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AlphaBeta: Computational inference of epimutation rates and spectra from high-throughput DNA methylation data in plants

ABSTRACT: AlphaBeta: Computational inference of epimutation rates and spectra from high-throughput DNA methylation data in plants

PROVIDER: PRJNA641352 | ENA |

REPOSITORIES: ENA

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AlphaBeta: Computational inference of epimutation rates and spectra from high-throughput DNA methylation data in plants

Project description:Heritable changes in cytosine methylation can arise stochastically in plant genomes independently of DNA sequence alterations. These so-called ‘spontaneous epimutations’ appear to be abyproduct of imperfect DNA methylation maintenance during mitotic or meitotic cell divisions. Accurate estimates of the rate and spectrum of these stochastic events are necessary to be able to quantify how epimutational processes shape methylome diversity in the context of plant evolution, development and aging.

2020-08-21 | GSE153055 | GEO

AlphaBeta: computational inference of epimutation rates and spectra from high-throughput DNA methylation data in plants.

Project description: Not available

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Molecular properties of epimutation hotspots

Project description:Mistakes in the maintenance of CG methylation is a source of heritable epimutations in plants. Multigenerational surveys indicate that the rate of these stochastic events varies substantially across the genome, with some regions harboring localized “epimutation hotspots”. Using Arabidopsis as a model, we show that epimutation hotspots are indexed by a specific set of chromatin states (CS) that map to sub-regions of gene body methylation genes. Although these regions comprise only ~12% of all CGs in the genome, they account for ~63% of all epimutation events per unit time. Molecular profiling revealed that these regions contain unique sequence features, harbor steady-state intermediate methylation levels, and act as putative targets of antagonistic DNA methylation pathways. We further demonstrate that experimentally-induced shifts in steady-state methylation in these hotspot regions are sufficient to significantly alter local epimutation intensities. Our work thus lays foundation for dissecting the molecular mechanisms of epimutation hotspots in plants.

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Molecular properties of epimutation hotspots

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Dominant MLH1 epimutation linked to 5'UTR variant c.-27C>A

Project description:Constitutional epimutations of tumor suppressor genes manifest as promoter methylation and transcriptional silencing of a single allele in normal somatic tissues, thereby predisposing to cancer. Constitutional MLH1 epimutations occur in individuals with young-onset cancer and demonstrate non-Mendelian inheritance through their reversal in the germline. We report a cancer-affected family showing dominant transmission of soma-wide highly mosaic MLH1 methylation and transcriptional repression linked to a particular genetic haplotype. The epimutation was erased in spermatozoa but reinstated in the somatic cells of the next generation. The affected haplotype harbored two single nucleotide substitutions in tandem: c.-27C>A located near the transcription initiation site and c.85G>T. The c.-27C>A variant significantly reduced transcriptional activity in reporter assays and is the probable cause of this epimutation. Five members of a three-generation Caucasian Lynch syndrome family with an autosomal dominant MLH1 epimutation linked to a single nucleotide variant (c.-27C>A) within the MLH1 5'UTR were examined for copy number variations and retention of heterozygosity on chromosome 3. These five carriers of constitutional MLH1 methylation and the c.-27C>A variant were compared with 300 healthy Caucasian controls from the Wellcome Trust Case Control Consortium using three algorithms (QuantiSNP, PennCNV, COKGEN) to detect any copy number variants. The five family members studied were female (the proband II5, her affected mother I1, and three asymptomatic relatives II2, II4 and III2) are labeled according to the pedigree in Figure 3 of the associated publication (Hitchins et al., Cancer Cell, 2011). The supplementary file 'GSE30348_gw6.lrr_baf.txt' contains log R ratio and B-allele frequency values in a tab-delimited format with one marker per row.

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p16 epimutation modulates the tumor microenvironment and promotes malignancy of Apc-mutant colon cancer (RNA-Seq)

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Inference of transcription regulatory network in low phytic acid soybean seeds

Project description:A dominant loss of function mutation in myo-inositol phosphate synthase gene and recessive loss of function mutations in two multidrug resistant protein type-ABC transporter genes not only reduce the seed phytic acid levels in soybean, but also affect the pathways associated with seed development, ultimately resulting in low emergence. To understand the regulatory mechanisms and identify key genes that intervene in the seed development process in low phytic acid crops, we performed computational inference of gene regulatory networks in low and normal phytic acid soybeans using a time course transcriptomic data and multiple network inference algorithms. We identified several transcription factors and their regulatory interactions with genes that have functions in myo-inositol biosynthesis, auxin-ABA signaling and seed dormancy. We validated the predicted regulatory network by comparing it with published regulatory interactions in Arabidopsis. Some regulatory interactions were found in the low phytic acid mutants but not in non-mutant plants. These findings provide important hypotheses on expression regulation of myo-inositol metabolism, and phytohormone signaling in developing low phytic acid soybeans. The computational pipeline used for unsupervised network learning in this study is provided as open source software and is freely available at https://lilabatvt.github.io/LPANetwork/.

2018-01-12 | GSE101692 | GEO

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