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Liu M, Zhang F, Lu H, Xue H, Dong X, Li Z, Xu J, Wang W, Wei C. PPanG: a precision pangenome browser enabling nucleotide-level analysis of genomic variations in individual genomes and their graph-based pangenome. BMC Genomics 2024; 25:405. [PMID: 38658835 PMCID: PMC11044437 DOI: 10.1186/s12864-024-10302-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 04/11/2024] [Indexed: 04/26/2024] Open
Abstract
Graph-based pangenome is gaining more popularity than linear pangenome because it stores more comprehensive information of variations. However, traditional linear genome browser has its own advantages, especially the tremendous resources accumulated historically. With the fast-growing number of individual genomes and their annotations available, the demand for a genome browser to visualize genome annotation for many individuals together with a graph-based pangenome is getting higher and higher. Here we report a new pangenome browser PPanG, a precise pangenome browser enabling nucleotide-level comparison of individual genome annotations together with a graph-based pangenome. Nine rice genomes with annotations were provided by default as potential references, and any individual genome can be selected as the reference. Our pangenome browser provides unprecedented insights on genome variations at different levels from base to gene, and reveals how the structures of a gene could differ for individuals. PPanG can be applied to any species with multiple individual genomes available and it is available at https://cgm.sjtu.edu.cn/PPanG .
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Affiliation(s)
- Mingwei Liu
- Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Fan Zhang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
- College of Agronomy, Anhui Agricultural University, Hefei, 230036, China
| | - Huimin Lu
- Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Hongzhang Xue
- Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Xiaorui Dong
- Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Zhikang Li
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
- College of Agronomy, Anhui Agricultural University, Hefei, 230036, China
| | - Jianlong Xu
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Wensheng Wang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China.
- College of Agronomy, Anhui Agricultural University, Hefei, 230036, China.
- National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, 572024, China.
| | - Chaochun Wei
- Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
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