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Environmentally selected aphid variants in clonality context display differential patterns of methylation in the genome.

ABSTRACT: Heritability of acquired phenotypic traits is an adaptive evolutionary process that appears more complex than the basic allele selection guided by environmental pressure. In insects, the trans-generational transmission of epigenetic marks in clonal and/or sexual species is poorly documented. Aphids were used as a model to explore this feature because their asexual phase generates a stochastic and/or environment-oriented repertoire of variants. The a priori unchanged genome in clonal individuals prompts us to hypothesize whether covalent methyl DNA marks might be associated to the phenotypic variability and fitness selection. The full differential transcriptome between two environmentally selected clonal variants that originated from the same founder mother was mapped on the entire genomic scaffolds, in parallel with the methyl cytosine distribution. Data suggest that the assortments of heavily methylated DNA sites are distinct in these two clonal phenotypes. This might constitute an epigenetic mechanism that confers the robust adaptation of insect species to various environments involving clonal reproduction.

SUBMITTER: Pasquier C

PROVIDER: S-EPMC4281257 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Environmentally selected aphid variants in clonality context display differential patterns of methylation in the genome.

Pasquier Claude C Clément Mathilde M Dombrovsky Aviv A Penaud Stéphanie S Da Rocha Martine M Rancurel Corinne C Ledger Neil N Capovilla Maria M Robichon Alain A

PloS one 20141231 12

Heritability of acquired phenotypic traits is an adaptive evolutionary process that appears more complex than the basic allele selection guided by environmental pressure. In insects, the trans-generational transmission of epigenetic marks in clonal and/or sexual species is poorly documented. Aphids were used as a model to explore this feature because their asexual phase generates a stochastic and/or environment-oriented repertoire of variants. The a priori unchanged genome in clonal individuals ...[more]

PMID: 25551225

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Project description:BackgroundDNA methylation is a key epigenetic regulator contributing to cancer development. To understand the role of DNA methylation in tumorigenesis, it is important to investigate and compare differential methylation (DM) patterns between normal and case samples across different cancer types. However, current pan-cancer analyses call DM separately for each cancer, which suffers from lower statistical power and fails to provide a comprehensive view for patterns across cancers.MethodsIn this work, we propose a rigorous statistical model, PanDM, to jointly characterize DM patterns across diverse cancer types. PanDM uses the hidden correlations in the combined dataset to improve statistical power through joint modeling. PanDM takes summary statistics from separate analyses as input and performs methylation site clustering, differential methylation detection, and pan-cancer pattern discovery. We demonstrate the favorable performance of PanDM using simulation data. We apply our model to 12 cancer methylome data collected from The Cancer Genome Atlas (TCGA) project. We further conduct ontology- and pathway-enrichment analyses to gain new biological insights into the pan-cancer DM patterns learned by PanDM.ResultsPanDM outperforms two types of separate analyses in the power of DM calling in the simulation study. Application of PanDM to TCGA data reveals 37 pan-cancer DM patterns in the 12 cancer methylomes, including both common and cancer-type-specific patterns. These 37 patterns are in turn used to group cancer types. Functional ontology and biological pathways enriched in the non-common patterns not only underpin the cancer-type-specific etiology and pathogenesis but also unveil the common environmental risk factors shared by multiple cancer types. Moreover, we also identify PanDM-specific DM CpG sites that the common strategy fails to detect.ConclusionsPanDM is a powerful tool that provides a systematic way to investigate aberrant methylation patterns across multiple cancer types. Results from real data analyses suggest a novel angle for us to understand the common and specific DM patterns in different cancers. Moreover, as PanDM works on the summary statistics for each cancer type, the same framework can in principle be applied to pan-cancer analyses of other functional genomic profiles. We implement PanDM as an R package, which is freely available at http://www.sta.cuhk.edu.hk/YWei/PanDM.html .

Project description:BackgroundPremature infants are highly vulnerable to infection. This is partly attributable to the preterm immune system, which differs from that of the term neonate in cell composition and function. Multiple studies have found differential DNA methylation (DNAm) between preterm and term infants' cord blood; however, interpretation of these studies is limited by the confounding factor of blood cell composition. This study evaluates the epigenetic impact of preterm birth in isolated hematopoietic cell populations, reducing the concern of cell composition differences.MethodsGenome-wide DNAm was measured using the Illumina 450K array in T cells, monocytes, granulocytes, and nucleated red blood cells (nRBCs) isolated from cord blood of 5 term and 5 preterm (<31 weeks gestational age) newborns. DNAm of hematopoietic cells was compared globally across the 450K array and through site-specific linear modeling.ResultsNucleated red blood cells (nRBCs) showed the most extensive changes in DNAm, with 9258 differentially methylated (DM) sites (FDR < 5%, |Δβ| > 0.10) discovered between preterm and term infants compared to the <1000 prematurity-DM sites identified in white blood cell populations. The direction of DNAm change with gestational age at these prematurity-DM sites followed known patterns of hematopoietic differentiation, suggesting that term hematopoietic cell populations are more epigenetically mature than their preterm counterparts. Consistent shifts in DNAm between preterm and term cells were observed at 25 CpG sites, with many of these sites located in genes involved in growth and proliferation, hematopoietic lineage commitment, and the cytoskeleton. DNAm in preterm and term hematopoietic cells conformed to previously identified DNAm signatures of fetal liver and bone marrow, respectively.ConclusionsThis study presents the first genome-wide mapping of epigenetic differences in hematopoietic cells across the late gestational period. DNAm differences in hematopoietic cells between term and <31 weeks were consistent with the hematopoietic origin of these cells during ontogeny, reflecting an important role of DNAm in their regulation. Due to the limited sample size and the high coincidence of prematurity and multiple births, the relationship between cause of preterm birth and DNAm could not be evaluated. These findings highlight gene regulatory mechanisms at both cell-specific and systemic levels that may be involved in fetal immune system maturation.

Dataset Information

Environmentally selected aphid variants in clonality context display differential patterns of methylation in the genome.

Publications

Environmentally selected aphid variants in clonality context display differential patterns of methylation in the genome.

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