title: Cryptic genetic variation in natural populations: a predictive framework.
abstract: Understanding how populations respond to rapid environmental change is critical both for preserving biodiversity and for human health. An increasing number of studies have shown that genetic variation that has no discernable effect under common ecological conditions can become amplified under stressful or novel conditions, suggesting that environmental change per se can provide the raw materials for adaptation. Indeed, the release of such hidden, or "cryptic," genetic variants has been increasingly viewed as playing a general and important role in allowing populations to respond to rapid environmental change. However, additional studies have suggested that there is a balance between cryptic genetic variants that are potentially adaptive in future environments and genetic variants that are deleterious. In this article, we begin by discussing how population and environmental parameters-such as effective population size and the historical frequency and strength of selection under inducing conditions-influence relative amounts of cryptic genetic variation among populations and the overall phenotypic effects of such variation. The amount and distribution of cryptic genetic variation will, in turn, determine the likelihood that cryptic variants, once expressed, will be adaptive or maladaptive during environmental transitions. We then present specific approaches for measuring these parameters in natural populations. Finally, we discuss one natural system that will be conducive to testing whether populations that vary in these parameters harbor different amounts, or types, of cryptic genetic variation. Generally, teasing apart how population and environmental parameters influence the accumulation of cryptic genetic variation will help us to understand how populations endure and adapt (or fail to adapt) to natural environmental change and anthropogenic disturbance.
authors.affiliation: *Department of Biology, Indiana University, Bloomington, IN 47405, USA; Department of Biology, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Environmental Studies, Elon University, Elon, NC 27244, USA; Program in Ecology, Evolutionary Biology and Behavior and Department of Zoology, Michigan State University, East Lansing, MI 48824, USA cristinacaitlin@gmail.com.
authors.forename: Cris C
authors.initials: CC
authors.lastname: Ledón-Rettig
authors.affiliation: *Department of Biology, Indiana University, Bloomington, IN 47405, USA; Department of Biology, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Environmental Studies, Elon University, Elon, NC 27244, USA; Program in Ecology, Evolutionary Biology and Behavior and Department of Zoology, Michigan State University, East Lansing, MI 48824, USA.
authors.forename: David W
authors.initials: DW
authors.lastname: Pfennig
authors.affiliation: *Department of Biology, Indiana University, Bloomington, IN 47405, USA; Department of Biology, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Environmental Studies, Elon University, Elon, NC 27244, USA; Program in Ecology, Evolutionary Biology and Behavior and Department of Zoology, Michigan State University, East Lansing, MI 48824, USA.
authors.forename: Amanda J
authors.initials: AJ
authors.lastname: Chunco
authors.affiliation: *Department of Biology, Indiana University, Bloomington, IN 47405, USA; Department of Biology, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Environmental Studies, Elon University, Elon, NC 27244, USA; Program in Ecology, Evolutionary Biology and Behavior and Department of Zoology, Michigan State University, East Lansing, MI 48824, USA.
authors.forename: Ian
authors.initials: I
authors.lastname: Dworkin
mesh_terms: D004777:Environment; D056890:Eukaryota / Q000235:genetics*; D014644:Genetic Variation; D008957:Models, Genetic; D010641:Phenotype