Integrated Analysis of DNA Methylation and Transcriptome

Fundamental cellular regulatory processes include gene expression and DNA methylation. DNA methylation is an epigenetic alteration that alters gene expression patterns by adding methyl groups to the cytosine residues of CpG dinucleotides. Transcriptome analysis offers significant details about the mRNA molecules present in the cell and reflect the pattern of gene expression. Epigenetic changes affect gene expression can be discovered by combining transcriptome and DNA methylation data. By combining DNA methylation and transcriptome analysis, new biological insights can be revealed, potential diagnostic biomarkers and therapeutic targets for a range of diseases can be found, and patient outcomes can be improved through personalized medicine.

Creative Proteomics has rich experience in multi-omics integration analysis. Based on our advanced multi-omics technology platform and strong team of experts, we aim to provide one-stop DNA methylation and transcriptome integration analysis services. Currently, our integrated DNA methylation and transcriptome analysis services have been widely used in biomedical research, agricultural crop improvement and other research fields.

Integration of DNA methylation and mRNA transcriptome profiles. (Wang M, et al. 2023)

What do we offer?

• Data Collection and Pre-processing. Large-scale datasets can be obtained from publicly accessible repositories like the Sequence Read Archive (SRA) or the Gene Expression Omnibus (GEO) in order to do an integrated study of DNA methylation and transcriptome data. To reduce experimental biases and ensure data dependability, the data is subjected to thorough pre-processing after acquisition, including quality control, normalization, and batch correction. These pre-processing processes involve the use of bioinformatics tools like Bismark and HISAT2.
• Differential Methylation Analysis. Next, differential methylation analysis identifies regions in the genome where DNA methylation patterns vary between different experimental conditions or cell types. Tools like MethylKit or DSS can detect these differently methylated regions (DMRs). DMRs are essential for understanding how DNA methylation changes impact gene expression levels.
• Differential Expression Analysis. Transcriptome data are analyzed using DESeq2 or edgeR. This step identifies genes with significantly altered expression levels between experimental conditions, offering insights into regulatory changes in gene expression.

Integration of DNA methylation and transcriptome data

• Identifying correlations. Finding connections between DNA methylation patterns and levels of gene expression is a requirement for the integration of transcriptome and DNA methylation data. Genes with differentially methylated promoter regions frequently experience corresponding alterations in gene expression.
• Pathway evaluation. Following the discovery of strong correlations, pathway analysis is carried out to find enriched biological pathways or Gene Ontology (GO) concepts linked to the differentially expressed and methylated genes.

Our service workflow

Advantages of our service

• We use both WGBS and transcriptomic technological tools to effectively apply to the study of the regulatory effects of methylation.
• We use various schemes such as modification trend curves, Venn diagrams, quadrant diagrams, etc. When integrating the results of DNA methylation and transcriptomics.
• We use enrichment analysis for functional interpretation, which enriches the results and makes them more consistent with real biological regulatory mechanisms.
• Combined with our professional bioinformatics services, we help our clients perform in-depth data integration and analysis to enhance the reliability of analysis results.

Creative Proteomics provides DNA Methylation and Transcriptome Integration Analysis services have helped to complete several life science research projects, greatly advancing the progress of life science research. If you are interested in us, please feel free to contact us.

Reference

1. Wang M, Bissonnette N, Laterrière M, et al,. Genome-Wide DNA Methylation and Transcriptome Integration Associates DNA Methylation Changes with Bovine Subclinical Mastitis Caused by Staphylococcus chromogenes. Int J Mol Sci. 2023 Jun 20;24(12):10369.

