Báo cáo khoa học: "Macrogeographic and fine-scale genetic structure in a North American oak species, Quercus rubra"

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article Original Macrogeographic and fine-scale genetic structure in a North American oak species, Quercus rubra L VL Sork, S Huang, E Wiener Department of Biology, University of Missouri-St Louis, St Louis, MO, 63121-4499, USA Summary — Northern red oak, Quercus rubra L, is a widely distributed forest-dominant tree in North America. In this paper, we present the results of 2 studies examining macrogeographic and fine- scale genetic structure in the North American oak species Quercus rubra L. The first study used allo- zymes as genetic markers to examine the distribution of genetic variation within and among 10 wide- ly distributed populations in midwestern USA. Our results revealed a high level of genetic variability within the species and a moderate level of genetic differentiation among 10 populations sampled (F st 0.092). In the second study, we evaluated fine-scale genetic structure of northern red oak in a sin- = gle forest site in Missouri, USA. First, we used F-statistics to determine whether subpopulations in adjacent microhabitats on the scale of 1 ha show genetic differentiation within a 4-ha plot. Our find- ings showed very low values of differentiation (F 0.011).However, we also used a statistical tech- st = nique called spatial autocorrelation analysis to evaluate the spatial dispersion of alleles within a 4-ha mapped plot. These analyses revealed that genetic structure exists on a much smaller scale. Using 3 different algorithms, we found that near-neighbors have significant spatial autocorrelation which suggests that family structure occurs within the study population. population genetic structure / genetic variation / genetic differentiation / isozymes / spatial autocorrelation / Quercus rubra Résumé — Structure génétique du chêne rouge d’Amérique à l’échelle géographique et à celle du peuplement. Le chêne rouge d’Amérique (Q rubra L) est une espèce très répandue en Amérique du Nord. Cette contribution présente les résultats d’une analyse de la structure génétique de cette espèce faite à l’échelle géographique et du peuplement. La première partie concerne l’étude de l’organisation de la diversité génétique faite à partir de 10 populations éloignées les unes des autres et issues du Midwest des États-Unis et basée sur les isozymes. Les résultats ont montré une diversité génétique élevée à l’intérieur de l’espèce et une différenciation génétique moyenne entre les 10 populations étudiées (F 0,092). Dans la seconde partie, l’étude a porté sur la struc- sI = ture génétique à l’intérieur d’un peuplement donné situé dans une forêt de l’État de Missouri (États- Unis). Tout d’abord les F statistiques ont été utilisées pour estimer le niveau de différenciation entre sous- populations d’une surface d’un ha, l’ensemble couvrant une surface de 4 ha. Les résultats ont montré que ce niveau restait faible (F = 0,011). Dans un second temps, les techniques d’autocor- st rélation spatiale ont révélé que la population était génétiquement structurée à une échelle plus fine. L’utilisation de 3 algorithmes différents a montré que les proches voisins au sein du peuplement sont génétiquement liés, indiquant qu’une structure familiale existe au sein de la population. génétique / variabilité génétique / différenciation génétique / isozymes / autocorréla- structure tion spatiale / Quercus rubra
INTRODUCTION and among individuals within lations ) st (F subpopulations (F F or G a similar in- ). is st st , dex derived by Nei (1973), provide a The distribution of genetic variability in a measure of genetic differentiation among species is the outcome of gene flow, natu- subpopulations. ral and artificial selection and genetic drift. In the second study, we evaluated fine- Among wind-pollinated tree species, we scale genetic structure of northern and oak expect widespread gene flow within and in a single forest site in Missouri, USA. among populations (Loveless and Ham- First, we examined genetic structure within rick, 1984) and opportunities for genetic a location among adjacent subpopulations drift to be minimal. However, population of Q rubra using F-statistics. If such struc- differentiation and subdivision will occur if ture exists, it suggests that differential se- either pollen or seed dispersal is restricted lection may be responsible because gene or natural selection on a local scale is flow is not likely to be restricted in this strong (Slatkin, 1973; Endler, 1977). Popu- wind-pollinated species (Sork, unpublished lations which occur in heterogeneous envi- data). Because F-statistics are not always ronments may be susceptible to locally sensitive enough to detect patterns of ge- varying selection pressures which could netic patchiness, especially within the sub- cause genetic subdivision of local popula- population (Heywood, 1991), we also used tions (Wright, 1943). The extent to which spatial autocorrelation statistics. These population subdivision occurs in tree popu- have been proposed as a means of identi- lations is valuable to know because the fying the scale of genetic structure without spatial scale of genetic differentiation may prior knowledge about that scale (Sokal influence the evolutionary dynamics of the and Oden, 1978; Epperson and Clegg, populations. 