DNA Methylation Profiling of Embryonic Stem Cell Differentiation into the Three Germ Layers

Embryogenesis is tightly regulated by multiple levels of epigenetic regulation such as DNA methylation, histone modification, and chromatin remodeling. DNA methylation patterns are erased in primordial germ cells and in the interval immediately following fertilization. Subsequent developmental reprogramming occurs by de novo methylation and demethylation. Variance in DNA methylation patterns between different cell types is not well understood. Here, using methylated DNA immunoprecipitation and tiling array technology, we have comprehensively analyzed DNA methylation patterns at proximal promoter regions in mouse embryonic stem (ES) cells, ES cell-derived early germ layers (ectoderm, endoderm and mesoderm) and four adult tissues (brain, liver, skeletal muscle and sperm). Most of the methylated regions are methylated across all three germ layers and in the three adult somatic tissues. This commonly methylated gene set is enriched in germ cell-associated genes that are generally transcriptionally inactive in somatic cells. We also compared DNA methylation patterns by global mapping of histone H3 lysine 4/27 trimethylation, and found that gain of DNA methylation correlates with loss of histone H3 lysine 4 trimethylation. Our combined findings indicate that differentiation of ES cells into the three germ layers is accompanied by an increased number of commonly methylated DNA regions and that these tissue-specific alterations in methylation occur for only a small number of genes. DNA methylation at the proximal promoter regions of commonly methylated genes thus appears to be an irreversible mark which functions to fix somatic lineage by repressing the transcription of germ cell-specific genes

フジゲン ジコ ソウジ シュウゴウ ニ ツイテ ジョウホウ ヒョウゲン ガッカ

This paper introduces a brand-new concept of negative dimension, which has been regarded as a scientific function or a so pathological theory that no one dears to mention to it. First I would like to show a lot of negative dimensional self similar sets as examples embedded in normal Euclidean spaces. The notion of negative dimension is contradictory to familiar well-established definitions of dimension, such as topological or Hausdorff dimensions. But I try to find a reasonable ground for supporting the concept of negative dimension especially in the case of self similar sets. It would be of course preferable to generalize the negative and positive dimensions into a single concept in the future

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts