Quantitative Trait Loci Differentiating the Outbreeding Mimulus guttatus From the Inbreeding M . PZutycaZyx

Theoretical predictions about the evolution of selfing depend on the genetic architecture of loci controlling selfing (monogenic us. polygenic determination, large us. small effect of alleles, dominance us. recessiveness), and studies of such architecture are lacking. We inferred the genetic basis of mating system differences between the outbreeding Mimulusguttatus and the inbreeding M. platycalyx by quantitative trait locus (QTL) mapping using random amplified polymorphic DNA and isozyme markers. One to three QTL were detected for each of five mating system characters, and each QTL explained 7.628. 6% of the phenotypic variance. Taken together, QTL accounted for up to 38% of the variation in mating system characters, and a large proportion of variation was unaccounted for. Inferred QTL often affected more than one trait, contributing to the genetic correlation between those traits. These results are consistent with the hypothesis that quantitative variation in plant mating system characters is primarily controlled by loci with small effect. T HE evolution of selfing has been studied in a variety of theoretical models, each with specific assumptions about its inheritance. Most models assume selfing rate to be controlled by a single locus with two alleles (e.g., FISHER 1941; CHARLESWORTH 1980; HOLSINGER et al. 1984; CAMBELL 1986; CHARLESWORTH et al. 1990). A purely polygenic basis for selfing was invoked by L W D E and SCHEMSKE (1985) in their models for the joint evolution of selfing and inbreeding depression. LATTA and RITLAND (1993) emphasized how facets of the genetic architecture (number of loci, average allelic effect, level of dominance) can affect the equilibrium selfing rate. However, empirical studies of the underlying genetic architecture of selfing are lacking. Biometrical methods (those based on phenotypic variances of segregating generations, cJ WRIGHT 1968; LANDE 1981) have been used to estimate the number of loci controlling floral character differences for a few plant species. FENSTER and RITLAND (1994) estimated between five and 12 loci for the differences in several mating system characters between M. guttatus and two other inbreeding taxa, M. mimanthus and M. laciniatus, but these estimates suffered from large standard errors. MACNAIR and CUMBES (1989) estimated between three and seven loci controlling the floral differences between the outbreeder M. guttatus and a copper-tolerant inbreeder M. cup-iphilus. Variation in anther-stigma separation between populations was estimated to be conCorresponding author: Jing-Zhong Lin, Division of Biological Sciences, University of Montana, Missoula, MT 59812. E-mail: jzlin@selway.umt. edu ish Columbia, Vancouver, BC V6T 124 Canada. ' Currat address: Department of Forest Sciences, University of BritGenetics 146 11151121 (July, 1997) trolled by at least seven loci in Clarkia temblorimsis (HOLTSFORD and ELLSTRAND 1992), and at least five loci in Turnera ulmifolia var. angustifolia (SHORE and BARRETT 1990). Anther-stigma separation has been found to be highly correlated with outcrossing rate in many self-compatible species (e.g. , RITLAND and RITLAND 1989; HOLTSFORD and ELLSTRAND 1992; BELAOUSSOFF and SHORE 1995), implying that selfing rate is controlled by several loci. However, biometrical methods have assumptions, such as additivity of gene effect, independence of loci and equality of allele effects, whose violation will bias estimates downward (ZENG et al. 1990). Furthermore, most biometrical techniques (save for those requiring generation of inbred lines) only infer average effects over all genes and do not identify individual gene effects. Until recently, evolutionists have not exploited the potential for gene mapping with molecular markers to identify and characterize quantitative trait loci (QTL). The genus Mimulus (Scrophulariaceae) is an ideal experimental system for QTL mapping because species are often intercrossable (VICKERY 1978) yet morphologically distinct. In a seminal study, BRADSHAW et al. (1995) employed QTL mapping techniques to detect individual QTL of large effect responsible for reproductive isolation between the bird-pollinated M. cardinalis and the bee-pollinated M. lauisii. In this paper, we employ QTL mapping to detect QTL responsible for differences of selfing rate between the two yellow monkeyflowers, M. guttatus and M. platycalyx. We first constructed a linkage map consisting of two isozyme and 99 random amplified polymorphic DNA (RAPD) markers, based on a backcross involving the 1116 J-Z. Lin and K. Ritland outbreeding M. guttatus and the inbreeding M. platycalyx (LIN and FUTLAND 1996a). This linkage map is used in this paper to infer the QTL map for each of six mating system characters differing between M. guttatus and M. platycalyx. We note that, as a quantitative trait, the actual rate of self-fertilization is difficult to measure, as it is inferred indirectly via marker segregation patterns among many progeny (HAUPTLI and JAIN 1985). An efficient alternative, employed here and by the aforementioned quantitative genetic studies, is to examine characters functionally related to selfing. We also use selective genotyping (the selective assay of genotypes at he extreme of the phenotypic distribution, c.J LANDER and BOTSTEIN 1989; LIN and RITLAND 1996b) to increase the power of QTL detection. The inferred QTL map gives the minimum number of loci for mating system differences among taxa, as well as the distribution of QTL effects. In particular, we seek to identify QTL with large effect on mating system characters. Finally, the shift from outcrossing to selfing is frequently associated with a change of an entire syndrome of selfing correlates, all related to male allocation and inbreeding avoidance (e.g., reduced attraction to pollinators and reduction of the spatial and temporal separation of male and female reproductive organs within the flower, CJ: ORNDUFF 1969; JAIN 1976; RITLAND and RITLAND 1989). This shift from outcrossing to selfing thus creates strong genetic correlations among mating system characters. Genetic correlations are caused either by genes with pleiotropic effects or by closely linked genes (FALCONER 1989, ch. 19). Linkage mapping can distinguish between these two causes of genetic correlations UIANG and ZENC 1995) through QTL comparisons of maps for different characters. Thus, in this study we also compare the similarity of QTL locations for different traits to determine if pleiotropy underlies the genetic correlations of mating system charac-