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DNA sequence properties that predict susceptibility to epiallelic switching.

ABSTRACT: Transgenerationally heritable epialleles are defined by the stable propagation of alternative transcriptional states through mitotic and meiotic cell cycles. Given that the propagation of DNA methylation at CpG sites, mediated in Arabidopsis by MET1, plays a central role in epigenetic inheritance, we examined genomewide DNA methylation in partial and complete loss-of-function met1 mutants. We interpreted the data in relation to transgenerational epiallelic stability, which allowed us to classify chromosomal targets of epigenetic regulation into (i) single copy and methylated exclusively at CpGs, readily forming epialleles, and (ii) transposon-derived, methylated at all cytosines, which may or may not form epialleles. We provide evidence that DNA sequence features such as density of CpGs and genomic repetitiveness of the loci predispose their susceptibility to epiallelic switching. The importance and predictive power of these genetic features were confirmed by analyses of common epialleles in natural Arabidopsis accessions, epigenetic recombinant inbred lines (epiRILs) and also verified in rice.

SUBMITTER: Catoni M

PROVIDER: S-EPMC5331756 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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DNA sequence properties that predict susceptibility to epiallelic switching.

Catoni Marco M Griffiths Jayne J Becker Claude C Zabet Nicolae Radu NR Bayon Carlos C Dapp Mélanie M Lieberman-Lazarovich Michal M Weigel Detlef D Paszkowski Jerzy J

The EMBO journal 20170109 5

Transgenerationally heritable epialleles are defined by the stable propagation of alternative transcriptional states through mitotic and meiotic cell cycles. Given that the propagation of DNA methylation at CpG sites, mediated in <i>Arabidopsis</i> by MET1, plays a central role in epigenetic inheritance, we examined genomewide DNA methylation in partial and complete loss-of-function <i>met1</i> mutants. We interpreted the data in relation to transgenerational epiallelic stability, which allowed ...[more]

PMID: 28069706

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Project description:AlphaFold2 has revolutionized protein structure prediction by leveraging sequence information to rapidly model protein folds with atomic-level accuracy. Nevertheless, previous work has shown that these predictions tend to be inaccurate for structurally heterogeneous proteins. To systematically assess factors that contribute to this inaccuracy, we tested AlphaFold2's performance on 98-fold-switching proteins, which assume at least two distinct-yet-stable secondary and tertiary structures. Topological similarities were quantified between five predicted and two experimentally determined structures of each fold-switching protein. Overall, 94% of AlphaFold2 predictions captured one experimentally determined conformation but not the other. Despite these biased results, AlphaFold2's estimated confidences were moderate-to-high for 74% of fold-switching residues, a result that contrasts with overall low confidences for intrinsically disordered proteins, which are also structurally heterogeneous. To investigate factors contributing to this disparity, we quantified sequence variation within the multiple sequence alignments used to generate AlphaFold2's predictions of fold-switching and intrinsically disordered proteins. Unlike intrinsically disordered regions, whose sequence alignments show low conservation, fold-switching regions had conservation rates statistically similar to canonical single-fold proteins. Furthermore, intrinsically disordered regions had systematically lower prediction confidences than either fold-switching or single-fold proteins, regardless of sequence conservation. AlphaFold2's high prediction confidences for fold switchers indicate that it uses sophisticated pattern recognition to search for one most probable conformer rather than protein biophysics to model a protein's structural ensemble. Thus, it is not surprising that its predictions often fail for proteins whose properties are not fully apparent from solved protein structures. Our results emphasize the need to look at protein structure as an ensemble and suggest that systematic examination of fold-switching sequences may reveal propensities for multiple stable secondary and tertiary structures.

Dataset Information

DNA sequence properties that predict susceptibility to epiallelic switching.

Publications

DNA sequence properties that predict susceptibility to epiallelic switching.

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