Microsatellite Diversity Correlated with Ecological-Edaphic and Genetic Factors in Three Microsites of Wild Emmer Wheat in North Israel

Youchun Li*, Tzion Fahima*, Abraham B. Korol*, Junhua Peng*, Marion S. Röder{dagger}, Valery Kirzhner*, Avigdor Beiles* and Eviatar NevoGo,*

*Institute of Evolution, University of Haifa, Haifa, Israel; and
{dagger}Institute of Plant Sciences and Crop Plant Research, Gatersleben, Germany


    Abstract
 TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Acknowledgements
 literature cited
 
This study was conducted to test the effects of internal (genetic) and external factors on allelic diversity at 27 dinucleotide microsatellite (simple sequence repeat [SSR]) loci in three Israeli natural populations of Triticum dicoccoides from Ammiad, Tabigha, and Yehudiyya, north of the Sea of Galilee. The results demonstrated that SSR diversity is correlated with the interaction of ecological and genetic factors. Genetic factors, including genome (A vs. B), chromosome, motif, and locus, affected average repeat number (ARN), variance in repeat number ({sigma}), and number of alleles (NA) of SSRs, but the significance of some factors varied among populations. Genome effect on SSR variation may result from different motif types, particularly compound (or imperfect) versus perfect motifs, which may be related to different evolutionary histories of genomes A and B. Ecological factors significantly affected SSR variation. Soil-unique and soil-specific alleles were found in two edaphic groups dwelling on terra rossa and basalt soils across macro- and microgeographical scales. The largest contributions of genetic and ecological effects were found for diversity of ARN and NA, respectively. Multiple regression indicated that replication slippage and unequal crossing over could be important mutational mechanisms, but their significance varied among motifs. Edaphic stresses may affect the probability of replication errors and recombination intermediates and thus control diversity level and divergence of SSRs. The results may indicate that SSR diversity is adaptive, channeled by natural selection and influenced by both internal and external factors and their interactions.


    Introduction
 TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Acknowledgements
 literature cited
 
Microsatellites, or simple sequence repeats (SSRs), are tandem repeats of short oligonucleotides that are ubiquitously interspersed in eukaryotic genomes (Tautz and Renz 1984Citation ; Kashi, King, and Soller 1997Citation ) and show high allelic diversity (Morgante and Olivieri 1993Citation ; Thomas and Scott 1993Citation ; Becker and Heun 1995Citation ; Van Treuren et al. 1997Citation ). SSRs are the fastest-evolving DNA sequences, with mutation rates of 10-2–10-3 per locus per gamete per generation (Weber and Wong 1993Citation ). Such mutations are frequent, site-specific, and readily reversible (King and Soller 1999Citation ). Some authors have sought to explain the ubiquitous occurrence of SSRs in terms of functional and regulatory significance (e.g., Stallings et al. 1991;Citation Kashi, King, and Soller 1997Citation ; King and Soller 1999Citation ), but most models of simple repeat evolution assume selective neutrality (Tachida and Iizuka 1992Citation ; Shriver et al. 1993Citation ; Valdes, Slatkin, and Freimer 1993Citation ; Di Rienzo et al. 1994Citation ; Stephan and Kim 1998Citation ). In fact, allelic sizes are rather strictly constrained (Garza, Slatkin, and Freimer 1995Citation ; Nauta and Weissing 1996Citation ; Feldman et al. 1997Citation ). Levels of diversity vary across different SSR loci and populations within species (e.g., Saghai-Maroof et al. 1994Citation ; Innan, Terauchi, and Miyashita 1997Citation ). Mutational biases or selective constraints on allele size may truncate and cause convergence of allelic distributions in divergent populations or species (Garza, Slatkin, and Freimer 1995Citation ; Slatkin 1995;Citation Amos et al. 1996Citation ; Nauta and Weissing 1996Citation ; Primmer et al. 1996Citation ; Zhivotovsky, Feldman, and Grishechkin 1997Citation ). Some authors suggest that natural selection controls the level of SSR diversity (e.g., Harding, Boyce, and Clegg 1992Citation ; Epplen et al. 1993Citation ; Stephan and Cho 1994Citation ; Garza, Slatkin, and Freimer 1995Citation ; Innan, Terauchi, and Miyashita 1997Citation ; Kashi, King, and Soller 1997Citation ; King and Soller 1999Citation ).

It has been suggested that the evolution of noncoding, tandemly repetitive DNAs is driven by slippage during DNA replication (Levinson and Gutman 1987Citation ; Wolff et al. 1991Citation ; Tautz and Schlötterer 1994Citation ; Stephan and Kim 1998Citation ), unequal crossing over (Harding, Boyce, and Clegg 1992Citation ), or gene conversion (Drake, Glickman, and Ripley 1983Citation ; Tautz and Renz 1984Citation ). Among these, replication slippage seems to play a more important role in producing new alleles at SSR loci (Levinson and Gutman 1987Citation ; Wolff et al. 1991Citation ; Innan, Terauchi, and Miyashita 1997Citation ). Stephan and Cho (1994)Citation simulated SSR evolution using a model of replication slippage, unequal crossing over, mutation, and natural selection. This model suggested that (1) unequal crossing over is a dominant long-range ordering force keeping these arrays homogeneous even in regions of very low recombination rates; (2) replication slippage may cause SSR variation, but unequal crossing over does not act on very short tracts of SSRs; and (3) natural selection plays an essential role in controlling the length of a repeat.

However, the relationship between repeat number and amount of expected diversity according to this mechanism was not consistent among studies (e.g., Weber 1990Citation ; Hudson et al. 1992Citation ; Valdes, Slatkin, and Freimer 1993Citation ; Bell and Ecker 1994Citation ; Plaschke, Ganal, and Röder 1995Citation ). In Arabidopsis thaliana, chromosome effect was significant for the number of alleles, but the effects of motif and unequal crossing over were not significant for SSR diversity (Innan, Terauchi, and Miyashita 1997Citation ). In other species, no clear conclusions have been reached on the genetic effects of SSR diversity.

Wild emmer wheat, Triticum dicoccoides (Poaceae), is the tetraploid progenitor of cultivated wheats (Zohary 1970Citation ) and carries two genomes (A and B) with 2n = 28 chromosomes. Genome A was derived from Triticum monococcum ssp. urartu, and genome B was derived from an ancient S genome of a species that was similar to the extant Triticum speltoides (Friebe and Gill 1996Citation ). Triticum dicoccoides is distributed over the Near East Fertile Crescent, but its center of distribution is found in the Upper Jordan Valley and surrounding areas. In this area, wild emmer grows as a highly selfing annual grass in several steppe-like herbaceous formations in Quercus ithaburensis or in Quercus brantii open park forest belts (Zohary 1973Citation ; Nevo and Beiles 1989Citation ). It grows mainly on basaltic and terra rossa soil types. The previous microgeographic studies using allozyme and random amplified polymorphic DNA (RAPD) markers for T. dicoccoides showed significant nonrandom adaptive molecular genetic differentiation at single- and multilocus levels in contrasting soils, topographies, and climates (Nevo, Beiles, and Krugman 1988a, 1988bCitation ; Nevo and Beiles 1989Citation ; Nevo et al. 1991Citation ; Fahima et al. 1999Citation ; Li et al. 1999Citation ).

Recently, 93 and 115 SSR loci were mapped on genomes A and B, respectively (Röder et al. 1998Citation ). The markers are randomly distributed along the linkage map, with clustering in several centromeric regions. However, we are still short of evidence on intra- and intergenomic variation of SSR in natural populations. Similar genetic patterns were observed at allozyme, RAPD, and SSR loci for an Ammiad population (Li et al. 2000Citation ). However, the ecological effects, including the edaphic effect on SSR diversity, are poorly known. The present study investigated SSR diversity of three natural populations of T. dicoccoides and examined genetic and ecological effects on SSR diversity in three populations of T. dicoccoides from Ammiad, Tabigha, and Yehudiyya in north Israel.


    Materials and Methods
 TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Acknowledgements
 literature cited
 
Plant Materials
The present study involved 335 individuals of T. dicoccoides collected from three sites around the Sea of Galilee in Israel (fig. 1 ).



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Fig. 1.—Geographic distribution and soil types of the three tested populations of wild emmer wheat in Israel

 

  1. The Ammiad (A) population is situated at a mean altitude of 300 m, with annual rainfall of 580 mm. Ammiad harbors an extensive population of wild emmer wheat growing on terra rossa soil, but it is diversified topographically, lithologically, and microclimatically (Nevo et al. 1991Citation ; Noy-Meir et al. 1991Citation ). Sampling (N = 75) was conducted in 1993 at this site.
  2. The Tabigha (T) population is located at the Mediterranean sea level, and its annual rainfall is 436 mm. This microsite includes two sharply separated soil types: terra rossa and basalt soils. Sampling was conducted in 1985 in two transects. Each transect was equally divided into 50 m of terra rossa and 50 m of basalt across a sharp geological boundary (about 1 m). Seeds were collected from 50 plants about 1 m apart from each other in each half of each transect (Nevo, Beiles, and Krugman 1988aCitation ). The present study included 155 individuals (79 and 76 from terra rossa and basalt, respectively) from two transects.
  3. The Yehudiyya (Y) population is located in an open oak park forest of Q. ithaburensis on basalt soil at the lower basalt foothills of the Golan Heights with an altitude of 200 m and an annual rainfall of 550 mm. Sampling was conducted in 1985 in the two niches at this microsite (Nevo, Beiles, and Krugman 1988bCitation ). In total, 105 individuals were examined in this study.

The three populations were classified into two edaphic groups according to soil type. The terra rossa (TR) group included the Ammiad population plus plants from the terra rossa microniche at Tabigha. The basalt (BA) group included the Yehudiyya population plus plants from the basalt microniche at Tabigha. The sample sizes were 151 and 184 individuals for the TR and BA groups, respectively.

The caolinitic terra rossa soil studied here developed on Middle Eocene hard limestone rocks and is unique in its characteristics: Available water is low (7%–9% of weight), exchange cation level is low (20–40 milliequivalent for 100 g soil), and no free Ca is found. The ratio between Ca and Mg is high (10–40), pH is relatively low (6–7), and the amount of P (phosphate) is relatively high. The plant association on this soil in Tabigha is unique (Nevo, Beiles, and Krugman 1988aCitation ), consisting of Andropogon hirsuta and Echinops viscosus (climax Zizyphus spina-Christi and Zizyphus lotus), Carlina corymbosa, Notobasis syriaca, Capparis spinosa, Erucaria myagroides with Ferula communis, Gundelia tournefortii, Phagnalon rupestre, Varthemia iphionoides, Dianthus multipunctatus, and the wild cereals Hordeum bulbosum, Hordeum spontaneum, and T. dicoccoides (less abundant than on basalt, and primarily the yellow spike morph).

The basalt soil is dark and clayey (montmorilonite) and developed on Upper Pleistocene basalt flows; it differs greatly from the terra rossa in its characteristics. It is poor in Ca, heavy, and rich in P, and available water is high (9%–12% of weight). The pH is relatively high (7.7–8.0). General and available amounts of P are higher in the basalt than in the terra rossa. The plant association and even some morphological characteristics of wild emmer plants on this soil (Nevo, Beiles, and Krugman 1988aCitation ) are different from those on the terra rossa. Plant association comprises Psoralea hirsuta and Echinops blancheanus (climax of Pistacia atlantica, Z. spina-Christi and Z. lotus), with Scolymus maculatus, Cichorium pumilum, Carthamus glaucus, Echium judaicum, Hirschfeldia incana, and Sinapis arvensis, and wild cereals Brachypodium distachyum, Phalaris bulbosum, Avena sterilis, H. bulbosom, H. spontaneum, and abundant T. dicoccoides (primarily the black spike morph). The intimate relationship between soil and vegetation was discussed in detail by Rabinovitch-Vin (1986)Citation .

Microsatellite PCR Analysis
Genomic DNA was extracted from seedlings using the method of Junghans and Metzlaff (1990)Citation . The 28 dinucleotide microsatellite DNA markers used in this study were described by Röder et al. (1995, 1998)Citation . These markers are located on different arms (one for each arm) of 14 chromosomes of T. dicoccoides. Table 1 presents the locus, repetitive motif, chromosomal location, and distance from the centromere (D). The procedure used to detect microsatellite polymorphism followed Fahima et al. (1998)Citation .


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Table 1 Motifs and Chromosomal Locations of 28 SSR Loci of Wheat Used in this Study

 
Data Analysis
Fragment sizes were estimated on the Fragment Manager (Pharmacia) computer program by comparison with internal size standards that were added to each lane in the loading buffer. Repeat number was calculated by comparison with the fragment sizes and number of repeat units at the corresponding locus in the cultivar Chinese Spring (Triticum aestivum; see Röder et al. 1995, 1998Citation ).

Since almost half of the 28 SSR markers used are compound or imperfect SSRs, and such SSRs may conform more closely to an "infinite alleles" model (Goldstein et al. 1995Citation ; Angers and Bernatchez 1997Citation ; Feldman et al. 1997Citation ), Nei's (1973)Citation gene diversity (He) was used to estimate SSR diversity. Number of alleles (NA) and He were calculated using the POPGENE program (Yeh et al. 1997Citation ). The STATISTICA program (Statsoft 1996Citation ) was used for statistical analyses. The Kruskal-Wallis one-way analysis of variance by rank (Siegel and Castellan 1988Citation ) was used to test for difference in average repeat number, since the distribution of repeat number at a locus is not normal. Wilcoxon's signed rank test (Siegel and Castellan 1988Citation ) was used to test significance of difference in SSR diversity among subpopulations by pairwise comparisons. Levene's test (Statsoft 1996Citation ) and Hartley's F ratio (Statsoft 1996Citation ) were used to test homogeneity of variance among the three populations and the two edaphic groups. Soil-specific alleles are those that significantly (by the {chi}2 test) predominate in one of the two soil types (either TR or BA) at both microgeographic (Tabigha microsite) and macrogeographic (Ammiad [TR] vs. Yehudiyya [BA] populations) levels. Soil-unique alleles are those that present in only one (either TR or BA) of the two soil types simultaneously at micro- and macrogeographic levels. A permutation test was performed for the observed allele soil specificity and soil uniqueness. For this analysis, rare alleles (with less than 15 copies per population) were excluded from consideration. Multivariate analysis of variance (MANOVA) was used to estimate effects and contributions of genetic and environmental factors on SSR diversity.

To estimate determination coefficients of internal (genetic) mechanisms and external (environmental) factors to SSR variation, multiple regression analysis was performed. The independent variables included D, average repeat number (ARN), edaphic group, motif, and their interactions. The dependent variables included NA and variance in repeat number ({sigma}2).


