SynGenes: a Python class for standardizing nomenclatures of mitochondrial and chloroplast genes and a web form for enhancing searches for evolutionary analyses.

BACKGROUND: The reconstruction of the evolutionary history of organisms has been greatly influenced by the advent of molecular techniques, leading to a significant increase in studies utilizing genomic data from different species. However, the lack of standardization in gene nomenclature poses a challenge in database searches and evolutionary analyses, impacting the accuracy of results obtained. RESULTS: To address this issue, a Python class for standardizing gene nomenclatures, SynGenes, has been developed. It automatically recognizes and converts different nomenclature variations into a standardized form, facilitating comprehensive and accurate searches. Additionally, SynGenes offers a web form for individual searches using different names associated with the same gene. The SynGenes database contains a total of 545 gene name variations for mitochondrial and 2485 for chloroplasts genes, providing a valuable resource for researchers. CONCLUSIONS: The SynGenes platform offers a solution for standardizing gene nomenclatures of mitochondrial and chloroplast genes and providing a standardized search solution for specific markers in GenBank. Evaluation of SynGenes effectiveness through research conducted on GenBank and PubMedCentral demonstrated its ability to yield a greater number of outcomes compared to conventional searches, ensuring more comprehensive and accurate results. This tool is crucial for accurate database searches, and consequently, evolutionary analyses, addressing the challenges posed by non-standardized gene nomenclature.

Population identification and genetic diversity analysis of Fritillaria ussuriensis (Fritillaria) based on chloroplast genes atpF and petB.

The chloroplast genomes of five Fritillaria ussuriensis materials from different production areas were comparatively analyzed, atpF and petB were screened as specific DNA barcodes, and the population identification and genetic diversity of F. ussuriensis were analyzed based on them. The F. ussuriensis chloroplast genome showed a total length of 151 515-151 548 bp with a typical tetrad structure and encoded 130 genes. atpF and petB were used to amplify 183 samples from 13 populations, and they could identify 6 and 9 haplotypes, respectively. Joint analysis of the two sequences revealed 18 haplotypes, named H1-H18, with the most widely distributed and most abundant being H4. Ten haplotypes were unique for 7 populations that they could be used to distinguish from others. Haplotype diversity and nucleotide diversity were 0.99 and 2.09 × 10-3, respectively, indicating the genetic diversity was relatively rich. The results of the intermediary adjacency network showed that H5 was the oldest haplotype, and stellate radiation was centered around it, indicating that population expansion occurred in genuine production areas. This study lays a theoretical foundation for the population identification, genetic evolution, and breed selection of F. ussuriensis.

Full-length transcriptome analysis of Ophioglossum vulgatum: effects of experimentally identified chloroplast gene clusters on expression and evolutionary patterns.

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.

Chloroplast gene control: unlocking RNA thermometer mechanisms in photosynthetic systems.

RNA thermometers offer straightforward, protein-independent methods to regulate gene expression at the post-transcriptional level. In this context, Chung and colleagues have discovered a revolutionary RNA thermometer in the chloroplast genome of Chlamydomonas reinhardtii. This will facilitate temperature-driven control of inducible transgene expression for biotechnology applications in plant and algal systems.