Dataset Information

Differentially methylated CpG sites in bull spermatozoa revealed by human DNA methylation arrays and bisulfite analysis.

ABSTRACT: The methylation status of sperm DNA differs between individual bulls. However, the relationship between methylation status and bull sperm parameters is not well elucidated. The present study investigated genome-wide methylation profiles at 450,000 CpG sites in bull spermatozoa by using a human DNA methylation microarray. Semen samples from three adult Japanese Black bulls with different in vitro fertilization (IVF) results and from a young Holstein bull through sexual maturation (at ages 10, 10.5, 15, and 25 months) were used for the analysis. The heatmap displaying the results of microarray analysis shows inter- and intra-individual differences in methylation profiles. After setting a cut-off of 0.2 for differences between ages (10, 10.5 vs. 15, 25 months) or between IVF results (developed to the blastocyst-stage, > 20% vs. < 10%), different methylation levels were detected at approximately 100 CpGs. We confirmed the different DNA methylation levels of CpG sites by using combined bisulfite restriction analysis (COBRA); five of the CpG sites reflected methylation levels similar to those detected by the microarray. One of the CpG sites was thought to reflect an age-related increase in methylation levels, which was confirmed by COBRA and bisulfite sequencing. However, the relationship between methylation status and IVF results could not be shown here. In conclusion, methylation profiles of individual and age-related alterations in bull spermatozoa can be revealed using a human microarray, and methylation changes in some CpG sites can be easily visualized using COBRA. Combined analysis of DNA methylation levels and sperm parameters could be considered an effective approach for assessing bull fertility in the future.

SUBMITTER: Takeda K

PROVIDER: S-EPMC5481630 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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Differentially methylated CpG sites in bull spermatozoa revealed by human DNA methylation arrays and bisulfite analysis.

Takeda Kumiko K Kobayashi Eiji E Akagi Satoshi S Nishino Kagetomo K Kaneda Masahiro M Watanabe Shinya S

The Journal of reproduction and development 20170319 3

The methylation status of sperm DNA differs between individual bulls. However, the relationship between methylation status and bull sperm parameters is not well elucidated. The present study investigated genome-wide methylation profiles at 450,000 CpG sites in bull spermatozoa by using a human DNA methylation microarray. Semen samples from three adult Japanese Black bulls with different in vitro fertilization (IVF) results and from a young Holstein bull through sexual maturation (at ages 10, 10. ...[more]

PMID: 28320989

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Project description:AIMS/INTRODUCTION:The incidence of type 2 diabetes mellitus is increasing worldwide, and it might partly cause metabolic disorder and type 2 diabetes mellitus susceptibility in patients' offspring through epigenetic modification. However, the underlying mechanisms remain largely unclear. Recent studies have shown a potential link between deoxyribonucleic acid methylation in paternal sperm and susceptibility to type 2 diabetes mellitus in offspring, so this article focuses on whether the whole-genome methylation profiles of spermatozoa in type 2 diabetes mellitus patients have changed. MATERIALS AND METHODS:We investigated the genome-wide deoxyribonucleic acid methylation profiles in spermatozoa by comparing eight individuals with type 2 diabetes mellitus and nine non-diabetic controls using whole-genome bisulfite sequencing method. RESULTS:First, we found that the proportion of methylated cytosine in the whole genome of the type 2 diabetes mellitus group was slightly lower than that of the control group. Interestingly, the proportion of methylated cytosines in the CG context decreased, and the proportion of methylated cytosines in the CHG context (H = A, T or C) increased in the type 2 diabetes mellitus group, but the proportion of methylated cytosines in the CHH context (H = A, T or C) barely changed. The methylated cytosines in the CG context were mainly distributed at the high methylated level, whereas methylated cytosines in the CHG context and methylated cytosines in the CHH context were mainly distributed at the low and middle methylated level in both groups. Second, functional enrichment analysis showed that differentially methylated genes played a significant role in nervous system development and cell metabolism. Finally, we identified 10 top type 2 diabetes mellitus-related differentially methylated genes, including IRS1, PRKCE, FTO, PPARGC1A, KCNQ1, ATP10A, GHR, CREB1, PRKAR1A and HNF1B. CONCLUSIONS:Our study provides the first evidence for deoxyribonucleic acid methylation reprogramming in spermatozoa of type 2 diabetes mellitus patients, and provides a new basis for explaining the complex mechanism of type 2 diabetes mellitus susceptibility in offspring.

