The quality and coverage of the available taxonomical and geographical information and the recognition that diversity is multi-faceted are two main factors that hinder to understand the spatial and temporal variations...The quality and coverage of the available taxonomical and geographical information and the recognition that diversity is multi-faceted are two main factors that hinder to understand the spatial and temporal variations of biodiversity. In this study, we aim to quantify the global distribution of five diversity components used to assess freshwater fish diversity in river basins around the world. The multidimensional character of these diversity components was estimated and the so obtained diversity dimensions mapped. This was done taking into account those well-surveyed basins discriminated by considering collector’s curves, and additionally by controlling for the effect of survey effort on all considered diversity components. A total of 1,472,109 occurrence records were analysed, corresponding to 17,292 species of freshwater fishes. Five diversity components were considered: functional richness, species richness, taxonomic diversity, and two rarity measures. Well-surveyed river basins were discriminated using accumulation curves. The effects of survey biases and knowledge gaps were minimized by determining the relationship of each component with the completeness values calculated for each river basin. The geographical pattern derived from raw data is skewed by the unequal knowledge available, and all diversity components were positively correlated with completeness values. The first dimension described the association between species richness and functional diversity. The second dimension represented rarity and taxonomic diversity. The congruence between species richness and functional diversity suggests that ecosystem functions increase with the number of fish species present in river basins and that a decrease in species richness may involve a loss of functionality. The levels of rarity and taxonomic diversity of many species-poor basins found in arid and cold regions suggest that the distinctiveness of their freshwater fishes is primarily a consequence of how isolated these basins are.展开更多
Natural components, evolved to help organisms adapt and defend against threats, are also vital sources for drug discovery due to their diverse and potent bioactivities. In the present work, we proposed the Gene-encode...Natural components, evolved to help organisms adapt and defend against threats, are also vital sources for drug discovery due to their diverse and potent bioactivities. In the present work, we proposed the Gene-encoded Natural Diverse Components Repository (GNDC, https://cbcb.cdutcm.edu.cn/gndc/), a primary and most extensive database dedicated to cataloging diverse natural components. GNDC currently catalogs over 234 million natural components that are organized into four specialized sub-databases: HerbalMDB for 2.32 million secondary metabolites, HerbalPDB for 229 million small peptides, HerbalRDB for 2.38 million small RNAs, and HerbalCDB for 0.26 million carbohydrates. By leveraging customized pipelines for high-throughput multi-omics data and AI technologies, the GNDC enables large-scale discovery and annotation of natural products from nuclear and organellar genomes of species listed in eight global pharmacopoeias and multi-resource data. Compared to existing resources, GNDC achieves a 10-fold increase in component yield and introduces over 200 million previously unreported components. To support this unprecedented data volume and complexity, state-of-the-art AI tools are seamlessly integrated to decipher and annotate vast data collections, such as classification and gene expression signature generation of millions of secondary metabolites. We envision that the GNDC will drive the transformation of drug discovery from an “experience-driven” approach to a “big data-driven” paradigm.展开更多
文摘The quality and coverage of the available taxonomical and geographical information and the recognition that diversity is multi-faceted are two main factors that hinder to understand the spatial and temporal variations of biodiversity. In this study, we aim to quantify the global distribution of five diversity components used to assess freshwater fish diversity in river basins around the world. The multidimensional character of these diversity components was estimated and the so obtained diversity dimensions mapped. This was done taking into account those well-surveyed basins discriminated by considering collector’s curves, and additionally by controlling for the effect of survey effort on all considered diversity components. A total of 1,472,109 occurrence records were analysed, corresponding to 17,292 species of freshwater fishes. Five diversity components were considered: functional richness, species richness, taxonomic diversity, and two rarity measures. Well-surveyed river basins were discriminated using accumulation curves. The effects of survey biases and knowledge gaps were minimized by determining the relationship of each component with the completeness values calculated for each river basin. The geographical pattern derived from raw data is skewed by the unequal knowledge available, and all diversity components were positively correlated with completeness values. The first dimension described the association between species richness and functional diversity. The second dimension represented rarity and taxonomic diversity. The congruence between species richness and functional diversity suggests that ecosystem functions increase with the number of fish species present in river basins and that a decrease in species richness may involve a loss of functionality. The levels of rarity and taxonomic diversity of many species-poor basins found in arid and cold regions suggest that the distinctiveness of their freshwater fishes is primarily a consequence of how isolated these basins are.
基金supported by Natural Science Foundation of Sichuan(2024ZDZX0019).
文摘Natural components, evolved to help organisms adapt and defend against threats, are also vital sources for drug discovery due to their diverse and potent bioactivities. In the present work, we proposed the Gene-encoded Natural Diverse Components Repository (GNDC, https://cbcb.cdutcm.edu.cn/gndc/), a primary and most extensive database dedicated to cataloging diverse natural components. GNDC currently catalogs over 234 million natural components that are organized into four specialized sub-databases: HerbalMDB for 2.32 million secondary metabolites, HerbalPDB for 229 million small peptides, HerbalRDB for 2.38 million small RNAs, and HerbalCDB for 0.26 million carbohydrates. By leveraging customized pipelines for high-throughput multi-omics data and AI technologies, the GNDC enables large-scale discovery and annotation of natural products from nuclear and organellar genomes of species listed in eight global pharmacopoeias and multi-resource data. Compared to existing resources, GNDC achieves a 10-fold increase in component yield and introduces over 200 million previously unreported components. To support this unprecedented data volume and complexity, state-of-the-art AI tools are seamlessly integrated to decipher and annotate vast data collections, such as classification and gene expression signature generation of millions of secondary metabolites. We envision that the GNDC will drive the transformation of drug discovery from an “experience-driven” approach to a “big data-driven” paradigm.
