Oilseed rape (Brassica napus L.) was formed~7500 years ago by hybridization between B. rapa and B. oleracea, followed by chromosome doubling, a process known as allopolyploidy. Together with more ancient polyploidizations, this conferred an aggregate 72× genome multiplication since the origin of angiosperms and high gene content. We examined the B. napus genome and the consequences of its recent duplication. The constituent A n and C n subgenomes are engaged in subtle structural, functional, and epigenetic cross-talk, with abundant homeologous exchanges. Incipient gene loss and expression divergence have begun. Selection in B. napus oilseed types has accelerated the loss of glucosinolate genes, while preserving expansion of oil biosynthesis genes. These processes provide insights into allopolyploid evolution and its relationship with crop domestication and improvement.T he Brassicaceae are a large eudicot family (1) and include the model plant Arabidopsis thaliana. Brassicas have a propensity for genome duplications ( Fig. 1) and genome mergers (2). They are major contributors to the human diet and were among the earliest cultigens (3).B. napus (genome A n A n C n C n ) was formed by recent allopolyploidy between ancestors of B. oleracea (Mediterranean cabbage, genome C o C o ) and B. rapa (Asian cabbage or turnip, genome A r A r ) and is polyphyletic (2, 4), with spontaneous formation regarded by Darwin as an example of unconscious selection (5). Cultivation began in Europe during the Middle Ages and spread worldwide. Diversifying selection gave rise to oilseed rape (canola), rutabaga, fodder rape, and kale morphotypes grown for oil, fodder, and food (4, 6).The homozygous B. napus genome of European winter oilseed cultivar 'Darmor-bzh' was assembled with long-read [>700 base pairs (bp)] 454 GS-FLX+ Titanium (Roche, Basel, Switzerland) and Sanger sequence (tables S1 to S5 and figs. S1 to S3) (7). Correction and gap filling used 79 Gb of Illumina (San Diego, CA) HiSeq sequence. A final assembly of 849.7 Mb was obtained with SOAP (8) and Newbler (Roche), with 89% nongapped sequence (tables S2 and S3). Unique mapping of 5× nonassembled 454 sequences from B. rapa ('Chiifu') or B. oleracea (' TO1000') assigned most of the 20,702 B. napus scaffolds to either the A n (8294) or the C n (9984) subgenomes (tables S4 and S5 and fig. S3). The assembly covers~79% of the 1130-Mb genome and includes 95.6% of Brassica expressed sequence tags (ESTs) (7). A single-nucleotide polymorphism (SNP) map (tables S6 to S9 and figs. S4 to S8) genetically anchored 712.3 Mb (84%) of the genome assembly, yielding pseudomolecules for the 19 chromosomes (table S10).The assembled C n subgenome (525.8 Mb) is larger than the A n subgenome (314.2 Mb), consistent with the relative sizes of the assembled C o genome of B. oleracea (540 Mb, 85% of thẽ 630-Mb genome) and the A r genome of B. rapa (312 Mb, 59% of the~530-Mb genome) (9-11). The B. napus assembly contains 34.8% transposable elements (TEs), less than the 40% estimated from raw reads (table...

Epigenetic modifications, including DNA methylation, represent a potential mechanism for environmental impacts on human disease. Maternal smoking in pregnancy remains an important public health problem that impacts child health in a myriad of ways and has potential lifelong consequences. The mechanisms are largely unknown, but epigenetics most likely plays a role. We formed the Pregnancy And Childhood Epigenetics (PACE) consortium and meta-analyzed, across 13 cohorts (n = 6,685), the association between maternal smoking in pregnancy and newborn blood DNA methylation at over 450,000 CpG sites (CpGs) by using the Illumina 450K BeadChip. Over 6,000 CpGs were differentially methylated in relation to maternal smoking at genome-wide statistical significance (false discovery rate, 5%), including 2,965 CpGs corresponding to 2,017 genes not previously related to smoking and methylation in either newborns or adults. Several genes are relevant to diseases that can be caused by maternal smoking (e.g., orofacial clefts and asthma) or adult smoking (e.g., certain cancers). A number of differentially methylated CpGs were associated with gene expression. We observed enrichment in pathways and processes critical to development. In older children (5 cohorts, n = 3,187), 100% of CpGs gave at least nominal levels of significance, far more than expected by chance (p value < 2.2 × 10(-16)). Results were robust to different normalization methods used across studies and cell type adjustment. In this large scale meta-analysis of methylation data, we identified numerous loci involved in response to maternal smoking in pregnancy with persistence into later childhood and provide insights into mechanisms underlying effects of this important exposure.

Pyrosequencing is a sequencing-by-synthesis method that quantitatively monitors the real-time incorporation of nucleotides through the enzymatic conversion of released pyrophosphate into a proportional light signal. Quantitative measures are of special importance for DNA methylation analysis in various developmental and pathological situations. Analysis of DNA methylation patterns by pyrosequencing combines a simple reaction protocol with reproducible and accurate measures of the degree of methylation at several CpGs in close proximity with high quantitative resolution. After bisulfite treatment and PCR, the degree of each methylation at each CpG position in a sequence is determined from the ratio of T and C. The process of purification and sequencing can be repeated for the same template to analyze other CpGs in the same amplification product. Quantitative epigenotypes are obtained using this protocol in approximately 4 h for up to 96 DNA samples when bisulfite-treated DNA is already available as the starting material.