Project description:BackgroundHypermethylation of promoter CpG islands is strongly correlated to transcriptional gene silencing and epigenetic maintenance of the silenced state. As well as its role in tumor development, CpG island methylation contributes to the acquisition of resistance to chemotherapy. Differential Methylation Hybridisation (DMH) is one technique used for genome-wide DNA methylation analysis. The study of such microarray data sets should ideally account for the specific biological features of DNA methylation and the non-symmetrical distribution of the ratios of unmethylated and methylated sequences hybridised on the array. We have therefore developed a novel algorithm tailored to this type of data, Methylation Linear Discriminant Analysis (MLDA).ResultsMLDA was programmed in R (version 2.7.0) and the package is available at CRAN 1. This approach utilizes linear regression models of non-normalised hybridisation data to define methylation status. Log-transformed signal intensities of unmethylated controls on the microarray are used as a reference. The signal intensities of DNA samples digested with methylation sensitive restriction enzymes and mock digested are then transformed to the likelihood of a locus being methylated using this reference. We tested the ability of MLDA to identify loci differentially methylated as analysed by DMH between cisplatin sensitive and resistant ovarian cancer cell lines. MLDA identified 115 differentially methylated loci and 23 out of 26 of these loci have been independently validated by Methylation Specific PCR and/or bisulphite pyrosequencing.ConclusionMLDA has advantages for analyzing methylation data from CpG island microarrays, since there is a clear rational for the definition of methylation status, it uses DMH data without between-group normalisation and is less influenced by cross-hybridisation of loci. The MLDA algorithm successfully identified differentially methylated loci between two classes of samples analysed by DMH using CpG island microarrays.

Project description:Deoxyribonucleic acid (DNA) methylation is an epigenetic alteration crucial for regulating stress responses. Identifying large-scale DNA methylation at single nucleotide resolution is made possible by whole genome bisulfite sequencing. An essential task following the generation of bisulfite sequencing data is to detect differentially methylated cytosines (DMCs) among treatments. Most statistical methods for DMC detection do not consider the dependency of methylation patterns across the genome, thus possibly inflating type I error. Furthermore, small sample sizes and weak methylation effects among different phenotype categories make it difficult for these statistical methods to accurately detect DMCs. To address these issues, the wavelet-based functional mixed model (WFMM) was introduced to detect DMCs. To further examine the performance of WFMM in detecting weak differential methylation events, we used both simulated and empirical data and compare WFMM performance to a popular DMC detection tool methylKit. Analyses of simulated data that replicated the effects of the herbicide glyphosate on DNA methylation in Arabidopsis thaliana show that WFMM results in higher sensitivity and specificity in detecting DMCs compared to methylKit, especially when the methylation differences among phenotype groups are small. Moreover, the performance of WFMM is robust with respect to small sample sizes, making it particularly attractive considering the current high costs of bisulfite sequencing. Analysis of empirical Arabidopsis thaliana data under varying glyphosate dosages, and the analysis of monozygotic (MZ) twins who have different pain sensitivities-both datasets have weak methylation effects of <1%-show that WFMM can identify more relevant DMCs related to the phenotype of interest than methylKit. Differentially methylated regions (DMRs) are genomic regions with different DNA methylation status across biological samples. DMRs and DMCs are essentially the same concepts, with the only difference being how methylation information across the genome is summarized. If methylation levels are determined by grouping neighboring cytosine sites, then they are DMRs; if methylation levels are calculated based on single cytosines, they are DMCs.

Project description:BACKGROUND:Psychiatric symptomatology during late childhood and early adolescence tends to persist later in life. In the present longitudinal study, we aimed to identify changes in genome-wide DNA methylation patterns that were associated with the emergence of psychopathology in youths from the Brazilian High-Risk Cohort (HRC) for psychiatric disorders. Moreover, for the differentially methylated genes, we verified whether differences in DNA methylation corresponded to differences in mRNA transcript levels by analyzing the gene expression levels in the blood and by correlating the variation of DNA methylation values with the variation of mRNA levels of the same individuals. Finally, we examined whether the variations in DNA methylation and mRNA levels were correlated with psychopathology measurements over time. METHODS:We selected 24 youths from the HRC who presented with an increase in dimensional psychopathology at a 3-year follow-up as measured by the Child Behavior Checklist (CBCL). The DNA methylation and gene expression data were compared in peripheral blood samples (n?=?48) obtained from the 24 youths before and after developing psychopathology. We implemented a methodological framework to reduce the effect of chronological age on DNA methylation using an independent population of 140 youths and the effect of puberty using data from the literature. RESULTS:We identified 663 differentially methylated positions (DMPs) and 90 differentially methylated regions (DMRs) associated with the emergence of psychopathology. We observed that 15 DMPs were mapped to genes that were differentially expressed in the blood; among these, we found a correlation between the DNA methylation and mRNA levels of RB1CC1 and a correlation between the CBCL and mRNA levels of KMT2E. Of the DMRs, three genes were differentially expressed: ASCL2, which is involved in neurogenesis; HLA-E, which is mapped to the MHC loci; and RPS6KB1, the gene expression of which was correlated with an increase in the CBCL between the time points. CONCLUSIONS:We observed that changes in DNA methylation and, consequently, in gene expression in the peripheral blood occurred concurrently with the emergence of dimensional psychopathology in youths. Therefore, epigenomic modulations might be involved in the regulation of an individual's development of psychopathology.

Project description:DNA methylation, as an epigenetic mechanism, has a vital role in heart development. An increasing number of studies have investigated aberrant DNA methylation in pediatric or adult heart samples from patients with congenital heart defects (CHD). Placenta tissue, umbilical cord blood, or newborn blood have also been used to detect DNA methylation biomarkers for CHD. However, few studies have compared the methylation levels in fetal heart tissue with cardiac defects with that in normal controls. The present study conducted an integrative whole-genome and CpG site-specific DNA methylation analysis of fetal heart samples from 17 isolated cardiac defect cases, 14 non-isolated cardiac defect cases, and 22 controls with normal hearts, using methylated DNA immunoprecipitation microarray and MassARRAY EpiTYPER assays. Expression of genes adjacent to differentially methylated regions (DMRs) was measured by RT-qPCR and western blot analysis. The results revealed that fetuses with cardiac defects presented global hypomethylation. Genomic analysis of DMRs revealed that a proportion of DMRs were located in exons (12.4%), distal intergenic regions (11.14%), and introns (8.97%). Only 55.7% of DMRs were observed at promoter regions. Functional enrichment analysis for genes adjacent to these DMRs revealed that hypomethylated genes were involved in embryonic heart tube morphogenesis and immune-related regulation functions. Intergenic hypermethylation of EGFR and solute carrier family 19 member 1 (SLC19A1), and intragenic hypomethylation of NOTCH1 were validated in fetal heart tissues with cardiac defects. Only SLC19A1 expression was significantly decreased at the mRNA level, while EGFR, NOTCH1, and SLC19A1 expression were all significantly decreased at the protein level. In conclusion, the present study demonstrated that fetal cardiac defects may be associated with alterations in regional and single CpG site methylation outside of promoter regions, resulting in differentiated expression of corresponding genes associated with heart development. These results present new insights into the epigenetic mechanisms underlying abnormal heart development.

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Differentially methylated CpG sites in bull spermatozoa revealed by human DNA methylation arrays and bisulfite analysis.

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Differentially methylated CpG sites in bull spermatozoa revealed by human DNA methylation arrays and bisulfite analysis.

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