Genetic effects on microsatellite diversity in wild emmer wheat - Nature

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Genetic effects on microsatellite diversity in wild emmer wheat (Triticum dicoccoides) at the Yehudiyya microsite, Israel Y-C Li1,3, T Fahima1, MS Ro¨der2, VM Kirzhner1, A Beiles1, AB Korol1 and E Nevo1 1 Institute of Evolution, University of Haifa, Mount Carmel, Haifa 31905, Israel; 2Institute for Plant Genetics and Crop Plant Research, Corrensstrasse 3, 06466 Gatersleben, Germany

This study investigated allele size constraints and clustering, and genetic effects on microsatellite (simple sequence repeat, SSR) diversity at 28 loci comprising seven types of tandem repeated dinucleotide motifs in a natural population of wild emmer wheat, Triticum dicoccoides, from a shade vs sun microsite in Yehudiyya, northeast of the Sea of Galilee, Israel. It was found that allele distribution at SSR loci is clustered and constrained with lower or higher boundary. This may imply that SSR have functional significance and natural constraints. Genetic factors, involving genome, chromosome, motif, and locus significantly affected SSR

diversity. Genome B appeared to have a larger average repeat number (ARN), but lower variance in repeat number (s2ARN), and smaller number of alleles per locus than genome A. SSRs with compound motifs showed larger ARN than those with perfect motifs. The effects of replication slippage and recombinational effects (eg, unequal crossing over) on SSR diversity varied with SSR motifs. Ecological stresses (sun vs shade) may affect mutational mechanisms, influencing the level of SSR diversity by both processes. Heredity (2003) 90, 150–156. doi:10.1038/sj.hdy.6800190

Keywords: SSR variation; allelic cluster; genome effect; mutational mechanism; Triticum dicoccoides; wheat’s progenitor

Introduction Microsatellites, or simple sequence repeats (SSR), are ubiquitously interspersed in eukaryotic genomes (Tautz and Renz, 1984; Kashi et al, 1997; Kashi and Soller, 1999; Li et al, 2002a). SSRs are among the fastest-evolving DNA sequences with high mutation rates, 102–103 per locus per gamete per generation (Weber and Wong, 1993), which leads to their high polymorphism in terms of repeat number. It has been suggested that replication slippage, sister-chromatid exchanges, unequal crossing over, and gene conversion may cause SSR diversity (Tautz and Renz, 1984). Among these mutational mechanisms, replication slippage seems to play a major role in producing new alleles at SSR loci (Levinson and Gutman, 1987; Wolff et al, 1991; Innan et al, 1997; Stephan and Kim, 1998). However, these suggestions need more critical analysis across species and populations. The distribution of allele sizes in SSR loci, seems to be nonrandom. For instance, alleles with long repeats were found to be more mutable than a bulk of the Ccon70 with short repeats (Crozier et al, 1999). Likewise, bimodal distribution of allele size was revealed at many SSR loci in some species including human (Rubinsztein et al, 1995), Mimulus guttatus (Awadalla and Ritland, 1997), Arabidopsis (Innan et al, 1997), and the fish Sparus aurata (Dermitzakis et al, 1998). The excessive similarity (more Correspondence: E Nevo, Institute of Evolution, University of Haifa, Mt Carmel, Haifa 31905, Israel. E-mail: [email protected] 3 Current address: Department of Plant Sciences, The University of Arizona, Tucson, AZ 857-19, USA.

than expected by chance) in allele size distributions among various allele series of the same locus suggests the existence of evolutionary constraints on that locus (Lehmann et al, 1996). Two alternative forces for such nonrandom distribution of allele-size frequency have been proposed: biased mutation and/or selection acting on allele size (Garza et al, 1995; Dermitzakis et al, 1998). The present study demonstrated constraints and clustering of allele size distribution in a natural population of wild emmer wheat, Triticum dicoccoides, and correlation between SSR diversity and repeat length, locus chromosomal location, and genetic effects on dinucleotide SSR diversity in a natural population of wild emmer wheat from two neighboring (a few meters apart) and contrasting microclimatic niches, sun, and shade. The microclimatic effect on SSR divergence and diversity are described in a complementary paper (Li et al, 2002b).

