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Background Mitochondria are crucial for energy production in plant tissues, but their quantity and activity vary in different tissues and developmental processes. Determining the factors underlying differential molecular evolutionary rates has long been a central question in evolutionary biology, with expression level emerging as the prime predictor. Although we have previously observed an anti-correlation between expression level (E) and evolutionary rate (R) in chloroplast genes, it remains unclear whether such an anti-correlation exists in plant mitochondrial genes. Ophioglossum vulgatum is a typical plant belonging to the Ophioglossaceae, characterized by its unique morphology with only a single leaf above ground. It holds significant scientific and medicinal value. Using the mitochondrial genome and transcriptome data of O. vulgatum , we first analyzed the correlation between mitochondrial gene expression, codon usage bias, and evolutionary rates in different tissues. Results Our findings indicated that mitochondrial gene expression level was the strongest between stem and leaf, while the weakest was between sporangium and root. Kruskal-Wallis tests revealed significant differences across various tissue types. Codon usage bias was influenced by both mutation and selection, with selection exerting a greater impact. The Spearman’s rank correlation coefficients between codon adaptation index and expression levels of sporangium, stem, leaf, and root were 0.1178, 0.3926, 0.4463, and 0.2945, respectively, with significance in stem and leaf ( P  < 0.05). The correlation coefficients between the nonsynonymous substitution rate (dN ) and expression levels in sporangium, stem, leaf, and root were -0.0840, -0.1786, -0.1714, and -0.0857, respectively, yet none are statistically significant. The correlation coefficient between the synonymous substitution rate ( dS ) and expression levels in sporangium was negative, whereas those between dS and the stem, leaf, and root were positive, although they were not significant. The dN / dS ratio exhibited a significant negative correlation with expression levels in both leaf and root ( P  < 0.05). Conclusions For the first time, our study revealed differences in the correlation between mitochondrial gene expression and codon usage bias, as well as evolutionary rates, across various tissues of O. vulgatum . Moreover, we also provide novel insights into understanding the effects of plant mitochondrial gene expression on evolutionary patterns.

Background Characterization of the key factors determining gene expression level has been of significant interest. Previous studies on the relationship among evolutionary rates, codon usage bias, and expression level mostly focused on either nuclear genes or unicellular/multicellular organisms but few in chloroplast (cp) genes. Ophioglossum vulgatum is a unique fern and has important scientific and medicinal values. In this study, we sequenced its cp genome and transcriptome to estimate the evolutionary rates ( dN and dS ), selective pressure ( dN / dS ), gene expression level, codon usage bias, and their correlations. Results The correlation coefficients between dN, dS, and dN / dS , and Transcripts Per Million (TPM) average values were -0.278 ( P  = 0.027 < 0.05), -0.331 ( P  = 0.008 < 0.05), and -0.311 ( P  = 0.013 < 0.05), respectively. The codon adaptation index (CAI) and tRNA adaptation index (tAI) were significantly positively correlated with TPM average values ( P  < 0.05). Conclusions Our results indicated that when the gene expression level was higher, the evolutionary rates and selective pressure were lower, but the codon usage bias was stronger. We provided evidence from cp gene data which supported the E-R (E stands for gene expression level and R stands for evolutionary rate) anti-correlation.

RNA editing is a crucial mechanism regulating gene expression in plant organellar genomes, which optimizes protein structures through base substitution and plays a vital role in plant growth, development, and stress adaptation. This study revises the conventional understanding restricting MORF proteins to seed plants by reporting their first identification in ferns, an early vascular plant lineage. We sequenced chloroplast genomes of O. japonica and P. vachellii, revealing one MORF9 homolog in O. japonica and three homologs (MORF1/8/9) in P. vachellii through comparative transcriptomics and structural validation. All identified MORF proteins harbor conserved MORF-box domains, suggesting structural and potentially functional conservation with angiosperms. Crucially, MORF members differentially regulate organellar RNA editing: chloroplast editing frequencies are predicted to show dose-dependent enhancement (0.7–1.0 in conserved sites), potentially influenced by MORF presence or copy number. In O. japonica, chloroplast editing exhibits tissue-specific patterns (conserved sites 0.7–1.0; tissue-specific sites lower efficiency at 0.1–0.2), while this study’s mitochondrial editing results show a balanced frequency distribution (0–1 range). Amino acid substitution analysis demonstrates MORF-mediated hydrophobic optimization (Ser→Leu > 30%, Pro→Leu > 18%), likely underpinning fern adaptability. This work provides crucial initial evidence for a conserved MORF-mediated RNA editing module shared between these early vascular plants (ferns) and angiosperms, offering fundamental insights into the evolutionary trajectory of plant organellar gene regulation.