Integrated analysis of DNA methylation, transcriptome, and global metabolites in interspecific heterotic Capsicum F 1 hybrid

Journal: iScience

Published: 2022

Abstract

Hybrid breeding is one of the most effective methods for crop improvement. In this article, the authors integrate DNA methylation and transcriptomic data to report work on the molecular basis of F 1 hybrid dominance. This is in the cross between Capsicum and C. frutescens. The authors first identified a total of 70,597 CGs, 108,797 CHGs, and 38,418 CHH differentially methylated regions (DMRs) in the F 1 hybrids and parents by sequencing, of which 4,891 DMRs displayed higher methylation than the mid-parental methylation value (MPMV) in the F 1. Subsequent transcriptome analysis showed that 46-55% of the differentially expressed genes (DE-Gs) were more highly expressed in the F 1 heterozygotes. Combining methylation and transcriptome data, qRT-PCR analysis of 24 DE-Gs with negative promoter methylation revealed 91.66% expression similarity to transcriptome data. A number of metabolites and 65-72% enriched genes in metabolite biosynthesis pathways showed an overall increase in expression in the F 1 heterozygote compared to the parent. Combined with the results of the above analyses, the authors provide insights into the combined roles of DNA methylation, gene and metabolite expression in the expression of hybrid dominance in pepper.

Results

The authors found that the genome-wide dynamics of cytosine methylation in the CG, CHG and CHH environments differed between the parental lines and their hybrids by methylation analysis. Choco showed the highest overall methylation in all three environments relative to Hybrid and Frut4. Compared to the parental Frut4, the hybrid showed higher global average methylation in the CG and CHG environments and lower methylation in the CHH environment (Fig. 1A). In a given case, the proportions of mCs observed at CG, CHG, and CHH were approximately 22.5-24.9%, 31.7-34.9%, and 40-45.7%, respectively, across the three genotypes. Notably, the hybrid had a greater proportion of mCs in symmetric (CG, CHG) environments than its parents, while it had a reduced proportion of mCs in asymmetric (CHH) environments. Segmentation of average chromosome methylation showed that methylation was higher in the symmetric CG and CHG contexts than in the asymmetric context. This was on all 12 chromosomes of all three genotypes. In addition, on segments of chromosomes (chr) chr2 to chr5, chr7 and chr11, both hybrid and Frut4 displayed slightly higher methylation than Choco. However, the same chromosomes in the hybrid showed a slight decrease in methylation compared to Frut4 (Fig. 1).

Figure 1

The authors identified more than 100 metabolites using GC-MS analysis, of which 71 were found in the parents alone, and used the hybrids for further analysis. By analyzing the overall changes in metabolic content between the parents and their hybrids, the authors found that the most commonly altered metabolites in the hybrids were amino acids and their derivatives, as well as the carboxylic acid and sugar derivative groups (Fig. 2).

Figure 2

Conclusion

In this study, the inheritance pattern of DNA methylation markers from parents to hybrids was determined. Several regions in the hybrids were hyper/hypermethylated with significant MPMV compared to the parental genotypes. Expression dynamics and overall metabolite analyses indicated the potential role of crosstalk among the three components (methylation, gene expression, and metabolites) in the development of early hybrid dominance in pepper F 1 hybrids. Gene expression analysis revealed large amounts of DE-G in the heterozygote, which was negatively correlated with promoter methylation. In addition, the authors showed by metabolite analysis that the expression of metabolites such as glycine, carboxylic acids, D-fructose, D-glucitol, sucrose, D-furanose, and L-threonine was significantly higher in the hybrids. The metabolites of the glyoxylate and dicarboxylic acid metabolic pathways were significantly enriched in the F 1 hybrids and parental lines, as well as in DE-G. The total number of metabolites in this pathway in F 1 hybrids and parental lines was 65%. In total, 65-72% of the enriched genes in this pathway showed an overall increase in expression in F 1 (of which 32.6% were promoter methylated below MPMV) mixed than the mid- genetic values. In conclusion, in the present article, the authors combine DNA methylation and transcriptome integration analyses. This provides insights into the plausible integrative roles of DNA methylation, gene and metabolite expression in early hybrid dominance in pepper hybrids.

Reference

1. Jaiswal V, Rawoof A, Gahlaut V, et al. Integrated analysis of DNA methylation, transcriptome, and global metabolites in interspecific heterotic Capsicum F 1 hybrid. iScience. 2022;25 (11):105318.