scholarly journals Whole-Genome DNA Methylation Associated With Differentially Expressed Genes Regulated Anthocyanin Biosynthesis Within Flower Color Chimera of Ornamental Tree Prunus mume

Forests ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 90
Author(s):  
Liangbao Jiang ◽  
Man Zhang ◽  
Kaifeng Ma

DNA methylation is one of the best-studied epigenetic modifications involved in many biological processes. However, little is known about the epigenetic mechanism for flower color chimera of Prunus mume (Japanese apricot, mei). Using bisulfate sequencing and RNA sequencing, we analyzed the white (FBW) and red (FBR) petals collected from an individual tree of Japanese apricot cv. ‘Fuban Tiaozhi’ mei to reveal the different changes in methylation patterns associated with gene expression leading to significant difference in anthocyanins accumulation of FBW (0.012 ± 0.005 mg/g) and FBR (0.078 ± 0.013 mg/g). It was found that gene expression levels were positively correlated with DNA methylation levels within gene-bodies of FBW and FBR genomes; however, negative correlations between gene expression and DNA methylation levels were detected within promoter domains. In general, the methylation level within methylome of FBW was higher; and in total, 4,618 differentially methylated regions (DMRs) and 1,212 differentially expressed genes (DEGs) were detected from FBW vs. FBR. We also identified 82 DMR-associated DEGs, and 13 of them, including PmBAHD, PmCYP450, and PmABC, were playing critical roles in phenylalanine metabolism pathway, glycosyltransferase activity, and ABC transporter. The evidence exhibited DNA methylation may regulate gene expression resulting in flower color chimera of Japanese apricot.

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Xiao-Liang Xing ◽  
Zhi-Yong Yao ◽  
Chaoqun Xing ◽  
Zhi Huang ◽  
Jing Peng ◽  
...  

Abstract Background Colorectal cancer (CRC) is the second most prevalent cancer, as it accounts for approximately 10% of all annually diagnosed cancers. Studies have indicated that DNA methylation is involved in cancer genesis. The purpose of this study was to investigate the relationships among DNA methylation, gene expression and the tumor-immune microenvironment of CRC, and finally, to identify potential key genes related to immune cell infiltration in CRC. Methods In the present study, we used the ChAMP and DESeq2 packages, correlation analyses, and Cox regression analyses to identify immune-related differentially expressed genes (IR-DEGs) that were correlated with aberrant methylation and to construct a risk assessment model. Results Finally, we found that HSPA1A expression and CCRL2 expression were positively and negatively associated with the risk score of CRC, respectively. Patients in the high-risk group were more positively correlated with some types of tumor-infiltrating immune cells, whereas they were negatively correlated with other tumor-infiltrating immune cells. After the patients were regrouped according to the median risk score, we could more effectively distinguish them based on survival outcome, clinicopathological characteristics, specific tumor-immune infiltration status and highly expressed immune-related biomarkers. Conclusion This study suggested that the risk assessment model constructed by pairing immune-related differentially expressed genes correlated with aberrant DNA methylation could predict the outcome of CRC patients and might help to identify those patients who could benefit from antitumor immunotherapy.


2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Cheng Zhang ◽  
Bingye Zhang ◽  
Di Meng ◽  
Chunlin Ge

Abstract Background The incidence of cholangiocarcinoma (CCA) has risen in recent years, and it has become a significant health burden worldwide. However, the mechanisms underlying tumorigenesis and progression of this disease remain largely unknown. An increasing number of studies have demonstrated crucial biological functions of epigenetic modifications, especially DNA methylation, in CCA. The present study aimed to identify and analyze methylation-regulated differentially expressed genes (MeDEGs) involved in CCA tumorigenesis and progression by bioinformatics analysis. Methods The gene expression profiling dataset (GSE119336) and gene methylation profiling dataset (GSE38860) were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were identified using the limma packages of R and GEO2R, respectively. The MeDEGs were obtained by overlapping the DEGs and DMGs. Functional enrichment analyses of these genes were then carried out. Protein–protein interaction (PPI) networks were constructed using STRING and visualized in Cytoscape to determine hub genes. Finally, the results were verified based on The Cancer Genome Atlas (TCGA) database. Results We identified 98 hypermethylated, downregulated genes and 93 hypomethylated, upregulated genes after overlapping the DEGs and DMGs. These genes were mainly enriched in the biological processes of the cell cycle, nuclear division, xenobiotic metabolism, drug catabolism, and negative regulation of proteolysis. The top nine hub genes of the PPI network were F2, AHSG, RRM2, AURKB, CCNA2, TOP2A, BIRC5, PLK1, and ASPM. Moreover, the expression and methylation status of the hub genes were significantly altered in TCGA. Conclusions Our study identified novel methylation-regulated differentially expressed genes (MeDEGs) and explored their related pathways and functions in CCA, which may provide novel insights into a further understanding of methylation-mediated regulatory mechanisms in CCA.


Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 3671-3671
Author(s):  
Michael Getman ◽  
Jeffrey Malik ◽  
James Palis ◽  
Laurie A Steiner

Abstract The molecular mechanisms that drive the maturation of a committed erythroid progenitor to a functional red blood cell are incompletely understood. LSD1 (Lysine-Specific Histone Demethylase 1) is a widely expressed histone demethylase that plays an important role in erythroid maturation (Kereyni, elife, 2013). Although LSD1 is important for a number of biologic processes ranging from embryonic development to leukemogenesis, the molecular mechanisms underlying the influence of LSD1 on gene expression are incompletely understood. The goal of our study is to elucidate the molecular mechanisms by which LSD1 regulates erythroid gene expression and influences erythroid maturation. We hypothesize that LSD1 promotes specific patterns of histone and DNA methylation that facilitate gene expression changes necessary for normal erythroid maturation to occur. To address this hypothesis, the functional and molecular consequences of LSD1 knockdown were assessed in Extensively Self Renewing Erythroblasts (ESREs), a non-transformed, karyotypically normal model of terminal erythroid maturation (England, Blood, 2011). Primary fetal liver was cultured in the presence of EPO, SCF, IGF1 and dexamethasone to derive ESREs. The ESREs were capable of extensive ex-vivo expansion, doubling daily at the proerythroblast phase, however when matured, >90% of cells became benzidine positive and >65% enucleated within 3 days. Lentiviral-mediated shRNA was used to knock down LSD1 in expanding ESREs. Imaging flow cytometry done on maturation day 3 demonstrated that the knockdown cells had impairments in multiple facets of maturation, with larger cell and nuclear areas, higher kit expression, and lower rates of enucleation than the scramble control. LSD1 knockdown was also associated with impaired hemoglobin accumulation (78% vs. 95% benzidine positive; p<0.005). Treatment of ESREs with an inhibitor to LSD1 (Tranylcypromine; TCP) resulted in similar abnormalities in cell and nuclear size, kit expression, hemoglobin accumulation, and enucleation (40% vehicle vs.1% TCP). The functional deficits in maturation, including abnormal kit expression and low rates of enucleation, persisted on maturation day 4. To delineate the molecular mechanisms underlying this maturation impairment, RNA-seq was done in LSD1 knockdown and scramble control samples, and 230 differentially expressed genes (FDR<0.01) were identified using cuffdiff (Trapnell, Nat Biotech, 2013). Consistent with LSD1’s role in erythroid maturation, Ingenuity Pathway Analysis identified multiple networks involving hemoglobin synthesis, and GATA1, EPO, and KLF1 were all predicted as upstream regulators (p-values of 8.24e10-11, 7.25 e10-6, and 3.86e10-4, respectively). To better understand how LSD1 influences gene expression, chromatin immunoprecipitation coupled with high throughput sequencing was used to identify sites of H3K4me2 binding in the differentially expressed genes. 214/230 differentially expressed genes were associated with sites of H3K4me2 occupancy. Quantitative ChIP demonstrated that LSD1 inhibition was associated with increases in H3K4me2 levels at a subset of these sites, however consistent with previous studies, global levels of H3K4me2, determined by Enzyme Linked Immunosorbent Assay (ELIZA), did not change significantly. Although it is known that LSD1 demethylates and stabilizes the maintenance DNA methyltransferase DNMT1 (Wang, Nat Genet 2009), the consequences of LSD1 loss on DNA methylation (5-methyl cytosine; 5-mC) have yet to be investigated. To gain a comprehensive understanding of how LSD1 regulates erythroid gene expression, changes in the level of 5-mC were assessed after knockdown or inhibition of LSD1. Global 5-mC levels, determined by ELIZA assay, were ∼30% lower in TCP treated samples than vehicle treated control (p<0.02) and western blot demonstrated a 3-fold decrease in DNMT1 protein in the TCP treated samples. Both methyl binding domain pull-down coupled with quantitative PCR and genome-wide bisulfite sequencing were utilized to assess changes in 5-mC levels in the differentially expressed genes. Loss of LSD1 was associated with significantly lower levels of 5-mC at several differentially expressed, erythroid-specific genes, such as bh1. Taken together, these data support the hypothesis that LSD1 influences both histone and DNA methylation at genes important for erythroid maturation. Disclosures: No relevant conflicts of interest to declare.


