scholarly journals Parental variation in CHG methylation is associated with allelic-specific expression in elite hybrid rice

2021 ◽  
Author(s):  
Xuan Ma ◽  
Feng Xing ◽  
Qingxiao Jia ◽  
Qinglu Zhang ◽  
Tong Hu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Hybrid Rice ◽  
Hybrid Vigor ◽  
Superior Performance ◽  
Specific Expression ◽  
Correlation Relationship ◽  
Parental Lines ◽  
Hybrid Lines ◽  
Methylation Variation

Abstract Heterosis refers to the superior performance of hybrid lines over inbred parental lines. Besides genetic variation, epigenetic differences between parental lines are suggested to contribute to heterosis. However, the precise nature and extent of differences between the parental epigenomes and the reprograming in hybrids that governs heterotic gene expression remain unclear. In this work, we analyzed DNA methylomes and transcriptomes of the widely cultivated and genetically studied elite hybrid rice (Oryza sativa) SY63, the reciprocal hybrid, and the parental varieties ZS97 and MH63, for which high-quality reference genomic sequences are available. We showed that the parental varieties displayed substantial variation in genic methylation at CG and CHG (H = A, C, or T) sequences. Compared with their parents, the hybrids displayed dynamic methylation variation during development. However, many parental differentially methylated regions (DMR) at CG and CHG sites were maintained in the hybrid. Only a small fraction of the DMRs displayed non-additive DNA methylation variation which, however, showed no overall correlation relationship with gene expression variation. By contrast, most of the allelic-specific expression (ASE) genes in the hybrid were associated with DNA methylation, and the ASE negatively associated with allelic-specific methylation (ASM) at CHG. These results revealed a specific DNA methylation reprogramming pattern in the hybrid rice and pointed to a role for parental CHG methylation divergence in ASE, which is associated with phenotype variation and hybrid vigor in several plant species.

scholarly journals Parental CG and CHG methylation variation is associated with allelic-specific expression in elite hybrid rice

2020 ◽  
Author(s):  
Xuan Ma ◽  
Feng Xin ◽  
Qingxiao Jia ◽  
Qinglu Zhang ◽  
Tong Hu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Hybrid Rice ◽  
Hybrid Vigor ◽  
Superior Performance ◽  
Specific Expression ◽  
Phenotype Variation ◽  
Important Variation ◽  
Parental Lines ◽  
Methylation Variation

ABSTRACTHeterosis refers to the superior performance of the hybrid over the inbred parental lines. Besides genetic variation, epigenetic difference between the parental lines has been suggested to be involved in heterosis. However, precise nature and extent of parental epigenome difference and reprograming in hybrids governing heterotic gene expression remain unclear. In this work, we analyzed DNA methylomes and transcriptomes of the widely cultivated and genetically studied elite hybrid rice SY63, the reciprocal hybrid, and the parental varieties ZS97 and MH63, of which the high-quality reference genomic sequences are available. We show that the parental varieties display important variation in genic methylation at CG and CHG (H=A, C, or T) sequences. Compared with the parents the hybrids display dynamic methylation variation during development. However, many parental differentially methylated regions (DMR) at CG and CHG sites are maintained in the hybrid. Only a small fraction of the DMRs display non-additive DNA methylation variation which, however, shows no overall correlation with gene expression variation. By contrast, most of the allelic-specific expression (ASE) genes in the hybrid are associated with DNA methylation and the ASE negatively correlates with allelic-specific methylation (ASM) at CHG but positively at CG sites. The results reveal a specific DNA methylation reprogramming pattern in the hybrid rice and point to a role of parental CG and CHG methylation divergence in allelic specific expression that has been associated with phenotype variation and hybrid vigor in several plant species.One sentence summaryParental CG and CHG methylation divergence is maintained in hybrid and is related to allelic specific expression associated with phenotype variation and hybrid vigor.

scholarly journals RNA-Seq Analyses Identify Additivity as the Predominant Gene Expression Pattern in F1 Chicken Embryonic Brain and Liver

Genes ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 27 ◽  
Author(s):  
Zhu Zhuo ◽  
Susan J. Lamont ◽  
Behnam Abasht
Keyword(s):  
Gene Expression ◽  
Expression Pattern ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Pairwise Comparison ◽  
Intermediate Phenotype ◽  
Superior Performance ◽  
Rna Seq ◽  
Specific Expression ◽  
Parental Lines

