The maintenance (or not) of polygenic variation by soft selection in heterogeneous environments

被引:69
|
作者
Spichtig, M [1 ]
Kawecki, TJ [1 ]
机构
[1] Univ Fribourg, Dept Biol, Div Ecol & Evolut, CH-1700 Fribourg, Switzerland
来源
AMERICAN NATURALIST | 2004年 / 164卷 / 01期
关键词
genetic polymorphism; genetic variance; heterogeneous environments; quantitative traits; soft selection;
D O I
10.1086/421335
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
On the basis of single-locus models, spatial heterogeneity of the environment coupled with strong population regulation within each habitat ( soft selection) is considered an important mechanism maintaining genetic variation. We studied the capacity of soft selection to maintain polygenic variation for a trait determined by several additive loci, selected in opposite directions in two habitats connected by dispersal. We found three main types of stable equilibria. Extreme equilibria are characterized by extreme specialization to one habitat and loss of polymorphism. They are analogous to monomorphic equilibria in singe-locus models and are favored by similar factors: high dispersal, weak selection, and low marginal average fitness of intermediate genotypes. At the remaining two types of equilibria the population mean is intermediate but variance is very different. At fully polymorphic equilibria all loci are polymorphic, whereas at low-variance equilibria at most one locus remains polymorphic. For most parameters only one type of equilibrium is stable; the transition between the domains of fully polymorphic and low-variance equilibria is typically sharp. Low-variance equilibria are favored by high marginal average fitness of intermediate genotypes, in contrast to single-locus models, in which marginal overdominance is particularly favorable for maintenance of polymorphism. The capacity of soft selection to maintain polygenic variation is thus more limited than extrapolation from single-locus models would suggest, in particular if dispersal is high and selection weak. This is because in a polygenic model, variance can evolve independently of the mean, whereas in the single-locus two-allele case, selection for an intermediate mean automatically leads to maintenance of polymorphism.
引用
收藏
页码:70 / 84
页数:15
相关论文
共 50 条
  • [42] EFFECT OF HETEROGENEOUS ENVIRONMENTS AND A COMPETITOR ON GENETIC-VARIATION IN DROSOPHILA
    POWELL, JR
    WISTRAND, H
    AMERICAN NATURALIST, 1978, 112 (987): : 935 - 947
  • [43] Polygenic adaptation in changing environments
    Jain, Kavita
    Devi, Archana
    EPL, 2018, 123 (04)
  • [44] Hybrid static–dynamic selection of implementation alternatives in heterogeneous environments
    D. del Rio Astorga
    Manuel F. Dolz
    Javier Fernandez
    Javier Garcia Blas
    The Journal of Supercomputing, 2019, 75 : 4098 - 4113
  • [45] Modeling the evolutionary and ecological consequences of selection and adaptation in heterogeneous environments
    Cohen, Dan
    ISRAEL JOURNAL OF ECOLOGY & EVOLUTION, 2006, 52 (3-4): : 467 - 484
  • [46] A Network Selection Algorithm for 5G Heterogeneous Environments
    Sgora, Aggeliki
    Bouropoulou, Nikolia
    Stamatelatos, Makis
    Konidaris, Agisilaos
    2022 IEEE CONFERENCE ON STANDARDS FOR COMMUNICATIONS AND NETWORKING, CSCN, 2022, : 48 - 52
  • [47] Efficient Path Selection for IoT Devices in Heterogeneous Service Environments
    Kim, Dae-Young
    Kim, Seokhoon
    ADVANCES IN COMPUTER SCIENCE AND UBIQUITOUS COMPUTING, 2017, 421 : 149 - 153
  • [48] Heterogeneous selection at specific loci in natural environments in Arabidopsis thaliana
    Weinig, C
    Dorn, LA
    Kane, NC
    German, ZM
    Hahdorsdottir, SS
    Ungerer, MC
    Toyonaga, Y
    Mackay, TFC
    Purugganan, MD
    Schmitt, J
    GENETICS, 2003, 165 (01) : 321 - 329
  • [49] SELECTION IN HETEROGENEOUS ENVIRONMENTS AND ITS MODELING BY THE THEORY OF SUBDIVIDED POPULATIONS
    LOESCHCKE, V
    BIOLOGISCHES ZENTRALBLATT, 1981, 100 (01): : 41 - 53
  • [50] A Network Selection Algorithm for 5G Heterogeneous Environments
    Sgora, Aggeliki
    Bouropoulou, Nikolia
    Stamatelatos, Makis
    Konidaris, Agisilaos
    2022 IEEE Conference on Standards for Communications and Networking, CSCN 2022, 2022, : 48 - 52