    Results
 TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Acknowledgements
 literature cited
 
SSR Divergence Among the Three Populations of T. dicoccoides
The SSR alleles were labeled using repeat numbers of motifs. The distributions of alleles differed in the three populations. The NA per locus was significantly lower in the A population (mean NA = 5.6) than in the T (mean NA = 7.7) and the Y (mean NA = 6.7) populations at most SSR loci. The proportions of polymorphic loci were 0.923, 0.963, and 0.926 in the A, T, and Y populations, respectively. The observed SSR diversity (He; Nei 1973Citation ) in the T population (He = 0.709) was significantly higher than that in the A population (He = 0.596; Wilcoxon's signed-ranks test, z = 2.085, P < 0.05). The He in the Y population (He = 0.674) was between that in the A population and that in the T population. This presumably reflects two soil types in the T population versus only one soil type in the A and Y populations.

Among the three populations, the ARNs were significantly different at 23 polymorphic loci (Kruskal-Wallis test, P < 0.05–0.00005; table 2 ). Wilcoxon's signed-ranks test showed that the ARN over all loci except GWM577 and 601 was significantly larger in the Y population than in the other two (z = 2.623, P < 0.01). {sigma}2 differed significantly at 25 loci among the three populations (Levene's test, P < 0.05–0.00005). At 15 loci, the A population showed much higher values of {sigma}2 than did the T and Y populations. Over all loci considered simultaneously, the {sigma}2 value for the A population was significantly greater (Wilcoxon's signed-ranks test, P < 0.01) than those for the T (z = 2.677) and Y (z = 2.785) populations (table 2 ).


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Table 2 Simple Sequence Repeat (SSR) Diversity at 27 Loci in Ammiad (A), Tabigha (T), and Yehudiyya (Y) Populations of Triticum dicoccoides

 
SSR Divergence Between Terra Rossa and Basalt Groups
Between the TR and BA groups, significant SSR diversity was observed at most of the loci assayed (table 3 ). ARN was significantly (P < 0.01–0.00005) higher in the BA group than in the TR group at 12 loci. An opposite ARN trend was observed at eight other loci between the two edaphic groups. The values of {sigma}2 were significantly larger at 15 loci in the TR group than in the BA group (P < 0.01–0.00005). The opposite pattern of {sigma}2 was observed at only five other loci. Pairwise comparison (Wilcoxon's signed-ranks test) showed that the {sigma}2 in repeat number over all 27 SSR loci was significantly (z = 2.53, P < 0.05) higher in the TR group ({sigma}2 = 40.15) than in the BA group ({sigma}2 = 20.76).


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Table 3 Comparison of Simple Sequence Repeat (SSR) Diversity in Terra Rossa (TR) and Basalt (BA) Soil Groups

 
In the TR and BA groups, 364 alleles were observed. Only 175 alleles were shared between the two edaphic groups (table 3 ). After the exclusion of rare alleles observed in <=14 individuals based on 0.05 probability of chance, eight BA-specific and seven TR-specific alleles were found ({chi}2 test, P < 0.05). Among these soil-specific alleles, one TR-unique and one BA-unique allele were found. Permutation tests were conducted to determine the effects of random drift. For this, genotypes within each pair of soil groups (micro- and macrogeographic) were randomly shuffled, maintaining the initial sample sizes. Out of 106 randomly shuffled sets, in no case did the number of soil-specific alleles exceed four. Thus, the significance of the 15 soil-specific alleles really observed is at least <10-6. Moreover, in no case did the random permutations produce any soil-unique allele in the foregoing sense. This result suggests with high confidence the nonrandomness of the revealed soil-specific population differentiation. Moreover, the fact that 2 out of 15 soil-specific alleles appeared to be soil-unique may indicate that these two alleles are not only markers linked to the selected loci, but are the selected targets themselves (or sites within selected genes).

SSR diversity (He; Nei 1973Citation ) was estimated for the two edaphic groups (table 3 ). Although the overall He was similar between the TR (0.755) and BA (0.733) groups, significant differences in allele composition were observed at some loci. For example, at five loci (GWM099, GWM162, GWM361, GWM415, and GWM429), the He values based on significantly different allele components (according to the {chi}2 test for homogeneity of allele frequencies at each locus, P < 0.00005) were larger in the TR group than in BA group; the differences in He ranged from 0.139 to 0.501. At two other loci (GWM095 and GWM537), allele composition was significantly different (P < 0.00005), and He values were higher in the BA group than in the TR group; the differences ranged from 0.200 to 0.277 (table 3 ).

Genetic Effects on SSR Variation
The ARN scores for genome B were higher than those for genome A over all three populations (table 4 ). Interestingly, the ARNs for each genome were very similar among the three populations; values for genome A were 20.8–23.8, and those for genome B were 28.2–29.6. The NA was higher for genome B than for genome A for all three populations. Analysis of variance (MANOVA) indicated that the effects of genome on SSR variation (ARN, NA, and {sigma}2) differed among the three populations (table 5 ). Genome significantly (P < 0.05–0.00005) affected ARN in the A and T populations and NA in the T and Y populations (table 5 ). Chromosome also affected (P < 0.05–0.00005) ARN, NA, and {sigma}2 of the A population, ARN and NA of the T population, and ARN and {sigma}2 of the Y population (table 5 ). Chromosome 1 (both 1A and 1B) showed the largest ARN and {sigma}2 in all three populations (table 4 ). The genome x chromosome interaction significantly (P < 0.05–0.0005) affected the NA values for all three populations, and ARN and {sigma}2 values for the A and Y populations, respectively. This study included seven types of motifs. Motif types significantly (P < 0.05–0.00005) affected the ARN values of all populations (table 5 ). Compound SSRs, such as (CA)n(TA)k and (CT)n(GT)k, had higher ARN, {sigma}2, and NA values than did simple SSRs ((CA)n, (GA)n, or (CT)n) (table 4 ). The locus effect was significant (P < 0.0005–0.00005) for ARN, NA, and {sigma}2 for all populations (table 5 ). According to table 2 , locus GWM136 showed the largest ARN (48.8–69.9) and {sigma}2 (69.0–233.6) values in the three populations. Locus GWM099 showed the smallest ARN value (8.1–15.6). The lowest {sigma}2 ({sigma}2 = 0) and NA (NA = 1) values were found for the monomorphic GWM601. The largest NA value was found for GWM169 in the A population, for GWM537 in the T population, and for GWM294 in the Y population (table 2 ).


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Table 4 Simple Sequence Repeat (SSR) Diversity in Different Genomes, Chromosomes, and Motifs Across 27 SSR Loci in the Ammiad (A), Tabigha (T), and Yehudiyya Populations of Triticum dicoccoides

 

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Table 5 The F Ratio of MANOVA for Effects of Genetic Factors on Simple Sequence Repeat (SSR) Diversity in Natural Populations of Wild Emmer Wheat Triticum dicoccoides from the Microsites in Ammiad, Tabigha, and Yehudiyya Populations, Israel

 
Effects of Genetic and Environmental Factors on SSR Variation
Multivariate analysis of variance (MANOVA) was performed to measure the effects of interactions among genetic (genome, chromosome, and motif) and environmental (population and soil type) factors on SSR diversity. The results showed that the main effects of genetic and ecological factors, and most of their interactions, were significant (P < 0.05–0.00005) for ARN and NA. Motif seemed to affect the significance of these main effects and their interactions for ARN and NA. When motif effect was ignored, the F ratios became smaller. But if motif effect was taken into account (as a covariate), the F ratios and significance level became larger and higher (table 6 ) for ARN and NA. This result may suggest that motif modifies genetic and ecological effects on ARN and NA.


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Table 6 The F Ratio of MANOVA for Effects of Genetic and Environmental Factors on Simple Sequence Repeat (SSR) Diversities in Wild Emmer Wheat

 
Contribution of Ecological and Genetic Factors to SSR Variation
The relative contributions of ecological (populations and edaphic niches) and genetic factors (genome, chromosome, and motif) to SSR diversity were estimated according to the proportion of sums of squares of ecological and genetic factors to the total sum of squares arising from all the factors (table 7 ). For the diversity of ARN, the relative contribution of genetic factors was high (43.0%), the ecological factors contributed 4.4%, and the interaction of genetic and ecological factors contributed 19.7%. For the diversity of {sigma}2, the interaction of genetic x ecological factors contributed 12.9%, the genetic factors contributed 8.7%, and the ecological factors contributed 2.0%. For the variation of NA, however, the ecological contribution reached 29.1%, the genetic contribution was only 18.0%, and the contribution of the interaction of genetics x ecology was 12.3% (table 7 ). The ecological effect was stronger for NA than for ARN and {sigma}2, but the genetic effect appeared to be stronger for ARN; the interactions of ecological and genetic factors seem to be similar for ARN, {sigma}2, and NA. The total contributions of the ecological and genetic effects investigated were 67.1%, 23.6%, and 59.4% for ARN, {sigma}2, and NA, respectively, suggesting that some other factors may also be responsible for SSR diversity.


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Table 7 Relative Contributions of Genetic (Genome, Chromosome, and Motif) and Ecological (Population and Microniche) Factors to Simple Sequence Repeat (SSR) Diversity According to Percentage of Sums of Squares of Ecological and Genetic Factors to the Total Sums of Squares

 
Determination of Mutational Mechanism and Edaphic Effect on SSR Variation
Multiple-regression analysis was performed to estimate the coefficients of determination of mutational mechanisms (replication slippage and unequal crossing over) and edaphic effect on SSR diversity (table 8 ). ARN and D were used to indirectly estimate the importance of replication slippage and unequal crossing over based on previous results obtained by Levinson and Gutman (1987)Citation , Wolff et al. (1991)Citation , and Innan, Terauchi, and Miyashita (1997)Citation . The products of the factors were used to measure the effects of interactions between them. The results suggest that edaphic factors may affect SSR variation, either directly (selection) or indirectly (e.g., by influencing mutational mechanisms or owing to hitchhiking) (table 8 ). Over all SSRs assayed in this study, replication slippage seems to be the most important mutational mechanism. This mechanism might be affected by edaphic stresses. Both soil x ARN and soil significantly affected NA (R2 = 0.247, P < 0.00005). ARN, soil x ARN, and soil were significantly correlated to {sigma}2 in repeat number (R2 = 0.183, P < 0.00005). The observed coefficients of determination (R2) to SSR diversity across all motifs seem quite low, probably suggesting a motif-specific mechanism.


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Table 8 The Number of Alleles (NA) and Variance in Repeat Number ({sigma}2) in Different Motifs as Dependent on the Mutational Mechanisms and Edaphic Factors

 
Next, multiple regression was conducted for each motif except (AT)n and (CT)n(CA)k due to few observations. Different mechanisms and R2 were observed among the five motifs (table 8 ). The soil x ARN interaction significantly affected the NA values of (GA)n SSRs (R2 = 0.277, P < 0.00005), suggesting that edaphic effect may affect replication slippage by affecting ARN and then modifying NA. For (CA)n SSRs, soil x ARN and D x ARN were significantly (R2 = 0.297, P < 0.01) correlated to NA, indicating effects from the interactions of edaphic factors and mechanisms. The soil x D interaction significantly affected NA values of (CT)n loci (R2 = 0.228, P < 0.01), suggesting that edaphic stresses may affect chromosomal recombination and then change NA. The D x ARN and soil x ARN interactions could significantly affect the {sigma}2 value of (CT)n loci (R2 = 0.358, P < 0.001). For (CA)n(TA)k loci, soil x D and ARN were significantly correlated to the NA (R2 = 0.373, P < 0.001); D x ARN, D, soil x ARN, ARN, and soil could determine 77.2% variation in {sigma}2 of (CA)n(TA)k SSRs (R2 = 0.772, P < 0.00005). In (CT)n(GT)k loci, D x ARN and D significantly affected NA (R2 = 0.507, P < 0.01) and {sigma}2 (R2 = 0.615, P < 0.01). These results may indicate motif specificity of mechanisms generating SSR diversity and mechanisms maintaining population diversity (with habitat-specific and soil-specific selection affecting differential clone selection).


    Discussion
 TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Acknowledgements
 literature cited
 
Edaphic Selection on SSR Diversity
Two soil types were present among the three populations: terra rossa and basalt soils. Significant SSR diversity was found between the two edaphic groups. Particularly, soil-specific and soil-unique alleles were revealed in each soil type. The permutation test suggested that the observed soil-specific or soil-unique alleles were unlikely to occur by chance. The results indicate that natural edaphic selection may cause the divergence at SSR loci in T. dicoccoides between the two edaphic groups dwelling on terra rossa and basalt soils over the entire regional analysis, including A, T, and Y, as well as in the two 100-m transects of T. Our results are consistent with the hypothesis that natural selection may control the level of SSR variation (e.g., Harding, Boyce, and Clegg 1992Citation ; Epplen et al. 1993Citation ; Stephan and Cho 1994Citation ; Garza, Slatkin, and Freimer 1995Citation ; Innan, Terauchi, and Miyashita 1997Citation ).

Natural stresses may accelerate replication error (Jackson, Chen, and Loeb 1998Citation ) and recombinational intermediates (Afzal et al. 1995Citation ) or decrease the ability of DNA mismatch-repair mechanisms (Radman et al. 1995Citation ; Brentnall et al. 1996Citation ; Jackson, Chen, and Loeb 1998Citation ) so as to increase SSR diversity. In our study, we found that the interactions of soil x ARN and soil x D significantly affected SSR diversity. The results may also indicate that edaphic stresses affect replication and recombination of chromosomes of T. dicoccoides, hence SSR diversity. The selective targets may be either SSR loci themselves or selected regions close to the SSR loci.

Innan, Terauchi, and Miyashita (1997)Citation suggested that there was no reason to reject some forms of natural selection, particularly if SSRs are involved in some biological role. In our study, soil-unique SSR diversity and strong motif and locus effects might suggest that the repeated tracts assayed are functionally important. The observed pattern might be an adaptation to environmental edaphic stresses. King and Soller (1999)Citation also suggested that many SSRs were functionally integrated into the genome, so such changes in tract length can exert a quantitative regulatory effect on gene transcription activity, and thereby on adaptive fitness. It was proved that (TC)n, (GA)n, and (TA)n control transcription activity of Ultrabithorax, hsp26, and actin5C genes in Drosophila; the (TG)n repeat modulates the transcription activity of the gene prolactin in rat (reviewed in Kashi, King, and Soller 1997Citation ). In humans, mice, and rats, (GT)n repeats can enhance gene activity not only of the GT repeats closer to promoter sequences, but also of those from distant positions, such as introns and 3'-flanking regions (Stallings et al. 1991Citation ). It was also suggested that SSRs might be involved in chromosome organization of Triticum (Cuadrado and Schwarzacher 1998Citation ). Genes associated with SSRs may be favored by indirect selection whenever quantitative variation in the affected traits can provide a population with genetic resiliency for adaptation, especially in fluctuating or heterogeneous environments (King and Soller 1999Citation ). Another interpretation results from the fact that T. dicoccoides is a highly selfing plant. Correspondingly, differential selection on fitness-related target loci will affect many other sites in the genome, either linked or unlinked to the selected loci (Korol, Preygel, and Preygel 1994Citation ). This may generate multiple niche-specific linkage disequilibria, and it is not an easy task to discriminate such a scenario and direct selection.

Microgeographic genetic divergence, despite gene flow, following ecological heterogeneity has been shown in Avena (Allard et al. 1972Citation ; Hamrick and Allard 1972Citation ) and other plants (reviewed in Brown 1979Citation ), as well as in the Triticum aegilops, H. spontaneum and T. dicoccoides, in the same transects at Tabigha and elsewhere (overviewed in Nevo [1988Citation ] and studied spatiotemporally by Nevo et al. [1991Citation ]). Such genetic divergence can occur over very short distances and also seems to be adaptive at the level of allozyme polymorphism. It suggests the operation of edaphic diversifying selection, in accordance with the ecological niche model of Levene (1953)Citation and the migration-selection model of Karlin (1982)Citation . It remains, however, to identify the specific selective soil components and the precise target of selection. Two experimental strategies can be proposed for that.

First, one can build a mapping population (say, F2) by crossing genotypes from the alternative niches carrying niche-unique SSR alleles and defining the quantitative traits that differ between the soil types. Such a population can be used for quantitative trait loci (QTL) mapping analysis of a multivariate fitness-related trait complex (Korol, Ronin, and Kirzhner 1995Citation ). This will allow testing of the significance of linkage between the formerly detected soil-unique (-specific) SSR(s) and fitness-related traits. But the final proof of the SSR being the target of selection should be based on the following cloning and sequencing of the detected QTL. The second approach uses a very different strategy, but the start is the same. The foregoing F2 population may be subjected to a series of further random intercrosses. This should destroy linkage disequilibria between linked loci. Then, the resulting populations should be subjected for a few generations to the alternative edaphic conditions and then scored for allele frequencies at the SSR. Only loci involved in response to edaphic selection or closely linked markers will show directed changes in allele frequencies. Any resolution can be achieved with a sufficient number of intercrosses. In fact, the two approaches can be combined into one (see Darvasi and Soller 1995Citation ; Xiong and Guo 1997Citation ).

SSR Divergence in Populations
This study demonstrated that SSRs significantly diverged in ARN, {sigma}2, and NA of three populations of T. dicoccoides from Ammiad, Tabigha, and Yehudiyya, located at different altitudes and under different levels of annual rainfall (Nevo, Beiles, and Krugman 1988a, 1988b;Citation Nevo et al. 1991Citation ). The A population showed the largest ARN, {sigma}2, and NA per locus across all SSR loci assayed. Particularly, in the A population, the GWM361 locus was monomorphic, suggesting that some forces either eliminate alleles or limit mutations of this locus. Locus GWM577 could only be amplified for three individuals of the A population, suggesting that some mutations may occur in the flanking regions. However, in the T and Y populations, these two loci were polymorphic. In the Y population, ARN across all the loci was the largest among the three populations. Locus GWM415 was monomorphic only in the Y population. These results may indicate environmental effects at the three sites. The Ammiad site covers four microhabitats across north-facing slope, valley, ridge with various slopes and aspects, and karst with deeply dissected rock relief (Nevo et al. 1991Citation ; Noy-Meir et al. 1991Citation ). The four microhabitats vary in rock relief, soil moisture, nitrogen content, and grazing pressure. The observed distinct results of the A population, in contrast to those of the other two populations, may arise from the more heterogeneous environment. Interestingly, although the three populations are located separately, they were monomorphic at GWM601 with the same repeat number. This may suggest that this (CT)n tract at this locus may be involved in some biological role in maintaining some characteristic of T. dicoccoides.

Genetic Effects on SSR Diversity
This study demonstrated that genetic factors (genome, chromosome, motif, locus, etc.) are strongly correlated with SSR diversity. Different patterns of SSR diversity were observed between compound (and/or imperfect) and simple perfect SSRs. This may be because compound or imperfect SSRs are involved in more complex evolutionary processing than perfect SSRs (Ortí, Pearse, and Avise 1997Citation ). Some evidence suggests that compound or imperfect SSRs may conform more closely to an "infinite alleles" model because of the larger number of potentially achievable allelic states (Goldstein et al. 1995Citation ; Angers and Bernatchez 1997Citation ; Feldman et al. 1997Citation ). In the present study, the observed genome effect on SSR diversity may also be explained by different evolutionary patterns between compound and simple perfect SSRs, since most loci in genome B assayed here are compound SSRs, and most loci assayed in genome A are simple perfect SSRs. Out of 95 and 115 loci mapped on genome A and B by Röder et al. (1998)Citation , 31.6% and 52.2% were compound (including the imperfect) SSRs, respectively. The difference in locus distribution of compound and simple perfect SSRs may arise from different evolutionary sources of genomes A and B in wheat. Genome A was derived from T. monococcum ssp. urartu in east Turkey and Armenia, and genome B was derived from an ancient S genome of a species that was similar to the extant T. speltoides in southern Turkey and the Near East (Friebe and Gill 1996Citation ). C-band polymorphisms and structural rearrangements in wild or cultivated wheat showed greater diversity in the B genome than in the A genome (Friebe and Gill 1996Citation ). One could expect that the repeated DNA regions are also more variable in the B genome than in the A genome, and this is precisely what we found in the present study.

The different levels of SSR variation among the seven groups of chromosomes may reflect heterogeneity of different chromosomes in T. dicoccoides. The pattern may also be explained by functional importance of SSRs in chromosome organization (Caudrado and Schwarzacher 1998Citation ).

In summary, genetic effects appeared to act on SSR variation mainly through SSR motif types, particularly compound and perfect types, potentially due to SSR functional importance and different evolutionary processes of compound and perfect SSRs.

Internal and External Effects on SSR Diversity
The evolution of noncoding tandemly repetitive DNAs was supposed to be driven by slippage during DNA replication (Levinson and Gutman 1987Citation ; Wolff et al. 1991Citation ; Tautz and Schlötterer 1994Citation ) and/or an unequal recombination (Harding, Boyce, and Clegg 1992Citation ). If so, a longer repeat should have more variation, since the chance of replication errors is higher for a longer sequence (Levinson and Gutman 1987Citation ; Wolff et al. 1991Citation ). SSR loci located farther from the centromeres should also have more variation, since recombination is suppressed around the centromeres of chromosomes (Gill et al. 1996Citation ). In other words, ARN and D may affect NA and {sigma}2 at SSR loci. In (CA)n and (GA)n SSRs, edaphic group affected NA by influencing ARN (or replication slippage). In (CT)n and (CA)n(TA)k, edaphic niche affected NA through the interaction with D; i.e., edaphic selection may affect recombination of chromosomes and then affect these SSR diversities. The D x ARN interaction significantly affected NA and {sigma}2 of (CT)n(GT)k and {sigma}2 of (CT)n and (CA)n(TA)k SSRs. This interaction can occur during DNA replication involved in recombination-dependent DNA repair: strand exchange between two homologous chromosomes may create a region of mismatched (heteroduplex) DNA. These regions undergo replication-dependent correction; hence, a slippage mechanism may also work in recombination tracts involving SSR arrays. One may further speculate that the level of slippage errors varies along the chromosome, together with the rate of recombination.

SSR variation is influenced by both genetic factors and ecological forces. We estimated ecological and genetic contributions to SSR variation of T. dicoccoides based on the three populations and two edaphic groups. The results showed different amounts of ecological and genetic contribution for different parameters of SSR variation. The results suggest that both genetic and ecological factors influence SSR variation and that their relative importance varies among different SSR motifs. Notably, the genetic factors may reflect past ecological evolution under differential environmental stresses, as emphasized earlier for genomes A and B. In other words, even the genetic factors may have been deeply affected by ecological origin.


    Conclusions
 TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Acknowledgements
 literature cited
 
Strong SSR diversity was found among the three populations and two edaphic groups of T. dicoccoides across macro- and microgeographic scales. SSR diversity correlated with both ecological and genetic factors. The revealed patterns may indicate that the relative importance of different mutational mechanisms (replication slippage and unequal crossing over) in generating new alleles at SSR loci vary among motifs. Ecological factors may affect the level and the pattern of SSR diversity directly by modulating mutation mechanisms, through natural selection for the maintenance of favorable mutants at SSR loci, or through linkage to other selected loci and linkage disequilibria caused by high selfing rates. At any rate, SSRs may be far from neutral genetic diversity, as indicated by the correlation of SSR variation with ecological factors and the observation of specific and, particularly, unique edaphic alleles. We believe that the idea of ‘junk DNA’ needs to be replaced by the idea of fine-tuned regulation in diverse ecologies. This idea should be critically tested in model organisms facing sharp ecological contrasts at microscales.


    Acknowledgements
 TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Acknowledgements
 literature cited
 
We thank V. Korzun and K. Wendehake for their excellent help. This work was supported by the grants from the Israel Discount Bank Chair of Evolutionary Biology, the Ancell-Teicher Research Foundation for Genetics and Molecular Evolution, and the Graduate School, University of Haifa. We also thank the Israel Science Foundation for providing us with indispensable equipment (grant 9030/96).


    Footnotes
 
Elizabeth Kellogg, Reviewing Editor

1 Abbreviations: LD, linkage disequilibrium; SSR, simple sequence repeat. Back

2 Keywords: microsatellite diversity genetic mechanism ecological effect wild emmer wheat Triticum dicoccoides. Back

3 Address for correspondence and reprints: Eviatar Nevo, Institute of Evolution, University of Haifa, Haifa 31905, Israel. E-mail: nevo{at}research.haifa.ac.il Back


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Accepted for publication January 28, 2000.