Next Article in Journal
A Role for the Interactions between Polδ and PCNA Revealed by Analysis of pol3-01 Yeast Mutants
Previous Article in Journal
The Complete Mitochondrial Genome of Torix tukubana (Annelida: Hirudinea: Glossiphoniidae)
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Genes
Volume 14
Issue 2
10.3390/genes14020389
genes-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Chromosome-Level Assembly of Flowering Cherry (Prunus campanulata) Provides Insight into Anthocyanin Accumulation

by
Dongyue Jiang
1,
Xiangkong Li
2,
Yingang Li
1,
Shiliang Zhou
3,
Qi Zhou
1,
Xinhong Liu
4,* and
Xin Shen
1,*
1
Institute of Tree Breeding, Zhejiang Academy of Forestry, 399 Liuhe Road, Hangzhou 310023, China
2
Novogene Bioinformatics Institute, Jiuxianqiao North Road, Beijing 100015, China
3
State Key Laboratory of Systematic & Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
4
Zhejiang Forestry Technology Popularization Station, 226 Kaixuan Road, Hangzhou 310019, China
*
Authors to whom correspondence should be addressed.
Genes 2023, 14(2), 389; https://doi.org/10.3390/genes14020389
Submission received: 5 January 2023 / Revised: 28 January 2023 / Accepted: 30 January 2023 / Published: 2 February 2023
(This article belongs to the Section Plant Genetics and Genomics)
Browse Figures
Review Reports Versions Notes

Abstract

:
The flowering cherries (genus Prunus, subgenus Cerasus) are popular ornamental trees in China, Japan, Korea, and elsewhere. Prunus campanulata Maxim. is an important species of flowering cherry native to Southern China, which is also distributed in Taiwan, the Ryukyu Islands of Japan, and Vietnam. It produces bell-shaped flowers with colors ranging from bright pink to crimson during the Chinese Spring Festival from January to March each year. We selected the P. campanulata cultivar “Lianmeiren”, with only 0.54% of heterozygosity, as the focus of this study, and generated a high-quality chromosome-scale genome assembly of P. campanulata by combining Pacific Biosciences (PacBio) single-molecule sequencing, 10× Genomics sequencing, and high-throughput chromosome conformation capture (Hi-C) technology. We first assembled a 300.48 Mb genome assembly with a contig N50 length of 2.02 Mb. In total, 28,319 protein-coding genes were predicted from the genome, 95.8% of which were functionally annotated. Phylogenetic analyses indicated that P. campanulata diverged from a common ancestor of cherry approximately 15.1 million years ago. Comparative genomic analyses showed that the expanded gene families were significantly involved in ribosome biogenesis, diterpenoid biosynthesis, flavonoid biosynthesis, and circadian rhythm. Furthermore, we identified 171 MYB genes from the P. campanulata genome. Based on the RNA-seq of five organs at three flowering stages, expression analyses revealed that the majority of the MYB genes exhibited tissue-specific expression patterns, and some genes were identified as being associated with anthocyanin accumulation. This reference sequence is an important resource for further studies of floral morphology and phenology, and comparative genomics of the subgenera Cerasus and Prunus.

1. Introduction

Flowering cherries are popular ornamental trees in China, Japan, Korea, and elsewhere, belonging to the subgenus Cerasus of the genus Prunus in the Rosaceae family [1,2]. It is well known that Japan is the cradle of flowering cherry cultivars based on nine native species [3]; however, most of the wild flowering cherry plants are widely scattered over China, with 38 species and eight varieties in total [4]. In addition, the vast majority of these have not been fully exploited or developed.
P. campanulata Maxim. is an important species of flowering cherry native to southern China, which is also distributed in Taiwan, the Ryukyu Islands of Japan, and Vietnam. Compared with the white or light pink bulbs of cherry commonly seen in Japan, it produces bell-shaped flowers with colors ranging from bright pink to crimson [4]. P. campanulata is a typical early flowering species of flowering cherry, which often blooms during the Chinese Spring Festival from January to February each year, with a flowering period lasting up to 50 days [5]. It is the progenitor of many early flowering cherry cultivars in Japan, e.g., P. × kanzakura “Kawazu-zakura”, P. × kanzakura “Rubescens”, and P. × introrsa “Introrsa” [6,7]. In addition, P. campanulata has stable and robust resistance to cherry leaf spot [6], which is the most problematic fungal disease of the subgenus Cerasus by Blumeriella jaapii [8]. These extraordinary characteristics make P. campanulata suitable as an ornamental woody plant.
A high-quality genome sequence is essential for genome evolution and comparison [9]. Because of the gametophytic self-incompatibility of flowering Prunus species [10], flowering cherries generally have highly heterozygous genomes. To date, whole-genome sequences of four Cerasus species have been published, including P. avium [11], P. yedoensis [12], Cerasus serrulata [13], and P. fruticosa [14]. However, their genomes are complicated because of high heterozygosity or ploidy level, which has hindered their utility for genetic and breeding studies. In the current study, to obtain a reference-quality genome sequence, the P. campanulata cultivar “Lianmeiren”, with only 0.54% heterozygosity, was used; “Lianmeiren” is also an ornamental plant with magenta-colored double flowers (Figure 1). We generated a reference genome for P. campanulata using a combination of Pacific Biosciences single-molecule real-time (PacBio SMRT), 10× Genomics, and high-throughput chromosome conformation capture (Hi-C) technologies. Furthermore, we conducted a comparative analysis between P. campanulata and other Prunus species to understand the genome structure and evolution of P. campanulata.

2. Materials and Methods

2.1. Plant Sample

P. campanulata “Lianmeiren” individuals were cultivated in Shaowu City, Fujian Province, China (27°9’15″ N, 117°21’23″ E, altitude: 445 m). A plant with a height of 3 m and a diameter at breast height of 10 cm was used for sampling. Fresh young leaves, stems, and roots were collected in April 2017. Buds were collected in November 2017. Flowers were collected at the initial flowering stage, full flowering stage, and late flowering stage in 2018. All plant samples were stored at −80 °C.

2.2. Genome Size and Heterozygosity Analysis

P. campanulata genome size and heterozygosity were estimated based on k-mer analysis. A paired-end library with a short insertion size (350 bp) was constructed and used for sequencing on an Illumina HiSeq2500 platform. We estimated the genome size and heterozygosity of P. campanulata using approximately 21.8 Gb of the quality-filtered reads of Illumina data with Jellyfish v2.0 (k = 17) [15] based on the k-mer method, using the following formula: genome size = total k-mer number/average k-mer depth [16]. The distribution of distinct k-mers (k = 17) showed one sharp main peak and another very small peak at a depth of 53 and 26, respectively, suggesting low heterozygosity of the P. campanulata genome. The final analysis estimated the genome size of P. campanulata to be approximately 327.89 Mb, with approximately 0.54% and 48.67% heterozygosity and repeats, respectively (Figure S1). And the GC content was 40.18% (Figure S2).

2.3. Genome Sequencing

High-quality genomic DNA was isolated from the frozen leaves of P. campanulata using the DNAsecure Plant Kit (Tiangen, Beijing, China). A short-insert genomic library (300–350 bp) was prepared using the Illumina Library Preparation Kit (Illumina Inc., San Diego, CA, USA) according to the manufacturer’s instructions. The library was sequenced on the Illumina HiSeqXTen platform at Novo (Novogene Bioinformatics Institute, Tianjing, China). At least 10 μg of DNA was fragmented by Covaris g-TUBETM (Covaris Inc., Woburn, MA, USA) for a 20 kb insert size library construction. The single-molecule real-time bell (SMRTbell) sequencing library was prepared with the SMRTbell® Express Template Prep kit (PacBio, Menlo Park, CA, USA), involving DNA concentration, damage repair, end repair, ligation of hairpin adapters, and template purification. The Sequel binding kit 3.0 was applied to bind sequencing polymerase to the SMRTbell library. Then, the single-molecular sequencing was performed on the Sequel (PacBio) sequencing platform using a Sequel Sequencing Kit v3.0 and SMRT Cell 1M v3 Tray (PacBio, Menlo Park, CA, USA). To build the 10× Genomics library, approximately 1 ng input DNA and the functionalized gel beads with unique barcoded primers were combined to form a “gel bead in emulsion” using a chromium automated microfluidic system (10× Genomics, San Francisco, CA, USA). The gel beads in the emulsion were amplified by PCR and then purified for Illumina sequencing on the Illumina HiSeqXTen platform. A Hi-C library was constructed using young leaves. First, young leaves were cross-linked with a 2% formaldehyde solution for 20 mins. Then, a restriction enzyme (Hind III) was applied to digest the samples at 37 °C. The DNA ends were marked with biotin-14-dCTP, and chromatin DNA was cyclized by ligation enzyme. DNA was purified by phenol-chloroform extraction. The library was sequenced on the Illumina HiSeqXTen platform.

2.4. Genome Assembly and Assessments

Genome assembly was conducted in a progressive manner. We first carried out a self-correction of errors of PacBio subreads using FALCON assembler v1.8.7 (parameters: length_cutoff_pr = 5000, max_diff = 120, max_cov = 130.) [17]. Then, the overlaps identified in all pairs of error-corrected reads were used to produce a directed string graph employing the “Myers” algorithm. Contigs were constructed based on the paths from the string graph. To eliminate the error rate of the preceding assembly, we used PacBio long-reads to polish assembled sequences using the consensus-calling algorithm Arrow v2.2.2 with default parameters [18], and then the corrected sequences were further polished using Pilon v1.20 [19], which mapped the Illumina reads to sequences with BWA v0.7.17 using default settings [20]. To order and orient these contigs into longer scaffolds, fragScaff [21] with default settings was used for 10× Genomics scaffolds extension as follows: (1) linked-reads were aligned to the consensus sequences of the PacBio assembly to form Super-Scaffolds using BOWTIE v2.2 with default parameters [22] and (2) qualitatively, the consensus sequences that were physically close to each other were supported by more linked-reads. By screening for linked-reads support, we filtered the consensus sequences without the linked-reads support and reserved the consensus sequences with the linked-reads support for the subsequent scaffolding. The Hi-C reads were mapped against the PacBio reads assembly using BWA v0.7.17 with the ‘-n 0′ option, which achieved mapping reads without any mismatches. Only read pairs aligned to the unique position of assembled sequences were preserved for Hi-C scaffolding. The strength of Hi-C interactions of contigs was quantified by standardizing the digestion sites of DpnII of read pairs on the genome sketch. LACHESIS v2e27abb [23] (parameters: CLUSTER N = 8, CLUSTER MIN RE SITES = 1157, CLUSTER MAX LINK DENSITY = 5, CLUSTER NONINFORMATIVE RATIO = 0) was used to cluster contigs into groups based on the strength of interactions, and then arranged and orientated in a linear order.
To verify the completeness of the assembled genome, the BUSCO database v3.0.2 [24] was used for the assessment, based on a benchmark of 1440 conserved plant genes. We also used CEGMA v2.5 to assess the assembly with 248 core eukaryotic genes [25].

2.5. Genome Annotation

Repetitive sequences, including tandem repeats and interspersed repeats, were identified in the genome assembly at both the DNA and protein levels. LTR_FINDER v1.06 [26], RepeatScout v1.05 [27], and RepeatModeler v1.0.11 [28] with default parameters were used to construct a de novo repeat sequences library. The de novo repeat sequences library was then mapped against Repbase [29] using Repeatmasker v4.0.7 withdefault parameters [30]. The mapped results from the above software were integrated based on the Uclust algorithm with the rule of 80-80-80 [31]. At the protein level, RepeatProteinMask v4.0.7 [32] with default parameters was used to identify the transposable element (TE) related proteins through mapping against the TE protein database from Repbase. Combing the results both at the DNA and protein level, the final TEs were obtained by removing redundant sequences.
The protein-coding genes were identified using de novo predictions-based, homology-based, and transcriptome-based approaches. For the de novo prediction, Augustus v2.5.5 [33], Genscan v3.1 [34], GlimmerHMM v3.0.1 [35], Geneid v1.4 [36], and SNAP [37] with default parameters were used to predict coding genes in the repeat-masked P. campanulata genome. For the homology-based prediction, the P. campanulata genome was mapped against the published sequences of Arabidopsis thaliana [38], P. persica [39], P. mume [40], P. avium, Malus domestica [41], Pyrus bretschneideri [42], and Fragaria vesca [43] using TblastN with an E-value cutoff of 1E-5 [44]. To improve the precision of spliced alignments, GeneWise v2.2.0 [45] with default parameters was used to filter all initially aligned coding sequences. For transcriptome-based prediction, a mixed library of five tissues (leaf, flower, bud, stem, and root) was constructed. The libraries were sequenced on an Illumina HiSeqXTen platform. A total of 32 Gb clean data were generated and de novo assembled with Trinity v2.11.0 using default settings (Grabherr et al., 2011), and then mapped against the genome assembly using TopHat v2.0.8 (parameters: -p 6 –max-intron-length 500,000-m2) [46]. Cufflinks v2.1.1 with default parameters [47] were used to assemble transcripts into gene models. The final consensus and non-redundant gene set were achieved using Evidence Modeler (EVM) v1.1.1 [48] with default parameters, which combined the genes predicted by the above three approaches. Moreover, PASA v2.4.1 under default settings [48] was used to correct the annotation results of EVM by generating untranslated regions. To annotate gene function, BlastP was used to blast the protein-coding gene sequences against Swiss-Prot (http://www.uniprot.org/ (accessed on 3 July 2019)) and TrEMBL [49] (E-value of 1 × 10−5). Protein domain annotation was performed using InterProScan v5.2 [50] and Hmmer v3.1 [51] with default parameters to search the InterPro (v66.0) and Pfam (v27.0) databases, respectively. Gene ontology (GO) terms [52] were assigned from the corresponding InterPro or Pfam results. The gene pathways were extracted by mapping genes against the Kyoto Encyclopedia of Genes and Genomes (KEGG) database [53].
The ribosomal RNA and micro-RNA genes in the P. campanulata genome were identified by searching the Rfam database (release 13.0) using BlastN (E-value of 1 × 10−10). The transfer RNA and small nuclear RNA were predicted by mapping against the Rfam database using tRNAscan-SE [54] and INFERNAL [55] with default settings, respectively.

2.6. Synteny Analysis

We applied McscanX v0.8 under default settings [56] to analyze the syntenic blocks and gene pairs between P. campanulata and P. avium, and P. persica genomes. MUMmer v3.23 software with default parameters [57] was used for detecting the genomic collinearity between P. campanulata and P. × kanzakura “Kawazu-zakura” genomes [58].

2.7. Gene Family Analyses and Evolution

To identify gene families in the P. campanulata genome, we used OrthoMCL v2.0.9 [59] to compare and cluster genes using all-to-all BlastP analysis (E-value of 1 × 10−5) among the protein sequences of 11 genomes, including P. campanulata, P. persica, P. mume, P. avium, P. bretschneideri, M. domestica, F. vesca, Potentilla micrantha [60], Rosa chinensis [61], Rubus occidentalis [62], and A. thaliana.
For detecting whole-genome duplication (WGD) events, first, collinear segments within P. campanulata and between P. campanulata and genomes of other related species (P. avium, P. mume, and P. persica) were identified using MCScanX v0.8 with default parameters [56]. Then, four-fold synonymous third-codon transversion (4DTv) values were calculated using the codeml tool in the PAML v4.8 with default parameters [63] according to the collinear segments. In addition, we calculated the number of synonymous substitutions per site (Ks) and non-synonymous substitutions per site (Ka) using protein-coding sequences. Then, the protein and nucleotide sequences were aligned using MUSCLE v3.8.31 with default settings [64], and Gblocks under default parameters [65] were used to exclude poorly aligned positions and divergent regions from the alignment. The branch-site likelihood ratio test was performed using codeml in the PAML v4.8 using default settings, and the ratio of Ka/Ks was calculated to identify positively selected genes (Ka/Ks > 1) in the P. campanulata genome. Based on the likelihood model implemented in CAFE v4.0 [66] with default parameters, expanded and contracted gene families were revealed in the P. campanulata genome.

2.8. Phylogenetic Analyses

The maximum likelihood (ML) analysis was performed using RAxML v8.2.12 [67], assuming the GTRCAT substitution model with 1000 bootstrap replicates based on sequence alignments using MUSCLE v3.8.31 with default parameters. Divergence times between the species were estimated using the Bayesian Markov Chain Monte Carlo algorithm implemented in PAML v4.8 with default parameters. In order to calibrate the phylogeny, fossil records of A. thaliana and P. persica from the TimeTree database (http://www.timetree.org (accessed on 10 September 2020)) were used for prior age calibration and secondary age calibration, respectively.

2.9. Identification of MYB Family Genes

All candidate protein sequences from the genome of P. campanulata were scanned by Hmmer v3.1 with default parameters employing the hidden Markov model profiles of the Myeloblastosis (MYB) domain (PF00249) downloaded from the Pfam (v30.0) databases. A database of transcription factors, constructed for the MYB gene family from A. thaliana downloaded from the Pfam (v30.0) database, was used as a query to search against the protein datasets of P. campanulata using BlastP. Subsequently, the protein datasets were analyzed with Swiss-Prot (http://www.uniprot.org/, accessed on 20 December 2020), using the method of auto-blasting two sequence sets to verify the domain composition. Based on the above methods, the preliminarily identified candidate sequences were determined by merging all the datasets and removing repeating sequences. The resulting candidate sequences were then confirmed by the Pfam (v30.0) and NCBI Conserved Domain Database (CDD, https://www.ncbi.nlm.nih.gov/cdd/ (accessed on 20 December 2020)). The sequences with MYB functional domains were retained for the following analysis.

2.10. Chromosome Distribution and Phylogenetic Analysis

The positions of MYB genes were validated by the General Feature Format (GFF) files of the P. campanulata genome. Additionally, the MYB genes from P. campanulata were located on the corresponding chromosomes and illustrated by the gene distribution and gene structure tools in TBtools software v1.09 [68]. MYB domain sequences from A. thaliana and P. campanulata were aligned with MAFFT v7.408 [69] under default parameters and adjusted manually with Se-Al v2.0 a11 under default parameters [70] if necessary. Phylogenetic trees were constructed in the MEGA X program [71] using the maximum likelihood (ML) method with 1000 non-parametric bootstrap replicates, LG substitution model, γ distributed (G) rates model among sites, and with other parameters under the default settings.

2.11. Transcriptomic Analysis

To analyze the expression levels of MYB genes, various tissues, including buds, mature leaves, stems, roots, and flowers at initial, full, and late flowering stages, were collected in three replicates to sequence using the Illumina HiseqXTen platform. The quality of sequencing data was controlled by Fastqc v0.11.9 with default parameters [72] and aligned to the reference genome from P. campanulata using Bowtie v2.2 with default parameters and TopHat v2.0.12 with parameters (‘mismatch = 2′). HTSeq v0.6.1 with default parameter [73] was used to count the reads numbers mapped to each gene. Then the values of fragments per kilobase of transcript sequence per million mapped reads (FPKM) of each gene were calculated based on the length of the gene and reads count mapped to the gene. Subsequently, differential expression analyses of various tissues and different flowering stages were performed using the DESeq R package v1.18.0 with default parameter [74]. Finally, heat maps of MYB gene expression were generated by using a plugin within TBtools software v1.09.

3. Results

3.1. Genome Sequencing and Assembly

P. campanulata (2n = 2x = 16) was used for whole-genome sequencing by a combination of Illumina short-read sequencing, PacBio SMRT sequencing, 10× Genomics sequencing, and Hi-C sequencing technologies. After adapter removal and low-quality reads filtering, a total of 53.47 Gb (163×) of clean reads from the HiSeqXTen platform, 42.73 Gb (130×) of subreads from the PacBio Sequel platform, 39.08 Gb (119×) of clean reads of 10× Genomics sequencing, and 42.20 Gb (130×) of clean Hi-C reads were generated (Table S1).
By correcting the PacBio long reads, polishing assembled sequences, and extending 10× Genomics scaffolds, a genome assembly was generated, of which the total length was 300.48 Mb, comprising 492 scaffolds with a contig N50 size of 2.02 Mb, and the largest contig size was 11.75 Mb (Table 1). To anchor the scaffolds to chromosomes, LACHESIS software v2e27abb was performed to cluster 428 scaffolds into eight groups. As a result, the combined length of Hi-C contigs was 300.08 Mb, accounting for 99.87% of the total length of the assembled genome, and the length of the scaffold N50 was improved to 32.53 Mb, with the longest scaffold being 51.49 Mb (Table S2). The final reference assembly comprised eight chromosome-scale pseudomolecules, corresponding to the haploid chromosome number of P. campanulata (Figure 2, Table S3).

