The search for elite cultivars with better architecture has been a demand by farmers of the chickpea and lentil crops, which aims to systematize their mechanized planting and harvesting on a large scale. Therefore, the identification of genes associated with the regulation of the branching and architecture of these plants has currently gained great importance. Herein, this work aimed to gain insight into transcriptomic changes of two contrasting chickpea and lentil cultivars in terms of branching pattern (little versus highly branched cultivars). In addition, we aimed to identify candidate genes involved in the regulation of shoot branching that could be used as future targets for molecular breeding. The axillary and apical buds of chickpea cultivars Blanco lechoso and FLIP07-318C, and lentil cultivars Castellana and Campisi, considered as little and highly branched, respectively, were harvested. A total of 1,624 and 2,512 transcripts were identified as differentially expressed among different tissues and contrasting cultivars of chickpea and lentil, respectively. Several gene categories were significantly modulated such as cell cycle, DNA transcription, energy metabolism, hormonal biosynthesis and signaling, proteolysis, and vegetative development between apical and axillary tissues and contrasting cultivars of chickpea and lentil. Based on differential expression and branching-associated biological function, ten chickpea genes and seven lentil genes were considered the main players involved in differentially regulating the plant branching between contrasting cultivars. These collective data putatively revealed the general mechanism and high-effect genes associated with the regulation of branching in chickpea and lentil, which are potential targets for manipulation through genome editing and transgenesis aiming to improve plant architecture.

UNASSIGNED: Rheumatoid arthritis (RA) is a systemic disease that attacks the joints and causes a heavy economic burden on humans worldwide. T cells regulate RA progression and are considered crucial targets for therapy. Therefore, we aimed to integrate multiple datasets to explore the mechanisms of RA. Moreover, we established a T cell-related diagnostic model to provide a new method for RA immunotherapy.
UNASSIGNED: scRNA-seq and bulk-seq datasets for RA were obtained from the Gene Expression Omnibus (GEO) database. Various methods were used to analyze and characterize the T cell heterogeneity of RA. Using Mendelian randomization (MR) and expression quantitative trait loci (eQTL), we screened for potential pathogenic T cell marker genes in RA. Subsequently, we selected an optimal machine learning approach by comparing the nine types of machine learning in predicting RA to identify T cell-related diagnostic features to construct a nomogram model. Patients with RA were divided into different T cell-related clusters using the consensus clustering method. Finally, we performed immune cell infiltration and clinical correlation analyses of T cell-related diagnostic features.
UNASSIGNED: By analyzing the scRNA-seq dataset, we obtained 10,211 cells that were annotated into 7 different subtypes based on specific marker genes. By integrating the eQTL from blood and RA GWAS, combined with XGB machine learning, we identified a total of 8 T cell-related diagnostic features (MIER1, PPP1CB, ICOS, GADD45A, CD3D, SLFN5, PIP4K2A, and IL6ST). Consensus clustering analysis showed that RA could be classified into two different T-cell patterns (Cluster 1 and Cluster 2), with Cluster 2 having a higher T-cell score than Cluster 1. The two clusters involved different pathways and had different immune cell infiltration states. There was no difference in age or sex between the two different T cell patterns. In addition, ICOS and IL6ST were negatively correlated with age in RA patients.
UNASSIGNED: Our findings elucidate the heterogeneity of T cells in RA and the communication role of these cells in an RA immune microenvironment. The construction of T cell-related diagnostic models provides a resource for guiding RA immunotherapeutic strategies.

