Network pharmacology and transcriptomics to determine Danggui Yifei Decoction mechanism of action for the treatment of chronic lung injury.

ETHNOPHARMACOLOGICAL RELEVANCE: Several children with pneumonia (especially severe cases) have symptoms of cough and expectoration during the recovery stage after standard symptomatic treatment, which eventually results in chronic lung injury. Danggui yifei Decoction (DGYFD), a traditional Chinese formula, has shown clinical promise for the treatment of chronic lung injury during the recovery stage of pneumonia, however, its mechanism of action is yet to be deciphered. AIM OF THIS STUDY: To investigate the therapeutic mechanism of DGYFD for the treatment of chronic lung injury by integrating network pharmacology and transcriptomics. MATERIALS AND METHODS: BALB/c mice were used to establish the chronic lung injury mouse model by intratracheal instillation of lipopolysaccharide (LPS). Pathological analysis of lung tissue, lung injury histological score, lung index, protein levels in bronchoalveolar lavage fluid (BALF), immunohistochemical staining, blood rheology, inflammatory cytokines, and oxidative stress levels were used to evaluate the pharmacological effects of DGYFD. Chemical components of DGYFD were identified using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Integrated network pharmacology together with transcriptomics was used to predict potential biological targets. Western blot analysis was used to verify the results. RESULTS: In this study, we demonstrated that DGYFD could improve lung injury pathological changes, decreases lung index, down-regulate NO and IL-6 levels, and regulate blood rheology. In addition, DGYFD was able to reduce the protein levels in BALF, up-regulate the expression levels of occludin and ZO-1, improve the ultrastructure of lung tissues, and reverse the imbalance of AT I and AT II cells to repair the alveolar-capillary permeability barrier. Twenty-nine active ingredients of DGYFD and 389 potential targets were identified by UPLC-MS/MS and network pharmacology, and 64 differentially expressed genes (DEGs) were identified using transcriptomics. GO and KEGG analysis revealed that the MAPK pathway may be the molecular target. Further, we found that DGYFD inhibits phosphorylation levels of p38 MAPK and JNK in chronic lung injury mouse models. CONCLUSIONS: DGYFD could regulate the imbalance between the excessive release of inflammatory cytokines and oxidative stress, repair the alveolar-capillary permeability barrier and improve the pathological changes during chronic lung injury by regulating the MAPK signaling pathway.

Combining transcriptomics and network pharmacology to reveal the mechanism of Zuojin capsule improving spasmolytic polypeptide-expressing metaplasia.

ETHNOPHARMACOLOGICAL RELEVANCE: Spasmolytic polypeptide-expressing metaplasia (SPEM) is a gastric precancerous lesion (GPL). Zuojin capsule (ZJC), consisting of Coptis chinensis Franch. (Ranunculaceae, recorded in the Chinese Pharmacopoeia as Rhizoma Coptidis) and Tetradium ruticarpum (A.Juss.) T.G.Hartley (Rutaceae, recorded in the Chinese Pharmacopoeia as Fructus Evodiae), has long been used for various gastrointestinal diseases. However, the effect and mechanism of ZJC on SPEM remain unclear. AIM OF THE STUDY: To clarify the role of ZJC in improving SPEM and study its mechanism. MATERIALS AND METHODS: The study utilized SPEM mice induced by 250 mg/kg body weight of tamoxifen (TAM) to assess the effects of ZJC and investigate its possible mechanisms. A strategy of transcriptomics combined with network pharmacology was conducted to explore the targets and mechanisms of ZJC in improving SPEM. The "ingredients-target-pathway" network was constructed, and the possible connections were verified by RT-qPCR and Western blot assays. RESULTS: ZJC significantly attenuated the abnormal serological indices, destruction of the gastric mucosal structure, hyperplasia of gastric pits, increased gastric mucus, massive secretion of CD44 and TFF2, oxyntic atrophy and massive proliferation of stem/progenitor cells in TAM-induced SPEM mice. Combined transcriptomics and network pharmacology analysis, 50 core targets of ZJC related to SPEM improvement were obtained. KEGG results showed that the core targets were significantly enriched in the cell cycle, and PI3K-AKT signaling pathway. The top-ranked targets according to PPI network analysis were CDK1, CCNB1, and CCNA2, which are also associated with cell cycle. Combined experiments demonstrated that ZJC can induce G2/M phase cycle arrest and inhibit TAM-induced malignant proliferation by regulating abnormal activation of cell cycle-related proteins such as CDK1, CCNB1, CCNA2 and PI3K-AKT signaling pathways. CONCLUSIONS: ZJC may improve TAM-induced SPEM by inhibiting abnormal activation of cell cycle-related proteins (CDK1, CCNB1, CCNA2) and PI3K-AKT signaling pathway. This finding supports the use of ZJC, a famous traditional Chinese medicine compound, as a potential treatment for gastric precancerous lesions.

