The molecular mechanism responsible for HbSC retinopathy may depend on the action of the angiogenesis-related genes ROBO1 and SLC38A5.

HbSC disease, a less severe form of sickle cell disease, affects the retina more frequently and patients have higher rates of proliferative retinopathy that can progress to vision loss. This study aimed to identify differences in the expression of endothelial cell-derived molecules associated with the pathophysiology of proliferative sickle cell retinopathy (PSCR). RNAseq was used to compare the gene expression profile of circulating endothelial colony-forming cells from patients with SC hemoglobinopathy and proliferative retinopathy (n = 5), versus SC patients without retinopathy (n = 3). Real-time polymerase chain reaction (qRT-PCR) was used to validate the RNAseq results. A total of 134 differentially expressed genes (DEGs) were found. DEGs were mainly associated with vasodilatation, type I interferon signaling, innate immunity and angiogenesis. Among the DEGs identified, we highlight the most up-regulated genes ROBO1 (log2FoldChange = 4.32, FDR = 1.35E-11) and SLC38A5 (log2FoldChange = 3.36 FDR = 1.59E-07). ROBO1, an axon-guided receptor, promotes endothelial cell migration and contributes to the development of retinal angiogenesis and pathological ocular neovascularization. Endothelial SLC38A5, an amino acid (AA) transporter, regulates developmental and pathological retinal angiogenesis by controlling the uptake of AA nutrient, which may serve as metabolic fuel for the proliferation of endothelial cells (ECs) and consequent promotion of angiogenesis. Our data provide an important step towards elucidating the molecular pathophysiology of PSCR that may explain the differences in ocular manifestations between individuals with hemoglobinopathies and afford insights for new alternative strategies to inhibit pathological angiogenesis.

Identification of differentially expressed genes, pathways, and immune infiltration in diabetes.

This study aimed to perform exhaustive bioinformatic analysis by using GSE29221 micro-array maps obtained from healthy controls and Type 2 Diabetes (T2DM) patients. Raw data are downloaded from the Gene Expression Omnibus database and processed by the limma package in R software to identify Differentially Expressed Genes (DEGs). Gene ontology functional analysis and Kyoto Gene Encyclopedia and Genome Pathway analysis are performed to determine the biological functions and pathways of DEGs. A protein interaction network is constructed using the STRING database and Cytoscape software to identify key genes. Finally, immune infiltration analysis is performed using the Cibersort method. This study has implications for understanding the underlying molecular mechanism of T2DM and provides potential targets for further research.

Proteo-genomic characterization of cirrhosis-associated liver cancers reveals potential subtypes and therapeutic targets.

BACKGROUND: This study aimed to identify potential subtypes of hepatocellular carcinoma (HCC) associated with cirrhosis and to investigate key markers using bioinformatic analysis of gene expression datasets-0. METHODS: Three data sets (GSE17548, GSE56140, and GSE87630) were extracted from the Gene Expression Omnibus (GEO) database and normalized using the Limma package in R. Principal component analysis (PCA) and cluster analysis was performed to examine data distribution and identify subtypes. Differential gene expression analysis was performed using the Limma software package. Protein-protein interaction analysis and functional annotation were performed using the STRING database and Cytoscape software. Important signaling pathways and processes were identified using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Analysis. RESULTS: The analysis revealed different subtypes of HCC associated with cirrhosis and identified several key genes, including CCNB2, MCM4, and CDC20, with strong binding power and prognostic value. Functional annotation indicated involvement in cell cycle regulation and metabolic pathways. ROC analysis showed high sensitivity and specificity of these genes in predicting HCC prognosis. CONCLUSION: These results suggest that CCNB2, MCM4, and CDC20 may serve as potential biomarkers for predicting HCC prognosis in patients with cirrhosis and provide insights into the molecular mechanisms of HCC progression.

Dual RNA-seq of maize and H. seropedicae ZAE94 association, in different doses of nitrate, reveals novel insights into Plant-PGPB-environment relationship.

