High-throughput Transcriptome Research Articles

Empirical Characterization of False Discovery Rates of Differentially Expressed Genes and Transcriptomic Benchmark Concentrations in Zebrafish Embryos.

High-throughput transcriptomics (HTTr) is increasingly applied to zebrafish embryos to survey the toxicological effects of environmental chemicals. Before the adoption of this approach in regulatory testing, it is essential to characterize background noise in order to guide experimental designs. We thus empirically quantified the HTTr false discovery rate (FDR) across different embryo pool sizes, sample sizes, and concentration groups for toxicology studies. We exposed zebrafish embryos to 0.1% dimethyl sulfoxide (DMSO) for 5 days. Pools of 1, 5, 10, and 20 embryos were created (n = 24 samples for each pool size). Samples were sequenced on the TempO-Seq platform and then randomly assigned to mock treatment groups before differentially expressed gene (DEG), pathway, and benchmark concentration (BMC) analyses. Given that all samples were treated with DMSO, any significant DEGs, pathways, or BMCs are false positives. As expected, we found decreasing FDRs for DEG and pathway analyses with increasing pool and sample sizes. Similarly, FDRs for BMC analyses decreased with increasing pool size and concentration groups, with more stringent BMC premodel filtering reducing BMC FDRs. Our study provides foundational data for determining appropriate experiment designs for regulatory toxicity testing with HTTr in zebrafish embryos.

Alterations in HCN1 expression and distribution during epileptogenesis in rats

BackgroundThe hyperpolarization-activated cyclic nucleotide-gated cation channel (HCN1) is predominantly located in key regions associated with epilepsy, such as the neocortex and hippocampus. Under normal physiological conditions, HCN1 plays a crucial role in the excitatory and inhibitory regulation of neuronal networks. In temporal lobe epilepsy, the expression of HCN1 is decreased in the hippocampi of both animal models and patients. However, whether HCN1 expression changes during epileptogenesis preceding spontaneous seizures remains unclear. ObjectiveThe aim of this study was to determine whether the expression of HCN1 is altered during the epileptic prodromal phase, thereby providing evidence for its role in epileptogenesis. MethodsWe utilized a cobalt wire-induced rat epilepsy model to observe changes in HCN1 during epileptogenesis and epilepsy. Additionally, we also compared HCN1 alterations in epileptogenic tissues between cobalt wire- and pilocarpine-induced epilepsy rat models. Long-term video EEG recordings were used to confirm seizures development. Transcriptional changes, translation, and distribution of HCN1 were assessed using high-throughput transcriptome sequencing, total protein extraction, membrane and cytoplasmic protein fractionation, western blotting, immunohistochemistry, and immunofluorescence techniques. ResultsIn the cobalt wire-induced rat epilepsy model during the epileptogenesis phase, total HCN1 mRNA and protein levels were downregulated. Specifically, the membrane expression of HCN1 was decreased, whereas cytoplasmic HCN1 expression showed no significant change. The distribution of HCN1 in the distal dendrites of neurons decreased. During the epilepsy period, similar HCN1 alterations were observed in the neocortex of rats with cobalt wire-induced epilepsy and hippocampus of rats with lithium pilocarpine-induced epilepsy, including downregulation of mRNA levels, decreased total protein expression, decreased membrane expression, and decreased distal dendrite expression. ConclusionsAlterations in HCN1 expression and distribution are involved in epileptogenesis beyond their association with seizure occurrence. Similarities in HCN1 alterations observed in epileptogenesis-related tissues from different models suggest a shared pathophysiological pathway in epileptogenesis involving HCN1 dysregulation. Therefore, the upregulation of HCN1 expression in neurons, maintenance of the HCN1 membrane, and distal dendrite distribution in neurons may represent promising disease-modifying strategies in epilepsy.

Transcriptome profiling and analysis of patients with esophageal squamous cell carcinoma from Kazakhstan.

Esophageal squamous cell carcinoma (ESCC) is the predominant subtype of esophageal cancer in Central Asia, often diagnosed at advanced stages. Understanding population-specific patterns of ESCC is crucial for tailored treatments. This study aimed to unravel ESCC's genetic basis in Kazakhstani patients and identify potential biomarkers for early diagnosis and targeted therapies. ESCC patients from Kazakhstan were studied. We analyzed histological subtypes and conducted in-depth transcriptome sequencing. Differential gene expression analysis was performed, and significantly dysregulated pathways were identified using KEGG pathway analysis (p-value < 0.05). Protein-protein interaction networks were constructed to elucidate key modules and their functions. Among Kazakhstani patients, ESCC with moderate dysplasia was the most prevalent subtype. We identified 42 significantly upregulated and two significantly downregulated KEGG pathways, highlighting molecular mechanisms driving ESCC pathogenesis. Immune-related pathways, such as viral protein interaction with cytokines, rheumatoid arthritis, and oxidative phosphorylation, were elevated, suggesting immune system involvement. Conversely, downregulated pathways were associated with extracellular matrix degradation, crucial in cancer invasion and metastasis. Protein-protein interaction network analysis revealed four distinct modules with specific functions, implicating pathways in esophageal cancer development. High-throughput transcriptome sequencing elucidated critical molecular pathways underlying esophageal carcinogenesis in Kazakhstani patients. Insights into dysregulated pathways offer potential for early diagnosis and precision treatment strategies for ESCC. Understanding population-specific patterns is essential for personalized approaches to ESCC management.

Exploring the allelopathic autotoxicity mechanism of ginsenosides accumulation under ginseng decomposition based on integrated analysis of transcriptomics and metabolomics.

Continuous cropping obstacles seriously constrained the sustainable development of the ginseng industry. The allelopathic autotoxicity of ginsenosides is the key "trigger" of continuous cropping obstacles in ginseng. During harvest, the ginseng plants could be broken and remain in the soil. The decomposition of ginseng residue in soil is one of the important release ways of ginsenosides. Therefore, the allelopathic mechanism of ginsenosides through the decomposed release pathway needs an in-depth study. To investigate this allelopathic regulation mechanism, the integrated analysis of transcriptomics and metabolomics was applied. The prototype ginsenosides in ginseng were detected converse to rare ginsenosides during decomposition. The rare ginsenosides caused more serious damage to ginseng hairy root cells and inhibited the growth of ginseng hairy roots more significantly. By high-throughput RNA sequencing gene transcriptomics study, the significantly differential expressed genes (DEGs) were obtained under prototype and rare ginsenoside interventions. These DEGs were mainly enriched in the biosynthesis of secondary metabolites and metabolic pathways, phytohormone signal transduction, and protein processing in endoplasmic reticulum pathways. Based on the functional enrichment of DEGs, the targeted metabolomics analysis based on UPLC-MS/MS determination was applied to screen endogenous differential metabolized phytohormones (DMPs). The influence of prototype and rare ginsenosides on the accumulation of endogenous phytohormones was studied. These were mainly involved in the biosynthesis of diterpenoid, zeatin, and secondary metabolites, phytohormone signal transduction, and metabolic pathways. After integrating the transcriptomics and metabolomics analysis, ginsenosides could regulate the genes in phytohormone signaling pathways to influence the accumulation of JA, ABA, and SA. The conclusion was that the prototype ginsenosides were converted into rare ginsenosides by ginseng decomposition and released into the soil, which aggravated its allelopathic autotoxicity. The allelopathic mechanism was to intervene in the response regulation of genes related to the metabolic accumulation of endogenous phytohormones in ginseng. This result provides a reference for the in-depth study of continuous cropping obstacles of ginseng.

Transcriptomics-Based Points of Departure for Daphnia magna Exposed to 18 Per- and Polyfluoroalkyl Substances.

Per- and polyfluoroalkyl substances (PFAS) represent a large group of contaminants of concern based on their widespread use, environmental persistence, and potential toxicity. Many traditional models for estimating toxicity, bioaccumulation, and other toxicological properties are not well suited for PFAS. Consequently, there is a need to generate hazard information for PFAS in an efficient and cost-effective manner. In the present study, Daphnia magna were exposed to multiple concentrations of 22 different PFAS for 24 h in a 96-well plate format. Following exposure, whole-body RNA was extracted and extracts, each representing five exposed individuals, were subjected to RNA sequencing. Following analytical measurements to verify PFAS exposure concentrations and quality control on processed cDNA libraries for sequencing, concentration-response modeling was applied to the data sets for 18 of the tested compounds, and the concentration at which a concerted molecular response occurred (transcriptomic point of departure; tPOD) was calculated. The tPODs, based on measured concentrations of PFAS, generally ranged from 0.03 to 0.58 µM (9.9-350 µg/L; interquartile range). In most cases, these concentrations were two orders of magnitude lower than similarly calculated tPODs for human cell lines exposed to PFAS. They were also lower than apical effect concentrations reported for seven PFAS for which some crustacean or invertebrate toxicity data were available, although there were a few exceptions. Despite being lower than most other available hazard benchmarks, D. magna tPODs were, on average, four orders of magnitude greater than the maximum aqueous concentrations of PFAS measured in Great Lakes tributaries. Overall, this high-throughput transcriptomics assay with D. magna holds promise as a component of a tiered hazard evaluation strategy employing new approach methodologies. Environ Toxicol Chem 2024;00:1-16. © 2024 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Population-level comparisons of gene regulatory networks modeled on high-throughput single-cell transcriptomics data.

Single-cell technologies enable high-resolution studies of phenotype-defining molecular mechanisms. However, data sparsity and cellular heterogeneity make modeling biological variability across single-cell samples difficult. Here we present SCORPION, a tool that uses a message-passing algorithm to reconstruct comparable gene regulatory networks from single-cell/nuclei RNA-sequencing data that are suitable for population-level comparisons by leveraging the same baseline priors. Using synthetic data, we found that SCORPION outperformed 12 existing gene regulatory network reconstruction techniques. Using supervised experiments, we show that SCORPION can accurately identify differences in regulatory networks between wild-type and transcription factor-perturbed cells. We demonstrate SCORPION's scalability to population-level analyses using a single-cell RNA-sequencing atlas containing 200,436 cells from colorectal cancer and adjacent healthy tissues. The differences between tumor regions detected by SCORPION are consistent across multiple cohorts as well as with our understanding of disease progression, and elucidate phenotypic regulators that may impact patient survival.

Pan-histone deacetylase inhibitor vorinostat suppresses osteoclastic bone resorption through modulation of RANKL-evoked signaling and ameliorates ovariectomy-induced bone loss

BackgroundEstrogen deficiency-mediated hyperactive osteoclast represents the leading role during the onset of postmenopausal osteoporosis. The activation of a series of signaling cascades triggered by RANKL-RANK interaction is crucial mechanism underlying osteoclastogenesis. Vorinostat (SAHA) is a broad-spectrum pan-histone deacetylase inhibitor (HDACi) and its effect on osteoporosis remains elusive.MethodsThe effects of SAHA on osteoclast maturation and bone resorptive activity were evaluated using in vitro osteoclastogenesis assay. To investigate the effect of SAHA on the osteoclast gene networks during osteoclast differentiation, we performed high-throughput transcriptome sequencing. Molecular docking and the assessment of RANKL-induced signaling cascades were conducted to confirm the underlying regulatory mechanism of SAHA on the action of RANKL-activated osteoclasts. Finally, we took advantage of a mouse model of estrogen-deficient osteoporosis to explore the clinical potential of SAHA.ResultsWe showed here that SAHA suppressed RANKL-induced osteoclast differentiation concentration-dependently and disrupted osteoclastic bone resorption in vitro. Mechanistically, SAHA specifically bound to the predicted binding site of RANKL and blunt the interaction between RANKL and RANK. Then, by interfering with downstream NF-κB and MAPK signaling pathway activation, SAHA negatively regulated the activity of NFATc1, thus resulting in a significant reduction of osteoclast-specific gene transcripts and functional osteoclast-related protein expression. Moreover, we found a significant anti-osteoporotic role of SAHA in ovariectomized mice, which was probably realized through the inhibition of osteoclast formation and hyperactivation.ConclusionThese data reveal a high affinity between SAHA and RANKL, which results in blockade of RANKL-RANK interaction and thereby interferes with RANKL-induced signaling cascades and osteoclastic bone resorption, supporting a novel strategy for SAHA application as a promising therapeutic agent for osteoporosis.

ScRNA-seq Reveals Novel Genetic Pathways and Sex Chromosome Regulation in Tribolium Spermatogenesis.

Spermatogenesis is critical to sexual reproduction yet evolves rapidly in many organisms. High-throughput single-cell transcriptomics promises unparalleled insight into this important process but understanding can be impeded in nonmodel systems by a lack of known genes that can reliably demarcate biologically meaningful cell populations. Tribolium castaneum, the red flour beetle, lacks known markers for spermatogenesis found in insect species like Drosophila melanogaster. Using single-cell sequencing data collected from adult beetle testes, we implement a strategy for elucidating biologically meaningful cell populations by using transient expression stage identification markers, weighted principal component clustering, and SNP-based haploid/diploid phasing. We identify populations that correspond to observable points in sperm differentiation and find species specific markers for each stage. Our results indicate that molecular pathways underlying spermatogenesis in Coleoptera are substantially diverged from those in Diptera. We also show that most genes on the X chromosome experience meiotic sex chromosome inactivation. Temporal expression of Drosophila MSL complex homologs coupled with spatial analysis of potential chromatin entry sites further suggests that the dosage compensation machinery may mediate escape from meiotic sex chromosome inactivation and postmeiotic reactivation of the X chromosome.

Mapping Interindividual Variability of Toxicodynamics Using High-Throughput Transcriptomics and Primary Human Hepatocytes from Fifty Donors.

Understanding the variability across the human population with respect to toxicodynamic responses after exposure to chemicals, such as environmental toxicants or drugs, is essential to define safety factors for risk assessment to protect the entire population. Activation of cellular stress response pathways are early adverse outcome pathway (AOP) key events of chemical-induced toxicity and would elucidate the estimation of population variability of toxicodynamic responses. We aimed to map the variability in cellular stress response activation in a large panel of primary human hepatocyte (PHH) donors to aid in the quantification of toxicodynamic interindividual variability to derive safety uncertainty factors. High-throughput transcriptomics of over 8,000 samples in total was performed covering a panel of 50 individual PHH donors upon 8 to 24 h exposure to broad concentration ranges of four different toxicological relevant stimuli: tunicamycin for the unfolded protein response (UPR), diethyl maleate for the oxidative stress response (OSR), cisplatin for the DNA damage response (DDR), and tumor necrosis factor alpha () for signaling. Using a population mixed-effect framework, the distribution of benchmark concentrations (BMCs) and maximum fold change were modeled to evaluate the influence of PHH donor panel size on the correct estimation of interindividual variability for the various stimuli. Transcriptome mapping allowed the investigation of the interindividual variability in concentration-dependent stress response activation, where the average of BMCs had a maximum difference of 864-, 13-, 13-, and 259-fold between different PHHs for UPR, OSR, DDR, and signaling-related genes, respectively. Population modeling revealed that small PHH panel sizes systematically underestimated the variance and gave low probabilities in estimating the correct human population variance. Estimated toxicodynamic variability factors of stress response activation in PHHs based on this dataset ranged between 1.6 and 6.3. Overall, by combining high-throughput transcriptomics and population modeling, improved understanding of interindividual variability in chemical-induced activation of toxicity relevant stress pathways across the human population using a large panel of plated cryopreserved PHHs was established, thereby contributing toward increasing the confidence of in vitro-based prediction of adverse responses, in particular hepatotoxicity. https://doi.org/10.1289/EHP11891.

Whole transcriptome scanning and validation of negatively related genes in UC-MSCs

BackgroundHuman umbilical cord mesenchymal stem cells (UC-MSCs) are one of the most extensively researched stem cell types due to their potential for multi-lineage differentiation, secretion of regenerative factors, modulations of immunological activities, and the release of regenerative substances and influence immunological processes. Since UC-MSCs must be cultivated on a large scale for clinical use, selecting the appropriate storing passage, such as the usage-based passage of UC-MSCs, is critical for long-term autologous or allogeneic usage. Long-term cultivation of stem cells, on the other hand, causes them to lose their pluripotent differentiation capacity. As a result, distinguishing between high and low passages of UC-MSCs and identifying the particular variations associated with stem cells and their modes of action is essential for regenerative medicine. Therefore, we investigated the biological features and transcriptional changes of UC-MSCs over passages. MethodsUC-MSCs were isolated from the tissues of the human umbilical cord, and UC-MSCs from five passages (P1, P3, P5, P10 and P15) with three repetitions were compared and identified based on morphology, cell markers, differentiation capacity, and aging-related characteristics. It was previously assumed that the phenotype of cells before the P10 passage was stable, defined as early passage, and that culture could be continued until the 15th passage, defined as late passage. Next, the five passages of UC-MSCs were sequenced using high-throughput complete transcriptome sequencing. Fuzzy C-Means Clustering (FCM) and Weighted Gene Co-expression Network Analysis (WGCNA) were used to find hub genes, and gene silencing was performed to investigate the impact of missing genes on the stemness of UC-MSC cells. ResultsUC-MSCs of different passages displayed similar surface markers, including CD73, CD105, CD90, CD34, CD45 and HLA-DR. However, the proliferation time of late-phase UC-MSCs was longer than that of early-phase UC-MSCs, and the expression of the senescence-associated (SA)-β-gal staining marker was higher. At the same time, pluripotency markers (NANOG, OCT4, SOX2 and KIF4A) were down-regulated, and the multi-differentiation potential was reduced. Meanwhile, KIFC1 and UBE2C were down-regulated in late-phase UC-MSCs, which were involved in the maintenance of stemness. ConclusionsKIFC1 and UBE2C were highly expressed in early-UC-MSCs and showed a downward gradient trend with cell expansion in vitro. They regulated UC-MSC proliferation, colony sphere formation, multiple differentiation, stemness maintenance, and other biological manifestations. Therefore, they are anticipated to be new biomarkers for UC-MSCs quality identification in regenerative medicine applications.

Multi-well plate lid for single-step pooling of 96 samples for high-throughput barcode-based sequencing

High-throughput transcriptomics is of increasing fundamental biological and clinical interest. The generation of molecular data from large collections of samples, such as biobanks and drug libraries, is boosting the development of new biomarkers and treatments. Focusing on gene expression, the transcriptomic market exploits the benefits of next-generation sequencing (NGS), leveraging RNA sequencing (RNA-seq) as standard for measuring genome-wide gene expression in biological samples. The cumbersome sample preparation, including RNA extraction, conversion to cDNA and amplification, prevents high-throughput translation of RNA-seq technologies. Bulk RNA barcoding and sequencing (BRB-seq) addresses this limitation by enabling sample preparation in multi-well plate format. Sample multiplexing combined with early pooling into a single tube reduces reagents consumption and manual steps. Enabling simultaneous pooling of all samples from the multi-well plate into one tube, our technology relies on smart labware: a pooling lid comprising fluidic features and small pins to transport the liquid, adapted to standard 96-well plates. Operated with standard fluidic tubes and pump, the system enables over 90% recovery of liquid in a single step in less than a minute. Large scale manufacturing of the lid is demonstrated with the transition from a milled polycarbonate/steel prototype into an injection molded polystyrene lid. The pooling lid demonstrated its value in supporting high-throughput barcode-based sequencing by pooling 96 different DNA barcodes directly from a standard 96-well plate, followed by processing within the single sample pool. This new pooling technology shows great potential to address medium throughput needs in the BRB-seq workflow, thereby addressing the challenge of large-scale and cost-efficient sample preparation for RNA-seq.Graphical abstract

Integrating high-throughput phenotypic profiling and transcriptomic analyses to predict the hepatosteatosis effects induced by per- and polyfluoroalkyl substances

Per- and polyfluoroalkyl substances (PFAS) is a large compound class (n > 12,000) that is extensively present in food, drinking water, and aquatic environments. Reduced serum triglycerides and hepatosteatosis appear to be the common phenotypes for different PFAS chemicals. However, the hepatosteatosis potential of most PFAS chemicals remains largely unknown. This study aims to investigate PFAS-induced hepatosteatosis using in vitro high-throughput phenotype profiling (HTPP) and high-throughput transcriptomic (HTTr) data. We quantified the in vitro hepatosteatosis effects and mitochondrial damage using high-content imaging, curated the transcriptomic data from the Gene Expression Omnibus (GEO) database, and then calculated the point of departure (POD) values for HTPP phenotypes or HTTr transcripts, using the Bayesian benchmark dose modeling approach. Our results indicated that PFAS compounds with fully saturated C-F bonds, sulfur- and nitrogen-containing functional groups, and a fluorinated carbon chain length greater than 8 have the potential to produce biological effects consistent with hepatosteatosis. PFAS primarily induced hepatosteatosis via disturbance in lipid transport and storage. The potency rankings of PFAS compounds are highly concordant among in vitro HTPP, HTTr, and in vivo hepatosteatosis phenotypes (ρ = 0.60–0.73). In conclusion, integrating the information from in vitro HTPP and HTTr analyses can accurately project in vivo hepatosteatosis effects induced by PFAS compounds.

Why do we age? The main signs of aging

Aging is a gradual and irreversible pathophysiological process. This is manifested in the decline of tissue and cell functions and a significant variety of pathologies associated with aging, including neurodegenerative diseases, cardiovascular diseases, metabolic disorders, increased risk of diseases of the skeleton and the immune system. Although modern medical advances have made a certain contribution to human health and greatly extended life expectancy, along with the aging of society, various chronic diseases are gradually emerging, which are the most important causes of disability and death of the elderly. Aim. The aim of the work is to analyze modern ideas in the field of causes and manifestations of aging processes for the possibility of developing a strategy to slow down its course. At the molecular and cellular level, aging is a complex biological process involving the gradual deterioration of various cellular and molecular processes in the body over time. The length of a person’s life is closely related to the decrease in the possibilities of repair and regeneration of tissues and organs. In response to stress at the molecular, cellular, and systemic levels, genetic, epigenetic, and environmental regulatory factors cause a decrease in the body’s physiological capabilities. They use complex molecular mechanisms that together contribute to aging. Molecular mechanisms (such as telomere shortening, accumulation of DNA damage, metabolic changes, and excessive free radical generation) strongly link various factors to the rate of aging. Collectively, these mechanisms inhibit cell proliferation, alter metabolism and gene expression, and induce high levels of free radicals, maintaining a senescent cell phenotype. Although the number of early senescent cells is low, they can limit the regenerative capacity of tissue stem cells and lead to the accumulation of cellular damage, thereby contributing to age-related diseases. Conclusions. Current advances in high-throughput genomics, transcriptomics, proteomics, and metabolomics enable the characterization and quantification of thousands of epigenetic markers, transcripts, proteins, metabolites, and can reveal general changes that occur with age in complex organisms at the molecular level. Thus, the integration of these molecular markers and related molecular mechanisms into a comprehensive assessment of biological age to prevent age-related functional decline and morbidity is becoming an increasingly pressing issue in medical science and should be implemented in practice as soon as possible.

Color components determination and full-length comparative transcriptomic analyses reveal the potential mechanism of carotenoid synthesis during Paphiopedilum armeniacum flowering.

Paphiopedilum armeniacum (P. armeniacum), an ornamental plant native to China, is known for its distinctive yellow blossoms. However, the mechanisms underlying P. armeniacum flower coloration remain unclear. We selected P. armeniacum samples from different flowering stages and conducted rigorous physicochemical analyses. The specimens were differentiated based on their chemical properties, specifically their solubilities in polar solvents. This key step enabled us to identify the main metabolite of flower color development of P. armeniacum, and to complete the identification by High-performance liquid chromatography (HPLC) based on the results. Additionally, we employed a combined approach, integrating both third-generation full-length transcriptome sequencing and second-generation high-throughput transcriptome sequencing, to comprehensively explore the molecular components involved. We combined physical and chemical analysis with transcriptome sequencing to reveal that carotenoid is the main pigment of P. armeniacum flower color. Extraction colorimetric method and HPLC were used to explore the characteristics of carotenoid accumulation during flowering. We identified 28 differentially expressed carotenoid biosynthesis genes throughout the flowering process, validated their expression through fluorescence quantification, and discovered 19 potential positive regulators involved in carotenoid synthesis. Among these candidates, three RCP2 genes showed a strong potential for governing the PDS and ZDS gene families. In summary, our study elucidates the fundamental mechanisms governing carotenoid synthesis during P. armeniacum flowering, enhancing our understanding of this process and providing a foundation for future research on the molecular mechanisms driving P. armeniacum flowering.

Uncovering lupus nephritis-specific genes and the potential of TNFRSF17-targeted immunotherapy: a high-throughput sequencing study.

Lupus nephritis (LN) is a severe manifestation of systemic lupus erythematosus (SLE). This study aimed to identify LN specific-genes and potential therapeutic targets. We performed high-throughput transcriptome sequencing on peripheral blood mononuclear cells (PBMCs) from LN patients. Healthy individuals and SLE patients without LN were used as controls. To validate the sequencing results, qRT-PCR was performed for 5 upregulated and 5 downregulated genes. Furthermore, the effect of the TNFRSF17-targeting drug IBI379 on patient plasma cells and B cells was evaluated by flow cytometry. Our analysis identified 1493 and 205 differential genes in the LN group compared to the control and SLE without LN groups respectively, with 70 genes common to both sets, marking them as LN-specific. These LN-specific genes were significantly enriched in the 'regulation of biological quality' GO term and the cell cycle pathway. Notably, several genes including TNFRSF17 were significantly overexpressed in the kidneys of both LN patients and NZB/W mice. TNFRSF17 levels correlated positively with urinary protein levels, and negatively with complement C3 and C4 levels in LN patients. The TNFRSF17-targeting drug IBI379 effectively induced apoptosis in patient plasma cells without significantly affecting B cells. Our findings suggest that TNFRSF17 could serve as a potential therapeutic target for LN. Moreover, IBI379 is presented as a promising treatment option for LN.

Controlling arbovirus infection: high-throughput transcriptome and proteome insights.

Arboviruses pose a significant threat to public health globally, demanding innovative approaches for their control. For this, a better understanding of the complex web of interactions established in arbovirus-infected mosquitoes is fundamental. High-throughput analyses allow a genome-wide view of arbovirus-induced alterations at different gene expression levels. This review provides a comprehensive perspective into the current literature in transcriptome and proteome landscapes in mosquitoes infected with arboviruses. It also proposes a coordinated research effort to define the critical nodes that determine arbovirus infection and transmission.

Molecular mechanism of Serratia marcescens Bizio infection in Reticulitermes chinensis Snyder based on full-length SMRT transcriptome sequencing.

Reticulitermes chinensis Snyder is an important pest in forestry and construction and is widely distributed in China. We found that Serratia marcescens Bizio strain SM1 has insecticidal activity to R. chinensis, but the pathogenic mechanism of SM1 to R. chinensis is not clear. Therefore, full-length transcriptome sequencing was performed on R. chinensis infected with SM1 and the control group. A total of 230 differentially expressed genes were identified by comparing SM1 infection group and the control group, among which 103 were downregulated and 127 were upregulated. We found downregulated genes in nine metabolic pathway categories, among which carbohydrate metabolism had the most downregulated genes, followed by energy metabolism and amino acid metabolism. We also found that some downregulated genes were related to pattern recognition receptors, cellular immunity, and humoral immunity, indicating that R. chinensis immunity was negatively affected by SM1 infection. In addition, some genes in signal transduction and genetic information processing pathways were downregulated. In this study, high-throughput full-length transcriptome analysis was used to analyse the pathogenic mechanism of SM1 to R. chinensis. The results of this study provide useful information for exploring the relationship between SM1 and R. chinensis, and provide theoretical support for the future application of SM1 and the prevention and treatment of R. chinensis.

Uncovering the potential molecular mechanism of liraglutide to alleviate the effects of high glucose on myoblasts based on high-throughput transcriptome sequencing technique

BackgroundMyoblasts play an important role in muscle growth and repair, but the high glucose environment severely affects their function. The purpose of this study is to explore the potential molecular mechanism of liraglutide in alleviating the effects of high glucose environments on myoblasts.MethodsMTT, western blot, and ELISA methods were used to investigate the role of liraglutide on C2C12 myoblasts induced by high glucose. The high-throughput transcriptome sequencing technique was used to sequence C2C12 myoblasts from different treated groups. The DESeq2 package was used to identify differentially expressed-mRNAs (DE-mRNAs). Then, functional annotations and alternative splicing (AS) were performed. The Cytoscape-CytoHubba plug-in was used to identify multicentric DE-mRNAs.ResultsThe MTT assay results showed that liraglutide can alleviate the decrease of myoblasts viability caused by high glucose. Western blot and ELISA tests showed that liraglutide can promote the expression of AMPKα and inhibit the expression of MAFbx, MuRF1 and 3-MH in myoblasts. A total of 15 multicentric DE-mRNAs were identified based on the Cytoscape-CytoHubba plug-in. Among them, Top2a had A3SS type AS. Functional annotation identifies multiple signaling pathways such as metabolic pathways, cytokine-cytokine receptor interaction, cAMP signaling pathway and cell cycle.ConclusionLiraglutide can alleviate the decrease of cell viability and degradation of muscle protein caused by high glucose, and improves cell metabolism and mitochondrial activity. The molecular mechanism of liraglutide to alleviate the effect of high glucose on myoblasts is complex. This study provides a theoretical basis for the clinical effectiveness of liraglutide in the treatment of skeletal muscle lesions in diabetes.

LncRNA LBX2-AS1 promotes proliferation and migratory capacity of clear cell renal cell carcinoma through mitophagy

BackgroundLong non-coding RNAs (lncRNAs) have been extensively investigated in the field of cancer, among which, lncRNA ladybird homeobox 2-antisense RNA 1 (LBX2-AS1) has been demonstrated to exert carcinogenic effects on a variety of malignancies. However, the biological functions of LBX2-AS1 in clear cell renal cell carcinoma (ccRCC) have not been explicitly elucidated.MethodsArraystar lncRNA chip and qRT-PCR verify the expression of LncRNA LBX2-AS1 in ccRCC. CCK-8 assay and cell cloning assay were used to assess the proliferative capacity of ccRCC cells. Migration abilities were quantified by scratch assay and transwell assay. Potential molecular signaling pathways were determined by high-throughput whole transcriptomics analysis. WB analysis was performed to validate the relationship between LBX2-AS1 and key molecules of mitophagy pathway. The effect of LBX2-AS1 on mitophagy was observed by laser confocal microscopy. Rescue experiments further validated the role of downstream gene FOXO3A in the LBX2-AS1 signaling pathway. Finally, the authentic effect of LBX2-AS1 was verified in vivo.ResultsLncRNA LBX2-AS1 was over expressed in ccRCC tissues and could enhance the proliferation and migration of ccRCC cells. Autophagic pathway was identified as a possible mechanism involved in the oncogenic effect of LBX2-AS1. Mitophagy levels were observed in LBX2-AS1 low-expressing cells through laser confocal microscopy. Knockdown of LBX2-AS1 significantly elevated mitophagy levels as observed using laser confocal microscopy and led to FOXOA3 decreasing in and BNIP3L and LC3 enrichment. Meanwhile, LBX2-AS1 knocking down dampened the proliferation of ccRCC cells in vivo.

SVM-Root: Identification of Root-Associated Proteins in Plants by Employing the Support Vector Machine with Sequence-Derived Features

Background: Root is a desirable trait for modern plant breeding programs, as the roots play a pivotal role in the growth and development of plants. Therefore, identification of the genes governing the root traits is an essential research component. With regard to the identification of root-associated genes/proteins, the existing wet-lab experiments are resource intensive and the gene expression studies are species-specific. Thus, we proposed a supervised learning-based computational method for the identification of root-associated proteins. Method: The problem was formulated as a binary classification, where the root-associated proteins and non-root-associated proteins constituted the two classes. Four different machine learning algorithms such as support vector machine (SVM), extreme gradient boosting, random forest, and adaptive boosting were employed for the classification of proteins of the two classes. Sequence-derived features such as AAC, DPC, CTD, PAAC, and ACF were used as input for the learning algorithms. Results: The SVM achieved higher accuracy with the 250 selected features of AAC+DPC+CTD than that of other possible combinations of feature sets and learning algorithms. Specifically, SVM with the selected features achieved overall accuracies of 0.74, 0.73, and 0.73 when evaluated with single 5-fold cross-validation (5F-CV), repeated 5F-CV, and independent test set, respectively. Conclusions: A web-enabled prediction tool SVM-Root (https://iasri-sg.icar.gov.in/svmroot/) has been developed for the computational prediction of the root-associated proteins. Being the first of its kind, the proposed model is believed to supplement the existing experimental methods and high throughput GWAS and transcriptome studies.