Mechanism of Xiaojianzhong decoction in alleviating aspirin-induced gastric mucosal injury revealed by transcriptomics and metabolomics.

ETHNOPHARMACOLOGICAL RELEVANCE: Aspirin, as a first-line drug for the treatment of cardiovascular diseases, currently has high clinical usage. However, reports of aspirin-induced gastric mucosal injury are increasing. Xiaojianzhong decoction (XJZD), a classic traditional Chinese medicine formula, has been shown to alleviate gastric mucosal injury, although its potential mechanism of action requires further study. AIM OF THE STUDY: This study aimed to explore the effect and mechanism of XJZD in preventing aspirin-induced gastric mucosal injury. MATERIALS AND METHODS: Aspirin was used to induce damage in the morning, while XJZD was applied as an intervention in the afternoon. The compounds in the XJZD were analyzed by means of both high-performance liquid chromatography and ultra-performance liquid chromatography-tandem mass spectrometry. The overall condition of the aspirin-related gastric mucosal injury was evaluated. The expressions of inflammatory factors and tight-junction-related proteins and apoptosis were observed via immunohistochemistry and immunofluorescence. The expression levels of the apoptosis-related proteins were detected using Western blot. Transcriptomics was used to perform the integrative analysis of gastric tissues, which was then validated. Molecular dynamics was used to explore the interaction of key compounds within the XJZD with relevant targets. Finally, non-targeted metabolomics was used to observe any metabolic changes and construct a network between the differentially expressed genes and the differential metabolites to elucidate their potential relationship. RESULTS: XJZD can alleviate inflammation response, maintain the gastric mucosal barrier's integrity, reduce apoptosis and necroptosis levels, and promote the proliferation and repair of gastric mucosal tissues. Its mechanism of action may be related to the regulation of TNF-α signaling. Furthermore, molecular docking showed that the cinnamaldehyde within XJZD played an important role in its effects. In addition, XJZD can correct metabolic disorders, mainly regulating amino acid metabolism pathways. Moreover, six differential genes (Cyp1a2, Cyp1a1, Pla2g4c, etc.) were determined to alleviate both gastric mucosal injury and inflammation by regulating arachidonic acid metabolism, Tryptophan metabolism, etc. CONCLUSIONS: This study is the first to report that XJZD can inhibit necroptosis and gastric mucosal injury induced by aspirin, thereby revealing the complex mechanism of XJZD in relation to alleviating gastric mucosal injury from multiple levels and perspectives.

Identification of key genes and biological regulatory mechanisms in diabetic nephropathy: Meta-analysis of gene expression datasets / Identificación de genes clave y mecanismos reguladores biológicos en la nefropatía diabética: metaanálisis de conjuntos de datos de expresión génica

Background: Diabetic nephropathy (DN) which refers to the cases with biopsy proven kidney lesions, is one of the main complications of diabetes all around the world; however, the underlying biological changes causing DN remain to be understood. Studying the alterations in gene expression profiles could give a holistic view of the molecular pathogenicity of DN and aid to discover key molecules as potential therapeutic targets. Here, we performed a meta-analysis study that included microarray gene expression profiles coming from glomerular samples of DN patients in order to acquire a list of consensus Differentially Expressed Genes (meta-DEGs) correlated with DN. Methods: After quality control and normalization steps, five gene expression datasets (GES1009, GSE30528, GSE47183, GSE104948, and GSE93804) were entered into the meta-analysis. The meta-analysis was performed by random effect size method and the meta-DEGs were put through network analysis and different pathway enrichment analyses steps. MiRTarBase and TRRUST databases were utilized to predict the meta-DEGs related miRNAs and transcription factors. A co-regulatory network including DEGs, transcription factors and miRNAs was constructed by Cytoscape, and top molecules were identified based on centrality scores in the network.(AU)