The interactions between plants, beneficial bacteria and their environment are profoundly shaped by various environmental factors, including light, temperature, water availability, and soil quality. Despite efforts to elucidate the molecular mechanisms involved in the association between plants and beneficial bacteria, like Plant Growth-Promoting Bacteria (PGPB), with many studies focusing on the transcriptional reprogramming in the plant, there is no report on the modulation of genetic controls from both plant and associated bacteria standpoints, in response to environment. The main goal of this study was to investigate the relationship between plant-bacteria-environment signaling, using as a model maize plants inoculated with H. seropedicae ZAE94 and cultivated with different doses of N (0.3 and 3 mM). For this purpose, we performed rRNA-depleted RNA-seq to determine the global gene expression of both maize roots and associated H. seropedicae ZAE94. Our results revealed a differential modulation of maize nitrogen metabolism, phytohormone and cell wall responses when associated with H. seropedicae ZAE94 at different N concentrations. In parallel, a modulation of the bacterial metabolism could be observed, by regulating genes involved in transport, secretion system, cell mobility, oxidoreductases, and chemotaxis, when bacteria were associated with maize roots and cultivated at different doses of N. The molecular and phenotypic data of maize plantlets suggested that different doses of N fertilization differentially regulated the beneficial effects of bacterial inoculation, as higher doses (3 mM) favored shoot elongation and lower doses (0.3 mM) favored increase in plant biomass. Our results provide a valuable integrated overview of differentially expressed genes in both maize and associated H. seropedicae ZAE94 in response to different N availability, revealing new insights into pathways involved in grass-PGPB associations.

Comparative Transcriptome Analysis of Babesia bigemina Attenuated Vaccine and Virulent Strains of Mexican Origin.

Bovine babesiosis, caused by the protozoan Babesia bigemina, is one of the most important hemoparasite diseases of cattle in Mexico and the world. An attenuated B. bigemina strain maintained under in vitro culture conditions has been used as a live attenuated vaccine; however, the biological mechanisms involved in attenuation are unknown. The objective of this study was to identify, through a comparative transcriptomics approach, the components of the B. bigemina virulent parasites that are differentially expressed in vivo, as opposed to those expressed by B. bigemina attenuated vaccine parasites when inoculated into naïve cattle. The biological material under study was obtained by inoculating spleen-intact cattle with infected erythrocytes containing either the attenuated strain or a virulent field strain. After RNA extraction, transcriptomic analysis (RNA-seq) was performed, followed by bioinformatic Differential Expression (DE) analysis and Gene Ontology (GO) term enrichment. The high-throughput sequencing results obtained by analyzing three biological replicates for each parasite strain ranged from 9,504,000 to 9,656,000, and 13,400,000 to 15,750,000 reads for the B. bigemina attenuated and virulent strains, respectively. At least 519 differentially expressed genes were identified in the analyzed strains. In addition, GO analysis revealed both similarities and differences across the three categories: cellular components, biological processes, and molecular functions. The attenuated strain of B. bigemina derived from in vitro culture presents global transcriptomic changes when compared to the virulent strain. Moreover, the obtained data provide insights into the potential molecular mechanisms associated with the attenuation or pathogenicity of each analyzed strain, offering molecular markers that might be associated with virulence or potential vaccine candidates.

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.

Genes and Pathways Involved in the Progression of Malignant Pleural Mesothelioma: A Meta-analysis of Genome-Wide Expression Studies.