The superior performance of hybrids to parents, termed heterosis, has been widely utilized in animal and plant breeding programs, but the molecular mechanism underlying heterosis remains an enigma. RNA-Seq provides a novel way to investigate heterosis at the transcriptome-wide level, because gene expression functions as an intermediate phenotype that contributes to observable traits. Here we compared embryonic gene expression between chicken hybrids and their inbred parental lines to identify inheritance patterns of gene expression. Inbred Fayoumi and Leghorn were crossed reciprocally to obtain F1 fertile eggs. RNA-Seq was carried out using 24 brain and liver samples taken from day 12 embryos, and the differentially expressed (DE) genes were identified by pairwise comparison among the hybrids, parental lines, and mid-parent expression values. Our results indicated the expression levels of the majority of the genes in the F1 cross are not significantly different from the mid-parental values, suggesting additivity as the predominant gene expression pattern in the F1. The second and third prevalent gene expression patterns are dominance and over-dominance. Additionally, we found only 7–20% of the DE genes exhibit allele-specific expression in the F1, suggesting that trans regulation is the main driver for differential gene expression and thus contributes to heterosis effect in the F1 crosses.

scholarly journals Predicting gene expression using DNA methylation in three human populations

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6757 ◽  
Author(s):  
Huan Zhong ◽  
Soyeon Kim ◽  
Degui Zhi ◽  
Xiangqin Cui
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Linear Regression ◽  
Human Population ◽  
Penalized Regression ◽  
Superior Performance ◽  
Gene Region ◽  
Human Populations ◽  
Epigenetic Mark ◽  
Lasso Regression

Background DNA methylation, an important epigenetic mark, is well known for its regulatory role in gene expression, especially the negative correlation in the promoter region. However, its correlation with gene expression across genome at human population level has not been well studied. In particular, it is unclear if genome-wide DNA methylation profile of an individual can predict her/his gene expression profile. Previous studies were mostly limited to association analyses between single CpG site methylation and gene expression. It is not known whether DNA methylation of a gene has enough prediction power to serve as a surrogate for gene expression in existing human study cohorts with DNA samples other than RNA samples. Results We examined DNA methylation in the gene region for predicting gene expression across individuals in non-cancer tissues of three human population datasets, adipose tissue of the Multiple Tissue Human Expression Resource Projects (MuTHER), peripheral blood mononuclear cell (PBMC) from Asthma and normal control study participates, and lymphoblastoid cell lines (LCL) from healthy individuals. Three prediction models were investigated, single linear regression, multiple linear regression, and least absolute shrinkage and selection operator (LASSO) penalized regression. Our results showed that LASSO regression has superior performance among these methods. However, the prediction power is generally low and varies across datasets. Only 30 and 42 genes were found to have cross-validation R2 greater than 0.3 in the PBMC and Adipose datasets, respectively. A substantially larger number of genes (258) were identified in the LCL dataset, which was generated from a more homogeneous cell line sample source. We also demonstrated that it gives better prediction power not to exclude any CpG probe due to cross hybridization or SNP effect. Conclusion In our three population analyses DNA methylation of CpG sites at gene region have limited prediction power for gene expression across individuals with linear regression models. The prediction power potentially varies depending on tissue, cell type, and data sources. In our analyses, the combination of LASSO regression and all probes not excluding any probe on the methylation array provides the best prediction for gene expression.

scholarly journals Can Forest Trees Cope with Climate Change?—Effects of DNA Methylation on Gene Expression and Adaptation to Environmental Change

2021 ◽  
Vol 22 (24) ◽  
pp. 13524
Author(s):  
Ewelina A. Klupczyńska ◽  
Ewelina Ratajczak
Keyword(s):  
Climate Change ◽  
Gene Expression ◽  
Dna Methylation ◽  
Global Climate ◽  
Regional Climate ◽  
Expression Patterns ◽  
Forest Tree ◽  
Epigenetic Modifications ◽  
Specific Expression ◽  
Epigenome Editing

Epigenetic modifications, including chromatin modifications and DNA methylation, play key roles in regulating gene expression in both plants and animals. Transmission of epigenetic markers is important for some genes to maintain specific expression patterns and preserve the status quo of the cell. This article provides a review of existing research and the current state of knowledge about DNA methylation in trees in the context of global climate change, along with references to the potential of epigenome editing tools and the possibility of their use for forest tree research. Epigenetic modifications, including DNA methylation, are involved in evolutionary processes, developmental processes, and environmental interactions. Thus, the implications of epigenetics are important for adaptation and phenotypic plasticity because they provide the potential for tree conservation in forest ecosystems exposed to adverse conditions resulting from global warming and regional climate fluctuations.

scholarly journals Role of DNA methylation in hybrid vigor in Arabidopsis thaliana

2016 ◽  
Vol 113 (43) ◽  
pp. E6704-E6711 ◽  
Author(s):  
Takahiro Kawanabe ◽  
Sonoko Ishikura ◽  
Naomi Miyaji ◽  
Taku Sasaki ◽  
Li Min Wu ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Arabidopsis Thaliana ◽  
Production Systems ◽  
Hybrid Vigor ◽  
Superior Performance ◽  
Partial Reduction ◽  
Hybrid Plants ◽  
Rna Polymerase Iv ◽  
Mutant Genes

Hybrid vigor or heterosis refers to the superior performance of F1 hybrid plants over their parents. Heterosis is particularly important in the production systems of major crops. Recent studies have suggested that epigenetic regulation such as DNA methylation is involved in heterosis, but the molecular mechanism of heterosis is still unclear. To address the epigenetic contribution to heterosis in Arabidopsis thaliana, we used mutant genes that have roles in DNA methylation. Hybrids between C24 and Columbia-0 (Col) without RNA polymerase IV (Pol IV) or methyltransferase I (MET1) function did not reduce the level of biomass heterosis (as evaluated by rosette diameter). Hybrids with a mutation in decrease in dna methylation 1 (ddm1) showed a decreased heterosis level. Vegetative heterosis in the ddm1 mutant hybrid was reduced but not eliminated; a complete reduction could result if there was a change in methylation at all loci critical for generating the level of heterosis, whereas if only a proportion of the loci have methylation changes there may only be a partial reduction in heterosis.

scholarly journals Sex-specific expression and DNA methylation in a species with extreme sexual dimorphism and paternal genome elimination

2020 ◽  
Author(s):  
Stevie A. Bain ◽  
Hollie Marshall ◽  
Laura Ross
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Alternative Splicing ◽  
Sexual Dimorphism ◽  
Planococcus Citri ◽  
Specific Gene ◽  
Paternal Genome ◽  
Specific Expression ◽  
Cis Acting ◽  
Genome Wide

AbstractSexual dimorphism is exhibited in many species across the tree of life with many phenotypic differences mediated by differential expression and alternative splicing of genes present in both sexes. However, the mechanisms that regulate these sex-specific expression and splicing patterns remain poorly understood. The mealybug, Planococcus citri, displays extreme sexual dimorphism and exhibits an unusual instance of sex-specific genomic imprinting, Paternal Genome Elimination (PGE), in which the paternal chromosomes in males are highly condensed and eliminated from the sperm. P. citri also has no sex chromosomes and as such both sexual dimorphism and PGE are predicted to be under epigenetic control. We recently showed that P. citri females display a highly unusual DNA methylation profile for an insect species, with the presence of promoter methylation associated with lower levels of gene expression. In this study we therefore decided to explore genome-wide differences in DNA methylation between male and female P. citri using whole genome bisulfite sequencing. We have identified extreme differences in genome-wide levels and patterns between the sexes. Males display overall higher levels of DNA methylation which manifests as more uniform low-levels across the genome. Whereas females display more targeted high levels of methylation. We suggest these unique sex-specific differences are due to chromosomal differences caused by PGE and may be linked to possible ploidy compensation. Using RNA-Seq we identified extensive sex-specific gene expression and alternative splicing. We found cis-acting DNA methylation is not directly associated with differentially expressed or differentially spliced genes, indicating a broader role for chromosome-wide trans-acting DNA methylation in this species.

scholarly journals A Novel Biomarker Identification Approach for Gastric Cancer Using Gene Expression and DNA Methylation Dataset

2021 ◽  
Vol 12 ◽  
Author(s):  
Ge Zhang ◽  
Zijing Xue ◽  
Chaokun Yan ◽  
Jianlin Wang ◽  
Huimin Luo
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Dna Methylation ◽  
Feature Selection ◽  
Gene Expression Data ◽  
Complex Disease ◽  
Biological Data ◽  
Computational Method ◽  
Superior Performance ◽  
Expression Data