Antecedentes: La nefropatía diabética (ND), que se refiere a los casos con lesiones renales comprobadas por biopsia, es una de las principales complicaciones de la diabetes en todo el mundo. Sin embargo, los cambios biológicos subyacentes que causan la ND aún no se han entendido. Aquí realizamos un estudio de metaanálisis que incluyó perfiles de expresión génica de micromatrices provenientes de muestras glomerulares de pacientes con ND para adquirir una lista de genes expresados diferencialmente (meta-DEG) de consenso correlacionados con ND. Métodos: Después de los pasos de control de calidad y normalización, se ingresaron en el metaanálisis cinco conjuntos de datos de expresión génica (GES1009, GSE30528, GSE47183, GSE104948 y GSE93804). El metaanálisis se realizó mediante el método de tamaño de efecto aleatorio y los meta-DEG se sometieron a análisis de red y a diferentes pasos de análisis de enriquecimiento de ruta. Se utilizaron las bases de datos MiRTarBase y TRRUST para predecir los factores de transcripción y los miARN relacionados con los meta-DEG. Cytoscape construyó una red de corregulación que incluye DEG, factores de transcripción y miARN, y las moléculas principales se identificaron en función de las puntuaciones de centralidad en la red. (AU)

Transcriptome and secretome profiling of sensory neurons reveals sex differences in pathways relevant to insulin sensing and insulin secretion.

Sensory neurons in the dorsal root ganglia (DRG) convey somatosensory and metabolic cues to the central nervous system and release substances from stimulated terminal endings in peripheral organs. Sex-biased variations driven by the sex chromosome complement (XX and XY) have been implicated in the sensory-islet crosstalk. However, the molecular underpinnings of these male-female differences are not known. Here, we aim to characterize the molecular repertoire and the secretome profile of the lower thoracic spinal sensory neurons and to identify molecules with sex-biased insulin sensing- and/or insulin secretion-modulating activity that are encoded independently of circulating gonadal sex hormones. We used transcriptomics and proteomics to uncover differentially expressed genes and secreted molecules in lower thoracic T5-12 DRG sensory neurons derived from sexually immature 3-week-old male and female C57BL/6J mice. Comparative transcriptome and proteome analyses revealed differential gene expression and protein secretion in DRG neurons in males and females. The transcriptome analysis identified, among others, higher insulin signaling/sensing capabilities in female DRG neurons; secretome screening uncovered several sex-specific candidate molecules with potential regulatory functions in pancreatic ß cells. Together, these data suggest a putative role of sensory interoception of insulin in the DRG-islet crosstalk with implications in sensory feedback loops in the regulation of ß-cell activity in a sex-biased manner. Finally, we provide a valuable resource of molecular and secretory targets that can be leveraged for understanding insulin interoception and insulin secretion and inform the development of novel studies/approaches to fathom the role of the sensory-islet axis in the regulation of energy balance in males and females.

Multimodal spatiotemporal transcriptomic resolution of embryonic palate osteogenesis.

The terminal differentiation of osteoblasts and subsequent formation of bone marks an important phase in palate development that leads to the separation of the oral and nasal cavities. While the morphogenetic events preceding palatal osteogenesis are well explored, major gaps remain in our understanding of the molecular mechanisms driving the formation of this bony union of the fusing palate. Through bulk, single-nucleus, and spatially resolved RNA-sequencing analyses of the developing secondary palate, we identify a shift in transcriptional programming between embryonic days 14.5 and 15.5 pinpointing the onset of osteogenesis. We define spatially restricted expression patterns of key osteogenic marker genes that are differentially expressed between these developmental timepoints. Finally, we identify genes in the palate highly expressed by palate nasal epithelial cells, also enriched within palatal osteogenic mesenchymal cells. This investigation provides a relevant framework to advance palate-specific diagnostic and therapeutic biomarker discovery.

The effects of maternal care on the developmental transcriptome and metatranscriptome of a wild bee.

