AITeQ: a machine learning framework for Alzheimer's prediction using a distinctive five-gene signature.

Neurodegenerative diseases, such as Alzheimer's disease, pose a significant global health challenge with their complex etiology and elusive biomarkers. In this study, we developed the Alzheimer's Identification Tool (AITeQ) using ribonucleic acid-sequencing (RNA-seq), a machine learning (ML) model based on an optimized ensemble algorithm for the identification of Alzheimer's from RNA-seq data. Analysis of RNA-seq data from several studies identified 87 differentially expressed genes. This was followed by a ML protocol involving feature selection, model training, performance evaluation, and hyperparameter tuning. The feature selection process undertaken in this study, employing a combination of four different methodologies, culminated in the identification of a compact yet impactful set of five genes. Twelve diverse ML models were trained and tested using these five genes (CNKSR1, EPHA2, CLSPN, OLFML3, and TARBP1). Performance metrics, including precision, recall, F1 score, accuracy, Matthew's correlation coefficient, and receiver operating characteristic area under the curve were assessed for the finally selected model. Overall, the ensemble model consisting of logistic regression, naive Bayes classifier, and support vector machine with optimized hyperparameters was identified as the best and was used to develop AITeQ. AITeQ is available at: https://github.com/ishtiaque-ahammad/AITeQ.

Single-cell RNA-seq data analysis reveals functionally relevant biomarkers of early brain development and their regulatory footprints in human embryonic stem cells (hESCs).

The complicated process of neuronal development is initiated early in life, with the genetic mechanisms governing this process yet to be fully elucidated. Single-cell RNA sequencing (scRNA-seq) is a potent instrument for pinpointing biomarkers that exhibit differential expression across various cell types and developmental stages. By employing scRNA-seq on human embryonic stem cells, we aim to identify differentially expressed genes (DEGs) crucial for early-stage neuronal development. Our focus extends beyond simply identifying DEGs. We strive to investigate the functional roles of these genes through enrichment analysis and construct gene regulatory networks to understand their interactions. Ultimately, this comprehensive approach aspires to illuminate the molecular mechanisms and transcriptional dynamics governing early human brain development. By uncovering potential links between these DEGs and intelligence, mental disorders, and neurodevelopmental disorders, we hope to shed light on human neurological health and disease. In this study, we have used scRNA-seq to identify DEGs involved in early-stage neuronal development in hESCs. The scRNA-seq data, collected on days 26 (D26) and 54 (D54), of the in vitro differentiation of hESCs to neurons were analyzed. Our analysis identified 539 DEGs between D26 and D54. Functional enrichment of those DEG biomarkers indicated that the up-regulated DEGs participated in neurogenesis, while the down-regulated DEGs were linked to synapse regulation. The Reactome pathway analysis revealed that down-regulated DEGs were involved in the interactions between proteins located in synapse pathways. We also discovered interactions between DEGs and miRNA, transcriptional factors (TFs) and DEGs, and between TF and miRNA. Our study identified 20 significant transcription factors, shedding light on early brain development genetics. The identified DEGs and gene regulatory networks are valuable resources for future research into human brain development and neurodevelopmental disorders.

A comprehensive assessment of cell type-specific differential expression methods in bulk data.

Accounting for cell type compositions has been very successful at analyzing high-throughput data from heterogeneous tissues. Differential gene expression analysis at cell type level is becoming increasingly popular, yielding biomarker discovery in a finer granularity within a particular cell type. Although several computational methods have been developed to identify cell type-specific differentially expressed genes (csDEG) from RNA-seq data, a systematic evaluation is yet to be performed. Here, we thoroughly benchmark six recently published methods: CellDMC, CARseq, TOAST, LRCDE, CeDAR and TCA, together with two classical methods, csSAM and DESeq2, for a comprehensive comparison. We aim to systematically evaluate the performance of popular csDEG detection methods and provide guidance to researchers. In simulation studies, we benchmark available methods under various scenarios of baseline expression levels, sample sizes, cell type compositions, expression level alterations, technical noises and biological dispersions. Real data analyses of three large datasets on inflammatory bowel disease, lung cancer and autism provide evaluation in both the gene level and the pathway level. We find that csDEG calling is strongly affected by effect size, baseline expression level and cell type compositions. Results imply that csDEG discovery is a challenging task itself, with room to improvements on handling low signal-to-noise ratio and low expression genes.

HBV-infected hepatocellular carcinoma can be robustly classified into three clinically relevant subgroups by a novel analytical protocol.

Liver cancer is the third leading cause of cancer-related death worldwide, and hepatocellular carcinoma (HCC) accounts for a relatively large proportion of all primary liver malignancies. Among the several known risk factors, hepatitis B virus (HBV) infection is one of the important causes of HCC. In this study, we demonstrated that the HBV-infected HCC patients could be robustly classified into three clinically relevant subgroups, i.e. Cluster1, Cluster2 and Cluster3, based on consistent differentially expressed mRNAs and proteins, which showed better generalization. The proposed three subgroups showed different molecular characteristics, immune microenvironment and prognostic survival characteristics. The Cluster1 subgroup had near-normal levels of metabolism-related proteins, low proliferation activity and good immune infiltration, which were associated with its good liver function, smaller tumor size, good prognosis, low alpha-fetoprotein (AFP) levels and lower clinical stage. In contrast, the Cluster3 subgroup had the lowest levels of metabolism-related proteins, which corresponded with its severe liver dysfunction. Also, high proliferation activity and poor immune microenvironment in Cluster3 subgroup were associated with its poor prognosis, larger tumor size, high AFP levels, high incidence of tumor thrombus and higher clinical stage. The characteristics of the Cluster2 subgroup were between the Cluster1 and Cluster3 groups. In addition, MCM2-7, RFC2-5, MSH2, MSH6, SMC2, SMC4, NCPAG and TOP2A proteins were significantly upregulated in the Cluster3 subgroup. Meanwhile, abnormally high phosphorylation levels of these proteins were associated with high levels of DNA repair, telomere maintenance and proliferative features. Therefore, these proteins could be identified as potential diagnostic and prognostic markers. In general, our research provided a novel analytical protocol and insights for the robust classification, treatment and prevention of HBV-infected HCC.

Boosting edgeR (Robust) by dealing with missing observations and gene-specific outliers in RNA-Seq profiles and its application to explore biomarker genes for diagnosis and therapies of ovarian cancer.

The edgeR (Robust) is a popular approach for identifying differentially expressed genes (DEGs) from RNA-Seq profiles. However, it shows weak performance against gene-specific outliers and is unable to handle missing observations. To address these issues, we proposed a pre-processing approach of RNA-Seq count data by combining the iLOO-based outlier detection and random forest-based missing imputation approach for boosting the performance of edgeR (Robust). Both simulation and real RNA-Seq count data analysis results showed that the proposed edgeR (Robust) outperformed than the conventional edgeR (Robust). To investigate the effectiveness of identified DEGs for diagnosis, and therapies of ovarian cancer (OC), we selected top-ranked 12 DEGs (IL6, XCL1, CXCL8, C1QC, C1QB, SNAI2, TYROBP, COL1A2, SNAP25, NTS, CXCL2, and AGT) and suggested hub-DEGs guided top-ranked 10 candidate drug-molecules for the treatment against OC. Hence, our proposed procedure might be an effective computational tool for exploring potential DEGs from RNA-Seq profiles for diagnosis and therapies of any disease.

Identification and validation of N7 -methylguanosine-associated gene NCBP1 as prognostic and immune-associated biomarkers in breast cancer patients.

We intend to evaluate the importance of N7 -methylguanosine (m7G) for the prognosis of breast cancer (BC). We gained 29 m7G-related genes from the published literature and among them, 16 m7G-related genes were found to have differential expression. Five differentially expressed genes (CYFIP1, EIF4E, EIF4E3, NCBP1 and WDR4) were linked to overall survival. This suggests that m7G-related genes might be prognostic or therapeutic targets for BC patients. We put the five genes to LASSO regression analysis to create a four-gene signature, including EIF4E, EIF4E3, WDR4 and NCBP1, that divides samples into two risky groups. Survival was drastically worsened in a high-risk group (p < 0.001). The signature's predictive capacity was demonstrated using ROC (10-year AUC 0.689; 10-year AUC 0.615; 3-year AUC 0.602). We found that immune status was significantly different between the two risk groups. In particular, NCBP1 also has a poor prognosis, with higher diagnostic value in ROC. NCBP1 also has different immune states according to its high or low expression. Meanwhile, knockdown of NCBP1 suppresses BC malignancy in vitro. Therefore, m7G RNA regulators are crucial participants in BC and four-gene mRNA levels are important predictors of prognosis. NCBP1 plays a critical target of m7G mechanism in BC.

Identification of hub genes and pathways associated with cellular senescence in diabetic foot ulcers via comprehensive transcriptome analysis.

This research aimed to find important genes and pathways related to cellular senescence (CS) in diabetic foot ulcers (DFU) and to estimate the possible pathways through which CS affects diabetic foot healing. The GSE80178 dataset was acquired from the Gene Expression Omnibus (GEO) database, containing six DFU and three diabetic foot skin (DFS) samples. The limma package was used to identify differentially expressed genes (DEGs). At the same time, DEGs associated with CS (CS-DEGs) were found using the CellAge database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted on the CS-DEGs. A protein-protein interaction (PPI) network was built using the String database, and the cytoHubba plug-in within Cytoscape helped identify hub genes. Lastly, the miRNA-TF-mRNA regulatory network for these hub genes was established. In total, 66 CS-DEGs were obtained. These genes mainly focus on CS, Kaposi sarcoma-associated herpesvirus infection and Toll-like receptor signalling pathway. Eight hub genes were identified to regulate cell senescence in DFU, including TP53, SRC, SIRT1, CCND1, EZH2, CXCL8, AR and CDK4. According to miRNA-TF-mRNA regulatory network, hsa-mir-132-3p/SIRT1/EZH2 axis is involved in senescence cell accumulation in DFU.

Contribution of FOS in neutrophils to venous thromboembolism via miR-144 based on bioinformatic prediction and validation.

The Finkel-Biskis-Jinkins Osteosarcoma (c-Fos; encoded by FOS) plays an important role in several cardiovascular diseases, including atherosclerosis and stroke. However, the relationship between FOS and venous thromboembolism (VTE) remains unknown. We identified differentially expressed genes in Gene Expression Omnibus dataset, GSE48000, comprising VTE patients and healthy individuals, and analysed them using CIBERSORT and weighted co-expression network analysis (WGCNA). FOS and CD46 expressions were significantly downregulated (FOS p = 2.26E-05, CD64 p = 8.83E-05) and strongly linked to neutrophil activity in VTE. We used GSE19151 and performed PCR to confirm that FOS and CD46 had diagnostic potential for VTE; however, only FOS showed differential expression by PCR and ELISA in whole blood samples. Moreover, we found that hsa-miR-144 which regulates FOS expression was significantly upregulated in VTE. Furthermore, FOS expression was significantly downregulated in neutrophils of VTE patients (p = 0.03). RNA sequencing performed on whole blood samples of VTE patients showed that FOS exerted its effects in VTE via the leptin-mediated adipokine signalling pathway. Our results suggest that FOS and related genes or proteins can outperform traditional clinical markers and may be used as diagnostic biomarkers for VTE.

Effect of supplementing lysins and methionine to low-protein diets on growth performance, hepatic antioxidant capacity, immune status, and glycolytic activity of tibetan sheep.

