Population Divergence along a Genetic Line of Least Resistance in the Tree Species Eucalyptus globulus

Abstract

The evolutionary response to selection depends on the distribution of genetic variation in traits under selection within populations, as defined by the additive genetic variance-covariance matrix (G). The structure and evolutionary stability of G will thus influence the course of phenotypic evolution. However, there are few studies assessing the stability of G and its relationship with population divergence within foundation tree species. We compared the G-matrices of Mainland and Island population groups of the forest tree Eucalyptus globulus, and determined the extent to which population divergence aligned with within-population genetic (co)variation. Four key wood property traits exhibiting signals of divergent selection were studied-wood density, extractive content, and lignin content and composition. The comparison of G-matrices of the mainland and island populations indicated that the G-eigenstructure was relatively well preserved at an intra-specific level. Population divergence tended to occur along a major direction of genetic variation in G. The observed conservatism of G, the moderate evolutionary timescale, and close relationship between genetic architecture and population trajectories suggest that genetic constraints may have influenced the evolution and diversification of the E. globulus populations for the traits studied. However, alternative scenarios, including selection aligning genetic architecture and population divergence, are discussed.

Keywords: Eucalyptus globulus; additive genetic variance-covariance matrix; evolvability; genetic constraint; genetic line of least resistance; quantitative genetics; response to selection; wood properties.

Figure 1

Simulated sampling distributions and 95% confidence intervals (depicted by the dashed vertical lines), obtained by the REML-MVN sampling approach [85], for the statistic ${\Psi }_m$ used to assess whether the mean-standardized G-matrices estimated for the Mainland and Island population groups shared a similar orientation, based on the following measures directly computed from a between-matrix comparison: (a) mean angle between vectors of response to a set of randomly-generated selection gradients (i.e., "random skewers"); and (b) Krzanowski’s index of overall similarity in orientation between matrix subspaces. For a given measure, the statistic ${\Psi }_m$ evaluates whether differences within matrices due to sampling error are similar to differences between matrices (Equation (9) in [86]; see Methods S7). When overlapping with zero, a 95% confidence interval for ${\Psi }_m$ indicates statistical support for similarity in orientation between the two matrices being compared.

Figure 2

Observed mean-scaled unconditional evolvabilities (e; black dots) and conditional evolvabilities (c; white dots) for each E. globulus population in the direction of its divergence from the inferred ancestral states, plotted against the amount of divergence in that direction. For comparison with the observed evolvabilities along the direction of population divergence, the dashed horizontal lines indicate (after [6,9]): the expected unconditional and conditional evolvabilites in a random direction, denoted as $\overline{e}$ and $\overline{c}$, respectively; the maximum and minimum possible values for either unconditional or conditional evolvability, denoted as e(max) and e(min), respectively. All the evolvability estimates were based on the mean-standardized G-matrix common to all populations, and further details are provided in Table 2.