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The information signature of diverging lineages

View ORCID ProfileDouglas G. Moore, Matheo Morales, View ORCID ProfileSara I. Walker, View ORCID ProfileGreer A. Dolby
doi: https://doi.org/10.1101/2021.08.30.458276
Douglas G. Moore
1The Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ
239Alpha Research, Tempe, AZ
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  • ORCID record for Douglas G. Moore
  • For correspondence: douglas.g.moore@asu.edu gadolby@asu.edu
Matheo Morales
3School of Life Sciences, Arizona State University, Tempe, AZ
4Department of Genetics, Yale University, New Haven, CT
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Sara I. Walker
1The Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ
5School of Earth and Space Exploration, Arizona State University, Tempe, AZ
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Greer A. Dolby
3School of Life Sciences, Arizona State University, Tempe, AZ
6Center for Mechanisms of Evolution, Biodesign Institute, Arizona State University, Tempe, AZ
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  • For correspondence: douglas.g.moore@asu.edu gadolby@asu.edu
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Abstract

The process of forming new species is the driving force behind the diversity of life on Earth. Yet, we have not answered the basic question: why are species unevenly distributed across taxonomic groups and geographic settings? This is because we lack the means to directly compare aspects of population (lineage) divergence across unrelated species because taxon-specific effects make comparisons difficult or impossible. Here, we present a new solution to this challenge by identifying the information signature of diverging lineages, calculated using partial information decomposition (PID), under different evolutionary scenarios. We show in silico how the informational decomposition of genetic metrics varies over time since divergence. Calculating PID over 97,200 lattices reveals that the decomposed nodes of Tajima’s D, θW, and π have strong information signatures, while FST was least useful for discriminating among divergence scenarios. The presence or absence of gene flow during divergence was the most detectable signature; mutation rate and effective population size (Ne) were also detectable whereas differences in recombination rate were not. This work demonstrates that PID can reveal evolutionary patterns that are minimally detectable using the raw metrics themselves; it does so by leveraging the architecture of the genome and the partial redundancy of information contained in genetic metrics. Our results demonstrate for the first time how to directly compare characteristics of diverging populations even among distantly related species, providing a foundational tool for understanding the diversity of life across Earth.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted September 01, 2021.
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The information signature of diverging lineages
Douglas G. Moore, Matheo Morales, Sara I. Walker, Greer A. Dolby
bioRxiv 2021.08.30.458276; doi: https://doi.org/10.1101/2021.08.30.458276
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The information signature of diverging lineages
Douglas G. Moore, Matheo Morales, Sara I. Walker, Greer A. Dolby
bioRxiv 2021.08.30.458276; doi: https://doi.org/10.1101/2021.08.30.458276

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