Reducing the levels of dietary protein is an effective nutritional approach in lowering feed cost and nitrogen emissions in ruminants. The purpose of this study was to evaluate the effects of dietary Lys/Met ratio in a low protein diet (10%, dry matter basis) on the growth performance and hepatic function (antioxidant capacity, immune status, and glycolytic activity) in Tibetan lambs. Ninety two-month-old rams with an average weight of 15.37 ± 0.92 kg were randomly assigned to LP-L (dietary Lys/Met = 1:1), LP-M (dietary Lys/Met = 2:1) and LP-H (dietary Lys/Met = 3:1) treatments. The trial was conducted over 100 d, including 10 d of adaption to the diets. Hepatic phenotypes, antioxidant capacity, immune status, glycolytic activity and gene expression profiling was detected after the conclusion of the feeding trials. The results showed that the body weight was higher in the LP-L group when compared to those on the LP-M group (P < 0.05). In addition, the activities of the catalase (CAT) and glutathione peroxidase (GSH-Px) in the LP-L group were significantly increased compared with the LP-M group (P < 0.05), while the malondialdehyde (MDA) levels in LP-H group were significantly decreased (P < 0.05). Compared with LP-H group, both hepatic glycogen (P < 0.01) and lactate dehydrogenase (LDH) (P < 0.05) were significantly elevated in LP-L group. For the LP-L group, the hepatocytes were arranged radially with the central vein in the center, and hepatic plates exhibited tight arrangement. Transcriptome analysis identified 29, 179, and 129 differentially expressed genes (DEGs) between the LP-M vs. LP-L, LP-H vs. LP-M, and LP-H vs. LP-L groups, respectively (Q-values < 0.05 and |log2Fold Change| > 1). Gene Ontology (GO) and correlation analyses showed that in the LP-L group, core genes (C1QA and JUNB) enriched in oxidoreductase activity were positively correlated with antioxidant indicators, while the MYO9A core gene enriched in the immune response was positively associated with immune indicators, and core genes enriched in molecular function (PDK3 and PDP2) were positively correlated with glycolysis indicators. In summary, low-protein diet with a low Lys/Met ratio (1:1) could reduce the hepatic oxidative stress and improve the glycolytic activity by regulating the expression of related genes of Tibetan sheep.

Comparative transcriptomic analysis primarily explores the molecular mechanism of compound eye formation in Neocaridina denticulata sinensis.

Compound eyes formation in decapod crustaceans occurs after the nauplius stage. However, the key genes and regulatory mechanisms of compound eye development during crustacean embryonic development have not yet been clarified. In this study, RNA-seq was used to investigate the gene expression profiles of Neocaridina denticulata sinensis from nauplius to zoea stage. Based on RNA-seq data analysis, the phototransduction and insect hormone biosynthesis pathways were enriched, and molting-related neuropeptides were highly expressed. There was strong cell proliferation in the embryo prior to compound eye development. The formation of the visual system and the hormonal regulation of hatching were the dominant biological events during compound eye development. The functional analysis of DEGs across all four developmental stages showed that cuticle formation, muscle growth and the establishment of immune system occurred from nauplius to zoea stage. Key genes related to eye development were discovered, including those involved in the determination and differentiation of the eye field, eye-color formation, and visual signal transduction. In conclusion, the results increase the understanding of the molecular mechanism of eye formation in crustacean embryonic stage.

Comparative transcriptomic profiles of Paulownia catalpifolia under different degrees of chilling stress during the seedling stage.

BACKGROUND: Paulownia, an ecologically and economically valuable plant species native to China, is notable for its excellent timber quality and strong adaptability. Among them, Paulownia catalpifolia displays the ability to survive in cold climate, a trait associated with northern China. Yet, the molecular information for its cold-tolerance has not been explored. This study was to investigate the changes in physiological indices and transcript levels of P. catalpifolia following cold exposure, which could provide evidence for revealing whether there were differences in the genetic basis of inducing physiological perturbations between moderate low temperature (MLT) and extreme low temperature (ELT). RESULTS: The detection of physiological indices under diverse degrees of chilling stress showed similar patterns of alteration. Enhanced accumulation of osmoregulatory substances, such as soluble sugar and soluble protein, were more conducive under ELT compared to MLT in P. catalpifolia. Moreover, we observed leaf wilting symptoms distinctly after exposure to ELT for 48 h, while this effect was not obvious after MLT exposure for 48 h. Comparative transcriptomic analysis between MLT and ELT demonstrated 13,688 differentially expressed genes (DEGs), most of them appeared after 12 h and 48 h of treatment. GO and KEGG analyses elucidated prominent enrichment in aromatic-L-amino-acid decarboxylase activity term and carbohydrate metabolism pathways. Therefore, it was speculated that the DEGs involved in the above processes might be related to the difference in the contents of soluble protein and soluble sugar between MLT and ELT. Time series clustering analyses further highlighted several key genes engaged in the 'Glycosyltransferases', 'Galactose metabolism' and 'Starch and sucrose metabolism' pathways as well as the 'tyrosine decarboxylase activity' term. For instance, cellulose synthase-like A (CLSA2/9), raffinose synthase (RafS2), ß-amylase (BAM1) and tyrosine/DOPA decarboxylase (TYDC1/2/5) genes, diverging in their expression trends between MLT and ELT, might significantly affect the soluble sugar and soluble protein abundance within P. catalpifolia. CONCLUSION: Between MLT and ELT treatments, partial overlaps in response pathways of P. catalpifolia were identified, while several genes regulating the accumulation of osmotic adjustment substances had disparate expression patterns. These findings could provide a novel physiological and molecular perspective for P. catalpifolia to adapt to complex low temperature habitats.

