AMIR: a multi-omics data platform for <i>Asteraceae</i> plants genetics and breeding research

As the largest family of dicotyledon, the Asteraceae family comprises a variety of economically important crops, ornamental plants and numerous medicinal herbs. Advancements in genomics and transcriptomic have revolutionized research in Asteraceae species, generating extensive omics data that necessitate an efficient platform for data integration and analysis. However, existing databases face challenges in mining genes with specific functions and supporting cross-species studies. To address these gaps, we introduce the Asteraceae Multi-omics Information Resource (AMIR; https://yanglab.hzau.edu.cn/AMIR/), a multi-omics hub for the Asteraceae plant community. AMIR integrates diverse omics data from 74 species, encompassing 132 genomes, 4 408 432 genes annotated across seven different perspectives, 3897 transcriptome sequencing samples spanning 131 organs, tissues and stimuli, 42 765 290 unique variants and 15 662 metabolites genes. Leveraging these data, AMIR establishes the first pan-genome, comparative genomics and transcriptome system for the Asteraceae family. Furthermore, AMIR offers user-friendly tools designed to facilitate extensive customized bioinformatics analyses. Two case studies demonstrate AMIR's capability to provide rapid, reproducible and reliable analysis results. In summary, by integrating multi-omics data of Asteraceae species and developing powerful analytical tools, AMIR significantly advances functional genomics research and contributes to breeding practices of Asteraceae.

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Publication Details

Journal
Nucleic Acids Research
Published
2024-10-08
DOI
https://doi.org/10.1093/nar/gkae833
Citations
7
Primary Topic
Plant biochemistry and biosynthesis
Type
article
Field-Weighted Citation Impact
1.64

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article

AMIR: a multi-omics data platform for Asteraceae plants genetics and breeding research

Rui Dai, Zhinan Mei, Chengfang Luo, Linna Zhang et al.
7 citations
Nucleic Acids Research
Plant biochemistry and biosynthesis
1.64
article

AMIR: a multi-omics data platform for Asteraceae plants genetics and breeding research

Rui Dai, Zhinan Mei, Chengfang Luo, Linna Zhang, Qingyong Yang, Hongxia Mao, Dongxu Liu, Xiaoyan Huang, Xiang Chen, Lin He, Jiawei Li
article en
7 citations

Abstract

As the largest family of dicotyledon, the Asteraceae family comprises a variety of economically important crops, ornamental plants and numerous medicinal herbs. Advancements in genomics and transcriptomic have revolutionized research in Asteraceae species, generating extensive omics data that necessitate an efficient platform for data integration and analysis. However, existing databases face challenges in mining genes with specific functions and supporting cross-species studies. To address these gaps, we introduce the Asteraceae Multi-omics Information Resource (AMIR; https://yanglab.hzau.edu.cn/AMIR/), a multi-omics hub for the Asteraceae plant community. AMIR integrates diverse omics data from 74 species, encompassing 132 genomes, 4 408 432 genes annotated across seven different perspectives, 3897 transcriptome sequencing samples spanning 131 organs, tissues and stimuli, 42 765 290 unique variants and 15 662 metabolites genes. Leveraging these data, AMIR establishes the first pan-genome, comparative genomics and transcriptome system for the Asteraceae family. Furthermore, AMIR offers user-friendly tools designed to facilitate extensive customized bioinformatics analyses. Two case studies demonstrate AMIR's capability to provide rapid, reproducible and reliable analysis results. In summary, by integrating multi-omics data of Asteraceae species and developing powerful analytical tools, AMIR significantly advances functional genomics research and contributes to breeding practices of Asteraceae.

Nucleic Acids ResearchVol. 53(D1)
Huazhong Agricultural University (CN)
National Natural Science Foundation of China, Huazhong Agricultural University, National Key Research and Development Program of China
Openalex Percentile: Top 16%
Plant biochemistry and biosynthesis
1.64
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