Comparative analysis of the chloroplast genomes of Rosa species and RNA editing analysis

Abstract

Background: The genus Rosa (Rosaceae) contains approximately 200 species, most of which have high ecological and economic values. Chloroplast genome sequences are important for studying species differentiation, phylogeny, and RNA editing.

Results: In this study, the chloroplast genomes of three Rosa species, Rosa hybrida, Rosa acicularis, and Rosa rubiginosa, were assembled and compared with other reported Rosa chloroplast genomes. To investigate the RNA editing sites in R. hybrida (commercial rose cultivar), we mapped RNA-sequencing data to the chloroplast genome and analyzed their post-transcriptional features. Rosa chloroplast genomes presented a quadripartite structure and had highly conserved gene order and gene content. We identified four mutation hotspots (ycf3-trnS, trnT-trnL, psbE-petL, and ycf1) as candidate molecular markers for differentiation in the Rosa species. Additionally, 22 chloroplast genomic fragments with a total length of 6,192 bp and > 90% sequence similarity with their counterparts were identified in the mitochondrial genome, representing 3.96% of the chloroplast genome. Phylogenetic analysis including all sections and all subgenera revealed that the earliest divergence in the chloroplast phylogeny roughly distinguished species of sections Pimpinellifoliae and Rosa and subgenera Hulthemia. Moreover, DNA- and RNA-sequencing data revealed 19 RNA editing sites, including three synonymous and 16 nonsynonymous, in the chloroplast genome of R. hybrida that were distributed among 13 genes.

Conclusions: The genome structure and gene content of Rosa chloroplast genomes are similar across various species. Phylogenetic analysis based on the Rosa chloroplast genomes has high resolution. Additionally, a total of 19 RNA editing sites were validated by RNA-Seq mapping in R. hybrida. The results provide valuable information for RNA editing and evolutionary studies of Rosa and a basis for further studies on genomic breeding of Rosa species.

Keywords: Chloroplast genome; Phylogenetic analysis; RNA editing; RNA-Seq; Rosa.

Fig. 1

Map of aligned Rosa chloroplast genomes. Gene map of the Rosa chloroplast genomes, sequence alignment of Rosa species chloroplast genomes with R. rugosa as the reference, GC skew, and GC content from outside to inside. The circular map was drawn using OGDraw

Fig. 2

Comparative analysis of five Rosa chloroplast genomes. (a) Comparison of the borders of large single-copy, inverted repeat, and small single-copy regions among the five Rosa genomes. Colored boxes indicate the genes across the junctions. (b) Rosa chloroplast genome collinearity comparison plot. Local co-linear blocks (LCB) were colored to indicate regions of commonality. The histogram within each block indicates the degree of sequence similarity. The results were visualized by IRscope and Mauve

Fig. 3

Sliding window analysis of the Rosa chloroplast genomes using the DnaSP program. Window length: 600 bp; step size: 200 bp. X-axis, Position of a window; Y-axis, Nucleotide diversity per window

Fig. 4

Schematic diagram of gene transfer between mitochondrial and chloroplast genomes in R. chinensis. Colored lines within the circle show where the chloroplast genome segment entering the mitochondrial genome. Genes within a circle are transcribed clockwise, while those outside the circle are transcribed counterclockwise. The gene transfer results were visualized using Circos

Fig. 5

Maximum Likelihood (ML) phylogenetic tree reconstruction of 44 Rosa species based on whole chloroplast genome sequences using IQ-TREE. The best-fit substitution model (TVM + F + I + G4) was used to build phylogenetic tree. Bootstrap resampling with 1,000 replicates was employed to assess branching support. Numbers with branches indicate ML bootstrap values, asterisk denotes 100% ML bootstrap support. Rubus crataegifolius was used as the outgroup. The GenBank numbers of all species are shown in the figure. Different colors correspond to the section names

Fig. 6

Overview of the RNA editing site identification and analysis pipeline