that does not rely on similarity to known genes to remove erroneous predictions resulting from transposable elements. Using the available EST data to adjust for residual errors in the predictions, the estimated gene count is at least 38,000–40,000. Only 2%–3% of the genes are unique to any one subspecies, comparable to the amount of sequence that might still be missing. Despite this lack of variation in gene content, there is enormous variation in the intergenic regions. At least a quarter of the two sequences could not be aligned, and where they could be aligned, single nucleotide polymorphism (SNP) rates varied from as little as 3.0 SNP/kb in the coding regions to 27.6 SNP/kb in the transposable elements. A more inclusive new approach for analyzing duplication history is introduced here. It reveals an ancient whole-genome duplication, a recent segmental duplication on Chromosomes 11 and 12, and massive ongoing individual gene duplications. We find 18 distinct pairs of duplicated segments that cover 65.7% of the genome; 17 of these pairs date back to a common time before the divergence of the grasses. More important, ongoing individual gene duplications provide a never-ending source of raw material for gene genesis and are major contributors to the differences between members of the grass family

Hotspots of biogeochemical activity linked to aridity and plant traits across global drylands

14 páginas.- 4 figuras.- 67 referencias.- The online version contains supplementary material available at https://doi.org/10.1038/s41477-024-01670-7Perennial plants create productive and biodiverse hotspots, known as fertile islands, beneath their canopies. These hotspots largely determine the structure and functioning of drylands worldwide. Despite their ubiquity, the factors controlling fertile islands under conditions of contrasting grazing by livestock, the most prevalent land use in drylands, remain virtually unknown. Here we evaluated the relative importance of grazing pressure and herbivore type, climate and plant functional traits on 24 soil physical and chemical attributes that represent proxies of key ecosystem services related to decomposition, soil fertility, and soil and water conservation. To do this, we conducted a standardized global survey of 288 plots at 88 sites in 25 countries worldwide. We show that aridity and plant traits are the major factors associated with the magnitude of plant effects on fertile islands in grazed drylands worldwide. Grazing pressure had little influence on the capacity of plants to support fertile islands. Taller and wider shrubs and grasses supported stronger island effects. Stable and functional soils tended to be linked to species-rich sites with taller plants. Together, our findings dispel the notion that grazing pressure or herbivore type are linked to the formation or intensification of fertile islands in drylands. Rather, our study suggests that changes in aridity, and processes that alter island identity and therefore plant traits, will have marked effects on how perennial plants support and maintain the functioning of drylands in a more arid and grazed world.This research was supported by the European Research Council (ERC grant 647038 (BIODESERT) awarded to F.T.M.) and Generalitat Valenciana (CIDEGENT/2018/041). D.J.E. was supported by the Hermon Slade Foundation (HSF21040). J. Ding was supported by the National Natural Science Foundation of China Project (41991232) and the Fundamental Research Funds for the Central Universities of China. M.D.-B. acknowledges support from TED2021-130908B-C41/AEI/10.13039/501100011033/Unión Europea Next Generation EU/PRTR and the Spanish Ministry of Science and Innovation for the I + D + i project PID2020-115813RA-I00 funded by MCIN/AEI/10.13039/501100011033. O.S. was supported by US National Science Foundation (Grants DEB 1754106, 20-25166), and Y.L.B.-P. by a Marie Sklodowska-Curie Actions Individual Fellowship (MSCA-1018 IF) within the European Program Horizon 2020 (DRYFUN Project 656035). K.G. and N.B. acknowledge support from the German Federal Ministry of Education and Research (BMBF) SPACES projects OPTIMASS (FKZ: 01LL1302A) and ORYCS (FKZ: FKZ01LL1804A). B.B. was supported by the Taylor Family-Asia Foundation Endowed Chair in Ecology and Conservation Biology, and M. Bowker by funding from the School of Forestry, Northern Arizona University. C.B. acknowledges funding from the National Natural Science Foundation of China (41971131). D.B. acknowledges support from the Hungarian Research, Development and Innovation Office (NKFI KKP 144096), and A. Fajardo support from ANID PIA/BASAL FB 210006 and the Millennium Science Initiative Program NCN2021-050. M.F. and H.E. received funding from Ferdowsi University of Mashhad (grant 39843). A.N. and M.K. acknowledge support from FCT (CEECIND/02453/2018/CP1534/CT0001, SFRH/BD/130274/2017, PTDC/ASP-SIL/7743/2020, UIDB/00329/2020), EEA (10/CALL#5), AdaptForGrazing (PRR-C05-i03-I-000035) and LTsER Montado platform (LTER_EU_PT_001) grants. O.V. acknowledges support from the Hungarian Research, Development and Innovation Office (NKFI KKP 144096). L.W. was supported by the US National Science Foundation (EAR 1554894). Y.Z. and X.Z. were supported by the National Natural Science Foundation of China (U2003214). H.S. is supported by a María Zambrano fellowship funded by the Ministry of Universities and European Union-Next Generation plan. The use of any trade, firm or product names does not imply endorsement by any agency, institution or government. Finally, we thank the many people who assisted with field work and the landowners, corporations and national bodies that allowed us access to their land.Peer reviewe