Malignant pleural mesothelioma (MPM) is a rare and aggressive neoplasm of the pleural tissue that lines the lungs and is mainly associated with long latency from asbestos exposure. This tumor has no effective therapeutic opportunities nowadays and has a very low five-year survival rate. In this sense, identifying molecular events that trigger the development and progression of this tumor is highly important to establish new and potentially effective treatments. We conducted a meta-analysis of genome-wide expression studies publicly available at the Gene Expression Omnibus (GEO) and ArrayExpress databases. The differentially expressed genes (DEGs) were identified, and we performed functional enrichment analysis and protein-protein interaction networks (PPINs) to gain insight into the biological mechanisms underlying these genes. Additionally, we constructed survival prediction models for selected DEGs and predicted the minimum drug inhibition concentration of anticancer drugs for MPM. In total, 115 MPM tumor transcriptomes and 26 pleural tissue controls were analyzed. We identified 1046 upregulated DEGs in the MPM samples. Cellular signaling categories in tumor samples were associated with the TNF, PI3K-Akt, and AMPK pathways. The inflammatory response, regulation of cell migration, and regulation of angiogenesis were overrepresented biological processes. Expression of SOX17 and TACC1 were associated with reduced survival rates. This meta-analysis identified a list of DEGs in MPM tumors, cancer-related signaling pathways, and biological processes that were overrepresented in MPM samples. Some therapeutic targets to treat MPM are suggested, and the prognostic potential of key genes is shown.

Identification of differentially expressed genes, pathways, and immune infiltration in diabetes

ABSTRACT This study aimed to perform exhaustive bioinformatic analysis by using GSE29221 micro-array maps obtained from healthy controls and Type 2 Diabetes (T2DM) patients. Raw data are downloaded from the Gene Expression Omnibus database and processed by the limma package in R software to identify Differentially Expressed Genes (DEGs). Gene ontology functional analysis and Kyoto Gene Encyclopedia and Genome Pathway analysis are performed to determine the biological functions and pathways of DEGs. A protein interaction network is constructed using the STRING database and Cytoscape software to identify key genes. Finally, immune infiltration analysis is performed using the Cibersort method. This study has implications for understanding the underlying molecular mechanism of T2DM and provides potential targets for further research.

Transcriptome Analysis of Sweet Cherry (Prunus avium L.) Cultivar 'Lapins' upon Infection of Pseudomonas syringae pv. syringae.

Bacterial canker caused by Pseudomonas syringae pv. syringae (Pss) is responsible for substantial loss to the production of sweet cherry in Chile. To date, the molecular mechanisms of the Pss-sweet cherry interaction and the disease-related genes in the plant are poorly understood. In order to gain insight into these aspects, a transcriptomic analysis of the sweet cherry cultivar 'Lapins' for differentially expressed genes (DEGs) in response to Pss inoculation was conducted. Three Pss strains, A1M3, A1M197, and 11116_b1, were inoculated in young twigs, and RNA was extracted from tissue samples at the inoculation site and distal sections. RNA sequencing and transcriptomic expression analysis revealed that the three strains induced different patterns of responses in local and distal tissues. In the local tissues, A1M3 triggered a much more extensive response than the other two strains, enriching DEGs especially involved in photosynthesis. In the distal tissues, the three strains triggered a comparable extent of responses, among which 11116_b1 induced a group of DEGs involved in defense responses. Furthermore, tissues from various inoculations exhibited an enrichment of DEGs related to carbohydrate metabolism, terpene metabolism, and cell wall biogenesis. This study opened doors to future research on the Pss-sweet cherry interaction, immunity responses, and disease control.

Identification of Hub Genes in Idiopathic Pulmonary Fibrosis and Their Association with Lung Cancer by Bioinformatics Analysis.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, and irreversible disease with a high mortality rate worldwide. However, the etiology and pathogenesis of IPF have not yet been fully described. Moreover, lung cancer is a significant complication of IPF and is associated with increased mortality. Nevertheless, identifying common genes involved in developing IPF and its progression to lung cancer remains an unmet need. The present study aimed to identify hub genes related to the development of IPF by meta-analysis. In addition, we analyzed their expression and their relationship with patients' progression in lung cancer. METHOD: Microarray datasets GSE24206, GSE21369, GSE110147, GSE72073, and GSE32539 were downloaded from Gene Expression Omnibus (GEO). Next, we conducted a series of bioinformatics analysis to explore possible hub genes in IPF and evaluated the expression of hub genes in lung cancer and their relationship with the progression of different stages of cancer. RESULTS: A total of 1888 differentially expressed genes (DEGs) were identified, including 1105 upregulated and 783 downregulated genes. The 10 hub genes that exhibited a high degree of connectivity from the PPI network were identified. Analysis of the KEGG pathways showed that hub genes correlate with pathways such as the ECM-receptor interaction. Finally, we found that these hub genes are expressed in lung cancer and are associated with the progression of different stages of lung cancer. CONCLUSIONS: Based on the integration of GEO microarray datasets, the present study identified DEGs and hub genes that could play an essential role in the pathogenesis of IPF and its association with the development of lung cancer in these patients, which could be considered potential diagnostic biomarkers or therapeutic targets for the disease.

Transcriptomic Analysis Reveals the Response Mechanisms of Bell Pepper (Capsicum annuum) to Phosphorus Deficiency.

Phosphorus (P) is an important nutritional element needed by plants. Roots obtain P as inorganic phosphate (Pi), mostly in H2PO-4 form. It is vital for plants to have a sufficient supply of Pi since it participates in important processes like photosynthesis, energy transfer, and protein activation, among others. The physicochemical properties and the organic material usually make Pi bioavailability in soil low, causing crops and undomesticated plants to experience variations in accessibility or even a persistent phosphate limitation. In this study, transcriptome data from pepper roots under low-Pi stress was analyzed in order to identify Pi starvation-responsive genes and their relationship with metabolic pathways and functions. Transcriptome data were obtained from pepper roots with Pi deficiency by RNASeq and analyzed with bioinformatic tools. A total of 97 differentially expressed genes (DEGs) were identified; Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment revealed that metabolic pathways, such as porphyrin and chlorophyll metabolism, were down-regulated, and galactose and fatty acid metabolism were up-regulated. The results indicate that bell pepper follows diverse processes related to low Pi tolerance regulation, such as the remobilization of internal Pi, alternative metabolic pathways to generate energy, and regulators of root development.

Integrated bioinformatics approach reveals methylation-regulated differentially expressed genes in obesity.

Objective: To identify DNA methylation and gene expression profiles involved in obesity by implementing an integrated bioinformatics approach. Materials and methods: Gene expression (GSE94752, GSE55200, and GSE48964) and DNA methylation (GSE67024 and GSE111632) datasets were obtained from the GEO database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) in subcutaneous adipose tissue of patients with obesity were identified using GEO2R. Methylation-regulated DEGs (MeDEGs) were identified by overlapping DEGs and DMGs. The protein-protein interaction (PPI) network was constructed with the STRING database and analyzed using Cytoscape. Functional modules and hub-bottleneck genes were identified by using MCODE and CytoHubba plugins. Functional enrichment analyses were performed based on Gene Ontology terms and KEGG pathways. To prioritize and identify candidate genes for obesity, MeDEGs were compared with obesity-related genes available at the DisGeNET database. Results: A total of 54 MeDEGs were identified after overlapping the lists of significant 274 DEGs and 11,556 DMGs. Of these, 25 were hypermethylated-low expression genes and 29 were hypomethylated-high expression genes. The PPI network showed three hub-bottleneck genes (PTGS2, TNFAIP3, and FBXL20) and one functional module. The 54 MeDEGs were mainly involved in the regulation of fibroblast growth factor production, the molecular function of arachidonic acid, and ubiquitin-protein transferase activity. Data collected from DisGeNET showed that 11 of the 54 MeDEGs were involved in obesity. Conclusion: This study identifies new MeDEGs involved in obesity and assessed their related pathways and functions. These results data may provide a deeper understanding of methylation-mediated regulatory mechanisms of obesity.

Inference of differentially expressed genes using generalized linear mixed models in a pairwise fashion.