In this study, we delved into the comparative analysis of gene expression data across RNA-Seq and NanoString platforms. While RNA-Seq covered 19,671 genes and NanoString targeted 773 genes associated with immune responses to viruses, our primary focus was on the 754 genes found in both platforms. Our experiment involved 16 different infection conditions, with samples derived from 3D airway organ-tissue equivalents subjected to three virus types, influenza A virus (IAV), human metapneumovirus (MPV), and parainfluenza virus 3 (PIV3). Post-infection measurements, after UV (inactive virus) and Non-UV (active virus) treatments, were recorded at 24-h and 72-h intervals. Including untreated and Mock-infected OTEs as control groups enabled differentiating changes induced by the virus from those arising due to procedural elements. Through a series of methodological approaches (including Spearman correlation, Distance correlation, Bland-Altman analysis, Generalized Linear Models Huber regression, the Magnitude-Altitude Score (MAS) algorithm and Gene Ontology analysis) the study meticulously contrasted RNA-Seq and NanoString datasets. The Magnitude-Altitude Score algorithm, which integrates both the amplitude of gene expression changes (magnitude) and their statistical relevance (altitude), offers a comprehensive tool for prioritizing genes based on their differential expression profiles in specific viral infection conditions. We observed a strong congruence between the platforms, especially in identifying key antiviral defense genes. Both platforms consistently highlighted genes including ISG15, MX1, RSAD2, and members of the OAS family (OAS1, OAS2, OAS3). The IFIT proteins (IFIT1, IFIT2, IFIT3) were emphasized for their crucial role in counteracting viral replication by both platforms. Additionally, CXCL10 and CXCL11 were pinpointed, shedding light on the organ tissue equivalent\'s innate immune response to viral infections. While both platforms provided invaluable insights into the genetic landscape of organoids under viral infection, the NanoString platform often presented a more detailed picture in situations where RNA-Seq signals were more subtle. The combined data from both platforms emphasize their joint value in advancing our understanding of viral impacts on lung organoids.

UNASSIGNED: Sex-differential biology may contribute to the consistently male-biased prevalence of autism spectrum disorder (ASD). Gene expression differences between males and females in the brain can indicate possible molecular and cellular mechanisms involved, although transcriptomic sex differences during human prenatal cortical development have been incompletely characterized, primarily due to small sample sizes.
UNASSIGNED: We performed a meta-analysis of sex-differential expression and co-expression network analysis in 2 independent bulk RNA sequencing datasets generated from cortex of 273 prenatal donors without known neuropsychiatric disorders. To assess the intersection between neurotypical sex differences and neuropsychiatric disorder biology, we tested for enrichment of ASD-associated risk genes and expression changes, neuropsychiatric disorder risk genes, and cell type markers within identified sex-differentially expressed genes (sex-DEGs) and sex-differential co-expression modules.
UNASSIGNED: We identified 101 significant sex-DEGs, including Y-chromosome genes, genes impacted by X-chromosome inactivation, and autosomal genes. Known ASD risk genes, implicated by either common or rare variants, did not preferentially overlap with sex-DEGs. We identified 1 male-specific co-expression module enriched for immune signaling that is unique to 1 input dataset.
UNASSIGNED: Sex-differential gene expression is limited in prenatal human cortex tissue, although meta-analysis of large datasets allows for the identification of sex-DEGs, including autosomal genes that encode proteins involved in neural development. Lack of sex-DEG overlap with ASD risk genes in the prenatal cortex suggests that sex-differential modulation of ASD symptoms may occur in other brain regions, at other developmental stages, or in specific cell types, or may involve mechanisms that act downstream from mutation-carrying genes.
Males are more commonly diagnosed with autism spectrum disorder than females, and sex differences in brain development may contribute to this difference. Here, we define differences in gene expression patterns between males and females in human prenatal brain tissue from 273 donors to identify 101 genes that are expressed at different levels in males and females and gene sets that show sex-specific expression correlations. Genes with autism-associated DNA variants and genes with altered expression in autism do not preferentially overlap with sex-differential genes, suggesting that sex-differential biology may influence autism risk mechanisms in other brain regions, at other developmental stages, or in specific cell types.

BACKGROUND: Viperin, also known as radical S-adenosyl-methionine domain containing protein 2 (RSAD2), is an interferon-inducible protein that is involved in the innate immune response against a wide array of viruses. In mammals, Viperin exerts its antiviral function through enzymatic conversion of cytidine triphosphate (CTP) into its antiviral analog ddhCTP as well as through interactions with host proteins involved in innate immune signaling and in metabolic pathways exploited by viruses during their life cycle. However, how Viperin modulates the antiviral response in fish remains largely unknown.
RESULTS: For this purpose, we developed a fathead minnow (Pimephales promelas) clonal cell line in which the unique viperin gene has been knocked out by CRISPR/Cas9 genome-editing. In order to decipher the contribution of fish Viperin to the antiviral response and its regulatory role beyond the scope of the innate immune response, we performed a comparative RNA-seq analysis of viperin-/- and wildtype cell lines upon stimulation with recombinant fathead minnow type I interferon.
CONCLUSIONS: Our results revealed that Viperin does not exert positive feedback on the canonical type I IFN but acts as a negative regulator of the inflammatory response by downregulating specific pro-inflammatory genes and upregulating repressors of the NF-κB pathway. It also appeared to play a role in regulating metabolic processes, including one carbon metabolism, bone formation, extracellular matrix organization and cell adhesion.

