Transcriptome Data Research Articles

Identification and expression analysis of the Xyloglucan transglycosylase/hydrolase (XTH) gene family under abiotic stress in oilseed (Brassica napus L.)

XTH genes are key genes that regulate the hydrolysis and recombination of XG components and plays role in the structure and composition of plant cell walls. Therefore, clarifying the changes that occur in XTHs during plant defense against abiotic stresses is informative for the study of the plant stress regulatory mechanism mediated by plant cell wall signals. XTH proteins in Arabidopsis thaliana was selected as the seed sequences in combination with its protein structural domains, 80 members of the BnXTH gene family were jointly identified from the whole genome of the Brassica napus ZS11, and analyzed for their encoded protein physicochemical properties, phylogenetic relationships, covariance relationships, and interoperating miRNAs. Based on the transcriptome data, the expression patterns of BnXTHs were analyzed in response to different abiotic stress treatments. The relative expression levels of some BnXTH genes under Al, alkali, salt, and drought treatments after 0, 6, 12 and 24 h were analyzed by using qRT-PCR to explore their roles in abiotic stress tolerance in B. napus. BnXTHs showed different expression patterns in response to different abiotic stress signals, indicating that the response mechanisms of oilseed rape against different abiotic stresses are also different. This paper provides a theoretical basis for clarifying the function and molecular genetic mechanism of the BnXTH gene family in abiotic stress tolerance in rapeseed.

Magnaporthe oryzae infection triggers rice resistance to brown planthopper through the influence of jasmonic acid on the flavonoid biosynthesis pathway.

In agroecosystems, plants are constantly exposed to attack from diverse herbivorous insects and microbes, and infestation with one species may change the plant defense response to other species. In our investigation of the relationships among rice plants, the brown planthopper Nilaparvata lugens (Stål) and the rice blast fungus Magnaporthe oryzae, we observed a significant increase in the resistance of rice treated with rice blast to N.lugens, as evidenced by improved plant survival rates in a small population resistance study. Subsequent transcriptome data analysis revealed that the rice blast fungus can induce the expression of genes in the jasmonic acid (JA) and flavonoid pathways. Similar to the flavonoid pathway, the JA pathway also contains 2 types of genes that exhibit similar and opposite trends in response to N.lugens and rice blast. Among these genes, the osjaz1 mutant and the osmyc2 mutant were phenotypically confirmed to positively and negatively regulate rice resistance to N.lugens and rice blast, respectively. Subsequent mass spectrometry and quantification experiments showed that the exogenous application of methyl jasmonate (MeJA) can induce the accumulation of eriodictyol, naringenin and quercetin, as well as the expression of OsF3H, Os4CL5 and OsCHI in the flavonoid pathway. This suggests a close connection between the JA pathway and the flavonoid pathway. However, OsF3'H, which negatively regulates rice resistance to N.lugens and rice blast, did not show increased expression. Phenotypic and molecular experiments confirmed that OsMYC2 can bind to and inhibit the expression of OsF3'H, thus revealing the mechanism of rice resistance to N.lugens after treatment with rice blast. These findings will deepen our understanding of the interactions among rice, N.lugens and rice blast.

Temporal Transcriptomic Profiling Reveals Dynamic Changes in Gene Expression of Giant Freshwater Prawn upon Acute Saline-Alkaline Stresses.