Maternal care acts as a strong environmental stimulus that can induce phenotypic plasticity in animals and may also alter their microbial communities through development. Here, we characterize the developmental metatranscriptome of the small carpenter bee, Ceratina calcarata, across developmental stages and in the presence or absence of mothers. Maternal care had the most influence during early development, with the greatest number and magnitude of differentially expressed genes between maternal care treatments, and enrichment for transcription factors regulating immune response in motherless early larvae. Metatranscriptomic data revealed fungi to be the most abundant group in the microbiome, with Aspergillus the most abundant in early larvae raised without mothers. Finally, integrative analysis between host transcriptome and metatranscriptome highlights several fungi correlating with developmental and immunity genes. Our results provide characterizations of the influence of maternal care on gene expression and the microbiome through development in a wild bee.

Comparative Transcriptomics of Chilodonella hexasticha and C. uncinata Provide New Insights into Adaptations to a Parasitic Lifestyle and Mdivi-1 as a Potential Agent for Chilodonellosis Control.

Chilodonella hexasticha is a harmful parasitic ciliate that can cause severe damage to fish and high mortalities worldwide. Its congeneric species, C. uncinata, is a facultative parasite that not only can be free-living but also can parasitize on fish gills and fins. In this study, single-cell transcriptomes of these two species were assembled and characterized. Numerous enzymes related to energy metabolism and parasitic adaption were identified through annotation in the Non-Redundant (NR), Clusters of Orthologous Genes (COG), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. The expression of isocitrate dehydrogenase (IDH), cytochrome c oxidase subunit 1 (Cox1) and ATP synthase F1, delta subunit (ATP5D) was up-regulated in C. hexasticha compared with C. uncinata. The oxidative phosphorylation process was also enriched in C. hexasticha. The main mitochondrial metabolic pathways in C. hexasticha were depicted and enzymes related to energy metabolism pathways were compared between these two species. More importantly, mitochondrial division inhibitor 1 (mdivi-1) proved to be very effective in killing both C. hexasticha and C. uncinata, which could be a novel drug for Chilodonellosis control. This study can help us better understand the energy metabolisms of C. hexasticha and C. uncinata and provide new insight into novel targets for chilodonellosis control. Meanwhile, the transcriptome data can also facilitate genomic studies of these two species in the future.

Transcriptome from Paired Samples Improves the Power of Comprehensive COVID-19 Host-Viral Characterization.

Previous transcriptome profiling studies showed significantly upregulated genes and altered biological pathways in acute COVID-19. However, changes in the transcriptional signatures during a defined time frame are not yet examined and described. The aims of this study included viral metagenomics and evaluation of the total expression in time-matched and tissue-matched paired COVID-19 samples with the analysis of the host splicing profile to reveal potential therapeutic targets. Prospective analysis of paired nasopharyngeal swabs (NPS) and blood (BL) samples from 18 COVID-19 patients with acute and resolved infection performed using Kallisto, Suppa2, Centrifuge, EdgeR, PantherDB, and L1000CDS2 tools. In NPS, we discovered 6 genes with changed splicing and 40 differentially expressed genes (DEG) that yielded 88 altered pathways. Blood samples yielded 15 alternatively spliced genes. Although the unpaired DEG analysis failed, pairing identified 78 genes and 242 altered pathways with meaningful clinical interpretation and new candidate drug combinations with up to 65% overlap. Metagenomics analyses showed SARS-CoV-2 dominance during and after the acute infection, with a significant reduction in NPS (0.008 vs. 0.002, p = 0.019). Even though both NPS and BL give meaningful insights into expression changes, this is the first demonstration of how the power of blood analysis is vastly maximized by pairing. The obtained results essentially showed that pairing is a determinant between a failed and a comprehensive study. Finally, the bioinformatics results prove to be a comprehensive tool for full-action insights, drug development, and infectious disease research when designed properly.

Identification of Potential Gene Targets for Suppressing Oviposition in Holotrichia parallela Using Comparative Transcriptome Analysis.

Holotrichia parallela is an important plant pest. Comparative feeding experiments showed that the egg production, oviposition duration and survival rate of H. parallela beetles were significantly higher when they fed on elm leaves than when they fed on willow or purpus privet leaves. RNA sequencing was used to determine transcriptomic changes associated with oviposition. Comparative transcriptome analysis revealed that the beetles that fed on elm and willow had a total of 171 genes with differential expression. When the beetles fed on elm and purpus privet, 3568 genes had differential expression. The vitellogenesis, ovarian serine protease, odorant-binding proteins, acyl-CoA synthetase and follicle cell proteins were commonly upregulated genes in elm-fed beetles compared with those fed on willow/purpus privet leaves. The involvement of the follicle cell protein 3C gene in the regulation of oviposition was confirmed using RNA interference. The results provide insights into the molecular mechanisms underlying oviposition in H. parallela feeding on different host plants. This study also describes a method for identifying potentially effective genes for pest control.

