Assessment of Genetic Diversity of Chinese Sand Pear Landraces (Pyrus pyrifolia Nakai) Using Simple Sequence Repeat Markers

in HortScience

The sand pear (Pyrus pyrifolia Nakai) is an important fruit crop in China. In this study, simple sequence repeats (SSRs) were used to estimate the level and pattern of genetic diversity among 233 sand pear landraces collected from 10 different geographic regions in China. The results demonstrated that the SSR technique is an effective tool for assessing genetic diversity and the geographic pattern of genetic variation among sand pear landraces of different origins. A total of 184 putative alleles was detected using 14 primer pairs with an average of 13.1 alleles per locus. The mean expected heterozygosity and observed heterozygosity across all loci were 0.705 and 0.671, respectively. High genetic diversity was found in all populations except for that originated from Jiangxi (Ae = 3.149; He = 0.655), whereas at the regional level, those from central China were less diverse than those from other regions. Analysis of molecular variance showed that most genetic differences resided among landraces within populations. Additionally, unweighted pair group with arithmetic average clustering and principal component analysis plotting based on Nei's genetic distance revealed distinct gene pools in agreement with geographic distribution.

Abstract

The sand pear (Pyrus pyrifolia Nakai) is an important fruit crop in China. In this study, simple sequence repeats (SSRs) were used to estimate the level and pattern of genetic diversity among 233 sand pear landraces collected from 10 different geographic regions in China. The results demonstrated that the SSR technique is an effective tool for assessing genetic diversity and the geographic pattern of genetic variation among sand pear landraces of different origins. A total of 184 putative alleles was detected using 14 primer pairs with an average of 13.1 alleles per locus. The mean expected heterozygosity and observed heterozygosity across all loci were 0.705 and 0.671, respectively. High genetic diversity was found in all populations except for that originated from Jiangxi (Ae = 3.149; He = 0.655), whereas at the regional level, those from central China were less diverse than those from other regions. Analysis of molecular variance showed that most genetic differences resided among landraces within populations. Additionally, unweighted pair group with arithmetic average clustering and principal component analysis plotting based on Nei's genetic distance revealed distinct gene pools in agreement with geographic distribution.

The sand pear (Pyrus pyrifolia Nakai) is one of the most important fruit tree crops in China and is extensively cultivated in central and southwest China. The species occurs naturally in southern and western China, recognized as the center of origin of the genus Pyrus (Rubtsov, 1944). There are very many landraces (local cultivars) of P. pyrifolia owing to nearly 3000 years of cultivation and the complex climatic and geographical variation in China. Many landraces have unique traits. For example, ‘Puguali’, from Zhejiang Province, is a large-fruited cultivar with a mean weight of 553 g and a maximum weight of 950 g. The skin is green when mature and covered with brown russet, which turns reddish brown when fruit are fully ripe. ‘Cangxili’, named after its place of origin, Cangxi county in Sichuan Province, is a traditional landrace with maximum fruit weight of 1850 g (average, 321.3 g), smooth skin, and crisp and tender flesh, which is sweet and juicy and of high quality. The rich genetic resources in sand pear provide great potential for cultivar improvement and enhancement of the sustainability of the pear industry. However, many traditional local cultivars have been threatened with extinction by the changes that have occurred in the modern Chinese fruit industry over the past three decades. There has been large-scale cultivation of a few elite cultivars and top-grafting or replacement of old cultivars or landraces. This genetic loss could lead to serious erosion of the gene pool of the cultivated sand pear. To conserve and manage the diversity of sand pear landraces and cultivars, the Wuhan Sand Pear Germplasm Repository (WSPGR) was established in 1986 as the national repository for sand pears, and since then, an exhaustive collection of local cultivars and landraces of Chinese sand pear has been assembled.

