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Abstract Background Acute myeloid leukemia (AML) is a heterogeneous disease with a poor prognosis. Dysregulation of the epigenetic machinery is a significant contributor to disease development. Some AML patients benefit from treatment with hypomethylating agents (HMAs), but no predictive biomarkers for therapy response exist. Here, we investigated whether unbiased genome-wide assessment of pre-treatment DNA-methylation profiles in AML bone marrow blasts can help to identify patients who will achieve a remission after an azacytidine-containing induction regimen. Results A total of n = 155 patients with newly diagnosed AML treated in the AMLSG 12-09 trial were randomly assigned to a screening and a refinement and validation cohort. The cohorts were divided according to azacytidine-containing induction regimens and response status. Methylation status was assessed for 664,227 500-bp-regions using methyl-CpG immunoprecipitation-seq, resulting in 1755 differentially methylated regions (DMRs). Top regions were distilled and included genes such as WNT10A and GATA3. 80% of regions identified as a hit were represented on HumanMethlyation 450k Bead Chips. Quantitative methylation analysis confirmed 90% of these regions (36 of 40 DMRs). A classifier was trained using penalized logistic regression and fivefold cross validation containing 17 CpGs. Validation based on mass spectra generated by MALDI-TOF failed (AUC 0.59). However, discriminative ability was maintained by adding neighboring CpGs. A recomposed classifier with 12 CpGs resulted in an AUC of 0.77. When evaluated in the non-azacytidine containing group, the AUC was 0.76. Conclusions Our analysis evaluated the value of a whole genome methyl-CpG screening assay for the identification of informative methylation changes. We also compared the informative content and discriminatory power of regions and single CpGs for predicting response to therapy. The relevance of the identified DMRs is supported by their association with key regulatory processes of oncogenic transformation and support the idea of relevant DMRs being enriched at distinct loci rather than evenly distribution across the genome. Predictive response to therapy could be established but lacked specificity for treatment with azacytidine. Our results suggest that a predictive epigenotype carries its methylation information at a complex, genome-wide level, that is confined to regions, rather than to single CpGs. With increasing application of combinatorial regimens, response prediction may become even more complicated.

Background: Acute myeloid leukemia (AML) is a heterogeneous disease with a poor prognosis. Dysregulation of the epigenetic machinery is a significant contributor to disease development. Some AML patients benefit from treatment with hypomethylating agents (HMAs), but no predictive biomarkers for therapy response exist. Here, we investigated whether unbiased genome-wide assessment of pre-treatment DNA-methylation profiles in AML bone marrow blasts can help to identify patients who will achieve a remission after an azacytidine-containing induction regimen. Results: A total of n = 155 patients with newly diagnosed AML treated in the AMLSG 12-09 trial were randomly assigned to a screening and a refinement and validation cohort. The cohorts were divided according to azacytidine-containing induction regimens and response status. Methylation status was assessed for 664,227 500-bp-regions using methyl-CpG immunoprecipitation-seq, resulting in 1755 differentially methylated regions (DMRs). Top regions were distilled and included genes such as WNT10A and GATA3. 80% of regions identified as a hit were represented on HumanMethlyation 450k Bead Chips. Quantitative methylation analysis confirmed 90% of these regions (36 of 40 DMRs). A classifier was trained using penalized logistic regression and fivefold cross validation containing 17 CpGs. Validation based on mass spectra generated by MALDI-TOF failed (AUC 0.59). However, discriminative ability was maintained by adding neighboring CpGs. A recomposed classifier with 12 CpGs resulted in an AUC of 0.77. When evaluated in the non-azacytidine containing group, the AUC was 0.76. Conclusions: Our analysis evaluated the value of a whole genome methyl-CpG screening assay for the identification of informative methylation changes. We also compared the informative content and discriminatory power of regions and single CpGs for predicting response to therapy. The relevance of the identified DMRs is supported by their association with key regulatory processes of oncogenic transformation and support the idea of relevant DMRs being enriched at distinct loci rather than evenly distribution across the genome. Predictive response to therapy could be established but lacked specificity for treatment with azacytidine. Our results suggest that a predictive epigenotype carries its methylation information at a complex, genome-wide level, that is confined to regions, rather than to single CpGs. With increasing application of combinatorial regimens, response prediction may become even more complicated. [ABSTRACT FROM AUTHOR]

The goal of this investigation was to determine whether there are alterations in DNA methylation patterns in children with autism spectrum disorder (ASD).Material and Methods: Controlled prospective observational case-control study. Within the ASD group, children were sub-classified based on the presence (AMR subgroup) or absence (ANMR subgroup) of neurodevelopmental regression during the first 2 years of life. We analyzed the global levels of DNA methylation, reflected in LINE-1, and the local DNA methylation pattern in two candidate genes, Neural Cell Adhesion Molecule (NCAM1) and Nerve Growth Factor (NGF) that, according to our previous studies, might be associated to an increased risk for ASD. For this purpose, we utilized blood samples from pediatric patients with ASD (n = 53) and their corresponding controls (n = 45).Results: We observed a slight decrease in methylation levels of LINE-1 in the ASD group, compared to the control group. One of the CpG in LINE-1 (GenBank accession no.X58075, nucleotide position 329) was the main responsible for such reduction, highly significant in the ASD subgroup of children with AMR (p < 0.05). Furthermore, we detected higher NCAM1 methylation levels in ASD children, compared to healthy children (p < 0.001). The data, moreover, showed higher NGF methylation levels in the AMR subgroup, compared to the control group and the ANMR subgroup. These results are consistent with our prior study, in which lower plasma levels of NCAM1 and higher levels of NGF were found in the ANMR subgroup, compared to the subgroup that comprised neurotypically developing children.Conclusions: We have provided new clues about the epigenetic changes that occur in ASD, and suggest two potential epigenetic biomarkers that would facilitate the diagnosis of the disorder. We similarly present with evidence of a clear differentiation in DNA methylation between the ASD subgroups, with or without mental regression.

Microenvironment plays an important role in cancer development. We have reported that the cancer-associated stromal cells exhibit phenotypic and functional changes compared to stromal cells neighboring to normal tissues. However, the molecular mechanisms as well as the maintenance of these changes remain elusive. Here we showed that through co-culture with breast cancer cells for at least three to four passages, breast normal tissue-associated fibroblasts (NAFs) gained persistent activity for promoting cancer cell invasion, partly via up-regulating ADAM metallopeptidase with thrombospondin type 1 motif, 1 (ADAMTS1). Furthermore, we demonstrated that the DNA methylation pattern in the ADAMTS1 promoter has no alteration. Instead, the loss of EZH2 binding to the ADAMTS1 promoter and the resulting decrease of promoter-associated histone H3K27 methylation may account for the up-regulation of ADAMTS1. Importantly, the lack of EZH2 binding and the H3K27 methylation on the ADAMTS1 promoter were sustained in cancer cell-precocultured NAFs after removal of cancer cells. These results suggest that cancer cells are capable of inducing stromal fibroblasts to secrete ADAMTS1 persistently for their invasion and the effect is epigenetically inheritable.

Recent advances in sequencing technologies have improved contiguity of de novo genome assemblies. Nevertheless, the genomes of all non-haploid eukaryotic organisms remain unfinished, limiting understanding of genetic and structural variation in complex organisms. Herein, we report the methodology and analysis of a 100 % complete, telomere-to-telomere genome assembly of the eukaryote, Scenedesmus obliquus UTEX 3031 (DOE0152Z) with fully assembled and resolved haplotypes for 16 of 17 chromosomes. Inter-haplotype heterozygosity was significant on most chromosomes yet one chromosome pair (Chromosome 15) was found to contain nearly no heterozygosity, prohibiting full phasing of this chromosome. Analysis of the 5mC methylation patterns revealed divergence in active gene content across haplotypes. Assembly of fully resolved chromosome pairs enabled complete resolution of genomic rearrangements revealing significant heterozygosity of the haplotypes, the genomic basis of trait gain/loss, and evolutionary divergence across chromosome pairs. Further, when combined with 5mC methylation patterns, the assembly provides critical annotation information for genetic engineering approaches to achieve full knock-outs in allelic pairs. • A complete, gapless, phased, telomere-to-telomere diploid genome assembly of Scenedesmus obliquus UTEX 3031 (DOE0152Z) was constructed. • Inter-haplotype heterozygosity was significant on most chromosomes yet one chromosome pair was found to contain nearly no heterozygosity. • PacBio derived 5mC methylation data showed differential methylation in the promoter regions of allelic genes, suggesting functional divergence of the haplotypes. • Genetic (meiosis and flagella genes) and phenotypic (Gamete formation) evidence indicate sexual reproduction is occurring in Scenedesmus yet incipient sex chromosomes could not be identified. • The chromosome pairs likely originated from two different ancestral parents and is not the result of a whole genome duplication. [ABSTRACT FROM AUTHOR]

DNA methylation is involved in many different biological processes in the development and well-being of crop plants such as transposon activation, heterosis, environment-dependent transcriptome plasticity, aging, and many diseases. Whole-genome bisulfite sequencing is an excellent technology for detecting and quantifying DNA methylation patterns in a wide variety of species, but optimized data analysis pipelines exist only for a small number of species and are missing for many important crop plants. This is especially important as most existing benchmark studies have been performed on mammals with hardly any repetitive elements and without CHG and CHH methylation. Pipelines for the analysis of whole-genome bisulfite sequencing data usually consists of four steps: read trimming, read mapping, quantification of methylation levels, and prediction of differentially methylated regions (DMRs). Here we focus on read mapping, which is challenging because un-methylated cytosines are transformed to uracil during bisulfite treatment and to thymine during the subsequent polymerase chain reaction, and read mappers must be capable of dealing with this cytosine/thymine polymorphism. Several read mappers have been developed over the last years, with different strengths and weaknesses, but their performances have not been critically evaluated. Here, we compare eight read mappers: Bismark, BismarkBwt2, BSMAP, BS-Seeker2, Bwameth, GEM3, Segemehl, and GSNAP to assess the impact of the read-mapping results on the prediction of DMRs. We used simulated data generated from the genomes of Arabidopsis thaliana, Brassica napus, Glycine max, Solanum tuberosum, and Zea mays, monitored the effects of the bisulfite conversion rate, the sequencing error rate, the maximum number of allowed mismatches, as well as the genome structure and size, and calculated precision, number of uniquely mapped reads, distribution of the mapped reads, run time, and memory consumption as features for benchmarking the eight read mappers mentioned above. Furthermore, we validated our findings using real-world data of Glycine max and showed the influence of the mapping step on DMR calling in WGBS pipelines. We found that the conversion rate had only a minor impact on the mapping quality and the number of uniquely mapped reads, whereas the error rate and the maximum number of allowed mismatches had a strong impact and leads to differences of the performance of the eight read mappers. In conclusion, we recommend BSMAP which needs the shortest run time and yields the highest precision, and Bismark which requires the smallest amount of memory and yields precision and high numbers of uniquely mapped reads.

DNA methylation is involved in many different biological processes in the development and well-being of crop plants such as transposon activation, heterosis, environment-dependent transcriptome plasticity, aging, and many diseases. Whole-genome bisulfite sequencing is an excellent technology for detecting and quantifying DNA methylation patterns in a wide variety of species, but optimized data analysis pipelines exist only for a small number of species and are missing for many important crop plants. This is especially important as most existing benchmark studies have been performed on mammals with hardly any repetitive elements and without CHG and CHH methylation. Pipelines for the analysis of whole-genome bisulfite sequencing data usually consists of four steps: read trimming, read mapping, quantification of methylation levels, and prediction of differentially methylated regions (DMRs). Here we focus on read mapping, which is challenging because un-methylated cytosines are transformed to uracil during bisulfite treatment and to thymine during the subsequent polymerase chain reaction, and read mappers must be capable of dealing with this cytosine/thymine polymorphism. Several read mappers have been developed over the last years, with different strengths and weaknesses, but their performances have not been critically evaluated. Here, we compare eight read mappers: Bismark, BismarkBwt2, BSMAP, BS-Seeker2, Bwameth, GEM3, Segemehl, and GSNAP to assess the impact of the read-mapping results on the prediction of DMRs. We used simulated data generated from the genomes of Arabidopsis thaliana , Brassica napus , Glycine max , Solanum tuberosum , and Zea mays , monitored the effects of the bisulfite conversion rate, the sequencing error rate, the maximum number of allowed mismatches, as well as the genome structure and size, and calculated precision, number of uniquely mapped reads, distribution of the mapped reads, run time, and memory consumption as features for benchmarking the eight read mappers mentioned above. Furthermore, we validated our findings using real-world data of Glycine max and showed the influence of the mapping step on DMR calling in WGBS pipelines. We found that the conversion rate had only a minor impact on the mapping quality and the number of uniquely mapped reads, whereas the error rate and the maximum number of allowed mismatches had a strong impact and leads to differences of the performance of the eight read mappers. In conclusion, we recommend BSMAP which needs the shortest run time and yields the highest precision, and Bismark which requires the smallest amount of memory and yields precision and high numbers of uniquely mapped reads. [ABSTRACT FROM AUTHOR]