Differential Type-I Interferon Response in Buffy Coat Transcriptome of Individuals Infected with SARS-CoV-2 Gamma and Delta Variants.

The innate immune system is the first line of defense against pathogens such as the acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The type I-interferon (IFN) response activation during the initial steps of infection is essential to prevent viral replication and tissue damage. SARS-CoV and SARS-CoV-2 can inhibit this activation, and individuals with a dysregulated IFN-I response are more likely to develop severe disease. Several mutations in different variants of SARS-CoV-2 have shown the potential to interfere with the immune system. Here, we evaluated the buffy coat transcriptome of individuals infected with Gamma or Delta variants of SARS-CoV-2. The Delta transcriptome presents more genes enriched in the innate immune response and Gamma in the adaptive immune response. Interactome and enriched promoter analysis showed that Delta could activate the INF-I response more effectively than Gamma. Two mutations in the N protein and one in the nsp6 protein found exclusively in Gamma have already been described as inhibitors of the interferon response pathway. This indicates that the Gamma variant evolved to evade the IFN-I response. Accordingly, in this work, we showed one of the mechanisms that variants of SARS-CoV-2 can use to avoid or interfere with the host Immune system.

Hormonal Regulation and Stimulation Response of Jatropha curcas L. Homolog Overexpression on Tobacco Leaf Growth by Transcriptome Analysis.

The Flowering locus T (FT) gene encodes the florigen protein, which primarily regulates the flowering time in plants. Recent studies have shown that FT genes also significantly affect plant growth and development. The FT gene overexpression in plants promotes flowering and suppresses leaf and stem development. This study aimed to conduct a transcriptome analysis to investigate the multiple effects of Jatropha curcas L. homolog (JcFT) overexpression on leaf growth in tobacco plants. The findings revealed that JcFT overexpression affected various biological processes during leaf development, including plant hormone levels and signal transduction, lipid oxidation metabolism, terpenoid metabolism, and the jasmonic-acid-mediated signaling pathway. These results suggested that the effects of FT overexpression in plants were complex and multifaceted, and the combination of these factors might contribute to a reduction in the leaf size. This study comprehensively analyzed the effects of JcFT on leaf development at the transcriptome level and provided new insights into the function of FT and its homologous genes.

Comprehensive Transcriptome and Metabolome Analyses Reveal Primary Molecular Regulation Pathways Involved in Peanut under Water and Nitrogen Co-Limitation.

The yield and quality of peanut (Arachis hypogaea L.), an oil crop planted worldwide, are often limited by drought stress (DS) and nitrogen (N) deficiency. To investigate the molecular mechanism by which peanut counteracts DS and N deficiency, we conducted comprehensive transcriptomic and metabolomic analyses of peanut leaves. Herein, 829 known differentially accumulated metabolites, 324 differentially expressed transcription factors, and 5294 differentially expressed genes (DEGs) were identified under different water and N conditions. The transcriptome analysis demonstrated that drought-related DEGs were predominantly expressed in "glycolysis/gluconeogenesis" and "glycerolipid metabolism", while N-deficiency-related DEGs were mainly expressed in starch and sucrose metabolism, as well as in the biosynthesis of amino acid pathways. The biosynthesis, transport, and catabolism of secondary metabolites accounted for a large proportion of the 1317 DEGs present in water and N co-limitation. Metabolomic analysis showed that the metabolic accumulation of these pathways was significantly dependent on the stress conditions. Additionally, the roles of metabolites and genes in these pathways, such as the biosynthesis of amino acids and phenylpropanoid biosynthesis under different stress conditions, were discussed. The results demonstrated that different genes, metabolic pathways, and metabolites were related to DS and N deficiency. Thus, this study elucidates the metabolic pathways and functional genes that can be used for the improvement of peanut resistance to abiotic stress.

Single-Cell Transcriptomic Analysis Reveals the Molecular Profile of Go-Opsin Photoreceptor Cells in Sea Urchin Larvae.

