Abstract
Rosa laevigata is an excellent rose germplasm, highly resistant to aphid, and immune to both rose black spot and powdery mildew disease. It is also a well-known edible plant with a long history of medicinal use in China, having the effects of improving kidney function, inhibiting arteriosclerosis, and reducing inflammation. In this study, we assembled a high-quality chromosome-scale genome for R. laevigata by combining Illumina, PacBio, and Hi-C data, which has a length of approximately 494.2 Mb with a scaffold N50 of 68.6 Mb. A total of 493.2 Mb (99.8%) of the draft genome sequences were anchored on seven pseudochromosomes and two gapless pseudochromosomes were included in the final genome assembly. A total of 37,117 protein-coding genes were predicted, 34,047 of which were functionally annotated. Repeat annotation revealed 659,558 (285.6 Mb) repeat elements, accounting for 57.8% of the genome. The chromosome-scale genome provides valuable information to facilitate comparative genomic analysis of rose family and will accelerate genome-guided breeding and germplasm improvement of both R. laevigata itself and modern roses.
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Background & Summary
Rosa laevigata Michx. (2n = 2x = 14)1 is an evergreen climbing shrub widely distributed in eastern and southern China, with altitude of 200–1,600 meters. Commonly known as Cherokee rose, R. laevigata is the only species in Rosa sect. Laevigatae of Rosaceae, with glabrous leathery leaves and large fragrant white flowers2 (Fig. 1). On one hand, R. laevigata is an excellent germplasm for the germplasm innovation and improvement of modern rose cultivars, highly resistant to aphid3, and immune to both black spot disease and powdery mildew disease of rose4. On the other hand, it is an edible and traditional herbal medicine in China5. The fruits of R. laevigata, known as “Jin-Ying-Zi” in Chinese, are a main Traditional Chinese Medicines ingredient that is prescribed as a kidney tonic for the treatment of urinary diseases, including urinary incontinence and urinary frequency, as well as menstrual irregularities, leucorrhea, and uterine prolapse6. The roots of R. laevigata possess functions such as clearing heat, detoxifying, cooling blood, promoting blood circulation, dispelling stasis, and relieving pain7. In addition, the roots of R. laevigata are used to treat gynecological infections and diseases of the urinary system6. The leaves of R. laevigata could cure burns, skin tumors and ulcers, while the flowers show efficacy in alleviating cold and heat, as well as contain insecticidal properties8.
Rosa laevigata Michx. (a) flowers and leaves, (b) fruit (photographed by H.Y. Jian).
Recent studies on R. laevigata revealed the presence of phenolic acids, steroids, triterpenoids, phenylpropanoids, and other chemical components in the plant that exhibits diverse pharmacological effects, such as antioxidant, anti-inflammatory, antibacterial, kidney function improvement, immunity enhancement, blood sugar reduction, and anti-tumor properties9,10. R. laevigata is also used in treatments for spermatorrhea, premature ejaculation, urinary incontinence, diarrhea, chronic bronchitis, and chronic kidney disease11. Among over 123 ingredients that have been isolated from different parts of R. laevigata, triterpenoids were regarded as the most significant bioactive substances12, and were useful to combat Alzheimer’s disease (AD)13,14,15.
There are more than 200 species in Rosa16 with varying ploidy levels, ranging from 2n = 2x to 10x17,18. Despite the fact that at least eight published nuclear genome sequences are publicly available at present (https://www.plabipd.de/), some of them are at the draft genome level with relatively low quality, e.g., R. multiflora19. Although draft genomes could provide useful genomic information, the construction of a high-quality genome assembly is a fundamental step for dissecting genomic variations that contribute to exploring the genetic and molecular basis of desirable traits in plants. Thus, in this study, we assembled a high-quality chromosome-scale genome of R. laevigata using Illumina, PacBio, and Hi-C data. The final genome assembly spans a total length of 494.2 Mb, featuring a scaffold N50 size of 68.6 Mb. Additionally, 99.8% (493.2 Mb) of the genome sequence has been successfully anchored on seven pseudochromosomes. The assembled genome sequence consists of repeat elements, which make up 57.8% of the total. The most abundant class of repeat elements is the long terminal repeats (LTRs), which account for 42.1% of the genome. A total of 37,117 protein-coding genes were found using ab initio gene prediction, RNA-seq, and homologous protein evidence. Out of these, 34,074 genes were annotated with their respective functions. We have also detected 151 miRNAs, 1,115 tRNAs, 1,289 rRNAs and 627 snRNAs in the genome of R. laevigata. The high-quality chromosome-scale genome provides valuable resource for exploring key genes and molecular regulatory mechanisms involved in the high resistance to pests and diseases of modern roses on one hand, and in the biosynthesis of important compounds such as triterpenoids on the other, which will facilitate genome-guided breeding and improvement of R. laevigata itself and modern roses.
