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Dryad

Data for: Gene flow accelerates adaptation to a parasite

Cite this dataset

Lewis, Jordan; Kandala, Prathyusha; Penley, McKenna; Morran, Levi (2023). Data for: Gene flow accelerates adaptation to a parasite [Dataset]. Dryad. https://doi.org/10.5061/dryad.9kd51c5ns

Abstract

Gene flow into populations can increase additive genetic variation and introduce novel beneficial alleles, thus facilitating adaptation. However, gene flow may also impede adaptation by disrupting beneficial genotypes, introducing deleterious alleles, or creating novel dominant negative interactions. While theory and fieldwork have provided insight as to the effects of gene flow, direct experimental tests are rare. Here, we evaluated the effects of gene flow on adaptation in the nematode Caenorhabditis elegans during exposure to the bacterial parasite Serratia marcescens. We evolved hosts against non-evolving parasites for ten passages while controlling host gene flow and source population. We used source nematode populations with three different genetic backgrounds (one similar to the sink population and two different) and two evolutionary histories (previously adapted to S. marcescens or naïve). We found that populations with gene flow exhibited greater increases in parasite resistance than those without gene flow. Additionally, gene flow from adapted populations resulted in greater increases in resistance than gene flow from naïve populations, particularly with gene flow from novel genetic backgrounds. Overall, this work demonstrates that gene flow can facilitate adaptation and suggests that the genetic architecture and evolutionary history of source populations can alter the sink population’s response to selection.

Methods

The raw data was collected by methods outlined in the materials and methods section of the manuscript. Data was recorded into an Excel spreadsheet, cleaned, then uploaded into JMP Pro 14 for statistical analysis and figure creation.

Funding

National Science Foundation, Award: 2017246734

National Science Foundation, Award: DEB-1750553