Background: Technological advances involving RNA-Seq and Bioinformatics allow quantifying the transcriptional levels of genes in cells, tissues, and cell lines, permitting the identification of Differentially Expressed Genes (DEGs). DESeq2 and edgeR are well-established computational tools used for this purpose and they are based upon generalized linear models (GLMs) that consider only fixed effects in modeling. However, the inclusion of random effects reduces the risk of missing potential DEGs that may be essential in the context of the biological phenomenon under investigation. The generalized linear mixed models (GLMM) can be used to include both effects. Methods: We present DEGRE (Differentially Expressed Genes with Random Effects), a user-friendly tool capable of inferring DEGs where fixed and random effects on individuals are considered in the experimental design of RNA-Seq research. DEGRE preprocesses the raw matrices before fitting GLMMs on the genes and the derived regression coefficients are analyzed using the Wald statistical test. DEGRE offers the Benjamini-Hochberg or Bonferroni techniques for P-value adjustment. Results: The datasets used for DEGRE assessment were simulated with known identification of DEGs. These have fixed effects, and the random effects were estimated and inserted to measure the impact of experimental designs with high biological variability. For DEGs' inference, preprocessing effectively prepares the data and retains overdispersed genes. The biological coefficient of variation is inferred from the counting matrices to assess variability before and after the preprocessing. The DEGRE is computationally validated through its performance by the simulation of counting matrices, which have biological variability related to fixed and random effects. DEGRE also provides improved assessment measures for detecting DEGs in cases with higher biological variability. We show that the preprocessing established here effectively removes technical variation from those matrices. This tool also detects new potential candidate DEGs in the transcriptome data of patients with bipolar disorder, presenting a promising tool to detect more relevant genes. Conclusions: DEGRE provides data preprocessing and applies GLMMs for DEGs' inference. The preprocessing allows efficient remotion of genes that could impact the inference. Also, the computational and biological validation of DEGRE has shown to be promising in identifying possible DEGs in experiments derived from complex experimental designs. This tool may help handle random effects on individuals in the inference of DEGs and presents a potential for discovering new interesting DEGs for further biological investigation.

The development of radioresistant oral squamous carcinoma cell lines and identification of radiotherapy-related biomarkers.

BACKGROUND: In the treatment of oral squamous cell carcinoma (OSCC), radiation resistance remains an important obstacle to patient outcomes. Progress in understanding the molecular mechanisms of radioresistance has been limited by research models that do not fully recapitulate the biological features of solid tumors. In this study, we aimed to develop novel in vitro models to investigate the underlying basis of radioresistance in OSCC and to identify novel biomarkers. METHODS: Parental OSCC cells (SCC9 and CAL27) were repeatedly exposed to ionizing radiation to develop isogenic radioresistant cell lines. We characterized the phenotypic differences between the parental and radioresistant cell lines. RNA sequencing was used to identify differentially expressed genes (DEGs), and bioinformatics analysis identified candidate molecules that may be related to OSCC radiotherapy. RESULTS: Two isogenic radioresistant cell lines for OSCC were successfully established. The radioresistant cells displayed a radioresistant phenotype when compared to the parental cells. Two hundred and sixty DEGs were co-expressed in SCC9-RR and CAL27-RR, and thirty-eight DEGs were upregulated or downregulated in both cell lines. The associations between the overall survival (OS) of OSCC patients and the identified genes were analyzed using data from the Cancer Genome Atlas (TCGA) database. A total of six candidate genes (KCNJ2, CLEC18C, P3H3, PIK3R3, SERPINE1, and TMC8) were closely associated with prognosis. CONCLUSION: This study demonstrated the utility of constructing isogenic cell models to investigate the molecular changes associated with radioresistance. Six genes were identified based on the data from the radioresistant cells that may be potential targets in the treatment of OSCC.

Comparative transcriptome analysis of endothelial progenitor cells of HbSS patients with and without proliferative retinopathy.

