Sperm methylome profiling can discern fertility levels in the porcine biomedical model
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB43108 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR5433900.fastq.gz | Fastqsanger.gz | |||
| ERR5433900_1.fastq.gz | Fastqsanger.gz | |||
| ERR5433900_2.fastq.gz | Fastqsanger.gz | |||
| ERR5433910.fastq.gz | Fastqsanger.gz | |||
| ERR5433910_1.fastq.gz | Fastqsanger.gz |
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Project description:Genomic imprinting describes the expression of a subset of mammalian genes from one parental chromosome. The parent-of-origin specific expression of imprinted genes relies on DNA methylation of CpG-dinucleotides at differentially methylated regions (DMRs) during gametogenesis. We identified the paternally methylated DMR at human chromosome 2 near the imprinted ZDBF2 gene using a methylated-DNA immunoprecipitation-on-chip (meDIP-on-chip) method applied to DNA from sperm. To analyze whether or not the GPR1-ZDBF2 DMR is conserved in human genome, methylation analysis of human sperm sample was performed using MeDIP and genome tiling array.
2010-05-05 | E-GEOD-18178 | biostudies-arrayexpress
Project description:Genomic imprinting describes the expression of a subset of mammalian genes from one parental chromosome. The parent-of-origin specific expression of imprinted genes relies on DNA methylation of CpG-dinucleotides at differentially methylated regions (DMRs) during gametogenesis. We identified the paternally methylated DMR at human chromosome 2 near the imprinted ZDBF2 gene using a methylated-DNA immunoprecipitation-on-chip (meDIP-on-chip) method applied to DNA from sperm.
2010-05-05 | GSE18178 | GEO
Project description:A combined Genotyping By Sequencing (GBS) and methylated DNA immunoprecipitation (MeDIP) protocol was used to identify-in parallel-genetic variation (Genomic-Wide Association Studies (GWAS) and epigenetic differences of Differentially Methylated Regions (DMR) in the genome of spermatozoa from the porcine animal model. Breeding boars with good semen quality (n = 11) and specific and well-documented differences in fertility (farrowing rate, FR) and prolificacy (litter size, LS) (n = 7) in artificial insemination programs, using combined FR and LS, were categorized as High Fertile (HF, n = 4) or Low Fertile (LF, n = 3), and boars with Unknown Fertility (UF, n = 4) were tested for eventual epigenetical similarity with those fertility-proven. We identified 165,944 Single Nucleotide Polymorphisms (SNPs) that explained 14-15% of variance among selection lines. Between HF and LF individuals (n = 7, 4 HF and 3 LF), we identified 169 SNPs with p ≤ 0.00015, which explained 58% of the variance. For the epigenetic analyses, we considered fertility and period of ejaculate collection (late-summer and mid-autumn). Approximately three times more DMRs were observed in HF than in LF boars across these periods. Interestingly, UF boars were clearly clustered with one of the other HF or LF groups. The highest differences in DMRs between HF and LF experimental groups across the pig genome were located in the chr 3, 9, 13, and 16, with most DMRs being hypermethylated in LF boars. In both HF and LF boars, DMRs were mostly hypermethylated in late-summer compared to mid-autumn. Three overlaps were detected between SNPs (p ≤ 0.0005, n = 1318) and CpG sites within DMRs. In conclusion, fertility levels in breeding males including FR and LS can be discerned using methylome analyses. The findings in this biomedical animal model ought to be applied besides sire selection for andrological diagnosis of idiopathic sub/infertility.
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Project description:Genome-wide DNA methylation profile of human spermatozoa using the meDIP technique and massively parallel sequencing. DNA methylation is an indispensible epigenetic modification required for regulating the expression of mammalian genomes. Immunoprecipitation-based methods for DNA methylome analysis are rapidly shifting the bottleneck in this field from data generation to data analysis, necessitating the development of better analytical tools. In particular, an inability to estimate absolute methylation levels remains a major analytical difficulty associated with immunoprecipitation-based DNA methylation profiling. To address this issue, we developed a cross-platform algorithm-Bayesian tool for methylation analysis (Batman)-for analyzing methylated DNA immunoprecipitation (MeDIP) profiles generated using oligonucleotide arrays (MeDIP-chip) or next-generation sequencing (MeDIP-seq). We developed the latter approach to provide a high-resolution whole-genome DNA methylation profile (DNA methylome) of a mammalian genome. Strong correlation of our data, obtained using mature human spermatozoa, with those obtained using bisulfite sequencing suggest that combining MeDIP-seq or MeDIP-chip with Batman provides a robust, quantitative and cost-effective functional genomic strategy for elucidating the function of DNA methylation. ArrayExpress Release Date: 2008-06-10 Publication Title: A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis Publication Author List: Thomas A Down; Vardhman K Rakyan; Daniel J Turner; Paul Flicek; Heng Li; Eugene Kulesha; Stefan Gräf; Nathan Johnson; Javier Herrero; Eleni M Tomazou; Natalie P Thorne; Liselotte Bäckdahl; Marlis Herberth; Kevin L Howe; David K Jackson; Marcos M Miretti; John C Marioni; Ewan Birney; Tim J P Hubbard; Richard Durbin; Simon Tavaré; Stephan Beck Person Roles: submitter; investigator Person Last Name: Flicek Person First Name: Paul Person Mid Initial Person Email: flicek@ebi.ac.uk Person Address: Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK Person Affiliation: European Bioinformatics Institute
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Project description:Epigenetic regulation of gene expression plays a pivotal role in the orchestration of immune responses and may determine the vigor, quality, or longevity of such responses. Chemical allergens can be divided into two categories: skin sensitizing chemicals associated with allergic contact dermatitis, and chemicals that cause sensitization of the respiratory tract and occupational asthma. In mice these are characterized by different T helper (Th) cell responses. To explore the regulation and maintenance of these divergent responses, mice were exposed to 2,4-dinitrochlorobenzene (DNCB; a contact allergen) or trimellitic anhydride (TMA; a respiratory allergen). DNA from draining lymph nodes was processed for methylated DNA immunoprecipitation (MeDIP) followed by hybridization to a whole-genome DNA promoter array. 6319 differently methylated regions (DMR) were identified following DNCB treatment, while 2178 DMRs were measured following TMA treatment, with approximately half of the TMA DMR common to DNCB. When limited to promoter region-associated DMR, 637 genes were uniquely associated with DNCB induced DMR but only 164 genes were unique to TMA DMR. Promoter-associated DMR unique to either DNCB or TMA were generally hypomethylated whereas DMR common to both allergens tended to be hypermethylated. Pathway analyses highlighted a number of immune related pathways, including chemokine and cytokine signalling. These data demonstrate that chemical allergen exposure results in characteristic patterns of DNA methylation indicative of epigenetic regulation of the allergic response.
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