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Briefings in Bioinformatics May 2020Genome-wide DNA methylation studies have quickly expanded due to advances in next-generation sequencing techniques along with a wealth of computational tools to analyze... (Review)
Review
Genome-wide DNA methylation studies have quickly expanded due to advances in next-generation sequencing techniques along with a wealth of computational tools to analyze the data. Most of our knowledge about DNA methylation profiles, epigenetic heritability and the function of DNA methylation in plants derives from the model species Arabidopsis thaliana. There are increasingly many studies on DNA methylation in plants-uncovering methylation profiles and explaining variations in different plant tissues. Additionally, DNA methylation comparisons of different plant tissue types and dynamics during development processes are only slowly emerging but are crucial for understanding developmental and regulatory decisions. Translating this knowledge from plant model species to commercial crops could allow the establishment of new varieties with increased stress resilience and improved yield. In this review, we provide an overview of the most commonly applied bioinformatics tools for the analysis of DNA methylation data (particularly bisulfite sequencing data). The performances of a selection of the tools are analyzed for computational time and agreement in predicted methylated sites for A. thaliana, which has a smaller genome compared to the hexaploid bread wheat. The performance of the tools was benchmarked on five plant genomes. We give examples of applications of DNA methylation data analysis in crops (with a focus on cereals) and an outlook for future developments for DNA methylation status manipulations and data integration.
Topics: Computational Biology; DNA Methylation; DNA, Plant; Humans; Plants
PubMed: 31220217
DOI: 10.1093/bib/bbz039 -
Clinical Epigenetics Mar 2023Imprinting disorders (ImpDis) comprise diseases which are caused by aberrant regulation of monoallelically and parent-of-origin-dependent expressed genes. A...
BACKGROUND
Imprinting disorders (ImpDis) comprise diseases which are caused by aberrant regulation of monoallelically and parent-of-origin-dependent expressed genes. A characteristic molecular change in ImpDis patients is aberrant methylation signatures at disease-specific loci, without an obvious DNA change at the specific differentially methylated region (DMR). However, there is a growing number of reports on multilocus imprinting disturbances (MLIDs), i.e. aberrant methylation at different DMRs in the same patient. These MLIDs account for a significant number of patients with specific ImpDis, and several reports indicate a central role of pathogenic maternal effect variants in their aetiology by affecting the maturation of the oocyte and the early embryo. Though several studies on the prevalence and the molecular causes of MLID have been conducted, homogeneous datasets comprising both genomic and methylation data are still lacking.
RESULTS
Based on a cohort of 36 MLID patients, we here present both methylation data obtained from next-generation sequencing (NGS, ImprintSeq) approaches and whole-exome sequencing (WES). The compilation of methylation data did not reveal a disease-specific MLID episignature, and a predisposition for the phenotypic modification was not obvious as well. In fact, this lack of epigenotype-phenotype correlation might be related to the mosaic distribution of imprinting defects and their functional relevance in specific tissues.
CONCLUSIONS
Due to the higher sensitivity of NGS-based approaches, we suggest that ImprintSeq might be offered at reference centres in case of ImpDis patients with unusual phenotypes but MLID negative by conventional tests. By WES, additional MLID causes than the already known maternal effect variants could not be identified, neither in the patients nor in the maternal exomes. In cases with negative WES results, it is currently unclear to what extent either environmental factors or undetected genetic variants contribute to MLID.
Topics: DNA Methylation; Genomics; Genotype; High-Throughput Nucleotide Sequencing
PubMed: 36859312
DOI: 10.1186/s13148-023-01453-5 -
Cell Reports Methods Sep 2022Cell-free methylated DNA immunoprecipitation sequencing (cfMeDIP-seq) identifies genomic regions with DNA methylation, using a protocol adapted to work with low-input...
Cell-free methylated DNA immunoprecipitation sequencing (cfMeDIP-seq) identifies genomic regions with DNA methylation, using a protocol adapted to work with low-input DNA samples and with cell-free DNA (cfDNA). We developed a set of synthetic spike-in DNA controls for cfMeDIP-seq to provide a simple and inexpensive reference for quantitative normalization. We designed 54 DNA fragments with combinations of methylation status (methylated and unmethylated), fragment length (80 bp, 160 bp, 320 bp), G + C content (35%, 50%, 65%), and fraction of CpG dinucleotides within the fragment (1/80 bp, 1/40 bp, 1/20 bp). Using 0.01 ng of spike-in controls enables training a generalized linear model that absolutely quantifies methylated cfDNA in MeDIP-seq experiments. It mitigates batch effects and corrects for biases in enrichment due to known biophysical properties of DNA fragments and other technical biases.
Topics: Epigenome; Genomics; DNA Methylation; DNA; Cell-Free Nucleic Acids
PubMed: 36160046
DOI: 10.1016/j.crmeth.2022.100294 -
RNA (New York, N.Y.) Nov 2023U7 snRNP is a multisubunit endonuclease required for 3' end processing of metazoan replication-dependent histone pre-mRNAs. In contrast to the spliceosomal snRNPs, U7...
U7 snRNP is a multisubunit endonuclease required for 3' end processing of metazoan replication-dependent histone pre-mRNAs. In contrast to the spliceosomal snRNPs, U7 snRNP lacks the Sm subunits D1 and D2 and instead contains two related proteins, Lsm10 and Lsm11. The remaining five subunits of the U7 heptameric Sm ring, SmE, F, G, B, and D3, are shared with the spliceosomal snRNPs. The pathway that assembles the unique ring of U7 snRNP is unknown. Here, we show that a heterodimer of Lsm10 and Lsm11 tightly interacts with the methylosome, a complex of the arginine methyltransferase PRMT5, MEP50, and pICln known to methylate arginines in the carboxy-terminal regions of the Sm proteins B, D1, and D3 during the spliceosomal Sm ring assembly. Both biochemical and cryo-EM structural studies demonstrate that the interaction is mediated by PRMT5, which binds and methylates two arginine residues in the amino-terminal region of Lsm11. Surprisingly, PRMT5 also methylates an amino-terminal arginine in SmE, a subunit that does not undergo this type of modification during the biogenesis of the spliceosomal snRNPs. An intriguing possibility is that the unique methylation pattern of Lsm11 and SmE plays a vital role in the assembly of the U7 snRNP.
Topics: Animals; Ribonucleoprotein, U7 Small Nuclear; Methylation; Ribonucleoproteins, Small Nuclear; Histones; Arginine
PubMed: 37562960
DOI: 10.1261/rna.079709.123 -
Protein Science : a Publication of the... May 2022Actin histidine N -methylation by histidine methyltransferase SETD3 plays an important role in human biology and diseases. Here, we report integrated synthetic,...
Actin histidine N -methylation by histidine methyltransferase SETD3 plays an important role in human biology and diseases. Here, we report integrated synthetic, biocatalytic, biostructural, and computational analyses on human SETD3-catalyzed methylation of actin peptides possessing histidine and its structurally and chemically diverse mimics. Our enzyme assays supported by biostructural analyses demonstrate that SETD3 has a broader substrate scope beyond histidine, including N-nucleophiles on the aromatic and aliphatic side chains. Quantum mechanical/molecular mechanical molecular dynamics and free-energy simulations provide insight into binding geometries and the free energy barrier for the enzymatic methyl transfer to histidine mimics, further supporting experimental data that histidine is the superior SETD3 substrate over its analogs. This work demonstrates that human SETD3 has a potential to catalyze efficient methylation of several histidine mimics, overall providing mechanistic, biocatalytic, and functional insight into actin histidine methylation by SETD3.
Topics: Actins; Histidine; Histone Methyltransferases; Humans; Methylation; Methyltransferases
PubMed: 35481649
DOI: 10.1002/pro.4305 -
PloS One 2022In humans, the nc886 locus is a polymorphically imprinted metastable epiallele. Periconceptional conditions have an effect on the methylation status of nc886, and...
BACKGROUND
In humans, the nc886 locus is a polymorphically imprinted metastable epiallele. Periconceptional conditions have an effect on the methylation status of nc886, and further, this methylation status is associated with health outcomes in later life, in line with the Developmental Origins of Health and Disease (DOHaD) hypothesis. Animal models would offer opportunities to study the associations between periconceptional conditions, nc886 methylation status and metabolic phenotypes further. Thus, we set out to investigate the methylation pattern of the nc886 locus in non-human mammals.
DATA
We obtained DNA methylation data from the data repository GEO for mammals, whose nc886 gene included all three major parts of nc886 and had sequency similarity of over 80% with the human nc886. Our final sample set consisted of DNA methylation data from humans, chimpanzees, bonobos, gorillas, orangutangs, baboons, macaques, vervets, marmosets and guinea pigs.
RESULTS
In human data sets the methylation pattern of nc886 locus followed the expected bimodal distribution, indicative of polymorphic imprinting. In great apes, we identified a unimodal DNA methylation pattern with 50% methylation level in all individuals and in all subspecies. In Old World monkeys, the between individual variation was greater and methylation on average was close to 60%. In guinea pigs the region around the nc886 homologue was non-methylated. Results obtained from the sequence comparison of the CTCF binding sites flanking the nc886 gene support the results on the DNA methylation data.
CONCLUSIONS
Our results indicate that unlike in humans, nc886 is not a polymorphically imprinted metastable epiallele in non-human primates or in guinea pigs, thus implying that animal models are not applicable for nc886 research. The obtained data suggests that the nc886 region may be classically imprinted in great apes, and potentially also in Old World monkeys, but not in guinea pigs.
Topics: Animals; Binding Sites; DNA Methylation; Genomic Imprinting; Guinea Pigs; Mammals
PubMed: 35294436
DOI: 10.1371/journal.pone.0261481 -
BMC Musculoskeletal Disorders Aug 2022Congenital scoliosis (CS) is a congenital deformity of the spine resulting from abnormal and asymmetrical development of vertebral bodies during pregnancy. However, the...
BACKGROUND
Congenital scoliosis (CS) is a congenital deformity of the spine resulting from abnormal and asymmetrical development of vertebral bodies during pregnancy. However, the etiology and mechanism of CS remain unclear. Epigenetics is the study of heritable variations in gene expression outside of changes in nucleotide sequence. Among these, DNA methylation was described first and is the most characteristic and most stable epigenetic mechanism. Therefore, in this study, we aim to explore the association between genome methylation and CS which are not been studied before.
METHODS
Two pairs of monozygotic twins were included, with each pair involving one individual with and one without CS. Agilent SureSelect XT Human Methyl-Sequencing was used for genome methylation sequencing. MethylTarget was used to detect methylation levels in target regions. Immunohistochemistry was performed to visualize expression of associated genes in candidate regions.
RESULTS
A total of 75 differentially methylated regions were identified, including 24 with an increased methylation level and 51 with a decreased methylation level in the CS group. Nine of the differentially methylated regions were selected (TNS3, SEMAC3, GPR124, MEST, DLK1, SNTG1, PPIB, DEF8, and GRHL2). The results showed that the methylation level of the promoter region of TNS3 was 0.72 ± 0.08 in the CS group and 0.43 ± 0.06 in the control group (p = 0.00070 < 0.01). There was no significant difference in the degree of methylation of SEMAC3, GPR124, MEST, DLK1, SNTG1, PPIB, DEF8, or GRHL2 between the two groups. Immunohistochemistry showed significantly decreased TNS3 expression in the cartilage of the articular process in CS (CS: 0.011 ± 0.002; control: 0.018 ± 0.006, P = 0.003 < 0.01).
CONCLUSION
Compared with the control group, high-level methylation of the TNS3 promoter region and low TNS3 expression in the cartilage layer of the articular process characterize CS. Thus, DNA methylation and TNS3 may play important roles in the pathogenesis of CS.
Topics: Base Sequence; DNA Methylation; Epigenesis, Genetic; Female; Humans; Pregnancy; Scoliosis; Tensins
PubMed: 35987623
DOI: 10.1186/s12891-022-05730-x -
Clinical Epigenetics Aug 2023Loss of epigenetic control is a hallmark of aging. Among the most prominent roles of epigenetic mechanisms is the inactivation of one of two copies of the X chromosome...
BACKGROUND
Loss of epigenetic control is a hallmark of aging. Among the most prominent roles of epigenetic mechanisms is the inactivation of one of two copies of the X chromosome in females through DNA methylation. Hence, age-related disruption of X-chromosome inactivation (XCI) may contribute to the aging process in women.
