The information signature of diverging lineages

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, thetaW, and pi; 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.

Implications of barrier ephemerality in geogenomic research

“…CDMetaPop allows easy parameterization of spatially explicit simulations but does not model genomic linkage between adaptive and neutral loci and therefore has limitations when modelling the emergent effects of differential selection on populations. Therefore, to explore the interactive effects caused by a barrier in addition to natural selection, we used S LiM v3.3.2 (Haller & Messer, 2019) following the methodology described by Moore et al (2021). We simulated 60,000 bp of sequence per individual under a mutation rate of 10 −8 for two groups (north and south) with 5000 individuals each, which is equivalent to CDMetaPop but without spatially substructured populations.…”

“…Therefore, to explore the interactive effects caused by a barrier in addition to natural selection, we used SLiM v3.3.2 (Haller & Messer, 2019) following the methodology described by Moore et al (2021). We simulated 60,000 bp of sequence per individual under a mutation rate of 10 −8 for two groups (north and south) with 5000 individuals each, which is equivalent to CDMetaPoP but without spatially substructured populations.…”