scholarly journals D-GPM: a deep learning method for gene promoter methylation inference

2018 ◽  
Author(s):  
Xingxin Pan ◽  
Biao Liu ◽  
Xingzhao Wen ◽  
Yulu Liu ◽  
Xiuqing Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Deep Learning ◽  
Promoter Methylation ◽  
Methylation Level ◽  
Target Genes ◽  
Gene Promoter ◽  
Support Vector ◽  
Whole Genome ◽  
Expression Levels ◽  
Gene Expression Levels

AbstractBackgroundGene promoter methylation plays a critical role in a wide range of biological processes, such as transcriptional expression, gene imprinting, X chromosome inactivation,etc. Whole-genome bisulfite sequencing generates a comprehensive profiling of the gene methylation levels but is limited by a high cost. Recent studies have partitioned the genes into landmark genes and target genes and suggested that the landmark gene expression levels capture adequate information to reconstruct the target gene expression levels. Moreover, the methylation level of the promoter is usually negatively correlated with its corresponding gene expression. This result inspired us to propose that the methylation level of the promoters might be adequate to reconstruct the promoter methylation level of target genes, which would eventually reduce the cost of promoter methylation profiling.ResultsHere, we developed a deep learning model (D-GPM) to predict the whole-genome promoter methylation level based on the methylation profile of the landmark genes. We benchmarked D-GPM against three machine learning methods, namely, linear regression (LR), regression tree (RT) and support vector machine (SVM), based on two criteria: the mean absolute deviation (MAE) and the Pearson correlation coefficient (PCC). After profiling the methylation beta value (MBV) dataset from the TCGA, with respect to MAE and PCC, we found that D-GPM outperforms LR by 9.59% and 4.34%, RT by 27.58% and 22.96% and SVM by 6.14% and 3.07% on average, respectively. For the number of better-predicted genes, D-GPM outperforms LR in 92.65% and 91.00%, RT in 95.66% and 98.25% and SVM in 85.49% and 81.56% of the target genes.ConclusionsD-GPM acquires the least overall MAE and the highest overall PCC on MBV-te compared to LR, RT, and SVM. For a genewise comparative analysis, D-GPM outperforms LR, RT, and SVM in an overwhelming majority of the target genes, with respect to the MAE and PCC. Most importantly, D-GPM predominates among the other models in predicting a majority of the target genes according to the model distribution of the least MAE and the highest PCC for the target genes.

scholarly journals D-GPM: A Deep Learning Method for Gene Promoter Methylation Inference

Genes ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 807 ◽  
Author(s):  
Pan ◽  
Liu ◽  
Wen ◽  
Liu ◽  
Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Deep Learning ◽  
Promoter Methylation ◽  
Methylation Level ◽  
Target Genes ◽  
Gene Promoter ◽  
Support Vector ◽  
Whole Genome ◽  
Expression Levels ◽  
Gene Expression Levels

Whole-genome bisulfite sequencing generates a comprehensive profiling of the gene methylation levels, but is limited by a high cost. Recent studies have partitioned the genes into landmark genes and target genes and suggested that the landmark gene expression levels capture adequate information to reconstruct the target gene expression levels. This inspired us to propose that the methylation level of the promoters in landmark genes might be adequate to reconstruct the promoter methylation level of target genes, which would eventually reduce the cost of promoter methylation profiling. Here, we propose a deep learning model called Deep-Gene Promoter Methylation (D-GPM) to predict the whole-genome promoter methylation level based on the promoter methylation profile of the landmark genes from The Cancer Genome Atlas (TCGA). D-GPM-15%-7000 × 5, the optimal architecture of D-GPM, acquires the least overall mean absolute error (MAE) and the highest overall Pearson correlation coefficient (PCC), with values of 0.0329 and 0.8186, respectively, when testing data. Additionally, the D-GPM outperforms the regression tree (RT), linear regression (LR), and the support vector machine (SVM) in 95.66%, 92.65%, and 85.49% of the target genes by virtue of its relatively lower MAE and in 98.25%, 91.00%, and 81.56% of the target genes based on its relatively higher PCC, respectively. More importantly, the D-GPM predominates in predicting 79.86% and 78.34% of the target genes according to the model distribution of the least MAE and the highest PCC, respectively.

