Project description:Chicken growth traits are important in poultry production, however, little is known for its regulatory mechanism at epigenetic level. Therefore, this study aims to compare DNA methylation profiles between fast- and slow-growing broilers in order to identify candidate genes underlying chicken growth. Methylated DNA immunoprecipitation-sequencing (MeDIP-seq) was used to investigate the genome-wide DNA methylation pattern in high and low tails of Recessive White Rock (WRRh, WRRl) and that of Xinhua Chickens (XHh, XHl). The results showed that the average of methylation density was the lowest in CGIs followed by promoters. Within the gene body, the methylation density of introns was higher than UTRs and exons. Moreover, different methylation levels were observed in different repeat types with the highest in LINE/CR1. Methylated CGIs were prominently distributed in the intergenic regions and were enriched in the size range of 200-300 bp. In total 13,294 methylated genes were found in four samples, including 4,085 differentially methylated genes between WRRh and WRRl, 5,599 between XHh and XHl, 4,204 between WRRh and XHh, as well as 7,301 between WRRl and XHl. Moreover, 132 differentially methylated genes related to growth and metabolism were observed in both inner contrasts (WRRh Vs. WRRl and XHh Vs. XHl), whereas 129 differentially methylated genes related to growth and metabolism were found in both across-breed contrasts (WRRh Vs. XHh and WRRl Vs. XHl). Further analysis showed that overall 75 genes exhibited altered DNA methylation in all four contrasts, which included some well-known growth factors of IGF1R, FGF12, FGF14, FGF18, FGFR2, and FGFR3. In addition, we further validate the MeDIP-seq results by bisulfite sequencing in some regions. 12 Breast muscle samples were collected from two breeds of different growth rate, Recessive White Rock (WRR) and Xinhua Chickens (XH). Each breed included low and high-weight groups and 3 samples from each group were pooled equally for methylated DNA immunoprecipitation-sequencing (MeDIP-seq).

Project description:Purpose: We characterized genome-wide DNA methylation profiles (methylome) in purified peripheral blood monocytes (PBMs) from 18 healthy postmenopausal Caucasian females aged 50-56 years. Methods: DNA methylome of Human Peripheral Blood Monocytes were generated by methylated DNA immunoprecipitation combined with high-throughput sequencing (MeDIP-seq), using Illumina GAIIx. The sequence reads that passed quality filters were analyzed using MEDIPS package. Targeted methylation validation analysis was performed by using MassARRAY EpiTYPER assays. Genome-wide gene expression profiles have been obtained for 7 of the 18 subjects by using Affymetrix 1.0 Human Exon ST arrays following the manufacturer's recommended protocols. Results: Using MeDIP-seq,a total of approximately 283 million reads were uniquely aligned to human genome (Build NCBI37, HG19), resulting in average ~16 million uniquely aligned high quality reads per sample. Distinct patterns were revealed at different genomic features. For instance, promoters were commonly (~58%) found to be unmethylated; whereas protein coding regions were largely (~84%) methylated. We found that approximately 24% CpG islands (CGIs) were highly methylated in PBMs. Further characterization of CGIs with respect to their relative locations to RefSeq genes revealed that the highly methylated CGIs were largely enriched (~89%) in CGIs located in gene bodies and intergenic regions. By integration of the methylome data with genome-wide PBM gene expression data, we found negative correlation between promoter methylation levels and gene transcription levels when comparing groups of genes with different expression levels, and this relationship was consistently observed across promoters with high to low CpG densities. Furthermore, we observed a modest but significant excess (permutation p<0.0001) of genes showing negative correlation between inter-individual promoter methylation and transcription levels, particularly for genes associated with CpG-rich promoters. Across the 18 individual PBM methylomes, we also identified genomic regions that were constitutively highly methylated in PBMs as well as regions showing large inter-individual variability. Conclusions: This study represents a comprehensive analysis of the PBM methylome and our data provides a valuable resource for future epigenomic and multi-omic studies exploring biological and disease-related regulatory mechanisms in PBMs. DNA methylome of human peripheral blood monocytes were generated by MeDIP-seq, using Illumina GAIIx.