2020 ◽  
Author(s):  
Shijie Gao ◽  
Guowang Li ◽  
Hao Yu ◽  
Shiyang Yuan ◽  
Wenxiang Li ◽  
...  

Abstract Background DNA methylation is a common epigenetic regulatory way, and it plays a critical role in various human diseases. However, the potential role of how DNA methylation impacts Ewing’s sarcoma (ES) is not clear. This study aimed to explore the regulatory role of DNA methylation in ES. Methods The microarray data of gene expression and methylation were downloaded from Gene Expression Omnibus (GEO) database, and analyzed via GEO2R. Venn analysis was then applied to identify aberrantly methylated differentially expressed genes (DEGs). Subsequently, Function and pathway enrichment analysis was conducted. Protein-protein interaction (PPI) network was constructed. Hub genes were determined. Besides, a connectivity map (CMap) analysis was performed to screen bioactive compounds for ES treatment. Results A total of 135 hypomethylated high expression genes and 523 hypermethylated low expression genes were identified. The hypomethylated high expression genes were enriched in signal transduction and the apoptosis process. Meanwhile, hypermethylated low expression genes were related to DNA replication and transcription regulation. We next determined 10 hub genes through PPI analysis, among them, C3, TF, and TCEB1 might serve as diagnostic and therapeutic targets. Furthermore, CMap analysis revealed 6 chemicals as potential options for ES treatment. Conclusions For the first time, we jointly analyzed gene profiling and methylation data about ES. The introduction of DNA methylation characteristics over DEGs is helpful to understand the pathogenesis of ES. The identified hub aberrantly methylated DEGs and chemicals might provide some novel insights on ES treatment.


2021 ◽  
Author(s):  
Shijie Gao ◽  
Guowang Li ◽  
Hao Yu ◽  
Shiyang Yuan ◽  
Wenxiang Li ◽  
...  

Abstract Background: DNA methylation is a common epigenetic regulatory way, and it plays a critical role in various human diseases. However, the potential role of how DNA methylation impacts Ewing’s sarcoma (ES) is not clear. This study aimed to explore the regulatory role of DNA methylation in ES.Methods: The microarray data of gene expression and methylation were downloaded from Gene Expression Omnibus (GEO) database, and analyzed via GEO2R. Venn analysis was then applied to identify aberrantly methylated differentially expressed genes (DEGs). Subsequently, Function and pathway enrichment analysis was conducted. Protein-protein interaction (PPI) network was constructed. Hub genes were determined. Besides, a connectivity map (CMap) analysis was performed to screen bioactive compounds for ES treatment.Results: A total of 135 hypomethylated high expression genes and 523 hypermethylated low expression genes were identified. The hypomethylated high expression genes were enriched in signal transduction and the apoptosis process. Meanwhile, hypermethylated low expression genes were related to DNA replication and transcription regulation. We next determined 10 hub genes through PPI analysis, among them, C3, TF, and TCEB1 might serve as diagnostic and therapeutic targets. Furthermore, CMap analysis revealed 6 chemicals as potential options for ES treatment. Conclusions: For the first time, we jointly analyzed gene profiling and methylation data about ES. The introduction of DNA methylation characteristics over DEGs is helpful to understand the pathogenesis of ES. The identified hub aberrantly methylated DEGs and chemicals might provide some novel insights on ES treatment.


2019 ◽  
Vol 14 (8) ◽  
pp. 783-792 ◽  
Author(s):  
Yuanyuan Zhang ◽  
Chuanhua Kou ◽  
Shudong Wang ◽  
Yulin Zhang

Background:: DNA methylation is an epigenetic modification that plays an important role in regulating gene expression. There is evidence that the hypermethylation of promoter regions always causes gene silencing. However, how the methylation patterns of other regions in the genome, such as gene body and 3’UTR, affect gene expression is unknown. Objective:: The study aimed to fully explore the relationship between DNA methylation and expression throughout the genome-wide analysis which is important in understanding the function of DNA methylation essentially. Method:: In this paper, we develop a heuristic framework to analyze the relationship between the methylated change in different regions and that of the corresponding gene expression based on differential analysis. Results:: To understande the methylated function of different genomic regions, a gene is divided into seven functional regions. By applying the method in five cancer datasets from the Synapse database, it was found that methylated regions with a significant difference between cases and controls were almost uniformly distributed in the seven regions of the genome. Also, the effect of DNA methylation in different regions on gene expression was different. For example, there was a higher percentage of positive relationships in 1stExon, gene body and 3’UTR than in TSS1500 and TSS200. The functional analysis of genes with a significant positive and negative correlation between DNA methylation and gene expression demonstrated the epigenetic mechanism of cancerassociated genes. Conclusion:: Differential based analysis helps us to recognize the change in DNA methylation and how this change affects the change in gene expression. It provides a basis for further integrating gene expression and DNA methylation data to identify disease-associated biomarkers.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Rowan AlEjielat ◽  
Anas Khaleel ◽  
Amneh H. Tarkhan

Abstract Background Ankylosing spondylitis (AS) is a rare inflammatory disorder affecting the spinal joints. Although we know some of the genetic factors that are associated with the disease, the molecular basis of this illness has not yet been fully elucidated, and the genes involved in AS pathogenesis have not been entirely identified. The current study aimed at constructing a gene network that may serve as an AS gene signature and biomarker, both of which will help in disease diagnosis and the identification of therapeutic targets. Previously published gene expression profiles of 16 AS patients and 16 gender- and age-matched controls that were profiled on the Illumina HumanHT-12 V3.0 Expression BeadChip platform were mined. Patients were Portuguese, 21 to 64 years old, were diagnosed based on the modified New York criteria, and had Bath Ankylosing Spondylitis Disease Activity Index scores > 4 and Bath Ankylosing Spondylitis Functional Index scores > 4. All patients were receiving only NSAIDs and/or sulphasalazine. Functional enrichment and pathway analysis were performed to create an interaction network of differentially expressed genes. Results ITM2A, ICOS, VSIG10L, CD59, TRAC, and CTLA-4 were among the significantly differentially expressed genes in AS, but the most significantly downregulated genes were the HLA-DRB6, HLA-DRB5, HLA-DRB4, HLA-DRB3, HLA-DRB1, HLA-DQB1, ITM2A, and CTLA-4 genes. The genes in this study were mostly associated with the regulation of the immune system processes, parts of cell membrane, and signaling related to T cell receptor and antigen receptor, in addition to some overlaps related to the IL2 STAT signaling, as well as the androgen response. The most significantly over-represented pathways in the data set were associated with the “RUNX1 and FOXP3 which control the development of regulatory T lymphocytes (Tregs)” and the “GABA receptor activation” pathways. Conclusions Comprehensive gene analysis of differentially expressed genes in AS reveals a significant gene network that is involved in a multitude of important immune and inflammatory pathways. These pathways and networks might serve as biomarkers for AS and can potentially help in diagnosing the disease and identifying future targets for treatment.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Hui Li ◽  
Jing-An Chen ◽  
Qian-Zhi Ding ◽  
Guan-Yi Lu ◽  
Ning Wu ◽  
...  

Abstract Background Methamphetamine (METH) is one of the most widely abused illicit substances worldwide; unfortunately, its addiction mechanism remains unclear. Based on accumulating evidence, changes in gene expression and chromatin modifications might be related to the persistent effects of METH on the brain. In the present study, we took advantage of METH-induced behavioral sensitization as an animal model that reflects some aspects of drug addiction and examined the changes in gene expression and histone acetylation in the prefrontal cortex (PFC) of adult rats. Methods We conducted mRNA microarray and chromatin immunoprecipitation (ChIP) coupled to DNA microarray (ChIP-chip) analyses to screen and identify changes in transcript levels and histone acetylation patterns. Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, were performed to analyze the differentially expressed genes. We then further identified alterations in ANP32A (acidic leucine-rich nuclear phosphoprotein-32A) and POU3F2 (POU domain, class 3, transcription factor 2) using qPCR and ChIP-PCR assays. Results In the rat model of METH-induced behavioral sensitization, METH challenge caused 275 differentially expressed genes and a number of hyperacetylated genes (821 genes with H3 acetylation and 10 genes with H4 acetylation). Based on mRNA microarray and GO and KEGG enrichment analyses, 24 genes may be involved in METH-induced behavioral sensitization, and 7 genes were confirmed using qPCR. We further examined the alterations in the levels of the ANP32A and POU3F2 transcripts and histone acetylation at different periods of METH-induced behavioral sensitization. H4 hyperacetylation contributed to the increased levels of ANP32A mRNA and H3/H4 hyperacetylation contributed to the increased levels of POU3F2 mRNA induced by METH challenge-induced behavioral sensitization, but not by acute METH exposure. Conclusions The present results revealed alterations in transcription and histone acetylation in the rat PFC by METH exposure and provided evidence that modifications of histone acetylation contributed to the alterations in gene expression caused by METH-induced behavioral sensitization.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Constantinos G. Broustas ◽  
Axel J. Duval ◽  
Sally A. Amundson

