The complete chloroplast genome sequences of three Broussonetia species and comparative analysis within the Moraceae

Abstract

Background Species of Broussonetia (family Moraceae) are commonly used to make textiles and high-grade paper. The distribution of Broussonetia papyrifera L. is considered to be related to the spread and location of humans. The complete chloroplast (cp) genomes of B. papyrifera, Broussonetia kazinoki Sieb., and Broussonetia kaempferi Sieb. were analyzed to better understand the status and evolutionary biology of the genus Broussonetia. Methods The cp genomes were assembled and characterized using SOAPdenovo2 and DOGMA. Phylogenetic and molecular dating analysis were performed using the concatenated nucleotide sequences of 35 species in the Moraceae family and were based on 66 protein-coding genes (PCGs). An analysis of the sequence divergence (pi) of each PCG among the 35 cp genomes was conducted using DnaSP v6. Codon usage indices were calculated using the CodonW program. Results All three cp genomes had the typical land plant quadripartite structure, ranging in size from 160,239 bp to 160,841 bp. The ribosomal protein L22 gene (RPL22) was either incomplete or missing in all three Broussonetia species. Phylogenetic analysis revealed two clades. Clade 1 included Morus and Artocarpus, whereas clade 2 included the other seven genera. Malaisia scandens Lour. was clustered within the genus Broussonetia. The differentiation of Broussonetia was estimated to have taken place 26 million years ago. The PCGs’ pi values ranged from 0.0005 to 0.0419, indicating small differences within the Moraceae family. The distribution of most of the genes in the effective number of codons plot (ENc-plot) fell on or near the trend line; the slopes of the trend line of neutrality plots were within the range of 0.0363–0.171. These results will facilitate the identification, taxonomy, and utilization of the Broussonetia species and further the evolutionary studies of the Moraceae family.

Analysis of the Chloroplast Genome of Ficus simplicissima Lour Collected in Vietnam and Proposed Barcodes for Identifying Ficus Plants

“…The GC content of the IR regions was higher than that of the non-coding intergenic regions because of the presence of rRNA genes [27]. In addition, the number of predicted genes was smaller (127) than that (131) which were previously reported in the F. simplicissima [13], F. concinna [28], and Broussonetia species [29] genomes with 15 intron-containing genes. Several genes are known to possess structural intron variation, such as atpF, rpoC2, rpl12, rps12, and rps16 [2,30].…”

Identifying Molecular Markers for Ficus erecta Thunb. Based on Complete Plastome Sequences of Korean Figs (Ficus L., Moraceae)

“…Furthermore, we annotated the psbN gene, responsible for encoding the photosystem biogenesis factor 1, as pbf 1. It was observed that the inf A gene, which encodes translation initiation factor 1, underwent pseudogenization, a common occurrence in many members of Moraceae [33][34][35][36]. Utilizing 78 plastid protein-coding genes, we achieved consistent topologies across MP, ML, and BI trees, supported by high bootstrap values and posterior probability (Figure 2).…”

Bioinformatic Analysis of Codon Usage Bias of HSP20 Genes in Four Cruciferous Species

“…A PR2 Rule bias plot was generated with A3/(A3 + T3) on the x-axis and G3/(G3 + T3) on the y-axis. If the base content of one strand is A = T and G = C, it signifies that mutation pressure and natural selection would not affect both complementary DNA strands [ 59 ]. The center of the plot is set at (0.5, 0.5), where the distance and direction from the center point represent the degree and direction of PR2 bias, respectively.…”

“…Complete CDSs of HSP20 genes were extracted using TBtools-IIv2.052, ensuring that ATG acted as the start codon and that TGA, TAA, and TAG acted as the stop codons. The relative synonymous codon usage (RSCU), codon adaptation index (CAI), synonymous codon GC content, and 3rd base contents (A3s, T3s, G3s, and C3s) were determined using CodonW 1.4.2 [59]. Codon usage frequencies were calculated with the CUSP tool on the EMBOSS services (https://www.bioinformatics.nl/emboss-explorer/) (accessed on 11 October 2023), while the effective codon numbers were obtained using CHIPS, while the effective codon numbers were obtained using CHIPS.…”