Dataset Information

Integrating networks and comparative genomics reveals retroelement proliferation dynamics in hominid genomes.

ABSTRACT: Retroelements (REs) are mobile DNA sequences that multiply and spread throughout genomes by a copy-and-paste mechanism. These parasitic elements are active in diverse genomes, from yeast to humans, where they promote diversity, cause disease, and accelerate evolution. Because of their high copy number and sequence similarity, studying their activity and tracking their proliferation dynamics is a challenge. It is particularly difficult to pinpoint the few REs in a genome that are still active in the haystack of degenerate and suppressed elements. We develop a computational framework based on network theory that tracks the path of RE proliferation throughout evolution. We analyze SVA (SINE-VNTR-Alu), the youngest RE family in human genomes, to understand RE dynamics across hominids. Integrating comparative genomics and network tools enables us to track the course of SVA proliferation, identify yet unknown active communities, and detect tentative "master REs" that played key roles in SVA propagation, providing strong support for the fundamental "master gene" model of RE proliferation. The method is generic and thus can be applied to REs of any of the thousands of available genomes to identify active RE communities and master REs that were pivotal in the evolution of their host genomes.

SUBMITTER: Levy O

PROVIDER: S-EPMC5640379 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Integrating networks and comparative genomics reveals retroelement proliferation dynamics in hominid genomes.

Levy Orr O Knisbacher Binyamin A BA Levanon Erez Y EY Havlin Shlomo S

Science advances 20171013 10

Retroelements (REs) are mobile DNA sequences that multiply and spread throughout genomes by a copy-and-paste mechanism. These parasitic elements are active in diverse genomes, from yeast to humans, where they promote diversity, cause disease, and accelerate evolution. Because of their high copy number and sequence similarity, studying their activity and tracking their proliferation dynamics is a challenge. It is particularly difficult to pinpoint the few REs in a genome that are still active in ...[more]

PMID: 29043294

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Project description:BackgroundComparative genomics methods enable the reconstruction of bacterial regulatory networks using available experimental data. In spite of their potential for accelerating research into the composition and evolution of bacterial regulons, few comparative genomics suites have been developed for the automated analysis of these regulatory systems. Available solutions typically rely on precomputed databases for operon and ortholog predictions, limiting the scope of analyses to processed complete genomes, and several key issues such as the transfer of experimental information or the integration of regulatory information in a probabilistic setting remain largely unaddressed.ResultsHere we introduce CGB, a flexible platform for comparative genomics of prokaryotic regulons. CGB has few external dependencies and enables fully customized analyses of newly available genome data. The platform automates the merging of experimental information and uses a gene-centered, Bayesian framework to generate and integrate easily interpretable results. We demonstrate its flexibility and power by analyzing the evolution of type III secretion system regulation in pathogenic Proteobacteria and by characterizing the SOS regulon of a new bacterial phylum, the Balneolaeota.ConclusionsOur results demonstrate the applicability of the CGB pipeline in multiple settings. CGB's ability to automatically integrate experimental information from multiple sources and use complete and draft genomic data, coupled with its non-reliance on precomputed databases and its easily interpretable display of gene-centered posterior probabilities of regulation provide users with an unprecedented level of flexibility in launching comparative genomics analyses of prokaryotic transcriptional regulatory networks. The analyses of type III secretion and SOS response regulatory networks illustrate instances of convergent and divergent evolution of these regulatory systems, showcasing the power of formal ancestral state reconstruction at inferring the evolutionary history of regulatory networks.

Dataset Information

Integrating networks and comparative genomics reveals retroelement proliferation dynamics in hominid genomes.

Publications

Integrating networks and comparative genomics reveals retroelement proliferation dynamics in hominid genomes.

Similar Datasets

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