1986; but see Slatkin and Arter, 1991). Northern red oak, Quercus rubra L, is a major forest-dominant species in tree North American deciduous forests (Braun, MATERIALS AND METHODS 1950). It is widely-distributed, ranging from southern Quebec and Ontario south to northern Florida, and from the eastern The sampling sites for the macrogeographical edges of Texas, Oklahoma and Kansas up study were 10 locations situated in the midwest- ern United States (fig 1, table I). These sites in- through Iowa east to southeastern Minne- clude northern, southern and western limits of sota (Schopmeyer, 1974). In this paper, the distribution of Q rubra. During June and July we present the results of 2 studies examin- of 1990 and 1991, we collected leaf tissue from ing macrogeographic and fine-scale genet- 25 adults at each location. Individual trees sam- ic structure in the North American oak spe- pled were > 10 m apart. cies Q rubra L. The first study used The intensive study site for the study of fine- allozymes as genetic markers to examine scale genetic structure was located at Tyson Re- the distribution of genetic variation within search Center, St Louis County, Missouri, USA, and among 10 widely distributed popula- an 800-ha ecological reserve administered by (38° Washington University. Tyson 31’N, tions. A frequently-used method of de- located on the northeastern end of 90°33’W) is scribing genetic structure is hierarchical F- the Ozark Plateau. The oak-hickory forest at Ty- statistics analysis (Wright, 1951, 1965). son comprises approximately 600 ha and is con- These statistics describe the extent to tiguous with approximately 2000 ha of forest on which genetic variation is distributed within adjacent public and privately-owned property. the total population (F among subpopu- Within the study site was located a 4-ha plot of ), it
oak-hickory forest which had been permanently 15°, range = 12-18°); and west-facing slope = gridded into 20 m x 20 m quadrants with all indi- with intermediate inclination (mean = 13°, range vidual trees with breast height diameter (DBH) > 10-15°) which we divided into lower west- = 2.5 cm labeled and mapped (Hampe, 1984). facing slope and upper west-facing slope. Dur- This plot included 4 microhabitats: north-facing ing the summer of 1990, we collected leaf sam- slope which had the greatest inclination (mean ples from all red oak adult trees (n = 226) on this = plot with DBH > 20 cm. 20°, range 15°-30°); southwest-facing (mean =
For both studies, leaves were collected from The F-statistics and genetic descriptive sta- tistics for the 10 widely distributed populations each individual with clipper poles, shot gun or and the 4 subpopulations within the intensive sling shot and then kept on ice until transported study plot were calculated using the program, back to the laboratory. Leaves were stored at BIOSYS-1 (Swofford and Selander, 1981). We -75 °C until ready for electrophoretic analysis. Starch-gels were run following the techniques used 15 loci for the macrogeographic analysis of genetic diversity and 11 polymorphic loci (0.99 of Gottlieb (1981) and Soltis et al (1983) using a phosphate extraction buffer (Mitton et al, 1977), level) for the estimation of F-statistics for both studies. For the spatial autocorrelation (SA) modified to 10% polyvinylpyrrolidone (Manos and Fairbrothers, 1987). The recipes for all en- analysis of Q rubra, we selected the 3 most vari- zymes were modified from Soltis et al (1983). able isozyme loci. The SA analysis was done We used buffer system 1 from Soltis et al using the program of Heywood (Dewey and Heywood, 1988). This program uses allozyme (1983) to detect 6-phosphogluconic dehydroge- nase (6PGD, EC 1.1.1.44), shikimate dehydrog- variation to calculate Moran’s I, a coefficient of enase (SDH, EC 1.1.1.25), phosphoglucomu- spatial autocorrelation (Sokal and Oden, 1978), which varies between + 1 (complete positive au- tase (PGM, EC 5.4.2.2), isocitrate dehydro- genase (IDH, EC 1.1.1.42) and malate dehy- tocorrelation) and -1 (complete negative auto- drogenase (MDH, EC 1.1.1.37). Buffer system 2 correlation) for any comparison of 2 individuals. We used 3 methods to calculate Moran’s I: near- (Soltis et al, 1983) was used for peroxidase est-neighbor maps which compare only 2 indi- (PER, EC 1.11.1.7). Buffer system 6 (Soltis et al, 1983) was used for phosphoglucoisomerase viduals, Gabriel-connected maps which com- (PGI, EC 5.3.1.9), triose-phosphate isomerase pare several neighboring individuals, and (TPI, EC 5.3.1.1),and acid phosphatase correlograms which examine all pairs of individu- (ACPH, EC 3.1.3.2). Buffer system 8 (Haufler, als within a specified distance class as a func- 1985) was used for fluorescent esterase (FES, tion of distance class. This latter method pro- EC 3.1.1-) and leucine- amino-peptidase (LAP, vides insight about the scale of genetic structure EC 3.4.11.1). All these enzymes have shown in- if it exists within the distance classes examined heritance patterns consistent with an interpreta- (for a more detailed description of these meth- tion of Mendelian inheritance. ods, see Sokal and Oden, 1978).
belii and Q macrocarpa (Schnabel and RESULTS AND DISCUSSION Hamrick, 1990a) and 18 other North Amer- ican oak species (Guttman and Weigt, Macrogeographic genetic structure 1989). In contrast, a mean heterozygosity of 0.081 was observed for 7 species of oaks in New Jersey, USA (Manos and of Q rubra maintain Individual populations relatively high levels of genetic variation Fairbrothers, 1987) but this area sampled is much smaller than that tested in other (table I). We found that the average per- studies. cent polymorphism across populations was 43%, the average number of alleles/locus The 10 populations surveyed showed a close to 2 1.97), and the (mean was = moderate degree of genetic differentiation heterozygosity ranged between mean based on the analysis of 11 polymorphic 0.136 and 0.231 with a mean of 0.167. We loci (overall F = 0.092, table II). This esti- st caution that these data may be biased up- mate of genetic differentiation among pop- ward because we selected loci that are ulations is at the high end of the range of likely to be polymorphic. At the species lev- values expected for wind-pollinated, long- el, we observed 3.19 alleles/locus with lived woody species (G 0.07-0.09; st = 94.1% showing some level of polymor- Hamrick and Godt, 1989) and in the middle phism in at least 1 population. of the range of G values summarized for st Our estimate of 0.167 average hetero- conifer species by El-Kassaby (1990), who reported a ranged of G values from 0 to zygosity is less than a mean value of 0.270 st 16.2% from 54 studies. However, our esti- reported for a sample of 11 studies of coni- mate of F is similar to that Schnabel and fer species (Mitton, 1983). However, our st similar to those found in Q gam- Hamrick (1990a) measured (G = 0.076 values st are
population, the hypothesis that iso- for 19 populations of Q macrocarpa and this zyme loci are neutral may be valid. The av- G 0.11 for 18 populations of Q gambe- st = erage fixation index is also low (F lii), but higher than that observed for 8 is = 0.067) which suggests that the adult sub- populations of Q rubra in Pennsylvania, populations are not inbred. This value is USA (Schwarzmann and Gerrold, 1991). slightly lower than the average level ob- The pattern of genetic differentiation that we observed in Q rubra is likely to be due served across populations (Fis 0.10, ta- = to a combination of factors. Because ble II). northern red oak occupies a great latitudi- finding that genetic differentiation Our nal range, natural selection due to environ- adjacent microhabitats is extremely across mental factors associated with that gradi- indicates that little population subdivi- low influence population ent may sion has occurred on this scale. However, differentiation. In addition, because of the this result contrasts with findings from a re- glacial history of midwestern United ciprocal transplant experiment at the same States, bottleneck effects, genetic drift and study site where we found evidence for lo- uneven migration patterns may all contrib- cal adaptation in seedling populations ute to a high degree of genetic differentia- (Sork et al, in press). In that study, a recip- tion (Schlarbaum et al, 1982). rocal transplant experiment utilizing acorns from maternal parents living in each micro- habitat revealed that percent leaf damage by insect herbivores was lower on seed- Fine-scale genetic structure The pattern of genetic variation based on 11 polymorphic loci measured on individu- al adults within the intensive study plot in Missouri is relatively high (table III) and quite comparable to the values reported for the macrogeographic survey (table I). Moreover, even within the microhabitats which are in the order of 1 ha in area, northern red oak maintains a large amount of variation. Although the microhabitats have unequal sample sizes (see table III), the general conclusions from these data should not be biased. That is, on every spatial scale-microhabitat, location and species, northern red oak has moderately high allelic diversity and heterozygosity. We analyzed the genetic structure of intensive study site and found that the our amount of genetic differentiation across 4 microhabitats is extremely low (F st = 0.011, table II). This low estimate is con- sistent across all 11 loci, suggesting that selection or some other factor has not act- ed on any of the individual loci. Thus, for