We developed a complete preprocessing pipeline for 450K BeadChip data using an original subset quantile normalization approach that performs both sample normalization and efficient Infinium I/II shift correction. The scripts, being freely available from the authors, will allow researchers to concentrate on the biological analysis of data, such as the identification of DNA methylation signatures.

In plants, genomic DNA methylation which contributes to development and stress responses can be actively removed by DEMETER-like DNA demethylases (DMLs). Indeed, in Arabidopsis DMLs are important for maternal imprinting and endosperm demethylation, but only a few studies demonstrate the developmental roles of active DNA demethylation conclusively in this plant. Here, we show a direct cause and effect relationship between active DNA demethylation mainly mediated by the tomato DML, SlDML2, and fruit ripeningan important developmental process unique to plants. RNAi SlDML2 knockdown results in ripening inhibition via hypermethylation and repression of the expression of genes encoding ripening transcription factors and rate-limiting enzymes of key biochemical processes such as carotenoid synthesis. Our data demonstrate that active DNA demethylation is central to the control of ripening in tomato.active DNA demethylation | DNA glycosylase lyase | epigenetic | tomato | fruit ripening G enomic DNA methylation is a major epigenetic mark that is instrumental to many aspects of chromatin function, including gene expression, transposon silencing, or DNA recombination (1-4). In plants, DNA methylation can occur at cytosine both in symmetrical (CG or CHG) and nonsymmetrical (CHH) contexts and is controlled by three classes of DNA methyltransferases, namely, the DNA Methyltransferase 1, Chromomethylases, and the Domain Rearranged Methyltransferases (5-7). Indeed, in all organisms, cytosine methylation can be passively lost after DNA replication in the absence of methyltransferase activity (1). However, plants can also actively demethylate DNA via the action of DNA GlycosylaseLyases, the so-called DEMETER-Like DNA demethylases (DMLs), that remove methylated cytosine, which is then replaced by a nonmethylated cytosine (8

Monozygotic (MZ) twin pair discordance for childhood-onset Type 1 Diabetes (T1D) is ∼50%, implicating roles for genetic and non-genetic factors in the aetiology of this complex autoimmune disease. Although significant progress has been made in elucidating the genetics of T1D in recent years, the non-genetic component has remained poorly defined. We hypothesized that epigenetic variation could underlie some of the non-genetic component of T1D aetiology and, thus, performed an epigenome-wide association study (EWAS) for this disease. We generated genome-wide DNA methylation profiles of purified CD14+ monocytes (an immune effector cell type relevant to T1D pathogenesis) from 15 T1D–discordant MZ twin pairs. This identified 132 different CpG sites at which the direction of the intra-MZ pair DNA methylation difference significantly correlated with the diabetic state, i.e. T1D–associated methylation variable positions (T1D–MVPs). We confirmed these T1D–MVPs display statistically significant intra-MZ pair DNA methylation differences in the expected direction in an independent set of T1D–discordant MZ pairs (P = 0.035). Then, to establish the temporal origins of the T1D–MVPs, we generated two further genome-wide datasets and established that, when compared with controls, T1D–MVPs are enriched in singletons both before (P = 0.001) and at (P = 0.015) disease diagnosis, and also in singletons positive for diabetes-associated autoantibodies but disease-free even after 12 years follow-up (P = 0.0023). Combined, these results suggest that T1D–MVPs arise very early in the etiological process that leads to overt T1D. Our EWAS of T1D represents an important contribution toward understanding the etiological role of epigenetic variation in type 1 diabetes, and it is also the first systematic analysis of the temporal origins of disease-associated epigenetic variation for any human complex disease.

Allergic diseases are on the rise in the Western world and well-known allergy-protecting and -driving factors such as microbial and dietary exposure, pollution and smoking mediate their influence through alterations of the epigenetic landscape. Here, we review key facts on the involvement of epigenetic modifications in allergic diseases and summarize and critically evaluate the lessons learned from epigenome-wide association studies. We show the potential of epigenetic changes for various clinical applications: as diagnostic tools, to assess tolerance following immunotherapy or possibly predict the success of therapy at an early time point. Furthermore, new technological advances such as epigenome editing and DNAzymes will allow targeted alterations of the epigenome in the future and provide novel therapeutic tools.

The Human Epigenome Project aims to identify, catalogue, and interpret genome-wide DNA methylation phenomena. Occurring naturally on cytosine bases at cytosine–guanine dinucleotides, DNA methylation is intimately involved in diverse biological processes and the aetiology of many diseases. Differentially methylated cytosines give rise to distinct profiles, thought to be specific for gene activity, tissue type, and disease state. The identification of such methylation variable positions will significantly improve our understanding of genome biology and our ability to diagnose disease. Here, we report the results of the pilot study for the Human Epigenome Project entailing the methylation analysis of the human major histocompatibility complex. This study involved the development of an integrated pipeline for high-throughput methylation analysis using bisulphite DNA sequencing, discovery of methylation variable positions, epigenotyping by matrix-assisted laser desorption/ionisation mass spectrometry, and development of an integrated public database available at http://www.epigenome.org. Our analysis of DNA methylation levels within the major histocompatibility complex, including regulatory exonic and intronic regions associated with 90 genes in multiple tissues and individuals, reveals a bimodal distribution of methylation profiles (i.e., the vast majority of the analysed regions were either hypo- or hypermethylated), tissue specificity, inter-individual variation, and correlation with independent gene expression data.