Bicarbonate and sulfate are among two primary ion constituents of saline-alkaline water, with excessive levels potentially causing metabolic disorders in crustaceans, affecting their molting and interrupting development. As an economically important crustacean species, the molecular adaptive mechanism of giant freshwater prawn Macrobrachium rosenbergii in response to the stress of bicarbonate and sulfate remains unexplored. To investigate the mechanism underlying NaHCO3, Na2SO4, and mixed NaHCO3, Na2SO4 stresses, M. rosenbergii larvae were exposed to the above three stress conditions, followed by total RNA extraction and high-throughput sequencing at eight distinct time points (0, 4, 8, 12, 24, 48, 72, and 96h). Subsequent analysis revealed 13, 16, and 13 consistently identified differentially expressed genes (DEGs) across eight time points under three stress conditions. These consistently identified DEGs were significantly involved in the Gene Ontology (GO) terms of chitin-based cuticle development, protein-carbohydrate complex, structural constituent of cuticle, carnitine biosynthetic process, extracellular matrix, and polysaccharide catabolic process, indicating that alkaline stresses might potentially impact the energy metabolism, growth, and molting of M. rosenbergii larvae. Particularly, the transcriptome data revealed that DEGs associated with energy metabolism, immunity, and amino acid metabolism were enriched across multiple time points under three stress conditions. These DEGs are linked to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, including glycolysis/glucogenesis, amino sugar and nucleotide sugar metabolism, and lysine degradation. Consistent enrichment findings across the three stress conditions support conclusions above. Together, these insights are instrumental in enhancing our understanding of the molecular mechanisms underlying the alkaline response in M. rosenbergii larvae. Additionally, they offer valuable perspectives on the regulatory mechanisms of freshwater crustaceans amid saline-alkaline water development.

Natural variations of heterosis-related allele-specific expression genes in promoter regions lead to allele-specific expression in maize

BackgroundHeterosis has successfully enhanced maize productivity and quality. Although significant progress has been made in delineating the genetic basis of heterosis, the molecular mechanisms underlying its genetic components remain less explored. Allele-specific expression (ASE), the imbalanced expression between two parental alleles in hybrids, is increasingly being recognized as a factor contributing to heterosis. ASE is a complex process regulated by both epigenetic and genetic variations in response to developmental and environmental conditions.ResultsIn this study, we explored the differential characteristics of ASE by analyzing the transcriptome data of two maize hybrids and their parents under four light conditions. On the basis of allele expression patterns in different hybrids under various conditions, ASE genes were divided into three categories: bias-consistent genes involved in basal metabolic processes in a functionally complementary manner, bias-reversal genes adapting to the light environment, and bias-specific genes maintaining cell homeostasis. We observed that 758 ASE genes (ASEGs) were significantly overlapped with heterosis quantitative trait loci (QTLs), and high-frequency variations in the promoter regions of heterosis-related ASEGs were identified between parents. In addition, 10 heterosis-related ASEGs participating in yield heterosis were selected during domestication.ConclusionsThe comprehensive analysis of ASEGs offers a distinctive perspective on how light quality influences gene expression patterns and gene-environment interactions, with implications for the identification of heterosis-related ASEGs to enhance maize yield.

Comparing Transcriptomic Points of Departure to Apical Effect Concentrations For Larval Fathead Minnow Exposed to Chemicals with Four Different Modes Of Action.

It is postulated that below a transcriptomic-based point of departure, adverse effects are unlikely to occur, thereby providing a chemical concentration to use in screening level hazard assessment. The present study extends previous work describing a high-throughput fathead minnow assay that can provide full transcriptomic data after exposure to a test chemical. One-day post-hatch fathead minnows were exposed to ten concentrations of three representatives of four chemical modes of action: organophosphates, ecdysone receptor agonists, plant photosystem II inhibitors, and estrogen receptor agonists for 24 h. Concentration response modeling was performed on whole body gene expression data from each exposure, using measured chemical concentrations when available. Transcriptomic points of departure in larval fathead minnow were lower than apical effect concentrations across fish species but not always lower than toxic effect concentrations in other aquatic taxa like crustaceans and insects. The point of departure was highly dependent on measured chemical concentration which were often lower than the nominal concentration. Differentially expressed genes between chemicals within modes of action were compared and often showed statistically significant overlap. In addition, reproducibility between identical exposures using a positive control chemical (CuSO4) and variability associated with the transcriptomic point of departure using in silico sampling were considered. Results extend a transcriptomic-compatible fathead minnow high-throughput assay for possible use in ecological hazard screening.

