Pleiotropy facilitates local adaptation to distant optima in common ragweed (Ambrosia artemisiifolia)

Autoři: Tuomas Hämälä aff001;  Amanda J. Gorton aff002;  David A. Moeller aff001;  Peter Tiffin aff001
Působiště autorů: Department of Plant and Microbial Biology, University of Minnesota, St. Paul, Minnesota, United States of America aff001;  Department of Ecology, Evolution and Behavior, University of Minnesota, St. Paul, Minnesota, United States of America aff002
Vyšlo v časopise: Pleiotropy facilitates local adaptation to distant optima in common ragweed (Ambrosia artemisiifolia). PLoS Genet 16(3): e32767. doi:10.1371/journal.pgen.1008707
Kategorie: Research Article
doi: 10.1371/journal.pgen.1008707


Pleiotropy, the control of multiple phenotypes by a single locus, is expected to slow the rate of adaptation by increasing the chance that beneficial alleles also have deleterious effects. However, a prediction arising from classical theory of quantitative trait evolution states that pleiotropic alleles may have a selective advantage when phenotypes are distant from their selective optima. We examine the role of pleiotropy in regulating adaptive differentiation among populations of common ragweed (Ambrosia artemisiifolia); a species that has recently expanded its North American range due to human-mediated habitat change. We employ a phenotype-free approach by using connectivity in gene networks as a proxy for pleiotropy. First, we identify loci bearing footprints of local adaptation, and then use genotype-expression mapping and co-expression networks to infer the connectivity of the genes. Our results indicate that the putatively adaptive loci are highly pleiotropic, as they are more likely than expected to affect the expression of other genes, and they reside in central positions within the gene networks. We propose that the conditionally advantageous alleles at these loci avoid the cost of pleiotropy by having large phenotypic effects that are beneficial when populations are far from their selective optima. We further use evolutionary simulations to show that these patterns are in agreement with a model where populations face novel selective pressures, as expected during a range expansion. Overall, our results suggest that highly connected genes may be targets of positive selection during environmental change, even though they likely experience strong purifying selection in stable selective environments.

Klíčová slova:

Gene expression – Genetic loci – Genetic networks – Population genetics – Principal component analysis – Quantitative trait loci – Sequence alignment – Transcriptome analysis


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