Simple sequence repeats (SSRs) are found in nonrandom distributions in genomes and are thought to impact gene expression. The distribution patterns of 48 295 SSRs of Paphiopedilum malipoense are mined and characterized based on the first full‐length transcriptome and comprehensive transcriptome dataset from 12 organs. Statistical genomics analyses are used to investigate how SSRs in transcripts affect gene expression. The results demonstrate the correlations between SSR distributions, characteristics, and expression level. Nine expression‐modulating motifs (expMotifs) are identified and a model is proposed to explain the effect of their key features, potency, and gene function on an intra‐transcribed region scale. The expMotif‐transcribed region combination is the most predominant contributor to the expression‐modulating effect of SSRs, and some intra‐transcribed regions are critical for this effect. Genes containing the same type of expMotif‐SSR elements in the same transcribed region are likely linked in function, regulation, or evolution aspects. This study offers novel evidence to understand how SSRs regulate gene expression and provides potential regulatory elements for plant genetic engineering. Statistical genomics analyses reveal a high‐density SSR landscape of slipper orchid P. malipoense transcriptome. Transcribed SSRs can alter the gene expression potential and tissue‐specificity where they are located. The expression regulation effects of expMotifs are finely delineated, hotspots of expMotifs exist within the transcribed regions, and the mechanisms are illustrated by a model.

Ophioglossum vulgatum is a rare and ancient fern. In this study, the chloroplast (cp) genome of O. vulgatum was completely sequenced. The genome size is 138,562 bp, which contains a large single-copy (LSC) region with 99,351 bp, a small single-copy (SSC) region with 19,661 bp, and two inverted repeats (IR) regions of 9,775 bp each. Additionally, the overall GC content is 42.14%. It encodes a total 129 genes, including 84 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. The Bayesian phylogenetic tree shows that O. vulgatum and O. californicum formed a monophyletic branch. This study can provide a molecular basis for studying the phylogenetic genomics and population variation of Ophioglossaceae.

Illumina sequencing was employed to determine the complete chloroplast (cp) genome sequence of Sphaeropteris brunoniana (S. brunoniana), which is a relict fern. The cp genome of S. brunoniana is indeed a circular DNA molecule with 156,659 bp. It includes an inverted repeats (IRs) pair with 24,011 bp each and two single-copy regions with 86,196 bp and 22,441 bp, respectively. Additionally, the genome contains 117 unique genes encoding 85 proteins, 28 tRNAs, four rRNAs. Pseudogenes of ycf66 and trnT-UGU are also detected in this genome.Bayesian phylogenetic tree strongly supports the deduction that S. brunoniana belongs to Cyatheaceae. To date, this is the first cp genome for the genus S. brunoniana.

