Quantitative Trait Locus Mapping for Plant Height and Branch Number in CCRI70 Recombinant Inbred Line Population of Upland Cotton (Gossypium hirsutum).

Upland cotton accounts for a high percentage (95%) of the world's cotton production. Plant height (PH) and branch number (BN) are two important agronomic traits that have an impact on improving the level of cotton mechanical harvesting and cotton yield. In this research, a recombinant inbred line (RIL) population with 250 lines developed from the variety CCRI70 was used for constructing a high-density genetic map and identification of quantitative trait locus (QTL). The results showed that the map harbored 8298 single nucleotide polymorphism (SNP) markers, spanning a total distance of 4876.70 centimorgans (cMs). A total of 69 QTLs for PH (9 stable) and 63 for BN (11 stable) were identified and only one for PH was reported in previous studies. The QTLs for PH and BN harbored 495 and 446 genes, respectively. Combining the annotation information, expression patterns and previous studies of these genes, six genes could be considered as potential candidate genes for PH and BN. The results could be helpful for cotton researchers to better understand the genetic mechanism of PH and BN development, as well as provide valuable genetic resources for cotton breeders to manipulate cotton plant architecture to meet future demands.

AK-MADDPG-Based Antijamming Strategy Design Method for Frequency Agile Radar.

Frequency agility refers to the rapid variation of the carrier frequency of adjacent pulses, which is an effective radar active antijamming method against frequency spot jamming. Variation patterns of traditional pseudo-random frequency hopping methods are susceptible to analysis and decryption, rendering them ineffective against increasingly sophisticated jamming strategies. Although existing reinforcement learning-based methods can adaptively optimize frequency hopping strategies, they are limited in adapting to the diversity and dynamics of jamming strategies, resulting in poor performance in the face of complex unknown jamming strategies. This paper proposes an AK-MADDPG (Adaptive K-th order history-based Multi-Agent Deep Deterministic Policy Gradient) method for designing frequency hopping strategies in frequency agile radar. Signal pulses within a coherent processing interval are treated as agents, learning to optimize their hopping strategies in the case of unknown jamming strategies. Agents dynamically adjust their carrier frequencies to evade jamming and collaborate with others to enhance antijamming efficacy. This approach exploits cooperative relationships among the pulses, providing additional information for optimized frequency hopping strategies. In addition, an adaptive K-th order history method has been introduced into the algorithm to capture long-term dependencies in sequential data. Simulation results demonstrate the superior performance of the proposed method.

Nanoparticle vaccines based on the receptor binding domain of porcine deltacoronavirus elicit robust protective immune responses in mice.

Background: Porcine deltacoronavirus (PDCoV), a novel swine enteropathogenic coronavirus, challenges the global swine industry. Currently, there are no approaches preventing swine from PDCoV infection. Methods: A new PDCoV strain named JS2211 was isolated. Next, the dimer receptor binding domain of PDCoV spike protein (RBD-dimer) was expressed using the prokaryotic expression system, and a novel nanoparticle containing RBD-dimer and ferritin (SC-Fe) was constructed using the SpyTag/SpyCatcher system. Finally, the immunoprotection of RBD-Fe nanoparticles was evaluated in mice. Results: The novel PDCoV strain was located in the clade of the late Chinese isolate strains and close to the United States strains. The RBD-Fe nanoparticles were successfully established. Immune responses of the homologous prime-boost regime showed that RBD-Fe nanoparticles efficiently elicited specific humoral and cellular immune responses in mice. Notably, high level PDCoV RBD-specific IgG and neutralizing antibody (NA) could be detected, and the histopathological results showed that PDCoV infection was dramatically reduced in mice immunized with RBD-Fe nanoparticles. Conclusion: This study effectively developed a candidate nanoparticle with receptor binding domain of PDCoV spike protein that offers protection against PDCoV infection in mice.

An adenovirus-vectored vaccine based on the N protein of feline coronavirus elicit robust protective immune responses.

Feline coronavirus (FCoV) is an unsegmented, single-stranded RNA virus belonging to the Alphacoronavirus genus. It can cause fatal feline infectious peritonitis (FIP) in cats of any ages. Currently, there are no effective prevention and control measures to against FCoV. In this study, we developed a recombinant adenovirus vaccine, AD5-N, based on the nucleocapsid(N) protein of FCoV. The immunogenicity of AD5-N was evaluated through intramuscular immunization in 6-week-old Balb/c mice and 9-12 months old cats. Compared to the control group, AD5-N specifically induced a significant increase in IgG and SIgA levels in the vaccinated mice. Furthermore, AD5-N not only effectively promoted strong cellular immune responses in cats but also induced high levels of specific SIgA, effectively helping cats resist FCoV infection. Our findings suggest that adenovirus vector vaccines based on the N gene have the potential to become candidate vaccines for the prevention and control of FCoV infection.

Fine mapping and candidate gene analysis of qFL-A12-5: a fiber length-related QTL introgressed from Gossypium barbadense into Gossypium hirsutum.

KEY MESSAGE: The fiber length-related qFL-A12-5 identified in CSSLs introgressed from Gossypium barbadense into Gossypium hirsutum was fine-mapped to an 18.8 kb region on chromosome A12, leading to the identification of the GhTPR gene as a potential regulator of cotton fiber length. Fiber length is a key determinant of fiber quality in cotton, and it is a key target of artificial selection for breeding and domestication. Although many fiber length-related quantitative trait loci have been identified, there are few reports on their fine mapping or candidate gene validation, thus hampering efforts to understand the mechanistic basis of cotton fiber development. Our previous study identified the qFL-A12-5 associated with superior fiber quality on chromosome A12 in the chromosome segment substitution line (CSSL) MBI7747 (BC4F3:5). A single segment substitution line (CSSL-106) screened from BC6F2 was backcrossed to construct a larger segregation population with its recurrent parent CCRI45, thus enabling the fine mapping of 2852 BC7F2 individuals using denser simple sequence repeat markers to narrow the qFL-A12-5 to an 18.8 kb region of the genome, in which six annotated genes were identified in Gossypium hirsutum. Quantitative real-time PCR and comparative analyses led to the identification of GH_A12G2192 (GhTPR) encoding a tetratricopeptide repeat-like superfamily protein as a promising candidate gene for qFL-A12-5. A comparative analysis of the protein-coding regions of GhTPR among Hai1, MBI7747, and CCRI45 revealed two non-synonymous mutations. The overexpression of GhTPR resulted in longer roots in Arabidopsis, suggesting that GhTPR may regulate cotton fiber development. These results provide a foundation for future efforts to improve cotton fiber length.

AAQSP increases mapping resolution of stable QTLs through applying NGS-BSA in multiple genetic backgrounds.

KEY MESSAGE: In this study, we present AAQSP as an extension of existing NGS-BSA applications for identifying stable QTLs at high resolution. GhPAP16 and GhIQD14 fine mapped on chromosome D09 of upland cotton are identified as important candidate genes for lint percentage (LP). Bulked segregant analysis combined with next generation sequencing (NGS-BSA) allows rapid identification of genome sequence differences responsible for phenotypic variation. The NGS-BSA approach applied to crops mainly depends on comparing two bulked DNA samples of individuals from an F2 population. Since some F2 individuals still maintain high heterozygosity, heterosis will exert complications in pursuing NGS-BSA in such populations. In addition, the genetic background influences the stability of gene expression in crops, so some QTLs mapped in one segregating population may not be widely applied in crop improvement. The AAQSP (Association Analysis of QTL-seq on Semi-homologous Populations) reported in our study combines the optimized scheme of constructing BSA bulks with NGS-BSA analysis in two (or more) different parental genetic backgrounds for isolating the stable QTLs. With application of AAQSP strategy and construction of a high-density linkage map, we have successfully identified a QTL significantly related to lint percentage (LP) in cultivated upland cotton, followed by map-based cloning to dissect two candidate genes, GhPAP16 and GhIQD14. This study demonstrated that AAQSP can efficiently identify stable QTLs for complex traits of interest, and thus accelerate the genetic improvement of upland cotton and other crop plants.

Linkage and association analyses reveal that hub genes in energy-flow and lipid biosynthesis pathways form a cluster in upland cotton.

Upland cotton is an important allotetraploid crop that provides both natural fiber for the textile industry and edible vegetable oil for the food or feed industry. To better understand the genetic mechanism that regulates the biosynthesis of storage oil in cottonseed, we identified the genes harbored in the major quantitative trait loci/nucleotides (QTLs/QTNs) of kernel oil content (KOC) in cottonseed via both multiple linkage analyses and genome-wide association studies (GWAS). In 'CCRI70' RILs, six stable QTLs were simultaneously identified by linkage analysis of CHIP and SLAF-seq strategies. In '0-153' RILs, eight stable QTLs were detected by consensus linkage analysis integrating multiple strategies. In the natural panel, thirteen and eight loci were associated across multiple environments with two algorithms of GWAS. Within the confidence interval of a major common QTL on chromosome 3, six genes were identified as participating in the interaction network highly correlated with cottonseed KOC. Further observations of gene differential expression showed that four of the genes, LtnD, PGK, LPLAT1, and PAH2, formed hub genes and two of them, FER and RAV1, formed the key genes in the interaction network. Sequence variations in the coding regions of LtnD, FER, PGK, LPLAT1, and PAH2 genes may support their regulatory effects on oil accumulation in mature cottonseed. Taken together, clustering of the hub genes in the lipid biosynthesis interaction network provides new insights to understanding the mechanism of fatty acid biosynthesis and TAG assembly and to further genetic improvement projects for the KOC in cottonseeds.

The effect of a loading dose of meropenem on outcomes of patients with sepsis treated by continuous renal replacement: study protocol for a randomized controlled trial.

BACKGROUND: Sepsis and continuous renal replacement therapy (CRRT) are both responsible for the alterations of the pharmacokinetics of antibiotics. For patients with sepsis receiving CRRT, the serum concentrations of meropenem in the early phase (< 48 h) was significantly lower than that in the late phase (> 48 h). This current trial aimed to investigate whether administration of a loading dose of meropenem results in a more likely achievement of the pharmacokinetic (PK)/pharmacodynamics (PD) target (100% fT > 4 × MIC) and better therapeutic results in the patients with sepsis receiving CRRT. METHODS: This is a single-blinded, single-center, randomized, controlled, two-arm, and parallel-group trial. This trial will be carried out in Guangzhou First People's Hospital, School of Medicine, South China University of Technology Guangdong, China. Adult patients (age ≥ 18 years) with critical sepsis or sepsis-related shock receiving CRRT will be included in the study. The subjects will be assigned to the control group and the intervention group (LD group) randomly at a 1:1 ratio, the estimated sample size should be 120 subjects in each group. In the LD group, the patient will receive a loading dose of 1.5-g meropenem resolved in 30-ml saline which is given via central line for 30 min. Afterward, 0.75-g meropenem will be given immediately for 30 min every 8 h. In the control group, the patient will receive 0.75-g meropenem for 30 min every 8 h. The primary objective is the probabilities of PK/PD target (100% fT > 4 × MIC) achieved in the septic patients who receive CRRT in the first 48 h. Secondary objectives include clinical cure rate, bacterial clearance rate, sepsis-related mortality and all-cause mortality, the total dose of meropenem, duration of meropenem treatment, duration of CRRT, Sequential Organ Failure Assessment (SOFA), C-reactive protein levels, procalcitonin levels, white blood cell count, and safety. DISCUSSION: This trial will assess for the first time whether administration of a loading dose of meropenem results in a more likely achievement of the PK/PD target and better therapeutic results in the patients with sepsis receiving CRRT. Since CRRT is an important therapeutic strategy for sepsis patients with hemodynamic instability, the results from this trial may help to provide evidence-based therapy for septic patients receiving CRRT. TRIAL REGISTRATION: Chinese Clinical Trials Registry, ChiCTR2000032865 . Registered on 13 May 2020, http://www.chictr.org.cn/showproj.aspx?proj=53616 .

Whole-Transcriptome Profiling and circRNA-miRNA-mRNA Regulatory Networks in B-Cell Development.

The generation and differentiation of B lymphocytes (B cells) is a flexible process with many critical regulatory factors. Previous studies indicated that non-coding RNAs play multiple roles in the development of lymphocytes. However, little has been known about the circular RNA (circRNA) profiles and their competing endogenous RNA (ceRNA) networks in B-cell development and differentiation. Here, four B-cell subsets were purified from single-cell suspensions of mouse bone marrow. Then RNA sequencing (RNA-Seq) was used to display expression profiles of circRNAs, miRNAs and mRNAs during B-cell differentiation. 175, 203, 219 and 207 circRNAs were specifically expressed in pro-B cells, pre-B cells, immature B cells and mature B cells, respectively. The circRNA-associated ceRNA networks constructed in two sequential stages of B-cell differentiation revealed the potential mechanism of circRNAs in these processes. This study is the first to explore circRNA profiles and circRNA-miRNA-mRNA networks in different B-cell developmental stages of mouse bone marrow, which contribute to further research on their mechanism in B-cell development and differentiation.

Multi-environment Evaluations Across Ecological Regions Reveal That the Kernel Oil Content of Cottonseed Is Equally Determined by Genotype and Environment.

Cotton is the fifth-largest oil crop in the world. A high kernel oil content (KOC) and high stability are important cottonseed attributes for food security. In this study, the phenotype of KOC and the genotype-by-environment interaction factors were collectively dissected using 250 recombinant inbred lines, their parental cultivars sGK156 and 901-001, and CCRI70 across multi-environments. ANOVA and correlation analysis showed that both genotype and environment contributed significantly to KOC accumulation. Analyses of additive main effect multiplicative interaction and genotype-by-environment interaction biplot models presented the effects of genotype, environment, and genotype by environment on KOC performance and the stability of the experimental materials. Interaction network analysis revealed that meteorological and geographical factors explained 38% of the total KOC variance, with average daily rainfall contributing the largest positive impact and cumulative rainfall having the largest negative impact on KOC accumulation. This study provides insight into KOC accumulation and could direct selection strategies for improved KOC and field management of cottonseed in the future.

Network-driven targeted analysis reveals that Astragali Radix alleviates doxorubicin-induced cardiotoxicity by maintaining fatty acid homeostasis.

ETHNOPHARMACOLOGICAL RELEVANCE: Astragali Radix (AR) is a popular traditional Chinese medicine that has been used for more than 2000 years. It is a well-known tonic for weak people with chronic diseases, such as heart failure and cerebral ischemia. Previous studies have reported that AR could support the "weak heart" of cancer patients who suffered from doxorubicin (DOX)-induced cardiotoxicity (DIC). However, the underlying mechanism remains unclear. AIM OF THE STUDY: This study aimed to uncover the critical pathways and molecular determinants for AR against DIC by fully characterizing the network-based relationship. MATERIALS AND METHODS: We integrated ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) profiling, database and literature searching, and the human protein-protein interactome to discover the specific network module associated with AR against DIC. To validate the network-based findings, a low-dose, long-term DIC mouse model and rat cardiomyoblast H9c2 cells were employed. The levels of potential key metabolites and proteins in hearts and cells were quantified by the LC-MS/MS targeted analysis and western blotting, respectively. RESULTS: We constructed one of the most comprehensive AR component-target network described to date, which included 730 interactions connecting 64 unique components and 359 unique targets. Relying on the network-based evaluation, we identified fatty acid metabolism as a putative critical pathway and peroxisome proliferator-activated receptors (PPARα and PPARγ) as potential molecular determinants. We then confirmed that DOX caused the accumulation of fatty acids in the mouse failing heart, while AR promoted fatty acid metabolism and preserved heart function. By inhibiting PPARγ in H9c2 cells, we further found that AR could alleviate DIC by activating PPARγ to maintain fatty acid homeostasis. CONCLUSIONS: Our findings imply that AR is a promising drug candidate that treats DIC by maintaining fatty acid homeostasis. More importantly, the network-based method developed here could facilitate the mechanism discovery of AR therapy and help catalyze innovation in its clinical application.

Identification and analysis of oil candidate genes reveals the molecular basis of cottonseed oil accumulation in Gossypium hirsutum L.

KEY MESSAGE: Based on the integration of QTL-mapping and regulatory network analyses, five high-confidence stable QTL regions, six candidate genes and two microRNAs that potentially affect the cottonseed oil content were discovered. Cottonseed oil is increasingly becoming a promising target for edible oil with its high content of unsaturated fatty acids. In this study, a recombinant inbred line (RIL) cotton population was constructed to detect quantitative trait loci (QTLs) for the cottonseed oil content. A total of 39 QTLs were detected across eight different environments, of which five QTLs were stable. Forty-three candidate genes potentially involved in carbon metabolism, fatty acid synthesis and triacylglycerol biosynthesis processes were further obtained in the stable QTL regions. Transcriptome analysis showed that nineteen of these candidate genes expressed during  the developing cottonseed ovules and may affect the cottonseed oil content. Besides, transcription factor (TF) and microRNA (miRNA) co-regulatory network analyses based on the nineteen candidate genes suggested that six genes, two core miRNAs (ghr-miR2949b and ghr-miR2949c), and one TF GhHSL1 were considered to be closely associated with the cottonseed oil content. Moreover, four vital genes were validated by quantitative real-time PCR (qRT-PCR). These results provide insights into the oil accumulation mechanism in developing cottonseed ovules through the construction of a detailed oil accumulation model.

Predicting the grades of Astragali radix using mass spectrometry-based metabolomics and machine learning.

Astragali radix (AR, the dried root of Astragalus) is a popular herbal remedy in both China and the United States. The commercially available AR is commonly classified into premium graded (PG) and ungraded (UG) ones only according to the appearance. To uncover novel sensitive and specific markers for AR grading, we took the integrated mass spectrometry-based untargeted and targeted metabolomics approaches to characterize chemical features of PG and UG samples in a discovery set (n=16 batches). A series of five differential compounds were screened out by univariate statistical analysis, including arginine, calycosin, ononin, formononetin, and astragaloside Ⅳ, most of which were observed to be accumulated in PG samples except for astragaloside Ⅳ. Then, we performed machine learning on the quantification data of five compounds and constructed a logistic regression prediction model. Finally, the external validation in an independent validation set of AR (n=20 batches) verified that the five compounds, as well as the model, had strong capability to distinguish the two grades of AR, with the prediction accuracy > 90%. Our findings present a panel of meaningful candidate markers that would significantly catalyze the innovation in AR grading.

Transformation and Overexpression of Primary Cell Wall Synthesis-Related Zinc Finger Gene Gh_A07G1537 to Improve Fiber Length in Cotton.

Molecular interventions have helped to explore the genes involved in fiber length, fiber strength, and other quality parameters with improved characteristics, particularly in cotton. The current study is an extension and functional validation of previous findings that Gh_A07G1537 influences fiber length in cotton using a chromosomal segment substitution line MBI7747 through RNA-seq data. The recombinant Gh_A07G1537 derived from the MBI7747 line was over-expressed in CCRI24, a genotype with a low profile of fiber quality parameters. Putative transformants were selected on MS medium containing hygromycin (25mg/ml), acclimatized, and shifted to a greenhouse for further growth and proliferation. Transgene integration was validated through PCR and Southern Blot analysis. Stable integration of the transgene (ΔGh_A07G1537) was validated by tracking its expression in different generations (T0, T1, and T2) of transformed cotton plants. It was found to be 2.97-, 2.86-, and 2.92-folds higher expression in T0, T1, and T2 plants, respectively, of transgenic compared with non-transgenic cotton plants. Fiber quality parameters were also observed to be improved in the engineered cotton line. Genetic modifications of Gh_A07G1537 support the improvement in fiber quality parameters and should be appreciated for the textile industry.

Attenuation of doxorubicin-induced oxidative damage in rat brain by regulating amino acid homeostasis with Astragali Radix.

The nervous system disorders caused by doxorubicin (DOX) are among the severe adverse effects that dramatically reduce the quality of life of cancer survivors. Astragali Radix (AR), a popular herbal drug and dietary supplement, is believed to help treat brain diseases by reducing oxidative stress and maintaining metabolic homeostasis. Here we show the protective effects of AR against DOX-induced oxidative damage in rat brain via regulating amino acid homeostasis. By constructing a clinically relevant low-dose DOX-induced toxicity rat model, we first performed an untargeted metabolomics analysis to discover specific metabolic features in the brain after DOX treatment and AR co-treatment. It was found that the amino acid (AA) metabolism pathways altered most significantly. To accurately characterize the brain AA profile, we established a sensitive, fast, and reproducible hydrophilic interaction chromatography-tandem mass spectrometry method for the simultaneous quantification of 22 AAs. The targeted analysis further confirmed the changes of AAs between different groups of rat brain. Specifically, the levels of six AAs, including glutamate, glycine, serine, alanine, citrulline, and ornithine, correlated (Pearson |r| > 0.47, p < 0.05) with the brain oxidative damage that was caused by DOX and rescued by AR. These findings present that AAs are among the regulatory targets of DOX-induced brain toxicity, and AR is a promising therapeutic agent for it.

Identification of hub genes through co-expression network of major QTLs of fiber length and strength traits in multiple RIL populations of cotton.

The present study demonstrated a de novo correlation among fiber quality genes in multiple RIL populations including sGK9708 × 0-153, LMY22 × LY343 and Lumianyan28 × Xinluzao24. The current study was conducted to identify the major common QTLs including fiber length and strength, and to identify the co-expression networks of fiber length and strength QTLs harbored genes to target the hub genes. The RNA-seq data of sGK9708 × 0-153 population highlighted 50 and 48 candidate genes of fiber length and fiber strength QTLs. A total of 29 and 21 hub genes were identified in fiber length and strength co-expression network modules. The absolute values of correlation coefficient close to 1 resulted highly positive correlation among hub genes. Results also suggested that the gene correlation significantly influence the gene expression at different fiber development stages. These results might provide useful reference for further experiments in multiple RIL populations and suggest potential candidate genes for functional studies in cotton.

Quantitative Trait Loci and Transcriptome Analysis Reveal Genetic Basis of Fiber Quality Traits in CCRI70 RIL Population of Gossypium hirsutum.

Upland cotton (Gossypium hirsutum) is widely planted around the world for its natural fiber, and producing high-quality fiber is essential for the textile industry. CCRI70 is a hybrid cotton plant harboring superior yield and fiber quality, whose recombinant inbred line (RIL) population was developed from two upland cotton varieties (sGK156 and 901-001) and were used here to investigate the source of high-quality related alleles. Based on the material of the whole population, a high-density genetic map was constructed using specific locus-amplified fragment sequencing (SLAF-seq). It contained 24,425 single nucleotide polymorphism (SNP) markers, spanning a distance of 4,850.47 centimorgans (cM) over 26 chromosomes with an average marker interval of 0.20 cM. In evaluating three fiber quality traits in nine environments to detect multiple environments stable quantitative trait loci (QTLs), we found 289 QTLs, of which 36 of them were stable QTLs and 18 were novel. Based on the transcriptome analysis for two parents and two RILs, 24,941 unique differentially expressed genes (DEGs) were identified, 473 of which were promising genes. For the fiber strength (FS) QTLs, 320 DEGs were identified, suggesting that pectin synthesis, phenylpropanoid biosynthesis, and plant hormone signaling pathways could influence FS, and several transcription factors may regulate fiber development, such as GAE6, C4H, OMT1, AFR18, EIN3, bZIP44, and GAI. Notably, the marker D13_56413025 in qFS-chr18-4 provides a potential basis for enhancing fiber quality of upland cotton via marker-assisted breeding and gene cloning of important fiber quality traits.

The Pivotal Role of Major Chromosomes of Sub-Genomes A and D in Fiber Quality Traits of Cotton.

Lack of precise information about the candidate genes involved in a complex quantitative trait is a major obstacle in the cotton fiber quality improvement, and thus, overall genetic gain in conventional phenotypic selection is low. Recent molecular interventions and advancements in genome sequencing have led to the development of high-throughput molecular markers, quantitative trait locus (QTL) fine mapping, and single nucleotide polymorphisms (SNPs). These advanced tools have resolved the existing bottlenecks in trait-specific breeding. This review demonstrates the significance of chromosomes 3, 7, 9, 11, and 12 of sub-genomes A and D carrying candidate genes for fiber quality. However, chromosome 7 carrying SNPs for stable and potent QTLs related to fiber quality provides great insights for fiber quality-targeted research. This information can be validated by marker-assisted selection (MAS) and transgene in Arabidopsis and subsequently in cotton.

Epidemiology investigation of PRRSV discharged by faecal and genetic variation of ORF5.

To obtain more information of Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) transmission via faeces in/between farms, 360 swine faecal samples were randomly collected from different farms in China from 2017 to 2019. Sixty-two ORF5 genes were amplified by PCR from 120 positive samples identified by real-time RT-PCR and further characterized by sequencing. Phylogenetic analysis based on the ORF5 gene revealed that these strains can be divided into four lineages: lineage 1 (NADC30-like), lineage 3 (QYYZ-like), lineage 5.1 (VR2332-like) and lineage 8.7 (JXA1-like), with 62.9% (39/62) NADC30-like virus, 21% (13/62) QYYZ-like virus, 1.6% (1/62) VR2332-like virus and 14.5% (9/62) for JAX1-like virus. In particular, 14 PRRSVs including lineage 1, 5.1 and 8.7 can be isolated from 120 positive faecal samples, which further suggests that faecal transmission may be an important factor in the spread of PRRSV in farms. Full-length genome sequencing analysis showed that 14 isolates share 83.1%-97.7% homology with each other and 82.3%-96.1% identity with NADC30, 83.2%-99.7% with VR2332, 79.6%-87.2% with QYYZ and 82.6%-98.9% with JXA1 and CH-1a, and only 60.1%-60.7% with LV. Recombination events were observed in the six out of 14 strains. Collectively, the data of this study are useful for understanding the spread of PRRSV via faeces. Additionally, the virus was isolated from positive faecal samples, suggesting that faecal transmission may be an important factor in the spread of PRRSV in farms.

Predicting the grades of Astragali radix using mass spectrometry-based metabolomics and machine learning / 药物分析学报

Astragali radix(AR,the dried root of Astragalus)is a popular herbal remedy in both China and the United States.The commercially available AR is commonly classified into premium graded(PG)and ungraded(UG)ones only according to the appearance.To uncover novel sensitive and specific markers for AR grading,we took the integrated mass spectrometry-based untargeted and targeted metabolomics ap-proaches to characterize chemical features of PG and UG samples in a discovery set(n=16 batches).A series of five differential compounds were screened out by univariate statistical analysis,including arginine,calycosin,ononin,formononetin,and astragaloside Ⅳ,most of which were observed to be accumulated in PG samples except for astragaloside Ⅳ.Then,we performed machine learning on the quantification data of five compounds and constructed a logistic regression prediction model.Finally,the external validation in an independent validation set of AR(n=20 batches)verified that the five com-pounds,as well as the model,had strong capability to distinguish the two grades of AR,with the pre-diction accuracy＞90％.Our findings present a panel of meaningful candidate markers that would significantly catalyze the innovation in AR grading.