The chromosome-level genome and functional database accelerate research about biosynthesis of secondary metabolites in Rosa roxburghii.


Journal

BMC plant biology
ISSN: 1471-2229
Titre abrégé: BMC Plant Biol
Pays: England
ID NLM: 100967807

Informations de publication

Date de publication:
17 May 2024
Historique:
received: 20 11 2023
accepted: 05 05 2024
medline: 18 5 2024
pubmed: 18 5 2024
entrez: 17 5 2024
Statut: epublish

Résumé

Rosa roxburghii Tratt, a valuable plant in China with long history, is famous for its fruit. It possesses various secondary metabolites, such as L-ascorbic acid (vitamin C), alkaloids and poly saccharides, which make it a high nutritional and medicinal value. Here we characterized the chromosome-level genome sequence of R. roxburghii, comprising seven pseudo-chromosomes with a total size of 531 Mb and a heterozygosity of 0.25%. We also annotated 45,226 coding gene loci after masking repeat elements. Orthologs for 90.1% of the Complete Single-Copy BUSCOs were found in the R. roxburghii annotation. By aligning with protein sequences from public platform, we annotated 85.89% genes from R. roxburghii. Comparative genomic analysis revealed that R. roxburghii diverged from Rosa chinensis approximately 5.58 to 13.17 million years ago, and no whole-genome duplication event occurred after the divergence from eudicots. To fully utilize this genomic resource, we constructed a genomic database RroFGD with various analysis tools. Otherwise, 69 enzyme genes involved in L-ascorbate biosynthesis were identified and a key enzyme in the biosynthesis of vitamin C, GDH (L-Gal-1-dehydrogenase), is used as an example to introduce the functions of the database. This genome and database will facilitate the future investigations into gene function and molecular breeding in R. roxburghii.

Identifiants

pubmed: 38760710
doi: 10.1186/s12870-024-05109-1
pii: 10.1186/s12870-024-05109-1
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

410

Subventions

Organisme : National Natural Science Foundation of China
ID : NO.32160139
Organisme : National Natural Science Foundation of China
ID : NO.32260140
Organisme : the University Science and Technology Innovation Team of the Guizhou Provincial Department of Education
ID : [2023]071
Organisme : the University Science and Technology Innovation Team of the Guizhou Provincial Department of Education
ID : [2023]071
Organisme : the Guizhou Provincial Science and Technology Projects
ID : ZK[2022]505
Organisme : the Guizhou Provincial Science and Technology Projects
ID : ZK[2022]505
Organisme : the National and Provincial Scientific and Technological Innovation Talent Team of the Guizhou University of Traditional Chinese Medicine
ID : GZYTDHZ[2022]003
Organisme : the National and Provincial Scientific and Technological Innovation Talent Team of the Guizhou University of Traditional Chinese Medicine
ID : GZYTDHZ[2022]003
Organisme : Guizhou Provincial Basic Research Program (Natural Science) under Grant number Qianke He Foundation
ID : ZK[2022] General 506
Organisme : Guizhou University of Traditional Chinese Medicine Graduate Education Innovation Program
ID : YCXJYS2023033

Informations de copyright

© 2024. The Author(s).

Références

Su J, Zhang B, Fu X, Huang Q, Li C, Liu G, Hai Liu R. Recent advances in polysaccharides from Rose Roxburghii Tratt fruits: isolation, structural characterization, and bioactivities. Food Funct. 2022;13(24):12561–71.
pubmed: 36453451 doi: 10.1039/D2FO02192G
Wang L, Wei T, Zheng L, Jiang F, Ma W, Lu M, Wu X, An H. Recent advances on main active ingredients, pharmacological activities of Rosa Roxbughii and its development and utilization. Foods 2023, 12(5).
Jiang L, Lu M, Rao T, Liu Z, Wu X, An H. Comparative analysis of Fruit Metabolome using widely targeted Metabolomics reveals nutritional characteristics of different Rosa roxburghii genotypes. Foods 2022, 11(6).
Xu J, Vidyarthi SK, Bai W, Pan ZJJFF. Nutritional constituents, health benefits and processing of Rosa Roxburghii: A review. 2019, 60:103456.
Shen C, Wang Y, Zhang H, Li W, Chen W, Kuang M, Song Y, Zhong Z. Exploring the active components and potential mechanisms of Rosa roxburghii Tratt in treating type 2 diabetes mellitus based on UPLC-Q-exactive Orbitrap/MS and network pharmacology. Chin Med. 2023;18(1):12.
pubmed: 36747287 pmcid: 9903504 doi: 10.1186/s13020-023-00713-z
Chen Y, Liu ZJ, Liu J, Liu LK, Zhang ES, Li WL. Inhibition of metastasis and invasion of ovarian cancer cells by crude polysaccharides from rosa roxburghii tratt in vitro. Asian Pac J Cancer Prev. 2014;15(23):10351–4.
pubmed: 25556474 doi: 10.7314/APJCP.2014.15.23.10351
van der Westhuizen FH, van Rensburg CS, Rautenbach GS, Marnewick JL, Loots du T, Huysamen C, Louw R, Pretorius PJ, Erasmus E. In vitro antioxidant, antimutagenic and genoprotective activity of Rosa roxburghii fruit extract. Phytother Res. 2008;22(3):376–83.
pubmed: 18167049 doi: 10.1002/ptr.2330
Wang L, Zhang B, Xiao J, Huang Q, Li C, Fu X. Physicochemical, functional, and biological properties of water-soluble polysaccharides from Rosa roxburghii Tratt fruit. Food Chem. 2018;249:127–35.
pubmed: 29407915 doi: 10.1016/j.foodchem.2018.01.011
Wang L, Zhang P, Li C, Xu F, Chen J. A polysaccharide from Rosa roxburghii Tratt fruit attenuates high-fat diet-induced intestinal barrier dysfunction and inflammation in mice by modulating the gut microbiota. Food Funct. 2022;13(2):530–47.
pubmed: 34932054 doi: 10.1039/D1FO03190B
Wang LT, Lv MJ, An JY, Fan XH, Dong MZ, Zhang SD, Wang JD, Wang YQ, Cai ZH, Fu YJ. Botanical characteristics, phytochemistry and related biological activities of Rosa roxburghii Tratt fruit, and its potential use in functional foods: a review. Food Funct. 2021;12(4):1432–51.
pubmed: 33533385 doi: 10.1039/D0FO02603D
Lafontaine DL, Yang L, Dekker J, Gibcus JH. Hi-C 3.0: Improved Protocol for genome-wide chromosome conformation capture. Curr Protoc. 2021;1(7):e198.
pubmed: 34286910 pmcid: 8362010 doi: 10.1002/cpz1.198
Pu X, Li Z, Tian Y, Gao R, Hao L, Hu Y, He C, Sun W, Xu M, Peters RJ, et al. The honeysuckle genome provides insight into the molecular mechanism of carotenoid metabolism underlying dynamic flower coloration. New Phytol. 2020;227(3):930–43.
pubmed: 32187685 pmcid: 7116227 doi: 10.1111/nph.16552
Tu L, Su P, Zhang Z, Gao L, Wang J, Hu T, Zhou J, Zhang Y, Zhao Y, Liu Y, et al. Genome of Tripterygium Wilfordii and identification of cytochrome P450 involved in triptolide biosynthesis. Nat Commun. 2020;11(1):971.
pubmed: 32080175 pmcid: 7033203 doi: 10.1038/s41467-020-14776-1
Zhang Y, Zhang GQ, Zhang D, Liu XD, Xu XY, Sun WH, Yu X, Zhu X, Wang ZW, Zhao X, et al. Chromosome-scale assembly of the Dendrobium chrysotoxum genome enhances the understanding of orchid evolution. Hortic Res. 2021;8(1):183.
pubmed: 34465765 pmcid: 8408244 doi: 10.1038/s41438-021-00621-z
Jiang L, Lin M, Wang H, Song H, Zhang L, Huang Q, Chen R, Song C, Li G, Cao Y. Haplotype-resolved genome assembly of Bletilla striata (Thunb.) Reichb.f. To elucidate medicinal value. Plant J. 2022;111(5):1340–53.
pubmed: 35785503 doi: 10.1111/tpj.15892
Marcais G, Kingsford C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics. 2011;27(6):764–70.
pubmed: 21217122 pmcid: 3051319 doi: 10.1093/bioinformatics/btr011
Liu B, Shi Y, Yuan J, Hu X, Zhang H, Li N, Li Z, Chen Y, Mu D, Fan WJQB. Estimation of genomic characteristics by analyzing k-mer frequency in de novo genome projects. 2013, 35(s 1–3):62–67.
Chen Y, Nie F, Xie SQ, Zheng YF, Dai Q, Bray T, Wang YX, Xing JF, Huang ZJ, Wang DP, et al. Efficient assembly of nanopore reads via highly accurate and intact error correction. Nat Commun. 2021;12(1):60.
