AnimalMetaOmics: a multi-omics data resources for exploring animal microbial genomes and microbiomes
文献类型： 外文期刊
作者： Hu, Ruirui 1 ; Li, Fulin 1 ; Chen, Yifan 2 ; Liu, Chuyang 1 ; Li, Jiawei 2 ; Ma, Zhongchen 4 ; Wang, Yue 1 ; Cui, Chaowen 1 ; Luo, Chengfang 2 ; Zhou, Ping 2 ; Ni, Wei 1 ; Yang, Qing-Yong 2 ; Hu, Shengwei 1 ;
作者机构： 1.Shihezi Univ, Coll Life Sci, Shihezi 832003, Xinjiang, Peoples R China
2.Xinjiang Acad Agr & Reclamat Sci, State Key Lab Sheep Genet Improvement & Hlth Prod, Xinjiang 832003, Peoples R China
3.Huazhong Agr Univ, Coll Informat, Hubei Key Lab Agr Bioinformat, Wuhan 430070, Peoples R China
4.Shihezi Univ, Coll Anim Sci & Technol, Shihezi 832003, Xinjiang, Peoples R China
期刊名称：NUCLEIC ACIDS RESEARCH （ 影响因子：14.9； 五年影响因子：16.4 ）
ISSN： 0305-1048
年卷期： 2023 年
页码：
收录情况： SCI
摘要： The Animal Meta-omics landscape database (AnimalMetaOmics, https://yanglab.hzau.edu.cn/animalmetaomics#/) is a comprehensive and freely available resource that includes metagenomic, metatranscriptomic, and metaproteomic data from various non-human animal species and provides abundant information on animal microbiomes, including cluster analysis of microbial cognate genes, functional gene annotations, active microbiota composition, gene expression abundance, and microbial protein identification. In this work, 55 898 microbial genomes were annotated from 581 animal species, including 42 924 bacterial genomes, 12 336 virus genomes, 496 archaea genomes and 142 fungi genomes. Moreover, 321 metatranscriptomic datasets were analyzed from 31 animal species and 326 metaproteomic datasets from four animal species, as well as the pan-genomic dynamics and compositional characteristics of 679 bacterial species and 13 archaea species from animal hosts. Researchers can efficiently access and acquire the information of cross-host microbiota through a user-friendly interface, such as species, genomes, activity levels, expressed protein sequences and functions, and pan-genome composition. These valuable resources provide an important reference for better exploring the classification, functional diversity, biological process diversity and functional genes of animal microbiota. Graphical Abstract
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