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Mendoza, D. Y.

Publications and source records attributed to Mendoza, D. Y..

2 recordsLinked to original sources

Reciprocal exchange obscures phylogenetic patterns of introgression

Hybridization and introgression are major evolutionary forces in eukaryotes that have shaped the evolutionary trajectories of crops, livestock, and modern humans. Yet current theoretical and statistical frameworks provide only a partial view of the dynamics and genomic consequences of introgression. An unexplored dimension is the possibility that introgression between two lineages can occur simultaneously in both directions at a single genomic locus--a process we term reciprocal introgression. Although this type of introgression is plausible, especially in cases of bidirectional introgression across the genome, it remains largely undetectable under widely used statistical approaches, hindering evaluation of its prevalence in natural systems. Moreover, unrecognized reciprocal introgression may bias summary statistics commonly used to quantify gene flow, obscuring our ability to resolve introgression events. To address this, here, we develop theoretical expectations of the impact of reciprocal introgression on phylogenetic and site-pattern-based results. To test these expectations, we implement coalescent simulations to model genomes experiencing reciprocal introgression and apply sliding-window introgression statistics to these data. We find that reciprocally introgressed loci produce phylogenetic patterns opposite to those expected under unidirectional introgression. These mixed signals can dilute evidence of introgression or even generate false signals of introgression events that never occurred. Taken together, our results highlight the need for updated statistical approaches and pave the way toward a more complete understanding of the impacts of introgression on gene histories and organismal evolution.

evolutionary biology↗

Detecting cryptic ghost lineage introgression in four-taxon genomic datasets

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

evolutionary biology↗