connections (Dewey and Heywood, 1988), lings grown in the maternal microhabitat. both algorithms demonstrate a pattern of Consequently, the set of isozyme genetic spatial autocorrelation. The 2 different meth- markers as measured on the adult popula- ods yield slightly different mean distances of tion in this study area seems neutral with nearest-neighbors with the Gabriel- respect to the selection of characters relat- connected map having a larger radius than ed to resistance to herbivores. This result the nearest-neighbor map (table V). Howev- indicates that quantitative characters which er, the scale of these differences is similar. are related to seedling performance may show significantly different patterns of ge- The correlogram suggests positive auto- netic differentiaton than isozyme genetic correlation for the 5 m distance class markers. which was significant (P < 0.05) for the FEST-2 and PER-1 loci (fig 2). Because Our additional analysis of fine-scale ge- this first distance class is the most likely netic structure using spatial autocorrelation one to reveal autocorrelation if there is iso- analysis on 3 loci (table IV) suggests that lation by distance, we only used this class structure may exist on a scale smaller than the microhabitat. We found that PER-1 and to test for significance from zero. After that distance class, the values vary around FEST-2 had positive SA for both the Ga- zero with an occasional value occurring briel-connected map and the nearest- much higher or lower but no clear pattern neighbor map at all 6 alleles (table IV). resulting. Consequently, we conclude that Moreover, Moran’s I was significantly great- the correlogram demonstrates a pattern of er than 0 for 2 alleles of PER-1 using the high relatedness among near-neighbors Gabriel-connected map and 1 allele of which is consistent with previous analyses PER-1 and 2 alleles of FEST-2 using the based on Gabriel-connected and nearest- nearest-neighbor map. Although the Ga- neighbor maps but random fluctuations af- briel-connected map provides a more pow- ter that distance. erful test of SA due to the greater number of
none of the allozymes using the near- and est-neighbor map (table IV). This pattern was not significant in the correlogram (fig where all 3 alleles at the 5 m distance 2) class have slightly negative values of Mo- ran’s I. This result is too weak to determine whether selection or disassortative mating is acting on the SDH1 allele or whether a the correlation is spurious. While it is not easy to infer mechanisms from spatial autocorrelation analyses (Slat- kin and Arter, 1991),we suggest that this pattern is more likely due to restricted gene dispersal than spatially variable selection. Because we know that Q rubra in this popu- lation and elsewhere (Schwartzmann and Gerhold, 1991; Sork et al, 1992) has high outcrossing rates, it is unlikely that pollen dispersal is restricted to the scale of 5 m. However, seed dispersal by mammals is re- stricted and often results in dispersal dis- tances of less than 10 m (Sork, 1984). While it is also possible that acorns may be dispersed by birds at greater distances, if a large proportion of the acorn crop falls beneath the canopy or is removed only short distances by mammals, local family clusters may result. The spatial autocorre- lation observed in this study is consistent with that scenario. Family clusters resulting from restricted seed dispersal have also been proposed for ponderosa pine (Linhart et al, 1981). Our finding of significant spatial autocor- relation is similar to that found in Gleditsia triacanthos where the occurrence of signifi- cant autocorrelation at several loci for sam- pled juveniles indicates genetic substruc- turing that also might be due to family clusters (Schnabel and Hamrick, 1990b). In contrast, a study of Pinus contorta where individuals were sampled at 15-m pattern of intervals in 2 Washington, USA popula- In contrast to this near- tions (Epperson and Allard, 1989) reported neighbor autocorrelation, SDH showed a significant negative SA at 1 of the 3 allo- little autocorrealtion except for a few loci. Those authors concluded that long dis- zymes using a Gabriel-connected map
