PPanG: a precision pangenome browser enabling nucleotide-level analysis of genomic variations in individual genomes and their graph-based pangenome.
Comparative pangenomics
Genome annotation
Genome browser
Graph pangenome
Rice
Journal
BMC genomics
ISSN: 1471-2164
Titre abrégé: BMC Genomics
Pays: England
ID NLM: 100965258
Informations de publication
Date de publication:
24 Apr 2024
24 Apr 2024
Historique:
received:
08
12
2023
accepted:
11
04
2024
medline:
25
4
2024
pubmed:
25
4
2024
entrez:
24
4
2024
Statut:
epublish
Résumé
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 .
Identifiants
pubmed: 38658835
doi: 10.1186/s12864-024-10302-5
pii: 10.1186/s12864-024-10302-5
doi:
Substances chimiques
Nucleotides
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
405Subventions
Organisme : the Hainan Yazhou Bay Seed Lab Project
ID : B23CJ0208
Organisme : the Hainan Yazhou Bay Seed Lab Project
ID : B23CJ0208
Organisme : the Hainan Yazhou Bay Seed Lab Project
ID : B23CJ0208
Organisme : Institute of Crop Sciences, Chinese Academy of Agricultural Sciences
ID : YBXM
Organisme : Scientific Innovation 2030 Program
ID : 2022ZD0401703
Organisme : Scientific Innovation 2030 Program
ID : 2022ZD0401703
Organisme : National Key Research and Development Program of China
ID : SQ2023YFF1000094
Organisme : National Natural Science Foundation of China
ID : 32170643
Organisme : Natural Science Foundation of Shanghai Municipality
ID : 20ZR1428200
Informations de copyright
© 2024. The Author(s).
Références
Bayer PE, Golicz AA, Scheben A, Batley J, Edwards D. Plant pan-genomes are the new reference. Nat Plants. 2020;6(8):914–20.
doi: 10.1038/s41477-020-0733-0
pubmed: 32690893
Li W, Liu J, Zhang H, Liu Z, Wang Y, Xing L, He Q, Du H. Plant pan-genomics: recent advances, new challenges, and roads ahead. J Genet Genomics. 2022;49(9):833–46.
doi: 10.1016/j.jgg.2022.06.004
pubmed: 35750315
Tettelin H, Masignani V, Cieslewicz MJ, Donati C, Medini D, Ward NL, Angiuoli SV, Crabtree J, Jones AL, Durkin AS, et al. Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: implications for the microbial pan-genome. Proc Natl Acad Sci U S A. 2005;102(39):13950–5.
doi: 10.1073/pnas.0506758102
pubmed: 16172379
pmcid: 1216834
Zhang F, Xue H, Dong X, Li M, Zheng X, Li Z, Xu J, Wang W, Wei C. Long-read sequencing of 111 rice genomes reveals significantly larger pan-genomes. Genome Res. 2022;32(5):853–63.
pubmed: 35396275
pmcid: 9104699
Duan Z, Qiao Y, Lu J, Lu H, Zhang W, Yan F, Sun C, Hu Z, Zhang Z, Li G, et al. HUPAN: a pan-genome analysis pipeline for human genomes. Genome Biol. 2019;20(1):149.
doi: 10.1186/s13059-019-1751-y
pubmed: 31366358
pmcid: 6670167
Li J, Yuan D, Wang P, Wang Q, Sun M, Liu Z, Si H, Xu Z, Ma Y, Zhang B, et al. Cotton pan-genome retrieves the lost sequences and genes during domestication and selection. Genome Biol. 2021;22(1):119.
doi: 10.1186/s13059-021-02351-w
pubmed: 33892774
pmcid: 8063427
Wang K, Hu H, Tian Y, Li J, Scheben A, Zhang C, Li Y, Wu J, Yang L, Fan X, et al. The Chicken Pan-genome reveals Gene Content Variation and a promoter region deletion in IGF2BP1 affecting body size. Mol Biol Evol. 2021;38(11):5066–81.
doi: 10.1093/molbev/msab231
pubmed: 34329477
pmcid: 8557422
Golicz AA, Bayer PE, Bhalla PL, Batley J, Edwards D. Pangenomics comes of age: from Bacteria to plant and animal applications. Trends Genet. 2020;36(2):132–45.
doi: 10.1016/j.tig.2019.11.006
pubmed: 31882191
Tranchant-Dubreuil C, Rouard M, Sabot F. Plant Pangenome: impacts on phenotypes and evolution. Ann Plant Rev Online. 2019;2(2):453–77.
doi: 10.1002/9781119312994.apr0664
Wang S, Qian YQ, Zhao RP, Chen LL, Song JM. Graph-based pan-genomes: increased opportunities in plant genomics. J Exp Bot. 2023;74(1):24–39.
doi: 10.1093/jxb/erac412
pubmed: 36255144
Golicz AA, Bayer PE, Barker GC, Edger PP, Kim H, Martinez PA, Chan CK, Severn-Ellis A, McCombie WR, Parkin IA, et al. The pangenome of an agronomically important crop plant Brassica oleracea. Nat Commun. 2016;7:13390.
doi: 10.1038/ncomms13390
pubmed: 27834372
pmcid: 5114598
Wang J, Yang W, Zhang S, Hu H, Yuan Y, Dong J, Chen L, Ma Y, Yang T, Zhou L, et al. A pangenome analysis pipeline provides insights into functional gene identification in rice. Genome Biol. 2023;24(1):19.
