Physiological Measurements and Transcriptomics Reveal the Fitness Costs of Monochamus saltuarius to Bursaphelenchus xylophilus.

The pine wood nematode (PWN) uses several Monochamus species as vehicles, through a temporary hitchhiking process known as phoresy, enabling it to access new host plant resources. Monochamus saltuarius acts as a new and major vector of the PWN in Northeastern China, showing lower PWN carrying capacity and a shorter transmission cycle compared to established vectors. The apparently altered symbiotic relationship offers an interesting area for researching the costs and adaptions involved in nematode-beetle, a specialized phoresy. We analyzed the response and fitness costs of M. saltuarius through physiological measurements and transcriptomics. The PWN exerted adverse repercussions on the growth and development of M. saltuarius. The PWN accelerated larval development into pupae, while beetle adults carrying the PWN exhibited an elevated abnormality rate and mortality, and reduced starvation resistance. During the pupal stage, the expression of growth-related genes, including ecdysone-inducible genes (E74EA), cuticle proteins, and chitin genes (CHTs), markedly increased. Meanwhile, the induced immune response, mainly by the IMD and Toll signaling pathways, could be a contributing factor to adult abnormality and mortality. Adult gonads and trachea exhibited enrichment in pathways related to fatty acid elongation, biosynthesis, and metabolism. FASN, ELOVL, and SCD possibly contributed to resistance against PWN. Our research indicated that phoretic interactions between vector beetles and PWN vary throughout the vector's lifespan, particularly before and after entry into the trachea. This study highlighted the fitness costs of immunity and metabolism on the vector beetle, indicating the adaptation mechanisms and evolutionary trade-offs to PWN.

Assessment and Partial Characterization of Candidate Genes in Dihydrochalcone and Arbutin Biosynthesis in an Apple-Pear Hybrid by De Novo Transcriptome Assembly.

Apples (Malus × domestica Borkh.) and pears (Pyrus communis L.) are valuable crops closely related within the Rosaceae family with reported nutraceutical properties derived from secondary metabolites including phloridzin and arbutin, which are distinctive phenolic metabolites characterizing apples and pears, respectively. Here, we generated a de novo transcriptome assembly of an intergeneric hybrid between apple and pear, accumulating intermediate levels of phloridzin and arbutin. Combining RNA-seq, in silico functional annotation prediction, targeted gene expression analysis, and expression-metabolite correlations, we identified candidate genes for functional characterization, resulting in the identification of active arbutin synthases in the hybrid and parental genotypes. Despite exhibiting an active arbutin synthase in vitro, the natural lack of arbutin in apples is reasoned by the absence of the substrate and broad substrate specificity. Altogether, our study serves as the basis for future assessment of potential physiological roles of identified genes by genome editing of hybrids and pears.

Transcriptomic analysis-guided assessment of precision-cut tumor slices (PCTS) as an ex-vivo tool in cancer research.

With cancer immunotherapy and precision medicine dynamically evolving, there is greater need for pre-clinical models that can better replicate the intact tumor and its complex tumor microenvironment (TME). Precision-cut tumor slices (PCTS) have recently emerged as an ex vivo human tumor model, offering the opportunity to study individual patient responses to targeted therapies, including immunotherapies. However, little is known about the physiologic status of PCTS and how culture conditions alter gene expression. In this study, we generated PCTS from head and neck cancers (HNC) and mesothelioma tumors (Meso) and undertook transcriptomic analyses to understand the changes that occur in the timeframe between PCTS generation and up to 72 h (hrs) in culture. Our findings showed major changes occurring during the first 24 h culture period of PCTS, involving genes related to wound healing, extracellular matrix, hypoxia, and IFNγ-dependent pathways in both tumor types, as well as tumor-specific changes. Collectively, our data provides an insight into PCTS physiology, which should be taken into consideration when designing PCTS studies, especially in the context of immunology and immunotherapy.

Assessment of the Effect of Leonurine Hydrochloride in a Mouse Model of PCOS by Gene Expression Profiling.

Polycystic ovary syndrome (PCOS) is an endocrine disease commonly associated with metabolic disorders in females. Leonurine hydrochloride (Leo) plays an important role in regulating immunity, tumours, uterine smooth muscle, and ovarian function. However, the effect of Leo on PCOS has not been reported. Here, we used dehydroepiandrosterone to establish a mouse model of PCOS, and some mice were then treated with Leo by gavage. We found that Leo could improve the irregular oestros cycle of PCOS mice, reverse the significantly greater serum testosterone (T) and luteinising hormone (LH) levels, significantly reduce the follicle-stimulating hormone (FSH) level, and significantly increase the LH/FSH ratio of PCOS mice. Leo could also change the phenomenon of ovaries in PCOS mice presented with cystic follicular multiplication and a lacking corpus luteum. Transcriptome analysis identified 177 differentially expressed genes related to follicular development between the model and Leo groups. Notably, the cAMP signalling pathway, neuroactive ligand-receptor interactions, the calcium signalling pathway, the ovarian steroidogenesis pathway, and the Lhcgr, Star, Cyp11a, Hsd17b7, Camk2b, Calml4, and Phkg1 genes may be most related to improvements in hormone levels and the numbers of ovarian cystic follicles and corpora lutea in PCOS mice treated by Leo, which provides a reference for further study of the mechanism of Leo.

stDiff: a diffusion model for imputing spatial transcriptomics through single-cell transcriptomics.

Spatial transcriptomics (ST) has become a powerful tool for exploring the spatial organization of gene expression in tissues. Imaging-based methods, though offering superior spatial resolutions at the single-cell level, are limited in either the number of imaged genes or the sensitivity of gene detection. Existing approaches for enhancing ST rely on the similarity between ST cells and reference single-cell RNA sequencing (scRNA-seq) cells. In contrast, we introduce stDiff, which leverages relationships between gene expression abundance in scRNA-seq data to enhance ST. stDiff employs a conditional diffusion model, capturing gene expression abundance relationships in scRNA-seq data through two Markov processes: one introducing noise to transcriptomics data and the other denoising to recover them. The missing portion of ST is predicted by incorporating the original ST data into the denoising process. In our comprehensive performance evaluation across 16 datasets, utilizing multiple clustering and similarity metrics, stDiff stands out for its exceptional ability to preserve topological structures among cells, positioning itself as a robust solution for cell population identification. Moreover, stDiff's enhancement outcomes closely mirror the actual ST data within the batch space. Across diverse spatial expression patterns, our model accurately reconstructs them, delineating distinct spatial boundaries. This highlights stDiff's capability to unify the observed and predicted segments of ST data for subsequent analysis. We anticipate that stDiff, with its innovative approach, will contribute to advancing ST imputation methodologies.

Cost-Efficient Transcriptomic-Based Drug Screening.

Transcriptomics allows to obtain comprehensive insights into cellular programs and their responses to perturbations. Despite a significant decrease in the costs of library production and sequencing in the last decade, applying these technologies at the scale necessary for drug screening remains prohibitively expensive, obstructing the immense potential of these methods. Our study presents a cost-effective system for transcriptome-based drug screening, combining miniaturized perturbation cultures with mini-bulk transcriptomics. The optimized mini-bulk protocol provides informative biological signals at cost-effective sequencing depth, enabling extensive screening of known drugs and new molecules. Depending on the chosen treatment and incubation time, this protocol will result in sequencing libraries within approximately 2 days. Due to several stopping points within this protocol, the library preparation, as well as the sequencing, can be performed time-independently. Processing simultaneously a high number of samples is possible; measurement of up to 384 samples was tested without loss of data quality. There are also no known limitations to the number of conditions and/or drugs, despite considering variability in optimal drug incubation times.

Unlocking the Power of Transcriptomic Biomarkers in Qualitative and Quantitative Genotoxicity Assessment of Chemicals.

To modernize genotoxicity assessment and reduce reliance on experimental animals, new approach methodologies (NAMs) that provide human-relevant dose-response data are needed. Two transcriptomic biomarkers, GENOMARK and TGx-DDI, have shown a high classification accuracy for genotoxicity. As these biomarkers were extracted from different training sets, we investigated whether combining the two biomarkers in a human-derived metabolically competent cell line (i.e., HepaRG) provides complementary information for the classification of genotoxic hazard identification and potency ranking. First, the applicability of GENOMARK to TempO-Seq, a high-throughput transcriptomic technology, was evaluated. HepaRG cells were exposed for 72 h to increasing concentrations of 10 chemicals (i.e., eight known in vivo genotoxicants and two in vivo nongenotoxicants). Gene expression data were generated using the TempO-Seq technology. We found a prediction performance of 100%, confirming the applicability of GENOMARK to TempO-Seq. Classification using TGx-DDI was then compared to GENOMARK. For the chemicals identified as genotoxic, benchmark concentration modeling was conducted to perform potency ranking. The high concordance observed for both hazard classification and potency ranking by GENOMARK and TGx-DDI highlights the value of integrating these NAMs in a weight of evidence evaluation of genotoxicity.