Functional annotation and meta-analysis of maize transcriptomes reveal genes involved in biotic and abiotic stress.

BACKGROUND: Environmental stress factors, such as biotic and abiotic stress, are becoming more common due to climate variability, significantly affecting global maize yield. Transcriptome profiling studies provide insights into the molecular mechanisms underlying stress response in maize, though the functions of many genes are still unknown. To enhance the functional annotation of maize-specific genes, MaizeGDB has outlined a data-driven approach with an emphasis on identifying genes and traits related to biotic and abiotic stress. RESULTS: We mapped high-quality RNA-Seq expression reads from 24 different publicly available datasets (17 abiotic and seven biotic studies) generated from the B73 cultivar to the recent version of the reference genome B73 (B73v5) and deduced stress-related functional annotation of maize gene models. We conducted a robust meta-analysis of the transcriptome profiles from the datasets to identify maize loci responsive to stress, identifying 3,230 differentially expressed genes (DEGs): 2,555 DEGs regulated in response to abiotic stress, 408 DEGs regulated during biotic stress, and 267 common DEGs (co-DEGs) that overlap between abiotic and biotic stress. We discovered hub genes from network analyses, and among the hub genes of the co-DEGs we identified a putative NAC domain transcription factor superfamily protein (Zm00001eb369060) IDP275, which previously responded to herbivory and drought stress. IDP275 was up-regulated in our analysis in response to eight different abiotic and four different biotic stresses. A gene set enrichment and pathway analysis of hub genes of the co-DEGs revealed hormone-mediated signaling processes and phenylpropanoid biosynthesis pathways, respectively. Using phylostratigraphic analysis, we also demonstrated how abiotic and biotic stress genes differentially evolve to adapt to changing environments. CONCLUSIONS: These results will help facilitate the functional annotation of multiple stress response gene models and annotation in maize. Data can be accessed and downloaded at the Maize Genetics and Genomics Database (MaizeGDB).

Apelin-13 modulates the endometrial transcriptome of the domestic pig during implantation.

BACKGROUND: The peri-implantation period is a critical time during pregnancy that mostly defines the overall litter size. Most authors agree that the highest percentage of embryo mortality occurs during this time. Despite the brevity of the peri-implantation period, it is the most dynamic part of pregnancy in which the sequential and uninterrupted course of several processes is essential to the animal's reproductive success. Also then, the maternal uterine tissues undergo an intensive remodelling process, and their energy demand dramatically increases. It is believed that apelin, a member of the adipokine family, is involved in the control of female reproductive functions in response to the current metabolic state. The verified herein hypothesis assumed the modulatory effect of apelin on the endometrial tissue transcriptome on days 15 to 16 of gestation (beginning of implantation). RESULTS: The analysis of data obtained during RNA-seq (Illumina HiSeq2500) of endometrial slices treated and untreated with apelin (n = 4 per group) revealed changes in the expression of 68 genes (39 up-regulated and 29 down-regulated in the presence of apelin), assigned to 240 gene ontology terms. We also revealed changes in the frequency of alternative splicing events (397 cases), as well as single nucleotide variants (1,818 cases) in the presence of the adipokine. The identified genes were associated, among others, with the composition of the extracellular matrix, apoptosis, and angiogenesis. CONCLUSIONS: The obtained results indicate a potential role of apelin in the regulation of uterine tissue remodelling during the peri-implantation period.

Comparative physiological and transcriptome analysis between potassium-deficiency tolerant and sensitive sweetpotato genotypes in response to potassium-deficiency stress.