ATF4, DLX3, FRA1, MSX2, C/EBP-ζ, and C/EBP-α Shape the Molecular Basis of Therapeutic Effects of Zoledronic Acid in Bone Disorders

2020 ◽  
Vol 20 (18) ◽  
pp. 2274-2284
Author(s):  
Faroogh Marofi ◽  
Jalal Choupani ◽  
Saeed Solali ◽  
Ghasem Vahedi ◽  
Ali Hassanzadeh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Zoledronic Acid ◽  
Mrna Expression ◽  
Promoter Methylation ◽  
Methylation Level ◽  
Target Genes ◽  
Osteoblastic Differentiation ◽  
Therapeutic Effects ◽  
Significant Difference ◽  
Scheduled Time

Objective: Zoledronic Acid (ZA) is one of the common treatment choices used in various boneassociated conditions. Also, many studies have investigated the effect of ZA on Osteoblastic-Differentiation (OSD) of Mesenchymal Stem Cells (MSCs), but its clear molecular mechanism(s) has remained to be understood. It seems that the methylation of the promoter region of key genes might be an important factor involved in the regulation of genes responsible for OSD. The present study aimed to evaluate the changes in the mRNA expression and promoter methylation of central Transcription Factors (TFs) during OSD of MSCs under treatment with ZA. Materials and Methods: MSCs were induced to be differentiated into the osteoblastic cell lineage using routine protocols. MSCs received ZA during OSD and then the methylation and mRNA expression levels of target genes were measured by Methylation Specific-quantitative Polymerase Chain Reaction (MS-qPCR) and real.time PCR, respectively. The osteoblastic differentiation was confirmed by Alizarin Red Staining and the related markers to this stage. Results: Gene expression and promoter methylation level for DLX3, FRA1, ATF4, MSX2, C/EBPζ, and C/EBPa were up or down-regulated in both ZA-treated and untreated cells during the osteodifferentiation process on days 0 to 21. ATF4, DLX3, and FRA1 genes were significantly up-regulated during the OSD processes, while the result for MSX2, C/EBPζ, and C/EBPa was reverse. On the other hand, ATF4 and DLX3 methylation levels gradually reduced in both ZA-treated and untreated cells during the osteodifferentiation process on days 0 to 21, while the pattern was increasing for MSX2 and C/EBPa. The methylation pattern of C/EBPζ was upward in untreated groups while it had a downward pattern in ZA-treated groups at the same scheduled time. The result for FRA1 was not significant in both groups at the same scheduled time (days 0-21). Conclusion: The results indicated that promoter-hypomethylation of ATF4, DLX3, and FRA1 genes might be one of the mechanism(s) controlling their gene expression. Moreover, we found that promoter-hypermethylation led to the down-regulation of MSX2, C/EBP-ζ and C/EBP-α. The results implicate that ATF4, DLX3 and FRA1 may act as inducers of OSD while MSX2, C/EBP-ζ and C/EBP-α could act as the inhibitor ones. We also determined that promoter-methylation is an important process in the regulation of OSD. However, yet there was no significant difference in the promoter-methylation level of selected TFs in ZA-treated and control cells, a methylation- independent pathway might be involved in the regulation of target genes during OSD of MSCs.

Identification of reference genes for gene expression studies during seed germination and seedling establishment in Ricinus communis L.

2014 ◽  
Vol 24 (4) ◽  
pp. 341-352 ◽  
Author(s):  
Paulo R. Ribeiro ◽  
Bas J. W. Dekkers ◽  
Luzimar G. Fernandez ◽  
Renato D. de Castro ◽  
Wilco Ligterink ◽  
...  
Keyword(s):  
Gene Expression ◽  
Seed Germination ◽  
Reference Genes ◽  
Target Genes ◽  
Ricinus Communis ◽  
Quantitative Polymerase Chain Reaction ◽  
Optimal Combination ◽  
Expression Levels ◽  
Gene Expression Studies ◽  
Gene Expression Levels

AbstractReverse transcription-quantitative polymerase chain reaction (RT-qPCR) is an important technology to analyse gene expression levels during plant development or in response to different treatments. An important requirement to measure gene expression levels accurately is a properly validated set of reference genes. In this context, we analysed the potential use of 17 candidate reference genes across a diverse set of samples, including several tissues, different stages and environmental conditions, encompassing seed germination and seedling growth in Ricinus communis L. These genes were tested by RT-qPCR and ranked according to the stability of their expression using two different approaches: GeNorm and NormFinder. GeNorm and Normfinder indicated that ACT, POB and PP2AA1 comprise the optimal combination for normalization of gene expression data in inter-tissue (heterogeneous sample panel) studies. We also describe the optimal combination of reference genes for a subset of root, endosperm and cotyledon samples. In general, the most stable genes suggested by GeNorm are very consistent with those indicated by NormFinder, which highlights the strength of the selection of reference genes in our study. We also validated the selected reference genes by normalizing the expression levels of three target genes involved in energy metabolism with the reference genes suggested by GeNorm and NormFinder. The approach used in this study to identify stably expressed genes, and thus potential reference genes, was applied successfully for R. communis and it provides important guidelines for RT-qPCR studies in seeds and seedlings for other species (especially in those cases where extensive microarray data are not available).

scholarly journals Discovering genetic polymorphism associated with gene expression levels across the whole genome

2009 ◽  
Author(s):  
A. Antoniades ◽  
I. Kalvari ◽  
C. Pattichis ◽  
N. Jones ◽  
P.M. Matthews ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Polymorphism ◽  
Whole Genome ◽  
Expression Levels ◽  
Gene Expression Levels

scholarly journals Effectiveness of orally-delivered double-stranded RNA on gene silencing in the stinkbug Plautia stali

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245081
Author(s):  
Yudai Nishide ◽  
Daisuke Kageyama ◽  
Yoshiaki Tanaka ◽  
Kakeru Yokoi ◽  
Akiya Jouraku ◽  
...  
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Insect Pest ◽  
Crop Protection ◽  
High Sensitivity ◽  
Double Stranded Rna ◽  
Expression Levels ◽  
Rnai Efficiency ◽  
Plautia Stali ◽  
Gene Expression Levels

Development of a reliable method for RNA interference (RNAi) by orally-delivered double-stranded RNA (dsRNA) is potentially promising for crop protection. Considering that RNAi efficiency considerably varies among different insect species, it is important to seek for the practical conditions under which dsRNA-mediated RNAi effectively works against each pest insect. Here we investigated RNAi efficiency in the brown-winged green stinkbug Plautia stali, which is notorious for infesting various fruits and crop plants. Microinjection of dsRNA into P. stali revealed high RNAi efficiency–injection of only 30 ng dsRNA into last-instar nymphs was sufficient to knockdown target genes as manifested by their phenotypes, and injection of 300 ng dsRNA suppressed the gene expression levels by 80% to 99.9%. Knockdown experiments by dsRNA injection showed that multicopper oxidase 2 (MCO2), vacuolar ATPase (vATPase), inhibitor of apoptosis (IAP), and vacuolar-sorting protein Snf7 are essential for survival of P. stali, as has been demonstrated in other insects. By contrast, P. stali exhibited very low RNAi efficiency when dsRNA was orally administered. When 1000 ng/μL of dsRNA solution was orally provided to first-instar nymphs, no obvious phenotypes were observed. Consistent with this, RT-qPCR showed that the gene expression levels were not affected. A higher concentration of dsRNA (5000 ng/μL) induced mortality in some cohorts, and the gene expression levels were reduced to nearly 50%. Simultaneous oral administration of dsRNA against potential RNAi blocker genes did not improve the RNAi efficiency of the target genes. In conclusion, P. stali shows high sensitivity to RNAi with injected dsRNA but, unlike the allied pest stinkbugs Halyomorpha halys and Nezara viridula, very low sensitivity to RNAi with orally-delivered dsRNA, which highlights the varied sensitivity to RNAi across different species and limits the applicability of the molecular tool for controlling this specific insect pest.

scholarly journals Correlation between miRNA-targeted-gene promoter methylation and miRNA regulation of target genes

F1000Research ◽  
2013 ◽  
Vol 2 ◽  
pp. 21 ◽  
Author(s):  
Y-h Taguchi
Keyword(s):  
Gene Expression ◽  
Promoter Methylation ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Gene Promoter ◽  
Gene Expression Omnibus ◽  
Seed Region ◽  
Mirna Regulation ◽  
Regulate Gene Expression ◽  
Mirna Targeting

