scholarly journals Dynamic Methylome Modification associated with mutational signatures in ageing and etiology of disease

2020 ◽  
Author(s):  
Gayathri Kumar ◽  
Kashyap Krishnasamy ◽  
Naseer Pasha ◽  
Naveenkumar Nagarajan ◽  
Bhavika Mam ◽  
...  
Keyword(s):  
Transcriptional Control ◽  
Cpg Islands ◽  
Single Nucleotide Variants ◽  
Mutational Signatures ◽  
Cpg Site ◽  
Disease Networks ◽  
System Disease ◽  
Genome Methylation ◽  
Differentially Methylated Genes ◽  
Over Time

AbstractEpigenetic markers and reversible change in the loci of genes regulating critical cell processes, have recently emerged as important biomarkers in the study of disease pathology. The epigenetic changes that accompany ageing in the context of population health risk needs to be explored. Additionally, the interplay between dynamic methylation changes that accompany ageing in relation to mutations that accrue in an individual’s genome over time needs further investigation. Our current study captures the role for variants acting in concurrence with dynamic methylation in an individual analysed over time, in essence reflecting the genome-epigenome interplay, affecting biochemical pathways controlling physiological processes. In our current study, we completed the whole genome methylation and variant analysis in one Zoroastrian-Parsi non-smoking individual, collected at an interval of 12 years apart (at 53 and 65 years respectively) (ZPMetG-Hv2a-1A (old, t0), ZPMetG-Hv2a-1B (recent, t0+12)) using Grid-ion Nanopore sequencer at 13X genome coverage overall. We further identified the Single Nucleotide Variants (SNVs) and indels in known CpG islands by employing GATK and MuTect2 variant caller pipeline with GRCh37 (patch 13) human genome as the reference.We found 5258 disease relevant genes differentially methylated across this individual over 12 years. Employing the GATK pipeline, we found 24,948 genes corresponding to 4,58,148 variants specific to ZPMetG-Hv2a-1B, indicative of variants that accrued over time. 242/24948 gene variants occurred within the CpG regions that were differentially methylated with 67/247 exactly occurring on the CpG site. Our analysis yielded a critical cluster of 10 genes which are significantly methylated and have variants at the CpG site or the ±4bp CpG region window. KEGG enrichment network analysis, Reactome and STRING analysis of mutational signatures of gene specific variants indicated an impact in biological process regulating immune system, disease networks implicated in cancer and neurodegenerative diseases and transcriptional control of processes regulating cellular senescence and longevity.Our current study provides an understanding of the ageing methylome over time through the interplay between differentially methylated genes and variants in the etiology of disease.

scholarly journals Temporal changes in DNA methylation and RNA expression in a small song bird: within- and between-tissue comparisons

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Melanie Lindner ◽  
Irene Verhagen ◽  
Heidi M. Viitaniemi ◽  
Veronika N. Laine ◽  
Marcel E. Visser ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Environmental Conditions ◽  
Brain Regions ◽  
Temporal Changes ◽  
Egg Laying ◽  
Gene Body ◽  
Cpg Site ◽  
Repeated Sampling ◽  
Over Time

Abstract Background DNA methylation is likely a key mechanism regulating changes in gene transcription in traits that show temporal fluctuations in response to environmental conditions. To understand the transcriptional role of DNA methylation we need simultaneous within-individual assessment of methylation changes and gene expression changes over time. Within-individual repeated sampling of tissues, which are essential for trait expression is, however, unfeasible (e.g. specific brain regions, liver and ovary for reproductive timing). Here, we explore to what extend between-individual changes in DNA methylation in a tissue accessible for repeated sampling (red blood cells (RBCs)) reflect such patterns in a tissue unavailable for repeated sampling (liver) and how these DNA methylation patterns are associated with gene expression in such inaccessible tissues (hypothalamus, ovary and liver). For this, 18 great tit (Parus major) females were sacrificed at three time points (n = 6 per time point) throughout the pre-laying and egg-laying period and their blood, hypothalamus, ovary and liver were sampled. Results We simultaneously assessed DNA methylation changes (via reduced representation bisulfite sequencing) and changes in gene expression (via RNA-seq and qPCR) over time. In general, we found a positive correlation between changes in CpG site methylation in RBCs and liver across timepoints. For CpG sites in close proximity to the transcription start site, an increase in RBC methylation over time was associated with a decrease in the expression of the associated gene in the ovary. In contrast, no such association with gene expression was found for CpG site methylation within the gene body or the 10 kb up- and downstream regions adjacent to the gene body. Conclusion Temporal changes in DNA methylation are largely tissue-general, indicating that changes in RBC methylation can reflect changes in DNA methylation in other, often less accessible, tissues such as the liver in our case. However, associations between temporal changes in DNA methylation with changes in gene expression are mostly tissue- and genomic location-dependent. The observation that temporal changes in DNA methylation within RBCs can relate to changes in gene expression in less accessible tissues is important for a better understanding of how environmental conditions shape traits that temporally change in expression in wild populations.

