RT Journal Article
SR Electronic
T1 Compensatory evolution via cryptic genetic variation: Distinct trajectories to phenotypic and fitness recovery
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 200725
DO 10.1101/200725
A1 Sudarshan Chari
A1 Christian Marier
A1 Cody Porter
A1 Emmalee Northrop
A1 Alexandra Belinky
A1 Ian Dworkin
YR 2017
UL http://biorxiv.org/content/early/2017/10/10/200725.abstract
AB Populations are constantly exposed to deleterious alleles, most of which are purged via natural selection. However, deleterious fitness effects of alleles can also be suppressed by compensatory adaptation. Compensatory mutations can act directly to reduce deleterious effects of an allele. Alternatively, compensation may also occur by altering other aspects of an organisms’ phenotype or performance, without suppressing the phenotypic effects of the deleterious allele. Moreover, the origin of allelic variation contributing to compensatory adaptation remains poorly understood. Compensatory evolution driven by mutations that arise during the selective process are well studied. However less is known about the role standing (cryptic) genetic variation plays in compensatory adaptation. To address these questions, we examined evolutionary trajectories of natural populations of Drosophila melanogaster fixed for mutations that disrupt wing morphology, resulting in deleterious effects on several components of fitness. Lineages subjected only to natural selection, evolved modifications to courtship behavior and several life history traits without compensation in wing morphology. Yet, we observed rapid phenotypic compensation of wing morphology under artificial selection, consistent with segregating variation for compensatory alleles. We show that alleles contributing to compensation of wing morphology have deleterious effects on other fitness components. These results demonstrate the potential for multiple independent avenues for rapid compensatory adaptation from standing genetic variation, which ultimately may reveal novel adaptive trajectories.