Materials and methods Wild emmer wheat, Triticum dicoccoides (Nevo et al, 2002) is the tetraploid and predominantly self-pollinated progenitor of cultivated wheat (Zohary, 1970). This tetraploid species contains two genomes and 28 chromosomes (2n ¼ 4x ¼ 28, genome AABB). The plant materials used in this analysis are described in detail in Li et al (2002b). A total of 28 dinucleotide SSR DNA markers (one for each chromosomal arm) were chosen for the analysis. The SSR primers used in this study were described by

Genetic effects on SSR diversity in wild emmer Y-C Li et al

151 Table 1 SSR motif and chromosomal locations Marker

GWM18 GWM60 GWM95 GWM99 GWM120 GWM124 GWM136 GWM162 GWM169 GWM186 GWM218 GWM219 GWM251 GWM294 GWM332 GWM340 GWM361 GWM368 GWM389 GWM408 GWM415 GWM429 GWM459 GWM537 GWM540 GWM577 GWM601 GWM637

Motif

(CA)nGA(TA)ck (CA)n (AC)n (AC)n (CT)n(CA)k (CT)n(GT)k (CT)n (CA)nAA(CA)k (GA)n (GA)n (CT)n (GA)n (CA)n (GA)nTA(GA)k (GA)n (GA)n (GA)n (AT)n (CT)n(GT)k (CA)n(TA)(CA)k(TA)m (GA)n (CT)n (GA)n (CA)n(TA)k (CT)n(CC)(CT)k (CA)n(TA)k (CT)n (CA)n

Chromosomal Locationa

Distanceb

1BS 7AS 2AS 1AL 2BL 1BL 1AS 3AL 6AL 5AL 3AS 6BL 4BL 2AL 7AL 3BL 6BS 4BS 3BS 5BL 5AS 2BS 6AS 7BS 5BS 7BL 4AS 4AL

5.7 52.3 10.8 95.3 23.7 82.2 38.8 91.0 49.6 38.4 30.4 40.5 28.9 16.1 53.0 131.4 11.4 8.7 118.4 73.8 25.4 29.0 62.5 43.6 9.3 105.0 8.1 40.1

a A, B: genome A and B; S, L: short and long arm. bDistance from the centromere (D, in cM), which was estimated according to the map of Ro¨der et al (1998), the distance of GWM 218 also referred to the map of Peng et al (2000). cm, n, and k symbolize repeat number.

Plaschke et al (1995) and Ro¨der et al (1995, 1998). Table 1 presents the repetitive motif, locus location, and distance from the centromere (D) in bread wheat, T. aestivum. The procedure used to detect SSR polymorphism followed Plaschke et al (1995) and Fahima et al (1998). Fragment sizes were calculated using the Fragment Manager (Pharmacia) computer program by comparing with internal size standards, which were added to each lane in the loading buffer. Analysis of variance (ANOVA) was used to analyze genetic effects on SSR diversity. Multiple regression was used to measure indirectly contributions of mutational mechanisms to SSR diversity in different repeat motifs. The statistical analyses were performed using the STATISTICA program (Statsoft, 1996).

Results SSR allele distribution with size clusters and constraints The distribution of alleles at locus GWM99 showed two clusters, one with small repeat numbers (7,8), the other with larger repeat numbers (21–24), with a considerable gap of 12 repeats of (AC) between them (Figure 1). Similar patterns were observed at loci GWM60, GWM537, and GWM577 (Figure 1). The allele-size distribution seems to have a low boundary at locus GWM577 and upper limits at locus GWM537 (Figure 1). At loci GWM415 and GWM601, alleles were limited to repeat numbers 19 and 17, respectively. Allele sizes at GWM95, GWM120, and GWM332a varied in the ranges of 15–20, 31–36, and 17–18 repeats, respectively. These results suggest that some constraints may exist on repeat number at SSR loci. The last assumption is especially supported by allele distribution at GWM537 (Figure 1).