3.2. Assessment of Genome Quality

To evaluate the correctness of the P. campanulata genome assembly, we mapped short reads from the Illumina HiSeq sequencing data to the genome assembly using BWA v0.7.17. The results showed that the mapping rate was 97.41%, and the genome coverage was 99.50%. Furthermore, through single nucleotide polymorphism calling using Samtools v1.10 [75], the proportion of homologous single nucleotide polymorphisms was 0.0002%. To verify the completeness of the assembled genome, the BUSCO database v3.0.2 was used for the assessment, based on a benchmark of 1440 conserved plant genes. The analysis revealed that 96.6% of the conserved genes had complete gene coverage (including 92.8% single genes and 3.8% duplicated genes), 0.8% were fragmented, and only 2.6% were missing (Table 1). We also used CEGMA v2.5 to assess the P. campanulata genome with 248 core eukaryotic genes, of which 96.77% were detected, including 94.76% complete genes (Table S4). In summary, the assessment of the correctness and completeness of the genome assembly indicated its high quality.

3.3. Genome Annotation

Repetitive sequences, including tandem repeats and interspersed repeats, were identified in the genome assembly at both the DNA and protein levels. Repetitive sequence length was 160,006,931 bp in total, accounting for 53.32% of the genome assembly. The most abundant repeat types were retrotransposons/class I elements, constituting 33.49% of the genome, of which long terminal repeat retrotransposons represented 31.15%. DNA transposons/class II elements and unknown repeat sequences represented 16.18% and 5.41%, respectively, of the whole genome (Figure 3 and Figure S3, Table 2).
We identified 28,319 protein-coding genes in the P. campanulata genome, with an average transcript length of 3135 bp, an average CDS length of 1226 bp, and an exon number of 4.75 per gene (Table 3). In addition, 26,352 protein-coding genes were annotated with ≥1 database, accounting for 93.1% of the annotated protein-coding genes (Table S5). For the identification of non-coding RNA (ncRNA), a total of 2230 ncRNAs were predicted, including 562 microRNA, 721 tRNA, 330 rRNA, and 617 small nuclear RNA, accounting for approximately 0.10% of the P. campanulata genome (Table S6).

3.4. Gene Family Analyses and Evolution

To understand orthologous relationships of genes between P. campanulata and ten other related species (P. persica, P. mume, P. avium, P. bretschneideri, M. domestica, F. vesca, P. micrantha, R. chinensis, R. occidentalis, and A. thaliana), after filtering gene sets, 286,011 genes were clustered into 27,921 orthologous groups (Figure 4B, Table S7). By comparing the gene families among P. campanulata and three closely related Prunus species (P. persica, P. mume, and P. avium), there were 237 unique gene families specific to P. campanulata. The unique gene families were enriched in 37 GO categories and 12 KEGG pathways (p-value < 0.05) (Figure 4A). GO enrichment results mainly involved 3-methyl-2-oxobutanoate hydroxymethyltransferase activity, the tetrapyrrole biosynthetic process, and the single-organism cellular process (q-value < 0.05) (Figure 4C), and KEGG analyses revealed the gene families were enriched in ABC transporters, pantothenate and CoA biosynthesis, plant circadian rhythm, and flavonoid biosynthesis (q-value < 0.05) (Figure 4D). We also analyzed the collinearity between the P. campanulata and P. avium, and P. campanulata and P.persica. The results showed that there were a total of 172 and 120 syntenic blocks, which included 15,329 genes of P. campanulata and 15,014 genes of P. avium genomes, and 18,546 genes of P. campanulata and 18,000 genes of P. persica genomes, covering 54.18% and 35.51%, and 65.6% and 60.8% of their identified genes, respectively (Figure 3, Figure S4, Table S8). To understand its contribution to early flowering cherry cultivars as a parent, we compared sequence synteny between the P. campanulata and C. campanulata haplotype, and the P. campanulata and C. spachiana haplotype, which were from P. × kanzakura “Kawazu-zakura” genome assembly [58]. A total of 227.4 Mb (76.01%) and 159.9 Mb (53.46%) of P. campanulata genomic sequences were syntenic with 223.5 Mb (85.24%) and 165 Mb (64.02%) of the C. campanulata haplotype (Table S9) and the C. spachiana haplotype (Table S10), respectively (Figure S5).
To clarify the phylogenetic position of P. campanulate among Rosaceae, 1090 single-copy orthologs of P. campanulate were used to construct a phylogenetic tree with nine species belonging to Rosaceae and A. thaliana as the outgroup. The ML tree revealed that P. campanulate formed a monophyletic clade with P. avium and was closely related to P. mume and P. persica (Figure 5A). Based on the phylogenetic relationship and fossil calibration, the node of our phylogenetic tree showed that P. campanulate and P. avium diverged approximately 15.1 million years ago. As representative species of Prunus, the clade with the four species diverged from the clade of M. domestica and P. bretschneideri approximately 64.1 million years ago. The divergent time estimation implied that P. campanulate was the most recently diverged species in Prunus (Figure 5A).
To determine the whole-genome duplication events in the P. campanulata genome, the 4DTv values among P. campanulata, P. avium, P. mume, and P. persica were estimated using their orthologous gene pairs. In the map, the peaks were grouped in 4DTv values of 0.02 and 0.55. One peak (4DTv approximately 0.02) indicated divergence events, including P. campanulata vs. P. avium, P. campanulata vs. P. persica, and P. campanulata vs. P. mume. Another peak (4DTv approximately 0.55) involving the four species suggested that a whole-genome or large-fragment duplication had occurred in their common ancestor (Figure 5B).
In order to comprehend the adaptive evolution of P. campanulata, we detected the genes under positive selection. Treating P. campanulata as the foreground branch, and P. avium, P. persica, and P. mume as background branches, 775 genes were identified as candidate genes under positive selection (p-value < 0.05) by an ML-based branch length test. GO and KEGG analyses showed that positive selection was especially detected in organic cyclic compound metabolism (q-value < 0.05) (Table S11).
The protein-coding genes of 11 species genomes in the phylogenetic analysis were used for surveying expanded and contracted gene families during the evolution of P. campanulata. Based on the likelihood model implemented in CAFE with default parameters, 43 expanded gene families and 241 contracted gene families in total were revealed significantly (p-value < 0.05) in the P. campanulata genome, after divergence from P. avium. The GO and KEGG pathway analyses showed that the expanded gene families were significantly involved in ribosome biogenesis, diterpenoid biosynthesis, flavonoid biosynthesis, and circadian rhythm (q-value < 0.05) (Table S12), and the contracted gene families were referred to pathogen/stress response (e.g., cyanoamino acid metabolism and plant–pathogen interaction), and phenylpropanoid biosynthesis (q-value < 0.05) (Table S13).

3.5. Identification and Phylogenetic Analysis of MYB Family Genes

Based on genome-wide analysis of MYB genes in the P. campanulata genome and a BlastP search utilizing the Pfam database and Swiss-Prot database as queries, 171 PcMYB proteins with MYB DNA binding domains were identified. The resulting protein number is in the same range as those reported from 168 in A. thaliana, 163 in P. persica and 133 in P. mume in the Plant Transcription Factor Database (http://planttfdb.gao-lab.org/ (accessed on 12 January 2021)). The identified PcMYB genes were named PcMYB1 ~ PcMYB168 following the nomenclature of locations on the corresponding chromosomes (Table S14). Notably, the proteins from four genes of the PcMYB gene family were closely related to MYB10 in P. persica [76] and P. mume [77], according to a phylogenetic tree constructed by using protein sequences, and they were named PcMYB10a, PcMYB10b, PcMYB10c, and PcMYB10d, respectively. The PcMYB genes were mapped to all eight chromosomes, but they were unevenly distributed. Chr1 contained the largest number of genes with 33 PcMYB genes, while Chr8 held the smallest number with 11 genes (Figure 6).
In order to explore the putative function of the predicted P. campanulata MYBs, the PcMYB proteins were assigned to the A. thaliana MYBs with known function and the most functional MYB gene family. The MYB proteins from P. campanulata (171 members) and A. thaliana (168 members) were used to construct a phylogenetic tree with a maximum likelihood method. According to the evolutionary relationship, the MYB genes’ functions appeared highly conserved across their clades, and closely related MYBs were recognized as the same or similar target genes, possessing cooperative, overlapping, or redundant functions. The results indicated MYB proteins were clustered into three separate subfamilies with branch support ranging from 17% to 100%. As shown in the unrooted tree, subfamily I included one AtMYB and six PcMYBs with branch support ranging from 74% to 100%; however, the function of AT5G04760.1 was not verified. As subfamily II only contained P. campanulata MYB members with branch support ranging from 73% to 100%, these MYB proteins may be unique to cherry. The majority of MYB members from P. campanulata and A. thaliana were distributed in subfamily III with branch support ranging from 17% to 100%, which contained many subgroups distributed loosely, as observed in other gene families generally (Figure 7).

3.6. MYB Gene Expression Profiles in Diverse Tissues

To analyze the expression levels of MYB genes in various tissues and at different flowering stages, including buds, mature leaves, stems, roots, and flowers at initial, full, and late flowering stages, the values of FPKM from unigenes were calculated and compared. The results of expression analyses, visualized in the form of heat maps, revealed that P. campanulata MYBs presented significant expression patterns in different organs and stages. The transcripts of 149 genes were detected in five tested tissues, while 22 genes were not exhibited. A total of 23 PcMYBs showed high levels of expression exclusively in buds, 20 in mature leaves, 14 in stems, 18 in roots, and 58 in flowers at the full flowering stage. The expression of 11 MYB genes was considerably higher in stems and roots, but lower in buds, leaves, and flowers. It was also found that five MYB genes were highly expressed in leaves, stems, and roots, but seldom transcribed in buds and flowers. Further investigation revealed that 19 genes uniquely exhibited high transcript abundance levels with expression at the initial flowering stage, 10 at the full, and 24 at the final flowering stage. Moreover, the expression levels of 31 genes increased gradually as the flowers matured, while those of 34 genes declined, and 20 genes first increased and then decreased (Figure 8, Table S15).