The ability to perceive and respond to light stimuli is fundamental not only for spatial vision but also to many other light-mediated interactions with the environment. In animals, light perception is performed by specific cells known as photoreceptors and, at molecular level, by a group of GPCRs known as opsins. Sea urchin larvae possess a group of photoreceptor cells (PRCs) deploying a Go-Opsin (Opsin3.2) which have been shown to share transcription factors and morphology with PRCs of the ciliary type, raising new questions related to how this sea urchin larva PRC is specified and whether it shares a common ancestor with ciliary PRCs or it if evolved independently through convergent evolution. To answer these questions, we combined immunohistochemistry and fluorescent in situ hybridization to investigate how the Opsin3.2 PRCs develop in the sea urchin Strongylocentrotus purpuratus larva. Subsequently, we applied single-cell transcriptomics to investigate the molecular signature of the Sp-Opsin3.2-expressing cells and show that they deploy an ancient regulatory program responsible for photoreceptors specification. Finally, we also discuss the possible functions of the Opsin3.2-positive cells based on their molecular fingerprint, and we suggest that they are involved in a variety of signaling pathways, including those entailing the thyrotropin-releasing hormone.

MAVEN: compound mechanism of action analysis and visualisation using transcriptomics and compound structure data in R/Shiny.

BACKGROUND: Understanding the Mechanism of Action (MoA) of a compound is an often challenging but equally crucial aspect of drug discovery that can help improve both its efficacy and safety. Computational methods to aid MoA elucidation usually either aim to predict direct drug targets, or attempt to understand modulated downstream pathways or signalling proteins. Such methods usually require extensive coding experience and results are often optimised for further computational processing, making them difficult for wet-lab scientists to perform, interpret and draw hypotheses from. RESULTS: To address this issue, we in this work present MAVEN (Mechanism of Action Visualisation and Enrichment), an R/Shiny app which allows for GUI-based prediction of drug targets based on chemical structure, combined with causal reasoning based on causal protein-protein interactions and transcriptomic perturbation signatures. The app computes a systems-level view of the mechanism of action of the input compound. This is visualised as a sub-network linking predicted or known targets to modulated transcription factors via inferred signalling proteins. The tool includes a selection of MSigDB gene set collections to perform pathway enrichment on the resulting network, and also allows for custom gene sets to be uploaded by the researcher. MAVEN is hence a user-friendly, flexible tool for researchers without extensive bioinformatics or cheminformatics knowledge to generate interpretable hypotheses of compound Mechanism of Action. CONCLUSIONS: MAVEN is available as a fully open-source tool at https://github.com/laylagerami/MAVEN with options to install in a Docker or Singularity container. Full documentation, including a tutorial on example data, is available at https://laylagerami.github.io/MAVEN .

Transcriptomic Analysis in Renal Cell Carcinoma and COVID-19 patients.

COVID-19 pandemic poses a heavy risk upon global public health. The disease's severity and infection rate are high, especially among cancer patients.  The current research was conducted to identify the most common biological pathways and how far they are associated with COVID-19 infection and clear cell renal cell carcinoma. In the current study, the authors analyzed the differentially expressed genes from the experimental and control groups with the help of the GEO2R tool. The study analyzed the protein-protein interactions that occur between the upregulated and downregulated genes from both groups based on the STRING database. In addition, the module analysis was conducted with the Cytoscape software using the MCODE plugin. The outcomes infer the upregulation of 67 genes and downregulation of 176 genes among COVID-19 patients. In the case of patients diagnosed with clear cell renal cell carcinoma, 106 genes got upregulated whereas 77 genes were downregulated. As per the outcomes achieved from the GO analysis, the differentially expressed genes play a role in C-X-C chemokine receptor activity and glycolytic process. Further, the results from the KEGG analysis establish the presence of a genetic association between HIF-1 signaling and lipid metabolism. The current study found the key genes that play a crucial role in the metabolic pathways of COVID-19 and clear cell renal cell carcinoma patients. These genes are found to be promising therapeutic targets in the prevention of complications of infection among cancer patients.

Transcriptomic Response of Differentiating Porcine Myotubes to Thermal Stress and Donor Piglet Age.

