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The model moss species Physcomitrium patens has long been used for studying divergence of land plants spanning from bryophytes to angiosperms. In addition to its phylogenetic relationships, the limited number of differential tissues, and comparable morphology to the earliest embryophytes provide a system to represent basic plant architecture. Based on plant-fungal interactions today, it is hypothesized these kingdoms have a long-standing relationship, predating plant terrestrialization. Mortierellaceae have origins diverging from other land fungi paralleling bryophyte divergence, are related to arbuscular mycorrhizal fungi but are free-living, observed to interact with plants, and can be found in moss microbiomes globally. Due to their parallel origins, we assess here how two Mortierellaceae species, Linnemannia elongata and Benniella erionia, interact with P. patens in coculture. We also assess how Mollicute-related or Burkholderia-related endobacterial symbionts (MRE or BRE) of these fungi impact plant response. Coculture interactions are investigated through high-throughput phenomics, microscopy, RNA-sequencing, differential expression profiling, gene ontology enrichment, and comparisons among 99 other P. patens transcriptomic studies. Here we present new high-throughput approaches for measuring P. patens growth, identify novel expression of over 800 genes that are not expressed on traditional agar media, identify subtle interactions between P. patens and Mortierellaceae, and observe changes to plant-fungal interactions dependent on whether MRE or BRE are present. Our study provides insights into how plants and fungal partners may have interacted based on their communications observed today as well as identifying L. elongata and B. erionia as modern fungal endophytes with P. patens.

The sacred datura plant (Solanales: Solanaceae: Datura wrightii) has been used to study plant-herbivore interactions for decades. The wealth of information that has resulted leads it to have potential as a model system for studying the ecological and evolutionary genomics of these interactions. We present a de novo Datura wrightii genome assembled using PacBio HiFi long-reads. Our assembly is highly complete and contiguous (N50 = 179Mb, BUSCO Complete = 97.6%). We successfully detected a previously documented ancient whole genome duplication using our assembly and have classified the gene duplication history that generated its coding sequence content. We use it as the basis for a genome-guided differential expression analysis to identify the induced responses of this plant to one of its specialized herbivores (Coleoptera: Chrysomelidae: Lema daturaphila). We find over 3000 differentially expressed genes associated with herbivory and that elevated expression levels of over 200 genes last for several days. We also combined our analyses to determine the role that different gene duplication categories have played in the evolution of Datura-herbivore interactions. We find that tandem duplications have expanded multiple functional groups of herbivore responsive genes with defensive functions, including UGT-glycosyltranserases, oxidoreductase enzymes, and peptidase inhibitors. Overall, our results expand our knowledge of herbivore-induced plant transcriptional responses and the evolutionary history of the underlying herbivore-response genes.

Multiple Sclerosis (MS) is an autoimmune neurodegenerative disease affecting approximately 3 million people globally. Despite rigorous research on MS, aspects of its development and progression remain unclear. We utilized a publicly available RNA-seq dataset (GSE138614) consisting of the post-mortem white matter tissues of five donors without any neurological disorders and ten MS patient donors. We investigated gene expression levels correlated with tissue inflammation and alternative splicing to identify possible pathological isoforms in MS tissues. We identified RNA-binding motifs, differentially expressed RNA-binding proteins, and single-nucleotide polymorphisms (SNPs) to unravel possible mechanisms of alternative splicing. Genes with expression changes that were positively correlated with tissue inflammation were enriched in the immune system and receptor interaction pathways. Genes showing a negative correlation were enriched in nervous system development and in metabolic pathways. A comparison of normal-appearing white matter (NAWM) and active or chronic active lesions within the same donors identified genes playing roles in immunity, white matter injury repair, and remyelination. We identified exon skipping events and spontaneous SNPs in membrane-associated ring-CH-type finger-1 (MARCHF1), UDP glycosyltransferase-8 (UGT8), and other genes important in autoimmunity and neurodegeneration. Overall, we identified unique genes, pathways, and novel splicing events that can be further investigated as potential novel drug targets for MS treatment. [ABSTRACT FROM AUTHOR]

Introduction: The advent of RNA sequencing (RNA-Seq) has significantly advanced our understanding of the transcriptomic landscape, revealing intricate gene expression patterns across biological states and conditions. However, the complexity and volume of RNA-Seq data pose challenges in identifying differentially expressed genes (DEGs), critical for understanding the molecular basis of diseases like cancer. Methods: We introduce a novel Machine Learning-Enhanced Genomic Data Analysis Pipeline (ML-GAP) that incorporates autoencoders and innovative data augmentation strategies, notably the MixUp method, to overcome these challenges. By creating synthetic training examples through a linear combination of input pairs and their labels, MixUp significantly enhances the model's ability to generalize from the training data to unseen examples. Results: Our results demonstrate the ML-GAP's superiority in accuracy, efficiency, and insights, particularly crediting the MixUp method for its substantial contribution to the pipeline's effectiveness, advancing greatly genomic data analysis and setting a new standard in the field. Discussion: This, in turn, suggests that ML-GAP has the potential to perform more accurate detection of DEGs but also offers new avenues for therapeutic intervention and research. By integrating explainable artificial intelligence (XAI) techniques, ML-GAP ensures a transparent and interpretable analysis, highlighting the significance of identified genetic markers. [ABSTRACT FROM AUTHOR]

Vitamin C, also referred to as ascorbic acid (AsA), is recognized for its capacity to cure and avert scurvy, and it is crucial for regular human growth and development. In various crops, AsA participates in stress response mechanisms mediated by abscisic acid and has been discovered to have a crucial function in the morphogenesis, growth, development, and production of male gametes in plants. GDP-D-mannose 3′,5′-epimerase (GME) is essential in the synthesis of vitamin C. Our research identified 91, 83, 51, and 46 genes, respectively, found in G. barbadense (GbGMEs), G. hirsutum (GhGMEs), G. arboretum (GaGMEs), and G. raimondii (GrGMEs). Plants resulting from VIGS infection with GhGME31D clearly showed yellowing, water loss and wilting of leaves and black spots on stems. Measurement of MDA and AsA levels indicated that the plants were more damaged. This indicates that AsA has a substantial impact on plant growth and development. [ABSTRACT FROM AUTHOR]

Background/Objectives: We present hidecan, an R package for generating visualisations that summarise the results of one or more genome-wide association studies (GWAS) and differential expression analyses, as well as manually curated candidate genes, e.g., extracted from the literature. This tool is applicable to all ploidy levels; we notably provide functionalities to facilitate the visualisation of GWAS results obtained for autotetraploid organisms with the GWASpoly package. Results: We illustrate the capabilities of hidecan with examples from two autotetraploid potato datasets. Conclusions: The hidecan package is implemented in R and is publicly available on the CRAN repository and on GitHub. A description of the package, as well as a detailed tutorial, is made available alongside the package. It is also part of the VIEWpoly tool for the visualisation and exploration of results from polyploids computational tools. [ABSTRACT FROM AUTHOR]

Differences between orbital and subcutaneous abdominal fat in the same patient have been noted but not formally investigated, previously. The objective of this research was to compare the differential expression of protein profiles in subcutaneous abdominal and orbital adipose tissues. In this cross-sectional, observational study, orbital fat tissue was sampled from 10 patients who underwent blepharoplasty and agreed to provide a small sample of subcutaneous abdominal fat. Shotgun mass spectrometry was performed on the extracted proteome. Data were analyzed using protein appearance patterns, differential expression and statistical enrichment. Protein analysis revealed significant differences in proteomics and differential expression between the orbital and subcutaneous abdominal adipose tissues, which presented five proteins that were uniquely expressed in the orbital fat and 18 in the subcutaneous abdominal fat. Gene Ontology analysis identified significantly different cellular processes and components related to the extracellular matrix or basement membrane components. This analysis shows the differences between orbital and subcutaneous abdominal fat found in proteomics differential expression, uniquely expressed proteins, and cellular processes. Further research is needed to correlate specific proteins and cellular processes to the mechanism of fat accumulation and obesity. [ABSTRACT FROM AUTHOR]

Abstract Background Circular RNAs (circRNAs) function as essential regulatory elements with pivotal roles in various biological processes. However, their expression profiles and functional regulation during the differentiation of goat myoblasts have not been thoroughly explored. This study conducts an analysis of circRNA expression profiles during the proliferation phase (cultured in growth medium, GM) and differentiation phase (cultured in differentiation medium, DM1/DM5) of skeletal muscle satellite cells (MuSCs) in goats. Results A total of 2,094 circRNAs were identified, among which 84 were differentially expressed as determined by pairwise comparisons across three distinct groups. Validation of the expression levels of six randomly selected circRNAs was performed using reverse transcription PCR (RT-PCR) and quantitative RT-PCR (qRT-PCR), with confirmation of their back-splicing junction sites. Enrichment analysis of the host genes associated with differentially expressed circRNAs (DEcircRNAs) indicated significant involvement in biological processes such as muscle contraction, muscle hypertrophy, and muscle tissue development. Additionally, these host genes were implicated in key signaling pathways, including Hippo, TGF-beta, and MAPK pathways. Subsequently, employing Cytoscape, we developed a circRNA-miRNA interaction network to elucidate the complex regulatory mechanisms underlying goat muscle development, encompassing 21 circRNAs and 47 miRNAs. Functional assays demonstrated that circTGFβ2 enhances myogenic differentiation in goats, potentially through a miRNA sponge mechanism. Conclusion In conclusion, we identified the genome-wide expression profiles of circRNAs in goat MuSCs during both proliferation and differentiation phases, and established that circTGFβ2 plays a role in the regulation of myogenesis. This study offers a significant resource for the advanced exploration of the biological functions and mechanisms of circRNAs in the myogenesis of goats.

Abstract Vitamin C, also referred to as ascorbic acid (AsA), is recognized for its capacity to cure and avert scurvy, and it is crucial for regular human growth and development. In various crops, AsA participates in stress response mechanisms mediated by abscisic acid and has been discovered to have a crucial function in the morphogenesis, growth, development, and production of male gametes in plants. GDP-D-mannose 3′,5′-epimerase (GME) is essential in the synthesis of vitamin C. Our research identified 91, 83, 51, and 46 genes, respectively, found in G. barbadense (GbGMEs), G. hirsutum (GhGMEs), G. arboretum (GaGMEs), and G. raimondii (GrGMEs). Plants resulting from VIGS infection with GhGME31D clearly showed yellowing, water loss and wilting of leaves and black spots on stems. Measurement of MDA and AsA levels indicated that the plants were more damaged. This indicates that AsA has a substantial impact on plant growth and development.

Abstract Single-cell RNA-sequencing (scRNA-seq) provides gene expression profiles of individual cells from complex samples, facilitating the detection of cell type-specific marker genes. In scRNA-seq experiments with multiple donors, the population level variation brings an extra layer of complexity in cell type-specific gene detection, for example, they may not appear in all donors. Motivated by this observation, we develop a statistical model named scCTS to identify cell type-specific genes from population-level scRNA-seq data. Extensive data analyses demonstrate that the proposed method identifies more biologically meaningful cell type-specific genes compared to traditional methods.

Abstract Background The study aims to comprehensively combine colorectal cancer data cohorts in order to analyze the effects of various DNA methylation-coding genes on colorectal cancer patients. The annual incidence and mortality of colorectal cancer are very high, and there are no effective treatments for advanced colorectal cancer. DNA methylation is a method widely used to regulate epigenetics in the molecular mechanism study of tumors. Method Three single-cell cohorts GSE166555, GSE146771, and EMTAB8107, and five transcriptome cohorts GSE17536, GSE39582, GSE72970, and TCGA-CRC (TCGA-COAD and TCGA-READ) were applied in this study. 2 erasers (ALKBH5 and FTO), There are 7 writers (METTL3, METTL14, WTAP, VIRMA, RBM15, RBM15B, and ZC3H13) and 11 readers (YTHDC1, IGF2BP1, IGF2BP2, IGF2BP3, YTHDF1, YTHDF3, YTHDC2, and HNRNPA2B1, YTHDF2, HNRNPC and RBMX), a total of 20 M6A regulators, were used as the basis of the dataset in this study and were applied to the construction of molecular typing and prognostic models. Drugs that are differentially sensitive in methylation-regulated gene-related prognostic models were identified using the ConsensusClusterPlus package, which was also used to identify distinct methylation regulatory expression patterns in colorectal cancer and to model the relationship between tissue gene expression profiles and drug IC50 values. Finally, TISCH2 assessed which immune cells were significantly expressed with M6A scores. The immunosuppression of M6A methylation is spatially explained. Results This study used data from 583 CRC patients in the TCGA-CRC cohort. Firstly, the mutation frequency and CNV variation frequency of 20 m6A modification-related factors were analyzed, and the corresponding histogram and heat map were drawn. The study next analyzed the expression variations between mutant and wild forms of the VIRMA gene and explored differences in the expression of these variables in tumor and normal tissues. In addition, the samples were divided into different subgroups by molecular clustering method based on m6A modification, and each subgroup’s expression and clinicopathological characteristics were analyzed. Finally, we compared prognostic differences, tumor microenvironment (TME) characteristics, immune cell infiltration, and gene function enrichment among different subpopulations. We also developed a colorectal cancer m6A-associated gene signature and validated its prognostic effects across multiple cohorts. Finally, using single-cell RNA sequencing data, we confirmed that tumor cells show elevated expression of m6A-related gene signatures. Discussion This study explored the mutation frequency, expression differences, interactions, molecular clustering, prognostic effect, and association with tumor characteristics of m6A modification-related factors in CRC and validated them at the single-cell level. These results clarify the association between m6A alteration and colorectal cancer (CRC) and offer important insights into the molecular recognition and management of cancer.

Abstract [Objective] WRKY is one of the plant specific transcription factor families, involved in various plant life activities. However, currently there are few reports related to the WRKY70 gene in strawberry. Analyzing the role of WRKY70 homologous genes in strawberry in response to stress will help accelerate the application of molecular breeding technology and cultivate new strawberry germplasm resources. [Methods] The FaWRKY70 gene was cloned from ‘Benihoppe’ strawberry fruits using homologous cloning method. Its conserved domain, physicochemical properties, protein structure, and evolutionary relationship were analyzed using bioinformatics. Expression pattern analysis was performed using qRT-PCR. [Results] The FaWRKY70 gene had a length of 1 020 bp and encodes 339 amino acids. Homologous gene alignment revealed that FaWRKY70 had a high degree of amino acid sequence similarity with species in the same family such as apple and peony. The homologous genes were mostly related to plant responses to biotic and abiotic stress, suggesting that FaWRKY70 may be involved in resistance to stress. FaWRKY70 was expressed in different organs of strawberry, with significant differences. The expression level was highest in flowers and lowest in fruits. Under salicylic acid treatment, the FaWRKY70 gene was quickly responded, reaching its highest expression level after 3 hours, and gradually decreased thereafter. Under the treatment with methyl jasmonate, the FaWRKY70 gene showed a slight degree of induction and an overall downward trend. [Conclusion] FaWRKY70 is involved in growth and hormone signal transduction through different response modes in strawberry.

Background: The study aims to comprehensively combine colorectal cancer data cohorts in order to analyze the effects of various DNA methylation-coding genes on colorectal cancer patients. The annual incidence and mortality of colorectal cancer are very high, and there are no effective treatments for advanced colorectal cancer. DNA methylation is a method widely used to regulate epigenetics in the molecular mechanism study of tumors. Method: Three single-cell cohorts GSE166555, GSE146771, and EMTAB8107, and five transcriptome cohorts GSE17536, GSE39582, GSE72970, and TCGA-CRC (TCGA-COAD and TCGA-READ) were applied in this study. 2 erasers (ALKBH5 and FTO), There are 7 writers (METTL3, METTL14, WTAP, VIRMA, RBM15, RBM15B, and ZC3H13) and 11 readers (YTHDC1, IGF2BP1, IGF2BP2, IGF2BP3, YTHDF1, YTHDF3, YTHDC2, and HNRNPA2B1, YTHDF2, HNRNPC and RBMX), a total of 20 M6A regulators, were used as the basis of the dataset in this study and were applied to the construction of molecular typing and prognostic models. Drugs that are differentially sensitive in methylation-regulated gene-related prognostic models were identified using the ConsensusClusterPlus package, which was also used to identify distinct methylation regulatory expression patterns in colorectal cancer and to model the relationship between tissue gene expression profiles and drug IC50 values. Finally, TISCH2 assessed which immune cells were significantly expressed with M6A scores. The immunosuppression of M6A methylation is spatially explained. Results: This study used data from 583 CRC patients in the TCGA-CRC cohort. Firstly, the mutation frequency and CNV variation frequency of 20 m6A modification-related factors were analyzed, and the corresponding histogram and heat map were drawn. The study next analyzed the expression variations between mutant and wild forms of the VIRMA gene and explored differences in the expression of these variables in tumor and normal tissues. In addition, the samples were divided into different subgroups by molecular clustering method based on m6A modification, and each subgroup's expression and clinicopathological characteristics were analyzed. Finally, we compared prognostic differences, tumor microenvironment (TME) characteristics, immune cell infiltration, and gene function enrichment among different subpopulations. We also developed a colorectal cancer m6A-associated gene signature and validated its prognostic effects across multiple cohorts. Finally, using single-cell RNA sequencing data, we confirmed that tumor cells show elevated expression of m6A-related gene signatures. Discussion: This study explored the mutation frequency, expression differences, interactions, molecular clustering, prognostic effect, and association with tumor characteristics of m6A modification-related factors in CRC and validated them at the single-cell level. These results clarify the association between m6A alteration and colorectal cancer (CRC) and offer important insights into the molecular recognition and management of cancer. [ABSTRACT FROM AUTHOR]

