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Cited by 499

The DOI matches its Crossref record; 110 of the 110 references it cites were found in a registry or an index.

Microbes Drive Evolution of Animals and Plants: the Hologenome Concept

Open access
Rosenberg, Eugene, Zilber-Rosenberg, Ilana·2016·mBio

Abstract

The hologenome concept of evolution postulates that the holobiont (host plus symbionts) with its hologenome (host genome plus microbiome) is a level of selection in evolution. Multicellular organisms can no longer be considered individuals by the classical definitions of the term. Every natural animal and plant is a holobiont consisting of the host and diverse symbiotic microbes and viruses. Microbial symbionts can be transmitted from parent to offspring by a variety of methods, including via cytoplasmic inheritance, coprophagy, direct contact during and after birth, and the environment. A large number of studies have demonstrated that these symbionts contribute to the anatomy, physiology, development, innate and adaptive immunity, and behavior and finally also to genetic variation and to the origin and evolution of species. Acquisition of microbes and microbial genes is a powerful mechanism for driving the evolution of complexity. Evolution proceeds both via cooperation and competition, working in parallel.

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Metadata

Authors
Rosenberg, E., & Zilber-Rosenberg, I.
Venue
mBio
Published
2016-05-04
Volume
7
Issue
2
Pages
e01395-e01395
ISSN
  • 2150-7511 (ISSN-L)
  • 2161-2129
OpenAlex
W2314620467
Cited by
499
References
110
FWCI
38.89
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Microbes Drive Evolution of Animals and Plants: the Hologenome Concept. https://app.cochat.ai/papers/10.1128/mbio.01395-15
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Rosenberg, E., & Zilber-Rosenberg, I. (2016). Microbes Drive Evolution of Animals and Plants: the Hologenome Concept. mBio. https://doi.org/10.1128/mbio.01395-15

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.