Rapeseed (Brassica napus L.) is a major oil crop worldwide that is vigorously promoted for cultivation in China.  Boron (B) is an essential micronutrient for plant growth and development.  However, the agricultural soils in rapeseed planting areas often show either B deficiency or severe B deficiency.  Increasing the resistance to B deficiency is a pivotal goal in the breeding of rapeseed, yet the genetic basis for variations in B efficiency-related traits remains unclear.  In this study, a natural population with 391 rapeseed accessions and a nutrient solution system were used to investigate B efficiency-related traits, including relative root length (RRL), shoot dry weight (SDW), root dry weight (RDW), and B efficiency coefficient (BEC), all of which exhibited extensive phenotypic variations under B deficiency.  Through a genome-wide association study (GWAS) of B efficiency-related traits using high-density SNP markers obtained from whole-genome resequencing, 106 significantly associated SNPs were identified by employing both the general linear model and the mixed linear model.  Among these SNP loci, two prominent SNP clusters were detected on chrA03: 14,087,835–14,764,672 and chrC03: 20,110,319–22,135,492 at low B levels across three repeated experiments of multiple traits.  Integrating those results with a transcriptome analysis, four genes exhibiting higher differentially expressed fold-change along with favorable haplotypes within the promoter or coding region, BnaA03g29020D, BnaA03g29440D, BnaC03g33010D, and BnaC03g34490D, were identified as candidate genes that could potentially be involved in efficient B utilization, and their favorable haplotypes were found to improve seedling growth and productivity under B deficiency.  Considering the lack of B mineral resources in China, the rapid and accurate identification of more B-efficient alleles and studying the genetic mechanism underlying crop responses to B deficiency have important theoretical and practical significance for cultivating B-efficient varieties and maintaining green, sustainable agriculture.

Denitrification plays a critical role in mitigating anthropogenic nitrate (NO₃^–) accumulation in ecosystems.  The isotopic composition of NO₃^– (δ¹⁵N and δ¹⁸O) serves as a powerful tracer for identifying N sources and transformation processes.  Denitrification often superimposed on the isotope effects of NO₂^– oxidation, resulting in parallel enrichment of δ¹⁵N- and δ¹⁸O-NO₃^– (Δδ¹⁸O:Δδ¹⁵N trajectory) that causes them to be either below or above 1.  This study compared the Δδ¹⁸O:Δδ¹⁵N trajectory during denitrification, functional genes (narG, napA, and nxrA), and carbon sources from metabolites in the Δδ¹⁸O:Δδ¹⁵N trajectories below or above 1 in unsaturated zones.  The results revealed that NO₃^– reduction was more important for variation in the Δδ¹⁸O:Δδ¹⁵N trajectory because the difference in isotope effects (¹⁵ε_{NO3 reduction} and ¹⁸ε_{NO3 reduction}) between the two Δδ¹⁸O:Δδ¹⁵N trajectory groups was significant, whereas the difference in isotope effects (¹⁵ε_nxr and ¹⁸ε_nxr) upon NO₂^– oxidation was not.  Carbon sources in the group with Δδ¹⁸O:Δδ¹⁵N trajectories below 1 facilitated more efficient electron production to promote NO₃^– reduction because of their low molecular weight and simple structure.  Conversely, the lower electron production efficiency due to the high molecular weight and complex structures of carbon sources in the group with Δδ¹⁸O:Δδ¹⁵N trajectories above 1 downregulated the expression of the three functional genes (narG, napA, and nxrA).  The group with Δδ¹⁸O:Δδ¹⁵N trajectories below 1 showed significantly higher levels of ¹⁵ε_{NO3 reduction}, ¹⁸ε_{NO3 reduction}, NO₂^– oxidation ratio, and copy numbers of narG, napA, and nxrA genes compared to the other group, revealing that NO₃^– reduction at the cellular level was more active in the former group.  This study elucidated the integrated influence of isotope effects, NO₃^– reductase and NO₂^– oxidoreductase activities, and carbon sources from metabolites.  These findings are significant for understanding the Δδ¹⁸O:Δδ¹⁵N trajectories of N cycling in terrestrial ecosystems and support groundwater conservation by improving carbon supplementation approaches that stimulate denitrification, with Δδ¹⁸O:Δδ¹⁵N trajectories serving as effective tracers for assessing denitrification performance in terrestrial environments.

Cadmium (Cd) contamination in wheat farmland is increasing at an alarming rate, posing threats to food security and public health.  Breeding and utilizing wheat varieties characterized by low Cd accumulation levels constitute an effective strategy in the battle against wheat Cd contamination.  The adoption of molecular marker-assisted approaches can greatly expedite the selection and enhancement of wheat varieties with low Cd accumulation.  Nonetheless, research concerning the genes associated with wheat cadmium accumulation remains scarce.  In this study, a high-density 660K SNP array was employed for conducting a genome-wide association study (GWAS) on the grain Cd concentration (GCdC), bioconcentration factor (BCF) and translocation factor (TF) in 175 wheat germplasms.  The findings revealed 401 significant SNPs identified across three diverse environments.  Linkage disequilibrium analysis revealed 30 core quantitative trait loci (QTLs) capable of reliably modulating wheat Cd accumulation phenotypes.  Through gene annotation, transcriptomics, and gene molecular features, four candidate genes (TraesCS7B02G000200, TraesCS4A02G035900, TraesCS4A02G040900, and TraesCS5D02G564000) were identified as potential constituents in the biological process of wheat Cd accumulation.  Furthermore, six wheat germplasms exhibiting low grain Cd accumulation were isolated, and two kompetitive allele specific PCR (KASP) markers conducive to breeding selection were developed.  These findings provide valuable genetic resources for cultivating wheat with low Cd accumulation and establish a foundation for understanding the molecular mechanisms underlying low Cd accumulation in wheat.  The candidate genes and KASP markers elucidated in this research have potential for effective use in genetic enhancement and marker-assisted selection in the breeding of wheat with low Cd accumulation.

Oral immunization is an alternative or supplementary approach that can significantly improve dog vaccination coverage, especially for free-roaming dogs.  Safe and effective oral rabies vaccines for dogs are still being sought.  In our previous studies, we generated a genetically modified rabies virus (RABV) ERA strain, rERAG_333E, containing a mutation from arginine (Arg, R) to glutamic acid (Glu, E) at residue 333 of the G protein (G_333E).  Our previous results demonstrated that rERAG_333E was safe for adult mice and dogs, and oral vaccination with rERAG_333E induced a strong and long-lasting protective immune response in dogs.  Here, we further investigated the safety and immunogenicity of rERAG_333E in non-target species, including suckling mice, rhesus monkeys, foxes, raccoon dogs, piglets, goats, and sheep.  Suckling mice studies demonstrated that the G_333E mutation significantly reduced the virulence of the ERA strain.  All of the suckling mice aged 10 days and above survived and showed no apparent signs of disease after intracerebral inoculation with rERAG_333E.  Animal studies demonstrated that rERAG_333E was safe in rhesus monkeys, foxes, raccoon dogs, piglets, goats, and sheep.  None of those animals inoculated orally with 10 times the intended field dose of rERAG_333E showed abnormal clinical signs before and after the booster immunization with Rabvac 3, an inactivated rabies vaccine.  Meanwhile, oral inoculation with rERAG_333E induced strong neutralizing antibody (NA) responses to RABV in rhesus monkeys, foxes, raccoon dogs, and piglets.  These results demonstrated that rERAG_333E has the potential to serve as a safe oral rabies vaccine for dogs.

In 2013, peste des petits ruminants (PPR) re-emerged in China and spread to the majority of provinces across the country.  The disease was effectively controlled through a vaccination campaign employing live attenuated vaccines, although sporadic cases still occurred.  However, limited information is currently available regarding the peste des petits ruminants virus (PPRV) endemic in China.  Here, a PPRV strain (HLJ/13) was isolated from a field sample in China using Vero cells expressing goat signalling lymphocyte activation molecule.  Phylogenetic analysis indicated that HLJ/13 belonged to lineage IV.  Subsequent intranasal and subcutaneous inoculation of goats with a dose of 2×10⁶ TCID₅₀ of HLJ/13 resulted in the development of typical clinical symptoms of PPR, including pyrexia, ocular and nasal discharges, stomatitis, and diarrhea.  All infected goats succumbed to the disease by day 8.  To gain further insight, viral loading, pathological examination and immunohistochemical analyses were conducted, elucidating the main targets of HLJ/13 as the respiratory system, digestive tract and lymphoid organs.  Employing the goat infection model established above, the goat poxvirus-vectored PPR vaccine, which was previously developed and could be used as DIVA (differentiating infected from vaccinated animals) vaccine, provided complete protection against the challenge of HLJ/13.  It is important to note that this study represents the first comprehensive report delineating the biology and pathogenicity characterization, and infection model of PPRV isolated in China. 

Gossypium raimondii (2n=2x=26, D₅), an untapped wild species, is the putative progenitor of the D-subgenome of G. hirsutum (2n=4x=52, AD₁), an extensively cultivated species.  Here, we developed a G. hirsutum (recipient)–G. raimondii (donor) introgression population to exploit the favorable QTLs/genes and mapped potential quantitative trait loci (QTLs) from wild cotton species.  The introgression population consisted of 256 lines with an introgression rate of 52.33% for the G. raimondii genome.  The introgression segment length range was 0.03–19.12 Mb, with an average of 1.22 Mb.  The coverage of total introgression fragments from G. raimondii was 386.98 Mb.  Further genome-wide association analysis (Q+K+MLM) and QTL mapping (RSTEP-LRT) identified 59 common QTLs, including 14 stable QTLs and six common QTL (co-QTL) clusters, and one hotspot of micronaire (MIC).  The common QTLs for seed index all showed positive additive effects, while the common QTLs for boll weight all had negative additive effects, indicating that the linkage between seed index and boll weight could be broken.  QTLs for lint percentage showed positive effects and could be beneficial for improving cotton yield.  Most QTLs for fiber quality had negative additive effects, implying these QTLs were domesticated/improved in G. hirsutum.  A few fiber quality QTLs showed positive additive effects, so they could be used to improve cotton fiber quality.  The introgression lines developed could be useful for molecular marker-assisted breeding and mapping QTLs precisely for mining desirable genes from the wild species G. raimondii.  Such genes can improve cultivated cotton in the future through a design-breeding approach. 

The wheat above-ground biomass (AGB) is an important index that shows the life activity of vegetation, which is of great significance for wheat growth monitoring and yield prediction.  Traditional biomass estimation methods specifically include sample surveys and harvesting statistics.  Although these methods have high estimation accuracy, they are time-consuming, destructive, and difficult to implement to monitor the biomass at a large scale.  The main objective of this study is to optimize the traditional remote sensing methods to estimate the wheat AGB based on improved convolutional features (CFs).  Low-cost unmanned aerial vehicles (UAV) were used as the main data acquisition equipment.  This study acquired RGB and multi-spectral (MS) image data of the wheat population canopy for two wheat varieties and five key growth stages.  Then, field measurements were conducted to obtain the actual wheat biomass data for validation.  Based on the remote sensing indices (RSIs), structural features (SFs), and convolutional features (CFs), this study proposed a new feature named AUR-50 (Multi-source combination based on convolutional feature optimization) to estimate the wheat AGB.  The results show that AUR-50 could more accurately estimate the wheat AGB than RSIs and SFs, and the average R² exceeded 0.77.  AUR-50_MS had the highest estimation accuracy (R² of 0.88) in the overwintering period.  In addition, AUR-50 reduced the effect of the vegetation index saturation on the biomass estimation accuracy by adding CFs, where the highest R² was 0.69 at the flowering stage.  The results of this study provide an effective method to evaluate the AGB in wheat with high throughput and a research reference for the phenotypic parameters of other crops.

The application of a male-sterile line is an ideal approach for hybrid seed production in non-heading Chinese cabbage (Brassica rapa ssp. chinensis).  However, the molecular mechanisms underlying male sterility in B. rapa are still largely unclear.  We previously obtained the natural male sterile line WS24-3 of non-heading Chinese cabbage and located the male sterile locus, Bra2Ms, on the A2 chromosome.  Cytological observations revealed that the male sterility of WS24-3 resulted from disruption of the meiosis process during pollen formation.  Fine mapping of Bra2Ms delimited the locus within a physical distance of about 129 kb on the A2 chromosome of B. rapa.  The Bra039753 gene encodes a plant homeodomain (PHD)-finger protein and is considered a potential candidate gene for Bra2Ms.  Bra039753 was significantly downregulated in sterile line WS24-3 compared to the fertile line at the meiotic anther stage.  Sequence analysis of Bra039753 identified a 369 bp fragment insertion in the first exon in male sterile plants, which led to an amino acid insertion in the Bra039753 protein.  In addition, the 369 bp fragment insertion was found to cosegregate with the male sterility trait.  This study identified a novel locus related to male sterility in non-heading Chinese cabbage, and the molecular marker obtained in this study will be beneficial for the marker-assisted selection of excellent sterile lines in non-heading Chinese cabbage and other Brassica crops.

African swine fever (ASF) represents a highly contagious and fatal condition affecting both domestic and wild pigs, necessitating mandatory reporting status as designated by the World Organisation for Animal Health (WOAH). Currently, the primary strategy for preventing and controlling ASF revolves around early detection and stringent culling practices. However, the swift dissemination of ASF in both newly affected and previously impacted countries and regions underscores the absence of efficient measures to effectively curb the disease. To address this threat, a diverse array of methodologies is being employed globally in the pursuit of developing vaccines to combat ASF. In this context, we delve into the advancements achieved in ASF vaccine research over the past decade, encompassing the challenges and prospects associated with attenuated vaccines, subunit/live vector vaccines, and more. A profound comprehension of the virus's genetic diversity, pathogenic mechanisms, as well as the strengths and weaknesses of vaccine-induced immune protection, will pave the way for the development of novel vaccines in the future.

Here, we generated three recombinant replication-competent vaccinia virus (VACV) Western Reserve (WR) strains rWR-S6P, rWR-DS6P, and rWR-BA2S6P. These recombinant viruses express the prefusion-stabilized S proteins S6P, DS6P, and BA2S6P, which target the full-length S protein of the strain ancestor and variants Delta and Omicron BA.2 of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), respectively. These recombinant viruses maintained the growth property of the parental virus WR in CV-1 cells. A mouse study indicated that the insertion of these modified S genes reduced the virulence of the vector virus WR. Oral or intramuscular vaccination with rWR-S6P elicited a robust neutralizing antibody (NA) response against live SARS-CoV-2 and provided complete protection against the SARS-CoV-2 challenge in mice and minks. Of note, oral vaccination with rWR-S6P induced significantly higher titers of SARS-CoV-2 NAs and superior protective efficacy compared to intramuscular vaccination at an equivalent dose. More importantly, oral administration of rWR-S6P effectively prevents transmission of SARS-CoV-2 among minks via respiratory droplets. Furthermore, combined oral vaccination with three recombinant WRs induced a strong and long-lasting NA response against homotypic SARS-CoV-2 pseudovirus in mice without compromising their immunogenicity profiles. These findings indicate that the attenuated replication-competent VACV-vectored vaccines hold promise as effective oral COVID-19 vaccines for minks while demonstrating that combined vaccination is an effective administration strategy for preventing and controlling COVID-19.

Rift Valley fever virus (RVFV) is a highly virulent zoonotic pathogen posing substantial risks to global public health and livestock industries. Classified by the WHO as a priority pathogen with high pandemic potential, RVFV underscores the critical need for fundamental research to accelerate the development of vaccines and antiviral agents. In this study, we engineered a replication-defective RVFV system that preserves the capacity for host cell infection and a single round of genomic replication. Targeted deletion of the envelope glycoprotein genes Gn and Gc, together with the non-structural protein NSm resulted in a replication-incompetent virus capable of producing infectious particles only in trans-complementing cell lines engineered to express the missing components. This system enables safe experimentation under BSL-2 containment. By incorporating a biotin acceptor peptide (AP) tag into the viral L protein and leveraging biotin-streptavidin bridging for quantum dot conjugation, we developed a highly specific, protein-level labeling platform for single-virus tracking of RVFV. This advanced methodology permits real-time visualization of the viral life cycle from the point of cellular entry. Using this system, we have obtained the first live-cell imaging evidence that RVFV undergoes microtubule-dependent transport via endocytic vesicles during infection. Our findings provide unprecedented insight into the dynamic post-entry trafficking of RVFV and establish a versatile and safe strategy applicable to the study of other high-containment pathogens.

Being one of the most crucial food crops globally, accurate yield prediction of wheat is essential for ensuring food security, enabling precision agricultural management, and addressing climate change challenges. Previous studies mainly focused on single-period feature extraction or time-series remote sensing features for yield prediction, but lacked in-depth explanation of the yield formation mechanism. Therefore, this study aimed to develop a yield prediction model based on growth curve parameters of aboveground biomass (AGB). A logistic S-shaped growth curve was fitted using measured AGB, and key growth parameters (K, V_max, S_GIP, S_RIP, S_SIP, V_GIP, V_RIP, V_SIP, etc.) were extracted and integrated into machine learning models for yield prediction. Results showed that this approach achieved high accuracy (R²=0.97, RMSE=355.38 kg ha^-1, MAE=255.74 kg ha^-1), and the extracted parameters had clear physiological significance. To enable rapid AGB acquisition, an AGB estimation model was further developed using multi-source remote sensing features, including vegetation indices (VIs), texture indices (TIs), canopy structure (CS), and canopy temperature (CT). As the growing season progressed, these multi-source features exhibited strong complementarity, reaching the highest accuracy at 30 days after anthesis (R²=0.83) and effectively alleviating the saturation problem of VIs. Moreover, growth parameters derived from the fitted curves of the estimated AGB also achieved accurate yield prediction (R²=0.87, RMSE=746.07 kg ha^-1, MAE=570.16 kg ha^-1). The model further demonstrated stable performance across different regions and years (R²=0.85, RMSE=784.52 kg ha^-1, MAE=569.56 kg ha^-1). In conclusion, this study introduced novel AGB growth curve parameters for wheat yield estimation, which improved prediction accuracy and enhanced physiological interpretability, providing insights for efficient field-scale management and yield prediction across regions.