Ecological genomics of adaptation to unpredictability in experimental rotifer populations

Tarazona, Eva; Hahn, Christoph; Franch-Gras, Lluís; García-Roger, Eduardo M.; Carmona, María José; Gómez, Africa

Abstract

Elucidating the genetic basis of phenotypic variation in response to different environments is key to understanding how populations evolve. Facultatively sexual rotifers can develop adaptive responses to fluctuating environments. In a previous evolution experiment, diapause-related traits changed rapidly in response to two selective regimes (predictable vs unpredictable) in laboratory populations of the rotifer Brachionus plicatilis. Here, we investigate the genomic basis of adaptation to environmental unpredictability in these experimental populations. We identified and genotyped genome-wide polymorphisms in 169 clones from both selective regimes after seven cycles of selection using genotyping by sequencing (GBS). Additionally, we used GBS data from the 270 field clones from which the laboratory populations were established. This GBS dataset was used to identify candidate SNPs under selection. A total of 76 SNPs showed divergent selection, three of which are candidates for being under selection in the particular unpredictable fluctuation pattern studied. Most of the remaining SNPs showed strong signals of adaptation to laboratory conditions. Furthermore, a genotype-phenotype association approach revealed five SNPs associated with two key life-history traits in the adaptation to unpredictability. Our results contribute to elucidating the genomic basis for adaptation to unpredictable environments and lay the groundwork for future evolution studies in rotifers.

Citation

Tarazona, E., Hahn, C., Franch-Gras, L., García-Roger, E. M., Carmona, M. J., & Gómez, A. (2019). Ecological genomics of adaptation to unpredictability in experimental rotifer populations. Scientific reports, 9(1), Article 19646. https://doi.org/10.1038/s41598-019-56100-y

• Journal Article Type: Article
• Acceptance Date: Dec 2, 2019
• Online Publication Date: Dec 23, 2019
• Publication Date: Dec 1, 2019
• Deposit Date: Feb 17, 2020
• Publicly Available Date: Feb 19, 2020
• Journal: Scientific Reports
• Print ISSN: 2045-2322
• Electronic ISSN: 2045-2322
• Publisher: Nature Publishing Group
• Peer Reviewed: Peer Reviewed
• Volume: 9
• Issue: 1
• Article Number: 19646
• DOI: https://doi.org/10.1038/s41598-019-56100-y
• Public URL: https://hull-repository.worktribe.com/output/3315983