Climate change is a current concern that directly and indirectly affects agriculture, especially the livestock sector. Neonatal piglets have a limited thermoregulatory capacity and are particularly stressed by ambient temperatures outside their optimal physiological range, which has a major impact on their survival rate. In this study, we focused on the effects of thermal stress (35 °C, 39 °C, and 41 °C compared to 37 °C) on differentiating myotubes derived from the satellite cells of Musculus rhomboideus, isolated from two different developmental stages of thermolabile 5-day-old (p5) and thermostable 20-day-old piglets (p20). Analysis revealed statistically significant differential expression genes (DEGs) between the different cultivation temperatures, with a higher number of genes responding to cold treatment. These DEGs were involved in the macromolecule degradation and actin kinase cytoskeleton categories and were observed at lower temperatures (35 °C), whereas at higher temperatures (39 °C and 41 °C), the protein transport system, endoplasmic reticulum system, and ATP activity were more pronounced. Gene expression profiling of HSP and RBM gene families, which are commonly associated with cold and heat responses, exhibited a pattern dependent on temperature variability. Moreover, thermal stress exhibited an inhibitory effect on cell cycle, with a more pronounced downregulation during cold stress driven by ADGR genes. Additionally, our analysis revealed DEGs from donors with an undeveloped thermoregulation capacity (p5) and those with a fully developed thermoregulation capacity (p20) under various cultivation temperature. The highest number of DEGs and significant GO terms was observed under temperatures of 35 °C and 37 °C. In particular, under 35 °C, the DEGs were enriched in insulin, thyroid hormone, and calcium signaling pathways. This result suggests that the different thermoregulatory capacities of the donor piglets determined the ability of the primary muscle cell culture to differentiate into myotubes at different temperatures. This work sheds new light on the underlying molecular mechanisms that govern piglet differentiating myotube response to thermal stress and can be leveraged to develop effective thermal management strategies to enhance skeletal muscle growth.

ZINBMM: a general mixture model for simultaneous clustering and gene selection using single-cell transcriptomic data.

Clustering is a critical component of single-cell RNA sequencing (scRNA-seq) data analysis and can help reveal cell types and infer cell lineages. Despite considerable successes, there are few methods tailored to investigating cluster-specific genes contributing to cell heterogeneity, which can promote biological understanding of cell heterogeneity. In this study, we propose a zero-inflated negative binomial mixture model (ZINBMM) that simultaneously achieves effective scRNA-seq data clustering and gene selection. ZINBMM conducts a systemic analysis on raw counts, accommodating both batch effects and dropout events. Simulations and the analysis of five scRNA-seq datasets demonstrate the practical applicability of ZINBMM.

Visual opsin gene expression evolution in the adaptive radiation of cichlid fishes of Lake Tanganyika.

Tuning the visual sensory system to the ambient light is essential for survival in many animal species. This is often achieved through duplication, functional diversification, and/or differential expression of visual opsin genes. Here, we examined 753 new retinal transcriptomes from 112 species of cichlid fishes from Lake Tanganyika to unravel adaptive changes in gene expression at the macro-evolutionary and ecosystem level of one of the largest vertebrate adaptive radiations. We found that, across the radiation, all seven cone opsins-but not the rhodopsin-rank among the most differentially expressed genes in the retina, together with other vision-, circadian rhythm-, and hemoglobin-related genes. We propose two visual palettes characteristic of very shallow- and deep-water living species, respectively, and show that visual system adaptations along two major ecological axes, macro-habitat and diet, occur primarily via gene expression variation in a subset of cone opsin genes.

On the interpretation of transcriptome-wide association studies.

Transcriptome-wide association studies (TWAS) aim to detect relationships between gene expression and a phenotype, and are commonly used for secondary analysis of genome-wide association study (GWAS) results. Results from TWAS analyses are often interpreted as indicating a genetic relationship between gene expression and a phenotype, but this interpretation is not consistent with the null hypothesis that is evaluated in the traditional TWAS framework. In this study we provide a mathematical outline of this TWAS framework, and elucidate what interpretations are warranted given the null hypothesis it actually tests. We then use both simulations and real data analysis to assess the implications of misinterpreting TWAS results as indicative of a genetic relationship between gene expression and the phenotype. Our simulation results show considerably inflated type 1 error rates for TWAS when interpreted this way, with 41% of significant TWAS associations detected in the real data analysis found to have insufficient statistical evidence to infer such a relationship. This demonstrates that in current implementations, TWAS cannot reliably be used to investigate genetic relationships between gene expression and a phenotype, but that local genetic correlation analysis can serve as a potential alternative.