Genes with similar or related functions in chloroplasts are often arranged in close proximity, forming clusters on chromosomes. These clusters are transcribed coordinated to facilitate the expression of genes with specific function. Our previous study revealed a significant negative correlation between the chloroplast gene expression level of the rare medicinal fern Ophioglossum vulgatum and its evolutionary rates as well as selection pressure. Therefore, in this study, we employed a combination of SMRT and Illumina sequencing technology to analyze the full-length transcriptome sequencing of O. vulgatum for the first time. In particular, we experimentally identified gene clusters based on transcriptome data and investigated the effects of chloroplast gene clustering on expression and evolutionary patterns. The results revealed that the total sequenced data volume of the full-length transcriptome of O. vulgatum amounted to 71,950,652,163 bp, and 110 chloroplast genes received transcript coverage. Nine different types of gene clusters were experimentally identified in their transcripts. The chloroplast cluster genes may cause a decrease in non-synonymous substitution rate and selection pressure, as well as a reduction in transversion rate, transition rate, and their ratio. While expression levels of chloroplast cluster genes in leaf, sporangium, and stem would be relatively elevated. The Mann–Whitney U test indicated statistically significant in the selection pressure, sporangia and leaves groups (P < 0.05). We have contributed novel full-length transcriptome data resources for ferns, presenting new evidence on the effects of chloroplast gene clustering on expression land evolutionary patterns, and offering new theoretical support for transgenic research through gene clustering.Key messageThe clustering of chloroplast genes in Ophioglossum vulgatum demonstrates a tendency towards elevated expression levels in sporangium, leaf, and stem, while exhibiting a decline in evolutionary rates and selection pressure.

Most of the correlation filter based tracking algorithms can achieve good performance and maintain fast computational speed. However, in some complicated tracking scenes, there is a fatal defect that causes the object to be located inaccurately, which is the trackers excessively dependent on the maximum response value to determine the object location. In order to address this problem, we propose a particle filter redetection based tracking approach for accurate object localization. During the tracking process, the kernelized correlation filter (KCF) based tracker can locate the object by relying on the maximum response value of the response map; when the response map becomes ambiguous, the tracking result becomes unreliable correspondingly. Our redetection model can provide abundant object candidates by particle resampling strategy to detect the object accordingly. Additionally, for the target scale variation problem, we give a new object scale evaluation mechanism, which merely considers the differences between the maximum response values in consecutive frames to determine the scale change of the object target. Extensive experiments on OTB2013 and OTB2015 datasets demonstrate that the proposed tracker performs favorably in relation to the state-of-the-art methods.

Many plant mitochondrial (mt) genomes have been sequenced but few in ferns. Ophioglossum vulgatum represents a typical species of fern genus Ophioglossum with medicinal and scientific value. However, its mt genome structure remains to be characterized. This study assembled and annotated the complete O. vulgatum mt genome and presented its structural characters and repeat sequences firstly. Its mt and chloroplast (cp) transfer sequences were explored, and the phylogenetic significance of both mt and cp genomes was also evaluated at the family level. Our results showed that the complete mt genome of O. vulgatum is a single circular genome of 369,673 bp in length, containing 5000 dispersed repetitive sequences. Phylogenetic trees reconstructed from cp and mt genomes displayed similar topologies, but also showed subtle differences at certain nodes. There exist 4818 bp common gene fragments between cp and mt genomes, of which more than 70% are located in tRNA intergenic regions (in mt). In conclusion, we assembled the complete mt genome of O. vulgatum, identified its remarkable structural characters, and provided new insights on ferns. The complementary results derived from mt and cp phylogeny highlighted that some higher taxonomic-level phylogenetic relationships among ferns remain to be resolved.

This paper introduces a robust bi-orthogonal projection (RBOP) learning method for dimensionality reduction (DR). The proposed RBOP enhances the flexibility, robustness, and sparsity of the embedding framework, extending beyond traditional DR methods such as principal component analysis (PCA), neighborhood preserving embedding (NPE), and locality preserving projection (LPP). Unlike conventional approaches that rely on a single type of projection, RBOP innovates by employing two types of projections: the “true” projection and the “counterfeit” projection. These projections are crafted to be orthogonal, offering enhanced flexibility for the “true” projection and facilitating more precise data transformation in the process of subspace learning. By utilizing sparse reconstruction, the acquired true projection has the capability to map the data into a low-dimensional subspace while efficiently maintaining sparsity. Observing that the two projections share many similar data structures, the method aims to maintain the similarity structure of the data through distinct reconstruction processes. Additionally, the incorporation of a sparse component allows the method to address noise-corrupted data, compensating for noise during the DR process. Within this framework, a number of new unsupervised DR techniques have been developed, such as RBOP_PCA, RBOP_NPE, and RBO_LPP. Experimental results from both natural and synthetic datasets indicate that these proposed methods surpass existing, well-established DR techniques.