Worldwide diversity of endophytic fungi and insects associated with dormant tree twigs

International trade in plants and climate change are two of the main factors causing damaging tree pests (i.e. fungi and insects) to spread into new areas. To mitigate these risks, a large-scale assessment of tree-associated fungi and insects is needed. We present records of endophytic fungi and insects in twigs of 17 angiosperm and gymnosperm genera, from 51 locations in 32 countries worldwide. Endophytic fungi were characterized by high-throughput sequencing of 352 samples from 145 tree species in 28 countries. Insects were reared from 227 samples of 109 tree species in 18 countries and sorted into taxonomic orders and feeding guilds. Herbivorous insects were grouped into morphospecies and were identified using molecular and morphological approaches. This dataset reveals the diversity of tree-associated taxa, as it contains 12,721 fungal Amplicon Sequence Variants and 208 herbivorous insect morphospecies, sampled across broad geographic and climatic gradients and for many tree species. This dataset will facilitate applied and fundamental studies on the distribution of fungal endophytes and insects in trees

Finding Our Way through Phenotypes

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility

Finding Our Way through Phenotypes

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility