Detecting cryptic ghost lineage introgression in four-taxon genomic datasets

Abstract

Premise

Hybridization and introgression are pervasive evolutionary forces that have played fundamental roles in shaping the diversity of wild and domesticated plants. Four-taxon tests for introgression provide a reliable framework for detecting signatures of ancient introgression from genomic data, which have played an important role in revealing the reticulate nature of plant evolution; however, there is emerging evidence that a cryptic process known as ghost lineage introgression has the potential to dramatically skew interpretations of four-taxon introgression statistics, particularly our ability to determine the lineages involved in introgression. This ambiguity limits our ability to resolve the mechanisms and functional implications of introgression because it means we can determine neither the donor nor the recipient of introgressed alleles with confidence.

Methods

Here, we develop ghostbuster, a statistical test designed to detect ghost lineage introgression in genomic data based on patterns of sequence divergence. We employ coalescent simulations to test our method and ascertain the conditions under which it accurately identifies ingroup versus ghost lineage introgression. Finally, to demonstrate the utility of ghostbuster, we apply it to a previously identified introgression event in the plant family Brassicaceae.

Results

Our simulations reveal that ghostbuster accurately distinguishes ghost lineage introgression from ingroup introgression across a range of introgression scenarios, with errors arising only when divergence events are closely spaced or when ancestral population sizes are unbalanced. Our analysis of empirical plant data reveals that the previously identified introgression likely constitutes ghost lineage introgression and, thus, was previously misinterpreted.

Discussion

Our analyses of simulated and empirical data demonstrate that ghostbuster will be a helpful tool in resolving reticulate evolution in plants and other taxa. We demonstrate the biological insights that ghostbuster provides by presenting an updated model of ghost lineage introgression in Brassicaceae, impacting our understanding of the molecular evolution of crop and model species in this important plant lineage. Ghostbuster code is freely available at: https://github.com/EvanForsythe/Ghost_introgression.