Methods
Sample collection, DNA extraction and sequencing
Fresh young leaves of R. laevigata, which had been propagated by cuttings collected from Changshou District of Chongqing Municipality (107°12′53.598″E, 30°10′42.169″N, 350 m), were sampled at the Flower Research Institute of the Yunnan Academy of Agricultural Sciences, Yunnan Province, China, for DNA extraction. At the same time, the tender roots, stems, leaves, and fruits of the same individual were used as source for RNA extraction. All samples were frozen using liquid nitrogen and transported to the laboratory to be stored in an ultra-low-temperature freezer at −80 °C, prior to the DNA and RNA extraction process.
Total high-molecular-weight genomic DNA was extracted from the leaves of R. laevigata using the Tiangen Extraction Kit (Tiangen Biotech, China) that was based on the cetyltrimethylammonium bromide (CTAB) method. The concentration of the DNA extract was ascertained by the Quant-iT PicoGreen assay (Invitrogen, Waltham, MA, USA). The quality and quantity of the DNA samples were assessed using an ultraviolet spectrophotometer at 260 nm and 280 nm wave lengths. The DNA was fragmented with a Covaris M220 Focused-ultrasonicator instrument. Genomic DNA sequencing was conducted at Novogene Co., Ltd., Beijing, China.
Three different genomic DNA sequence libraries were constructed in this study. For the first approach, the DNA PCR-free libraries with insert sizes of 350 bp were constructed by using the NEBNext Ultra DNA library Pre-Kit for Illumina short-reads sequencing. The resulting barcoded libraries were sequenced on an Illumina NovaSeq6000 platform to generate 150-bp paired-end reads. Quality control was carried out on all the obtained reads by trimming adaptors and low-quality reads using fastp v0.23.220. A total of 53 Gb filtered short reads were obtained and used in subsequent data processing steps.
The second approach used the single-molecule real-time (SMRT) PacBio libraries that were constructed by using the PacBio 15-kb protocol and sequenced by using a PacBio Sequel IIe platform. The raw data generated with the PacBio Sequel IIe system were processed through the SMRT Analysis software suite v5.1.0 (https://www.pacb.com/products-and-services/analytical-software/smrt-analysis/), whereas the consensus HiFi reads were produced by the CCS subprogram (https://github.com/PacificBiosciences/ccs) with default parameters, which then generated approximately 36 Gb filtered data.
The last approach would be via the Hi-C library that was generated by using the restriction endonuclease MboI. The MboI-digested chromatin was labeled with biotin-14-dATP, and in situ DNA ligation was performed. The DNA underwent extraction, purification, and shearing. After A-tailing, pull-down, and adapter ligation steps, the DNA library was subjected to sequencing on an Illumina NovaSeq6000 platform. The total filtered data generated from Hi-C library was approximately 99 Gb (Table 1).
RNA extraction and sequencing
Fresh roots, stems, leaves, and fruits of the same R. laevigata individual were used for transcriptome sequencing. Total RNA was extracted using the TRIzol reagent (Thermo Fisher Scientific, MA, USA) according to the manufacturer’s protocol. A 150-bp paired-end RNA-seq library was constructed and sequenced on an Illumina Novaseq6000 platform. After trimming the adapters and low-quality raw sequence reads using fastp, approximately 25 Gb clean data were obtained (Table 1).
Genome survey and assembly
Previous studies have shown that R. laevigata is a diploid plant21. Flow cytometry analysis determined the nuclear DNA content of R. laevigata to be 0.51 pg22, indicating that its genome size is approximately 498.78 Mb (1 pg = 978 Mb). In this study, by employing Jellyfish v2.3.023 and GenomeScope224 with 19-kmer to estimate the genome size, heterozygosity, and repeat content based on Illumina short reads, the genome of R. laevigata was estimated to be 510.2 Mb in size, with a heterozygosity of 0.6% and a repeat content of 53.9% (Fig. 2), which is consistent with the results of previous studies. For the genome de novo assembly of R. laevigata, the bam2fastq v3.0.0 (https://github.com/PacificBiosciences/pbtk#bam2fastx) pipeline was first used to convert the raw data into the fastq format. A primary assembly was then constructed by using hifiasm v0.16.125 with default parameters, while the redundant sequences were removed using purge_dups v1.2.526 with default parameters. The draft genome assembly comprised of 56 contigs, which had a combined length of 494.2 Mb, an N50 size of 63.1 Mb, and a GC content of 38.8% (Table 2).
