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Dissecting direct reprogramming through integrative genomic analysis.

ABSTRACT: Somatic cells can be reprogrammed to a pluripotent state through the ectopic expression of defined transcription factors. Understanding the mechanism and kinetics of this transformation may shed light on the nature of developmental potency and suggest strategies with improved efficiency or safety. Here we report an integrative genomic analysis of reprogramming of mouse fibroblasts and B lymphocytes. Lineage-committed cells show a complex response to the ectopic expression involving induction of genes downstream of individual reprogramming factors. Fully reprogrammed cells show gene expression and epigenetic states that are highly similar to embryonic stem cells. In contrast, stable partially reprogrammed cell lines show reactivation of a distinctive subset of stem-cell-related genes, incomplete repression of lineage-specifying transcription factors, and DNA hypermethylation at pluripotency-related loci. These observations suggest that some cells may become trapped in partially reprogrammed states owing to incomplete repression of transcription factors, and that DNA de-methylation is an inefficient step in the transition to pluripotency. We demonstrate that RNA inhibition of transcription factors can facilitate reprogramming, and that treatment with DNA methyltransferase inhibitors can improve the overall efficiency of the reprogramming process.

SUBMITTER: Mikkelsen TS

PROVIDER: S-EPMC2754827 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundIt has been an abiding belief among geneticists that multicellular organisms' genomes can be analyzed under the assumption that a single individual has a uniform genome in all its cells. Despite some evidence to the contrary, this belief has been used as an axiomatic assumption in most genome analysis software packages. In this paper we present observations in human whole genome data, human whole exome data and in mouse whole genome data to challenge this assumption. We show that heterogeneity is in fact ubiquitous and readily observable in ordinary Next Generation Sequencing (NGS) data.ResultsStarting with the assumption that a single NGS read (or read pair) must come from one haplotype, we built a procedure for directly observing haplotypes at a local level by examining 2 or 3 adjacent single nucleotide polymorphisms (SNPs) which are close enough on the genome to be spanned by individual reads. We applied this procedure to NGS data from three different sources: whole genome of a Central European trio from the 1000 genomes project, whole genome data from laboratory-bred strains of mouse, and whole exome data from a set of patients of head and neck tumors. Thousands of loci were found in each genome where reads spanning 2 or 3 SNPs displayed more than two haplotypes, indicating that the locus is heterogeneous. We show that such loci are ubiquitous in the genome and cannot be explained by segmental duplications. We explain them on the basis of cellular heterogeneity at the genomic level. Such heterogeneous loci were found in all normal and tumor genomes examined.ConclusionsOur results highlight the need for new methods to analyze genomic variation because existing ones do not systematically consider local haplotypes. Identification of cancer somatic mutations is complicated because of tumor heterogeneity. It is further complicated if, as we show, normal tissues are also heterogeneous. Methods for biomarker discovery must consider contextual haplotype information rather than just whether a variant "is present".

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Dissecting direct reprogramming through integrative genomic analysis.

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