doi: 10.1186/s13059-023-02861-9
pubmed: 36703158
pmcid: 9878884
Bayer PE, Petereit J, Durant E, Monat C, Rouard M, Hu H, Chapman B, Li C, Cheng S, Batley J, et al. Wheat panache: a pangenome graph database representing presence-absence variation across sixteen bread wheat genomes. Plant Genome. 2022;15(3):e20221.
doi: 10.1002/tpg2.20221
pubmed: 35644986
Kehr B, Trappe K, Holtgrewe M, Reinert K. Genome alignment with graph data structures: a comparison. BMC Bioinformatics. 2014;15:99.
doi: 10.1186/1471-2105-15-99
pubmed: 24712884
pmcid: 4020321
Paten B, Novak AM, Eizenga JM, Garrison E. Genome graphs and the evolution of genome inference. Genome Res. 2017;27(5):665–76.
doi: 10.1101/gr.214155.116
pubmed: 28360232
pmcid: 5411762
Shang L, Li X, He H, Yuan Q, Song Y, Wei Z, Lin H, Hu M, Zhao F, Zhang C, et al. A super pan-genomic landscape of rice. Cell Res. 2022;32(10):878–96.
doi: 10.1038/s41422-022-00685-z
pubmed: 35821092
pmcid: 9525306
Garrison E, Siren J, Novak AM, Hickey G, Eizenga JM, Dawson ET, Jones W, Garg S, Markello C, Lin MF, et al. Variation graph toolkit improves read mapping by representing genetic variation in the reference. Nat Biotechnol. 2018;36(9):875–9.
doi: 10.1038/nbt.4227
pubmed: 30125266
pmcid: 6126949
Beyer W, Novak AM, Hickey G, Chan J, Tan V, Paten B, Zerbino DR. Sequence tube maps: making graph genomes intuitive to commuters. Bioinformatics. 2019;35(24):5318–20.
doi: 10.1093/bioinformatics/btz597
pubmed: 31368484
pmcid: 6954646
Diesh C, Stevens GJ, Xie P, De Jesus Martinez T, Hershberg EA, Leung A, Guo E, Dider S, Zhang J, Bridge C, et al. JBrowse 2: a modular genome browser with views of synteny and structural variation. Genome Biol. 2023;24(1):74.
doi: 10.1186/s13059-023-02914-z
pubmed: 37069644
pmcid: 10108523
Monna L, Kitazawa N, Yoshino R, Suzuki J, Masuda H, Maehara Y, Tanji M, Sato M, Nasu S, Minobe Y. Positional cloning of rice semidwarfing gene, sd-1: rice green revolution gene encodes a mutant enzyme involved in gibberellin synthesis. DNA Res. 2002;9(1):11–7.
doi: 10.1093/dnares/9.1.11
pubmed: 11939564
Sasaki A, Ashikari M, Ueguchi-Tanaka M, Itoh H, Nishimura A, Swapan D, Ishiyama K, Saito T, Kobayashi M, Khush GS, et al. A mutant gibberellin-synthesis gene in rice. Nature. 2002;416(6882):701–2.
doi: 10.1038/416701a
pubmed: 11961544
Chen X, Liu P, Mei L, He X, Chen L, Liu H, Shen S, Ji Z, Zheng X, Zhang Y, et al. Xa7, a new executor R gene that confers durable and broad-spectrum resistance to bacterial blight disease in rice. Plant Commun. 2021;2(3):100143.
doi: 10.1016/j.xplc.2021.100143
pubmed: 34027390
pmcid: 8132130
Luo D, Huguet-Tapia JC, Raborn RT, White FF, Brendel VP, Yang B. The Xa7 resistance gene guards the rice susceptibility gene SWEET14 against exploitation by the bacterial blight pathogen. Plant Commun. 2021;2(3):100164.
doi: 10.1016/j.xplc.2021.100164
pubmed: 34027391
pmcid: 8132128
Ouyang S, Zhu W, Hamilton J, Lin H, Campbell M, Childs K, Thibaud-Nissen F, Malek RL, Lee Y, Zheng L, et al. The TIGR Rice Genome Annotation Resource: improvements and new features. Nucleic Acids Res. 2007;35(Database issue):D883–887.
doi: 10.1093/nar/gkl976
pubmed: 17145706
Yuan Q, Ouyang S, Wang A, Zhu W, Maiti R, Lin H, Hamilton J, Haas B, Sultana R, Cheung F, et al. The institute for genomic research Osa1 rice genome annotation database. Plant Physiol. 2005;138(1):18–26.
doi: 10.1104/pp.104.059063
pubmed: 15888674
pmcid: 1104156
Yokoyama TT, Sakamoto Y, Seki M, Suzuki Y, Kasahara M. MoMI-G: modular multi-scale integrated genome graph browser. BMC Bioinformatics. 2019;20(1):548.
doi: 10.1186/s12859-019-3145-2
pubmed: 31690272
pmcid: 6833150
Fu L, Niu B, Zhu Z, Wu S, Li W. CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinformatics. 2012;28(23):3150–2.
doi: 10.1093/bioinformatics/bts565
pubmed: 23060610
pmcid: 3516142
Li W, Godzik A. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics. 2006;22(13):1658–9.
doi: 10.1093/bioinformatics/btl158
pubmed: 16731699
Garrison E, Guarracino A, Heumos S, Villani F, Bao Z, Tattini L, Hagmann J, Vorbrugg S, Marco-Sola S, Kubica C et al. Building pangenome graphs. bioRxiv 2023.
Hickey G, Monlong J, Ebler J, Novak AM, Eizenga JM, Gao Y, Marschall T, Li H, Paten B. Pangenome graph construction from genome alignments with Minigraph-Cactus. Nat Biotechnol 2023.