Comparing the adaptive landscape across trait types: larger QTL effect size in traits under biotic selection
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BMC Evolutionary Biology 2011, 11:60 doi:10.1186/1471-2148-11-60Published: 7 March 2011
In a spatially and temporally variable adaptive landscape, mutations operating in opposite directions and mutations of large effect should be commonly fixed due to the shifting locations of phenotypic optima. Similarly, an adaptive landscape with multiple phenotypic optima and deep valleys of low fitness between peaks will favor mutations of large effect. Traits under biotic selection should experience a more spatially and temporally variable adaptive landscape with more phenotypic optima than that experienced by traits under abiotic selection. To test this hypothesis, we assemble information from QTL mapping studies conducted in plants, comparing effect directions and effect sizes of detected QTL controlling traits putatively under abiotic selection to those controlling traits putatively under biotic selection.
We find no differences in the fraction of antagonistic QTL in traits under abiotic and biotic selection, suggesting similar consistency in selection pressure on these two types of traits. However, we find that QTL controlling traits under biotic selection have a larger effect size than those under abiotic selection, supporting our hypothesis that QTL of large effect are more commonly detected in traits under biotic selection than in traits under abiotic selection. For traits under both abiotic and biotic selection, we find a large number of QTL of large effect, with 10.7% of all QTLs detected controlling more than 20% of the variance in phenotype.
These results suggest that mutations of large effect are more common in adaptive landscapes strongly determined by biotic forces, but that these types of adaptive landscapes do not result in a higher fraction of mutations acting in opposite directions. The high number of QTL of large effect detected shows that QTL of large effect are more common than predicted by the infinitesimal model of genetic adaptation.