Machine Learning-Based Integrated Multiomics Characterization of Colorectal Cancer Reveals Distinctive Metabolic Signatures.

The metabolic signature identification of colorectal cancer is critical for its early diagnosis and therapeutic approaches that will significantly block cancer progression and improve patient survival. Here, we combined an untargeted metabolic analysis strategy based on internal extractive electrospray ionization mass spectrometry and the machine learning approach to analyze metabolites in 173 pairs of cancer samples and matched normal tissue samples to build robust metabolic signature models for diagnostic purposes. Screening and independent validation of metabolic signatures from colorectal cancers via machine learning methods (Logistic Regression_L1 for feature selection and eXtreme Gradient Boosting for classification) was performed to generate a panel of seven signatures with good diagnostic performance (the accuracy of 87.74%, sensitivity of 85.82%, and specificity of 89.66%). Moreover, seven signatures were evaluated according to their ability to distinguish between cancer and normal tissues, with the metabolic molecule PC (30:0) showing good diagnostic performance. In addition, genes associated with PC (30:0) were identified by multiomics analysis (combining metabolic data with transcriptomic data analysis) and our results showed that PC (30:0) could promote the proliferation of colorectal cancer cell SW480, revealing the correlation between genetic changes and metabolic dysregulation in cancer. Overall, our results reveal potential determinants affecting metabolite dysregulation, paving the way for a mechanistic understanding of altered tissue metabolites in colorectal cancer and design interventions for manipulating the levels of circulating metabolites.

Machine-learning developed an iron, copper, and sulfur-metabolism associated signature predicts lung adenocarcinoma prognosis and therapy response

BackgroundPrevious studies have largely neglected the role of sulfur metabolism in LUAD, and no study has combine iron, copper, and sulfur-metabolism associated genes together to create prognostic signatures.MethodsThis study encompasses 1564 LUAD patients, 1249 NSCLC patients, and over 10,000 patients with various cancer types from diverse cohorts. We employed the R package ConsensusClusterPlus to separate patients into different ICSM (Iron, Copper, and Sulfur-Metabolism) subtypes. Various machine-learning methods were utilized to develop the ICSMI. Enrichment analyses were conducted using ClusterProfiler and GSVA, while IOBR quantified immune cell infiltration. GISTIC2.0 and maftools were utilized for CNV and SNV data analysis. The Oncopredict package predicted drug information based on GDSC1. TIDE algorithm and cohorts GSE91061 and IMvigor210 evaluated patient response to immunotherapy. Single-cell data was processed using the Seurat package, AUCell package calculated cells geneset activity scores, and the Scissor algorithm identified ICSMI-associated cells. In vitro experiments was conducted to explore the role of ICSMRGs in LUAD.ResultsUnsupervised clustering identified two distinct ICSM subtypes of LUAD, each with unique clinical characteristics. The ICSMI, comprising 10 genes, was constructed using integrated machine-learning methods. Its prognostic power was validated in 10 independent datasets, revealing that LUAD patients with higher ICSMI levels had poorer prognoses. Furthermore, ICSMI demonstrated superior predictive abilities compared to 102 previously published signatures. A nomogram incorporating ICSMI and clinical features exhibited high predictive performance. ICSMI positively correlated with patients gene mutations, and integrated analysis of bulk and single-cell transcriptome data revealed its association with TME modulators. Cells representing the high-ICSMI phenotype exhibited more malignant features. LUAD patients with high ICSMI levels exhibited sensitivity to chemotherapy and targeted therapy but displayed resistance to immunotherapy. In a comprehensive analysis across various cancers, ICSMI retained significant prognostic value and emerged as a risk factor for the majority of cancer patients.ConclusionsICSMI provides critical prognostic insights for LUAD patients, offering valuable insights into the tumor microenvironment and predicting treatment responsiveness.

GAGE-seq concurrently profiles multiscale 3D genome organization and gene expression in single cells.