Socioeconomic inequalities in early adulthood disrupt the immune transcriptomic landscape via upstream regulators.

Disparities in socio-economic status (SES) predict many immune system-related diseases, and previous research documents relationships between SES and the immune cell transcriptome. Drawing on a bioinformatically-informed network approach, we situate these findings in a broader molecular framework by examining the upstream regulators of SES-associated transcriptional alterations. Data come from the National Longitudinal Study of Adolescent to Adult Health (Add Health), a nationally representative sample of 4543 adults in the United States. Results reveal a network-of differentially expressed genes, transcription factors, and protein neighbors of transcription factors-that shows widespread SES-related dysregulation of the immune system. Mediational models suggest that body mass index (BMI) plays a key role in accounting for many of these associations. Overall, the results reveal the central role of upstream regulators in socioeconomic differences in the molecular basis of immunity, which propagate to increase risk of chronic health conditions in later-life.

Protectiveness of NAM-based hazard assessment - which testing scope is required?

Hazard assessment (HA) requires toxicity tests to allow deriving protective points of departure (PoDs) for risk assessment irrespective of a compound's mode of action (MoA). The scope of in vitro test batteries (ivTB) thereby necessitated for systemic toxicity is still unclear. We explored the protectiveness regarding systemic toxicity of an ivTB with a scope, which was guided by previous findings from rodent studies, where examining six main targets, including liver and kidney, was sufficient to predict the guideline scope-based PoD with high probability. The ivTB comprises human in vitro models representing liver, kidney, lung and the neuronal system covering transcriptome, mitochondrial dysfunction and neuronal outgrowth. Additionally, 32 CALUX®- and 10 HepG2 BAC-GFP reporters cover a broad range of disturbance mechanisms. Eight compounds were chosen for causing adverse effects such as immunotoxicity or anemia in vivo, i.e., effects not directly covered by assays in the ivTB. PoDs derived from the ivTB and from oral repeated dose studies in rodents were extrapolated to maximum unbound plasma concentrations for comparison. The ivTB-based PoDs were one to five orders of magnitude lower than in vivo PoDs for six of eight compounds, implying that they were protective. The extent of in vitro response varied across test compounds. Especially for hematotoxic substances, the ivTB showed either no response or only cytotoxicity. Assays better capturing this type of hazard would be needed to complement the ivTB. This study highlights the potentially broad applicability of ivTBs for deriving protective PoDs of compounds with unknown MoA.

Animal tests are used to determine which amount of a chemical is toxic ('threshold of toxicity') and which organs are affected. In principle, the threshold can also be derived solely from tests with cultured cells. However, only a limited number of cell types can practically be tested, so one challenge is to determine how many and which types shall be tested. In animal studies, only few organs including liver and kidney are regularly among those most sensitively affected. We explored whether a cell-based test battery representing these sensitive organs and covering important mechanisms of toxicity can be used to derive protective human thresholds. To challenge this approach, eight chemicals were tested that primarily cause effects in organs not directly represented in our test battery. Results provided protective thresholds for most of the investigated compounds and gave indications how to further improve the approach towards a full-fledged replacement for animal tests.

Adding a Gene Expression Profile Test to Aid Differential Diagnosis and Treatment in Aggressive Large B-Cell Lymphoma: An Early Exploratory Economic Evaluation.