4. Discussion

Prunus L. consists of over 200 species of deciduous and evergreen trees and shrubs, with many economically important species, such as cherries, peaches, plums, apricots, almonds, and others [78]. The plastid data support three main clades for Prunus L. sensu lato, including the subgenus Prunus, subgenus Cerasus, and subgenus Padus, which correspond to three groups based on inflorescence structure: the solitary-flower group, the corymbose inflorescence group, and the racemose inflorescence group, respectively [2,79,80]. As a transition type from the racemose group to the solitary group, subgenus Cerasus plants are valuable for genetic evolution and comparative genomics research of Prunus. Subgenus Cerasus involves 50–60 species distributed across the Northern Hemisphere and into the subtropics and tropics [2]. In the process of adaptation to diverse environments, these wild species have evolved various characteristics [81], which are paramount to cultivated cherry improvements in the future. However, the genome information of most of these wild Cerasus species is largely unavailable, and compared with the other two subgenera in Prunus, wild Cerasus species have a complex genome due to their variable ploidy levels and heterozygosity, which makes it difficult to obtain a high-quality reference genome [82]. The genome of P. avium (Satonishiki) was assembled using Illumina short-read technologies and the scaffold N50 length was only about 219.6 kb, which is incomplete and highly fragmented [11]. After that, the P. yedoensis genome was assembled based on Pacbio long-read and Illumina short-read technologies, but the contig N50 length was only 132 kb [12]. Yi et al. reported a high-quality reference genome of C. serrulata with a contig N50 length of around 1.56 Mb based on a combination of Nanopore, Illumina, and Hi-C sequencing technologies, which greatly improved the genome quality compared with the short-read-based draft genome of P. avium [13]. Recently, the genome of a tetraploid wild species, P. fruticosa, was assembled using Nanopore and the Hi-C sequencing platform with a contig N50 length of 533 kb [14] (Table 1). Nevertheless, because of the limitations of second-generation sequencing technologies and high-level ploidy and heterozygosity, these draft genomes are highly fragmented with a total size larger than expected, or fail to capture the true genome composition [83,84]. Here, we provide a high-quality genome of diploid cherry P. campanulata using SMRT Pacific Biosciences sequencing, Illumina sequencing, 10× Genomics sequencing, and Hi-C genome scaffolding, which can be used for genome evolution and comparative genomics research, and for identifying genes controlling important traits.
The genome size of P. campanulata is 300.08 Mb. It is 44.21 Mb and 66.42 Mb smaller than P. avium “Tieton” [85] and P. fruticosa [14], and 28.08 Mb and 34.68 Mb more than P. avium “Satonishiki” [11] and C. serrulata [13]. Besides the high-level heterozygosity and sequencing methods, as shown in Table S16, TEs content is a leading reason for their genome size differences. Many studies have reported a strong correlation between genome size and TEs content [86,87,88]. P. campanulata is a species with magenta flowers, which is rare in the subgenus Cerasus [4]. In addition, it can flower very early due to a low chilling requirement [89]. These characteristics may have a major impact on its capacity for adaptation to the warm climate in subtropical and tropical regions. Our results indicate that the significantly expanded gene families in P. campanulata are mainly involved in ribosome biogenesis, diterpenoid biosynthesis, flavonoid biosynthesis, and circadian rhythm compared with other species (Table S13). We also found that P. campanulata-specific genes were enriched in pathways participating in ABC transporters, protein export, pantothenate and CoA biosynthesis, phagosomes, glucosinolate biosynthesis, plant circadian rhythm, flavonoid biosynthesis, and biotin metabolism (Figure 4C, D). These gene families in P. campanulata may account for its phenotype and resistance to biotic/abiotic stress. P. campanulata is considered a progenitor of P. × kanzakura, which generated many early flowering cultivars with high ornamental value. Shirasawa et al. [58] reported the genome sequences of two early flowering cherry plants (P. × kanzakura), “Kawazu-zakura” and “Atami-zakura” for defining their origin, but due to missing the reference genome of P. campanulata, it is difficult to document their origin. Here, we compared the genome of P. campanulata with the C. campanulata haplotype and the C. spachiana haplotype from “Kawazu-zakura” genome assembly, respectively. The results show that the proportion of the P. campanulata and C. campanulata haplotype (85.24%) is significantly higher than the C. spachiana haplotype (64.02%), which indicated that P. campanulata is most likely a progenitor of P. × kanzakura. The MYB family is one of the largest transcription factor (TF) families in plants [90]. MYBs function in cell differentiation [91], hormone signal transduction [92], cell wall biosynthesis [93], and response to the biotic and abiotic stress of plants [94]. Furthermore, MYB genes play a crucial role in anthocyanin accumulation [95] and dormancy regulation [96], which are closely related to flower color and flowering time, respectively. Here, we identified a total of 171 MYB genes in the genome of P. campanulata. The number of MYB genes is similar to P. persica, P. mume, and A. thaliana in the Plant Transcription Factor Database. MYB10 is considered the master regulator in controlling anthocyanin accumulation in Prunus species, such as cherry (PavMYB10, PavMYB10.1) [97,98,99], peach (PpMYB10.1, PpMYB10.2, PpMYB10.3, PpMYB10.4) [76,100,101], apricot (PmMYBa1, PaMYB10) [77,102], and plum (PsMYB10) [103]. In this study, the homologous MYB10 genes in the P. campanulata genome exhibit tissue-specificity of expression. PcMYB10a, PcMYB10c, and PcMYB10d expression showed an obvious upward trend during flowering, whereas PcMYB10b expression was observed in the stem, root, leaf, and bud (Figure 7). In Prunus, such a situation also arises in the peach; PpMYB10.1, PpMYB10.2, and PpMYB10.3 are related to anthocyanin accumulation in fruit, whereas PpMYB10.4 and PpMYB10.2 are related to accumulation in leaves and flowers, respectively [100,104]. So PcMYB10a, PcMYB10c, and PcMYB10d may be involved in anthocyanin accumulation of flowers of P. campanulata, and PcMYB10b may be involved in anthocyanin accumulation of other tissues. Additionally, PcMYB10a and PcMYB10c performed high expression at the initial flowering stage, whereas PcMYB10d showed high expression at the full flowering stage, which means that they may contribute to flower coloration at different stages. These results will facilitate elucidating the regulation of anthocyanin accumulation in the flowering cherry.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/genes14020389/s1, Figure S1: Estimation of the genome size of P. campanulata, based on k-mer analysis (k = 17). The x-axis is k-mer depth; the y-axis is the proportion that represents the frequency at that depth divided by the total frequency of all depths; Figure S2: GC content analysis of P. campanulata genome based on Illumina reads; Figure S3: Divergence analyses of transposable elements in the genome of P. campanulata based on Kimura distance (K-value from 0 to 60); Figure S4: Synteny analysis between P. campanulata, P. avium, and P. persica genomes. (A) Collinearity pattern of gene pairs between P. campanulata and P. avium. (B) Collinearity pattern of gene pairs between P. campanulata and P. persica; Figure S5: Genomic synteny between P. campanulata and P. × kanzakura “Kawazu-zakura”. (A) Collinearity pattern of genomes between P. campanulata and C. campanulata haplotype. (B) Collinearity pattern of genomes between P. campanulata and C. spachiana haplotype. Pca: P. campanulata; Cam: C. campanulata haplotype; Spe: C. spachiana haplotype. Table S1: Summary of sequencing data of P. campanulata; Table S2: Summary of Hi-C assembly; Table S3: Chromosome clusters using Hi-C sequencing data; Table S4: Quality assessment of the assembled genome of P. campanulata using BUSCO and CEGMA; Table S5: Summary of function annotation of protein-coding genes in P. campanulata using different databases; Table S6: Summary of non-coding RNAs annotation in P. campanulata; Table S7: The numbers of orthologs among 11 species; Table S8: The numbers of collinear gene pairs in the chromosomes of P. campanulata, P. avium, and P. persica; Table S9: Syntenic regions between P. campanulata and the C. campanulata haplotype of P. × kanzakura “Kawazu-zakura”; Table S10: Syntenic regions between the P. campanulata and C. spachiana haplotype of P. × kanzakura “Kawazu-zakura”; Table S11: Significantly enriched GO terms for family genes under positive selection; Table S12: Significantly enriched GO terms for family genes under expansion and contraction; Table S13: Significantly enriched KEGG terms for family genes under expansion and contraction; Table S14: The gene ID of MYB genes identified in the genome of P. campanulata; Table S15: The FPKM values of the PcMYB genes in the various tissues of P. campanulata; Table S16: Summary of TE contents in P. campanulata, P. avium “Tieton”, P. avium “Satonishiki”, C. serrulata, and P. fruticosa.

Author Contributions

Conceptualization, X.S. and X.L. (Xinhong Liu); methodology, D.J. and X.S.; software, X.L. (Xiangkong Li) and D.J.; formal analysis, Y.L. and S.Z.; investigation, Q.Z. and Y.L.; resources, X.L. (Xiangkong Li) and Q.Z.; writing—original draft preparation, D.J. and X.L. (Xiangkong Li); writing—review and editing, X.S. and S.Z.; supervision, X.L. (Xinhong Liu); funding acquisition, X.S. and D.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China, grant number 32101585. The research was supported by the Zhejiang Science and Technology Major Program on Agricultural New Variety Breeding, grant number 2021C02071-4.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available at NCBI BioProject under accession no. PRJNA884816.

