The evolutionary genomics of serpentine adaptation

0540571 - BÚ 2021 RIV CH eng J - Journal Article
Konečná, Veronika - Yant, L. - Kolář, Filip
The evolutionary genomics of serpentine adaptation.
Frontiers in Plant Science. Roč. 11, Dec. 16 (2020), s. 1-10, č. článku 574616. ISSN 1664-462X. E-ISSN 1664-462X
Institutional support: RVO:67985939
Keywords : serpentine * adaptation * population genomics
OECD category: Plant sciences, botany
Impact factor: 5.754, year: 2020
Method of publishing: Open access
https://doi.org/10.3389/fpls.2020.574616

Serpentine barrens are among the most challenging settings for plant life. Representing a perfect storm of hazards, serpentines consist of broadly skewed elemental profiles, including abundant toxic metals and low nutrient contents on drought-prone, patchily distributed substrates. Accordingly, plants that can tolerate the challenges of serpentine have fascinated biologists for decades, yielding important insights into adaptation to novel ecologies through physiological change. Here we highlight recent progress from studies which demonstrate the power of serpentine as a model for the genomics of adaptation. Given the moderate – but still tractable – complexity presented by the mix of hazards on serpentine, these venues are well-suited for the experimental inquiry of adaptation both in natural and manipulated conditions. Moreover, the island-like distribution of serpentines across landscapes provides abundant natural replicates, offering power to evolutionary genomic inference. Exciting recent insights into the genomic basis of serpentine adaptation point to a partly shared basis that involves sampling from common allele pools available from retained ancestral polymorphism or via gene flow. However, a lack of integrated studies deconstructing complex adaptations and linking candidate alleles with fitness consequences leaves room for much deeper exploration. Thus, we still seek the crucial direct link between the phenotypic effect of candidate alleles and their measured adaptive value – a prize that is exceedingly rare to achieve in any study of adaptation. We expect that closing this gap is not far off using the promising model systems described here.
Permanent Link: http://hdl.handle.net/11104/0318197