Figure 1 Allele distributions with clusters and constraint at loci GWM60, GWM99, GWM537, and GWM577. Heredity


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Genetic effect on SSR variation Analysis of variance (ANOVA) was used to test the effects of genetic factors (genome, chromosome, and motif) (Table 2). The results suggested that genome (A vs B) significantly (Po0.05) affected the average repeat number (ARN), with genome B showing larger ARN (30.2) than genome A (25.1). Genome A showed larger variance in repeat number (s2 ¼ 27.8) than genome B (s2 ¼ 19.0). The SSR ARN on chromosome 1 (including both 1A and 1B) were significantly (F(6,40) ¼ 3.85, Po0.01) larger (ARN ¼ 42.5) than those of other chromosomes (ranged from 22 to 31). Microsatellites on chromosome 7 showed the highest variance (s2 ¼ 53.5) in repeat number (F(6,40) ¼ 2.72, Po0.05) compared with those on other chromosomes. Compound SSRs, such as (CA)n(TA)k, (CT)n(GT)k, and (CT)n(CA)k, appeared to have significantly (F(6,47) ¼ 2.88, Po0.01) larger ARN (433) than simple or perfect SSRs, such as (GA)n and (AT)n. (ARN ¼ 24–29). The SSRs with (CA)n showed the smallest ARN ( ¼ 20, Li et al, 2002b). Locus effect was highly significant (Po0.00005, Table 2) for number of alleles (NA), ARN, and s2. Locus GWM294 showed the largest NA (13), whereas each of GWM415 and GWM601 displayed only one allele. Locus GWM136 appeared to have the largest ARN (70.0) and GWM99 the smallest ARN (10.0). Loci GWM332a and GWM332b showed the smallest (0.27–0.55) and largest (97.6–127.0) s2, respectively (Li et al, 2002b).

then microsatellite loci, located farther from the centromeres should have larger diversity, because recombination is suppressed around the centromeres (Gill et al, 1996). In other words, the ARN and locus distance from the centromere (D) may affect the genetic diversity at SSR loci, allele number (NA) and variance in repeat number (s2), serving as indirect evidence in favor of one of the explanatory models. Forward stepwise regression was used to estimate contributions of ARN, D, and microniches to the A and s2 of different motifs (Table 3). The results indicated that ARN were the most important factor for (GA)n loci. Mutational mechanisms (represented indirectly by ARN, D, and D ARN) could significantly affect s2 at (GA)n loci (R2 ¼ 0.827, Po0.00005). Niche could also alone (r ¼ 0.466, Po0.05) or through interaction niche ARN (r ¼ 0.538, Po0.05) affect the s2 of (GA)n loci. Both the mutational mechanisms and ecological effects could significantly determine the s2 of (GA)n loci (R2 ¼ 0.889, Po0.00005). In (CA)n SSRs, D ARN and microniche were highly responsible

Mutational mechanism for producing SSR variation Replication slippage (Levinson and Gutman, 1987; Wolff et al, 1991; Innan et al, 1997) and unequal crossing over (Harding et al, 1992) were regarded as mechanisms for generating new alleles or diversity at SSR loci. With replication slippage, a longer repeat would tend to have larger diversity, since the chance of replication errors is higher for a longer sequence (Levinson and Gutman, 1987; Wolff et al, 1991). If recombination is important,

Genome Chromosome Genome chromosome Motif Locus

Table 2 Analysis of variance for genetic effects on microsatellite variation (number of alleles per locus, NA; average repeat number, ARN; and variance in repeat number of microsatellites) F ratio

Genetic factora (df1, df2)

NA

ARN

Variance 0.474 2.716* 3.059*

1, 40 6, 40 6, 40

3.865c 1.886 5.896***

4.987*b 3.848** 0.470

6, 47 26, 27

1.473 37.717****

2.877** 114.132****

1.059 7.957****

Interaction of some genetic factors could not be estimated because of incomplete design. bSignificance: *, **, ***, ****Po0.05, 0.01, 0.0005, 0.00005. cPo0.10. a

Table 3 Multiple regression of the genetic factors, microniche and their interactions as independent variables with number of alleles per locus (NA) and variance (s2) in repeat number in the Yehudiyya population of T. dicoccoides as dependent variables Motif

No. cases

Step

NA

Enter variablea rb

Step

Enter variable

R2,c

s2 in repeat number rb

R2

(GA)n

22

1

ARN

0.427*

0.182*

1 2 3 4 5

ARN D ARN D Niche ARN Niche

0.862**** 0.738*** 0.696** 0.538* 0.466*

0.602**** 0.723**** 0.827**** 0.858**** 0.889****

(CA)n

10

1 2

D ARN Niche

0.856** 0.628*

0.621** 0.770**

1

—d

—

—

(CT)n

10

1

—

—

—

1 2 3 4

D ARN ARN D Niche ARN

0.989**** 0.996**** 0.994**** 0.969****

0.987**** 0.989**** 0.997**** 0.999****

(CA)n(TA)k

8

1 2

D ARN Niche ARN

0.975*** 0.651*

0.924*** 0.950***

1

D ARN

0.838*

0.703*

a ARN: average repeat number; D: locus distance from the centromere (cM), : interaction. br: partial correlation coefficient at the last step with significance of t-test. cR2: coefficient of multiple determination with significance of F test for multiple correlation. *, **, ***, **** Po0.05, 0.01, 0.0005, 0.00005. d—: no significant factors entered the multiple regression.

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for the NA (R2 ¼ 0.770, Po0.01). At (CT)n SSRs, significant effects on s2 in repeat number were displayed by mutational mechanisms (ARN, D and D ARN; R2 ¼ 0.997, Po0.00005) and the interaction niche ARN (r ¼ 0.969, Po0.0005). In (CA)n(TA)k SSRs, ARN D and niche ARN affected NA (R2 ¼ 0.950, Po0.0005), whereas the ARN D interaction was significant for s2 (R2 ¼ 0.703, Po0.05). These results implied the importance of mutational mechanisms and other factors for producing and maintaining population variation. These factors may vary among different motifs of SSRs. The results also suggest that in addition to internal mechanisms, external microniche factors may directly or indirectly affect SSR diversity.

Discussion Constraints on allele sizes Our results demonstrated significant skewness to the right of allele distributions at a variety of loci, combined with a clear boundary and/or a large gap on the distribution, suggesting that constraints may exist on repeat number at SSR loci, as shown by previous studies (Deka et al, 1994; Garza et al, 1995; Dermitzakis et al, 1998; Pollock et al, 1998). Two possible mechanisms for constraining allele sizes are biased mutation and selection on the SSR loci themselves (Garza et al, 1995; Zhivotovsky et al, 1997; Dermitzakis et al, 1998). According to our results, it seems that natural constraints may act on both short and long arrays in wild populations of T. dicoccoides. If so, the short and long repeats may have functional meaning, and natural selection may prevent them from overstepping certain minimum or maximum thresholds. This pattern was displayed by the distributions of repeat numbers at GWM60, GWM99, GWM537, and GWM577 with motifs (CA)n and (CA)n(TA)k. The two microclimatic niches were significant factors for the number of alleles at (CA)n and (CA)n(TA)k SSRs suggesting that these repeats may have some functional regulatory meaning (Li et al, 2002b). King and Soller (1999) also suggested that many SSRs are functionally integrated into the genome, so that such changes in tract length can exert a quantitative regulatory effect on gene transcription activity. It has been shown that (TC)n, (GA)n, and (TA)n control transcription activity of Ultrabithorax, hsp26, and actin5C genes in Drosophila. Similarly, a (TG)n repeat modulates the transcription activity of a prolactin gene of rat (reviewed in Kashi et al, 1997; Kashi and Soller, 1999; Trifonov, 2003). In human, mouse, and rat (GT)n repeats could enhance gene activity not only from sites residing close to promoter sequences, but also from distant positions, such as introns or 30 -flanking regions (Stallings et al, 1991). For SSR arrays that might indeed be involved in gene regulation, therefore, one could expect that selection constrains the reduction and/or expansion in repeat number in certain positions inside some minimum thresholds, as suggested by GWM577 (Figure 1). For the SSR repeats involved in chromosome organization (Cuadrado and Schwarzacher, 1998), and dinucleotide repeats correlated with regional variation in the rate of recombination (Schug et al, 1998), one could assume that selection limits the increase in the repeat number under some maximum thresholds that may be motif-specific. If