Acknowledgments

We thank Qiang Ou of Fujian Jinxiangyun Agricultural Development Co., Ltd. for providing the P. campanulata materials and plant conservation.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Bortiri, E.; Oh, S.H.; Jiang, J.; Baggett, S.; Granger, A.; Weeks, C.; Buckingham, M.; Potter, D.; Parfitt, D.E. Phylogeny and Systematics of Prunus (Rosaceae) as Determined by Sequence Analysis of ITS and the Chloroplast trnL-trnF Spacer DNA. Syst. Bot. 2001, 26, 797–807. [Google Scholar] [CrossRef]
  2. Shi, S.; Li, J.; Sun, J.; Yu, J.; Zhou, S. Phylogeny and Classification of Prunus sensu lato (Rosaceae). J. Integr. Plant Biol. 2013, 55, 1069–1079. [Google Scholar] [CrossRef] [PubMed]
  3. Kato, S.; Matsumoto, A.; Yoshimura, K.; Katsuki, T.; Iwamoto, K.; Kawahara, T.; Mukai, Y.; Tsuda, Y.; Ishio, S.; Nakamura, K.; et al. Origins of Japanese Flowering Cherry (Prunus subgenus Cerasus) Cultivars Revealed Using Nuclear SSR Markers. Tree Genet. Genomes 2014, 10, 477–487. [Google Scholar] [CrossRef]
  4. Yu, D.J.; Li, C.L. China Flora; Science Press: Beijing, China, 1986; ISBN 13031.3176. [Google Scholar]
  5. Chien, C.T.; Chen, S.Y.; Yang, J.C. Effect of Stratification and Drying on the Germination and Storage of Prunus campanulata Seeds. Taiwan J. For. Sci. 2002, 17, 413–420. [Google Scholar] [CrossRef]
  6. Kato, S.; Matsumoto, A.; Yoshimura, K.; Katsuki, T.; Iwamoto, K.; Tsuda, Y.; Ishio, S.; Nakamura, K.; Moriwaki, K.; Shiroishi, T.; et al. Clone Identification in Japanese Flowering Cherry (Prunus Subgenus Cerasus) Cultivars Using Nuclear SSR Markers. Breed. Sci. 2012, 62, 248–255. [Google Scholar] [CrossRef]
  7. Kanazawa, Y.; Kameyama, Y.; JingXiu, L.; Hamano, C.; Suzuki, K. Genetic Relationship Between Early-Flowering Cherry Cultivars and Regional Populations of Prunus Campanulata. Hortic. Res. Jpn. 2016, 15, 129–138. [Google Scholar] [CrossRef]
  8. Guo, Y.; Kramer, M.; Pooler, M. Screening Ornamental Cherry (Prunus) Taxa for Resistance to Infection by Blumeriella Jaapii. HortSci. 2018, 53, 200–203. [Google Scholar] [CrossRef]
  9. Charlesworth, D.; Wright, S.I. Breeding Systems and Genome Evolution. Curr. Opin. Genet. Dev. 2001, 11, 685–690. [Google Scholar] [CrossRef]
  10. Tao, R.; Iezzoni, A.F. The S-RNase-Based Gametophytic Self-Incompatibility System in Prunus Exhibits Distinct Genetic and Molecular Features. Sci. Hortic. 2010, 124, 423–433. [Google Scholar] [CrossRef]
  11. Shirasawa, K.; Isuzugawa, K.; Ikenaga, M.; Saito, Y.; Yamamoto, T.; Hirakawa, H.; Isobe, S. The Genome Sequence of Sweet Cherry (Prunus avium) for Use in Genomics-Assisted Breeding. DNA Res. 2017, 24, 499–508. [Google Scholar] [CrossRef] [Green Version]
  12. Baek, S.; Choi, K.; Kim, G.B.; Yu, H.J.; Cho, A.; Jang, H.; Kim, C.; Kim, H.J.; Chang, K.S.; Kim, J.H.; et al. Draft Genome Sequence of Wild Prunus yedoensis Reveals Massive Inter-Specific Hybridization between Sympatric Flowering Cherries. Genome Biol. 2018, 19, 1–17. [Google Scholar] [CrossRef]
  13. Yi, X.G.; Yu, X.Q.; Chen, J.; Zhang, M.; Liu, S.W.; Zhu, H.; Li, M.; Duan, Y.F.; Chen, L.; Wu, L.; et al. The Genome of Chinese Flowering Cherry (Cerasus serrulata) Provides New Insights into Cerasus Species. Hortic. Res. 2020, 7, 165. [Google Scholar] [CrossRef] [PubMed]
  14. Wöhner, T.W.; Emeriewen, O.F.; Wittenberg, A.H.J.; Schneiders, H.; Vrijenhoek, I.; Halász, J.; Hrotkó, K.; Hoff, K.J.; Gabriel, L.; Lempe, J.; et al. The Draft Chromosome-Level Genome Assembly of Tetraploid Ground Cherry (Prunus fruticosa Pall.) from Long Reads. Genomics 2021, 113, 4173–4183. [Google Scholar] [CrossRef] [PubMed]
  15. Marçais, G.; Kingsford, C. A Fast, Lock-Free Approach for Efficient Parallel Counting of Occurrences of k-Mers. Bioinformatics 2011, 27, 764–770. [Google Scholar] [CrossRef]
  16. Liu, B.H.; Shi, Y.J.; Yuan, J.Y.; Hu, X.S.; Zhang, H.; Li, N.; Li, Z.Y.; Chen, Y.X.; Mu, D.S.; Fan, W. Estimation of Genomic Characteristics by Analyzing K-Mer Frequency in De Novo Genome Projects. arXiv 2020, arXiv:1308.2012. [Google Scholar]
  17. Chin, C.S.; Peluso, P.; Sedlazeck, F.J.; Nattestad, M.; Concepcion, G.T.; Clum, A.; Dunn, C.; O’Malley, R.; Figueroa-Balderas, R.; Morales-Cruz, A.; et al. Phased Diploid Genome Assembly with Single-Molecule Real-Time Sequencing. Nat Methods 2016, 13, 1050–1054. [Google Scholar] [CrossRef]
  18. Chin, C.S.; Alexander, D.H.; Marks, P.; Klammer, A.A.; Drake, J.; Heiner, C.; Clum, A.; Copeland, A.; Huddleston, J.; Eichler, E.E.; et al. Nonhybrid, Finished Microbial Genome Assemblies from Long-Read SMRT Sequencing Data. Nat. Methods 2013, 10, 563–569. [Google Scholar] [CrossRef]
  19. Walker, B.J.; Abeel, T.; Shea, T.; Priest, M.; Abouelliel, A.; Sakthikumar, S.; Cuomo, C.A.; Zeng, Q.; Wortman, J.; Young, S.K.; et al. Pilon: An Integrated Tool for Comprehensive Microbial Variant Detection and Genome Assembly Improvement. PLoS ONE 2014, 9, e112963. [Google Scholar] [CrossRef]
  20. Li, H.; Durbin, R. Fast and Accurate Short Read Alignment with Burrows–Wheeler Transform. Bioinformatics 2009, 25, 1754–1760. [Google Scholar] [CrossRef]
  21. Adey, A.; Kitzman, J.O.; Burton, J.N.; Daza, R.; Kumar, A.; Christiansen, L.; Ronaghi, M.; Amini, S.; Gunderson, K.L.; Steemers, F.J.; et al. In Vitro, Long-Range Sequence Information for de Novo Genome Assembly via Transposase Contiguity. Genome Res. 2014, 24, 2041–2049. [Google Scholar] [CrossRef]
  22. Langmead, B.; Salzberg, S.L. Fast Gapped-Read Alignment with Bowtie 2. Nat. Methods 2012, 9, 357–359. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Burton, J.N.; Adey, A.; Patwardhan, R.P.; Qiu, R.; Kitzman, J.O.; Shendure, J. Chromosome-Scale Scaffolding of de Novo Genome Assemblies Based on Chromatin Interactions. Nat. Biotechnol. 2013, 31, 1119–1125. [Google Scholar] [CrossRef]
  24. Simão, F.A.; Waterhouse, R.M.; Ioannidis, P.; Kriventseva, E.V.; Zdobnov, E.M. BUSCO: Assessing Genome Assembly and Annotation Completeness with Single-Copy Orthologs. Bioinformatics 2015, 31, 3210–3212. [Google Scholar] [CrossRef] [PubMed]
  25. Parra, G.; Bradnam, K.; Korf, I. CEGMA: A Pipeline to Accurately Annotate Core Genes in Eukaryotic Genomes. Bioinformatics 2007, 23, 1061–1067. [Google Scholar] [CrossRef] [PubMed]
  26. Zhao, X.; Hao, W. LTR_FINDER: An Efficient Tool for the Prediction of Full-Length LTR Retrotransposons. Nucl. Acids Res. 2007, 35, W265–W268. [Google Scholar] [CrossRef]
  27. Price, A.L.; Jones, N.C.; Pevzner, P.A. De Novo Identification of Repeat Families in Large Genomes. Bioinformatics 2005, 21, i351–i358. [Google Scholar] [CrossRef]
  28. Smit, A.; Hubley, R. RepeatModeler-1.0.11. Inst. Sys-Tems Biol. Available online: http://www.repeatmasker.org/RepeatModeler (accessed on 9 April 2019).
  29. Jurka, J.; Kapitonov, V.V.; Pavlicek, A.; Klonowski, P.; Kohany, O.; Walichiewicz, J. Repbase Update, a Database of Eukaryotic Repetitive Elements. Cytogenet. Genome Res. 2005, 110, 462–467. [Google Scholar] [CrossRef]
  30. Smit, A.; Hubley, R.; Green, P. RepeatMasker Open 4.0. Inst. Sys-Tems Biol. Available online: http://www.repeatmasker.org/RepeatMasker (accessed on 3 September 2019).
  31. Edgar, R.C. Search and Clustering Orders of Magnitude Faster than BLAST. Bioinformatics 2010, 26, 2460–2461. [Google Scholar] [CrossRef]
  32. Tarailo-Graovac, M.; Chen, N. Using Repeat Masker to Identify Repetitive Elements in Genomic Sequences. Curr. Protoc. Bioinforma. 2009, 25, 4.10.1–4.10.14. [Google Scholar] [CrossRef]
  33. Stanke, M.; Keller, O.; Gunduz, I.; Hayes, A.; Waack, S.; Morgenstern, B. Augustus: Ab Initio Prediction of Alternative Transcripts. Nucl. Acids Res. 2006, 34, W435–W439. [Google Scholar] [CrossRef]
  34. Burge, C. Identification of Genes in Human Genomic DNA. Ph.D. Thesis, Stanford University, Stanford, CA, USA, 1997. [Google Scholar]
  35. Majoros, W.H.; Pertea, M.; Salzberg, S.L. TigrScan and GlimmerHMM: Two Open Source Ab Initio Eukaryotic Gene-Finders. Bioinformatics 2004, 20, 2878–2879. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Haussler, D.K.D.; Eeckman, M.G.R.F.H. A Generalized Hidden Markov Model for the Recognition of Human Genes in DNA. In Proceedings of the International Conference on Intelligent Systems for Molecular Biology, St. Louis, MI, USA, 12-15 June 1996; pp. 134–142. [Google Scholar] [PubMed]