Among sickle cell anemia (SCA) complications, proliferative sickle cell retinopathy (PSCR) is one of the most important, being responsible for visual impairment in 10-20% of affected eyes. The aim of this study was to identify differentially expressed genes (DEGs) present in pathways that may be implicated in the pathophysiology of PSCR from the transcriptome profile analysis of endothelial progenitor cells. RNA-Seq was used to compare gene expression profile of circulating endothelial colony-forming cells (ECFCs) from HbSS patients with and without PSCR. Furthermore, functional enrichment analysis and protein-protein interaction (PPI) networks were performed to gain further insights into biological functions. The differential expression analysis identified 501 DEGs, when comparing the groups with and without PSCR. Furthermore, functional enrichment analysis showed associations of the DEGs in 200 biological processes. Among these, regulation of mitogen-activated protein (MAP) kinase activity, positive regulation of phosphatidylinositol 3-kinase (PI3K), and positive regulation of Signal Transducer and Activator of Transcription (STAT) receptor signaling pathway were observed. These pathways are associated with angiogenesis, cell migration, adhesion, differentiation, and proliferation, important processes involved in PSCR pathophysiology. Moreover, our results showed an over-expression of VEGFC (vascular endothelial growth factor-C) and FLT1 (Fms-Related Receptor Tyrosine Kinase 1) genes, when comparing HbSS patients with and without PSCR. These results may indicate a possible association between VEGFC and FLT1 receptor, which may activate signaling pathways such as PI3K/AKT and MAPK/ERK and contribute to the mechanisms implicated in neovascularization. Thus, our findings contain preliminary results that may guide future studies in the field, since the molecular mechanisms of PSCR are still poorly understood.

Transcriptome profile of skeletal muscle using different sources of dietary fatty acids in male pigs.

Pork is of great importance in world trade and represents the largest source of fatty acids in the human diet. Lipid sources such as soybean oil (SOY), canola (CO), and fish oil (FO) are used in pig diets and influence blood parameters and the ratio of deposited fatty acids. In this study, the main objective was to evaluate changes in gene expression in porcine skeletal muscle tissue resulting from the dietary oil sources and to identify metabolic pathways and biological process networks through RNA-Seq. The addition of FO in the diet of pigs led to intramuscular lipid with a higher FA profile composition of C20:5 n-3, C22:6 n-3, and SFA (C16:0 and C18:0). Blood parameters for the FO group showed lower cholesterol and HDL content compared with CO and SOY groups. Skeletal muscle transcriptome analyses revealed 65 differentially expressed genes (DEG, FDR 10%) between CO vs SOY, and 32 DEG for CO vs FO, and 531 DEG for SOY vs FO comparison. Several genes, including AZGP1, PDE3B, APOE, PLIN1, and LIPS, were found to be down-regulated in the diet of the SOY group compared to the FO group. The enrichment analysis revealed DEG involved in lipid metabolism, metabolic diseases, and inflammation between the oil groups, with specific gene functions in each group and altered blood parameters. The results provide mechanisms to help us understand the behavior of genes according to fatty acids.

Exploration and analysis of differentially expressed genes in Epstein-Barr virus negative and positive plasmablastic lymphoma.

OBJECTIVES: Plasmablastic lymphoma (PBL) is a subtype of diffuse large B-cell lymphoma (DLBCL) often associated with Epstein-Barr virus (EBV) infection. Despite recent advances in treatment, PBL still has a poor prognosis. EBV is listed as one of the human tumor viruses that may cause cancer, and is closely related to the occurrence of some nasopharyngeal carcinoma (NPC), lymphoma and 10% of gastric cancer (GC). It is very important to explore the differentially expressed genes (DEGs) between EBV-positive and EBV-negative PBL. Through bioinformatics analysis of DEGs between EBV-positive PBL and EBV-negative PBL, we gain a deeper understanding of the pathogenesis of EBV-positive PBL. METHODS: We selected the GSE102203 data set, and screened the DEGs between EBV-positive PBL and EBV-negative PBL. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were applied. The protein-protein interaction (PPI) network was constructed, and screened for the hub genes. Finally, Gene Set Enrichment Analysis (GSEA) was performed. RESULTS: In EBV-positive PBL, the immune-related pathway is upregulated and Cluster of differentiation 27 (CD27) and programmed cell death-ligand 1 (PD-L1) are hub genes. CONCLUSIONS: In EBV-positive PBL, EBV may affect tumorigenesis through activation of immune-related pathways and upregulation of CD27, PD-L1. Immune checkpoint blockers of CD70/CD27 and programmed cell death 1 (PD-1)/PD-L1 pathways may be one of the effective strategies for the treatment of EBV-positive PBL.