BACKGROUND AND OBJECTIVE: Adding gene expression profiles (GEPs) to the current diagnostic work-up of aggressive large B-cell lymphomas may lead to the reclassification of patients, treatment changes and improved outcomes. A GEP test is in development using TempO-Seq® technology to distinguish Burkitt lymphoma (BL) and primary mediastinal large B-cell lymphoma (PMBCL) from diffuse large B-cell lymphoma (DLBCL), and to classify patients with DLBLC and to predict the benefit of (e.g.) adding bortezomib to R-CHOP therapy (RB-CHOP). This study aims to estimate the potential impact of a GEP test on costs and health outcomes to inform pricing and evidence generation strategies. METHODS: Three decision models were developed comparing diagnostic strategies with and without GEP signatures over a lifetime horizon using a UK health and social care perspective. Inputs were taken from a recent clinical trial, literature and expert opinion. We estimated the maximum price of the test using a threshold of Great Britain Pound (GBP) 30,000 per quality-adjusted life-year (QALY). Sensitivity analyses were conducted. RESULTS: The estimated maximum threshold price for a combined test to be cost effective is GBP 15,352. At base-case values, the BL signature delivers QALY gains of 0.054 at an additional cost of GBP 275. This results in a net monetary benefit at a threshold of GBP 30,000 per QALY of GBP 1345. For PMBCL, the QALY gain was 0.0011 at a cost saving of GBP 406 and the net monetary benefit was GBP 437. The hazard ratio for the impact of treating BL less intensively must be at least 1.2 for a positive net monetary benefit. For identifying patients with the DLBCL subtype responsive to bortezomib, QALY gain was 0.2465 at a cost saving of GBP 6175, resulting in a net monetary benefit of GBP 13,570. In a probabilistic sensitivity analysis using 1000 simulations, a testing strategy was superior to a treat all with R-CHOP strategy in 81% of the simulations and with a cost saving in 92% assuming a cost price of zero. CONCLUSIONS: Our estimates show that the combined test has a high probability of being cost effective. There is good quality evidence for the benefit of subtyping DLBCL but the evidence on the number of patients reclassified to or from BL and PMBCL and the impact of a more precise diagnosis and the cost of treatment is weak. The developers can use the price estimate to inform a return on investment calculations. Evidence will be required of how well the TempO-Seq® technology performs compared to the testing GEP technology used for subtyping in the recent clinical trial. For BL and PMBCL elements of the test, evidence would be required of the number of patients reclassified and improved costing information would be useful. The diagnostic and therapeutic environment in haematological malignancies is fast moving, which increases the risk for developers of diagnostic tests.

A genetic and transcriptomic assessment of the KTN1 gene in Parkinson's disease risk.

Parkinson's disease (PD) is a progressive neurological disorder caused by both genetic and environmental factors. An association has been described between KTN1 genetic variants and changes in its expression in the putamen and substantia nigra brain regions and an increased risk for PD. Here, we examine the link between PD susceptibility and KTN1 using individual-level genotyping data and summary statistics from the most recent genome-wide association studies (GWAS) for PD risk and age at onset from the International Parkinson's Disease Genomics Consortium (IPDGC), as well as whole-genome sequencing data from the Accelerating Medicines Partnership Parkinson's disease (AMP-PD) initiative. To investigate the potential effect of changes in KTN1 expression on PD compared to unaffected individuals, we further assess publicly available expression quantitative trait loci (eQTL) results from GTEx v8 and BRAINEAC and transcriptomics data from AMP-PD. Overall, we found no genetic associations between KTN1 and PD in our cohorts but found potential evidence of differences in mRNA expression, which needs to be further explored.

Common and ethnic-specific derangements in skeletal muscle transcriptome associated with obesity.

BACKGROUND: Obesity is a common disease with a higher prevalence among African Americans. Obesity alters cellular function in many tissues, including skeletal muscle, and is a risk factor for many life-threatening diseases, including cardiovascular disease and diabetes. The similarities and differences in molecular mechanisms that may explain ethnic disparities in obesity between African and European ancestry individuals have not been studied. METHODS: In this study, data from transcriptome-wide analyses on skeletal muscle tissues from well-powered human cohorts were used to compare genes and biological pathways affected by obesity in European and African ancestry populations. Data on obesity-induced differentially expressed transcripts and GWAS-identified SNPs were integrated to prioritize target genes for obesity-associated genetic variants. RESULTS: Linear regression analysis in the FUSION (European, N = 301) and AAGMEx (African American, N = 256) cohorts identified a total of 2569 body mass index (BMI)-associated transcripts (q < 0.05), of which 970 genes (at p < 0.05) are associated in both cohorts, and the majority showed the same direction of effect on BMI. Biological pathway analyses, including over-representation and gene-set enrichment analyses, identified enrichment of protein synthesis pathways (e.g., ribosomal function) and the ceramide signaling pathway in both cohorts among BMI-associated down- and up-regulated transcripts, respectively. A comparison using the IPA-tool suggested the activation of inflammation pathways only in Europeans with obesity. Interestingly, these analyses suggested repression of the mitochondrial oxidative phosphorylation pathway in Europeans but showed its activation in African Americans. Integration of SNP-to-Gene analyses-predicted target genes for obesity-associated genetic variants (GWAS-identified SNPs) and BMI-associated transcripts suggested that these SNPs might cause obesity by altering the expression of 316 critical target genes (e.g., GRB14) in the muscle. CONCLUSIONS: This study provides a replication of obesity-associated transcripts and biological pathways in skeletal muscle across ethnicities, but also identifies obesity-associated processes unique in either African or European ancestry populations.