Project description:Purpose: We characterized genome-wide DNA methylation profiles (methylome) in purified peripheral blood monocytes (PBMs) from 18 healthy postmenopausal Caucasian females aged 50-56 years. Methods: DNA methylome of Human Peripheral Blood Monocytes were generated by methylated DNA immunoprecipitation combined with high-throughput sequencing (MeDIP-seq), using Illumina GAIIx. The sequence reads that passed quality filters were analyzed using MEDIPS package. Targeted methylation validation analysis was performed by using MassARRAY EpiTYPER assays. Genome-wide gene expression profiles have been obtained for 7 of the 18 subjects by using Affymetrix 1.0 Human Exon ST arrays following the manufacturer's recommended protocols. Results: Using MeDIP-seq,a total of approximately 283 million reads were uniquely aligned to human genome (Build NCBI37, HG19), resulting in average ~16 million uniquely aligned high quality reads per sample. Distinct patterns were revealed at different genomic features. For instance, promoters were commonly (~58%) found to be unmethylated; whereas protein coding regions were largely (~84%) methylated. We found that approximately 24% CpG islands (CGIs) were highly methylated in PBMs. Further characterization of CGIs with respect to their relative locations to RefSeq genes revealed that the highly methylated CGIs were largely enriched (~89%) in CGIs located in gene bodies and intergenic regions. By integration of the methylome data with genome-wide PBM gene expression data, we found negative correlation between promoter methylation levels and gene transcription levels when comparing groups of genes with different expression levels, and this relationship was consistently observed across promoters with high to low CpG densities. Furthermore, we observed a modest but significant excess (permutation p<0.0001) of genes showing negative correlation between inter-individual promoter methylation and transcription levels, particularly for genes associated with CpG-rich promoters. Across the 18 individual PBM methylomes, we also identified genomic regions that were constitutively highly methylated in PBMs as well as regions showing large inter-individual variability. Conclusions: This study represents a comprehensive analysis of the PBM methylome and our data provides a valuable resource for future epigenomic and multi-omic studies exploring biological and disease-related regulatory mechanisms in PBMs.

Project description:Chronic liver inflammation precedes the majority of hepatocellular carcinomas (HCC). Here, we explore the connection between chronic inflammation and DNA methylation in the liver at the late precancerous stages of HCC development in Mdr2/Abcb4-knockout (Mdr2-KO) mice, a model of inflammation-mediated HCC. Using methylated DNA immunoprecipitation (MeDIP) followed by hybridization with Agilent CpG Islands (CGIs) microarrays we found specific CGIs in 76 genes which were hypermethylated in the Mdr2-KO liver compared to age-matched controls. Methylation of thirty among these genes was highly specific to the studied HCC model. We revealed that in most tested cases, the observed hypermethylation resulted from an age-dependent decrease of methylation of the specific CGIs in control livers with no decrease in mutant mice. Chronic inflammation did not change global levels of DNA methylation in Mdr2-KO liver, but caused a 2-fold decrease of the global 5-hydroxymethylcytosine level in mutants compared to controls. This decrease could result from a less efficient age-dependent demethylation of specific CpG sites in the liver of Mdr2-KO mutants, as described above. Expression of some tested hypermethylated genes was increased in Mdr2-KO livers compared to controls (28%), others were either similarly expressed (44%), or not expressed in the liver (28%). Liver cell fractionation revealed, that the relative hypermethylation of specific CGIs in Mdr2-KO compared to control livers affected either hepatocyte, or non-hepatocyte, or both fractions. There was only episodic correlation between changes of gene methylation and expression in cell fractions. Conclusion: Chronic liver inflammation causes hypermethylation of specific CGIs, which may affect both hepatocytes and non-hepatocyte liver cells. These changes may serve as markers of an increased regenerative activity and of a precancerous microenvironment in the chronically inflamed liver. Two-condition experiment, Mdr2-KO vs Mdr2-/+ liver tissue from 12m-old male FVB strain mice. Biological replicates: 3 control replicates, 3 knockout replicates.

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Comparison of the genome-wide DNA methylation profiles between fast-growing and slow-growing broilers

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