The genetic covariance among clinal environments after adaptation to an environmental gradient in Drosophila serrata.
We examined the genetic basis of clinal adaptation by determining the evolutionary response of life-history traits to laboratory natural selection along a gradient of thermal stress in Drosophila serrata. A gradient of heat stress was created by exposing larvae to a heat stress of 36 degrees for 4 hr for 0, 1, 2, 3, 4, or 5 days of larval development, with the remainder of development taking place at 25 degrees. Replicated lines were exposed to each level of this stress every second generation for 30 generations. At the end of selection, we conducted a complete reciprocal transfer experiment where all populations were raised in all environments, to estimate the realized additive genetic covariance matrix among clinal environments in three life-history traits. Visualization of the genetic covariance functions of the life-history traits revealed that the genetic correlation between environments generally declined as environments became more different and even became negative between the most different environments in some cases. One exception to this general pattern was a life-history trait representing the classic trade-off between development time and body size, which responded to selection in a similar genetic fashion across all environments. Adaptation to clinal environments may involve a number of distinct genetic effects along the length of the cline, the complexity of which may not be fully revealed by focusing primarily on populations at the ends of the cline.
Centre for Environmental Stress and Adaptation Research, La Trobe University, Melbourne 3083, Victoria, Australia. c.sgro@latrobe.edu.au
Carla M
CM
Sgrò
Mark W
MW
Blows
D000220:Adaptation, Biological / Q000235:genetics*; D000818:Animals; D049628:Body Size; D004330:Drosophila / Q000235:genetics* / Q000502:physiology; D004777:Environment; D006358:Hot Temperature; D007814:Larva / Q000502:physiology; D012641:Selection, Genetic; D013997:Time Factors