TCOD: an integrated resource for tropical crops.

Tropical crops are vital for tropical agriculture, with resource scarcity, functional diversity and extensive market demand, providing considerable economic benefits for the world's tropical agriculture-producing countries. The rapid development of sequencing technology has promoted a milestone in tropical crop research, resulting in the generation of massive amount of data, which urgently needs an effective platform for data integration and sharing. However, the existing databases cannot fully satisfy researchers' requirements due to the relatively limited integration level and untimely update. Here, we present the Tropical Crop Omics Database (TCOD, https://ngdc.cncb.ac.cn/tcod), a comprehensive multi-omics data platform for tropical crops. TCOD integrates diverse omics data from 15 species, encompassing 34 chromosome-level de novo assemblies, 1 255 004 genes with functional annotations, 282 436 992 unique variants from 2048 WGS samples, 88 transcriptomic profiles from 1997 RNA-Seq samples and 13 381 germplasm items. Additionally, TCOD not only employs genes as a bridge to interconnect multi-omics data, enabling cross-species comparisons based on homology relationships, but also offers user-friendly online tools for efficient data mining and visualization. In short, TCOD integrates multi-species, multi-omics data and online tools, which will facilitate the research on genomic selective breeding and trait biology of tropical crops.

[Exploration of transcriptome SSR markers and its application in genetic diversity assessment of Asarum sieboldii].

To explore the genetic diversity of Asarum sieboldii this study developed SSR markers based on transcriptome sequencing results and five populations of A.sieboldii from different regions were used as samples for genetic diversity assessment using software such as GenALEx 6.5, NTSYS 2.1, and Structure 2.3.4. The results showed that 16 SSR markers with high polymorphism and good repeatability were selected from the A.sieboldii transcriptome. Primers designed based on the flanking sequences of these markers successfully amplified 56 polymorphic fragments from 150 individual samples of the five A.sieboldii populations. On average, each primer amplified 3.5 polymorphic fragments, ranging from 2 to 8. The mean values of expected heterozygosity(H_e), Shannon's diversity index(I), Nei's gene diversity index(H), and the polymorphic information content(PIC) were 0.172, 0.281, 0.429, and 0.382, respectively. The mean population differentiation coefficient(F_(ST)) was 0.588, consistent with the analysis of molecular variance(AMOVA) results, which indicated greater genetic variation among A.sieboldii populations(69%) than that within populations(31%). The percentage of polymorphic loci(PPL) ranged from highest to lowest as SNJ>LN>SY>SZ>TB. Principal coordinate analysis(PCoA) and UPGMA clustering analysis further revealed genetic clustering of A.sieboldii individuals based on their geographical distribution, consistent with the results of the structure clustering analysis. In summary, the SSR markers developed from the transcriptome effectively assessed the genetic differentiation and population structure of natural A.sieboldii populations, revealing a relatively low genetic diversity in A.sieboldii, with genetic variation primarily observed at the population level and a correlation between population differentiation and geographic distance.

Comparative Transcriptomic Assessment of Chemosensory Genes in Adult and Larval Olfactory Organs of Cnaphalocrocis medinalis.

The rice leaf folder, Cnaphalocrocis medinalis (Lepidoptera: Pyralidae), is a notorious pest of rice in Asia. The larvae and adults of C. medinalis utilize specialized chemosensory systems to adapt to different environmental odors and physiological behaviors. However, the differences in chemosensory genes between the olfactory organs of these two different developmental stages remain unclear. Here, we conducted a transcriptome analysis of larvae heads, male antennae, and female antennae in C. medinalis and identified 131 putative chemosensory genes, including 32 OBPs (8 novel OBPs), 23 CSPs (2 novel CSPs), 55 ORs (17 novel ORs), 19 IRs (5 novel IRs) and 2 SNMPs. Comparisons between larvae and adults of C. medinalis by transcriptome and RT-qPCR analysis revealed that the number and expression of chemosensory genes in larval heads were less than that of adult antennae. Only 17 chemosensory genes (7 OBPs and 10 CSPs) were specifically or preferentially expressed in the larval heads, while a total of 101 chemosensory genes (21 OBPs, 9 CSPs, 51 ORs, 18 IRs, and 2 SNMPs) were specifically or preferentially expressed in adult antennae. Our study found differences in chemosensory gene expression between larvae and adults, suggesting their specialized functions at different developmental stages of C. medinalis. These results provide a theoretical basis for screening chemosensory genes as potential molecular targets and developing novel management strategies to control C. medinalis.

Transcriptomic characterization of Trichoderma harzianum T34 primed tomato plants: assessment of biocontrol agent induced host specific gene expression and plant growth promotion.

In this study, we investigated the intricate interplay between Trichoderma and the tomato genome, focusing on the transcriptional and metabolic changes triggered during the late colonization event. Microarray probe set (GSE76332) was utilized to analyze the gene expression profiles changes of the un-inoculated control (tomato) and Trichoderma-tomato interactions for identification of the differentially expressed significant genes. Based on principal component analysis and R-based correlation, we observed a positive correlation between the two cross-comaparable groups, corroborating the existence of transcriptional responses in the host triggered by Trichoderma priming. The statistically significant genes based on different p-value cut-off scores [(padj-values or q-value); padj-value < 0.05], [(pcal-values); pcal-value < 0.05; pcal < 0.01; pcal < 0.001)] were cross compared. Through cross-comparison, we identified 156 common genes that were consistently significant across all probability thresholds, and showing a strong positive corelation between p-value and q-value in the selected probe sets. We reported TD2, CPT1, pectin synthase, EXT-3 (extensin-3), Lox C, and pyruvate kinase (PK), which exhibited upregulated expression, and Glb1 and nitrate reductase (nii), which demonstrated downregulated expression during Trichoderma-tomato interaction. In addition, microbial priming with Trichoderma resulted into differential expression of transcription factors related to systemic defense and flowering including MYB13, MYB78, ERF2, ERF3, ERF5, ERF-1B, NAC, MADS box, ZF3, ZAT10, A20/AN1, polyol sugar transporter like zinc finger proteins, and a novel plant defensin protein. The potential bottleneck and hub genes involved in this dynamic response were also identified. The protein-protein interaction (PPI) network analysis based on 25 topmost DEGS (pcal-value < 0.05) and the Weighted Correlation Gene Network Analysis (WGCNA) of the 1786 significant DEGs (pcal-value < 0.05) we reported the hits associated with carbohydrate metabolism, secondary metabolite biosynthesis, and the nitrogen metabolism. We conclude that the Trichoderma-induced microbial priming re-programmed the host genome for transcriptional response during the late colonization event and were characterized by metabolic shifting and biochemical changes specific to plant growth and development. The work also highlights the relevance of statistical parameters in understanding the gene regulatory dynamics and complex regulatory networks based on differential expression, co-expression, and protein interaction networks orchestrating the host responses to beneficial microbial interactions.

Delivery and Transcriptome Assessment of an In Vitro Three-Dimensional Proximal Tubule Model Established by Human Kidney 2 Cells in Clinical Gelatin Sponges.

The high prevalence of kidney diseases and the low identification rate of drug nephrotoxicity in preclinical studies reinforce the need for representative yet feasible renal models. Although in vitro cell-based models utilizing renal proximal tubules are widely used for kidney research, many proximal tubule cell (PTC) lines have been indicated to be less sensitive to nephrotoxins, mainly due to altered expression of transporters under a two-dimensional culture (2D) environment. Here, we selected HK-2 cells to establish a simplified three-dimensional (3D) model using gelatin sponges as scaffolds. In addition to cell viability and morphology, we conducted a comprehensive transcriptome comparison and correlation analysis of 2D and 3D cultured HK-2 cells to native human PTCs. Our 3D model displayed stable and long-term growth with a tubule-like morphology and demonstrated a more comparable gene expression profile to native human PTCs compared to the 2D model. Many missing or low expressions of major genes involved in PTC transport and metabolic processes were restored, which is crucial for successful nephrotoxicity prediction. Consequently, we established a cost-effective yet more representative model for in vivo PTC studies and presented a comprehensive transcriptome analysis for the systematic characterization of PTC lines.