The modulation of the activity of DNA methyltransferases (DNMTs) represents a crucial epigenetic mechanism affecting gene expressions or DNA repair mechanisms in the cells. Aberrant modifications in the function of DNMTs are a fundamental event and part of the pathogenesis of human cancer. Phytochemicals, which are biosynthesized in plants in the form of secondary metabolites, represent an important source of biomolecules with pleiotropic effects and thus provide a wide range of possible clinical applications. It is well documented that phytochemicals demonstrate significant anticancer properties, and in this regard, rapid development within preclinical research is encouraging. Phytochemicals affect several epigenetic molecular mechanisms, including DNA methylation patterns such as the hypermethylation of tumor-suppressor genes and the global hypomethylation of oncogenes, that are specific cellular signs of cancer development and progression. This review will focus on the latest achievements in using plant-derived compounds and plant-based diets targeting epigenetic regulators and modulators of gene transcription in preclinical and clinical research in order to generate novel anticancer drugs as sensitizers for conventional therapy or compounds suitable for the chemoprevention clinical setting in at-risk individuals. In conclusion, indisputable anticancer activities of dietary phytochemicals linked with proper regulation of DNA methylation status have been described. However, precisely designed and well-controlled clinical studies are needed to confirm their beneficial epigenetic effects after long-term consumption in humans.

DNA methylation has been proved to play important roles in cell development and complex diseases through comparative studies of DNA methylation profiles across different tissues and samples. Current studies indicate that the regulation of DNA methylation to gene expression depends on the genomic locations of CpGs. Common DNA methylation patterns shared across different cell types and tissues are abundant, and they are likely involved in the basic functions of cell development, such as housekeeping functions. By way of contrast, cell type-specific DNA methylation patterns show distinct functional relevance with cell type specificity. Additionally, abnormal DNA methylation patterns are extensively involved in tumour development. Pan-cancer methylation patterns reveal common mechanisms and new similarities of different cancers, while cancer-specific patterns are relating to tumour heterogeneity and patient survival. Moreover, DNA methylation patterns in specific cancer are relevant with diverse regulatory elements such as enhancers and long non-coding RNAs. In this review, we survey the recent advances on DNA methylation patterns in normal or tumour states to illustrate their potential roles in cell development and cell canceration. [ABSTRACT FROM AUTHOR]

Background: Bisulphite sequencing enables the detection of cytosine methylation. The sequence of the methylation states of cytosines on any given read forms a methylation pattern that carries substantially more information than merely studying the average methylation level at individual positions. In order to understand better the complexity of DNA methylation landscapes in biological samples, it is important to study the diversity of these methylation patterns. However, the accurate quantification of methylation patterns is subject to sequencing errors and spurious signals due to incomplete bisulphite conversion of cytosines. Results: A statistical model is developed which accounts for the distribution of DNA methylation patterns at any given locus. The model incorporates the effects of sequencing errors and spurious reads, and enables estimation of the true underlying distribution of methylation patterns. Conclusions: Calculation of the estimated distribution over methylation patterns is implemented in the R Bioconductor package MPFE. Source code and documentation of the package are also available for download at http://bioconductor.org/packages/3.0/bioc/html/MPFE.html. [ABSTRACT FROM AUTHOR]

The modulation of the activity of DNA methyltransferases (DNMTs) represents a crucial epigenetic mechanism affecting gene expressions or DNA repair mechanisms in the cells. Aberrant modifications in the function of DNMTs are a fundamental event and part of the pathogenesis of human cancer. Phytochemicals, which are biosynthesized in plants in the form of secondary metabolites, represent an important source of biomolecules with pleiotropic effects and thus provide a wide range of possible clinical applications. It is well documented that phytochemicals demonstrate significant anticancer properties, and in this regard, rapid development within preclinical research is encouraging. Phytochemicals affect several epigenetic molecular mechanisms, including DNA methylation patterns such as the hypermethylation of tumor-suppressor genes and the global hypomethylation of oncogenes, that are specific cellular signs of cancer development and progression. This review will focus on the latest achievements in using plant-derived compounds and plant-based diets targeting epigenetic regulators and modulators of gene transcription in preclinical and clinical research in order to generate novel anticancer drugs as sensitizers for conventional therapy or compounds suitable for the chemoprevention clinical setting in at-risk individuals. In conclusion, indisputable anticancer activities of dietary phytochemicals linked with proper regulation of DNA methylation status have been described. However, precisely designed and well-controlled clinical studies are needed to confirm their beneficial epigenetic effects after long-term consumption in humans. [ABSTRACT FROM AUTHOR]