types within populations of lodgepole pine. tance pollen and seed dispersal reduces Genetics 121, 369-377 the opportunity for genetic structure but se- lection may be affecting the genotypes at Gottlieb LD (1981) Electrophoretic evidence and plant populations. In: Progress in Phytochem- those significant loci. The Pinus results istry, (Reingold J, Harborne JB, Swain T, eds), may differ from our oak results because Pergamon Press, New York, vol 8,1-46 dispersal of pine seeds differs dramatically Guttman LI, Weigt LA (1989) Electrophoretic evi- from acorns. Until we see a broader range dence of relationships among Quercus of studies which evaluates the genetic (oaks) of eastern North America. Can J Bot structure within tree populations, we can- 67, 339-351 not determine the extent to which this com- Hampe CL (1984) A description of species com- ponent of genetic variation is important. position, population structures, and spatial patterns in a Missouri oak-hickory forest. MS thesis, Univ Missouri, St Louis ACKNOWLEDGMENTS Hamrick JL, Godt MJ (1989) Allozyme diversity in plant species. In: Plant Population Genet- ics Breeding, and Genetic Resources (Brown We thank AM Escalante and G Coello for consid- AHD, Clegg MT, Kahler AL, Weir BS, eds) erable help with the electrophoresis; M Cecil and Sinauer Associates, Sunderland, MA, 43-63 A Klemm for help in the laboratory; and K Stowe, Haufler CH (1985) Enzyme variability and J Frazee, N Schellhorne, and C Hochwender for modes of evolution in Bommeria (Ptrida- field assistance. We are grateful to J Hamrick and ceae). Syst Bot10, 92-104 J Heywood for comments on this manuscripts. This project is supported by a National Science Heywood JS (1991) Spatial analysis of genetic Foundation grant (BSR-8814620) to VLS. variation in plant populations. Annu Rev Ecol 335-355 Syst 22, Linhart YBJ, Mitton B, Sturgeon KB, Davis ML REFERENCES (1981) Genetic variation in space and time in a population of ponderosa pine. Heredity 46, 407-426 Braun L (1950) Deciduous Forests of Eastern Loveless MD, Hamrick JL (1984) Ecological de- North America. McGraw-Hill, New York, USA terminants of genetic structure in plant popu- Dewey SE, Heywood JH (1988) Spatial genetic lations. Annu Rev Ecol Syst 15, 65-95 structure in a population of Psychotria nervo- Manos PS, Fairbrothers DE (1987) Allozyme sa. I. Distribution of genotypes. Evolution 42, variation in populations of six northeastern 834-838 American red oaks (Fagaceae: Quercus YA (1990) Genetic variation within El-Kassaby subg Erythrobalanus). Syst Bot 12, 365-373 and among conifer populations: review and Mitton JB (1983) Conifers. In: Isozymes in Plant evaluations of methods. In: Biochemical Genetics and Breeding, Part B (Tanksley S, Markers in the Population Genetics of Forest Orton T, eds) Elsevier, Amsterdam, 443-472 Trees (Hattemer HH, Fineschi S, eds) Aca- demic Press, The Hague, 59-74 Mitton JB, Linhart YB, Hamrick JL, Beckman JH (1977) Observations on the genetic structure Endler JA (1977) Geographical Variation, Speci- and mating system of ponderosa pine in the ation, and Clines. Princeton University Press, Colorado Front Range. Theor Appl Genet 51, Princeton, NJ 5-13 Epperson BK, Clegg MT (1986) Spatial- Nei M (1973) Analysis of genetic diversity in autocorrelation analysis of flower color poly- subdivided populations. Proc Natl Acad Sci morphisms within substructured populations USA 70, 3321-3323 of morning glory (Ipomoea purpurea). Am Nat 128, 840-858 (1978) Estimation of average heterozy- Nei M and genetic distance from a small gosity Epperson BK, Allard RW (1989) Spatial autocor- the distribution of geno- number of individuals. Genetics 89, 583-590 relation analysis of
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