The Cosmonaut Sea is one of the least accessed regions in the Southern Ocean, and our knowledge about the fish biodiversity in the region is sparse. In this study, we provided a description of demersal fish diversity in the Cosmonaut Sea by analysing cytochrome oxidase I (COI) barcodes of 98 fish samples that were hauled by trawling during the 37th and 38th Chinese National Antarctic Research Expedition (CHINARE) cruises. Twenty-four species representing 19 genera and 11 families, namely, Artedidraconidae, Bathydraconidae, Bathylagidae, Channichthyidae, Liparidae, Macrouridae, Muraenolepididae, Myctophidae, Nototheniidae, Paralepididae and Zoarcidae, were discriminated and identified, which were largely identical to local fish occurrence records and the general pattern of demersal fish communities at high Antarctic shelf areas. The validity of a barcoding gap failed to be detected and confirmed across all species due to the indicative signals of two potential cryptic species. Nevertheless, DNA barcoding still demonstrated to be a very efficient and sound method for the discrimination and classification of Antarctic fishes. In the future, various sampling strategies that cover all geographic sections and depth strata of the Cosmonaut Sea are encouraged to enhance our understanding of local fish communities, within which DNA barcoding can play an important role in either molecular taxonomy or the establishment of a dedicated local reference database for eDNA metabarcoding analyses.

Sheep and goat may become carriers of some zoonotic diseases. They are important livestock and experimental model animals for human beings. The fast and accurate identification of genetic materials originating from sheep and goat can prevent and inhibit the spread of some zoonotic diseases, monitor market product quality, and maintain the stability of animal husbandry and food industries. This study proposed a methodology for identifying sheep and goat common specific sites from a genome-wide perspective. A total of 150 specific sites were selected from three data sources, including the coding sequences of single copy genes from nine species (sheep, goat, cow, pig, dog, horse, human, mouse, and chicken), the dbSNPs for these species, and human 100-way alignment data. These 150 sites exhibited low intraspecific heterogeneity in the resequencing data of 1450 samples from five species (sheep, goat, cow, pig, and chicken) and high interspecific divergence in the human 100-way alignment data after quality control. The results were proven to be reliable at the data level. Using the process proposed in this study, specific sites of other species can be screened, and genome-level species identification can be performed using the screened sites.

Mushroom poisoning contributes significantly to global foodborne diseases and related fatalities. Amanita mushrooms frequently cause such poisonings; however, identifying these toxic species is challenging due to the unavailability of fresh and intact samples. It is often necessary to analyze residues, vomitus, or stomach extracts to obtain DNA sequences for the identification of species responsible for causing food poisoning. This usually proves challenging to obtain usable DNA sequences that can be analyzed using conventional molecular biology techniques. Therefore, this study aimed to develop a DNA mini-barcoding method for the identification of Amanita species. Following the evaluation and optimization of universal primers for DNA mini-barcoding in Amanita mushrooms, we found that the internal transcribed spacer (ITS) gene sequence primer ITS-a was the most suitable DNA barcode primer for identifying Amanita species. Forty-three Amanita samples were subsequently amplified and sequenced. The sequences obtained were analyzed for intra- and inter-species genetic distances, and a phylogenetic tree was constructed. The findings indicated that the designed primers had strong universality among the Amanita samples and could accurately identify the target gene fragment with a length of 290 bp. Notably, the DNA mini-barcode accurately identified the 43 Amanita samples, demonstrating high consistency with the conventional DNA barcode. Furthermore, it effectively identified DNA from digested samples. In summary, this DNA mini-barcode is a promising tool for detecting accidental ingestion of toxic Amanita mushrooms. It may be used as an optimal barcode for species identification and traceability in events of Amanita-induced mushroom poisoning. KEY POINTS: • Development of a DNA mini-barcoding method for Amanita species identification without fresh samples. • The ITS-a primer set was optimized for robust universality in Amanita samples. • The mini-barcode is suitable for screening toxic mushroom species in mushroom poisoning cases.

For species identification analysis, methods based on deep learning are becoming prevalent due to their data-driven and task-oriented nature. The most commonly used convolutional neural network (CNN) model has been well applied in Raman spectra recognition. However, when faced with similar molecules or functional groups, the features of overlapping peaks and weak peaks may not be fully extracted using the CNN model, which can potentially hinder accurate species identification. Based on these practical challenges, the fusion of multi-modal data can effectively meet the comprehensive and accurate analysis of actual samples when compared with single-modal data. In this study, we propose a double-branch CNN model by integrating Raman and image multi-modal data, named SI-DBNet. In addition, we have developed a one-dimensional convolutional neural network combining dilated convolutions and efficient channel attention mechanisms for spectral branching. The effectiveness of the model has been demonstrated using the Grad-CAM method to visualize the key regions concerned by the model. When compared to single-modal and multi-modal classification methods, our SI-DBNet model achieved superior performance with a classification accuracy of 98.8%. The proposed method provided a new reference for species identification based on multi-modal data fusion.

The integration of recombinase polymerase amplification (RPA) with CRISPR/Cas technology has revolutionized molecular diagnostics and pathogen detection due to its unparalleled sensitivity and trans-cleavage ability. However, its potential in the ecological and environmental monitoring scenarios for aquatic ecosystems remains largely unexplored, particularly in accurate qualitative/quantitative detection, and its actual performance in handling complex real environmental samples. Using zooplankton as a model, we have successfully optimized the RPA-CRISPR/Cas12a fluorescence detection platform (RPA-Cas-FQ), providing several crucial \"technical tips\". Our findings indicate the sensitivity of CRISPR/Cas12a alone is 5 × 109 copies/reaction, which can be dramatically increased to 5 copies/reaction when combined with RPA. The optimized RPA-Cas-FQ enables reliable qualitative and semi-quantitative detection within 50 min, and exhibits a good linear relationship between fluorescence intensity and DNA concentration (R2 = 0.956-0.974***). Additionally, we developed a rapid and straightforward identification procedure for single zooplankton by incorporating heat-lysis and DNA-barcode techniques. We evaluated the platform\'s effectiveness using real environmental DNA (eDNA) samples from the Three Gorges Reservoir, confirming its practicality. The eDNA-RPA-Cas-FQ demonstrated strong consistency (Kappa = 0.43***) with eDNA-Metabarcoding in detecting species presence/absence in the reservoir. Furthermore, the two semi-quantitative eDNA technologies showed a strong positive correlation (R2 = 0.58-0.87***). This platform also has the potential to monitor environmental pollutants by selecting appropriate indicator species. The novel insights and methodologies presented in this study represent a significant advancement in meeting the complex needs of aquatic ecosystem protection and monitoring.

Scorpio, a commonly used animal medicine in China, is derived from Buthus martensii as recorded in the Chinese Pharmacopoeia. China harbors rich species of Scorpionida and adulterants exist in the raw medicinal material and deep-processed products of Scorpio. The microscopic characteristics of the deep-processed products may be incomplete or lost during processing, which makes the identification difficult. In this study, the maximum likelihood(ML) tree was constructed based on the morphology and cytochrome C oxidase subunit I(COⅠ) to identify the species of Scorpio products. The results showed that the main adulterant of Scorpio was Lychas mucronatus. According to the specific SNP sites in the COⅠ sequence of B. martensii, the stable primers were designed for the identification of the medicinal material and formula granules of Scorpio. The polymerase chain reaction(PCR) at the annealing temperature of 61 ℃ and 30 cycles produced bright specific bands at about 150 bp for both B. martensii and its formula particles and no band for adulterants. The adaptability of the method was investigated, which showed that the bands at about 150 bp were produced for Scorpio medicinal material, lyophilized powder, and formula granules, and commercially available formula granules. The results showed that the established method could be used to identify the adulterants of Scorpio and its formula granules, which could help to improve the quality control system and ensure the safe clinical application of Scorpio formula granules.

BACKGROUND: The genus Caragana encompasses multiple plant species that possess medicinal and ecological value. However, some species of Caragana are quite similar in morphology, so identifying species in this genus based on their morphological characteristics is considerably complex. In our research, illumina paired-end sequencing was employed to investigate the genetic organization and structure of Caragana tibetica and Caragana turkestanica, including the previously published chloroplast genome sequence of 7 Caragana plants.
RESULTS: The lengths of C. tibetica and C. turkestanica chloroplast genomes were 128,433 bp and 129,453 bp, respectively. The absence of inverted repeat sequences in these two species categorizes them under the inverted repeat loss clade (IRLC). They encode 110 and 111 genes (4 /4 rRNA genes, 30 /31tRNA genes, and 76 /76 protein-coding genes), respectively. Comparison of the chloroplast genomes of C. tibetica and C. turkestanica with 7 other Caragana species revealed a high overall sequence similarity. However, some divergence was observed between certain intergenic regions (matK-rbcL, psbD-psbM, atpA-psbI, and etc.). Nucleotide diversity (π) analysis revealed the detection of five highly likely variable regions, namely rps2-atpI, accD-psaI-ycf4, cemA-petA, psbN-psbH and rpoA-rps11. Phylogenetic analysis revealed that C. tibetica\'s sister species is Caragana jubata, whereas C. turkestanica\'s closest relative is Caragana arborescens.
CONCLUSIONS: The present study provides worthwhile information about the chloroplast genomes of C. tibetica and C. turkestanica, which aids in the identification and classification of Caragana species.

The classification system for the genus Aconitum is highly complex. It is also the subject of ongoing debate. Aconitum pendulum Busch and Aconitum flavum Hand.-Mazz. are perennial herbs of the genus Aconitum. Dried roots of these two plants are used in traditional Chinese medicine. In this study, morphological observations and ISSR molecular markers were employed to discriminate between A. flavum and A. pendulum, with the objective of gaining insights into the interspecies classification of Aconitum. The pubescence on the inflorescence of A. flavum was found to be appressed, while that on the inflorescence of A. pendulum was spread. UPGMA (unweighted pair-group method with arithmetic average) cluster analysis, PCoA (principal coordinates analysis), and Bayesian structural analysis divided the 199 individuals (99 individuals from DWM population and 100 individuals from QHL population) into two main branches, which is consistent with the observations of the morphology of pubescence on the inflorescence. These analyses indicated that A. flavum and A. pendulum are distinct species. No diagnostic bands were found between the two species. Two primer combinations (UBC808 and UBC853) were ultimately selected for species identification of A. flavum and A. pendulum. This study revealed high levels of genetic diversity in both A. flavum (He = 0.254, I = 0.395, PPB = 95.85%) and A. pendulum (He = 0.291, I = 0.445, PPB = 94.58%). We may say, therefore, that ISSR molecular markers are useful for distinguishing A. flavum and A. pendulum, and they are also suitable for revealing genetic diversity and population structure.

BACKGROUND: Rapid identification and classification of bats are critical for practical applications. However, species identification of bats is a typically detrimental and time-consuming manual task that depends on taxonomists and well-trained experts. Deep Convolutional Neural Networks (DCNNs) provide a practical approach for the extraction of the visual features and classification of objects, with potential application for bat classification.
RESULTS: In this study, we investigated the capability of deep learning models to classify 7 horseshoe bat taxa (CHIROPTERA: Rhinolophus) from Southern China. We constructed an image dataset of 879 front, oblique, and lateral targeted facial images of live individuals collected during surveys between 2012 and 2021. All images were taken using a standard photograph protocol and setting aimed at enhancing the effectiveness of the DCNNs classification. The results demonstrated that our customized VGG16-CBAM model achieved up to 92.15% classification accuracy with better performance than other mainstream models. Furthermore, the Grad-CAM visualization reveals that the model pays more attention to the taxonomic key regions in the decision-making process, and these regions are often preferred by bat taxonomists for the classification of horseshoe bats, corroborating the validity of our methods.
CONCLUSIONS: Our finding will inspire further research on image-based automatic classification of chiropteran species for early detection and potential application in taxonomy.

DNA-based methods are reliable for a precise identification of species in processed products. In this study, we assessed five typical DNA extraction methods from multiple aspects. Full-length and mini-length DNA barcoding were performed to detect the species substitution and mislabeling of 305 processed fish products from the Chinese market covering six processed fish products. The salt extraction method that exhibited the best overall performance was applied. All samples were successfully extracted; however, only 19.3 % of samples could be amplified using the full-DNA barcode primer set, and 90.2 % of samples could be amplified using the newly designed mini-DNA barcode primer sets (401 and 320 bp). Overall, the molecular identification results revealed that 36.4 % (111/305) of the samples were inconsistent with the labels, with commercial fraud observed in all six types of processed fish products. The survey findings provide technical references for effective fish authentication monitoring, offering insights into the seafood safety in markets.