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so, a negatively skewed allele frequency distributions toward long SSRs with a relatively sharp cutoff length, are expected (Amos, 1999). The allele distribution at GWM537 (Figure 1) fits these expectations. In the evolutionary model of simple tandem repetitive DNA proposed by Stephan and Cho (1994), natural selection is expected to play an essential role in controlling the length of a nucleotide string in minisatellite and SSR DNA. Natural stresses may accelerate replication errors (Jackson et al, 1998) and recombination intermediates (Korol et al, 1994; Afzal et al, 1995), or decrease the ability of DNA mismatch-repair mechanisms (Radman et al, 1995; Brentnall et al, 1996; Jackson et al, 1998) so as to increase SSR diversity. Natural stress could also select the favorable alleles or eliminate deleterious mutants, thereby changing the level and pattern of SSR diversity (Hartl and Clark, 1997). A biased mutation process could also regulate repeat number. However, the only bias in mutation observed has been predominance of upward mutations. Garza et al (1995) modeled a symmetric process in which the same type of bias affects large and small alleles. Stephan and Cho (1994) suggested that replication slippage work on SSRs but unequal crossing over cannot act on very short tandem arrays like SSRs. Our study suggested that the mechanisms for generating new alleles may differ in different motif types. Replication slippage seems to be the most important mechanism for (GA)n SSRs, and the interaction of replication slippage and unequal crossing over appears to be an important factor for diversity of (CA)n, (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, 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 (Li et al, 2002a). Notably, in a selfer, recombination is largely ineffective in creating new haplotypes, that is, the effective rate of recombination between polymorphic loci is much lower than the absolute rate (Narain, 1966). However, in the case of unequal crossing over even between equivalent chromosomes, repeat number will be changed. Clusters of SSR alleles In our study, we found clusters of alleles with some gaps X nine repeats at the GWM60, 99, 537, and 577 loci. This phenomenon may have implications for the evolution of SSRs with respect to mutational models and homoplasy among alleles. SSR mutation rate is positively correlated to repeat length (Wierdl et al, 1997; Primmer et al, 1998); it is also allele-specific (Schlo¨tterer et al, 1998). It has been shown that for a given locus, propensity to generate mutations could be different among alleles (Wierdl et al, 1997). For example, the types of alterations observed in long and short (GT)n tracts in wild-type strains with mismatch repair system were different in two ways. First, tracts with nX51 bp (including flanking region) had significantly larger deletions of length change than those with np33 bp. Second, for the 99- and 105-bp tracts, almost all events involving single repeats were Heredity