  37. Korf, I. Gene Finding in Novel Genomes. BMC Bioinform. 2004, 5, 1–9. [Google Scholar] [CrossRef] [PubMed]
  38. The Arabidopsis Genome Initiative Analysis of the Genome Sequence of the Flowering Plant Arabidopsis thaliana. Nature 2000, 408, 796–815. [CrossRef] [PubMed]
  39. Verde, I.; Abbott, A.G.; Scalabrin, S.; Jung, S.; Shu, S.; Marroni, F.; Zhebentyayeva, T.; Dettori, M.T.; Grimwood, J.; Cattonaro, F.; et al. The High-Quality Draft Genome of Peach (Prunus persica) Identifies Unique Patterns of Genetic Diversity, Domestication and Genome Evolution. Nat. Genet. 2013, 45, 487–494. [Google Scholar] [CrossRef]
  40. Zhang, Q.; Chen, W.; Sun, L.; Zhao, F.; Huang, B.; Yang, W.; Tao, Y.; Wang, J.; Yuan, Z.; Fan, G.; et al. The Genome of Prunus mume. Nat. Commun. 2012, 3, 1318. [Google Scholar] [CrossRef] [PubMed]
  41. Velasco, R.; Zharkikh, A.; Affourtit, J.; Dhingra, A.; Cestaro, A.; Kalyanaraman, A.; Fontana, P.; Bhatnagar, S.K.; Troggio, M.; Pruss, D.; et al. The Genome of the Domesticated Apple (Malus × domestica Borkh.). Nat. Genet. 2010, 42, 833–839. [Google Scholar] [CrossRef]
  42. Wu, J.; Wang, Z.; Shi, Z.; Zhang, S.; Ming, R.; Zhu, S.; Khan, M.A.; Tao, S.; Korban, S.S.; Wang, H.; et al. The Genome of the Pear (Pyrus bretschneideri Rehd.). Genome Res. 2013, 23, 396–408. [Google Scholar] [CrossRef]
  43. Shulaev, V.; Sargent, D.J.; Crowhurst, R.N.; Mockler, T.C.; Folkerts, O.; Delcher, A.L.; Jaiswal, P.; Mockaitis, K.; Liston, A.; Mane, S.P.; et al. The Genome of Woodland Strawberry (Fragaria vesca). Nat. Genet. 2011, 43, 109–116. [Google Scholar] [CrossRef]
  44. Camacho, C.; Coulouris, G.; Avagyan, V.; Ma, N.; Papadopoulos, J.; Bealer, K.; Madden, T.L. BLAST+: Architecture and Applications. BMC Bioinform. 2009, 10, 1–9. [Google Scholar] [CrossRef]
  45. Birney, E.; Clamp, M.; Durbin, R. GeneWise and Genomewise. Genome Res. 2004, 14, 988–995. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  46. Kim, D.; Pertea, G.; Trapnell, C.; Pimentel, H.; Kelley, R.; Salzberg, S.L. TopHat2: Accurate Alignment of Transcriptomes in the Presence of Insertions, Deletions and Gene Fusions. Genome Biol. 2013, 14, 1–13. [Google Scholar] [CrossRef]
  47. Trapnell, C.; Williams, B.A.; Pertea, G.; Mortazavi, A.; Kwan, G.; van Baren, M.J.; Salzberg, S.L.; Wold, B.J.; Pachter, L. Transcript Assembly and Quantification by RNA-Seq Reveals Unannotated Transcripts and Isoform Switching during Cell Differentiation. Nat. Biotechnol. 2010, 28, 511–515. [Google Scholar] [CrossRef]
  48. Haas, B.J.; Salzberg, S.L.; Zhu, W.; Pertea, M.; Allen, J.E.; Orvis, J.; White, O.; Buell, C.R.; Wortman, J.R. Automated Eukaryotic Gene Structure Annotation Using EVidenceModeler and the Program to Assemble Spliced Alignments. Genome Biol. 2008, 9, 1–22. [Google Scholar] [CrossRef] [PubMed]
  49. Consortium, U. UniProt: A Worldwide Hub of Protein Knowledge. Nucl. Acids Res. 2019, 47, D506–D515. [Google Scholar] [CrossRef] [PubMed]
  50. Zdobnov, E.M.; Apweiler, R. InterProScan–an Integration Platform for the Signature-Recognition Methods in InterPro. Bioinformatics 2001, 17, 847–848. [Google Scholar] [CrossRef]
  51. Eddy, S.R. Accelerated Profile HMM Searches. PLoS Comput. Biol. 2011, 7, e1002195. [Google Scholar] [CrossRef] [PubMed]
  52. Ashburner, M.; Ball, C.A.; Blake, J.A.; Botstein, D.; Butler, H.; Cherry, J.M.; Davis, A.P.; Dolinski, K.; Dwight, S.S.; Eppig, J.T. Gene Ontology: Tool for the Unification of Biology. Nat. Genet. 2000, 25, 25–29. [Google Scholar] [CrossRef] [PubMed]
  53. Kanehisa, M.; Goto, S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucl. Acids Res. 2000, 28, 27–30. [Google Scholar] [CrossRef]
  54. Lowe, T.M.; Eddy, S.R. TRNAscan-SE: A Program for Improved Detection of Transfer RNA Genes in Genomic Sequence. Nucl. Acids Res. 1997, 25, 955–964. [Google Scholar] [CrossRef]
  55. Nawrocki, E.P.; Eddy, S.R. Infernal 1.1: 100-Fold Faster RNA Homology Searches. Bioinformatics 2013, 29, 2933–2935. [Google Scholar] [CrossRef] [Green Version]
  56. Wang, Y.; Tang, H.; DeBarry, J.D.; Tan, X.; Li, J.; Wang, X.; Lee, T.; Jin, H.; Marler, B.; Guo, H. MCScanX: A Toolkit for Detection and Evolutionary Analysis of Gene Synteny and Collinearity. Nucl. Acids Res. 2012, 40, e49. [Google Scholar] [CrossRef]
  57. Delcher, A.L.; Salzberg, S.L.; Phillippy, A.M. Using MUMmer to Identify Similar Regions in Large Sequence Sets. Curr. Protoc. Bioinforma. 2003, 1, 10.3.1–10.3.18. [Google Scholar] [CrossRef] [PubMed]
  58. Shirasawa, K.; Itai, A.; Isobe, S. Genome Sequencing and Analysis of Two Early-Flowering Cherry (Cerasus × Kanzakura) Varieties, ‘Kawazu-Zakura’ and ‘Atami-Zakura. DNA Res. 2021, 28, dsab026. [Google Scholar] [CrossRef]
  59. Li, L.; Stoeckert, C.J.; Roos, D.S. OrthoMCL: Identification of Ortholog Groups for Eukaryotic Genomes. Genome Res. 2003, 13, 2178–2189. [Google Scholar] [CrossRef] [PubMed]
  60. Buti, M.; Moretto, M.; Barghini, E.; Mascagni, F.; Natali, L.; Brilli, M.; Lomsadze, A.; Sonego, P.; Giongo, L.; Alonge, M. The Genome Sequence and Transcriptome of Potentilla micrantha and Their Comparison to Fragaria vesca (the Woodland Strawberry). GigaScience 2018, 7, giy010. [Google Scholar] [CrossRef] [PubMed]
  61. Hibrand Saint-Oyant, L.; Ruttink, T.; Hamama, L.; Kirov, I.; Lakhwani, D.; Zhou, N.-N.; Bourke, P.M.; Daccord, N.; Leus, L.; Schulz, D. A High-Quality Genome Sequence of Rosa chinensis to Elucidate Ornamental Traits. Nat. Plants 2018, 4, 473–484. [Google Scholar] [CrossRef]
  62. VanBuren, R.; Wai, C.M.; Colle, M.; Wang, J.; Sullivan, S.; Bushakra, J.M.; Liachko, I.; Vining, K.J.; Dossett, M.; Finn, C.E. A Near Complete, Chromosome-Scale Assembly of the Black Raspberry (Rubus occidentalis) Genome. Gigascience 2018, 7, giy094. [Google Scholar] [CrossRef]
  63. Yang, Z. PAML 4: Phylogenetic Analysis by Maximum Likelihood. Mol. Biol. Evol. 2007, 24, 1586–1591. [Google Scholar] [CrossRef]
  64. Edgar, R.C. MUSCLE: Multiple Sequence Alignment with High Accuracy and High Throughput. Nucl. Acids Res. 2004, 32, 1792–1797. [Google Scholar] [CrossRef]
  65. Castresana, J. Selection of Conserved Blocks from Multiple Alignments for Their Use in Phylogenetic Analysis. Mol. Biol. Evol. 2000, 17, 540–552. [Google Scholar] [CrossRef] [Green Version]
  66. De Bie, T.; Cristianini, N.; Demuth, J.P.; Hahn, M.W. CAFE: A Computational Tool for the Study of Gene Family Evolution. Bioinformatics 2006, 22, 1269–1271. [Google Scholar] [CrossRef] [PubMed]
  67. Stamatakis, A. RAxML Version 8: A Tool for Phylogenetic Analysis and Post-Analysis of Large Phylogenies. Bioinformatics 2014, 30, 1312–1313. [Google Scholar] [CrossRef] [PubMed]
  68. Chen, C.; Chen, H.; Zhang, Y.; Thomas, H.R.; Frank, M.H.; He, Y.; Xia, R. TBtools: An Integrative Toolkit Developed for Interactive Analyses of Big Biological Data. Mol. Plant 2020, 13, 1194–1202. [Google Scholar] [CrossRef] [PubMed]
  69. Katoh, K.; Standley, D.M. MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability. Mol. Biol. Evol. 2013, 30, 772–780. [Google Scholar] [CrossRef]
  70. Rambaut, A. Se-Al Sequence Alignment Editor, Version 2.0 A11. Available online: http://tree.bio.ed.ac.uk/software/seal (accessed on 2 February 2021).
  71. Kumar, S.; Stecher, G.; Li, M.; Knyaz, C.; Tamura, K. MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms. Mol. Biol. Evol. 2018, 35, 1547. [Google Scholar] [CrossRef]
  72. Brown, J.; Pirrung, M.; McCue, L.A. FQC Dashboard: Integrates FastQC Results into a Web-Based, Interactive, and Extensible FastQ Quality Control Tool. Bioinformatics 2017, 33, 3137–3139. [Google Scholar] [CrossRef]
  73. Anders, S.; Pyl, P.T.; Huber, W. HTSeq—A Python Framework to Work with High-Throughput Sequencing Data. Bioinformatics 2015, 31, 166–169. [Google Scholar] [CrossRef]
  74. Anders, S.; Huber, W. Differential Expression Analysis for Sequence Count Data. Nat. Preced. 2010, 11, 1. [Google Scholar] [CrossRef]
  75. Li, H.; Handsaker, B.; Wysoker, A.; Fennell, T.; Ruan, J.; Homer, N.; Marth, G.; Abecasis, G.; Durbin, R. The Sequence Alignment/Map Format and SAMtools. Bioinformatics 2009, 25, 2078–2079. [Google Scholar] [CrossRef]
