PPGR: a comprehensive perennial plant genomes and regulation database.
Sen YangWenting ZongLingling ShiRuisi LiZhenshu MaShubao MaJingna SiZhijing WuJinglan ZhaiYingke MaZhuojing FanSisi ChenHuahong HuangDeiqiang ZhangYiming BaoRujiao LiJianbo XiePublished in: Nucleic acids research (2023)
Perennial woody plants hold vital ecological significance, distinguished by their unique traits. While significant progress has been made in their genomic and functional studies, a major challenge persists: the absence of a comprehensive reference platform for collection, integration and in-depth analysis of the vast amount of data. Here, we present PPGR (Resource for Perennial Plant Genomes and Regulation; https://ngdc.cncb.ac.cn/ppgr/) to address this critical gap, by collecting, integrating, analyzing and visualizing genomic, gene regulation and functional data of perennial plants. PPGR currently includes 60 species, 847 million protein-protein/TF (transcription factor)-target interactions, 9016 transcriptome samples under various environmental conditions and genetic backgrounds. Noteworthy is the focus on genes that regulate wood production, seasonal dormancy, terpene biosynthesis and leaf senescence representing a wealth of information derived from experimental data, literature mining, public databases and genomic predictions. Furthermore, PPGR incorporates a range of multi-omics search and analysis tools to facilitate browsing and application of these extensive datasets. PPGR represents a comprehensive and high-quality resource for perennial plants, substantiated by an illustrative case study that demonstrates its capacity in unraveling gene functions and shedding light on potential regulatory processes.
Keyphrases
- genome wide
- copy number
- transcription factor
- protein protein
- big data
- electronic health record
- human health
- genome wide identification
- cell wall
- dna methylation
- small molecule
- single cell
- healthcare
- systematic review
- gene expression
- dna damage
- endothelial cells
- emergency department
- optical coherence tomography
- machine learning
- adverse drug
- artificial intelligence
- mental health
- risk assessment
- rna seq
- lymph node metastasis
- living cells
- social media
- dna binding
- stress induced
- life cycle