Methylation at CpG sites in genomes of aphid Acyrtosiphon pisum and its endosymbiont Buchnera

Pea aphid Acyrtosiphon pisum, a sap-feeding insect, has established a mutualistic relationship with an endosymbiotic bacteria (Buchnera aphidicola) that constitutes an evolutionary successful symbiosis to synthetize complex chemical compounds from a nutrient deprived diet. In this study, led by the presence of DNMT1 and a putative DNMT3 methylase in the aphid genome, we investigated the distribution of the methyl groups on 5'cytosine in CpG motifs on the whole genomes of host and endosymbiont, and looked into their correlation with gene expression. The DNA methylation turned to be present at low level in aphid (around 3% of total genomic cytosine) compared to mammals and plants, but increased to ~9% in genes. Interestingly, the reduced genome of the endosymbiont Buchnera also shows global low level of methyl cytosine despite the fact that its genome does not shelter any DNA methylase. This finding argues for the import of DNA methylase from the host to the endosymbiont. The observed differences in methylation patterns between two clonal variants (host plus endosymbiont) are reported along with the differences in their transcriptome profiles. Our data allowed to decipher a dynamic combinatorial DNA methylation and epigenetic cross talk between host and symbiont in a clonality context that might count for the aphid adaptation to environment.

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Examination of the dynamics of global DNA methylation pattern establishment during spermatogenesiss

Clinical & Investigative Medicine ◽

10.25011/cim.v30i4.2868 ◽

2007 ◽

Vol 30 (4) ◽

pp. 90

Author(s):

Kirsten Niles ◽

Sophie La Salle ◽

Christopher Oakes ◽

Jacquetta Trasler

Keyword(s):

Dna Methylation ◽

Germ Cell ◽

Germ Cells ◽

Epigenetic Modification ◽

Methylation Pattern ◽

Chromosome 9 ◽

Specific Gene ◽

Global Methylation ◽

Dna Methylation Pattern ◽

Methylation Patterns

Background: DNA methylation is an epigenetic modification involved in gene expression, genome stability, and genomic imprinting. In the male, methylation patterns are initially erased in primordial germ cells (PGCs) as they enter the gonadal ridge; methylation patterns are then acquired on CpG dinucleotides during gametogenesis. Correct pattern establishment is essential for normal spermatogenesis. To date, the characterization and timing of methylation pattern acquisition in PGCs has been described using a limited number of specific gene loci. This study aimed to describe DNA methylation pattern establishment dynamics during male gametogenesis through global methylation profiling techniques in a mouse model. Methods: Using a chromosome based approach, primers were designed for 24 regions spanning chromosome 9; intergenic, non-repeat, non-CpG island sequences were chosen for study based on previous evidence that these types of sequences are targets for testis-specific methylation events. The percent methylation was determined in each region by quantitative analysis of DNA methylation using real-time PCR (qAMP). The germ cell-specific pattern was determined by comparing methylation between spermatozoa and liver. To examine methylation in developing germ cells, spermatogonia from 2 day- and 6 day-old Oct4-GFP (green fluorescent protein) mice were isolated using fluorescence activated cell sorting. Results: As compared to liver, four loci were hypomethylated and five loci were hypermethylated in spermatozoa, supporting previous results indicating a unique methylation pattern in male germ cells. Only one region was hypomethylated and no regions were hypermethylated in day 6 spermatogonia as compared to mature spermatozoa, signifying that the bulk of DNA methylation is established prior to type A spermatogonia. The methylation in day 2 spermatogonia, germ cells that are just commencing mitosis, revealed differences of 15-20% compared to day 6 spermatogonia at five regions indicating that the most crucial phase of DNA methylation acquisition occurs prenatally. Conclusion: Together, these studies provide further evidence that germ cell methylation patterns differ from those in somatic tissues and suggest that much of methylation at intergenic sites is acquired during prenatal germ cell development. (Supported by CIHR)

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DNA methylation patterns identify subgroups of pancreatic neuroendocrine tumors with clinical association

Communications Biology ◽

10.1038/s42003-020-01469-0 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Vanessa Lakis ◽

◽

Rita T. Lawlor ◽

Felicity Newell ◽

Ann-Marie Patch ◽

...

Keyword(s):

Dna Methylation ◽

Neuroendocrine Tumors ◽

Methylation Profile ◽

Pancreatic Neuroendocrine Tumors ◽

Wild Type ◽

Genomic Information ◽

Chromosome 11 ◽

Dna Methylation Profile ◽

Methylation Patterns ◽

Recurrent Patterns

AbstractHere we report the DNA methylation profile of 84 sporadic pancreatic neuroendocrine tumors (PanNETs) with associated clinical and genomic information. We identified three subgroups of PanNETs, termed T1, T2 and T3, with distinct patterns of methylation. The T1 subgroup was enriched for functional tumors and ATRX, DAXX and MEN1 wild-type genotypes. The T2 subgroup contained tumors with mutations in ATRX, DAXX and MEN1 and recurrent patterns of chromosomal losses in half of the genome with no association between regions with recurrent loss and methylation levels. T2 tumors were larger and had lower methylation in the MGMT gene body, which showed positive correlation with gene expression. The T3 subgroup harboured mutations in MEN1 with recurrent loss of chromosome 11, was enriched for grade G1 tumors and showed histological parameters associated with better prognosis. Our results suggest a role for methylation in both driving tumorigenesis and potentially stratifying prognosis in PanNETs.

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Multi-species and multi-tissue methylation clocks for age estimation in toothed whales and dolphins

Communications Biology ◽

10.1038/s42003-021-02179-x ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Todd R. Robeck ◽

Zhe Fei ◽

Ake T. Lu ◽

Amin Haghani ◽

Eve Jourdain ◽

...

Keyword(s):

Dna Methylation ◽

Age Estimation ◽

Species Conservation ◽

Genome Wide ◽

Epigenetic Aging ◽

Highly Correlated ◽

Methylation Patterns ◽

Cg Dinucleotides ◽

Free Ranging ◽

Unique Species

AbstractThe development of a precise blood or skin tissue DNA Epigenetic Aging Clock for Odontocete (OEAC) would solve current age estimation inaccuracies for wild odontocetes. Therefore, we determined genome-wide DNA methylation profiles using a custom array (HorvathMammalMethyl40) across skin and blood samples (n = 446) from known age animals representing nine odontocete species within 4 phylogenetic families to identify age associated CG dinucleotides (CpGs). The top CpGs were used to create a cross-validated OEAC clock which was highly correlated for individuals (r = 0.94) and for unique species (median r = 0.93). Finally, we applied the OEAC for estimating the age and sex of 22 wild Norwegian killer whales. DNA methylation patterns of age associated CpGs are highly conserved across odontocetes. These similarities allowed us to develop an odontocete epigenetic aging clock (OEAC) which can be used for species conservation efforts by provide a mechanism for estimating the age of free ranging odontocetes from either blood or skin samples.

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Aging-associated distinctive DNA methylation changes of LINE-1 retrotransposons in pure cell-free DNA from human blood

Scientific Reports ◽

10.1038/s41598-020-79126-z ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Wardah Mahmood ◽

Lars Erichsen ◽

Pauline Ott ◽

Wolfgang A. Schulz ◽

Johannes C. Fischer ◽

...

Keyword(s):

Dna Methylation ◽

Cell Free Dna ◽

The Past ◽

Free Dna ◽

Genome Wide ◽

Cancerous Cell ◽

Pure Cell ◽

Epigenetic Biomarker ◽

Methylation Patterns ◽

Cancerous Cells

AbstractLINE-1 hypomethylation of cell-free DNA has been described as an epigenetic biomarker of human aging. However, in the past, insufficient differentiation between cellular and cell-free DNA may have confounded analyses of genome-wide methylation levels in aging cells. Here we present a new methodological strategy to properly and unambiguously extract DNA methylation patterns of repetitive, as well as single genetic loci from pure cell-free DNA from peripheral blood. Since this nucleic acid fraction originates mainly in apoptotic, senescent and cancerous cells, this approach allows efficient analysis of aged and cancerous cell-specific DNA methylation patterns for diagnostic and prognostic purposes. Using this methodology, we observe a significant age-associated erosion of LINE-1 methylation in cfDNA suggesting that the threshold of hypomethylation sufficient for relevant LINE-1 activation and consequential harmful retrotransposition might be reached at higher age. We speculate that this process might contribute to making aging the main risk factor for many cancers.

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