pubmed: 33397900 pmcid: 7782737 doi: 10.1038/s41467-020-20236-7
Hu J, Fan J, Sun Z, Liu S. NextPolish: a fast and efficient genome polishing tool for long-read assembly. Bioinformatics. 2020;36(7):2253–5.
pubmed: 31778144 doi: 10.1093/bioinformatics/btz891
Dudchenko O, Batra SS, Omer AD, Nyquist SK, Hoeger M, Durand NC, Shamim MS, Machol I, Lander ES, Aiden AP, et al. De novo assembly of the Aedes aegypti genome using Hi-C yields chromosome-length scaffolds. Science. 2017;356(6333):92–5.
pubmed: 28336562 pmcid: 5635820 doi: 10.1126/science.aal3327
Servant N, Varoquaux N, Lajoie BR, Viara E, Chen CJ, Vert JP, Heard E, Dekker J, Barillot E. HiC-Pro: an optimized and flexible pipeline for Hi-C data processing. Genome Biol. 2015;16:259.
pubmed: 26619908 pmcid: 4665391 doi: 10.1186/s13059-015-0831-x
Akdemir KC, Chin L. HiCPlotter integrates genomic data with interaction matrices. Genome Biol. 2015;16(1):198.
pubmed: 26392354 pmcid: 4576377 doi: 10.1186/s13059-015-0767-1
Manni M, Berkeley MR, Seppey M, Simao FA, Zdobnov EM. BUSCO Update: Novel and Streamlined Workflows along with broader and deeper phylogenetic Coverage for Scoring of Eukaryotic, Prokaryotic, and viral genomes. Mol Biol Evol. 2021;38(10):4647–54.
pubmed: 34320186 pmcid: 8476166 doi: 10.1093/molbev/msab199
Flynn JM, Hubley R, Goubert C, Rosen J, Clark AG, Feschotte C, Smit AF. RepeatModeler2 for automated genomic discovery of transposable element families. Proc Natl Acad Sci U S A. 2020;117(17):9451–7.
pubmed: 32300014 pmcid: 7196820 doi: 10.1073/pnas.1921046117
Tempel S. Using and understanding RepeatMasker. Methods Mol Biol. 2012;859:29–51.
pubmed: 22367864 doi: 10.1007/978-1-61779-603-6_2
Kim D, Paggi JM, Park C, Bennett C, Salzberg SL. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat Biotechnol. 2019;37(8):907–15.
pubmed: 31375807 pmcid: 7605509 doi: 10.1038/s41587-019-0201-4
Kovaka S, Zimin AV, Pertea GM, Razaghi R, Salzberg SL, Pertea M. Transcriptome assembly from long-read RNA-seq alignments with StringTie2. Genome Biol. 2019;20(1):278.
pubmed: 31842956 pmcid: 6912988 doi: 10.1186/s13059-019-1910-1
Vaser R, Sovic I, Nagarajan N, Sikic M. Fast and accurate de novo genome assembly from long uncorrected reads. Genome Res. 2017;27(5):737–46.
pubmed: 28100585 pmcid: 5411768 doi: 10.1101/gr.214270.116
Li H. Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences. Bioinformatics. 2016;32(14):2103–10.
pubmed: 27153593 pmcid: 4937194 doi: 10.1093/bioinformatics/btw152
Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, Madden TL. BLAST+: architecture and applications. BMC Bioinformatics. 2009;10:421.
pubmed: 20003500 pmcid: 2803857 doi: 10.1186/1471-2105-10-421
Slater GS, Birney E. Automated generation of heuristics for biological sequence comparison. BMC Bioinformatics. 2005;6:31.
pubmed: 15713233 pmcid: 553969 doi: 10.1186/1471-2105-6-31
Huang X, Yan H, Zhai L, Yang Z, Yi Y. Characterization of the Rosa roxburghii Tratt transcriptome and analysis of MYB genes. PLoS ONE. 2019;14(3):e0203014.
pubmed: 30860996 pmcid: 6414006 doi: 10.1371/journal.pone.0203014
Buchfink B, Xie C, Huson DH. Fast and sensitive protein alignment using DIAMOND. Nat Methods. 2015;12(1):59–60.
pubmed: 25402007 doi: 10.1038/nmeth.3176
Xie C, Mao X, Huang J, Ding Y, Wu J, Dong S, Kong L, Gao G, Li CY, Wei L. KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases. Nucleic Acids Res. 2011;39(Web Server issue):W316–322.
pubmed: 21715386 pmcid: 3125809 doi: 10.1093/nar/gkr483
Emms DM, Kelly S. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol. 2019;20(1):238.
pubmed: 31727128 pmcid: 6857279 doi: 10.1186/s13059-019-1832-y
Stamatakis A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics. 2014;30(9):1312–3.
pubmed: 24451623 pmcid: 3998144 doi: 10.1093/bioinformatics/btu033
Yang Z. PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol. 2007;24(8):1586–91.
pubmed: 17483113 doi: 10.1093/molbev/msm088
De Bie T, Cristianini N, Demuth JP, Hahn MW. CAFE: a computational tool for the study of gene family evolution. Bioinformatics. 2006;22(10):1269–71.
pubmed: 16543274 doi: 10.1093/bioinformatics/btl097
Zwaenepoel A, Van de Peer Y. Wgd-simple command line tools for the analysis of ancient whole-genome duplications. Bioinformatics. 2019;35(12):2153–5.
pubmed: 30398564 doi: 10.1093/bioinformatics/bty915