scholarly journals Mutational signatures are jointly shaped by DNA damage and repair

2019 ◽  
Author(s):  
Nadezda V Volkova ◽  
Bettina Meier ◽  
Víctor González-Huici ◽  
Simone Bertolini ◽  
Santiago Gonzalez ◽  
...  
Keyword(s):  
Dna Damage ◽  
Dna Repair ◽  
Excision Repair ◽  
Dna Lesions ◽  
Single Nucleotide Variants ◽  
Mutational Signatures ◽  
Experimental Conditions ◽  
Repair Deficiency ◽  
Dna Repair Deficiency ◽  
Mutation Spectra

AbstractMutations arise when DNA lesions escape DNA repair. To delineate the contributions of DNA damage and DNA repair deficiency to mutagenesis we sequenced 2,717 genomes of wild-type and 53 DNA repair defective C. elegans strains propagated through several generations or exposed to 11 genotoxins at multiple doses. Combining genotoxin exposure and DNA repair deficiency alters mutation rates or leads to unexpected mutation spectra in nearly 40% of all experimental conditions involving 9/11 of genotoxins tested and 32/53 genotypes. For 8/11 genotoxins, signatures change in response to more than one DNA repair deficiency, indicating that multiple genes and pathways are involved in repairing DNA lesions induced by one genotoxin. For many genotoxins, the majority of observed single nucleotide variants results from error-prone translesion synthesis, rather than primary mutagenicity of altered nucleotides. Nucleotide excision repair mends the vast majority of genotoxic lesions, preventing up to 99% of mutations. Analogous mutagenic DNA damage-repair interactions can also be found in cancers, but, except for rare cases, effects are weak owing to the unknown histories of genotoxic exposures and DNA repair status. Overall, our data underscore that mutation spectra are joint products of DNA damage and DNA repair and imply that mutational signatures computationally derived from cancer genomes are more variable than currently anticipated.

scholarly journals Association of mutation signature effectuating processes with mutation hotspots in driver genes and non-coding regions

2022 ◽  
Vol 13 (1) ◽  
Author(s):  
John K. L. Wong ◽  
Christian Aichmüller ◽  
Markus Schulze ◽  
Mario Hlevnjak ◽  
Shaymaa Elgaafary ◽  
...  
Keyword(s):  
Somatic Hypermutation ◽  
Regulatory Elements ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Driver Mutations ◽  
Base Substitution ◽  
Single Nucleotide Variants ◽  
Mutational Signatures ◽  
Coding Regions ◽  
Mutational Hotspots

AbstractCancer driving mutations are difficult to identify especially in the non-coding part of the genome. Here, we present sigDriver, an algorithm dedicated to call driver mutations. Using 3813 whole-genome sequenced tumors from International Cancer Genome Consortium, The Cancer Genome Atlas Program, and a childhood pan-cancer cohort, we employ mutational signatures based on single-base substitution in the context of tri- and penta-nucleotide motifs for hotspot discovery. Knowledge-based annotations on mutational hotspots reveal enrichment in coding regions and regulatory elements for 6 mutational signatures, including APOBEC and somatic hypermutation signatures. APOBEC activity is associated with 32 hotspots of which 11 are known and 11 are putative regulatory drivers. Somatic single nucleotide variants clusters detected at hypermutation-associated hotspots are distinct from translocation or gene amplifications. Patients carrying APOBEC induced PIK3CA driver mutations show lower occurrence of signature SBS39. In summary, sigDriver uncovers mutational processes associated with known and putative tumor drivers and hotspots particularly in the non-coding regions of the genome.

Somatic mutations in single human cardiomyocytes demonstrate accelerated age-related DNA damage and cell fusion

2020 ◽  
Author(s):  
Christopher Walsh ◽  
Sangita Choudhury ◽  
August Huang ◽  
Junho Junho Kim ◽  
Katherine Morillo ◽  
...  
Keyword(s):  
Cell Fusion ◽  
Excision Repair ◽  
Single Nucleotide Variants ◽  
Mutational Signatures ◽  
Human Cardiomyocytes ◽  
Age Related ◽  
Lineage Tree ◽  
Dividing Cells ◽  
Heart Muscle Cells ◽  
Genetic Compensation

Abstract The accumulation of somatic DNA mutations is a hallmark of aging in many dividing cells and contributes to carcinogenesis. Here we survey the landscape of somatic single-nucleotide variants (sSNVs) in heart muscle cells (cardiomyocytes) which normally do not proliferate but often become polyploid with age. Using single-cell whole-genome sequencing we analyzed sSNVs from 48 single cardiomyocytes from 10 healthy individuals (ages 0.4 - 82 yrs.). Cardiomyocyte sSNVs increased strikingly with age, at rates faster than reported in many dividing cells, or in non-dividing neurons. Analysis of nucleotide substitution patterns revealed age-related “clock-like” mutational signatures resembling those previously described. However, cardiomyocytes showed distinct mutational signatures that are rare or absent in other cells, implicating failed nucleotide excision repair of oxidative damage and defective mismatch repair (MMR) during aging. A lineage tree of cardiomyocytes, constructed using clonal sSNVs, revealed that some tetraploid (10%) and most cardiomyocytes with higher ploidy (>60%) derive from distinct clonal origins, implicating cell fusion as a mechanism contributing to many polyploid cardiomyocytes. Since age-accumulated sSNVs create dozens of damaging exonic mutations, cell fusion to form multiploid cardiomyocytes may represent an evolutionary mechanism of cellular genetic compensation that minimizes complete knockout of essential genes during aging. The rates and patterns of accumulation of cardiac mutations provide a paradigm to understand the influence of genomic aging on age-related heart disease.

scholarly journals Genome aging: somatic mutation in the brain links age-related decline with disease and nominates pathogenic mechanisms

2019 ◽  
Vol 28 (R2) ◽  
pp. R197-R206 ◽  
Author(s):  
Michael A Lodato ◽  
Christopher A Walsh
Keyword(s):  
Human Brain ◽  
Somatic Mutation ◽  
Somatic Mutations ◽  
Late Onset ◽  
Whole Genome ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Age Related ◽  
The Brain ◽  
Over Time

AbstractAging is a mysterious process, not only controlled genetically but also subject to random damage that can accumulate over time. While DNA damage and subsequent mutation in somatic cells were first proposed as drivers of aging more than 60 years ago, whether and to what degree these processes shape the neuronal genome in the human brain could not be tested until recent technological breakthroughs related to single-cell whole-genome sequencing. Indeed, somatic single-nucleotide variants (SNVs) increase with age in the human brain, in a somewhat stochastic process that may nonetheless be controlled by underlying genetic programs. Evidence from the literature suggests that in addition to demonstrated increases in somatic SNVs during aging in normal brains, somatic mutation may also play a role in late-onset, sporadic neurodegenerative diseases, such as Alzheimer’s disease and Parkinson’s disease. In this review, we will discuss somatic mutation in the human brain, mechanisms by which somatic mutations occur and can be controlled, and how this process can impact human health.

scholarly journals Genome-wide DNA methylation profiles of porcine ovaries in estrus and proestrus

2018 ◽  
Vol 50 (9) ◽  
pp. 714-723 ◽  
Author(s):  
Xiaolong Zhou ◽  
Songbai Yang ◽  
Feifei Yan ◽  
Ke He ◽  
Ayong Zhao
Keyword(s):  
Dna Methylation ◽  
Epigenetic Modification ◽  
Cpg Islands ◽  
Biological Processes ◽  
Hormone Regulation ◽  
Methylated Dna ◽  
Coding Regions ◽  
Genome Wide ◽  
Differentially Methylated Genes ◽  
Flanking Regions

DNA methylation is an important epigenetic modification involved in the estrous cycle and the regulation of reproduction. Here, we investigated the genome-wide profiles of DNA methylation in porcine ovaries in proestrus and estrus using methylated DNA immunoprecipitation sequencing. The results showed that DNA methylation was enriched in intergenic and intron regions. The methylation levels of coding regions were higher than those of the 5′- and 3′-flanking regions of genes. There were 4,813 differentially methylated regions (DMRs) of CpG islands in the estrus vs. proestrus ovarian genomes. Additionally, 3,651 differentially methylated genes (DMGs) were identified in pigs in estrus and proestrus. The DMGs were significantly enriched in biological processes and pathways related to reproduction and hormone regulation. We identified 90 DMGs associated with regulating reproduction in pigs. Our findings can serve as resources for DNA methylome research focused on porcine ovaries and further our understanding of epigenetically regulated reproduction in mammals.

scholarly journals Methylation-Mediated Transcriptional Silencing in Euchromatin by Methyl-CpG Binding Protein MBD1 Isoforms

1999 ◽  
Vol 19 (9) ◽  
pp. 6415-6426 ◽  
Author(s):  
Naoyuki Fujita ◽  
Shin-ichiro Takebayashi ◽  
Katsuzumi Okumura ◽  
Shinichi Kudo ◽  
Tsutomu Chiba ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Transcriptional Repression ◽  
Mammalian Cells ◽  
Fluorescent Protein ◽  
Cpg Islands ◽  
Transcriptional Silencing ◽  
Pericentromeric Region ◽  
Chromosome 1 ◽  
Reverse Transcription Pcr ◽  
Genome Methylation

ABSTRACT DNA methylation of promoter-associated CpG islands is involved in the transcriptional repression of vertebrate genes. To investigate the mechanisms underlying gene inactivation by DNA methylation, we characterized a human MBD1 protein, one of the components of MeCP1, which possesses a methyl-CpG binding domain (MBD) and cysteine-rich (CXXC) domains. Four novel MBD1 isoforms (MBD1v1, MBD1v2, MBD1v3, and MBD1v4) were identified by the reverse transcription-PCR method. We found that these transcripts were alternatively spliced in the region of CXXC domains and the C terminus. Green fluorescent protein-fused MBD1 was localized to multiple foci on the human genome, mostly in the euchromatin regions, and particularly concentrated in the pericentromeric region of chromosome 1. Both the MBD sequence and genome methylation were required for proper localization of the MBD1 protein. We further investigated whether MBD1 isoforms are responsible for transcriptional repression of human genes. A bacterially expressed MBD1 protein bound preferentially to methylated DNA fragments containing CpG islands from the tumor suppressor genes p16,VHL, and E-cadherin and from an imprintedSNRPN gene. All MBD1 isoforms inhibited promoter activities of these genes via methylation. Interestingly, MBD1 isoforms v1 and v2 containing three CXXC domains also suppressed unmethylated promoter activities in mammalian cells. These effects were further manifested inDrosophila melanogaster cells, which lack genome methylation. Sp1-activated transcription of methylated p16and SNRPN promoters was inhibited by all of the MBD1 isoforms, whereas the isoforms v1 and v2 reduced Sp1-activated transcription from unmethylated promoters as well. These findings suggested that the MBD1 isoforms have different roles in methylation-mediated transcriptional silencing in euchromatin.

scholarly journals MethylExtract: High-Quality methylation maps and SNV calling from whole genome bisulfite sequencing data

F1000Research ◽  
2014 ◽  
Vol 2 ◽  
pp. 217 ◽  
Author(s):  
Guillermo Barturen ◽  
Antonio Rueda ◽  
José L. Oliver ◽  
Michael Hackenberg
Keyword(s):  
High Throughput ◽  
Sequence Variation ◽  
High Throughput Sequencing ◽  
Whole Genome ◽  
Single Nucleotide Variants ◽  
High Quality ◽  
Single Nucleotide ◽  
Error Sources ◽  
Link Type ◽  
Genome Methylation

Whole genome methylation profiling at a single cytosine resolution is now feasible due to the advent of high-throughput sequencing techniques together with bisulfite treatment of the DNA. To obtain the methylation value of each individual cytosine, the bisulfite-treated sequence reads are first aligned to a reference genome, and then the profiling of the methylation levels is done from the alignments. A huge effort has been made to quickly and correctly align the reads and many different algorithms and programs to do this have been created. However, the second step is just as crucial and non-trivial, but much less attention has been paid to the final inference of the methylation states. Important error sources do exist, such as sequencing errors, bisulfite failure, clonal reads, and single nucleotide variants.We developed MethylExtract, a user friendly tool to: i) generate high quality, whole genome methylation maps and ii) detect sequence variation within the same sample preparation. The program is implemented into a single script and takes into account all major error sources. MethylExtract detects variation (SNVs – Single Nucleotide Variants) in a similar way to VarScan, a very sensitive method extensively used in SNV and genotype calling based on non-bisulfite-treated reads. The usefulness of MethylExtract is shown by means of extensive benchmarking based on artificial bisulfite-treated reads and a comparison to a recently published method, called Bis-SNP.MethylExtract is able to detect SNVs within High-Throughput Sequencing experiments of bisulfite treated DNA at the same time as it generates high quality methylation maps. This simultaneous detection of DNA methylation and sequence variation is crucial for many downstream analyses, for example when deciphering the impact of SNVs on differential methylation. An exclusive feature of MethylExtract, in comparison with existing software, is the possibility to assess the bisulfite failure in a statistical way. The source code, tutorial and artificial bisulfite datasets are available at http://bioinfo2.ugr.es/MethylExtract/ and http://sourceforge.net/projects/methylextract/, and also permanently accessible from 10.5281/zenodo.7144.

scholarly journals Epigenetic deregulation of GATA3 in neuroblastoma is associated with increased GATA3 protein expression and with poor outcomes

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Bader Almutairi ◽  
Jessica Charlet ◽  
Anthony R. Dallosso ◽  
Marianna Szemes ◽  
Heather C. Etchevers ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Protein Expression ◽  
Poor Prognosis ◽  
Transcriptional Control ◽  
Neuroblastoma Cells ◽  
Sympathetic Ganglia ◽  
Genome Wide ◽  
Promising Target ◽  
Differentially Methylated Genes ◽  
Poor Outcomes

AbstractTo discover epigenetic changes that may underly neuroblastoma pathogenesis, we identified differentially methylated genes in neuroblastoma cells compared to neural crest cells, the presumptive precursors cells for neuroblastoma, by using genome-wide DNA methylation analysis. We previously described genes that were hypermethylated in neuroblastoma; in this paper we report on 67 hypomethylated genes, which were filtered to select genes that showed transcriptional over-expression and an association with poor prognosis in neuroblastoma, highlighting GATA3 for detailed studies. Specific methylation assays confirmed the hypomethylation of GATA3 in neuroblastoma, which correlated with high expression at both the RNA and protein level. Demethylation with azacytidine in cultured sympathetic ganglia cells led to increased GATA3 expression, suggesting a mechanistic link between GATA3 expression and DNA methylation. Neuroblastomas that had completely absent GATA3 methylation and/or very high levels of protein expression, were associated with poor prognosis. Knock-down of GATA3 in neuroblastoma cells lines inhibited cell proliferation and increased apoptosis but had no effect on cellular differentiation. These results identify GATA3 as an epigenetically regulated component of the neuroblastoma transcriptional control network, that is essential for neuroblastoma proliferation. This suggests that the GATA3 transcriptional network is a promising target for novel neuroblastoma therapies.

scholarly journals SomaticSignatures: Inferring Mutational Signatures from Single Nucleotide Variants

2014 ◽  
Author(s):  
Julian S. Gehring ◽  
Bernd Fischer ◽  
Michael Lawrence ◽  
Wolfgang Huber
Keyword(s):  
Large Scale ◽  
R Package ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Mutational Signatures ◽  
Single Nucleotide ◽  
Pattern Decomposition ◽  
Bioconductor Project ◽  
Mutational Processes

Mutational signatures are patterns in the occurrence of somatic single nucleotide variants (SNVs) that can reflect underlying mutational processes. The SomaticSignatures package provides flexible, interoperable, and easy-to-use tools that identify such signatures in cancer sequencing data. It facilitates large-scale, cross-dataset estimation of mutational signatures, implements existing methods for pattern decomposition, supports extension through user-defined methods and integrates with Bioconductor workflows. The R package SomaticSignatures is available as part of the Bioconductor project (R Core Team, 2014; Gentleman et al., 2004). Its documentation provides additional details on the methodology and demonstrates applications to biological datasets.

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