Background miRNA regulation of target genes and promoter methylation are known to be the primary mechanisms underlying the epigenetic regulation of gene expression. However, how these two processes cooperatively regulate gene expression has not been extensively studied.Methods Gene expression and promoter methylation profiles of 270 distinct human cell lines were obtained from Gene Expression Omnibus. P-values that describe both miRNA-targeted-gene promoter methylation and miRNA regulation of target genes were computed using the MiRaGE method proposed recently by the author.Results Significant changes in promoter methylation were associated with miRNA targeting. It was also found that miRNA-targeted-gene promoter hypomethylation was related to differential target gene expression; the genes with miRNA-targeted-gene promoter hypomethylation were downregulated during cell senescence and upregulated during cellular differentiation. Promoter hypomethylation was especially enhanced for genes targeted by miR-548 miRNAs, which are non-conserved, primate-specific miRNAs that are typically expressed at lower levels than the frequently investigated conserved miRNAs. miRNA-targeted-gene promoter methylation may also be related to the seed region features of miRNA.Conclusions It was found that promoter methylation was correlated to miRNA targeting. Furthermore, miRNA-targeted-gene promoter hypomethylation was especially enhanced in promoters of genes targeted by miRNAs that are not strongly expressed (e.g., miR-548 miRNAs) and was suggested to be highly related to some seed region features of miRNAs.

scholarly journals Transcriptome and Small RNA Combined Sequencing Analysis of Cold Tolerance in Non-heading Chinese Cabbage

2021 ◽  
Vol 12 ◽  
Author(s):  
Jin Wang ◽  
Qinxue Zhang ◽  
Xiong You ◽  
Xilin Hou
Keyword(s):  
Gene Expression ◽  
Brassica Rapa ◽  
Small Rna ◽  
Target Genes ◽  
Differentially Expressed ◽  
Sequencing Analysis ◽  
Pak Choi ◽  
Expression Levels ◽  
Heading Chinese Cabbage ◽  
Gene Expression Levels

BackgroundNon-heading Chinese cabbage (Brassica rapa ssp. chinensis) is an important leaf vegetable grown worldwide. However, there has currently been not enough transcriptome and small RNA combined sequencing analysis of cold tolerance, which hinders further functional genomics research.ResultsIn this study, 63.43 Gb of clean data was obtained from the transcriptome analysis. The clean data of each sample reached 6.99 Gb, and the basic percentage of Q30 was 93.68% and above. The clean reads of each sample were sequence aligned with the designated reference genome (Brassica rapa, IVFCAASv1), and the efficiency of the alignment varied from 81.54 to 87.24%. According to the comparison results, 1,860 new genes were discovered in Pak-choi, of which 1,613 were functionally annotated. Among them, 13 common differentially expressed genes were detected in all materials, including seven upregulated and six downregulated. At the same time, we used quantitative real-time PCR to confirm the changes of these gene expression levels. In addition, we sequenced miRNA of the same material. Our findings revealed a total of 34,182,333 small RNA reads, 88,604,604 kinds of small RNAs, among which the most common size was 24 nt. In all materials, the number of common differential miRNAs is eight. According to the corresponding relationship between miRNA and its target genes, we carried out Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis on the set of target genes on each group of differentially expressed miRNAs. Through the analysis, it is found that the distributions of candidate target genes in different materials are different. We not only used transcriptome sequencing and small RNA sequencing but also used experiments to prove the expression levels of differentially expressed genes that were obtained by sequencing. Sequencing combined with experiments proved the mechanism of some differential gene expression levels after low-temperature treatment.ConclusionIn all, this study provides a resource for genetic and genomic research under abiotic stress in Pak-choi.

scholarly journals Impact of RNA degradation on measurements of gene expression

2014 ◽  
Author(s):  
Irene Gallego Romero ◽  
Athma A. Pai ◽  
Jenny Tung ◽  
Yoav Gilad
Keyword(s):  
Gene Expression ◽  
Expression Profiling ◽  
Rna Extraction ◽  
Rna Degradation ◽  
Significant Loss ◽  
Whole Genome ◽  
Expression Levels ◽  
Rna Quality ◽  
The Impact ◽  
Gene Expression Levels

The use of low quality RNA samples in whole-genome gene expression profiling remains controversial. It is unclear if transcript degradation in low quality RNA samples occurs uniformly, in which case the effects of degradation can be normalized, or whether different transcripts are degraded at different rates, potentially biasing measurements of expression levels. This concern has rendered the use of low quality RNA samples in whole-genome expression profiling problematic. Yet, low quality samples are at times the sole means of addressing specific questions – e.g., samples collected in the course of fieldwork. We sought to quantify the impact of variation in RNA quality on estimates of gene expression levels based on RNA-seq data. To do so, we collected expression data from tissue samples that were allowed to decay for varying amounts of time prior to RNA extraction. The RNA samples we collected spanned the entire range of RNA Integrity Number (RIN) values (a quality metric commonly used to assess RNA quality). We observed widespread effects of RNA quality on measurements of gene expression levels, as well as a slight but significant loss of library complexity in more degraded samples. While standard normalizations failed to account for the effects of degradation, we found that a simple linear model that controls for the effects of RIN can correct for the majority of these effects. We conclude that in instances where RIN and the effect of interest are not associated, this approach can help recover biologically meaningful signals in data from degraded RNA samples.