Wang Y, Tang H, Debarry JD, Tan X, Li J, Wang X, Lee TH, Jin H, Marler B, Guo H, et al. MCScanX: a toolkit for detection and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Res. 2012;40(7):e49.
pubmed: 22217600 pmcid: 3326336 doi: 10.1093/nar/gkr1293
Krzywinski M, Schein J, Birol I, Connors J, Gascoyne R, Horsman D, Jones SJ, Marra MA. Circos: an information aesthetic for comparative genomics. Genome Res. 2009;19(9):1639–45.
pubmed: 19541911 pmcid: 2752132 doi: 10.1101/gr.092759.109
Pertea M, Pertea GM, Antonescu CM, Chang TC, Mendell JT, Salzberg SL. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol. 2015;33(3):290–5.
pubmed: 25690850 pmcid: 4643835 doi: 10.1038/nbt.3122
Zheng Y, Jiao C, Sun H, Rosli HG, Pombo MA, Zhang P, Banf M, Dai X, Martin GB, Giovannoni JJ, et al. iTAK: a program for genome-wide prediction and Classification of Plant Transcription Factors, transcriptional regulators, and Protein Kinases. Mol Plant. 2016;9(12):1667–70.
pubmed: 27717919 doi: 10.1016/j.molp.2016.09.014
Zhou J, Xu Y, Lin S, Guo Y, Deng W, Zhang Y, Guo A, Xue Y. iUUCD 2.0: an update with rich annotations for ubiquitin and ubiquitin-like conjugations. Nucleic Acids Res. 2018;46(D1):D447–53.
pubmed: 29106644 doi: 10.1093/nar/gkx1041
Yi X, Du Z, Su Z. PlantGSEA: a gene set enrichment analysis toolkit for plant community. Nucleic Acids Res. 2013;41(Web Server issue):W98–103.
pubmed: 23632162 pmcid: 3692080 doi: 10.1093/nar/gkt281
Yang J, Yan H, Liu Y, Da L, Xiao Q, Xu W, Su Z. GURFAP: a platform for gene function analysis in Glycyrrhiza Uralensis. Front Genet. 2022;13:823966.
pubmed: 35495163 pmcid: 9039005 doi: 10.3389/fgene.2022.823966
Yu J, Zhang Z, Wei J, Ling Y, Xu W, Su Z. SFGD: a comprehensive platform for mining functional information from soybean transcriptome data and its use in identifying acyl-lipid metabolism pathways. BMC Genomics. 2014;15:271.
pubmed: 24712981 pmcid: 4051163 doi: 10.1186/1471-2164-15-271
Yang J, Li P, Li Y, Xiao Q. GelFAP v2.0: an improved platform for Gene functional analysis in Gastrodia Elata. BMC Genomics. 2023;24(1):164.
pubmed: 37016293 pmcid: 10074892 doi: 10.1186/s12864-023-09260-1
Deng W, Nickle DC, Learn GH, Maust B, Mullins JI. ViroBLAST: a stand-alone BLAST web server for flexible queries of multiple databases and user’s datasets. Bioinformatics. 2007;23(17):2334–6.
pubmed: 17586542 doi: 10.1093/bioinformatics/btm331
Buels R, Yao E, Diesh CM, Hayes RD, Munoz-Torres M, Helt G, Goodstein DM, Elsik CG, Lewis SE, Stein L, et al. JBrowse: a dynamic web platform for genome visualization and analysis. Genome Biol. 2016;17:66.
pubmed: 27072794 pmcid: 4830012 doi: 10.1186/s13059-016-0924-1
Tian F, Yang DC, Meng YQ, Jin J, Gao G. PlantRegMap: charting functional regulatory maps in plants. Nucleic Acids Res. 2020;48(D1):D1104–13.
pubmed: 31701126
Chen F, Su L, Hu S, Xue JY, Liu H, Liu G, Jiang Y, Du J, Qiao Y, Fan Y, et al. A chromosome-level genome assembly of rugged rose (Rosa rugosa) provides insights into its evolution, ecology, and floral characteristics. Hortic Res. 2021;8(1):141.
pubmed: 34145222 pmcid: 8213826 doi: 10.1038/s41438-021-00594-z
Lorence A, Chevone BI, Mendes P, Nessler CL. Myo-inositol oxygenase offers a possible entry point into plant ascorbate biosynthesis. Plant Physiol. 2004;134(3):1200–5.
pubmed: 14976233 pmcid: 389944 doi: 10.1104/pp.103.033936
Huang M, Xu Q, Deng XX. L-Ascorbic acid metabolism during fruit development in an ascorbate-rich fruit crop chestnut rose (Rosa roxburghii Tratt). J Plant Physiol. 2014;171(14):1205–16.
pubmed: 25019249 doi: 10.1016/j.jplph.2014.03.010
Vargas JA, Leonardo DA, D’Muniz Pereira H, Lopes AR, Rodriguez HN, Cobos M, Marapara JL, Castro JC, Garratt RC. Structural characterization of L-Galactose dehydrogenase: an Essential Enzyme for Vitamin C Biosynthesis. Plant Cell Physiol. 2022;63(8):1140–55.
pubmed: 35765894 pmcid: 9381564 doi: 10.1093/pcp/pcac090
Wheeler GL, Jones MA, Smirnoff N. The biosynthetic pathway of vitamin C in higher plants. Nature. 1998;393(6683):365–9.
pubmed: 9620799 doi: 10.1038/30728
Chen M, Ma Y, Wu S, Zheng X, Kang H, Sang J, Xu X, Hao L, Li Z, Gong Z, et al. Genome warehouse: a public Repository Housing genome-scale data. Genomics Proteom Bioinf. 2021;19(4):584–9.
doi: 10.1016/j.gpb.2021.04.001
Members C-N, Partners. Database resources of the National Genomics Data Center, China National Center for Bioinformation in 2024. Nucleic Acids Res. 2024;52(D1):D18–32.
doi: 10.1093/nar/gkad1078