The organization of mammalian genomes features a complex, multiscale three-dimensional (3D) architecture, whose functional significance remains elusive because of limited single-cell technologies that can concurrently profile genome organization and transcriptional activities. Here, we introduce genome architecture and gene expression by sequencing (GAGE-seq), a scalable, robust single-cell co-assay measuring 3D genome structure and transcriptome simultaneously within the same cell. Applied to mouse brain cortex and human bone marrow CD34+ cells, GAGE-seq characterized the intricate relationships between 3D genome and gene expression, showing that multiscale 3D genome features inform cell-type-specific gene expression and link regulatory elements to target genes. Integration with spatial transcriptomic data revealed in situ 3D genome variations in mouse cortex. Observations in human hematopoiesis unveiled discordant changes between 3D genome organization and gene expression, underscoring a complex, temporal interplay at the single-cell level. GAGE-seq provides a powerful, cost-effective approach for exploring genome structure and gene expression relationships at the single-cell level across diverse biological contexts.

Genomic identification and expression analysis of acid invertase (AINV) gene family in Dendrobium officinale Kimura et Migo

BackgroundDendrobium officinale Kimura et Migo, a renowned traditional Chinese orchid herb esteemed for its significant horticultural and medicinal value, thrives in adverse habitats and contends with various abiotic or biotic stresses. Acid invertases (AINV) are widely considered enzymes involved in regulating sucrose metabolism and have been revealed to participate in plant responses to environmental stress. Although members of AINV gene family have been identified and characterized in multiple plant genomes, detailed information regarding this gene family and its expression patterns remains unknown in D. officinale, despite their significance in polysaccharide biosynthesis.ResultsThis study systematically analyzed the D. officinale genome and identified four DoAINV genes, which were classified into two subfamilies based on subcellular prediction and phylogenetic analysis. Comparison of gene structures and conserved motifs in DoAINV genes indicated a high-level conservation during their evolution history. The conserved amino acids and domains of DoAINV proteins were identified as pivotal for their functional roles. Additionally, cis-elements associated with responses to abiotic and biotic stress were found to be the most prevalent motif in all DoAINV genes, indicating their responsiveness to stress. Furthermore, bioinformatics analysis of transcriptome data, validated by quantitative real-time reverse transcription PCR (qRT-PCR), revealed distinct organ-specific expression patterns of DoAINV genes across various tissues and in response to abiotic stress. Examination of soluble sugar content and interaction networks provided insights into stress release and sucrose metabolism.ConclusionsDoAINV genes are implicated in various activities including growth and development, stress response, and polysaccharide biosynthesis. These findings provide valuable insights into the AINV gene amily of D. officinale and will aid in further elucidating the functions of DoAINV genes.

Enhancing pathological complete response prediction in breast cancer: the role of dynamic characterization of DCE-MRI and its association with tumor heterogeneity