K-mer analysis of the R. laevigata genome based on the 19-mer frequency distribution.
After removing adapter and low-quality sequences, we employed Juicer v1.627 to align the filtered Hi-C data to the primary assembly and generate a deduplicated list of Hi-C reads with default parameters. By using 3D-DNA v20100828, the primary contigs were anchored on the pseudochromosomes, while the heatmap for Hi-C interaction was generated using the 3D-DNA visualize module. The heatmap was further visualized, and manual curation was conducted with Juicebox v2.17.0029. The seven pseudochromosomes with lengths ranging from 49.9 Mb to 88.5 Mb were identified via distinct interaction signals in the Hi-C interaction heatmap (Fig. 3). Among them, two pseudochromosomes were gapless (Supplementary Table 1). The final genome assembly of R. laevigata was 494.2 Mb in size, with a scaffold N50 of 68.6 Mb (Table 2, Fig. 4).
Hi-C contact map at chromosome-scale for the genome assembly of R. laevigata.
Overview of genome features of R. laevigata. Syntenic blocks among inter-chromosome were analysed with MCScanX74. Each layer of the genome map represents the level of (a) gene density, (b) GC content, (c) transposon element density, (d) LTR/Copia density, (e) LTR/Gypsy density, (f) tandem repeat density.
Repeat annotation
Tandem repeats in the final genome assembly were identified by using TRF v4.0930 based on default parameters. By selecting the masked genome sequence as the target genome, transposon element (TE) identification was conducted using a combination approach via de novo and homology. The miniature inverted repeat transposable elements (MITEs) and long terminal repeat (LTR) elements were identified by de novo methods with MITE-Hunter (11–2011)31 and LTR_retriever v2.8.732. LTR_retriever incorporated LTRs predicted from LTRHarvest33 and LTR_FINDER v1.0.734. A species-specific repeat sequence library was also constructed using by RepeatModeler v2.0.335, while homology-based predictions were performed using by RepeatMasker v4.1.4 (http://repeatmasker.org/) and referring to the Repbase v2018 (http://www.girinst.org/server/RepBase/index.php) database. Annotation was carried out for all the repeat sequences with RepeatMasker based on a combined reference library that combined the MITEs, LTRs, species-specific library and homology library. The LTR Assembly Index (LAI) that is embedded in LTR_retriever was used to assess the assembly quality of the genome. A total of 285.6 Mb of repetitive elements were identified, which constituted 57.8% of the genome of R. laevigata. Among these repeats, the most abundant repeating element was the LTRs (42.14%). Within LTRs, Copia and Gypsy were the two most dominant classes in the genome, accounting for 16.9% and 24.7%, respectively (Fig. 5, Table 3).
Repeat landscape plots illustrating the transposon element (TE) accumulation history of R. laevigata genome, based on Kimura distance-based copy divergence analysis. The y-axis represents the percentage of the genome represented by each TE type, while the X-axis represents the sequence divergence at CpG adjusted Kimura substitution level. The legend on the top right corner indicates the colour code used for each type of transposon.
Gene prediction and annotation
Gene annotation was carried out by using the repeat masked genome. The protein-coding genes were annotated by incorporating transcriptional evidence, homology-based, and ab initio methods. For transcriptional evidence, fastp was used to trim the data separately, based on different tissues, and the clean data were aligned to the assembled genome of R. laevigata by using HISAT2 v2.2.136. The transcripts were assembled by using Stringtie v2.2.137 based on default parameters, while the transcripts from all samples were merged and subjected to protein-coding sequence prediction and quality filtering via TransDecoder (https://github.com/TransDecoder/TransDecoder/wiki), which is available in PASA v2.4.138. Only complete transcripts were retained for subsequent analysis. The protein sequences from Arabidopsis thaliana39, Crataegus pinnatifida var. major40, Eriobotrya japonica41, Fragaria vesca42, Malus domestica43, Potentilla anserina44, Prunus armeniaca45, Pyrus communis46, Rosa chinensis47, Rosa rugosa48, and Rubus idaeus49 were mapped to the assembled genome using by GeMoMa v1.950 to identify high-quality protein structures. Ab initio gene prediction was carried out by using Augustus v3.3.351, GeneMark-ESSuite v4.5752, and SNAP v2006-07-2853. They were all trained by high-quality transcripts from the previous step. Ab initio gene identification was performed according to the manuals. All predicted gene structures were integrated into a nonredundant gene set by using EVdenceModeler (EVM)38 v1.1.1. The weight values for high-quality RNA-seq transcripts, homologous proteins, and ab initio prediction were set to 10, 7, and 3 (Table 4). The EVM-predicted genes were further corrected by using PASA v2.4.138 to identify the untranslated and alternative splicing regions. In total, 37,117 protein-coding genes were predicted and annotated, with an average gene length of 3,047.31 bp (Table 5).