Auteurs

Jiaotong Yang (J)

Resource Institute for Chinese and Ethnic Materia Medica, Guizhou University of Traditional Chinese Medicine, Guizhou, 550025, China. y_jiaotong@163.com.

Jingjie Zhang (J)

Resource Institute for Chinese and Ethnic Materia Medica, Guizhou University of Traditional Chinese Medicine, Guizhou, 550025, China.

Hengyu Yan (H)

College of Agronomy, Qingdao Agricultural University, Qingdao, 266109, China.

Xin Yi (X)

State Key Laboratory of Plant Diversity and Specialty Crops, Institute of Botany, The Chinese Academy of Sciences, Beijing, China.

Qi Pan (Q)

Resource Institute for Chinese and Ethnic Materia Medica, Guizhou University of Traditional Chinese Medicine, Guizhou, 550025, China.

Yahua Liu (Y)

Resource Institute for Chinese and Ethnic Materia Medica, Guizhou University of Traditional Chinese Medicine, Guizhou, 550025, China.

Mian Zhang (M)

Resource Institute for Chinese and Ethnic Materia Medica, Guizhou University of Traditional Chinese Medicine, Guizhou, 550025, China.

Jun Li (J)

Resource Institute for Chinese and Ethnic Materia Medica, Guizhou University of Traditional Chinese Medicine, Guizhou, 550025, China.

Qiaoqiao Xiao (Q)

Resource Institute for Chinese and Ethnic Materia Medica, Guizhou University of Traditional Chinese Medicine, Guizhou, 550025, China. xqqiao2021@163.com.

Articles similaires

Aspergillus Hydrogen-Ion Concentration Coculture Techniques Secondary Metabolism Streptomyces rimosus
Genome Size Genome, Plant Magnoliopsida Evolution, Molecular Arabidopsis
Genome, Plant Medicago sativa Crops, Agricultural Genomics Polyploidy
Obesity Machine Learning Animals Biomarkers Computational Biology

Classifications MeSH