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      Genetic sources of population epigenomic variation.

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          Abstract

          The field of epigenomics has rapidly progressed from the study of individual reference epigenomes to surveying epigenomic variation in populations. Recent studies in a number of species, from yeast to humans, have begun to dissect the cis- and trans-regulatory genetic mechanisms that shape patterns of population epigenomic variation at the level of single epigenetic marks, as well as at the level of integrated chromatin state maps. We show that this information is paving the way towards a more complete understanding of the heritable basis underlying population epigenomic variation. We also highlight important conceptual challenges when interpreting results from these genetic studies, particularly in plants, in which epigenomic variation can be determined both by genetic and epigenetic inheritance.

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          Most cited references79

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          Principles and challenges of genomewide DNA methylation analysis.

          Methylation of cytosine bases in DNA provides a layer of epigenetic control in many eukaryotes that has important implications for normal biology and disease. Therefore, profiling DNA methylation across the genome is vital to understanding the influence of epigenetics. There has been a revolution in DNA methylation analysis technology over the past decade: analyses that previously were restricted to specific loci can now be performed on a genome-scale and entire methylomes can be characterized at single-base-pair resolution. However, there is such a diversity of DNA methylation profiling techniques that it can be challenging to select one. This Review discusses the different approaches and their relative merits and introduces considerations for data analysis.
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            Identification of functional elements and regulatory circuits by Drosophila modENCODE.

            To gain insight into how genomic information is translated into cellular and developmental programs, the Drosophila model organism Encyclopedia of DNA Elements (modENCODE) project is comprehensively mapping transcripts, histone modifications, chromosomal proteins, transcription factors, replication proteins and intermediates, and nucleosome properties across a developmental time course and in multiple cell lines. We have generated more than 700 data sets and discovered protein-coding, noncoding, RNA regulatory, replication, and chromatin elements, more than tripling the annotated portion of the Drosophila genome. Correlated activity patterns of these elements reveal a functional regulatory network, which predicts putative new functions for genes, reveals stage- and tissue-specific regulators, and enables gene-expression prediction. Our results provide a foundation for directed experimental and computational studies in Drosophila and related species and also a model for systematic data integration toward comprehensive genomic and functional annotation.
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              The rate and molecular spectrum of spontaneous mutations in Arabidopsis thaliana.

              To take complete advantage of information on within-species polymorphism and divergence from close relatives, one needs to know the rate and the molecular spectrum of spontaneous mutations. To this end, we have searched for de novo spontaneous mutations in the complete nuclear genomes of five Arabidopsis thaliana mutation accumulation lines that had been maintained by single-seed descent for 30 generations. We identified and validated 99 base substitutions and 17 small and large insertions and deletions. Our results imply a spontaneous mutation rate of 7 x 10(-9) base substitutions per site per generation, the majority of which are G:C-->A:T transitions. We explain this very biased spectrum of base substitution mutations as a result of two main processes: deamination of methylated cytosines and ultraviolet light-induced mutagenesis.
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                Author and article information

                Journal
                Nat. Rev. Genet.
                Nature reviews. Genetics
                Springer Nature
                1471-0064
                1471-0056
                Jun 2016
                : 17
                : 6
                Affiliations
                [1 ] Quantitative Epigenetics, European Research Institute for the Biology of Ageing, University Medical Center Groningen, Antonius Deusinglaan 1, Groningen NL-9713 AV, The Netherlands.
                [2 ] Institute for Computational Biology, Helmholtz Center Munich, Ingolstädter Landstrasse 1, Neuherberg 85764, Germany.
                [3 ] Population Epigenetics and Epigenomics, Technical University of Munich, Liesel-Beckmann-Strasse 2, Freising 85354, Germany.
                [4 ] Institute for Advanced Study, Technical University of Munich, Lichtenbergstrasse 2a, Garching 85748, Germany.
                Article
                nrg.2016.45
                10.1038/nrg.2016.45
                27156976
                e330b7af-becf-4670-9466-0e414b62009e
                History

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