  76. Tuan, P.A.; Bai, S.; Yaegaki, H.; Tamura, T.; Hihara, S.; Moriguchi, T.; Oda, K. The Crucial Role of PpMYB10.1 in Anthocyanin Accumulation in Peach and Relationships between Its Allelic Type and Skin Color Phenotype. BMC Plant Biol. 2015, 15, 1–14. [Google Scholar] [CrossRef] [Green Version]
  77. Zhang, Q.; Hao, R.; Xu, Z.; Yang, W.; Wang, J.; Cheng, T.; Pan, H.; Zhang, Q. Isolation and Functional Characterization of a R2R3-MYB Regulator of Prunus mume Anthocyanin Biosynthetic Pathway. Plant Cell Tissue Organ Cult. PCTOC 2017, 131, 417–429. [Google Scholar] [CrossRef]
  78. Lee, S.; Wen, J. A Phylogenetic Analysis of Prunus and the Amygdaloideae (Rosaceae) Using ITS Sequences of Nuclear Ribosomal DNA. Am. J. Bot. 2001, 88, 150–160. [Google Scholar] [CrossRef] [PubMed]
  79. Chin, S.W.; Shaw, J.; Haberle, R.; Wen, J.; Potter, D. Diversification of Almonds, Peaches, Plums and Cherries—Molecular Systematics and Biogeographic History of Prunus (Rosaceae). Mol. Phylogenet. Evol. 2014, 76, 34–48. [Google Scholar] [CrossRef]
  80. Chin, S.; Lutz, S.; Wen, J.; Potter, D.A. The Bitter and the Sweet: Inference of Homology and Evolution of Leaf Glands in Prunus (Rosaceae) through Anatomy, Micromorphology, and Ancestral–Character State Reconstruction. Int. J. Plant Sci. 2013, 174, 27–46. [Google Scholar] [CrossRef]
  81. Bradshaw, A.D. Evolutionary Significance of Phenotypic Plasticity in Plants. Adv. Genet. 1965, 13, 115–155. [Google Scholar] [CrossRef]
  82. Sun, Y.; Shang, L.; Zhu, Q.H.; Fan, L.; Guo, L. Twenty Years of Plant Genome Sequencing: Achievements and Challenges. Trends Plant Sci. 2022, 27, 391–401. [Google Scholar] [CrossRef]
  83. Pryszcz, L.P.; Gabaldón, T. Redundans: An Assembly Pipeline for Highly Heterozygous Genomes. Nucl. Acids Res. 2016, 44, e113. [Google Scholar] [CrossRef]
  84. Michael, T.P.; VanBuren, R. Building Near-Complete Plant Genomes. Curr. Opin. Plant Biol. 2020, 54, 26–33. [Google Scholar] [CrossRef]
  85. Wang, J.; Liu, W.; Zhu, D.; Hong, P.; Zhang, S.; Xiao, S.; Tan, Y.; Chen, X.; Xu, L.; Zong, X.; et al. Chromosome-Scale Genome Assembly of Sweet Cherry (Prunus avium L.) cv. Tieton Obtained Using Long-Read and Hi-C Sequencing. Hortic. Res. 2020, 7, 1–11. [Google Scholar] [CrossRef]
  86. Bennetzen, J.L.; Wang, H. The Contributions of Transposable Elements to the Structure, Function, and Evolution of Plant Genomes. Annu. Rev. Plant Biol. 2014, 65, 505–530. [Google Scholar] [CrossRef]
  87. Lee, S.-I.; Kim, N.-S. Transposable Elements and Genome Size Variations in Plants. Genom. Inform. 2014, 12, 87–97. [Google Scholar] [CrossRef] [PubMed]
  88. Tenaillon, M.I.; Hufford, M.B.; Gaut, B.S.; Ross-Ibarra, J. Genome Size and Transposable Element Content as Determined by High-Throughput Sequencing in Maize and Zea Luxurians. Genome Biol. Evol. 2011, 3, 219–229. [Google Scholar] [CrossRef] [PubMed]
  89. Huang, K.F.; Wen, C.H.; Wang, C.T.; Chu, F.H. Transcriptome and Flower Genes Analysis of Prunus campanulata Maxim. J. Hortic. Sci. Biotechnol. 2020, 95, 44–52. [Google Scholar] [CrossRef]
  90. Stracke, R.; Werber, M.; Weisshaar, B. The R2R3-MYB Gene Family in Arabidopsis thaliana. Curr. Opin. Plant Biol. 2001, 4, 447–456. [Google Scholar] [CrossRef] [PubMed]
  91. Ramsay, N.A.; Glover, B.J. MYB–BHLH–WD40 Protein Complex and the Evolution of Cellular Diversity. Trends Plant Sci. 2005, 10, 63–70. [Google Scholar] [CrossRef] [PubMed]
  92. Shin, R.; Burch, A.Y.; Huppert, K.A.; Tiwari, S.B.; Murphy, A.S.; Guilfoyle, T.J.; Schachtman, D.P. The Arabidopsis Transcription Factor MYB77 Modulates Auxin Signal Transduction. Plant Cell 2007, 19, 2440–2453. [Google Scholar] [CrossRef]
  93. Xiao, R.; Zhang, C.; Guo, X.; Li, H.; Lu, H. MYB Transcription Factors and Its Regulation in Secondary Cell Wall Formation and Lignin Biosynthesis during Xylem Development. Int. J. Mol. Sci. 2021, 22, 3560. [Google Scholar] [CrossRef]
  94. Dubos, C.; Stracke, R.; Grotewold, E.; Weisshaar, B.; Martin, C.; Lepiniec, L. MYB Transcription Factors in Arabidopsis. Trends Plant Sci. 2010, 15, 573–581. [Google Scholar] [CrossRef]
  95. Naing, A.H.; Kim, C.K. Roles of R2R3-MYB Transcription Factors in Transcriptional Regulation of Anthocyanin Biosynthesis in Horticultural Plants. Plant Mol. Biol. 2018, 98, 1–18. [Google Scholar] [CrossRef]
  96. Cooke, J.E.; Eriksson, M.E.; Junttila, O. The Dynamic Nature of Bud Dormancy in Trees: Environmental Control and Molecular Mechanisms. Plant Cell Environ. 2012, 35, 1707–1728. [Google Scholar] [CrossRef]
  97. Jin, W.; Wang, H.; Li, M.; Wang, J.; Yang, Y.; Zhang, X.; Yan, G.; Zhang, H.; Liu, J.; Zhang, K. The R2R3 MYB Transcription Factor PavMYB10.1 Involves in Anthocyanin Biosynthesis and Determines Fruit Skin Colour in Sweet Cherry (Prunus avium L.). Plant Biotechnol. J. 2016, 14, 2120–2133. [Google Scholar] [CrossRef] [PubMed]
  98. Starkevič, P.; Paukštytė, J.; Kazanavičiūtė, V.; Denkovskienė, E.; Stanys, V.; Bendokas, V.; Siksnianas, T.; Razanskiene, A.; Razanskas, R. Expression and Anthocyanin Biosynthesis-Modulating Potential of Sweet Cherry (Prunus avium L.) MYB10 and BHLH Genes. PLoS ONE 2015, 10, e0126991. [Google Scholar] [CrossRef] [PubMed]
  99. Ye, X.; Zhang, F.; Tao, Y.; Song, S.; Fang, J. Reference Gene Selection for Quantitative Real-Time PCR Normalization in Different Cherry Genotypes, Developmental Stages and Organs. Sci. Hortic. 2015, 181, 182–188. [Google Scholar] [CrossRef]
  100. Zhou, H.; Peng, Q.; Zhao, J.; Owiti, A.; Ren, F.; Liao, L.; Wang, L.; Deng, X.; Jiang, Q.; Han, Y. Multiple R2R3-MYB Transcription Factors Involved in the Regulation of Anthocyanin Accumulation in Peach Flower. Front. Plant Sci. 2016, 7, 1557. [Google Scholar] [CrossRef] [PubMed]
  101. Rahim, M.; Busatto, N.; Trainotti, L. Regulation of Anthocyanin Biosynthesis in Peach Fruits. Planta 2014, 240, 913–929. [Google Scholar] [CrossRef]
  102. Xi, W.; Feng, J.; Liu, Y.; Zhang, S.; Zhao, G. The R2R3-MYB Transcription Factor PaMYB10 is Involved in Anthocyanin Biosynthesis in Apricots and Determines Red Blushed Skin. BMC Plant Biol. 2019, 19, 1–14. [Google Scholar] [CrossRef]
  103. Fiol, A.; García-Gómez, B.E.; Jurado-Ruiz, F.; Alexiou, K.; Howad, W.; Aranzana, M.J. Characterization of Japanese Plum (Prunus salicina) PsMYB10 Alleles Reveals Structural Variation and Polymorphisms Correlating with Fruit Skin Color. Front. Plant Sci. 2021, 12, 655267. [Google Scholar] [CrossRef]
  104. Zhou, Y.; Zhou, H.; Lin-Wang, K.; Vimolmangkang, S.; Espley, R.V.; Wang, L.; Allan, A.C.; Han, Y. Transcriptome analysis and transient transformation suggest an ancient duplicated MYB transcription factor as a candidate gene for leaf red coloration in peach. BMC Plant Biol. 2014, 14, 1–13. [Google Scholar] [CrossRef] [Green Version]
Genes 14 00389 g001 550
Figure 1. Morphology of P. campanulata cultivar “Lianmeiren”. (A) P. campanulata tree grows in Shaowu City, Fujian Province. (B) Flower branch and inflorescence. (C) Flower. (D) Leaves. The scale unit of the ruler is a centimeter.
Figure 1. Morphology of P. campanulata cultivar “Lianmeiren”. (A) P. campanulata tree grows in Shaowu City, Fujian Province. (B) Flower branch and inflorescence. (C) Flower. (D) Leaves. The scale unit of the ruler is a centimeter.
Genes 14 00389 g001
Genes 14 00389 g002 550
Figure 2. Hi-C contact map revealing extensive hierarchical chromatin interactions in the genome of P. campanulata.
Figure 2. Hi-C contact map revealing extensive hierarchical chromatin interactions in the genome of P. campanulata.
Genes 14 00389 g002
Genes 14 00389 g003 550
Figure 3. Circular diagram depicting the characteristics of P. campanulata genome. (a) Genome of P. campanulata. (b) Gene density in 1 Mb sliding windows. (c) GC content in 1 Mb sliding windows. (d) Repeat density in 1 Mb sliding windows. (e) Copia density in 1 Mb sliding windows. (f) Gypsy density in 1 Mb sliding windows. (g) Syntenic relationships of gene pairs between P. campanulata and P. avium genomes using the best-hit method. Pca: P. campanulata; Pav: P. avium.
Figure 3. Circular diagram depicting the characteristics of P. campanulata genome. (a) Genome of P. campanulata. (b) Gene density in 1 Mb sliding windows. (c) GC content in 1 Mb sliding windows. (d) Repeat density in 1 Mb sliding windows. (e) Copia density in 1 Mb sliding windows. (f) Gypsy density in 1 Mb sliding windows. (g) Syntenic relationships of gene pairs between P. campanulata and P. avium genomes using the best-hit method. Pca: P. campanulata; Pav: P. avium.
Genes 14 00389 g003
Genes 14 00389 g004 550
Figure 4. Gene family analysis of the genome of P. campanulata. (A) The unique and shared gene families among four species. Pcam: P. campanulata; Pper: P. persica; Pmum: P. mume; Pavi: P. avium. (B) Comparison of orthologs between P. campanulata and other angiosperm species. Pcam: P. campanulata; Pper: P. persica; Pmum: P. mume; Pavi: P. avium; Pbre: P. bretschneideri; Mdom: M. domestica; Fves: F. vesca; Pmic: P. micrantha; Rchi: R. chinensis; Rocc: R. occidentalis; Atha: A. thaliana. (C) GO enrichment analysis of P. campanulata-specific genes. (D) KEGG enrichment analysis of P. campanulata-specific genes.
Figure 4. Gene family analysis of the genome of P. campanulata. (A) The unique and shared gene families among four species. Pcam: P. campanulata; Pper: P. persica; Pmum: P. mume; Pavi: P. avium. (B) Comparison of orthologs between P. campanulata and other angiosperm species. Pcam: P. campanulata; Pper: P. persica; Pmum: P. mume; Pavi: P. avium; Pbre: P. bretschneideri; Mdom: M. domestica; Fves: F. vesca; Pmic: P. micrantha; Rchi: R. chinensis; Rocc: R. occidentalis; Atha: A. thaliana. (C) GO enrichment analysis of P. campanulata-specific genes. (D) KEGG enrichment analysis of P. campanulata-specific genes.
Genes 14 00389 g004
Genes 14 00389 g005 550
Figure 5. Evolution of the genome and gene families of P. campanulata. (A) Phylogenetic tree with the number of gene families displaying expansion and contraction from 11 species for estimating divergence time. The numbers on the branches show the expanded (green) and contracted (red) gene family numbers among all gene families. (B) Distribution of 4DTv values in Prunus species. Pcam: P. campanulata; Pper: P. persica; Pmum: P. mume; Pavi: P. avium.
Figure 5. Evolution of the genome and gene families of P. campanulata. (A) Phylogenetic tree with the number of gene families displaying expansion and contraction from 11 species for estimating divergence time. The numbers on the branches show the expanded (green) and contracted (red) gene family numbers among all gene families. (B) Distribution of 4DTv values in Prunus species. Pcam: P. campanulata; Pper: P. persica; Pmum: P. mume; Pavi: P. avium.
Genes 14 00389 g005
Genes 14 00389 g006 550
Figure 6. Chromosomal localizations of the MYB genes. The bars represent the P. campanulata chromosomes. The scale bar on the left indicates the physical distance of the MYB genes on the chromosomes. Four MYB genes on the right are located on the scattered scaffolds.
Figure 6. Chromosomal localizations of the MYB genes. The bars represent the P. campanulata chromosomes. The scale bar on the left indicates the physical distance of the MYB genes on the chromosomes. Four MYB genes on the right are located on the scattered scaffolds.
Genes 14 00389 g006
Genes 14 00389 g007 550
Figure 7. Phylogenetic relationships of the MYB proteins from P. campanulata and A. thaliana. The red triangle denotes the protein from P. campanulata, and the green circle denotes the protein from A. thaliana.
Figure 7. Phylogenetic relationships of the MYB proteins from P. campanulata and A. thaliana. The red triangle denotes the protein from P. campanulata, and the green circle denotes the protein from A. thaliana.
Genes 14 00389 g007
Genes 14 00389 g008 550
Figure 8. Expression profiles of the MYB genes in various tissues. F1: flowers at the initial flowering stage; F2: flowers at the full flowering stage; F3: flowers at the late flowering stage. The color bar in the middle indicates log2 expression values, with red representing high levels and green representing low levels of expression.
Figure 8. Expression profiles of the MYB genes in various tissues. F1: flowers at the initial flowering stage; F2: flowers at the full flowering stage; F3: flowers at the late flowering stage. The color bar in the middle indicates log2 expression values, with red representing high levels and green representing low levels of expression.
Genes 14 00389 g008
Table
Table 1. Comparison of the genome assembly among the four cherry species.
Table 1. Comparison of the genome assembly among the four cherry species.
ParameterP. campanulataP. avium
“Satonishiki”		P. yedoensisC. serrulataP. fruticosa
Sequencing platformPacBio, Illumina, 10× Genomics, Hi-CIlluminaPacBio, IlluminaNanopore, Illumina, Hi-CNanopore, Hi-C
Heterozygosity percentage0.54%——1.67%—
N50 length (contigs) (Mb)2.02—0.1331.560.533
N50 length (scaffolds) (Mb)33.440.2190.19831.1243.82
No. of protein-coding genes28,31943,34941,29429,09458,880
Chromosome level/Total size of assigned scaffolds (Mb)Yes/283.62Yes/191.70NoYes/252.25Yes/—
No. of scaffolds37010, 1483, 18567—
Total length of assembled scaffolds (Mb)300.48272.36323.78265.4—
No. of contigs68751,87742921821275
Total size of assembled contigs (Mb)299.15—318.74263.16366.5
Busco assessmentC:96.6% [S:92.8%,D:3.8%], F:0.8%,M:2.6%,n:1440 C:96% [S:78.3%,D:17.7%], F:1.8%,M:2.2%,n:956N/AC:94.7% [S:83.8%,D:10.9%], F:1.86%,M:3.47%,n:1614C:96.4% [S:94.1%,D:2.3%], F:1.3%,M:2.3%,n:1614
Table
Table 2. Summary of repetitive sequences in the genome of P. campanulata.
Table 2. Summary of repetitive sequences in the genome of P. campanulata.
TypeDe novo + Repbase 1TE Proteins 2Combined TEs 3
Length(bp)% in GenomeLength(bp)% in Genome Length(bp)% in Genome
DNA46,577,99915.528,655,2572.8848,545,28116.18
LINE 45,778,3241.932,431,2020.817,025,2672.34
SINE 514,54400014,5440
LTR 692,381,32030.7922,553,4467.5293,460,21931.15
Unknown 716,239,7535.410016,239,7535.41
Total157,524,47752.4933,566,60411.19160,006,93153.32
1 De novo + Repbase: annotated de novo by RepeatModeler, RepeatScout, and LTR_FINDER; 2 TE proteins: annotated by RepeatProteinMasker based on RepBase protein database; 3 Combined TEs: merged results from approaches above by removing overlaps; 4 LINE: long interspersed nuclear element; 5 SINE: short interspersed nuclear element; 6 LTR: long terminal repeat; 7 Unknown: repeat sequences cannot classify.
Table
Table 3. Summary of protein-coding genes annotation in P. campanulata via three methods.
Table 3. Summary of protein-coding genes annotation in P. campanulata via three methods.
MethodGene SetNumberAverage Transcript Length (bp)Average CDS Length (bp)Average Exons Per GeneAverage Exon Length (bp)Average Intron Length (bp)
De novoAugustus21,8372714.221201.264.98241.3380.31
GlimmerHMM35,7726382.00796.83.41234.012322.32
SNAP22,2563128.31721.534.17172.89758.43
Geneid31,5973987.08914.414.49203.78881.1
Genscan20,4938917.351370.016.42213.251391.37
HomologArabidopsis_thaliana26,2862299.761045.173.79276.13450.47
Fragaria_vesca21,2183082.181347.824.46302.29501.45
Malus_domestica25,1352556.851263.624.2300.84404.10
Prunus_avium27,3592019.39891.103.68242.34421.46
Prunus_mume24,9602764.2612734.5283.05426.38
Prunus_persica29,6262176.781082.374.01269.93363.61
Pyrus_bretschneideri21,8372893.411292.814.42292.21467.42
RNAseqPASA70,3322899.391019.994.79212.94495.89
Cufflinks47,6255826.712195.126.17355.93702.80
EVM 30,6443031.101161.664.53256.69530.25
Pasa-update 30,4313022.991181.124.56258.99517.31
Final set 28,2913135.451226.504.75258.41509.54
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Jiang, D.; Li, X.; Li, Y.; Zhou, S.; Zhou, Q.; Liu, X.; Shen, X. Chromosome-Level Assembly of Flowering Cherry (Prunus campanulata) Provides Insight into Anthocyanin Accumulation. Genes 2023, 14, 389. https://doi.org/10.3390/genes14020389

AMA Style

Jiang D, Li X, Li Y, Zhou S, Zhou Q, Liu X, Shen X. Chromosome-Level Assembly of Flowering Cherry (Prunus campanulata) Provides Insight into Anthocyanin Accumulation. Genes. 2023; 14(2):389. https://doi.org/10.3390/genes14020389

Chicago/Turabian Style

Jiang, Dongyue, Xiangkong Li, Yingang Li, Shiliang Zhou, Qi Zhou, Xinhong Liu, and Xin Shen. 2023. "Chromosome-Level Assembly of Flowering Cherry (Prunus campanulata) Provides Insight into Anthocyanin Accumulation" Genes 14, no. 2: 389. https://doi.org/10.3390/genes14020389

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop