From micro to macroevolution through quantitative genetic variation: Positive evidence from field crickets

Department of Biology, McGill University, Montréal, Québec, H3A 1B1, Canada.
Evolution (Impact Factor: 4.61). 11/2004; 58(10):2287-304. DOI: 10.1554/04-059
Source: PubMed


Quantitative genetics has been introduced to evolutionary biologists with the suggestion that microevolution could be directly linked to macroevolutionary patterns using, among other parameters, the additive genetic variance/ covariance matrix (G) which is a statistical representation of genetic constraints to evolution. However, little is known concerning the rate and pattern of evolution of G in nature, and it is uncertain whether the constraining effect of G is important over evolutionary time scales. To address these issues, seven species of field crickets from the genera Gryllus and Teleogryllus were reared in the laboratory, and quantitative genetic parameters for morphological traits were estimated from each of them using a nested full-sibling family design. We used three statistical approaches (T method, Flury hierarchy, and Mantel test) to compare G matrices or genetic correlation matrices in a phylogenetic framework. Results showed that G matrices were generally similar across species, with occasional differences between some species. We suggest that G has evolved at a low rate, a conclusion strengthened by the consideration that part of the observed across-species variation in G can be explained by the effect of a genotype by environment interaction. The observed pattern of G matrix variation between species could not be predicted by either morphological trait values or phylogeny. The constraint hypothesis was tested by comparing the multivariate orientation of the reconstructed ancestral G matrix to the orientation of the across-species divergence matrix (D matrix, based on mean trait values). The D matrix mainly revealed divergence in size and, to a much smaller extent, in a shape component related to the ovipositor length. This pattern of species divergence was found to be predictable from the ancestral G matrix in agreement with the expectation of the constraint hypothesis. Overall, these results suggest that the G matrix seems to have an influence on species divergence, and that macroevolution can be predicted, at least qualitatively, from quantitative genetic theory. Alternative explanations are discussed.

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Available from: Derek Roff, Oct 10, 2015
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    • "The predictive power of quantitative genetics and the importance of genetic constraints in dictating patterns and pace of population differentiation depend on the stability of G. However, with recent theoretical and empirical developments, the question has switched from asking whether G is stable (Arnold et al. 2001) to assessing the conditions favouring its stability or influencing its evolution (Steppan et al. 2002; Jones et al. 2003; Begin & Roff 2004; Arnold et al. 2008). Arnold et al. (2008) have recently reviewed the evolutionary models put forth to elucidate the evolution of G-matrices. "
    Quantitative Genetics in the Wild, Edited by Anne Charmantier, Dany Garant, and Loeske E. B. Kruuk, 03/2014: chapter Evolutionary potential and constraints in wild populations: pages 190-208; Oxford University Press.
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    • "In the T method [19] the differentiation between two matrices is measured as the sum of the absolute differences between the two matrices’ elements. In particular, I used the T% statistic, in which the sum is made relative to the average size of the elements in the two matrices [20]: "
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    ABSTRACT: Background Comparing the covariation patterns of populations or species is a basic step in the evolutionary analysis of quantitative traits. Here I propose a new, simple method to make this comparison in two population samples that is based on comparing the variance explained in each sample by the eigenvectors of its own covariance matrix with that explained by the covariance matrix eigenvectors of the other sample. The rationale of this procedure is that the matrix eigenvectors of two similar samples would explain similar amounts of variance in the two samples. I use computer simulation and morphological covariance matrices from the two morphs in a marine snail hybrid zone to show how the proposed procedure can be used to measure the contribution of the matrices orientation and shape to the overall differentiation. Results I show how this procedure can detect even modest differences between matrices calculated with moderately sized samples, and how it can be used as the basis for more detailed analyses of the nature of these differences. Conclusions The new procedure constitutes a useful resource for the comparison of covariance matrices. It could fill the gap between procedures resulting in a single, overall measure of differentiation, and analytical methods based on multiple model comparison not providing such a measure.
    BMC Evolutionary Biology 11/2012; 12(1):222. DOI:10.1186/1471-2148-12-222 · 3.37 Impact Factor
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    • "In brief, the breeding experiment is based on a full-sibling design, where the genetic component of variation is estimated from the variation among families of full-siblings. Although the crickets were reared at three different temperatures (24 • C, 28 • C, and 32 • C), we pooled all families in this study to maximize the sample size (genetic covariance matrices for other morphological measurements were stable across temperatures; Bégin et al. 2004). An additional factor is that G. firmus is a wing dimorphic species, where some individuals have fully developed hindwings (long-winged morph) and others have reduced, nonfunctional hindwings (short-winged morph; Veazey et al. 1976; Roff 1986). "
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    ABSTRACT: The role of developmental and genetic integration for evolution is contentious. One hypothesis states that integration acts as a constraint on evolution, whereas an alternative is that developmental and genetic systems evolve to match the functional modularity of organisms. This study examined a morphological structure, the cricket wing, where developmental and functional modules are discordant, making it possible to distinguish the two alternatives. Wing shape was characterized with geometric morphometrics, quantitative genetic information was extracted using a full-sibling breeding design, and patterns of developmental integration were inferred from fluctuating asymmetry of wing shape. The patterns of genetic, phenotypic, and developmental integration were clearly similar, but not identical. Heritabilities for different shape variables varied widely, but no shape variables were devoid of genetic variation. Simulated selection for specific shape changes produced predicted responses with marked deflections due to the genetic covariance structure. Three hypotheses of modularity according to the wing structures involved in sound production were inconsistent with the genetic, phenotypic, or developmental covariance structure. Instead, there appears to be strong integration throughout the wing. The hypothesis that genetic and developmental integration evolve to match functional modularity can therefore be rejected for this example.
    Evolution 10/2010; 64(10):2935-51. DOI:10.1111/j.1558-5646.2010.01030.x · 4.61 Impact Factor
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