Oxidation-reduction process of Arabidopsis thaliana roots induced by bisphenol compounds based on RNA-seq analysis.

Bisphenol compounds (BPs) have various industrial uses and can enter the environment through various sources. To evaluate the ecotoxicity of BPs and identify potential gene candidates involved in the plant toxicity, Arabidopsis thaliana was exposed to bisphenol A (BPA), BPB, BPE, BPF, and BPS at 1, 3, 10 mg/L for a duration of 14 days, and their growth status were monitored. At day 14, roots and leaves were collected for internal BPs exposure concentration detection, RNA-seq (only roots), and morphological observations. As shown in the results, exposure to BPs significantly disturbed root elongation, exhibiting a trend of stimulation at low concentration and inhibition at high concentration. Additionally, BPs exhibited pronounced generation of reactive oxygen species, while none of the pollutants caused significant changes in root morphology. Internal exposure concentration analysis indicated that BPs tended to accumulate in the roots, with BPS exhibiting the highest level of accumulation. The results of RNA-seq indicated that the shared 211 differently expressed genes (DEGs) of these 5 exposure groups were enriched in defense response, generation of precursor metabolites, response to organic substance, response to oxygen-containing, response to hormone, oxidation-reduction process and so on. Regarding unique DEGs in each group, BPS was mainly associated with the redox pathway, BPB primarily influenced seed germination, and BPA, BPE and BPF were primarily involved in metabolic signaling pathways. Our results provide new insights for BPs induced adverse effects on Arabidopsis thaliana and suggest that the ecological risks associated with BPA alternatives cannot be ignored.

Acute exposure to mercury drives changes in gene expression in Drosophila melanogaster.

OBJECTIVE: We quantified the effect of acute exposure to a high dosage of inorganic mercury on gene expression in Drosophila melanogaster using RNA-sequencing of whole adult females. RESULTS: We found 119 genes with higher gene expression following treatment (including all 5 Drosophila metallothionine genes and a number of heat shock protein genes), and 31 with lower expression (several of which are involved in egg formation). Our results highlight biological processes and genetic pathways impacted by exposure to this toxic metal, and provide motivation for future studies to understand the genetic basis of response to mercury.

scPanel: a tool for automatic identification of sparse gene panels for generalizable patient classification using scRNA-seq datasets.

Single-cell RNA sequencing (scRNA-seq) technologies can generate transcriptomic profiles at a single-cell resolution in large patient cohorts, facilitating discovery of gene and cellular biomarkers for disease. Yet, when the number of biomarker genes is large, the translation to clinical applications is challenging due to prohibitive sequencing costs. Here, we introduce scPanel, a computational framework designed to bridge the gap between biomarker discovery and clinical application by identifying a sparse gene panel for patient classification from the cell population(s) most responsive to perturbations (e.g. diseases/drugs). scPanel incorporates a data-driven way to automatically determine a minimal number of informative biomarker genes. Patient-level classification is achieved by aggregating the prediction probabilities of cells associated with a patient using the area under the curve score. Application of scPanel to scleroderma, colorectal cancer, and COVID-19 datasets resulted in high patient classification accuracy using only a small number of genes (<20), automatically selected from the entire transcriptome. In the COVID-19 case study, we demonstrated cross-dataset generalizability in predicting disease state in an external patient cohort. scPanel outperforms other state-of-the-art gene selection methods for patient classification and can be used to identify parsimonious sets of reliable biomarker candidates for clinical translation.

Dissecting the Single-Cell Diversity and Heterogeneity Underlying Cervical Precancerous Lesions and Cancer Tissues.

The underlying cellular diversity and heterogeneity from cervix precancerous lesions to cervical squamous cell carcinoma (CSCC) is investigated. Four single-cell datasets including normal tissues, normal adjacent tissues, precancerous lesions, and cervical tumors were integrated to perform disease stage analysis. Single-cell compositional data analysis (scCODA) was utilized to reveal the compositional changes of each cell type. Differentially expressed genes (DEGs) among cell types were annotated using BioCarta. An assay for transposase-accessible chromatin sequencing (ATAC-seq) analysis was performed to correlate epigenetic alterations with gene expression profiles. Lastly, a logistic regression model was used to assess the similarity between the original and new cohort data (HRA001742). After global annotation, seven distinct cell types were categorized. Eight consensus-upregulated DEGs were identified in B cells among different disease statuses, which could be utilized to predict the overall survival of CSCC patients. Inferred copy number variation (CNV) analysis of epithelial cells guided disease progression classification. Trajectory and ATAC-seq integration analysis identified 95 key transcription factors (TF) and one immunohistochemistry (IHC) testified key-node TF (YY1) involved in epithelial cells from CSCC initiation to progression. The consistency of epithelial cell subpopulation markers was revealed with single-cell sequencing, bulk sequencing, and RT-qPCR detection. KRT8 and KRT15, markers of Epi6, showed progressively higher expression with disease progression as revealed by IHC detection. The logistic regression model testified the robustness of the resemblance of clusters among the various datasets utilized in this study. Valuable insights into CSCC cellular diversity and heterogeneity provide a foundation for future targeted therapy.

SAE-Impute: imputation for single-cell data via subspace regression and auto-encoders.

BACKGROUND: Single-cell RNA sequencing (scRNA-seq) technology has emerged as a crucial tool for studying cellular heterogeneity. However, dropouts are inherent to the sequencing process, known as dropout events, posing challenges in downstream analysis and interpretation. Imputing dropout data becomes a critical concern in scRNA-seq data analysis. Present imputation methods predominantly rely on statistical or machine learning approaches, often overlooking inter-sample correlations. RESULTS: To address this limitation, We introduced SAE-Impute, a new computational method for imputing single-cell data by combining subspace regression and auto-encoders for enhancing the accuracy and reliability of the imputation process. Specifically, SAE-Impute assesses sample correlations via subspace regression, predicts potential dropout values, and then leverages these predictions within an autoencoder framework for interpolation. To validate the performance of SAE-Impute, we systematically conducted experiments on both simulated and real scRNA-seq datasets. These results highlight that SAE-Impute effectively reduces false negative signals in single-cell data and enhances the retrieval of dropout values, gene-gene and cell-cell correlations. Finally, We also conducted several downstream analyses on the imputed single-cell RNA sequencing (scRNA-seq) data, including the identification of differential gene expression, cell clustering and visualization, and cell trajectory construction. CONCLUSIONS: These results once again demonstrate that SAE-Impute is able to effectively reduce the droupouts in single-cell dataset, thereby improving the functional interpretability of the data.

Transcriptome-based prediction for polygenic traits in rice using different gene subsets.

BACKGROUND: Transcriptome-based prediction of complex phenotypes is a relatively new statistical method that links genetic variation to phenotypic variation. The selection of large-effect genes based on a priori biological knowledge is beneficial for predicting oligogenic traits; however, such a simple gene selection method is not applicable to polygenic traits because causal genes or large-effect loci are often unknown. Here, we used several gene-level features and tested whether it was possible to select a gene subset that resulted in better predictive ability than using all genes for predicting a polygenic trait. RESULTS: Using the phenotypic values of shoot and root traits and transcript abundances in leaves and roots of 57 rice accessions, we evaluated the predictive abilities of the transcriptome-based prediction models. Leaf transcripts predicted shoot phenotypes, such as plant height, more accurately than root transcripts, whereas root transcripts predicted root phenotypes, such as crown root length, more accurately than leaf transcripts. Furthermore, we used the following three features to train the prediction model: (1) tissue specificity of the transcripts, (2) ontology annotations, and (3) co-expression modules for selecting gene subsets. Although models trained by a gene subset often resulted in lower predictive abilities than the model trained by all genes, some gene subsets showed improved predictive ability. For example, using genes expressed in roots but not in leaves, the predictive ability for crown root diameter was improved by more than 10% (R2 = 0.59 when using all genes; R2 = 0.66, using 1,554 root-specifically expressed genes). Similarly, genes annotated as "gibberellic acid sensitivity" showed higher predictive ability than using all genes for root dry weight. CONCLUSIONS: Our results highlight both the possibility and difficulty of selecting an appropriate gene subset to predict polygenic traits from transcript abundance, given the current biological knowledge and information. Further integration of multiple sources of information, as well as improvements in gene characterization, may enable the selection of an optimal gene set for the prediction of polygenic phenotypes.

Exploring the potential mechanism of Radix Bupleuri in the treatment of sepsis: a study based on network pharmacology and molecular docking.

AIM: To explore, using network pharmacology and RNA-seq technologies, potential active targets and mechanisms underpinning Radix Bupleuri's effectiveness during sepsis treatment. METHODS: Following the Sepsis-3.0 criteria, the research cohort, comprising 23 sepsis patients and 10 healthy participants, was obtained from public databases. Peripheral blood samples were collected and subjected to RNA-seq analysis. Active ingredients and potential targets of Radix Bupleuri were identified using the Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine 2.0 (BATMAN-TCM 2.0) database and TCMSP database. Subsequently, protein-protein interaction (PPI) network construction, Gene Ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were conducted to explore cross-targets between disease and drugs. Survival analysis of key targets was performed using the GSE65682 dataset, and single-cell RNA-seq was employed for cellular localization analysis of key genes. Finally, molecular docking and Molecular dynamics simulation of the core target was conducted. RESULTS: Differential expression analysis revealed 4253 genes associated with sepsis. Seventy-six active components and 1030 potential targets of Radix Bupleuri were identified. PPI, GO, and pathway enrichment analyses indicated involvement in the regulation of transmembrane transport, monatomic ion transport, and MAPK signaling. Survival curve analysis identified PIK3CD, ARRB2, SUCLG1, and SPI1 as key targets associated with lower mortality in the high expression group, while higher mortality was observed in the high PNP and FURIN expression groups. Single-cell RNA sequencing unveiled the cellular localization of PIK3CD, PNP, SPI1, and FURIN within macrophages, while ARRB2 and SUCLG1 exhibited localization in both macrophages and T-cells. Subsequent molecular docking and Molecular dynamics simulation indicated a potential binding interaction for Carvone-PIK3CD, Encecalin-ARRB2, Lauric Acid-SUCLG1, Pulegone-FURIN, Nootkatone-SPI1, and Saikogenin F-PNP. CONCLUSION: Radix Bupleuri could modulate immune function by affecting PIK3CD, ARRB2, SUCLG1, FURIN, SPI1, and PNP, thereby potentially improving the prognosis of sepsis.

[Bipolar Action of Inhibitor of Vasculogenic Mimicry on Gene Expression in Melanoma Cells].

Multiple exogenous or endogenous factors alter gene expression patterns by different mechanisms that are poorly understood. We used RNA-Seq analysis in order to study changes in gene expression in melanoma cells that are capable of vasculogenic mimicry that is inhibited upon the action of an inhibitor of vasculogenic mimicry. Here, we show that the drug induces a strong upregulation of 50 genes that control the cell cycle and microtubule cytoskeleton coupled with a strong downregulation of 50 genes that control different cellular metabolic processes. We found that both groups of genes are simultaneously regulated by multiple sets of transcription factors. We conclude that one way for coordinated regulation of large groups of genes is regulation simultaneously by multiple transcription factors.

Transcriptomic analyses in the gametophytes of the apomictic fern Dryopteris affinis.

MAIN CONCLUSION: A novel genomic map of the apogamous gametophyte of the fern Dryopteris affinis unlocks oldest hindrance with this complex plant group, to gain insight into evo-devo approaches. The gametophyte of the fern Dryopteris affinis ssp. affinis represents a good model to explore the molecular basis of vegetative and reproductive development, as well as stress responses. Specifically, this fern reproduces asexually by apogamy, a peculiar case of apomixis whereby a sporophyte forms directly from a gametophytic cell without fertilization. Using RNA-sequencing approach, we have previously annotated more than 6000 transcripts. Here, we selected 100 of the inferred proteins homolog to those of Arabidopsis thaliana, which were particularly interesting for a detailed study of their potential functions, protein-protein interactions, and distance trees. As expected, a plethora of proteins associated with gametogenesis and embryogenesis in angiosperms, such as FERONIA (FER) and CHROMATING REMODELING 11 (CHR11) were identified, and more than a dozen candidates potentially involved in apomixis, such as ARGONAUTE family (AGO4, AGO9, and AGO 10), BABY BOOM (BBM), FASCIATED STEM4 (FAS4), FERTILIZATION-INDEPENDENT ENDOSPERM (FIE), and MATERNAL EFFECT EMBRYO ARREST29 (MEE29). In addition, proteins involved in the response to biotic and abiotic stresses were widely represented, as shown by the enrichment of heat-shock proteins. Using the String platform, the interactome revealed that most of the protein-protein interactions were predicted based on experimental, database, and text mining datasets, with MULTICOPY SUPPRESSOR OF IRA4 (MSI4) showing the highest number of interactions: 16. Lastly, some proteins were studied through distance trees by comparing alignments with respect to more distantly or closely related plant groups. This analysis identified DCL4 as the most distant protein to the predicted common ancestor. New genomic information in relation to gametophyte development, including apomictic reproduction, could expand our current vision of evo-devo approaches.

Multiple congenital anomalies in two fetuses with glutathione-synthetase deficit (GSS).

Glutathione synthetase deficiency is a rare inborn metabolic disease usually caused by biallelic variants in GSS. Clinical severity varies from isolated hemolytic anemia, sometimes associated with chronic metabolic acidosis and 5-oxoprolinuria, to severe neurological phenotypes with neonatal lethality. Here we report on two fetal siblings from two pregnancies with glutathione synthetase deficiency exhibiting similar multiple congenital anomalies associating phocomelia, cleft palate, intra-uterine growth retardation, genito-urinary malformations, and congenital heart defect. Genome sequencing showed that both fetuses were compound heterozygous for two GSS variants: the previously reported pathogenic missense substitution NM_000178.4 c.800G>A p.(Arg267Gln), and a 2.4 kb intragenic deletion NC_000020.11:g.34944530_34946833del. RNA-seq on brain tissue revealed the out-of-frame deletion of the exon 3 and an almost monoallelic expression of the missense variant (88%), suggesting degradation of the deletion-harboring allele by nonsense-mediated mRNA decay. 5-oxoproline (pyroglutamic acid) levels in amniotic fluid were elevated, suggesting an alteration of the gamma-glutamyl cycle, and corroborating the pathogenicity of the two GSS variants. Only one case of glutathione synthetase deficiency with limb malformations has previously been reported, in a newborn homozygous for the c.800G>A variant. Thus, our data allow us to discuss a potential phenotypic extension of glutathione synthetase deficiency, with a possible involvement of the c.800G>A variant.

Transcriptomic analysis of Asparagus officinalis cultivars with varying levels of freezing tolerance over fall acclimation and spring deacclimation periods.

Asparagus (Asparagus officinalis L.) is an important vegetable crop in southern Ontario, Canada, where winter air and soil temperatures below 0°C are common. Consequently, cultivars growing in this area must possess winterhardiness and freezing tolerance for survival. Asparagus acquires freezing tolerance in the fall through cold acclimation and loses freezing tolerance in the spring through deacclimation. To understand the molecular bases of these processes, transcriptomic analysis (RNA-Seq) was conducted on two cultivars, one adapted, 'Guelph Millennium' (GM), and one unadapted, 'UC157' (UC), to the winter conditions of southern Ontario. RNA extracted from bud and rhizome tissues, sampled on three dates during early spring and late fall, was subjected to sequencing. In the fall, the numbers of differentially expressed (DE) genes at the second and third harvests increased, relative to the first harvest, in dormant buds and rhizomes as freezing tolerance of cultivars increased, and the majority of DE genes were downregulated. In spring, freezing tolerance decreased as plants deacclimated and most genes DE at second and third harvests were upregulated in both cultivars. GM had lower LT50 (lethal temperature at which 50% of plants die) values and hence higher freezing tolerance than UC on specific sampling dates during both spring and fall, and expression patterns of specific genes were correlated with LT50 differences. Functional analysis revealed that these genes were involved in carbohydrate metabolic process, plant hormone signal transduction (auxin and gibberellin), proline metabolism, biosynthesis of secondary metabolites, circadian rhythm, and late embryogenesis abundant proteins and could be associated with cold acclimation and deacclimation processes. These findings will help researchers understand the molecular mechanisms of freezing tolerance in asparagus, leading to breeding and genetic strategies to improve the trait.

Sink strength, nutrient allocation, cannabinoid yield and associated transcript profiles vary in two drug-type Cannabis chemovars.

Cannabis sativa L. is one of the oldest domesticated crops. Hemp-type cultivars, which predominantly produce non-intoxicating cannabidiol (CBD), have been selected for their fast growth, seed, and fibre production, while drug-type chemovars were bred for high accumulation of tetrahydrocannabinol (THC). We investigated how the generation of CBD-dominant chemovars by introgression of hemp- into drug-type Cannabis impacted plant performance. The THC-dominant chemovar showed superior sink strength, higher flower biomass and demand-driven control of nutrient uptake. By contrast, the CBD-dominant chemovar hyperaccumulated phosphate in sink organs leading to reduced carbon and nitrogen assimilation in leaves, which limited flower biomass and cannabinoid yield. RNA-seq analyses determined organ- and chemovar-specific differences in expression of genes associated with nitrate and phosphate homeostasis as well as growth-regulating transcription factors that were correlated with measured traits. Among these were genes positively selected for during Cannabis domestication encoding an inhibitor of the phosphate starvation response SPX DOMAIN GENE3, nitrate reductase and two nitrate transporters. Altered nutrient sensing, acquisition or distribution are likely a consequence of adaption to growth on marginal, low-nutrient input lands in hemp. Our data provide evidence that such ancestral traits may become detrimental for female flower development and consequently overall CBD yield in protected cropping environments.

Ferulic Acid Methyl Ester Attenuates Cerebral Ischemia-Reperfusion Injury in Rats by Modulating PI3K/HIF-1α/VEGF Signaling Pathway.

Background: Cerebral ischaemia-reperfusion injury (CIRI) could worsen the inflammatory response and oxidative stress in brain tissue. According to previous studies, ferulic acid methyl ester (FAME), as the extract with the strongest comprehensive activity in the traditional Chinese medicine Huang Hua oil dot herb, has significant anti-oxidative stress and neuroprotective functions, and can effectively alleviate CIRI, but its mechanism of action is still unclear. Methods: Firstly, the pharmacological effects of FAME were investigated by in vitro oxidative stress and inflammatory experiments. Secondly, evaluate the therapeutic effects of FAME in the treatment of CIRI by brain histopathological staining and cerebral infarct area by replicating the in vivo MACO model. Thirdly, RNA-Seq and network pharmacology were utilized to predict the possible targets and mechanisms of FAME for CIRI at the molecular level. Finally, the expression of key target proteins, as well as the key regulatory relationships were verified by molecular docking visualization, Western Blotting and immunohistochemistry. Results: The results of in vitro experiments concluded that FAME could significantly reduce the content of TNF-α, IL-1ß and ROS, inhibiting COX-2 and iNOS protein expression in cells(p<0.01). FAME was demonstrated to have anti-oxidative stress and anti-inflammatory effects. The results of in vivo experiments showed that after the administration of FAME, the area of cerebral infarction in rats with CIRI was reduced, the content of Bcl-2 and VEGF was increased(p<0.05). Network pharmacology and RNA-Seq showed that the alleviation of CIRI by FAME may be through PI3K-AKT and HIF-1 signaling pathway. Enhanced expression of HIF-1α, VEGF, p-PI3K, p-AKT proteins in the brain tissues of rats in the FAME group was verified by molecular docking and Western Blotting. Conclusion: FAME possesses significant anti-inflammatory and anti-oxidative stress activities and alleviates CIRI through the PI3K/HIF-1α/VEGF signaling pathway.

Single-cell RNA sequencing reveals microenvironmental infiltration in non-small cell lung cancer with different responses to immunotherapy.

BACKGROUND: Immunotherapy represents a groundbreaking and monumental achievement in the field of cancer therapy, marking a significant advancement in fighting against this devastating disease. Lung cancer has showed consistent clinical improvements in response to immunotherapy treatments, yet, it is undeniable that challenges such as limited response rates acquire resistance, and the unclear fundamental mechanisms were inevitable problems. METHODS: The cellular composition was defined and distinguished through single-cell RNA sequencing (scRNA-seq) analysis of MPR (major pathologic response) and NMPR (non-major pathologic response) samples in GSE207422, including four primary MPR samples and eight primary NMPR samples. RESULTS: We found obvious difference in CD8+ T cell population between MPR and NMPR samples, with high expression of TYMS, RRM2, and BIRC5 in NPMR samples. Meanwhile, the proportion of macrophages and tumor epithelial cells infiltration increased in the NMPR samples. We discovered biomarkers (ACTN4, ATF3, BRD2, CDKN1A, and CHMP4B) in epithelial cells which were potentially represented worse outcomes. CONCLUSIONS: By exploring the difference of tumor microenvironment (TME) in samples with different corresponding degrees of neoadjuvant immunotherapy, this research introduces a number of novel biomarkers for predicting the response of treatment and a theoretical basis for overcoming immunotherapy resistance.

Effects of Arborvitae (Thuja plicata) Essential Oil on Cervical Cancer Cells: Insights into Molecular Mechanisms.

AIMS: This study aimed to assess the effects of AEO in an in vitro model of cell lines derived from cervical cancer-namely, HeLa and SiHa-by screening for AEO's cytotoxic properties and examining its influence on the modulation of gene expression. BACKGROUND: Cervical cancer stands as a prevalent global health concern, affecting millions of women worldwide. The current treatment modalities encompass surgery, radiation, and chemotherapy, but significant limitations and adverse effects constrain their effectiveness. Therefore, exploring novel treatments that offer enhanced efficacy and reduced side effects is imperative. Arborvitae essential oil, extracted from Thuja Plicata, has garnered attention for its antimicrobial, anti-inflammatory, immunomodulatory, and tissue-remodeling properties; however, its potential in treating cervical cancer remains uncharted. OBJECTIVE: The objective of this study was to delve into the molecular mechanisms induced by arborvitae essential oil in order to learn about its anticancer effects on cervical cancer cell lines. METHODS: The methods used in this study were assessments of cell viability using WST-1 and annexin V- propidium iodide, mRNA sequencing, and subsequent bioinformatics analysis. RESULTS: The findings unveiled a dose-dependent cytotoxic effect of arborvitae essential oil on both HeLa and SiHa cell lines. Minor effects were observed only at very low doses in the HaCaT non-tumorigenic human keratinocyte cells. RNA-Seq bioinformatics analysis revealed the regulatory impact of arborvitae essential oil on genes enriched in the following pathways: proteasome, adherens junctions, nucleocytoplasmic transport, cell cycle, proteoglycans in cancer, protein processing in the endoplasmic reticulum, ribosome, spliceosome, mitophagy, cellular senescence, and viral carcinogenesis, among others, in both cell lines. It is worth noting that the ribosome and spliceosome KEGG pathways are the most significantly enriched pathways in HeLa and SiHa cells. CONCLUSION: Arborvitae essential oil shows potential as a cytotoxic and antiproliferative agent against cervical cancer cells, exerting its cytotoxic properties by regulating many KEGG pathways.

First report of tomato as a natural host of tobacco vein banding mosaic virus (TVBMV) in Yunnan, China.

Tomatoes (Solanum lycopersicum L.), as a significant solanaceous crop, have attracted global research interest focused on elucidating its plant virus incidence, epidemiology, and pathogenicity, especially in field production (Li et al. 2021; Rivarez et al. 2023). Tobacco vein banding mosaic virus (TVBMV) is classified in the genus Potyvirus. Since its discovery, TVBMV has been documented to infect tobacco, potato, jimsonweed, wild eggplant under nature conditions (Wang et al. 2017). Also, TVBMV could be transmitted to tomatoes by aphids (Myzus persicae) in laboratory conditions (Bi et al. 2020). However, to date, there is no sequence representing TVBMV infecting tomato deposited in NCBI nucleotide database. In August 2023, about 30% of tomato planted in an open field showing typical viral disease symptoms (chlorosis, yellowing, mosaic, curling, and mottling) in Dali, Yunnan, China. To identify the potential pathogen, about 9 symptomatic leave from different plants were collected, pooled and sent for high-throughput sequencing. In summary, total RNA was extracted using TRIzol® Reagent (Invitrogen, CA, USA). Subsequently, RNA sequencing libraries were constructed using the TruSeq RNA sample prep kit (Illumina, CA, USA), followed by RNA-Seq sequencing performed on an Illumina HiSeq4000 platform (LC Sciences, USA). A total of 71,368,934 raw reads (paired-end) of the length 150-bp were generated. After quality control, 69,746,872 reads were retained and subjected to de novo assembly using Trinity (version 2.8.5). The assembled contigs (ranging from 186 nt to 15,573 nt) were searched against the NCBI non-redundant protein (NR) to detect potential viral pathogens using BLASTx with a cutoff e-value of 10-5. As a result, 2 viral contigs were assigned to 2 known viruses: TVBMV (Depth: 1960X, BLASTn similarity: 95.26%) and chilli veinal mottle virus (ChiVMV) (Depth: 3581X, BLASTn similarity: 98.22%). No other viruses and viroids were detected. The presence of TVBMV and ChiVMV were tested positive in all of the 9 samples originally collected. Notably, the detection primer for TVBMV identified in tomato (TVBMV-tomato) was designed from the newly assembled TVBMV genome (Forward: 5'- CTCGGTGAGGAAGGTGACATAAGT'; Reverse: 5'- CTTTCAACACCAGGGAATCTAGTG -3'). The nearly complete genome sequence of TVBMV-tomato was validated by overlapping RT-PCR and submitted to NCBI nucleotide database (accession: PP848192). To assess TVBMV-tomato infectivity, symptomatic tomato leaf sap was mechanically inoculated onto 4 healthy tomatoes, with healthy tomato leaf sap serving as a control. After 3 weeks, plants inoculated with symptomatic sap showed leaf curling and stunting, while control plants remained unaffected. All symptomatic samples tested positive for TVBMV via RT-PCR (4/4). For comparison, TVBMV could not be detected in the control sample. Sanger sequencing verified the expected 986 bp amplicon sequences. However, ChiVMV was also detected in all symptomatic tomato samples, which makes it possible that the symptoms after inoculation were the result of the synergism of TVBMV and ChiVMV. Phylogenetic analysis based on complete coding sequence revealed that TVBMV-tomato was most closely related to TVBMV identified from Solanum lyratum. To our knowledge, this work represents the first report of natural occurrence of TVBMV in agroecosystem in Yunnan, China.

Multi-omics analysis reveals the impact of influenza a virus host adaptation on immune signatures in pig tracheal tissue.

Introduction: Influenza A virus (IAV) infection is a global respiratory disease, which annually leads to 3-5 million cases of severe illness, resulting in 290,000-650,000 deaths. Additionally, during the past century, four global IAV pandemics have claimed millions of human lives. The epithelial lining of the trachea plays a vital role during IAV infection, both as point of viral entry and replication as well as in the antiviral immune response. Tracheal tissue is generally inaccessible from human patients, which makes animal models crucial for the study of the tracheal host immune response. Method: In this study, pigs were inoculated with swine- or human-adapted H1N1 IAV to gain insight into how host adaptation of IAV shapes the innate immune response during infection. In-depth multi-omics analysis (global proteomics and RNA sequencing) of the host response in upper and lower tracheal tissue was conducted, and results were validated by microfluidic qPCR. Additionally, a subset of samples was selected for histopathological examination. Results: A classical innate antiviral immune response was induced in both upper and lower trachea after infection with either swine- or human-adapted IAV with upregulation of genes and higher abundance of proteins associated with viral infection and recognition, accompanied by a significant induction of interferon stimulated genes with corresponding higher proteins concentrations. Infection with the swine-adapted virus induced a much stronger immune response compared to infection with a human-adapted IAV strain in the lower trachea, which could be a consequence of a higher viral load and a higher degree of inflammation. Discussion: Central components of the JAK-STAT pathway, apoptosis, pyrimidine metabolism, and the cytoskeleton were significantly altered depending on infection with swine- or human-adapted virus and might be relevant mechanisms in relation to antiviral immunity against putative zoonotic IAV. Based on our findings, we hypothesize that during host adaptation, IAV evolve to modulate important host cell elements to favor viral infectivity and replication.

Identification of a novel immunogenic death-associated model for predicting the immune microenvironment in lung adenocarcinoma from single-cell and Bulk transcriptomes.

Background: Studies on immunogenic death (ICD) in lung adenocarcinoma are limited, and this study aimed to determine the function of ICD in LUAD and to construct a novel ICD-based prognostic model to improve immune efficacy in lung adenocarcinoma patients. Methods: The data for lung adenocarcinoma were obtained from the Cancer Genome Atlas (TCGA) database and the National Center for Biotechnology Information (GEO). The single-cell data were obtained from Bischoff P et al. To identify subpopulations, we performed descending clustering using TSNE. We collected sets of genes related to immunogenic death from the literature and identified ICD-related genes through gene set analysis of variance (GSVA) and weighted gene correlation network analysis (WGCNA). Lung adenocarcinoma patients were classified into two types using consistency clustering. The difference between the two types was analyzed to obtain differential genes. An immunogenic death model (ICDRS) was established using LASSO-Cox analysis and compared with lung adenocarcinoma models of other individuals. External validation was performed in the GSE31210 and GSE50081 cohorts. The efficacy of immunotherapy was assessed using the TIDE algorithm and the IMvigor210, GSE78220, and TCIA cohorts. Furthermore, differences in mutational profiles and immune microenvironment between different risk groups were investigated. Subsequently, ROC diagnostic curves and KM survival curves were used to screen ICDRS key regulatory genes. Finally, RT-qPCR was used to verify the differential expression of these genes. Results: Eight ICD genes were found to be highly predictive of LUAD prognosis and significantly correlated with it. Multivariate analysis showed that patients in the low-risk group had a higher overall survival rate than those in the high-risk group, indicating that the model was an independent predictor of LUAD. Additionally, ICDRS demonstrated better predictive ability compared to 11 previously published models. Furthermore, significant differences in biological function and immune cell infiltration were observed in the tumor microenvironment between the high-risk and low-risk groups. It is noteworthy that immunotherapy was also significant in both groups. These findings suggest that the model has good predictive efficacy. Conclusions: The ICD model demonstrated good predictive performance, revealing the tumor microenvironment and providing a new method for evaluating the efficacy of pre-immunization. This offers a new strategy for future treatment of lung adenocarcinoma.

Identification of diagnostic candidates in Mendelian disorders using an RNA sequencing-centric approach.

BACKGROUND: RNA sequencing (RNA-seq) is increasingly being used as a complementary tool to DNA sequencing in diagnostics where DNA analysis has been uninformative. RNA-seq enables the identification of aberrant splicing and aberrant gene expression, improving the interpretation of variants of unknown significance (VUSs), and provides the opportunity to scan the transcriptome for aberrant splicing and expression in relevant genes that may be the cause of a patient's phenotype. This work aims to investigate the feasibility of generating new diagnostic candidates in patients without a previously reported VUS using an RNA-seq-centric approach. METHODS: We systematically assessed the transcriptomic profiles of 86 patients with suspected Mendelian disorders, 38 of whom had no candidate sequence variant, using RNA from blood samples. Each VUS was visually inspected to search for splicing abnormalities. Once aberrant splicing was identified in cases with VUS, multiple open-source alternative splicing tools were used to investigate if they would identify what was observed in IGV. Expression outliers were detected using OUTRIDER. Diagnoses in cases without a VUS were explored using two separate strategies. RESULTS: RNA-seq allowed us to assess 71% of VUSs, detecting aberrant splicing in 14/48 patients with a VUS. We identified four new diagnoses by detecting novel aberrant splicing events in patients with no candidate sequence variants from prior DNA testing (n = 32) or where the candidate VUS did not affect splicing (n = 23). An additional diagnosis was made through the detection of skewed X-inactivation. CONCLUSION: This work demonstrates the utility of an RNA-centric approach in identifying novel diagnoses in patients without candidate VUSs. It underscores the utility of blood-based RNA analysis in improving diagnostic yields and highlights optimal approaches for such analyses.

A florigen-expressing subpopulation of companion cells expresses other small proteins and reveals a nitrogen-sensitive FT repressor.

The precise onset of flowering is crucial to ensure successful plant reproduction. The gene FLOWERING LOCUS T (FT) encodes florigen, a mobile signal produced in leaves that initiates flowering at the shoot apical meristem. In response to seasonal changes, FT is induced in phloem companion cells located in distal leaf regions. Thus far, a detailed molecular characterization of the FT-expressing cells has been lacking. Here, we used bulk nuclei RNA-seq and single nuclei RNA (snRNA)-seq to investigate gene expression in FT-expressing cells and other phloem companion cells. Our bulk nuclei RNA-seq demonstrated that FT-expressing cells in cotyledons and in true leaves differed transcriptionally. Within the true leaves, our snRNA-seq analysis revealed that companion cells with high FT expression form a unique cluster in which many genes involved in ATP biosynthesis are highly upregulated. The cluster also expresses other genes encoding small proteins, including the flowering and stem growth inducer FPF1-LIKE PROTEIN 1 (FLP1) and the anti-florigen BROTHER OF FT AND TFL1 (BFT). In addition, we found that the promoters of FT and the genes co-expressed with FT in the cluster were enriched for the consensus binding motifs of NITRATE-INDUCIBLE GARP-TYPE TRANSCRIPTIONAL REPRESSOR 1 (NIGT1). Overexpression of the paralogous NIGT1.2 and NIGT1.4 repressed FT expression and significantly delayed flowering under nitrogen-rich conditions, consistent with NIGT1s acting as nitrogen-dependent FT repressors. Taken together, our results demonstrate that major FT-expressing cells show a distinct expression profile that suggests that these cells may produce multiple systemic signals to regulate plant growth and development.