scholarly journals Gene Expression and Photophysiological Changes in Pocillopora acuta Coral Holobiont Following Heat Stress and Recovery

2020 ◽  
Vol 8 (8) ◽  
pp. 1227
Author(s):  
Rosa Celia Poquita-Du ◽  
Yi Le Goh ◽  
Danwei Huang ◽  
Loke Ming Chou ◽  
Peter A. Todd
Keyword(s):  
Gene Expression ◽  
Heat Stress ◽  
Target Genes ◽  
Differential Expression Analysis ◽  
Heat Exposure ◽  
Small Heat Shock Protein ◽  
Expression Levels ◽  
Chl A ◽  
Coral Holobiont ◽  
Gene Expression Levels

The ability of corals to withstand changes in their surroundings is a critical survival mechanism for coping with environmental stress. While many studies have examined responses of the coral holobiont to stressful conditions, its capacity to reverse responses and recover when the stressor is removed is not well-understood. In this study, we investigated among-colony responses of Pocillopora acuta from two sites with differing distance to the mainland (Kusu (closer to the mainland) and Raffles Lighthouse (further from the mainland)) to heat stress through differential expression analysis of target genes and quantification of photophysiological metrics. We then examined how these attributes were regulated after the stressor was removed to assess the recovery potential of P. acuta. The fragments that were subjected to heat stress (2 °C above ambient levels) generally exhibited significant reduction in their endosymbiont densities, but the extent of recovery following stress removal varied depending on natal site and colony. There were minimal changes in chl a concentration and maximum quantum yield (Fv/Fm, the proportion of variable fluorescence (Fv) to maximum fluorescence (Fm)) in heat-stressed corals, suggesting that the algal endosymbionts’ Photosystem II was not severely compromised. Significant changes in gene expression levels of selected genes of interest (GOI) were observed following heat exposure and stress removal among sites and colonies, including Actin, calcium/calmodulin-dependent protein kinase type IV (Camk4), kinesin-like protein (KIF9), and small heat shock protein 16.1 (Hsp16.1). The most responsive GOIs were Actin, a major component of the cytoskeleton, and the adaptive immune-related Camk4 which both showed significant reduction following heat exposure and subsequent upregulation during the recovery phase. Our findings clearly demonstrate specific responses of P. acuta in both photophysiological attributes and gene expression levels, suggesting differential capacity of P. acuta corals to tolerate heat stress depending on the colony, so that certain colonies may be more resilient than others.

Genetic and epigenetic MTHFR gene variants in the mothers of attention-deficit/hyperactivity disorder affected children as possible risk factors for neurodevelopmental disorders

Epigenomics ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 813-823
Author(s):  
Ignazio Stefano Piras ◽  
Anna Costa ◽  
Maria Cristina Tirindelli ◽  
Andrea Stoccoro ◽  
Matthew J Huentelman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Attention Deficit Hyperactivity Disorder ◽  
Attention Deficit ◽  
Promoter Methylation ◽  
Mthfr Gene ◽  
Expression Levels ◽  
Hyperactivity Disorder ◽  
Genotype Frequencies ◽  
Healthy Control ◽  
Gene Expression Levels

Aim: To assess promoter methylation levels, gene expression levels and 677C>T/1298A>C genotype and allele frequencies of the MTHFR gene in 45 mothers of attention-deficit/hyperactivity disorder affected child/children (ADHDM) and compare it with age matched healthy control mothers (HCM). Materials & methods: High resolution melting analysis, quantitative real time PCR and PCR-RFLP were performed to assess methylation, gene expression and genotyping, respectively. Significance between ADHDM and HCM was assessed by linear (methylation and gene expression) and logistic regression (genotypes). Results: MTHFR gene expression levels were significantly higher in the ADHDM compared with the HCM group (adj-p < 7.7E-04). No differences in MTHFR promoter methylation level and 677C>T/1298A>C genotype frequencies were detected between ADHDM and HCM. Conclusion: We observed increased MTHFR expression levels not resulting from promoter methylation changes in ADHDM respect to HMC, potentially contributing to the ADHD condition in their children and deserving further investigation.

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