BACKGROUND: Sweetpotato is a typical ''potassium (K+) favoring'' food crop, which root differentiation process needs a large supply of potassium fertilizer and determine the final root yield. To further understand the regulatory network of the response to low potassium stress, here we analyze physiological and biochemical characteristics, and investigated root transcriptional changes in two sweetpotato genotypes, namely, - K tolerant "Xu32" and - K susceptible"NZ1". RESULT: We found Xu32 had the higher capability of K+ absorption than NZ1 with better growth performance, higher net photosynthetic rate and higher chlorophyll contents under low potassium stress, and identified 889 differentially expressed genes (DEGs) in Xu32, 634 DEGs in NZ1, 256 common DEGs in both Xu32 and NZ1. The Gene Ontology (GO) term in molecular function enrichment analysis revealed that the DEGs under low K+ stress are predominately involved in catalytic activity, binding, transporter activity and antioxidant activity. Moreover, the more numbers of identified DEGs in Xu32 than that in NZ1 responded to K+-deficiency belong to the process of photosynthesis, carbohydrate metabolism, ion transport, hormone signaling, stress-related and antioxidant system may result in different ability to K+-deficiency tolerance. The unique genes in Xu32 may make a great contribution to enhance low K+ tolerance, and provide useful information for the molecular regulation mechanism of K+-deficiency tolerance in sweetpotato. CONCLUSIONS: The common and distinct expression pattern between the two sweetpotato genotypes illuminate a complex mechanism response to low potassium exist in sweetpotato. The study provides some candidate genes, which can be used in sweetpotato breeding program for improving low potassium stress tolerance.

Transcriptome analysis of long non-coding RNA and mRNA Profiles in VSV-infected BHK-21 Cells.

BACKGROUND: Vesicular stomatitis virus (VSV) is a typical non-segmented negative-sense RNA virus of the genus Vesiculovirus in the family Rhabdoviridae. VSV can infect a wide range of animals, including humans, with oral blister epithelial lesions. VSV is an excellent model virus with a wide range of applications as a molecular tool, a vaccine vector, and an oncolytic vector. To further understand the interaction between VSV and host cells and to provide a theoretical basis for the application prospects of VSV, we analyzed the expression of host differentially expressed genes (DEGs) during VSV infection using RNA-Seq. RESULTS: Our analyses found a total of 1015 differentially expressed mRNAs and 161 differentially expressed LncRNAs in BHK-21 cells infected with VSV for 24 h compared with controls. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment showed that the differentially expressed lncRNAs and their target genes were mainly concentrated in pathways related to apoptosis, cancer, disease, and immune system activation, including the TNF, P53, MAPK, and NF-kappaB signaling pathways. The differentially expressed lncRNA can modulate immune processes by regulating genes involved in these signaling transmissions. Ten randomly selected DEGs, namely, Il12rb2, F2, Masp2, Mcl1, FGF18, Ripk1, Fas, BMF, POLK, and JAG1, were validated using RT-qPCR. As predicted through RNA-Seq analysis, these DEGs underwent either up- or downregulation, suggesting that they may play key regulatory roles in the pathways mentioned previously. CONCLUSIONS: Our study showed that VSV infection alters the host metabolic network and activates immune-related pathways, such as MAPK and TNF. The above findings provide unique insights for further study of the mechanism of VSV-host interactions and, more importantly, provide a theoretical basis for VSV as an excellent vaccine carrier.

RNA-binding proteins potentially regulate the alternative splicing of apoptotic genes during knee osteoarthritis progression.

BACKGROUND: Alternative splicing (AS) is a principal mode of genetic regulation and one of the most widely used mechanisms to generate structurally and functionally distinct mRNA and protein variants. Dysregulation of AS may result in aberrant transcription and protein products, leading to the emergence of human diseases. Although considered important for regulating gene expression, genome-wide AS dysregulation, underlying mechanisms, and clinical relevance in knee osteoarthritis (OA) remain unelucidated. Therefore, in this study, we elucidated and validated AS events and their regulatory mechanisms during OA progression. RESULTS: In this study, we identified differentially expressed genes between human OA and healthy meniscus samples. Among them, the OA-associated genes were primarily enriched in biological pathways such as extracellular matrix organization and ossification. The predominant OA-associated regulated AS (RAS) events were found to be involved in apoptosis during OA development. The expression of the apoptosis-related gene BCL2L13, XAF1, and NF2 were significantly different between OA and healthy meniscus samples. The construction of a covariation network of RNA-binding proteins (RBPs) and RAS genes revealed that differentially expressed RBP genes LAMA2 and CUL4B may regulate the apoptotic genes XAF1 and BCL2L13 to undergo AS events during OA progression. Finally, RT-qPCR revealed that CUL4B expression was significantly higher in OA meniscus samples than in normal controls and that the AS ratio of XAF1 was significantly different between control and OA samples; these findings were consistent with their expected expression and regulatory relationships. CONCLUSIONS: Differentially expressed RBPs may regulate the AS of apoptotic genes during knee OA progression. XAF1 and its regulator, CUL4B, may serve as novel biomarkers and potential therapeutic targets for this disease.

Integrated analysis of transcriptomics and defense-related phytohormones to discover hub genes conferring maize Gibberella ear rot caused by Fusarium Graminearum.

BACKGROUND: Gibberella ear rot (GER) is one of the most devastating diseases in maize growing areas, which directly reduces grain yield and quality. However, the underlying defense response of maize to pathogens infection is largely unknown. RESULTS: To gain a comprehensive understanding of the defense response in GER resistance, two contrasting inbred lines 'Nov-82' and 'H10' were used to explore transcriptomic profiles and defense-related phytohormonal alterations during Fusarium graminearum infection. Transcriptomic analysis revealed 4,417 and 4,313 differentially expressed genes (DEGs) from the Nov-82 and H10, respectively, and 647 common DEGs between the two lines. More DEGs were obviously enriched in phenylpropanoid biosynthesis, secondary metabolites biosynthesis, metabolic process and defense-related pathways. In addition, the concentration of the defense-related phytohormones, jasmonates (JAs) and salicylates (SAs), was greatly induced after the pathogen infection. The level of JAs in H10 was more higher than in Nov-82, whereas an opposite pattern for the SA between the both lines. Integrated analysis of the DEGs and the phytohormones revealed five vital modules based on co-expression network analysis according to their correlation. A total of 12 hub genes encoding fatty acid desaturase, subtilisin-like protease, ethylene-responsive transcription factor, 1-aminocyclopropane-1-carboxylate oxidase, and sugar transport protein were captured from the key modules, indicating that these genes might play unique roles in response to pathogen infection, CONCLUSIONS: Overall, our results indicate that large number DEGs related to plant disease resistance and different alteration of defensive phytohormones were activated during F. graminearum infection, providing new insight into the defense response against pathogen invasion, in addition to the identified hub genes that can be further investigated for enhancing maize GER resistance.

Transcriptome analysis reveals the potential mechanism of the response to scale insects in Camellia sasanqua Thunb.

BACKGROUND: Camellia sasanqua Thunb. is an essential woody ornamental plant. Our continuous observation found that scale insects often infest C. sasanqua all year round in Kunming, China, resulting in poor growth. Scientifically preventing and controlling the infestation of scale insects should be paid attention to, and the mechanism of scale insects influencing C. sasanqua should be used as the research basis. RESULTS: The scale insect was identified as Pseudaulacaspis sasakawai Takagi. We analyzed transcriptome sequencing data from leaves of C. sasanqua infested with scale insects. A total of 1320 genes were either up-regulated or down-regulated and differed significantly in response to scale insects. GO (Gene Ontology) annotation analysis showed that the pathway of catalytic activity, binding, membrane part, cell part, and cellular process were affected. KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis showed that most DEGs (differentially expressed genes) involved in plant hormone signal transduction, MAPK signaling pathway, flavonoid biosynthesis, tropane, piperidine and pyridine alkaloid biosynthesis. We also observed that the expression of galactose metabolism and carotenoid biosynthesis were significantly influenced. In addition, qRT-PCR (quantitative real-time PCR) validated the expression patterns of DEGs, which showed an excellent agreement with the transcriptome sequencing. CONCLUSIONS: Our transcriptomic analysis revealed that the C. sasanqua had an intricate resistance strategy to cope with scale insect attacks. After sensing the attack signal of scale insects, C. sasanqua activated the early signal MAPK (mitogen-activated protein kinase) to activate further transcription factors and Auxin, ET, JA, ABA, and other plant hormone signaling pathways, ultimately leading to the accumulation of lignin, scopolin, flavonoids and other secondary metabolites, produces direct and indirect resistance to scale insects. Our results suggested that it provided some potential resources of defense genes that would benefit the following resistance breeding in C. sasanqua to scale insects.

Phenotypic divergence between broiler and layer chicken lines is regulated at the molecular level during development.

BACKGROUND: Understanding the molecular underpinnings of phenotypic variations is critical for enhancing poultry breeding programs. The Brazilian broiler (TT) and laying hen (CC) lines exhibit striking differences in body weight, growth potential, and muscle mass. Our work aimed to compare the global transcriptome of wing and pectoral tissues during the early development (days 2.5 to 3.5) of these chicken lines, unveiling disparities in gene expression and regulation. RESULTS: Different and bona-fide transcriptomic profiles were identified for the compared lines. A similar number of up- and downregulated differentially expressed genes (DEGs) were identified, considering the broiler line as a reference. Upregulated DEGs displayed an enrichment of protease-encoding genes, whereas downregulated DEGs exhibited a prevalence of receptors and ligands. Gene Ontology analysis revealed that upregulated DEGs were mainly associated with hormone response, mitotic cell cycle, and different metabolic and biosynthetic processes. In contrast, downregulated DEGs were primarily linked to communication, signal transduction, cell differentiation, and nervous system development. Regulatory networks were constructed for the mitotic cell cycle and cell differentiation biological processes, as their contrasting roles may impact the development of distinct postnatal traits. Within the mitotic cell cycle network, key upregulated DEGs included CCND1 and HSP90, with central regulators being NF-κB subunits (RELA and REL) and NFATC2. The cell differentiation network comprises numerous DEGs encoding transcription factors (e.g., HOX genes), receptors, ligands, and histones, while the main regulatory hubs are CREB, AR and epigenetic modifiers. Clustering analyses highlighted PIK3CD as a central player within the differentiation network. CONCLUSIONS: Our study revealed distinct developmental transcriptomes between Brazilian broiler and layer lines. The gene expression profile of broiler embryos seems to favour increased cell proliferation and delayed differentiation, which may contribute to the subsequent enlargement of pectoral tissues during foetal and postnatal development. Our findings pave the way for future functional studies and improvement of targeted traits of economic interest in poultry.

Identification and functionalization of thyrotropin receptor antibodies (TRAb) with different antigenic epitopes.

CONTEXT: One of the sensitive markers for autoimmune thyroid disease (AITD) clinical identification is TRAb. To quickly distinguish TRAb with distinct antigenic epitopes, a straightforward and uncomplicated technique has not yet been created. OBJECTIVE: To search for molecular diagnostic targets for different types of AITD (Graves' disease (GD), Graves' orbitopathy (GO), GD with III degree goiter (GD(3)), Hypothyroidism combined with positive TRAb (HT(TRAb+))) as molecular diagnostic targets. METHODS: Following action on thyroid cells, differential genes (DEGs) generated by TRAb with distinct antigenic epitopes were detected and identified by RNA-seq, bioinformatics analysis, and RT-qPCR in the serum of AITD patients. Using the EdU assay, the effect of co-culturing thyroid cells with different antigenic TRAb epitopes on the cells' capacity to proliferate was investigated. RESULTS: Bioinformatics analysis and RT-qPCR validation identified one GD key gene (AHSG), two GO key genes (ADRA1D and H2BC18), two GD(3) key genes (SOCS1 and CYBB), and one HT (TRAb+) key gene (MASP2). Correlation analysis and ROC curves showed that the above genes could be used as molecular diagnostic targets for different types of AITD. Finally, EdU results showed that TRAb inhibited thyroid cell proliferation in the HT (TRAb+) group compared with the normal control group, while the remaining three groups promoted thyroid cell proliferation, with a statistically significant difference (P < 0.05). CONCLUSION: We identified six key genes for different types of AITD, which have diagnostic value for different types of AITD. Meanwhile, we found that TRAb of different antigenic epitopes in AITD have different biological functions.