Attribution of Runoff Reduction in the Juma River Basin to Climate Variation, Direct Human Intervention, and Land Use Change

Juma River, located in the Midwest of the Haihe River basin, is an important source of water supply to Beijing and Hebei. Over the past decades, the region has been seriously threatened by water shortages owing to complex climate conditions and intensive human activities. This study investigated the runoff characteristics of the Juma River by employing the Soil and Water Assessment Tool (SWAT) and stochastic methods for the period of 1961⁻2013. Accordingly, the runoff changes attributed to the climate variation and different types of anthropogenic activities (land use change and direct human intervention) were estimated, respectively, in conjunction with the improved quantitative response analysis. The results indicated that the annual runoff of both Zijingguan station and Zhangfang station has decreased significantly at the 0.001 significance level, and reduction rates were −0.054 billion m3 and −0.10 billion m3, respectively. Moreover, the persistency of this trend has been shown for decades (Hurst coefficient > 0.50). The SWAT model was calibrated and validated during the baseline period of 1961⁻1978. Significant rising temperatures and declining precipitation were the main reasons for runoff reduction, especially during the two periods of 1998⁻2002 and 2003⁻2008. Additionally, water withdrawal of Wuyi canal aggravated the runoff reduction and water scarcity conditions in the region. After 2009, the effects of direct human intervention exceeded those of climate change. However, the impact of land use change can be seen as negligible during the study period. Climate change had a greater effect on runoff reduction in winter, while the impact of human activities was more dramatic in summer

Evaluating the Impacts of Climate Change and Vegetation Restoration on the Hydrological Cycle over the Loess Plateau, China

In recent decades, both observation and simulation data have demonstrated an obvious decrease in runoff and soil moisture, with increasing evapotranspiration, over the Loess Plateau. In this study, we employed a Variable Infiltration Capacity model coupled with scenario simulation to explore the impact of change in climate and land cover on four hydrological variables (HVs) over the Loess Plateau, i.e., evapotranspiration (ET), runoff (Runoff), shallow soil moisture (SM1), and deep soil moisture (SM2). Results showed precipitation, rather than temperature, had the closest relationship with the four HVs, with r ranging from 0.76 to 0.97 (p < 0.01), and this was therefore presumed to be the dominant climate-based driving factor in the variation of hydrological regimes. Vegetation conversion, from cropland and grassland to woodland, significantly reduced runoff and increased soil moisture consumption, to sustain an increased ET, and, assuming that the reduction of SM2 is entirely evaporated, we can attribute 71.28% ± 18.64%, 65.89% ± 24.14% of the ET increase to the water loss of SM2 in the two conversion modes, respectively. The variation in HVs, induced by land cover change, were higher than the expected climate change with respect to SM1, while different factors were selected to determine HVs variation in six catchments, due to differences in the mode and intensity of vegetation conversion, and the degree of climate change. Our findings are critical for understanding and quantifying the impact of climate change and vegetation conversions, and provide a further basis for the design of water resources and land-use management strategies with respect to climate change, especially in the water-limited Loess Plateau

Quantitative Assessment for the Dynamics of the Main Ecosystem Services and their Interactions in the Northwestern Arid Area, China

Evaluating changes in the spatial–temporal patterns of ecosystem services (ESs) and their interrelationships provide an opportunity to understand the links among them, as well as to inform ecosystem-service-based decision making and governance. To research the development trajectory of ecosystem services over time and space in the northwestern arid area of China, three main ecosystem services (carbon sequestration, soil retention, and sand fixation) and their relationships were analyzed using Pearson’s coefficient and a time-lagged cross-correlation analysis based on the mountain–oasis–desert zonal scale. The results of this study were as follows: (1) The carbon sequestration of most subregions improved, and that of the oasis continuously increased from 1990 to 2015. Sand fixation decreased in the whole region except for in the Alxa Plateau–Hexi Corridor area, which experienced an “increase–decrease” trend before 2000 and after 2000; (2) the synergies and trade-off relationships of the ES pairs varied with time and space, but carbon sequestration and soil retention in the most arid area had a synergistic relationship, and most oases retained their synergies between carbon sequestration and sand fixation over time. Most regional relationships of sand fixation and soil retention with a weak trade-off during the before-2000 stage turned into weak synergies at the after-2000 stage; (3) the ES pairs of carbon sequestration and sand fixation had significant time-lagged trade-off relationships in most arid areas, and these time trade-offs were generally maintained for 2–6 years, where a higher absolute value of the maximum time-lagged correlation coefficient corresponded to a longer time-lag. This study could assist us in understanding the trade-off and synergy of ESs and will provide quantitative zonal information for the ecosystem-services-based ecomanagement of arid areas

Co-embedding of edges and nodes with deep graph convolutional neural networks

Abstract Graph neural networks (GNNs) have significant advantages in dealing with non-Euclidean data and have been widely used in various fields. However, most of the existing GNN models face two main challenges: (1) Most GNN models built upon the message-passing framework exhibit a shallow structure, which hampers their ability to efficiently transmit information between distant nodes. To address this, we aim to propose a novel message-passing framework, enabling the construction of GNN models with deep architectures akin to convolutional neural networks (CNNs), potentially comprising dozens or even hundreds of layers. (2) Existing models often approach the learning of edge and node features as separate tasks. To overcome this limitation, we aspire to develop a deep graph convolutional neural network learning framework capable of simultaneously acquiring edge embeddings and node embeddings. By utilizing the learned multi-dimensional edge feature matrix, we construct multi-channel filters to more effectively capture accurate node features. To address these challenges, we propose the Co-embedding of Edges and Nodes with Deep Graph Convolutional Neural Networks (CEN-DGCNN). In our approach, we propose a novel message-passing framework that can fully integrate and utilize both node features and multi-dimensional edge features. Based on this framework, we develop a deep graph convolutional neural network model that prevents over-smoothing and obtains node non-local structural features and refined high-order node features by extracting long-distance dependencies between nodes and utilizing multi-dimensional edge features. Moreover, we propose a novel graph convolutional layer that can learn node embeddings and multi-dimensional edge embeddings simultaneously. The layer updates multi-dimensional edge embeddings across layers based on node features and an attention mechanism, which enables efficient utilization and fusion of both node and edge features. Additionally, we propose a multi-dimensional edge feature encoding method based on directed edges, and use the resulting multi-dimensional edge feature matrix to construct a multi-channel filter to filter the node information. Lastly, extensive experiments show that CEN-DGCNN outperforms a large number of graph neural network baseline methods, demonstrating the effectiveness of our proposed method

Detection and Attribution of Runoff Reduction of Weihe River over Different Periods during 1961–2016

An obvious decline in runoff of the Weihe River has been detected during the last half-century. Climate change and human activity acted as two major factors inducing the reduction. However, little knowledge is acquired on how and to what extent the decadal climate change and human activity induced runoff variations, which is essential for regional water resources planning and management. In this study, the observed data of 3 hydrological stations and 31 meteorological stations were used to analyze the runoff variability, and Variable Infiltration Capacity (VIC) model (Xu Liang, Seattle, WA, United States of America) coupled with scenario simulation was employed to attribute runoff variation of each period. The results showed that runoff decreased significantly at a rate of −1.01 × 108 m3·year−1 with obvious stage characteristic during 1961–2016. The water yield was highest in the 1960s and varying degrees of decline were detected in the following periods, resulting in a decrease of available freshwater by 20.54%–58.24%. Human activity had a dominant contribution to induce an increasing runoff decline from 2.068 to 5.776 km3, while the effect of climate was relatively small and lead to runoff reduction, except in the 1970s. This study gave a comprehensive understanding of time-varying runoff variability and highlighted the importance of appropriate human intervention with respect to climate change to ensure water resources security

Calcium Ion Flow Permeates Cells through SOCs to Promote Cathode-Directed Galvanotaxis.

Sensing and responding to endogenous electrical fields are important abilities for cells engaged in processes such as embryogenesis, regeneration and wound healing. Many types of cultured cells have been induced to migrate directionally within electrical fields in vitro using a process known as galvanotaxis. The underlying mechanism by which cells sense electrical fields is unknown. In this study, we assembled a polydimethylsiloxane (PDMS) galvanotaxis system and found that mouse fibroblasts and human prostate cancer PC3 cells migrated to the cathode. By comparing the effects of a pulsed direct current, a constant direct current and an anion-exchange membrane on the directed migration of mouse fibroblasts, we found that these cells responded to the ionic flow in the electrical fields. Taken together, the observed effects of the calcium content of the medium, the function of the store-operated calcium channels (SOCs) and the intracellular calcium content on galvanotaxis indicated that calcium ionic flow from the anode to the cathode within the culture medium permeated the cells through SOCs at the drift velocity, promoting migration toward the cathode. The RTK-PI3K pathway was involved in this process, but the ROCK and MAPK pathways were not. PC3 cells and mouse fibroblasts utilized the same mechanism of galvanotaxis. Together, these results indicated that the signaling pathway responsible for cathode-directed cellular galvanotaxis involved calcium ionic flow from the anode to the cathode within the culture medium, which permeated the cells through SOCs, causing cytoskeletal reorganization via PI3K signaling