Introduction: The Euchromatic Histone Methyl Transferase Protein 2 (EHMT2), also known as G9a, deposits transcriptionally repressive chromatin marks that play pivotal roles in the maturation and homeostasis of multiple organs. Recently, we have shown that Ehmt2 inactivation in the mouse pancreas alters growth and immune gene expression networks, antagonizing Kras-mediated pancreatic cancer initiation and promotion. Here, we elucidate the essential role of Ehmt2 in maintaining a transcriptional landscape that protects organs from inflammation. Methods: Comparative RNA-seq studies between normal postnatal and young adult pancreatic tissue from Ehmt2 conditional knockout animals (Ehmt2 fl/fl ) targeted to the exocrine pancreatic epithelial cells (Pdx1-Cre and P48 Cre/+ ), reveal alterations in gene expression networks in the whole organ related to injury-inflammation-repair, suggesting an increased predisposition to damage. Thus, we induced an inflammation repair response in the Ehmt2 fl/fl pancreas and used a data science-based approach to integrate RNA-seq-derived pathways and networks, deconvolution digital cytology, and spatial transcriptomics. We also analyzed the tissue response to damage at the morphological, biochemical, and molecular pathology levels. Results and discussion: The Ehmt2 fl/fl pancreas displays an enhanced injury-inflammation-repair response, offering insights into fundamental molecular and cellular mechanisms involved in this process. More importantly, these data show that conditional Ehmt2 inactivation in exocrine cells reprograms the local environment to recruit mesenchymal and immunological cells needed to mount an increased inflammatory response. Mechanistically, this response is an enhanced injury-inflammation-repair reaction with a small contribution of specific Ehmt2-regulated transcripts. Thus, this new knowledge extends the mechanisms underlying the role of the Ehmt2-mediated pathway in suppressing pancreatic cancer initiation and modulating inflammatory pancreatic diseases.

Placental hypoxia is hazardous to maternal health as well as fetal growth and development. Preeclampsia and intrauterine growth restriction are common pregnancy problems, and one of the causes is placental hypoxia. Placental hypoxia is linked to a number of pregnancy illnessesv. To investigate their potential function in anoxic circumstances, we mimicked the anoxic environment of HTR-8/Svneo cells and performed lncRNA and circRNA studies on anoxic HTR-8/Svneo cells using high-throughput RNA sequencing. The miRNA target genes were predicted by integrating the aberrant expression of miRNAs in the placenta of preeclampsia and intrauterine growth restriction, and a ceRNA network map was developed to conduct a complete transcriptomic and bioinformatics investigation of circRNAs and lncRNAs. The signaling pathways in which the genes were primarily engaged were predicted using GO and KEGG analyses. To propose a novel explanation for trophoblastic organism failure caused by lncRNAs and circRNAs in an anoxic environment.

BACKGROUND: High-throughput RNA sequencing has become indispensable for decoding gene activities, yet the challenge of reconstructing full-length transcripts persists. Traditional single-sample assemblers frequently produce fragmented transcripts, especially in single-cell RNA-seq data. While algorithms designed for assembling multiple samples exist, they encounter various limitations.
RESULTS: We present Aletsch, a new assembler for multiple bulk or single-cell RNA-seq samples. Aletsch incorporates several algorithmic innovations, including a \"bridging\" system that can effectively integrate multiple samples to restore missed junctions in individual samples, and a new graph-decomposition algorithm that leverages \"supporting\" information across multiple samples to guide the decomposition of complex vertices. A standout feature of Aletsch is its application of a random forest model with 50 well-designed features for scoring transcripts. We demonstrate its robust adaptability across different chromosomes, datasets, and species. Our experiments, conducted on RNA-seq data from several protocols, firmly demonstrate Aletsch\'s significant outperformance over existing meta-assemblers. As an example, when measured with the partial area under the precision-recall curve (pAUC, constrained by precision), Aletsch surpasses the leading assemblers TransMeta by 22.9%-62.1% and PsiCLASS by 23.0%-175.5% on human datasets.
METHODS: Aletsch is freely available at https://github.com/Shao-Group/aletsch. Scripts that reproduce the experimental results of this manuscript is available at https://github.com/Shao-Group/aletsch-test.