BackgroundEarly prediction of pathological complete response (pCR) is important for deciding appropriate treatment strategies for patients. In this study, we aimed to quantify the dynamic characteristics of dynamic contrast-enhanced magnetic resonance images (DCE-MRI) and investigate its value to improve pCR prediction as well as its association with tumor heterogeneity in breast cancer patients.MethodsThe DCE-MRI, clinicopathologic record, and full transcriptomic data of 785 breast cancer patients receiving neoadjuvant chemotherapy were retrospectively included from a public dataset. Dynamic features of DCE-MRI were computed from extracted phase-varying radiomic feature series using 22 CAnonical Time-sereis CHaracteristics. Dynamic model and radiomic model were developed by logistic regression using dynamic features and traditional radiomic features respectively. Various combined models with clinical factors were also developed to find the optimal combination and the significance of each components was evaluated. All the models were evaluated in independent test set in terms of area under receiver operating characteristic curve (AUC). To explore the potential underlying biological mechanisms, radiogenomic analysis was implemented on patient subgroups stratified by dynamic model to identify differentially expressed genes (DEGs) and enriched pathways.ResultsA 10-feature dynamic model and a 4-feature radiomic model were developed (AUC = 0.688, 95%CI: 0.635–0.741 and AUC = 0.650, 95%CI: 0.595–0.705) and tested (AUC = 0.686, 95%CI: 0.594–0.778 and AUC = 0.626, 95%CI: 0.529–0.722), with the dynamic model showing slightly higher AUC (train p = 0.181, test p = 0.222). The combined model of clinical, radiomic, and dynamic achieved the highest AUC in pCR prediction (train: 0.769, 95%CI: 0.722–0.816 and test: 0.762, 95%CI: 0.679–0.845). Compared with clinical-radiomic combined model (train AUC = 0.716, 95%CI: 0.665–0.767 and test AUC = 0.695, 95%CI: 0.656–0.714), adding the dynamic component brought significant improvement in model performance (train p < 0.001 and test p = 0.005). Radiogenomic analysis identified 297 DEGs, including CXCL9, CCL18, and HLA-DPB1 which are known to be associated with breast cancer prognosis or angiogenesis. Gene set enrichment analysis further revealed enrichment of gene ontology terms and pathways related to immune system.ConclusionDynamic characteristics of DCE-MRI were quantified and used to develop dynamic model for improving pCR prediction in breast cancer patients. The dynamic model was associated with tumor heterogeniety in prognostic-related gene expression and immune-related pathways.

Genome-wide identification of the walnut MYC gene family and functional characterization of Xinjiang wild walnut under low-temperature stress

Introduction: MYC transcription factors are the basic regulators of the jasmonic acid signaling pathway and play important roles in plant growth and development and the response to adverse stress. In recent years, severe winter freezing and late spring frost in the main planting area of walnut in Xinjiang have affected the growth and development of walnut, which has become a prominent problem restricting walnut production. Xinjiang wild walnut is the only remaining wild species of walnuts in China, which contains a lot of genes with excellent traits, and is important for the cultivation and breeding.Methods: In this paper, the physicochemical properties and bioinformatics of MYC transcription factor members in walnut were analyzed, and the nine MYC were screened from the transcriptome data under low temperature stress. At last, we study the subcellular localizations and the expression patterns of the nine MYC members in Xinjiang wild walnut.Results: The results revealed that 30 MYC members were identified from published walnut whole-genome data, and their evolutionary relationships with Arabidopsis and poplar were divided into six groups according to clustering analysis, among which JrMYC22 and JrMYC23 had high homology with PtrMYC2b, which is induced by jasmonic acid in response to low-temperature stress. Walnut MYC members are unevenly distributed on 12 chromosomes. The prediction of promoter cis-acting elements of walnut MYC transcription factor family members revealed that cis-acting elements related to jasmonic acid and lowtemperature stress were the ones with the greatest number of members, with 12. In addition, all nine MYC family members in Xinjiang wild walnut plants responding to low-temperature stress exhibited strong fluorescence responses in the nucleus. The expression levels of these members in response to low-temperature stress revealed that JrMYC28, JrMYC31, JrMYC33, JrMYC34, and JrMYC35 were highly expressed, and it was hypothesized that JrMYC28, JrMYC31, JrMYC33, JrMYC34, and JrMYC35 might play a key role in the response to lowtemperature stress.Discussion: The results of this study provide a theoretical basis for further research on the functional mechanisms of the MYC transcription factor family members in walnut.

Starch and sucrose metabolism plays an important role in the stem development in Medicago sativa.