Drought is a major abiotic stress factor that reduces agricultural productivity. Understanding the molecular regulatory network of drought response in winter rape is of great significance for molecular Brassica rapa. In order to comprehensively analyze the network expression of DEGs and DEMIs in winter rape under drought stress, in this study we used Longyou 7 as the experimental material to identify DEGs and DEMIs related to drought stress by transcriptome and miRNA sequencing. A total of 14–15 key differential mRNA genes related to drought stress and biological stress were screened out under different treatments in the three groups. and 32 differential miRNAs were identified through targeted regulatory relationships, and the mRNA expression of 20 target genes was negatively regulated by the targeting regulatory relationship. It is mainly enriched in starch and sucrose metabolism, carbon metabolism and other pathways. Among them, gra-MIR8731-p3_2ss13GA18GA regulated the expression of multiple mRNAs in the three treatments. miRNA is mainly involved in the drought resistance of Chinese cabbage winter rape by regulating the expression of target genes, such as starch and sucrose metabolism, amino acid biosynthesis, and carbon metabolism. These miRNAs and their target genes play an indispensable role in winter rapeseed drought stress tolerance regulation. [ABSTRACT FROM AUTHOR]

Long non-coding RNAs (lncRNAs) are involved in numerous biological processes and serve crucial regulatory functions in both animals and plants. Nevertheless, there is limited understanding of lncRNAs and their patterns of expression and roles in sharks. In the current study, we systematically identified and characterized lncRNAs in the blue shark (Prionace glauca) from four tissues (liver, spleen, muscle, and kidney) using high-throughput sequencing and bioinformatics tools. A total of 21,932 high-confidence lncRNAs were identified, with 8984 and 3067 stably and tissue-specific expressed lncRNAs, respectively. In addition, a total of 45,007 differentially expressed (DE) lncRNAs were obtained among tissues, with kidney versus muscle having the largest numbers across tissues. DE lncRNAs trans target protein-coding genes were predicted, and functional gene ontology enrichment of these genes showed GO terms such as muscle system processes, cellular/metabolic processes, and stress and immune responses, all of which correspond with the specific biological functions of each tissue analyzed. These results advance our knowledge of lncRNAs in sharks and present novel data on tissue-specific lncRNAs, providing key information to support future functional shark investigations. [ABSTRACT FROM AUTHOR]

Introduction: Chronic alcoholism is one of the most common neurological diseases in modern society. However, the key mechanisms underlying learning and memory impairments caused by chronic alcohol exposure remain unclear. In this study, a microRNA-messenger RNA (miRNA-mRNA) network was constructed to explore the potential function of key genes in chronic alcohol exposure, their effects on the hippocampus, and their mechanisms which facilitate brain injury in mice. Methods: The Morris water maze test was used to assess the learning ability of mice in each group. Mitochondrial ATPase activity and H2S levels in the hippocampi of mice were determined. Differentially expressed miRNAs and mRNAs in the mouse hippocampus were identified using second-generation sequencing. Using the TargetScan, miRTarBase, and miRDB databases, we predicted miRNA target genes and constructed a miRNA-mRNA regulatory network. Furthermore, using the Gene Ontology and KEGG databases we performed functional enrichment and protein-protein interaction analyses. Real-time quantitative polymerase chain reaction (qPCR) and other methods were employed to verify the mRNA expression of related genes. Results: The Morris water maze test revealed that mice exposed to chronic alcohol exhibited a significantly reduced learning ability compared to the control group (p < 0.05). Compared with the control group, the activity of mitochondrial ATPase in the hippocampal tissue of alcohol-treated mice was significantly decreased (p < 0.01), suggesting brain injury. In the model group, H2S significantly increased in the mice hippocampi (p < 0.01), indicating that chronic alcohol exposure could activate cystathionine β-synthase (CBS) and catalyze the mass formation of H2S, suggesting brain injury. A total of 208 differentially expressed miRNAs and 377 differentially expressed mRNAs were screened through bioinformatic analysis. Enrichment analysis indicated that the main pathways were involved in neurodegeneration and regulation of the Wnt signaling pathway. The PCR detected a significant down regulation in the expressions of FOS and EGR1 genes. Discussion: Consequently, chronic alcohol exposure may regulate the expression of FOS and EGR1 in the hippocampus through miR-222-3p, miR- 132-3p, miR-212-3p, and miR-191-5p, reduce the activity of hippocampal mitochondrial ATPase, activate CBS, catalyze the large amount of H2S formation, and destroy the mitochondrial structure, resulting in decreased learning ability. Our findings revealed valuable genes and miRNAs for the study of chronic alcohol exposure. [ABSTRACT FROM AUTHOR]

By analyzing two large atlases of almost 4 million cells, we show that immune‐senescence involves a gradual loss of cellular identity, reflecting increased cellular heterogeneity, for effector, and cytotoxic immune cells. The effects are largely similar in both males and females and were robustly reproduced in two atlases, one assembled from 35 diverse studies including 678 adults, the other the OneK1K study of 982 adults. Since the mean transcriptional differences among cell‐types remain constant across age deciles, there is little evidence for the alternative mechanism of convergence of cell‐type identity. Key pathways promoting activation and stemness are down‐regulated in aged T cells, while CD8 TEM and CD4 CTLs exhibited elevated inflammatory, and cytotoxicity in older individuals. Elevated inflammatory signaling pathways, such as MAPK and TNF‐alpha signaling via NF‐kB, also occur across all aged immune cells, particularly amongst effector immune cells. This finding of lost transcriptional identity with age carries several implications, spanning from a fundamental biological understanding of aging mechanisms to clinical perspectives on the efficacy of immunomodulation in elderly people. [ABSTRACT FROM AUTHOR]

Glycation is a non-enzymatic posttranslational modification coming from the reaction between reducing sugars and free amino groups in proteins, where early glycation products (fructosyl-lysine, FL) and advanced glycation end products (AGEs) are formed. The occurrence of glycation and accumulation of AGEs have been closely associated with hepatocellular carcinoma (HCC). Here, we reported the characterization of differential glycation in HCC using tissue proteomics with stable isotopic labeling; early glycation-modified peptides were enriched with boronate affinity chromatography (BAC), and AGEs-modified peptides were fractionated with basic reversed-phase separation. By this integrated approach, 3717 and 1137 early and advanced glycated peptides corresponding to 4007 sites on 1484 proteins were identified with a false discovery rate (FDR) of no more than 1%. One hundred fifty-five sites were modified with both early and advanced end glycation products. Five early and 7 advanced glycated peptides were quantified to be differentially expressed in HCC tissues relative to paired adjacent tissues. Most (8 out of 10) of the proteins corresponding to the differential glycated peptides have previously been reported with dysregulation in HCC. The results together may deepen our knowledge of glycation as well as provide insights for therapeutics. [ABSTRACT FROM AUTHOR]

Introduction: The purpose of this study was to explore the regulatory mechanisms of FGF2 in carotid atherosclerotic plaque development using bioinformatics analysis. Material and methods: Expression profiles of 32 atheroma plaque (AP) and 32 paired distant macroscopically intact (DMI) tissues samples in the GSE43292 dataset were downloaded from the Gene Expression Omnibus database. Following identification of differential expression genes (DEGs), correlation analysis of fibroblast growth factor 2 (FGF2) and DEGs was conducted. Subsequently, functional enrichment analysis and the proteinprotein interaction network for FGF2 significantly correlated DEGs were constructed. Then, microRNAs (miRNAs) that regulated FGF2 and regulatory pairs of long noncoding RNA (lncRNA)-miRNA were predicted to construct the lncRNA-miRNA-FGF2 network. Results: A total of 101 DEGs between AP and DMI samples were identified, and 31 DEGs were analyzed to have coexpression relationships with FGF2, including 23 positively correlated and 8 negatively correlated DEGs. VAV3 had the lowest r value among all FGF2 negatively correlated DEGs. FGF2 positively correlated DEGs were closely related to "regulation of smooth muscle contraction" (e.g., calponin 1 (CNN1)), while FGF2 negatively correlated DEGs were significantly associated with "platelet activation" (e.g., Vav guanine nucleotide exchange factor 3 (VAV3)). In addition, a total of 12 miRNAs that regulated FGF2 were predicted, and hsa-miR-15a-5p and hsamiR-16-5p were highlighted in the lncRNA-miRNA-FGF2 regulatory network. Conclusions: CNN1 might cooperate with FGF2 to regulate smooth muscle contractility during CAP formation. VAV3 might cooperate with FGF2 to be responsible for the development of CAP through participating in platelet activation. Hsa-miR-15a-5p and hsa-miR-16-5p might participate in the development of CAP via regulating FGF2. [ABSTRACT FROM AUTHOR]

Ras-related Rap1A GTPase is implicated in pancreas β-cell insulin secretion and is stimulated by the cAMP sensor Epac2, a guanine exchange factor and activator of Rap1 GTPase. In this study, we examined the differential proteomic profiles of pancreata from C57BL/6 Rap1A-deficient (Null) and control wild-type (WT) mice with nanoLC-ESI-MS/MS to assess targets of Rap1A potentially involved in insulin regulation. We identified 77 overlapping identifier proteins in both groups, with 8 distinct identifier proteins in Null versus 56 distinct identifier proteins in WT mice pancreata. Functional enrichment analysis showed four of the eight Null unique proteins, ERO1-like protein β (Ero1lβ), triosephosphate isomerase (TP1), 14-3-3 protein γ, and kallikrein-1, were exclusively involved in insulin biogenesis, with roles in insulin metabolism. Specifically, the mRNA expression of Ero1lβ and TP1 was significantly (p < 0.05) increased in Null versus WT pancreata. Rap1A deficiency significantly affected glucose tolerance during the first 15–30 min of glucose challenge but showed no impact on insulin sensitivity. Ex vivo glucose-stimulated insulin secretion (GSIS) studies on isolated Null islets showed significantly impaired GSIS. Furthermore, in GSIS-impaired islets, the cAMP-Epac2-Rap1A pathway was significantly compromised compared to the WT. Altogether, these studies underscore an essential role of Rap1A GTPase in pancreas physiological function. [ABSTRACT FROM AUTHOR]

Background: Fold change is a common metric in biomedical research for quantifying group differences in omics variables. However, inconsistent calculation methods and inadequate reporting lead to discrepancies in results. This study evaluated various fold-change calculation methods aiming at a recommendation of a preferred approach. Methods: The primary distinction in fold-change calculations lies in defining group expected values for log ratio computation. To challenge method interchangeability in a "stress test" scenario, we generated diverse artificial data sets with varying distributions (identity, uniform, normal, log-normal, and a mixture of these) and compared calculated fold-changes to known values. Additionally, we analyzed a multi-omics biomedical data set to estimate to what extent the findings apply to real-world data. Results: Using arithmetic means as expected values for treatment and reference groups yielded inaccurate fold-change values more frequently than other methods, particularly when subgroup distributions and/or standard deviations differed significantly. Conclusions: The arithmetic mean method, often perceived as standard or picked without considering alternatives, is inferior to other definitions of the group expected value. Methods using median, geometric mean, or paired fold-change combinations are more robust against violations of equal variances or dissimilar group distributions. Adhering to methods less sensitive to data distribution without trade-offs and accurately reporting calculation methods in scientific reports is a reasonable practice to ensure correct interpretation and reproducibility. [ABSTRACT FROM AUTHOR]

Ramie is one of the most important fiber crops in China, with fibers extracted from stem barks having been used as textile materials for thousands of years. DNA methylation is an important epigenetic modification involved in plant growth and development. However, the role of methylation in ramie fiber growth remains poorly understood. In the present study, we investigated the DNA methylation landscape of the nuclear genome in bark sections taken from the top (TPS) and the middle (MPS) of the stems of ramie plants, which represent different stages of fiber growth, using whole-genome bisulfite sequencing. We detected 7,709,555 and 8,508,326 5-methylcytosines in the TPS and MPS genomes, respectively. The distribution of methylation across three sequence contexts, CG, CHG, and CHH, varied greatly among gene elements, with methylation at CHH being the most prevalent. Comparison of methylation levels between the TPS and MPS genomes revealed 23.162 Mb of differentially methylated genomic regions, encompassing 9485 genes. Among these differentially methylated genes, 841 exhibited altered expression in the MPS genome. Notably, an SND2 ortholog Bni05G006779 showed a negative correlation between its expression and methylation levels. Overexpression of Bni05G006779 in Arabidopsis dramatically increased the number of xylem fibers and the secondary wall thickness of the fibers in the stems of transgenic plants. These findings provide important insights into the involvement of DNA methylation in regulating ramie fiber growth. [ABSTRACT FROM AUTHOR]

Extracellular vesicles (EVs) are of growing interest in the context of screening for highly informative cancer markers. We have previously shown that uterine aspirate EVs (UA EVs) are a promising source of ovarian cancer (OC) diagnostic markers. In this study, we first conducted an integrative analysis of EV-miRNA profiles from UA, malignant ascitic fluid (AF), and a conditioned medium of cultured ascites cells (ACs). Using three software packages, we identified 79 differentially expressed miRNAs (DE-miRNAs) in UA EVs from OC patients and healthy individuals. To narrow down this panel and select miRNAs most involved in OC pathogenesis, we aligned these molecules with the DE-miRNA sets obtained by comparing the EV-miRNA profiles from OC-related biofluids with the same control. We found that 76% of the DE-miRNAs from the identified panel are similarly altered (differentially co-expressed) in AF EVs, as are 58% in AC EVs. Interestingly, the set of miRNAs differentially co-expressed in AF and AC EVs strongly overlaps (40 out of 44 miRNAs). Finally, the application of more rigorous criteria for DE assessment, combined with the selection of miRNAs that are differentially co-expressed in all biofluids, resulted in the identification of a panel of 29 miRNAs for ovarian cancer screening. [ABSTRACT FROM AUTHOR]

Papaya ringspot virus (PRSV) is one of the most devastating viruses of papaya that has significantly hampered papaya production across the globe. Although PRSV resistance is known in some of its wild relatives, such as Vasconcellea cauliflora and in some of the improved papaya genotypes, the molecular basis of this resistance mechanism has not been studied and understood. Plant microRNAs are an important class of small RNAs that regulate the gene expression in several plant species against the invading plant pathogens. These miRNAs are known to manifest the expression of genes involved in resistance against plant pathogens, through modulation of the plant's biochemistry and physiology. In this study we made an attempt to study the overall expression pattern of small RNAs and more specifically the miRNAs in different papaya genotypes from India, that exhibit varying levels of tolerance or resistance to PRSV. Our study found that the expression of some of the miRNAs was differentially regulated in these papaya genotypes and they had entirely different miRNA expression profile in healthy and PRSV infected symptomatic plants. This data may help in improvement of papaya cultivars for resistance against PRSV through new breeding initiatives or biotechnological approaches such as genome editing. [ABSTRACT FROM AUTHOR]