UNASSIGNED: Sodium pheophorbide a (SPA) is a natural plant-derived photosensitizer, with high photoactivated antifungal activity against some phytopathogenic fungi. However, its fungicidal effect on Diaporthe mahothocarpus, a novel pathogen that causes Camellia oleifera leaf spot blight, is unclear.
UNASSIGNED: In the present study, we explored its inhibitory effects on spore germination and mycelial growth of D. mahothocarpus. Then we determined its effects on the cell membrane, mycelial morphology, redox homeostasis, and cell death through bioassay. Finally, RNA-seq was used further to elucidate its mode of action at the transcriptional level.
UNASSIGNED: We found that SPA effectively inhibited the growth of D. mahothocarpus, with half-maximal effective concentrations to inhibit mycelial growth and spore germination of 1.059 and 2.287 mg/mL, respectively. After 1.0 mg/mL SPA treatment, the conductivity and malondialdehyde content of D. mahothocarpus were significantly increased. Scanning electron microscopy and transmission electron microscopy indicated that SPA significantly affected the morphology and ultrastructure of D. mahothocarpus hyphae, revealing that SPA can destroy the mycelial morphology and cell structure, especially the cell membrane of D. mahothocarpus. Furthermore, transcriptome analysis revealed that SPA significantly suppressed the expression of genes involved in morphology, cell membrane permeability, and oxidative stress. Then, we also found that SPA significantly promoted the accumulation of reactive oxygen species (ROS) in of D. mahothocarpus, while it decreased the content of reduced glutathione, inhibited the enzyme activities of superoxide dismutase and catalase, and exacerbated DNA damage. Annexin V-FITC/PI staining also confirmed that 1.0 mg/mL SPA could significantly induce apoptosis and necrosis.
UNASSIGNED: Generally, SPA can induce ROS-mediated oxidative stress and cell death, thus destroying the cell membrane and hyphal morphology, and ultimately inhibiting mycelial growth, which indicates that SPA has multiple modes of action, providing a scientific basis for the use of SPA as an alternative plant-derived photoactivated fungicide against C. oleifera leaf spot blight.

BACKGROUND: Tuberculosis is a serious life-threatening disease among the top global health challenges and rapid and effective diagnostic biomarkers are vital for early diagnosis especially given the increasing prevalence of multidrug resistance.
METHODS: Two human whole blood microarray datasets, GSE42826 and GSE42830 were retrieved from publicly available gene expression omnibus (GEO) database. Deregulated genes (DEGs) were identified using GEO2R online tool and Gene Ontology (GO), protein-protein interaction (PPI) network analysis was performed using Metascape and STRING databases. Significant genes (n = 8) were identified using T-test/ANOVA and Molecular Complex Detection (MCODE) score ≥10, which was validated in GSE34608 dataset. The diagnostic potential of three biomarkers was assessed using Area Under Curve (AUC) of Receiver Operating Characteristic (ROC) plot. The transcriptional levels of these genes were also examined in a separate dataset GSE31348, to monitor the patterns of variation during tuberculosis treatment.
RESULTS: A total of 62 common DEGs (57 upregulated, 7 downregulated genes) were identified in two discovery datasets. GO functions and pathway enrichment analysis shed light on the functional roles of these DEGs in immune response and type-II interferon signaling. The genes in Module-1 (n = 18) were linked to innate immune response, interferon-gamma signaling. The common genes (n = 8) were validated in GSE34608 dataset, that corroborates the results obtained from discovery sets. The gene expression levels demonstrated responsiveness to Mtb infection during anti-TB therapy in GSE31348 dataset. In GSE34608 dataset, the expression levels of three specific genes, GBP5, IFITM3, and EPSTI1, emerged as potential diagnostic makers. In combination, these genes scored remarkable diagnostic performance with 100% sensitivity and 89% specificity, resulting in an impressive Area Under Curve (AUC) of 0.958. However, GBP5 alone showed the highest AUC of 0.986 with 100% sensitivity and 89% specificity.
CONCLUSIONS: The study presents valuable insights into the critical gene network perturbed during tuberculosis. These genes are determinants for assessing the effectiveness of an anti-TB response and distinguishing between active TB and healthy individuals. GBP5, IFITM3 and EPSTI1 emerged as candidate core genes in TB and holds potential as novel molecular targets for the development of interventions in the treatment of TB.