Stress Knowledge Map(SKM;https://skm.nib.si)is a publicly available resource containing two complementary knowledge graphs that describe the current knowledge of biochemical,signaling,and regulatory molecular interact...Stress Knowledge Map(SKM;https://skm.nib.si)is a publicly available resource containing two complementary knowledge graphs that describe the current knowledge of biochemical,signaling,and regulatory molecular interactions in plants:a highly curated model of plant stress signaling(PSS;543 reactions)and a large comprehensive knowledge network(488390 interactions).Both were constructed by domain experts through systematic curation of diverse literature and database resources.SKM provides a single entry point for investigations of plant stress response and related growth trade-offs,as well as interactive explorations of current knowledge.PSS is also formulated as a qualitative and quantitative model for systems biology and thus represents a starting point for a plant digital twin.Here,we describe the features of SKM and show,through two case studies,how it can be used for complex analyses,including systematic hypothesis generation and design of validation experiments,or to gain new insights into experimental observations in plant biology.展开更多
Genome sequences from over 200 plant species have already been published, with this number expected to increase rapidly due to advances in sequencing technologies. Once a new genome has been assembled and the genes id...Genome sequences from over 200 plant species have already been published, with this number expected to increase rapidly due to advances in sequencing technologies. Once a new genome has been assembled and the genes identified, the functional annotation of their putative translational products, proteins, using ontologies is of key importance as it places the sequencing data in a biological context. Furthermore, to keep pace with rapid production of genome sequences, this functional annotation process must be fully automated. Here we present a redesigned and significantly enhanced MapMan4 framework, together with a revised version of the associated online Mercator annotation tool. Compared with the original MapMan, the new ontology has been expanded almost threefold and enforces stricter assignment rules. This framework was then incorporated into Mercator4, which has been upgraded to reflect current knowledge across the land plant group, providing protein annotations for all embryophytes with a comparably high quality. The annotation process has been optimized to allow a plant genome to be annotated in a matter of minutes. The output results continue to be compatible with the established MapMan desktop application.展开更多
基金funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 862858(ADAPT)the Slovenian Research Agency under grant agreements 1000-15-0105,Z7-1888,J4-1777,P4-0165,N4-0199,Z4-50146,and J4-3089ELIXIR,the research infrastructure for life science data through the ELIXIR Implementation Study“Increasing plant data findability for ELIXIR and beyond”and ELIXIR-SI.We gratefully acknowledge funding from the Deutsche Forschungsgemeinschaft(DFG)to U.C.V.(INST 217/939-1 FUGG).
文摘Stress Knowledge Map(SKM;https://skm.nib.si)is a publicly available resource containing two complementary knowledge graphs that describe the current knowledge of biochemical,signaling,and regulatory molecular interactions in plants:a highly curated model of plant stress signaling(PSS;543 reactions)and a large comprehensive knowledge network(488390 interactions).Both were constructed by domain experts through systematic curation of diverse literature and database resources.SKM provides a single entry point for investigations of plant stress response and related growth trade-offs,as well as interactive explorations of current knowledge.PSS is also formulated as a qualitative and quantitative model for systems biology and thus represents a starting point for a plant digital twin.Here,we describe the features of SKM and show,through two case studies,how it can be used for complex analyses,including systematic hypothesis generation and design of validation experiments,or to gain new insights into experimental observations in plant biology.
文摘Genome sequences from over 200 plant species have already been published, with this number expected to increase rapidly due to advances in sequencing technologies. Once a new genome has been assembled and the genes identified, the functional annotation of their putative translational products, proteins, using ontologies is of key importance as it places the sequencing data in a biological context. Furthermore, to keep pace with rapid production of genome sequences, this functional annotation process must be fully automated. Here we present a redesigned and significantly enhanced MapMan4 framework, together with a revised version of the associated online Mercator annotation tool. Compared with the original MapMan, the new ontology has been expanded almost threefold and enforces stricter assignment rules. This framework was then incorporated into Mercator4, which has been upgraded to reflect current knowledge across the land plant group, providing protein annotations for all embryophytes with a comparably high quality. The annotation process has been optimized to allow a plant genome to be annotated in a matter of minutes. The output results continue to be compatible with the established MapMan desktop application.