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IntroductionAphids are phloem sap-sucking insects and are a serious destructive pest of several crop plants. Aphids are categorized as “generalists” or “specialists” depending on their host range. Myzus persicae (Sulz.) is a generalist aphid with a broad host range while Lipaphis erysimi (Kalt.), a specialist aphid, has a narrow host range. Aphid infestation involves several sequential stages including host recognition and selection, overcoming primary plant defence barriers, feeding on phloem sap and detoxification of host defence responses. Information on the molecular basis of variations between generalist and specialist aphids with reference to the above processes is limited.MethodsIn the current study, we generated transcriptome data of M. persicae and L. erysimi from adult and nymph stages and analysed the differential expression of genes between adults of the generalist and specialist aphid and similarly, between nymphs of the two aphid species. We categorized these differentially expressed genes into nine different categories namely, chemosensation-related, plant cell wall degrading enzymes, detoxification-related, digestive enzymes, peptidases, carbohydrate-, lipid-, amino acid-metabolism and reproduction. We also identified putative effector molecules in both M. persicae and L. erysimi from the transcriptome data,Results and discussionGene expression analysis identified 7688 and 8194 differentially expressed unigenes at adult and nymph stages, respectively of M. persicae and L. erysimi. M. persicae showed significantly higher levels of expression in a greater number of unigenes (5112 in adults and 5880 in nymphs) in contrast to the specialist, L. erysimi (2576 in adults and 2314 in nymphs) in both developmental stages. In addition, M. persicae displayed a greater number (350 in adults and 331 in nymphs) of upregulated unigenes involved in important processes such as host recognition, plant cell wall degradation, detoxification, digestion and metabolism, which correlate with its dynamic and polyphagous nature in contrast to the specialist (337 in adults and 251 in nymphs). We also observed a greater number of putative effectors in M. persicae (948 in adults and 283 in nymphs) than L. erysimi (797 in adults and 245 in nymphs). Based on our analysis, we conclude that the generalist aphid, M. persicae has a more diversified and stronger arsenal of genes that influence its polyphagous feeding behaviour and effective response to plant defence mechanisms against insect-herbivory. Our study provides a compendium of such candidate genes that would be most useful in studies on aphid biology, evolution and control.

The article "QUIC-seq: Quick ultra-affordable high-throughput convenient RNA sequencing" introduces a new method for gene expression analysis called QUIC-seq, which is quick, cost-effective, and suitable for high-throughput applications. The method involves extracting RNA, reverse transcription, Tn5 transposase fragmentation, and direct PCR amplification. QUIC-seq simplifies library construction, reduces costs, and offers high reproducibility. The method was used to identify differentially expressed genes in response to nitrogen and phosphorus stress, as well as in exploring gene regulatory networks. QUIC-seq is compared to other RNA-seq methods, showing advantages in cost, throughput, and efficiency. [Extracted from the article]

Abstract Background Recent advances in imaging-based spatially resolved transcriptomics (im-SRT) technologies now enable high-throughput profiling of targeted genes and their locations in fixed tissues. Normalization of gene expression data is often needed to account for technical factors that may confound underlying biological signals. Results Here, we investigate the potential impact of different gene count normalization methods with different targeted gene panels in the analysis and interpretation of im-SRT data. Using different simulated gene panels that overrepresent genes expressed in specific tissue regions or cell types, we demonstrate how normalization methods based on detected gene counts per cell differentially impact normalized gene expression magnitudes in a region- or cell type-specific manner. We show that these normalization-induced effects may reduce the reliability of downstream analyses including differential gene expression, gene fold change, and spatially variable gene analysis, introducing false positive and false negative results when compared to results obtained from gene panels that are more representative of the gene expression of the tissue’s component cell types. These effects are not observed with normalization approaches that do not use detected gene counts for gene expression magnitude adjustment, such as with cell volume or cell area normalization. Conclusions We recommend using non-gene count-based normalization approaches when feasible and evaluating gene panel representativeness before using gene count-based normalization methods if necessary. Overall, we caution that the choice of normalization method and gene panel may impact the biological interpretation of the im-SRT data.

Abstract Background Maedi-visna virus (MVV) is a lentivirus that infects monocyte/macrophage lineage cells in sheep, goats, and wild ruminants and causes pneumonia, mastitis, arthritis, and encephalitis. The immune response to MVV infection is complex, and a complete understanding of its infection and pathogenesis is lacking. This study investigated the in vivo transcriptomic patterns of lung tissues in sheep exposed to MVV using the RNA sequencing technology. Result The results indicated that 2,739 genes were significantly differentially expressed, with 1,643 downregulated genes and 1,096 upregulated genes. Many variables that could be unique to MVV infections were discovered. Gene Ontology analysis revealed that a significant proportion of genes was enriched in terms directly related to the immune system and biological responses to viral infections. Kyoto Encyclopedia of Genes and Genomes analysis revealed that the most enriched pathways were related to virus-host cell interactions and inflammatory responses. Numerous immune-related genes, including those encoding several cytokines and interferon regulatory factors, were identified in the protein-protein interaction network of differentially expressed genes (DEGs). The expression of DEGs was evaluated using real-time polymerase chain reaction and western blot analysis. CXCL13, CXCL6, CXCL11, CCR1, CXCL8, CXCL9, CXCL10, TNFSF8, TNFRSF8, IL7R, IFN-γ, CCL2, and MMP9 were upregulated. Immunohistochemical analysis was performed to identify the types of immune cells that infiltrated MVV-infected tissues. B cells, CD4+ and CD8+ T cells, and macrophages were the most prevalent immune cells correlated with MVV infection in the lungs. Conclusion Overall, the findings of this study provide a comprehensive understanding of the in vivo host response to MVV infection and offer new perspectives on the gene regulatory networks that underlie pathogenesis in natural hosts.

Abstract Background Extrachromosomal circular DNAs (eccDNAs) have been reported to play a key role in the occurrence and development of various diseases. However, the characterization and role of eccDNAs in pulmonary arterial hypertension (PAH) remain unclear. Methods In the discovery cohort, we first explored eccDNA expression profiles by Circle-sequencing analysis. The candidate eccDNAs were validated by routine polymerase chain reaction (PCR), TOPO-TA cloning and Sanger sequencing. In the validation cohort, 30 patients with PAH and 10 healthy controls were recruited for qPCR amplification to detect the candidate eccDNAs. Datas at the baseline were collected, including clinical background, biochemical variables, echocardiography and hemodynamic factors. Receiver operating characteristic curve was used to investigate the diagnostic effect of the eccDNA. Results We identified a total of 21,741 eccDNAs in plasma samples of 3 IPAH patients and 3 individuals in good health, and the expression frequency, GC content, length distribution, and genome distribution of the eccDNAs were thoroughly characterized and analyzed. In the validation cohort, 687 eccDNAs were differentially expressed in patients with IPAH compared with healthy controls (screening threshold: |FC|≥2 and P

Background Expression proteomics involves the global evaluation of protein abundances within a system. In turn, differential expression analysis can be used to investigate changes in protein abundance upon perturbation to such a system. Methods Here, we provide a workflow for the processing, analysis and interpretation of quantitative mass spectrometry-based expression proteomics data. This workflow utilises open-source R software packages from the Bioconductor project and guides users end-to-end and step-by-step through every stage of the analyses. As a use-case we generated expression proteomics data from HEK293 cells with and without a treatment. Of note, the experiment included cellular proteins labelled using tandem mass tag (TMT) technology and secreted proteins quantified using label-free quantitation (LFQ). Results The workflow explains the software infrastructure before focusing on data import, pre-processing and quality control. This is done individually for TMT and LFQ datasets. The application of statistical differential expression analysis is demonstrated, followed by interpretation via gene ontology enrichment analysis. Conclusions A comprehensive workflow for the processing, analysis and interpretation of expression proteomics is presented. The workflow is a valuable resource for the proteomics community and specifically beginners who are at least familiar with R who wish to understand and make data-driven decisions with regards to their analyses.

The widespread availability of high-dimensional biological data has made the simultaneous screening of many biological characteristics a central problem in computational and high-dimensional biology. As the dimensionality of datasets continues to grow, so too does the complexity of identifying biomarkers linked to exposure patterns. The statistical analysis of such data often relies upon parametric modeling assumptions motivated by convenience, inviting opportunities for model misspecification. While estimation frameworks incorporating flexible, data adaptive regression strategies can mitigate this, their standard variance estimators are often unstable in high-dimensional settings, resulting in inflated Type-I error even after standard multiple testing corrections. We adapt a shrinkage approach compatible with parametric modeling strategies to semiparametric variance estimators of a family of efficient, asymptotically linear estimators of causal effects, defined by counterfactual exposure contrasts. Augmenting the inferential stability of these estimators in high-dimensional settings yields a data adaptive approach for robustly uncovering stable causal associations, even when sample sizes are limited. Our generalized variance estimator is evaluated against appropriate alternatives in numerical experiments, and an open source R/Bioconductor package, biotmle, is introduced. The proposal is demonstrated in an analysis of high-dimensional DNA methylation data from an observational study on the epigenetic effects of tobacco smoking.

As ancient organisms, tree ferns play a crucial role as an evolutionary bridge between lower and higher plant species, providing various utilitarian benefits. However, they face challenges such as overexploitation, climate change, adverse environmental conditions, and insect pests, resulting in conservation concerns. In this study, we provide an overview of metabolic and transcriptomic resources of leaves in two typical tree ferns, A. spinulosa and A. metteniana, and explore the resistance genes for the first time. The landscape of metabolome showed that the compound skimmin may hold medicinal significance. A total of 111 differentially accumulated metabolites (DAMs) were detected, with pathway enrichment analysis highlighting 14 significantly enriched pathways, including 2-oxocarboxylic acid metabolism possibly associated with environmental adaptations. A total of 14,639 differentially expressed genes (DEGs) were found, among which 606 were resistance (R) genes. We identified BAM1 as a significantly differentially expressed R gene, which is one of the core genes within the R gene interaction network. Both the maximum-likelihood phylogenetic tree and the PPI network revealed a close relationship between BAM1, FLS2, and TMK. Moreover, BAM1 showed a significant positive correlation with neochlorogenic acid and kaempferol-7-O-glucoside. These metabolites, known for their antioxidant and anti-inflammatory properties, likely play a crucial role in the defense response of tree ferns. This research provides valuable insights into the metabolic and transcriptomic differences between A. spinulosa and A. metteniana, enhancing our understanding of resistance genes in tree ferns. [ABSTRACT FROM AUTHOR]

With the development of gene testing technology, we have found many different genes, and lncRNA is one of them. LncRNAs refer to a non-protein coding RNA molecule with a length of more than 200bp, which is one of the focuses of research on human malignant diseases such as LUAD. LncRNAs act as an oncogene or inhibitor to regulate the occurrence and progression of tumors. The differential expression of LncRNAs promotes or inhibits the progression of lung adenocarcinoma by affecting cell proliferation, metastasis, invasion, and apoptosis, thus affecting the prognosis and survival rate of patients. Therefore, LncRNAs can be used as a potential target for diagnosis and treatment of cancer. The early diagnosis of the disease was made through the detection of tumor markers. Because lung adenocarcinoma is not easy to diagnose in the early stage and tumor markers are easy to ignore, LncRNAs play an important role in the diagnosis and treatment of lung adenocarcinoma. The main purpose of this article is to summarize the known effects of LncRNAs on lung adenocarcinoma, the effect of differential expression of LncRNAs on the progression of lung adenocarcinoma, and related signal transduction pathways. And to provide a new idea for the future research of lung adenocarcinoma-related LncRNAs. [ABSTRACT FROM AUTHOR]

Simple Summary: The oriental fruit fly, Bactrocera dorsalis, has become a major threat to fruit and vegetable production due to the serious damage it causes, its worldwide distribution and invasive capacity, and resistance to commonly used insecticides. Moreover, the fly has a high reproductive capacity, and this prolific reproductive capacity can lead to extreme levels of destruction in affected fruits. Considering the fly's high fertility, targeting the gonads could theoretically be an effective method of pest control. However, the molecular mechanisms underlying gonadal development remain largely unrevealed. To identify gonad-specific expressed genes, an analysis of gonadal transcriptomic sequencing was conducted. A total of 1338, 336, 35, and 479 differentially expressed genes were found in the testis, ovary, female accessory gland, and male accessory gland, respectively. Surprisingly, approximately half of highly expressed gonad-specific genes were uncharacterized. Therefore, the functional motifs or domains of uncharacterized highly expressed gonad-specific genes were predicted, and 23% of novel highly expressed gonad-specific genes encoded proteins that contained signal peptides or transmembrane domains. Furthermore, the spatiotemporal expression and sequence characterization of six novel highly expressed gonad-specific genes were analyzed. Overall, genes associated with gonadal development may aid us in the search for pest control targets to improve pest management approaches. Bactrocera dorsalis (Hendel) (Diptera: Tephritidae) is one of the most devastating agricultural pests worldwide due to its high reproductive and invasive abilities. The elucidation of its gonadal developmental characteristics and the identification of sex-related genes will provide a useful genetic basis for reproductive-based pest control. Here, the gonadal transcriptome of B. dorsalis was sequenced, and novel gonad-specific expressed genes were analyzed. A total of 1338, 336, 35, and 479 differentially expressed genes (DEGs) were found in the testis (TE), ovary (OV), female accessory gland (FAG), and male accessory gland (MAG), respectively. Furthermore, 463 highly expressed gonad-specific genes were identified, with the TE having the highest number of specific highly expressed genes, at 402, followed by 51 in the OV, 9 in the MAG, and only 1 in the FAG. Strikingly, approximately half of highly expressed gonad-specific genes were uncharacterized. Then, it was found that 35, 17, 3, 2, and 1 of 202 uncharacterized highly expressed TE-specific genes encoded proteins that contained transmembrane domains, signal peptides, high-mobility group boxes, the zinc finger domain, and the BTB/POZ domain, respectively. Interestingly, approximately 40% of uncharacterized highly expressed gonad-specific genes encoding proteins were not predicted to possess functional motifs or domains. Finally, the spatiotemporal expression and sequence characterization of six novel highly expressed gonad-specific genes were analyzed. Altogether, our findings provide a valuable dataset for future functional analyses of sex-related genes and potential target sites for pest control. [ABSTRACT FROM AUTHOR]

Background: Maedi-visna virus (MVV) is a lentivirus that infects monocyte/macrophage lineage cells in sheep, goats, and wild ruminants and causes pneumonia, mastitis, arthritis, and encephalitis. The immune response to MVV infection is complex, and a complete understanding of its infection and pathogenesis is lacking. This study investigated the in vivo transcriptomic patterns of lung tissues in sheep exposed to MVV using the RNA sequencing technology. Result: The results indicated that 2,739 genes were significantly differentially expressed, with 1,643 downregulated genes and 1,096 upregulated genes. Many variables that could be unique to MVV infections were discovered. Gene Ontology analysis revealed that a significant proportion of genes was enriched in terms directly related to the immune system and biological responses to viral infections. Kyoto Encyclopedia of Genes and Genomes analysis revealed that the most enriched pathways were related to virus-host cell interactions and inflammatory responses. Numerous immune-related genes, including those encoding several cytokines and interferon regulatory factors, were identified in the protein-protein interaction network of differentially expressed genes (DEGs). The expression of DEGs was evaluated using real-time polymerase chain reaction and western blot analysis. CXCL13, CXCL6, CXCL11, CCR1, CXCL8, CXCL9, CXCL10, TNFSF8, TNFRSF8, IL7R, IFN-γ, CCL2, and MMP9 were upregulated. Immunohistochemical analysis was performed to identify the types of immune cells that infiltrated MVV-infected tissues. B cells, CD4+ and CD8+ T cells, and macrophages were the most prevalent immune cells correlated with MVV infection in the lungs. Conclusion: Overall, the findings of this study provide a comprehensive understanding of the in vivo host response to MVV infection and offer new perspectives on the gene regulatory networks that underlie pathogenesis in natural hosts. [ABSTRACT FROM AUTHOR]

The normalization of RNA sequencing data is a primary step for downstream analysis. The most popular method used for the normalization is the trimmed mean of M values (TMM) and DESeq. The TMM tries to trim away extreme log fold changes of the data to normalize the raw read counts based on the remaining non-deferentially expressed genes. However, the major problem with the TMM is that the values of trimming factor M are heuristic. This paper tries to estimate the adaptive value of M in TMM based on Jaeckel's Estimator, and each sample acts as a reference to find the scale factor of each sample. The presented approach is validated on SEQC, MAQC2, MAQC3, PICKRELL and two simulated datasets with two-group and three-group conditions by varying the percentage of differential expression and the number of replicates. The performance of the present approach is compared with various state-of-the-art methods, and it is better in terms of area under the receiver operating characteristic curve and differential expression. [ABSTRACT FROM AUTHOR]

Pathogen perception generates the activation of signal transduction cascades to host defense. White pine blister rust (WPBR) is caused by Cronartium ribicola J.C. Fisch and affects a number of species of Pinus. One of the most severely affected species is Pinus albicaulis Engelm (whitebark pine). WPBR resistance in the species is a polygenic and complex trait that requires an optimized immune response. We identified early responses in 2-year-old seedlings after four days of fungal inoculation and compared the underlying transcriptomic response with that of healthy non-inoculated individuals. A de novo transcriptome assembly was constructed with 56,796 high quality-annotations derived from the needles of susceptible and resistant individuals in a resistant half-sib family. Differential expression analysis identified 599 differentially expressed transcripts, from which 375 were upregulated and 224 were downregulated in the inoculated seedlings. These included components of the initial phase of active responses to abiotic factors and stress regulators, such as those involved in the first steps of flavonoid biosynthesis. Four days after the inoculation, infected individuals showed an overexpression of chitinases, reactive oxygen species (ROS) regulation signaling, and flavonoid intermediates. Our research sheds light on the first stage of infection and emergence of disease symptoms among whitebark pine seedlings. RNA sequencing (RNA-seq) data encoding hypersensitive response, cell wall modification, oxidative regulation signaling, programmed cell death, and plant innate immunity were differentially expressed during the defense response against C. ribicola. [ABSTRACT FROM AUTHOR]

Background: Multiple myeloma (MM), an incurable malignancy of plasma cells (PCs), is the second most common hematological cancer caused primarily by structural variations (chromosomal aberrations and somatic mutations). The majority of the patients acquired resistance against standard therapeutic approaches for MM and experienced relapse despite the continuous advances in MM therapies. Methods: We performed Differential Gene Expression (DGE), literature mining and SNV analysis of Next Generation Sequencing (NGS) data of Newly Diagnosed MM (NDMM) and Relapsed/Refractory MM (RRMM). The selected Differentially Expressed Genes (DEGs) were subjected to functional enrichment and pathway analysis. Immune cells infiltration analysis was also performed to estimate immune cells variations in the Tumor Microenvironment (TME) of RRMM. Result: CSF1R, VCAN, NRP1, COL22A1, BPI, BIRC5, MNX1, FAT1, ERG, TCL1A, AFF3 were selected after DGE, literature mining and SNV analysis. The functional enrichment of these DEGs showed significant enrichment for positive regulation of cell population proliferation, serene/threonine kinase activity, endothelial cell proliferation, cytokine binding, G protein activity and GDP binding, whereas KEGG pathway analysis revealed vital role of PI3K-Akt signaling pathway along with various cancer pathways. The immune cells infiltration analysis revealed the higher count of neutrophils and lesser level of T cells (CD8+) in TME of RRMM. Conclusion: Our study suggests that neutrophils play an important role in modulation of TME in RRMM. The selected DEGs have previously been identified in progression, drug resistance and relapse of various cancers. The role of these biomarkers in RRMM has not been explored yet. Therefore, neutrophils, selected DEGs and PI3K-Akt signaling pathway are potential targets to investigate in RRMM. [ABSTRACT FROM AUTHOR]

Background: Extrachromosomal circular DNAs (eccDNAs) have been reported to play a key role in the occurrence and development of various diseases. However, the characterization and role of eccDNAs in pulmonary arterial hypertension (PAH) remain unclear. Methods: In the discovery cohort, we first explored eccDNA expression profiles by Circle-sequencing analysis. The candidate eccDNAs were validated by routine polymerase chain reaction (PCR), TOPO-TA cloning and Sanger sequencing. In the validation cohort, 30 patients with PAH and 10 healthy controls were recruited for qPCR amplification to detect the candidate eccDNAs. Datas at the baseline were collected, including clinical background, biochemical variables, echocardiography and hemodynamic factors. Receiver operating characteristic curve was used to investigate the diagnostic effect of the eccDNA. Results: We identified a total of 21,741 eccDNAs in plasma samples of 3 IPAH patients and 3 individuals in good health, and the expression frequency, GC content, length distribution, and genome distribution of the eccDNAs were thoroughly characterized and analyzed. In the validation cohort, 687 eccDNAs were differentially expressed in patients with IPAH compared with healthy controls (screening threshold: |FC|≥2 and P < 0.05). Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that the specific eccDNAs in IPAH were significantly enriched in calcium channel activity, the mitogen-activated protein kinase pathway, and the wnt signaling pathway. Verification queue found that the expression of eccDNA-chr2:131208878–131,424,362 in PAH was considerably higher than that in healthy controls and exhibited a high level of accuracy in predicting PAH with a sensitivity of 86.67% and a specificity of 90%. Furthermore, correlation analysis disclosed a significant association between serum eccDNA-chr2:131208878–131,424,362 and mean pulmonary artery pressure (mPAP) (r = 0.396, P = 0.03), 6 min walking distance (6MWD) (r = -0.399, P = 0.029), N-terminal pro-B-type natriuretic peptide (NT-proBNP) (r = 0.685, P < 0.001) and cardiac index (CI) (r = − 0.419, P = 0.021). Conclusions: This is the first study to identify and characterize eccDNAs in patients with PAH. We revealed that serum eccDNA-chr2:131208878–131,424,362 is significantly overexpressed and can be used in the diagnosis of PAH, indicating its potential as a novel non-invasive biomarker. [ABSTRACT FROM AUTHOR]

Background: Adamantinomatous craniopharyngiomas (ACPs) are rare benign epithelial tumours with high recurrence and poor prognosis. Biological differences between recurrent and primary ACPs that may be associated with disease recurrence and treatment have yet to be evaluated at the proteomic level. In this study, we aimed to determine the proteomic profiles of paired recurrent and primary ACP, gain biological insight into ACP recurrence, and identify potential targets for ACP treatment. Method: Patients with ACP (n = 15) or Rathke's cleft cyst (RCC; n = 7) who underwent surgery at Sanbo Brain Hospital, Capital Medical University, Beijing, China and received pathological confirmation of ACP or RCC were enrolled in this study. We conducted a proteomic analysis to investigate the characteristics of primary ACP, paired recurrent ACP, and RCC. Western blotting was used to validate our proteomic results and assess the expression of key tumour-associated proteins in recurrent and primary ACPs. Flow cytometry was performed to evaluate the exhaustion of tumour-infiltrating lymphocytes (TILs) in primary and recurrent ACP tissue samples. Immunohistochemical staining for CD3 and PD-L1 was conducted to determine differences in T-cell infiltration and the expression of immunosuppressive molecules between paired primary and recurrent ACP samples. Results: The bioinformatics analysis showed that proteins differentially expressed between recurrent and primary ACPs were significantly associated with extracellular matrix organisation and interleukin signalling. Cathepsin K, which was upregulated in recurrent ACP compared with that in primary ACP, may play a role in ACP recurrence. High infiltration of T cells and exhaustion of TILs were revealed by the flow cytometry analysis of ACP. Conclusions: This study provides a preliminary description of the proteomic differences between primary ACP, recurrent ACP, and RCC. Our findings serve as a resource for craniopharyngioma researchers and may ultimately expand existing knowledge of recurrent ACP and benefit clinical practice. [ABSTRACT FROM AUTHOR]

Background Expression proteomics involves the global evaluation of protein abundances within a system. In turn, differential expression analysis can be used to investigate changes in protein abundance upon perturbation to such a system. Methods Here, we provide a workflow for the processing, analysis and interpretation of quantitative mass spectrometry-based expression proteomics data. This workflow utilises open-source R software packages from the Bioconductor project and guides users end-to-end and step-by-step through every stage of the analyses. As a use-case we generated expression proteomics data from HEK293 cells with and without a treatment. Of note, the experiment included cellular proteins labelled using tandem mass tag (TMT) technology and secreted proteins quantified using label-free quantitation (LFQ). Results The workflow explains the software infrastructure before focusing on data import, pre-processing and quality control. This is done individually for TMT and LFQ datasets. The application of statistical differential expression analysis is demonstrated, followed by interpretation via gene ontology enrichment analysis. Conclusions A comprehensive workflow for the processing, analysis and interpretation of expression proteomics is presented. The workflow is a valuable resource for the proteomics community and specifically beginners who are at least familiar with R who wish to understand and make data-driven decisions with regards to their analyses.

IntroductionThe advent of RNA sequencing (RNA-Seq) has significantly advanced our understanding of the transcriptomic landscape, revealing intricate gene expression patterns across biological states and conditions. However, the complexity and volume of RNA-Seq data pose challenges in identifying differentially expressed genes (DEGs), critical for understanding the molecular basis of diseases like cancer.MethodsWe introduce a novel Machine Learning-Enhanced Genomic Data Analysis Pipeline (ML-GAP) that incorporates autoencoders and innovative data augmentation strategies, notably the MixUp method, to overcome these challenges. By creating synthetic training examples through a linear combination of input pairs and their labels, MixUp significantly enhances the model’s ability to generalize from the training data to unseen examples.ResultsOur results demonstrate the ML-GAP’s superiority in accuracy, efficiency, and insights, particularly crediting the MixUp method for its substantial contribution to the pipeline’s effectiveness, advancing greatly genomic data analysis and setting a new standard in the field.DiscussionThis, in turn, suggests that ML-GAP has the potential to perform more accurate detection of DEGs but also offers new avenues for therapeutic intervention and research. By integrating explainable artificial intelligence (XAI) techniques, ML-GAP ensures a transparent and interpretable analysis, highlighting the significance of identified genetic markers.

Background & aimsLiver disease carries significant healthcare burden and frequently requires a combination of blood tests, imaging, and invasive liver biopsy to diagnose. Distinguishing between inflammatory liver diseases, which may have similar clinical presentations, is particularly challenging. In this study, we implemented a machine learning pipeline for the identification of diagnostic gene expression biomarkers across several alcohol-associated and non-alcohol-associated liver diseases, using either liver tissue or blood-based samples.MethodsWe collected peripheral blood mononuclear cells (PBMCs) and liver tissue samples from participants with alcohol-associated hepatitis (AH), alcohol-associated cirrhosis (AC), non-alcohol-associated fatty liver disease, chronic HCV infection, and healthy controls. We performed RNA sequencing (RNA-seq) on 137 PBMC samples and 67 liver tissue samples. Using gene expression data, we implemented a machine learning feature selection and classification pipeline to identify diagnostic biomarkers which distinguish between the liver disease groups. The liver tissue results were validated using a public independent RNA-seq dataset. The biomarkers were computationally validated for biological relevance using pathway analysis tools.ResultsUtilizing liver tissue RNA-seq data, we distinguished between AH, AC, and healthy conditions with overall accuracies of 90% in our dataset, and 82% in the independent dataset, with 33 genes. Distinguishing 4 liver conditions and healthy controls yielded 91% overall accuracy in our liver tissue dataset with 39 genes, and 75% overall accuracy in our PBMC dataset with 75 genes.ConclusionsOur machine learning pipeline was effective at identifying a small set of diagnostic gene biomarkers and classifying several liver diseases using RNA-seq data from liver tissue and PBMCs. The methodologies implemented and genes identified in this study may facilitate future efforts toward a liquid biopsy diagnostic for liver diseases.Lay summaryDistinguishing between inflammatory liver diseases without multiple tests can be challenging due to their clinically similar characteristics. To lay the groundwork for the development of a non-invasive blood-based diagnostic across a range of liver diseases, we compared samples from participants with alcohol-associated hepatitis, alcohol-associated cirrhosis, chronic hepatitis C infection, and non-alcohol-associated fatty liver disease. We used a machine learning computational approach to demonstrate that gene expression data generated from either liver tissue or blood samples can be used to discover a small set of gene biomarkers for effective diagnosis of these liver diseases.

Over the past decade, copper (Cu) has been recognized as a crucial metal in the differential expression of soluble (sMMO) and particulate (pMMO) forms of methane monooxygenase (MMO) through a mechanism referred to as the “Cu switch”. In this study, we used Methylosinus trichosporium OB3b as a model bacterium to investigate the range of Cu concentrations that trigger the expression of sMMO to pMMO and its effect on growth and methane oxidation. The Cu switch was found to be regulated within Cu concentrations from 3 to 5 µM, with a strict increase in the methane consumption rates from 3.09 to 3.85 µM occurring on the 6th day. Our findings indicate that there was a decrease in the fold changes in the expression of methanobactin (Mbn) synthesis gene (mbnA) with a higher Cu concentration, whereas the Ton-B siderophore receptor gene (mbnT) showed upregulation at all Cu concentrations. Furthermore, the upregulation of the di-heme enzyme at concentrations above 5 µM Cu may play a crucial role in the copper switch by increasing oxygen consumption; however, the role has yet not been elucidated. We developed a quantitative assay based on the naphthalene–Molisch principle to distinguish between the sMMO- and pMMO-expressing cells, which coincided with the regulation profile of the sMMO and pMMO genes. At 0 and 3 µM Cu, the naphthol concentration was higher (8.1 and 4.2 µM, respectively) and gradually decreased to 0 µM naphthol when pMMO was expressed and acted as the sole methane oxidizer at concentrations above 5 µM Cu. Using physical protein–protein interaction, we identified seven transporters, three cell wall biosynthesis or degradation proteins, Cu resistance operon proteins, and 18 hypothetical proteins that may be involved in Cu toxicity and homeostasis. These findings shed light on the key regulatory genes of the Cu switch that will have potential implications for bioremediation and biotechnology applications.

Abstract The sacred datura plant (Solanales: Solanaceae: Datura wrightii) has been used to study plant–herbivore interactions for decades. The wealth of information that has resulted leads it to have potential as a model system for studying the ecological and evolutionary genomics of these interactions. We present a de novo Datura wrightii genome assembled using PacBio HiFi long-reads. Our assembly is highly complete and contiguous (N50 = 179Mb, BUSCO Complete = 97.6%). We successfully detected a previously documented ancient whole genome duplication using our assembly and have classified the gene duplication history that generated its coding sequence content. We use it as the basis for a genome-guided differential expression analysis to identify the induced responses of this plant to one of its specialized herbivores (Coleoptera: Chrysomelidae: Lema daturaphila). We find over 3000 differentially expressed genes associated with herbivory and that elevated expression levels of over 200 genes last for several days. We also combined our analyses to determine the role that different gene duplication categories have played in the evolution of Datura-herbivore interactions. We find that tandem duplications have expanded multiple functional groups of herbivore responsive genes with defensive functions, including UGT-glycosyltranserases, oxidoreductase enzymes, and peptidase inhibitors. Overall, our results expand our knowledge of herbivore-induced plant transcriptional responses and the evolutionary history of the underlying herbivore-response genes.

Differences between orbital and subcutaneous abdominal fat in the same patient have been noted but not formally investigated, previously. The objective of this research was to compare the differential expression of protein profiles in subcutaneous abdominal and orbital adipose tissues. In this cross-sectional, observational study, orbital fat tissue was sampled from 10 patients who underwent blepharoplasty and agreed to provide a small sample of subcutaneous abdominal fat. Shotgun mass spectrometry was performed on the extracted proteome. Data were analyzed using protein appearance patterns, differential expression and statistical enrichment. Protein analysis revealed significant differences in proteomics and differential expression between the orbital and subcutaneous abdominal adipose tissues, which presented five proteins that were uniquely expressed in the orbital fat and 18 in the subcutaneous abdominal fat. Gene Ontology analysis identified significantly different cellular processes and components related to the extracellular matrix or basement membrane components. This analysis shows the differences between orbital and subcutaneous abdominal fat found in proteomics differential expression, uniquely expressed proteins, and cellular processes. Further research is needed to correlate specific proteins and cellular processes to the mechanism of fat accumulation and obesity.

Fruit development has been central in the evolution and domestication of flowering plants. In common bean (Phaseolus vulgaris), the principal global grain legume staple, two main production categories are distinguished by fibre deposition in pods: dry beans, with fibrous, stringy pods; and stringless snap/green beans, with reduced fibre deposition, which frequently revert to the ancestral stringy state. Here, we identify genetic and developmental patterns associated with pod fibre deposition. Transcriptional, anatomical, epigenetic and genetic regulation of pod strings were explored through RNA-seq, RT-qPCR, fluorescence microscopy, bisulfite sequencing and whole-genome sequencing. Overexpression of the INDEHISCENT ('PvIND') orthologue was observed in stringless types compared with isogenic stringy lines, associated with overspecification of weak dehiscence-zone cells throughout the pod vascular sheath. No differences in DNA methylation were correlated with this phenotype. Nonstringy varieties showed a tandemly direct duplicated PvIND and a Ty1-copia retrotransposon inserted between the two repeats. These sequence features are lost during pod reversion and are predictive of pod phenotype in diverse materials, supporting their role in PvIND overexpression and reversible string phenotype. Our results give insight into reversible gain-of-function mutations and possible genetic solutions to the reversion problem, of considerable economic value for green bean production.