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iSymBase: an integrative functional-genomic platform for ecological exploration of insect symbionts
Zuoqi Wang1, Yingjie Zhu1, Xunyan Liu1
1State Key Laboratory of Rice Biology and Breeding & Ministry of Agricultural and Rural Affairs Key Laboratory of Molecular Biology of Crop Pathogens and Insect Pests & Zhejiang Key Laboratory of Biology and Ecological Regulation of Crop Pathogens and Insects, Institute of Insect Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China.
Abstract:
Insect symbionts play essential roles in host biology, influencing nutrition, immunity, reproduction, and environmental adaptation, ultimately shaping insect physiology, ecology, and evolution. With the rapid growth of functional and genomic datasets on insect symbionts, there remains a critical need for a dedicated platform to systematically compile, organize, and analyze these datasets from an integrative ecological perspective. Here, we developed an insect Symbiont database, named as iSymBase, by manually curating functional records and genomic datasets of insect symbionts from published academic literature. Currently, iSymBase contains over 2657 insect symbiont functional records spanning 795 host species, along with 1494 metagenomes, 14 992 amplicon datasets, and standardized genome and gene catalogs, providing a comprehensive resource for ecological and comparative insect symbiont researches. iSymBase offers standardized query functionalities, such as data browsing, keyword associative search, sequence alignment, data download, and submission. Beyond conventional database functionalities, iSymBase provides several innovative tools: insect-symbiont interaction network for host-symbiont ecological relationships, a batch annotation tool for detecting ecologically functional symbionts from microbiome profiles, and an artificial intelligence (AI)-powered chatbot iSymSeek designed to assist researchers with related knowledge queries. Taken together, iSymBase will serve as an open-access and continually updated platform for storing, querying, and analyzing insect symbiont data, supporting ecological exploration of host-symbiont interactions, symbiont functional diversity, and microbiome-driven adaptation. Database URL: http://symbiont.insect-genome.com/.
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