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Exploration of sequence space as the basis of viral RNA genome segmentation.

ABSTRACT: The mechanisms of viral RNA genome segmentation are unknown. On extensive passage of foot-and-mouth disease virus in baby hamster kidney-21 cells, the virus accumulated multiple point mutations and underwent a transition akin to genome segmentation. The standard single RNA genome molecule was replaced by genomes harboring internal in-frame deletions affecting the L- or capsid-coding region. These genomes were infectious and killed cells by complementation. Here we show that the point mutations in the nonstructural protein-coding region (P2, P3) that accumulated in the standard genome before segmentation increased the relative fitness of the segmented version relative to the standard genome. Fitness increase was documented by intracellular expression of virus-coded proteins and infectious progeny production by RNAs with the internal deletions placed in the sequence context of the parental and evolved genome. The complementation activity involved several viral proteins, one of them being the leader proteinase L. Thus, a history of genetic drift with accumulation of point mutations was needed to allow a major variation in the structure of a viral genome. Thus, exploration of sequence space by a viral genome (in this case an unsegmented RNA) can reach a point of the space in which a totally different genome structure (in this case, a segmented RNA) is favored over the form that performed the exploration.

SUBMITTER: Moreno E

PROVIDER: S-EPMC4020086 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

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Exploration of sequence space as the basis of viral RNA genome segmentation.

Moreno Elena E Ojosnegros Samuel S García-Arriaza Juan J Escarmís Cristina C Domingo Esteban E Perales Celia C

Proceedings of the National Academy of Sciences of the United States of America 20140422 18

The mechanisms of viral RNA genome segmentation are unknown. On extensive passage of foot-and-mouth disease virus in baby hamster kidney-21 cells, the virus accumulated multiple point mutations and underwent a transition akin to genome segmentation. The standard single RNA genome molecule was replaced by genomes harboring internal in-frame deletions affecting the L- or capsid-coding region. These genomes were infectious and killed cells by complementation. Here we show that the point mutations i ...[more]

PMID: 24757055

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Project description:Current genome-wide ChIP-seq experiments on different epigenetic marks aim at unraveling the interplay between their regulation mechanisms. Published evaluation tools, however, allow testing for predefined hypotheses only. Here, we present a novel method for annotation-independent exploration of epigenetic data and their inter-correlation with other genome-wide features. Our method is based on a combinatorial genome segmentation solely using information on combinations of epigenetic marks. It does not require prior knowledge about the data (e.g. gene positions), but allows integrating the data in a straightforward manner. Thereby, it combines compression, clustering and visualization of the data in a single tool. Our method provides intuitive maps of epigenetic patterns across multiple levels of organization, e.g. of the co-occurrence of different epigenetic marks in different cell types. Thus, it facilitates the formulation of new hypotheses on the principles of epigenetic regulation. We apply our method to histone modification data on trimethylation of histone H3 at lysine 4, 9 and 27 in multi-potent and lineage-primed mouse cells, analyzing their combinatorial modification pattern as well as differentiation-related changes of single modifications. We demonstrate that our method is capable of reproducing recent findings of gene centered approaches, e.g. correlations between CpG-density and the analyzed histone modifications. Moreover, combining the clustered epigenetic data with information on the expression status of associated genes we classify differences in epigenetic status of e.g. house-keeping genes versus differentiation-related genes. Visualizing the distribution of modification states on the chromosomes, we discover strong patterns for chromosome X. For example, exclusively H3K9me3 marked segments are enriched, while poised and active states are rare. Hence, our method also provides new insights into chromosome-specific epigenetic patterns, opening up new questions how "epigenetic computation" is distributed over the genome in space and time.

Dataset Information

Exploration of sequence space as the basis of viral RNA genome segmentation.

Publications

Exploration of sequence space as the basis of viral RNA genome segmentation.

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