The forage quality of alfalfa (Medicago sativa ) stems is greater than the leaves. Sucrose hydrolysis provides energy for stem development, with starch being enzymatically converted into sucrose to maintain energy homeostasis. To understand the physiological and molecular networks controlling stem development, morphological characteristics and transcriptome profiles in the stems of two alfalfa cultivars (Zhungeer and WL168) were investigated. Based on transcriptome data, we analysed starch and sugar contents, and enzyme activity related to starch-sugar interconversion. Zhungeer stems were shorter and sturdier than WL168, resulting in significantly higher mechanical strength. Transcriptome analysis showed that starch and sucrose metabolism were significant enriched in the differentially expressed genes of stems development in both cultivars. Genes encoding INV , bglX , HK , TPS and glgC downregulated with the development of stems, while the gene encoding was AMY upregulated. Weighted gene co-expression network analysis revealed that the gene encoding glgC was pivotal in determining the variations in starch and sucrose contents between the two cultivars. Soluble carbohydrate, sucrose, and starch content of WL168 were higher than Zhungeer. Enzyme activities related to sucrose synthesis and hydrolysis (INV, bglX, HK, TPS) showed a downward trend. The change trend of enzyme activity was consistent with gene expression. WL168 stems had higher carbohydrate content than Zhungeer, which accounted for more rapid growth and taller plants. WL168 formed hollow stems were formed during rapid growth, which may be related to the redistribution of carbohydrates in the pith tissue. These results indicated that starch and sucrose metabolism play important roles in the stem development in alfalfa.

Deciphering the role of a SINE-VNTR-Alu retrotransposon polymorphism as a biomarker of Parkinson’s disease progression

SINE-VNTR-Alu (SVA) retrotransposons are transposable elements which represent a source of genetic variation. We previously demonstrated that the presence/absence of a human-specific SVA, termed SVA_67, correlated with the progression of Parkinson’s disease (PD). In the present study, we demonstrate that SVA_67 acts as expression quantitative trait loci, thereby exhibiting a strong regulatory effect across the genome using whole genome and transcriptomic data from the Parkinson’s progression markers initiative cohort. We further show that SVA_67 is polymorphic for its variable number tandem repeat domain which correlates with both regulatory properties in a luciferase reporter gene assay in vitro and differential expression of multiple genes in vivo. Additionally, this variation’s utility as a biomarker is reflected in a correlation with a number of PD progression markers. These experiments highlight the plethora of transcriptomic and phenotypic changes associated with SVA_67 polymorphism which should be considered when investigating the missing heritability of neurodegenerative diseases.

Nanoformulation of dasatinib cannot overcome therapy resistance of pancreatic cancer cells with low LYN kinase expression.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most difficult to treat tumors. The Src (sarcoma) inhibitor dasatinib (DASA) has shown promising efficacy in preclinical studies of PDAC. However, clinical confirmation could not be achieved. Overall, our aim was to deliver arguments for the possible reinitiating clinical testing of this compound in a biomarker-stratifying therapy trial for PDAC patients. We tested if the nanofunctionalization of DASA can increase the drug efficacy and whether certain Src members can function as clinical predictive biomarkers. Methods include manufacturing of poly(vinyl alcohol) stabilized gold nanoparticles and their drug loading, dynamic light scattering, transmission electron microscopy, thermogravimetric analysis, Zeta potential measurement, sterile human cell culture, cell growth quantification, accessing and evaluating transcriptome and clinical data from molecular tumor dataset TCGA, as well as various statistical analyses. We generated homo-dispersed nanofunctionalized DASA as an AuNP@PVA-DASA conjugate. The composite did not enhance the anti-growth effect of DASA on PDAC cell lines. The cell model with high LYN expression showed the strongest response to the therapy. We confirm deregulated Src kinetome activity as a prevalent feature of PDAC by revealing mRNA levels associated with higher malignancy grade of tumors. BLK (B lymphocyte kinase) expression predicts shorter overall survival of diabetic PDAC patients. Nanofunctionalization of DASA needs further improvement to overcome the therapy resistance of PDAC. LYN mRNA is augmented in tumors with higher malignancy and can serve as a predictive biomarker for the therapy resistance of PDAC cells against DASA. Studying the biological roles of BLK might help to identify underlying molecular mechanisms associated with PDAC in diabetic patients.

Coevolution of Non-Homologous End Joining efficiency and encephalization.

