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.

There are criminal cases that no frequently used evidence, for example, DNAs from the criminal, is available. Such cases usually are unresolvable. With the advent of DNA metabarcoding, evidences are mined from environmental DNA and such cases become resolvable. This study reports how a criminal suspect was determined by environmental plant DNA metabarcoding technology. A girl was killed in a rural wet area in China without a witness or video record. Pants with dried mud was found from one of her boyfriend's house. The mud was removed from the pants and 11 more mud or soil samples surrounding murder scene were collected. DNA was extracted from the soil. Chloroplast rbcL gene fragments were amplified and sequenced on a next generation sequencing platform. Of the 2980 ZOTUs in total from the 12 samples, 1495 ZOTUs were identified to species, genera or families based on the existing public database. The feast analysis based on either taxa or taxa plus abundance data demonstrated that the mud on the suspect's pants was from the criminal scene. The suspect finally made a clean breast of his crime. This case implies that plant DNA in the environment soil is a new source of evidence in determination of suspects using DNA metabarcoding technology and has high potentials of extensive applications in criminal cases.

Plastid genomes are unique to plants and play an important role in genomics and evolutionary biology. Next-generation sequencing has revolutionized plastid genome data acquisition in a way that genome assembly and annotation became bottlenecks for large plastid genome data usage. Here we develop a novel open-source, cross-platform tool, NOVOWrap, with both command-line and graphical user interfaces for plastid genome automatic assembly using personal computers. With minimum inputs and user intervention, NOVOWrap could automatically assemble plastid genomes, validate results and standardize the structure with affordable computer resources. The performance of the software has been successfully benchmarked against eleven plastid genomes of species belonging to lycopods, gymnosperms, and angiosperms. The program is expected to liberate researchers from laborious computer manipulations and create reliable and standard genomic data.

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.