METHODS
We analyzed 9,777 CpGs on the X chromosome in whole blood samples from 2343 females and 1688 males (Illumina 450k methylation array) and replicated findings in duplicate using one whole blood and one purified monocyte data set (in total, 991/924 females/males). We used double generalized linear models to detect age-related differentially methylated CpGs (aDMCs), whose mean methylation level differs with age, and age-related variably methylated CpGs (aVMCs), whose methylation level becomes more variable with age.
RESULTS
In females, aDMCs were relatively uncommon (n = 33) and preferentially occurred in regions known to escape XCI. In contrast, many CpGs (n = 987) were found to display an increased variance with age (aVMCs). Of note, the replication rate of aVMCs was also high in purified monocytes (94%), indicating an independence of cell composition. aVMCs accumulated in CpG islands and regions subject to XCI suggesting that they stemmed from the inactive X. In males, carrying an active copy of the X chromosome only, aDMCs (n = 316) were primarily driven by cell composition, while aVMCs replicated well (95%) but were infrequent (n = 37).
CONCLUSIONS
Our results imply that age-related DNA methylation differences at the inactive X chromosome are dominated by the accumulation of variability.
Topics: Male; Female; Humans; DNA Methylation; X Chromosome; X Chromosome Inactivation; Aging; Epigenesis, Genetic
PubMed: 37626340
DOI: 10.1186/s13148-023-01549-y -
Human Molecular Genetics Oct 2017Recent advances in cell-type deconvolution approaches are adding to our understanding of the biology underlying disease development and progression. DNA methylation... (Review)
Review
Recent advances in cell-type deconvolution approaches are adding to our understanding of the biology underlying disease development and progression. DNA methylation (DNAm) can be used as a biomarker of cell types, and through deconvolution approaches, to infer underlying cell type proportions. Cell-type deconvolution algorithms have two main categories: reference-based and reference-free. Reference-based algorithms are supervised methods that determine the underlying composition of cell types within a sample by leveraging differentially methylated regions (DMRs) specific to cell type, identified from DNAm measures of purified cell populations. Reference-free algorithms are unsupervised methods for use when cell-type specific DMRs are not available, allowing scientists to estimate putative cellular proportions or control for potential confounding from cell type. Reference-based deconvolution is typically applied to blood samples and has potentiated our understanding of the relation between immune profiles and disease by allowing estimation of immune cell proportions from archival DNA. Bioinformatic analyses using DNAm to infer immune cell proportions, part of a new field known as Immunomethylomics, provides a new direction for consideration in epigenome wide association studies (EWAS).
Topics: Algorithms; Animals; Computational Biology; Computer Simulation; DNA Methylation; Genome-Wide Association Study; Humans; Sequence Analysis, DNA
PubMed: 28977446
DOI: 10.1093/hmg/ddx275 -
Toxicology Jun 2021Between 1990 and 2020, our understanding of the significance of arsenic biomethylation changed in remarkable ways. At the beginning of this period, the conversion of... (Review)
Review
Between 1990 and 2020, our understanding of the significance of arsenic biomethylation changed in remarkable ways. At the beginning of this period, the conversion of inorganic arsenic into mono- and di-methylated metabolites was viewed primarily as a process that altered the kinetic behavior of arsenic. By increasing the rate of clearance of arsenic, the formation of methylated metabolites reduced exposure to this toxin; that is, methylation was detoxification. By 2020, it was clear that at least some of the toxic effects associated with As exposure depended on formation of methylated metabolites containing trivalent arsenic. Because the trivalent oxidation state of arsenic is associated with increased potency as a cytotoxin and clastogen, these findings were consistent with methylation-related changes in the dynamic behavior of arsenic. That is, methylation was activation. Our current understanding of the role of methylation as a modifier of kinetic and dynamic behaviors of arsenic is the product of research at molecular, cellular, organismic, and population levels. This information provides a basis for refining our estimates of risk associated with long term exposure to inorganic arsenic in environmental media, food, and water. This report summarizes the growth of our knowledge of enzymatically catalyzed methylation of arsenic over this period and considers the prospects for new discoveries.
Topics: Animals; Arsenic; Arsenic Poisoning; Environmental Exposure; Humans; Methylation; Oxidation-Reduction
PubMed: 33901604
DOI: 10.1016/j.tox.2021.152800