Double strand breaks, the most difficult to repair DNA damage, are mainly repaired by Non-Homologous End-Joining (NHEJ) or Homologous Recombination (HR). Previous studies seem to indicate that primates, and particularly humans, have a better NHEJ system. A distinctive feature of the primate lineage (beside longevity) is encephalization, i.e. the expansion of brain relative to body mass. Using existing transcriptome data from 34 mammalian species, we investigated the possible correlations between the expression of genes involved in NHEJ and encephalization, body mass and longevity. The same was done also for genes involved in the HR pathway. We found that, while HR gene expression is better correlated with longevity, NHEJ gene expression is strongly (and better) correlated with encephalization. Since the brain is composed of post-mitotic cells, double-strand breaks repair should be mainly performed by NHEJ in this organ. Therefore, we interpret the correlation we found as an indication that NHEJ efficiency coevolved with encephalization.

Genome-Wide Identification and Characterization of the PPPDE Gene Family in Rice

Protein ubiquitination is common and crucial in cellular functions, however, little is known about how deubiquitinating enzymes (DUBs) reverse regulate the ubiquitination signaling process. PPPDE family proteins are a novel class of deubiquitinating peptidases with demonstrated deubiquitination/deSUMOylating activities. In this study, we identified 10 PPPDE genes from the rice (Oryza sativa L.) genome unevenly distributed on five chromosomes, where most of these members have not been reported to date. Based on the gene structure, the OsPPPDE family consists of three distinct subgroups within the phylogenetic tree. Cis-element analysis identified light/phytohormone-responsive, development, and abiotic stress-related elements in the promoters of OsPPPDE. Furthermore, we conducted and analyzed the transcript abundance of OsPPPDE under various tissues and stresses using the transcriptome data of 352 samples from the Rice Expression Database and GEO datasets. Moreover, OsPPPDE5 showed differential regulation of its transcript abundance during Cd and drought stress. Collinearity and syntenic analysis of 101 PPPDEs and PPPDE-like proteins in 10 plant genomes indicated that this family is evolutionarily conserved. Domestication analysis suggests that OsPPPDEs may contribute to indica–japonica divergence using the data from the 3K Rice Genome Project. Our study provides a foundation for further study on the function and molecular mechanism of the OsPPPDE gene family.

Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

BackgroundVitamin C (ascorbate) is a water-soluble antioxidant and an important cofactor for various biosynthetic and regulatory enzymes. Mice can synthesize vitamin C thanks to the key enzyme gulonolactone oxidase (Gulo) unlike humans. In the current investigation, we used Gulo−/− mice, which cannot synthesize their own ascorbate to determine the impact of this vitamin on both the transcriptomics and proteomics profiles in the whole liver. The study included Gulo−/− mouse groups treated with either sub-optimal or optimal ascorbate concentrations in drinking water. Liver tissues of females and males were collected at the age of four months and divided for transcriptomics and proteomics analysis. Immunoblotting, quantitative RT-PCR, and polysome profiling experiments were also conducted to complement our combined omics studies.ResultsPrincipal component analyses revealed distinctive differences in the mRNA and protein profiles as a function of sex between all the mouse cohorts. Despite such sexual dimorphism, Spearman analyses of transcriptomics data from females and males revealed correlations of hepatic ascorbate levels with transcripts encoding a wide array of biological processes involved in glucose and lipid metabolisms as well as in the acute-phase immune response. Moreover, integration of the proteomics data showed that ascorbate modulates the abundance of various enzymes involved in lipid, xenobiotic, organic acid, acetyl-CoA, and steroid metabolism mainly at the transcriptional level, especially in females. However, several proteins of the mitochondrial complex III significantly correlated with ascorbate concentrations in both males and females unlike their corresponding transcripts. Finally, poly(ribo)some profiling did not reveal significant enrichment difference for these mitochondrial complex III mRNAs between Gulo−/− mice treated with sub-optimal and optimal ascorbate levels.ConclusionsThus, the abundance of several subunits of the mitochondrial complex III are regulated by ascorbate at the post-transcriptional levels. Our extensive omics analyses provide a novel resource of altered gene expression patterns at the transcriptional and post-transcriptional levels under ascorbate deficiency.