Functional annotation of the protein-coding genes was performed based on sequence similarity and the identification of conserved domains. For sequence similarity, the protein-coding genes were matched against the Universal Protein Knowledgebase (UniProt) database54, the Kyoto Encyclopedia of Genes and Genomes (KEGG) database55, and the eggNOG56 database using diamond v2.0.1157 with a specified E-value cut-off of 1e-5. For the identification of conserved domains, InterProScan v5.5258 was employed to detect and classify domains and motifs by referring to the Pfam59, SMART60, PANTHER61, PRINTS62, and ProDom63 databases. With both approaches, a total of 34,074 (91.8%) protein-coding genes were functionally annotated (Table 6).
Noncoding RNA was annotated by using RNAmmer v1.264 for rRNA, tRNAscan-SE65 v2.0.9 for tRNA and the cmscan module in Infernal v1.1.266 for miRNA, snRNA. All predictions were performed with the default parameters, with the exception of tRNAs, which were filtered with a score >40. Finally, a total of 3,182 noncoding RNAs were predicted (Table 7), including 1,115 transfer RNAs (tRNAs), 1,289 ribosomal RNAs (rRNAs), 151 micro-RNAs (miRNAs), and 627 small nuclear RNAs (snRNAs).
Data Records
The Illumina short reads, PacBio long-reads, Hi-C sequencing data, and RNA-seq data have been deposited in the National Center for Biotechnology Information Sequence Read Archive (SRA) database with the accession number SRP51180767. The chromosome-scale genome assembly has been deposited in DDBJ/ENA/GenBank under the accession number JBEFKI00000000068. The genome annotation files were submitted to Figshare69.
Technical Validation
To assess the accuracy of the assembly, BWA70 v0.7.17 and Minimap2 v2.2471 were used to remapped the Illumina short reads and PacBio long reads into the final assembled genome. A 99.8% and 99.9% mapping rates of short and long reads was achieved, respectively. The Benchmarking Universal Single-Copy Orthologs (BUSCO, v5.4.772) was used to further evaluate the genome completeness by performing searches against the embryophyte_odb10 database. The BUSCO analysis showed that the final genome sequence contained 99.0% (1,598) complete BUSCOs (including 95.4% (1,540) single-copy BUSCOs, 3.6% (58) duplicated BUSCOs), 0.6% (9) fragmented BUSCOs and 0.4% (7) missing BUSCOs (Table 8). The LTR Assembly Index (LAI) was used to assess the quality of the R. laevigata genome assembly. An LAI value of 25.21 was obtained, indicating that the quality of R laevigata genome assembly qualified the level as a reference genome (Table 9). Merqury v1.373 was used to assess the consensus quality value (QV) of the R. laevigata genome assembly. The QVs were 64.8 and 55.3 estimated with HiFi and Illumina k-mers, respectively (Supplementary Figure 1). The above evaluation results indicate that the R. laevigata genome assembly has high accuracy and integrity.
Furthermore, BUSCO was used to evaluate the completeness of the R. laevigata genome annotation by performing searches against the embryophyte_odb10 database. The BUSCO analysis showed that 95.1% of conserved orthologous genes were complete in the predicted protein coding genes, comprising 90.8% single-copy and 4.3% duplicated genes (Table 10).
Code availability
No in-house code or scripts were used in this study. Commands and pipelines used for data processing were executed using their corresponding default parameters.
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Acknowledgements
The authors thank Guodong Li and Chunlin Gao from Yunnan University of Chinese Medicine and Ticao Zhang from Kunming Institute of Botany, Chinese Academy of Sciences for their technical assistance and valuable discussions. This work was financially supported by the Technology Talents and Innovation Team Project of Yunnan Province (No. 202305AS350002 to Jian) and the National Natural Science Foundation of China (No. 31760048 to Zhang).
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Jian H.Y., Yan H.J., Qiu X.Q. and Zhang H. conceived the research and collected materials. Wang Y. assembled the sequences and analyzed the data. Wang Y. and Zhang Y.H. prepare the manuscript. Zhang Y.H. and Jian H.Y. revised the manuscript. All authors read, edited and approved the final manuscript.
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Wang, Y., Yan, H., Qiu, X. et al. A high-quality chromosome-scale genome assembly of the Cherokee rose (Rosa laevigata). Sci Data 12, 132 (2025). https://doi.org/10.1038/s41597-025-04461-7
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DOI: https://doi.org/10.1038/s41597-025-04461-7