As one type of complex disease, gastric cancer has high mortality rate, and there are few effective treatments for patients in advanced stage. With the development of biological technology, a large amount of multiple-omics data of gastric cancer are generated, which enables computational method to discover potential biomarkers of gastric cancer. That will be very important to detect gastric cancer at earlier stages and thus assist in providing timely treatment. However, most of biological data have the characteristics of high dimension and low sample size. It is hard to process directly without feature selection. Besides, only using some omic data, such as gene expression data, provides limited evidence to investigate gastric cancer associated biomarkers. In this research, gene expression data and DNA methylation data are integrated to analyze gastric cancer, and a feature selection approach is proposed to identify the possible biomarkers of gastric cancer. After the original data are pre-processed, the mutual information (MI) is applied to select some top genes. Then, fold change (FC) and T-test are adopted to identify differentially expressed genes (DEG). In particular, false discover rate (FDR) is introduced to revise p_value to further screen genes. For chosen genes, a deep neural network (DNN) model is utilized as the classifier to measure the quality of classification. The experimental results show that the approach can achieve superior performance in terms of accuracy and other metrics. Biological analysis for chosen genes further validates the effectiveness of the approach.

scholarly journals Predicting gene expression using DNA methylation in two human populations

2018 ◽  
Author(s):  
Huan Zhong ◽  
Soyeon Kim ◽  
Degui Zhi ◽  
Xiangqin Cui
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Linear Regression ◽  
Penalized Regression ◽  
Superior Performance ◽  
Gene Region ◽  
Human Populations ◽  
Epigenetic Mark ◽  
Lasso Regression ◽  
Cpg Sites

Background. DNA methylation, an important epigenetic mark, is well known for its regulatory role in gene expression, especially the negative regulation in the promoter region. However, its correlation with gene expression at population level has not been well studied. In particular, it is unclear if genome-wide DNA methylation profile of an individual can predict her/his gene expression profile. Previous studies were mostly limited to association analyses between single CpG site methylation and gene expression. It is not known whether DNA methylation of a gene has enough prediction power to serve as a surrogate for gene expression in existing human study cohorts with DNA samples but not RNA samples. Results. We studied two human population datasets, Multiple Tissue Human Expression Resource Projects (MuTHER)’s Adipose tissue as well as asthma and normal peoples’ peripheral blood mononuclear cell (PBMC), for predicting gene expression using methylation of all CpG sites from the gene region. Three prediction models were investigated; single linear regression, multiple linear regression, and least absolute shrinkage and selection operator (LASSO) penalized regression. Our results showed that LASSO regression has superior performance among these methods. However, even with LASSO regression, very small prediction R2 was obtained for the majority of genes and only about one thousand genes had prediction R2 greater than 0.1. GO term and pathway analyses of these more predictable genes showed that they are enriched for immune and defense genes. Conclusion. In human populations, DNA methylation of CpG sites at gene region have weak prediction power for gene expression. The relatively more predictable genes tend to be defense and immune genes.

scholarly journals CG methylation covaries with differential gene expression between leaf and floral bud tissues of Brachypodium distachyon

2015 ◽  
Author(s):  
Kyria Roessler ◽  
Shohei Takuno ◽  
Brandon Gaut
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Sequence Data ◽  
Brachypodium Distachyon ◽  
Grass Species ◽  
Specific Gene ◽  
Specific Expression ◽  
Tissue Specific ◽  
Model Grass ◽  
Floral Bud

DNA methylation has the potential to influence plant growth and development through its influence on gene expression. To date, however, the evidence from plant systems is mixed as to whether patterns of DNA methylation vary significantly among tissues and, if so, whether these differences affect tissue-specific gene expression. To address these questions, we analyzed both bisulfite sequence (BSseq) and transcriptomic sequence data from three biological replicates of two tissues (leaf and floral bud) from the model grass species Brachypodium distachyon. Our first goal was to determine whether tissues were more differentiated in DNA methylation than explained by variation among biological replicates. Tissues were more differentiated than biological replicates, but the analysis of replicated data revealed high (>50%) false positive rates for the inference of differentially methylated sites (DMSs) and differentially methylated regions (DMRs). Comparing methylation to gene expression, we found that differential CG methylation consistently covaried negatively with gene expression, regardless as to whether methylation was within genes, within their promoters or even within their closest transposable element. The relationship between gene expression and either CHG or CHH methylation was less consistent. In total, CG methylation in promoters explained 9% of the variation in tissue-specific expression across genes, suggesting that CG methylation is a minor but appreciable factor in tissue differentiation.

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