De novo transcriptome assemblies of C3 and C4 non-model grass species reveal key differences in leaf development.

BACKGROUND: C4 photosynthesis is a mechanism that plants have evolved to reduce the rate of photorespiration during the carbon fixation process. The C4 pathway allows plants to adapt to high temperatures and light while more efficiently using resources, such as water and nitrogen. Despite decades of studies, the evolution of the C4 pathway from a C3 ancestor remains a biological enigma. Interestingly, species with C3-C4 intermediates photosynthesis are usually found closely related to the C4 lineages. Indeed, current models indicate that the assembly of C4 photosynthesis was a gradual process that included the relocalization of photorespiratory enzymes, and the establishment of intermediate photosynthesis subtypes. More than a third of the C4 origins occurred within the grass family (Poaceae). In particular, the Otachyriinae subtribe (Paspaleae tribe) includes 35 American species from C3, C4, and intermediates taxa making it an interesting lineage to answer questions about the evolution of photosynthesis. RESULTS: To explore the molecular mechanisms that underpin the evolution of C4 photosynthesis, the transcriptomic dynamics along four different leaf segments, that capture different stages of development, were compared among Otachyriinae non-model species. For this, leaf transcriptomes were sequenced, de novo assembled, and annotated. Gene expression patterns of key pathways along the leaf segments showed distinct differences between photosynthetic subtypes. In addition, genes associated with photorespiration and the C4 cycle were differentially expressed between C4 and C3 species, but their expression patterns were well preserved throughout leaf development. CONCLUSIONS: New, high-confidence, protein-coding leaf transcriptomes were generated using high-throughput short-read sequencing. These transcriptomes expand what is currently known about gene expression in leaves of non-model grass species. We found conserved expression patterns of C4 cycle and photorespiratory genes among C3, intermediate, and C4 species, suggesting a prerequisite for the evolution of C4 photosynthesis. This dataset represents a valuable contribution to the existing genomic resources and provides new tools for future investigation of photosynthesis evolution.

Transcriptomic Approach for Global Distribution of SNP/Indel and Plant Genotyping.

Single Nucleotide Polymorphisms (SNPs) are the most common structural variants found in any genome. They have been used for different genetic studies, from the understanding of genetic structure of populations to the development of breeding selection markers. In this chapter we present the use of transcriptomic data obtained from contrasting phenotypes for a target trait, in searching of SNPs and insertions/deletions (InDels). This approach has the advantage that the identified markers are in or close to differentially expressed genes, and so they have higher chances to tag the genes underlying the phenotypic expression of a particular trait.

Lung Cancer Gene Regulatory Network of Transcription Factors Related to the Hallmarks of Cancer.

The transcriptomic analysis of microarray and RNA-Seq datasets followed our own bioinformatic pipeline to identify a transcriptional regulatory network of lung cancer. Twenty-six transcription factors are dysregulated and co-expressed in most of the lung cancer and pulmonary arterial hypertension datasets, which makes them the most frequently dysregulated transcription factors. Co-expression, gene regulatory, coregulatory, and transcriptional regulatory networks, along with fibration symmetries, were constructed to identify common connection patterns, alignments, main regulators, and target genes in order to analyze transcription factor complex formation, as well as its synchronized co-expression patterns in every type of lung cancer. The regulatory function of the most frequently dysregulated transcription factors over lung cancer deregulated genes was validated with ChEA3 enrichment analysis. A Kaplan-Meier plotter analysis linked the dysregulation of the top transcription factors with lung cancer patients' survival. Our results indicate that lung cancer has unique and common deregulated genes and transcription factors with pulmonary arterial hypertension, co-expressed and regulated in a coordinated and cooperative manner by the transcriptional regulatory network that might be associated with critical biological processes and signaling pathways related to the acquisition of the hallmarks of cancer, making them potentially relevant tumor biomarkers for lung cancer early diagnosis and targets for the development of personalized therapies against lung cancer.