A multilevel investigation to reveal the regulatory mechanism of lignin accumulation in juice sac granulation of pomelo

Granulation of juice sacs is a physiological disorder, which affects pomelo fruit quality. Here, the transcriptome and ubiquitinome of the granulated juice sacs were analyzed in Guanxi pomelo. We found that lignin accumulation in the granulated juice sacs was regulated at transcription and protein modification levels. In transcriptome data, we found that the genes in lignin biosynthesis pathway and antioxidant enzyme system of the granulated juice sacs were significantly upregulated. However, in ubiquitinome data, we found that ubiquitinated antioxidant enzymes increased in abundance but the enzyme activities decreased after the modification, which gave rise to reactive oxygen species (ROS) contents in granulated juice sacs. This finding suggests that ubiquitination level of the antioxidant enzymes is negatively correlated with the enzyme activities. Increased H2O2 is considered to be a signaling molecule to activate the key gene expressions in lignin biosynthesis pathway, which leads to the lignification in granulated juice sacs of pomelo. This regulatory mechanism in juice sac granulation of pomelo was further confirmed through the verification experiment using tissue culture by adding H2O2 or dimethylthiourea (DMTU). Our findings suggest that scavenging H2O2 and other ROS are important for reducing lignin accumulation, alleviating juice sac granulation and improving pomelo fruit quality.

A novel disulfide death-related genes prognostic signature identifies the role of IPO4 in glioma progression

Background“Disulfide death,” a form of cellular demise, is triggered by the abnormal accumulation of intracellular disulfides under conditions of glucose deprivation. However, its role in the prognosis of glioma remains undetermined. Therefore, the main objective of this study is to establish prognostic signature based on disulfide death-related genes (DDRGs) and to provide new solutions in choosing the effective treatment of glioma.MethodsThe RNA transcriptome, clinical information, and mutation data of glioma samples were sourced from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA), while normal samples were obtained from the Genotype-Tissue Expression (GTEx). DDRGs were compiled from previous studies and selected through differential analysis and univariate Cox regression analysis. The molecular subtypes were determined through consensus clustering analysis. Further, LASSO analysis was employed to select characteristic genes, and subsequently, a risk model comprising seven DDRGs was constructed based on multivariable Cox analysis. Kaplan-Meier survival curves were employed to assess survival differences between high and low-risk groups. Additionally, functional analyses (GO, KEGG, GSEA) were conducted to explore the potential biological functions and signaling pathways of genes associated with the model. The study also explored immune checkpoint (ICP) genes, immune cell infiltration levels, and immune stromal scores. Finally, the effect of Importin-4(IPO4) on glioma has been further confirmed through RT-qPCR, Western blot, and cell functional experiments.Results7 genes associated with disulfide death were obtained and two subgroups of patients with different prognosis and clinical characteristics were identified. Risk signature was subsequently developed and proved to serve as an prognostic predictor. Notably, the high-risk group exhibited an immunosuppressive microenvironment characterized by a high concentration of M2 macrophages and regulatory T cells (Tregs). In contrast, the low-risk group showed lower half-maximal inhibitory concentration (IC50) values. Therefore, patients in the high-risk group may benefit more from immunotherapy, while patients in the low-risk group may benefit more from chemotherapy. In addition, in vitro experiments have shown that inhibition of the expression of IPO4 leads to a significant reduction in the proliferation, migration, and invasion of glioma cells.ConclusionThis study identified two glioma subtypes and constructed a prognostic signature based on DDRGs. The signature has the potential to optimize the selection of patients for immune- and chemotherapy and provided a potential therapeutic target for glioma.

Retraction Note: Identification of biomarkers of hepatocellular carcinoma gene prognosis based on the immune-related lncRNA signature of transcriptome data.

Retraction Note: Identification of biomarkers of hepatocellular carcinoma gene prognosis based on the immune-related lncRNA signature of transcriptome data.