Transcriptome analysis revealed immune responses in the kidney of Atlantic salmon (Salmo salar) co-infected with sea lice (Lepeophtheirus salmonis) and infectious salmon anemia virus.

Sea lice (Lepeophtheirus salmonis) and infectious salmon anemia virus (ISAv) are two of the most important pathogens in Atlantic salmon (Salmo salar) farming and typically cause substantial economic losses to the industry. However, the immune interactions between hosts and these pathogens are still unclear, especially in the scenario of co-infection. In this study, we artificially infected Atlantic salmon with sea lice and ISAv, and investigated the gene expression patterns of Atlantic salmon head kidneys in response to both lice only and co-infection with lice and ISAv by transcriptomic analysis. The challenge experiment indicated that co-infection resulted in a cumulative mortality rate of 47.8 %, while no mortality was observed in the lice alone infection. We identified 240 differentially expressed genes (DEGs) under the lice alone infection, of which 185 were down-regulated and 55 were up-regulated, while a total of 994 DEGs were identified in the co-infection, of which 206 were down-regulated and 788 were significantly up-regulated. The pathway enrichment analysis revealed that single-infection significantly suppressed the innate immune system (e.g., the complement system), whereas co-infection induced a strong immune response, leading to the activation of immune-related signaling pathways such as Toll-like receptors and NOD-like receptors pathways, as well as significant upregulation of genes related to the activation of interferon and MH class I protein complex. Our results provide the first global transcriptomic study of gene expression in the Atlantic salmon head kidney in response to co-infection with sea lice and ISAv, and provided the baseline knowledge for understanding the immune responses during co-infection.

Hidden Markov random field models for cell-type assignment of spatially resolved transcriptomics.

MOTIVATION: The recent development of spatially resolved transcriptomics (SRT) technologies has facilitated research on gene expression in the spatial context. Annotating cell types is one crucial step for downstream analysis. However, many existing algorithms use an unsupervised strategy to assign cell types for SRT data. They first conduct clustering analysis and then aggregate cluster-level expression based on the clustering results. This workflow fails to leverage the marker gene information efficiently. On the other hand, other cell annotation methods designed for single-cell RNA-seq data utilize the cell-type marker genes information but fail to use spatial information in SRT data. RESULTS: We introduce a statistical spatial transcriptomics cell assignment model, SPAN, to annotate clusters of cells or spots into known types in SRT data with prior knowledge of predefined marker genes and spatial information. The SPAN model annotates cells or spots from SRT data using predefined overexpressed marker genes and combines a mixture model with a hidden Markov random field to model the spatial dependency between neighboring spots. We demonstrate the effectiveness of SPAN against spatial and nonspatial clustering algorithms through extensive simulation and real data experiments. AVAILABILITY AND IMPLEMENTATION: https://github.com/ChengZ352/SPAN.

Nerve transcriptomes in autoimmune and genetic demyelinating neuropathies: Pathogenic pathway assessment of nerve demyelination.

The pathogenesis of autoimmune demyelinating neuropathies is poorly understood compared to inherited demyelinating forms. We performed whole transcriptome (RNA-Seq) using nerve biopsy tissues of patients with different autoimmune and inherited demyelinating neuropathies (CIDP n = 10, POEMS n = 18, DADS n = 3, CMT1 n = 3) versus healthy controls (n = 6). A limited number of differentially expressed genes compared to healthy controls were identified (POEMS = 125, DADS = 15, CMT = 14, CIDP = 5). Divergent pathogenic pathways including inflammatory, demyelinating and neurite regeneration such as with the triggering receptor expressed on myeloid cells (TREM1) part of the immunoglobulin superfamily and RhoGD1 are found. Shared and discordant pathogenic injury are discovered between autoimmune and inherited forms.