Organelle genomes serve as crucial datasets for investigating the genetics and evolution of plants and animals, genome diversity, and species identification. To enhance the collection, analysis, and visualization of such data, we have developed a novel open-source software tool named Organelle Genome Utilities (OGU). The software encompasses three modules designed to streamline the handling of organelle genome data. The data collection module is dedicated to retrieving, validating, and organizing sequence information. The evaluation module assesses sequence variance using a range of methods, including novel metrics termed stem and terminal phylogenetic diversity, as well as observed resolution. The primer module could design universal primers for downstream applications. Finally, a visualization pipeline has been developed to present comprehensive insights into organelle genomes across different lineages rather than focusing solely on individual species. The performance, compatibility, and stability of OGU have been rigorously evaluated through benchmarking with four datasets, including one million mixed GenBank records, plastid genomic data from the Lamiaceae family, mitochondrial data from rodents, and 308 plastid genomes sourced from various angiosperm families. Based on software capabilities, we have identified 30 plastid intergenic spacers that exhibit a moderate evolutionary rate and offer practical utility comparable to coding regions, which highlights the potential applications of intergenic spacers in organelle genomes. We anticipate that OGU will substantially enhance the efficient utilization of organelle genomic data and broaden the prospects for related research endeavors.

Desert areas occupy approximately 25% of total land area and are characterized by scarce precipitation, poor soil conditions, and a harsh ecological environment. Desertification may result in the loss of unique biological resources. Therefore, exploring the biodiversity of deserts and the causal factors of desertification is necessary to develop future solutions to global desertification. The desert area in northwest China is an important part of the arid zone of central Asia as it was traveled during the ancient Silk Road and witnessed the rise and fall of many civilizations, making it an ideal location for desertification research. This study utilized environmental DNA in the surface soil along the eastern part of the Silk Road and DNA metabarcoding technology. Bioinformatic analysis identified 782 plant species belonging to 505 genera and 133 families, and plant species diversity gradually decreased from east to west along the Silk Road. Temperature, altitude, and longitude were the main factors affecting plant species diversity in the area, while the impact of precipitation was relatively small. Correlation analysis between species diversity, population density, and major human settlements revealed that human activity significantly affected plant species diversity. Our study successfully used environmental DNA and metabarcoding technology to reveal the plant species diversity and its influencing factors for a large-scale desert area, which will provide a fundamental and theoretical basis for desert management and biodiversity protection.

Rice (genus Oryza) is one of the most important crops in the world, supporting half of the world’s population. Breeding of high-yielding and quality cultivars relies on genetic resources from both cultivated and wild species, which are collected and maintained in seed banks. Unfortunately, numerous seeds are mislabeled due to taxonomic issues or misidentifications. Here, we applied the phylogenomics of 58 complete chloroplast genomes and two hypervariable nuclear genes to determine species identity in rice seeds. Twenty-one Oryza species were identified. Conspecific relationships were determined between O. glaberrima and O. barthii, O. glumipatula and O. longistaminata, O. grandiglumis and O. alta, O. meyeriana and O. granulata, O. minuta and O. malampuzhaensis, O. nivara and O. sativa subsp. indica, and O. sativa subsp. japonica and O. rufipogon. D and L genome types were not found and the H genome type was extinct. Importantly, we evaluated the performance of four conventional plant DNA barcodes (matK, rbcL, psbA-trnH, and ITS), six rice-specific chloroplast DNA barcodes (psaJ-rpl33, rpoB-trnC, rps16-trnQ, rps19-rpl22, trnK-matK, and trnV-ndhC), two rice-specific nuclear DNA barcodes (NP78 and R22), and a chloroplast genome super DNA barcode. The latter was the most reliable marker. The six rice-specific chloroplast barcodes revealed that 17% of the 53 seed accessions from rice seed banks or field collections were mislabeled. These results are expected to clarify the concept of rice species, aid in the identification and use of rice germplasms, and support rice biodiversity.