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additions; for the smaller tracts, both additions and deletions of single repeats were common (Wierdl et al, 1997). Such a size-dependent mutation seems to be able to form bimodal allele distribution. Based on the assumption that replication slippage is the main mechanism, and on empirical data that mutations in SSR repeats are biased with a tendency to make the array grow larger (Weber and Wong, 1993; Amos et al, 1996), Dermitzakis et al (1998) also proposed a possible process of how this clustering was generated in SSRs. In this model, at two linked loci, allele sizeconstraints (natural selection or mutation bias) eliminate repeat number randomly from short or long arrays with equal possibilities. In such a case, long arrays lose repeats with the same rate as short ones, but gains repeats faster than the short arrays. If this mechanism is allowed to act for long, it may generate two clusters of about the same size, but at the two extremes. Genetic factors affecting SSR variation In our study of T. dicoccoides, the significant effects of genome, chromosome, and motif on SSR diversity were found. In many cases, compound motifs tended to have larger repeat number than simple (or perfect) motifs. This is explicable by assuming that a compound motif, for example, (CT)n(GT)k, may have more chances to gain a new repeat unit of either (CT)n or (GT)k than a simple motif, such as (CT)n. Compound or imperfect SSRs seem to manifest more complex evolutionary patterns than do perfect SSRs (Ortı´ et al, 1997). Some previous studies suggested that imperfection in repeated regions might cause a decrease in the mutation rate of SSR loci (Garza et al, 1995). We also found that some imperfect SSR loci, such as GWM361 and GWM415, showed a low level of diversity. Imperfection in repeated regions possibly constrains the mutation process and stabilizes some SSRs. Some evidence suggested that compound SSRs may conform more closely to the ‘infinite alleles’ model (Estoup et al, 1995) because of the larger number of potentially achievable allelic states (Goldstein et al, 1995; Angers and Bernatchez, 1997). The genome effect on SSR diversity in this study could be explained by different evolutionary patterns between compound and perfect SSRs, since most loci in genome B assayed here are compound SSRs, whereas most of the loci in genome A are perfect SSRs. The difference in locus distribution of compound or simple SSRs may arise from different evolutionary origins of genomes A and B in wheat. The A genome was derived from T. urartu, and the B genome from an ancient S genome species that was similar to the present T. speltoides (Friebe and Gill, 1996). The A genome as a whole appears to have experienced a faster rate of evolution than the B and D genomes (Sallares and Brown, 1999). Hence, one may expect that SSRs in genome A also evolve faster than in genome B. This expectation seems to be supported by the higher variance in repeat number of SSRs in genome A than in genome B, and by a higher proportion of perfect (and less stable) SSRs in genome A than in B. Out of 95 and 115 SSR loci mapped on genomes A and B, 31.6 and 52.2%, respectively, are compound or imperfect (Ro¨der et al, 1998). Selective sweeps and background selection Low recombination rate, like in selfing species as wild emmer wheat or around centromeres of chromosomes Heredity

(Gill et al, 1996), may increase the effects of selective sweep (see Hedrick, 1980) and background selection (Liu et al, 1999). Therefore, distance of microsatellite loci from the centromeres (D) may affect the level of SSR variance in repeat size. In this study, we observed significant correlation between the D and variance in repeat size for dinucleotide SSRs in three populations of wild emmer wheat at Yehudiyya (Spearman’s rank order correlation rs ¼ 0.393, n ¼ 54, Po0.005). The simplest interpretation of such correlation between recombination and D is an effect of background selection or selective sweeps. Similarly, both background selection and selective sweeps may contribute to the correlation between DNA sequence variation at 18 dinucleotide microsatellites and recombination in Drosophila (Schug et al, 1998). The relative contribution of background selection versus selective sweeps to the correlation depends on the mutation rate of SSRs. However, it is not easy to distinguish between these two explanations of background selection and selective sweeps (reviewed in Li et al, 2002a).

Conclusion In conclusion, our study demonstrated allele size cluster and constraint at some SSR loci, and significant effects of genome, chromosome, SSR motif and locus for SSR diversity in the Yehudiyya microsite population of wild emmer wheat. Genome B and those SSRs with compound motifs showed longer repeats. This may result from specific evolutionary origin or evolutionary feature. The revealed patterns by multiple regression may reflect the fact that the relative importance of different mutational mechanisms (replication slippage and unequal crossing over) in generating new alleles at SSR loci varies between motifs. Background selection and selective sweeps may also influence SSR variation, since wild emmer wheat is a selfer and some of the GWM loci studied are located not far away from the centromere. Microniche conditions may affect the level and the pattern of SSR diversity directly, through microclimatic selection posing some ‘constraints’ on the repeat numbers at different loci, and by modulating the mutation/recombination mechanisms (Li et al, 2002a, b).

Acknowledgements The authors thank Dr V Korzun and Ms K Wendehake for their excellent help, and the Graduate School, University of Haifa for financial support to this study whose microsatellite work was conducted in Germany at the laboratory of the Institute for Plant Genetics and Crop Plant Research. This research is part of the PhD research project of the first author. The research was financially supported by an equipment grant of The Israel Science Foundation (No. 9048/99); and by the German–Israeli Cooperation Project (DIP project funded by the BMBF and supported by BMBF’s International Bureau at the DLR). This work was also supported by the Israeli Discount Bank Chair of Evolutionary Biology and the Ancell–Teicher Research Foundation for Genetics and Molecular Evolution.


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