AbstractAs a radiation biodosimetry tool, gene expression profiling is being developed using mouse and human peripheral blood models. The impact of dose, dose-rate, and radiation quality has been studied with the goal of predicting radiological tissue injury. In this study, we determined the impact of aging on the gene expression profile of blood from mice exposed to radiation. Young (2 mo) and old (21 mo) male mice were irradiated with 4 Gy x-rays, total RNA was isolated from whole blood 24 h later, and subjected to whole genome microarray analysis. Pathway analysis of differentially expressed genes revealed young mice responded to x-ray exposure by significantly upregulating pathways involved in apoptosis and phagocytosis, a process that eliminates apoptotic cells and preserves tissue homeostasis. In contrast, the functional annotation of senescence was overrepresented among differentially expressed genes from irradiated old mice without enrichment of phagocytosis pathways. Pathways associated with hematologic malignancies were enriched in irradiated old mice compared with irradiated young mice. The fibroblast growth factor signaling pathway was underrepresented in older mice under basal conditions. Similarly, brain-related functions were underrepresented in unirradiated old mice. Thus, age-dependent gene expression differences should be considered when developing gene signatures for use in radiation biodosimetry.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Kai Yu ◽  
Huan Yang ◽  
Qiao-li Lv ◽  
Li-chong Wang ◽  
Zi-long Tan ◽  
...  

Abstract Background Glioblastoma is the most common primary malignant brain tumor. Because of the limited understanding of its pathogenesis, the prognosis of glioblastoma remains poor. This study was conducted to explore potential competing endogenous RNA (ceRNA) network chains and biomarkers in glioblastoma by performing integrated bioinformatics analysis. Methods Transcriptome expression data from The Cancer Genome Atlas database and Gene Expression Omnibus were analyzed to identify differentially expressed genes between glioblastoma and normal tissues. Biological pathways potentially associated with the differentially expressed genes were explored by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, and a protein-protein interaction network was established using the STRING database and Cytoscape. Survival analysis using Gene Expression Profiling Interactive Analysis was based on the Kaplan–Meier curve method. A ceRNA network chain was established using the intersection method to align data from four databases (miRTarBase, miRcode, TargetScan, and lncBace2.0), and expression differences and correlations were verified by quantitative reverse-transcription polymerase chain reaction analysis and by determining the Pearson correlation coefficient. Additionally, an MTS assay and the wound-healing and transwell assays were performed to evaluate the effects of complement C1s (C1S) on the viability and migration and invasion abilities of glioblastoma cells, respectively. Results We detected 2842 differentially expressed (DE) mRNAs, 2577 DE long non-coding RNAs (lncRNAs), and 309 DE microRNAs (miRNAs) that were dysregulated in glioblastoma. The final ceRNA network consisted of six specific lncRNAs, four miRNAs, and four mRNAs. Among them, four DE mRNAs and one DE lncRNA were correlated with overall survival (p < 0.05). C1S was significantly correlated with overall survival (p= 0.015). In functional assays, knockdown of C1S inhibited the proliferation and invasion of glioblastoma cell lines. Conclusions We established four ceRNA networks that may influence the occurrence and development of glioblastoma. Among them, the MIR155HG/has-miR-129-5p/C1S axis is a potential marker and therapeutic target for glioblastoma. Knockdown of C1S inhibited the proliferation, migration, and invasion of glioblastoma cells. These findings clarify the role of the ceRNA regulatory network in glioblastoma and provide a foundation for further research.


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