4.5 Article

WATER STRESS ALTERS THE GENETIC ARCHITECTURE OF FUNCTIONAL TRAITS ASSOCIATED WITH DROUGHT ADAPTATION IN AVENA BARBATA

期刊

EVOLUTION
卷 63, 期 3, 页码 702-715

出版社

WILEY-BLACKWELL PUBLISHING, INC
DOI: 10.1111/j.1558-5646.2008.00580.x

关键词

Avena barbata; functional traits; G-matrices; physiological adaptation; water stress

资金

  1. Ontario Graduate Scholarship
  2. Natural Sciences and Engineering Research Council
  3. Canada Foundation for Innovation
  4. Ontario Innovation Trust

向作者/读者索取更多资源

Environmental stress can alter genetic variation and covariation underlying functional traits, and thus affect adaptive evolution in response to natural selection. However, the genetic basis of functional traits is rarely examined in contrasting resource environments, and consequently, there is no consensus regarding whether environmental stress constrains or facilitates adaptive evolution. We tested whether resource availability affects genetic variation for and covariation among seven physiological traits and seven morphological/performance traits by growing the annual grass Avena barbata in dry and well-watered treatments. We found that differences in the overall genetic variance-covariance (G) matrix between environments were driven by physiological traits rather than morphology and performance traits. More physiological traits were heritable in the dry treatment than the well-watered treatment and many of the genetic correlations among physiological traits were environment dependent. In contrast, genetic variation and covariation among the morphological and performance traits did not differ across treatments. Furthermore, genetic correlations between physiology and performance were stronger in the dry treatment, which contributed to differences in the overall G-matrix. Our results therefore suggest that physiological adaptation would be constrained by low heritable variation in resource-rich environments, but facilitated by higher heritable variation and stronger genetic correlations with performance traits in resource-poor environments.

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