Molecular techniques are useful tools for evaluating genetic diversity and for defining genetic relationships in fruit tree crops. In pear, chloroplast polymerase chain reaction–restriction fragment length polymorphisms (RFLPs) were used to examine relationships between east Asian species (Iketani et al., 1998). Dominant nuclear markers, random amplified polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), and intersimple sequence repeat (ISSR) were used in an investigation of genetic relationships among species and for pear cultivar fingerprinting (Cao et al., 2007; Shen et al., 2006; Teng et al., 2001, 2002; Zhang et al., 2007), and nuclear and chloroplast DNA sequences have been used to identify pear cultivars (Kimura et al., 2003; Lee et al., 2004). Of the DNA marker systems currently available, simple sequence repeats (SSRs) have been considered one of the most useful for assessment of genetic diversity and cultivar fingerprinting at the intraspecific level because of their abundance, hyperpolymorphism, and codominant inheritance (Morgante and Olivieri, 1993; Tautz, 1989). However, the published work to date reported the use of a set of SSRs isolated from apple for verifying the transferability of SSRs between apple and pear (Yamamoto et al., 2001) and the cultivar identification by SSRs in a limited number of cultivars developed in Japan (Kimura et al., 2002). SSR markers have been proved as a robust tool for revealing genetic diversity in sand pear (Cao et al., 2007; Kimura et al., 2002, 2003), red-skin sand pear (Zhang et al., 2007), and some other pears in west China (Fan et al., 2007).

Current germplasm evaluation in China mostly focuses on morphological descriptions and documenting pomological traits. The exchange of plants between repositories or commercial orchards raises problems in that some individual sand pear landraces or cultivars may be known by several different names or the one name may be used for different landraces or cultivars. The information from current evaluation of sand pears was not sufficient. Furthermore, detailed morphological descriptions and comparisons of plants are time-consuming and fruit-related traits cannot be observed until plants are mature to produce fruit. Genetic characterization of the gene pool of the cultivated sand pears in the WSPGR collection has not previously been attempted but is urgently needed for formulating management strategies for the WSPGR and for furnishing useful genetic information for future sand pear breeding efforts. This should provide a better understanding of the genetic diversity that exists in the gene pool of the cultivated sand pears and the diverse sources of useful genes in the germplasm repository. Therefore, the objectives of the present investigation were to determine the genetic diversity of the overall gene pool of sand pear landraces and assess the genetic variation among sand pear landrace groups in relation to their geographical distribution in China.

Materials and Methods

A total of 233 landraces originating from 10 provinces (designated as populations in this study) was obtained from the WSPGR (Wuhan, China). Provinces were assigned to four regions (east, south, central, and southwest China). Details are given in Table 1 and Figure 1, and the numbers of landraces for each region and population are shown in Table 2.

Table 1.

Chinese landraces of sand pear evaluated.

Table 1.
Table 2.

Estimates of genetic diversity of sand pear in different provinces and regions.

Table 2.
Fig. 1.
Fig. 1.

Sixty-six geographic origins of 233 sand pear landraces evaluated in this study. 1) Yiwu; 2) Lishui; 3) Yunhe; 4) Leqing; 5) Shouning; 6) Fuan; 7) Pingnan; 8) Pucheng; 9) Jianyang; 10) Jianou; 11) Shunchang; 12) Jinjiang; 13) Jiujiang; 14) Wuyuan; 15); Shangrao; 16) Lianping; 17) Huiyang; 18) Gaoyao; 19) Fengkai; 20) Wuzhou; 21) Guanyang; 22) Gongcheng; 23) Longsheng; 24) Guilin; 25) Lipu; 26) Beiliu; 27) Liucheng; 28) Hengxian; 29) Wuming; 30) Leye; 31) Baise; 32) Tianyang; 33) Debao; 34) Jingxi; 35) Linwu; 36) Yizhang; 37) Longhui; 38) Jingxian; 39) Anjiang; 40) Baojing; 41) Wuhan; 42) Suizhou; 43) Yuanan; 44) Badong; 45) Jianshi; 46) Xuanen; 47) Xianfeng; 48) Lichuan; 49) Meitan; 50) Zunyi; 51) Xingyi; 52) Weining; 53) Tongliang; 54) Cangxi; 55) Jianyan; 56) Jinchuan; 57) Luding; 58) Hanyuan; 59) Huili; 60) Lijing; 61) Dali; 62) Fuyuan; 63) Midu; 64) Kunming; 65) Chuxiong; 66) Chenggong.

Citation: HortScience horts 44, 3; 10.21273/HORTSCI.44.3.619

Total genomic DNA was extracted from 1 to 2 g of fresh leaf tissue using the 2 × CTAB method of Doyle and Doyle (1987) with a slight modification (3 × CTAB). Extracted DNA was quantified in a BioPhotometer spectrophotometer (Eppendorf, Hamburg, Germany).

Sixteen SSR primer pairs developed from sand pear (P. pyrifolia) (Yamamoto et al., 2002b) and two developed from apple (Gianfranceschi et al., 1998) were used for initial assay and of these,14 SSR primer pairs were chosen based on gel clarity and reliability of alleles (Table 3). Polymerase chain reactions were performed in a final volume of 10 μL containing 20 mm (NH4)2SO4, 1.5 mm MgCl2, 0.1‰ Tween 20, 75 mm Tris-HCl (pH 8.8), 0.2 mm dNTPs, 0.2 μM of primer, 20 ng genomic DNA, and 0.5 unit Taq polymerase (Fermentas, Lithuania). The amplification was carried out in a PTC-200 thermal cycler (MJ Research, Watertown, MA) with the following protocol: 5 min at 95 °C followed by 35 cycles of 50 s at 94 °C, 50 s at 55 °C, and 50 s at 72 °C followed by a final 8-min extension at 72 °C. The amplification products with an aliquot 25 bp DNA ladder (Promega, Madison, WI) were electrophoresed in 6% denaturing polyacrylamide gel using a Sequi-Gen® GT/Power Pac 3000 Sequencer System (Bio-Rad, Hercules, CA) for ≈1.5 h at 55 W followed by a modified silver staining procedure (Sanguinetti et al., 1994). The bands of amplified DNA fragments were scored manually.

Table 3.

Simple sequence repeat (SSR) primers and estimates of SSR polymorphism parameters based on 233 Chinese sand pear landraces.

Table 3.

SSR markers were designated by the developer's primer code (referred to as locus) corresponding to the primer pair sequences followed by the product size (bp). Genetic diversity parameters were estimated: number of alleles per locus (A), number of effective alleles per locus (Ae), observed heterozygosity (Ho), expected heterozygosity (He), and Shannon-Weaver's information index (I) using the program GenAlEx (Peakall and Smouse, 2001). The relative magnitude of genetic differentiation between geographic cultivar groups [Wright's F-statistic (FST)] was calculated by different methods implemented in analysis of molecular variance (AMOVA) (Excoffier et al., 1992) and GenAlEx software. The power of discrimination (PD=1 − ∑pi2, where pi is the frequency of the i-th genotype (Kloosterman et al., 1993), was also calculated for each locus. Nei et al.'s (1983) genetic distance (DA) between populations was generated by the program POPULATION Version 1.2.28 (Olivier Langella; available at http://www.pge.cnrs-gif.fr/bioinfo/populations). DA has been considered the appropriate approach for phylogenetic analysis of closely related populations when SSR markers are used (Takezaki and Nei, 1996). The SAHN procedure of NTSYS-pc2.0 software (Rohlf, 1997) was used to construct the unweighted pair group using arithmetic average (UPGMA) dendrogram as described by Sneath and Sokal (1973). A principal coordinate analysis (Gower, 1966) was also conducted using the same software package.

Results

Simple sequence repeat polymorphism and fingerprinting sand pear landraces.

Of the 16 primer pairs prescreened, 14 resolved clear SSR banding patterns, whereas those of NH012a were not adequately clear for allele scoring and CH01E12 failed to amplify in several samples. These two primer pairs were therefore discarded. The 14 loci generated a total of 184 alleles among 233 sand pear landraces, varying from six to 21 alleles per locus with an average of 13.1 alleles per locus (Table 3). The mean value of gene diversity (He) was 0.705, ranging from 0.527 for NH005b to 0.825 for NH014a. The observed heterozygosity (Ho) ranged from 0.451 for NH013a to 0.844 for NH004a with a mean value 0.671. The fixation index (F), which estimates the degree of allelic fixation by comparison of He and Ho, was 0.048, suggesting predominantly outcrossing in sand pears. The mean Wright's FST was 0.129, ranging from 0.097 to 0.156 (Table 3). The mean estimate of power of discrimination (PD) was relatively high with mean value of 0.91 and ranged from 0.77 for NH005b to 0.97 for NH014a. These results indicated that the 14 SSR loci used were efficient in distinguishing the 233 sand pear landraces.

A total of 20 unique alleles (alleles present in only one or two landraces) was found in eight populations, ranging from one allele in two landraces from both Jiangxi and Yunnan Provinces to five alleles in five different landraces from Guizhou Province (Table 4). At the geographical region level, southern and central China each has three unique alleles, whereas five and nine were found in eastern China and southwestern China, respectively. In addition, two unique alleles were detected in ‘Xianfengbaijie’, which came from Hubei Province in central China.

Table 4.

Unique simple sequence repeat alleles in eight pear landrace populations.

Table 4.

Genetic diversity within and among populations.

At the population level, the mean number of alleles per locus (A) ranged from 5.643 in Jiangxi Province to 8.500 in Guangxi and Guizhou, and the mean effective number of alleles per locus (Ae) was also lowest in Jiangxi (3.149) and highest in Guangxi (5.071) (Table 2). The estimates of expected heterozygosity (He) and Shannon-Weaver's information index (I) showed gene diversity to be highest in Guangxi (He = 0.773, I = 1.765) and lowest in Jiangxi (He = 0.655, I = 1.322) (Table 4). At the regional level, landraces in central China were found to be genetically less diverse than those in other regions, whereas the eastern, southern, and southwestern China regions had similar levels of genetic diversity (Table 2).

The estimate of Wright's FST across 10 populations of sand pear landraces was 0.129, suggesting that ≈87% of the total genetic variance resided within populations. Furthermore, AMOVA revealed that 88.60% of the total molecular variation was attributed to differentiation among individuals within populations, and only a small amount of variation was partitioned among regions (3.85%) and among populations (7.55%), yet there was a significant level of differentiation among regions and populations (P < 0.01) (data now shown).

Genetic relatedness of sand pear landraces from different provinces and regions.

Nei et al.'s (1983) genetic distance (DA) for all possible pairwise population comparisons ranged from 0.450 between Guangdong and Guangxi to 0.792 between Guangdong and Jiangxi (Table 5). The UPGMA based on DA values revealed three main clusters, which show clear genetic relationships reflecting their geographic distribution (Fig. 2). Each cluster was further subdivided into two subclusters; Cluster I was made up of three populations from east China, including Jiangxi, Zhejiang, and Fujian Provinces. Three populations from southwest China were grouped into Cluster II, whereas Cluster III has two subclusters consisting of two populations (Guangdong, Guangxi) in south and southwest China and two populations (Hubei, Hunan) in central China.

Table 5.

Genetic distance (DA, Nei et al., 1983) matrix of 10 populations of Pyrus pyrifolia in China.

Table 5.
Fig. 2.
Fig. 2.

Unweighted pair group with arithmetic average dendrograms of 10 populations of sand pear based on Nei et al.'s (1983) genetic distance (DA).

Citation: HortScience horts 44, 3; 10.21273/HORTSCI.44.3.619

The relationships revealed by principal components analysis (PCA) were similar to those revealed by UPGMA. The first three components of the PCA explained more than 55% of the variation found in the DA genetic distance matrix. The bidimensional scatterplot strongly differentiated geographically all of the populations except that from Jiangxi (Fig. 3). The first two components, which accounted for 27.62% and 14.39% of total variation, respectively, divided the 10 populations into three major groups and a single population, Jiangxi.

Fig. 3.
Fig. 3.

Plot of first and second principal components of principal components analysis on 10 populations of sand pear, together accounting for 42.01% of the total variation.

Citation: HortScience horts 44, 3; 10.21273/HORTSCI.44.3.619

Discussion

Effective conservation of plant germplasm requires a thorough understanding of the existing genetic diversity in the species being studied, its genetic structure and geographic distribution and whether it is to be conserved ex situ or in situ (Allard, 1988; Hamrick and Godt, 1997). Molecular markers, for example, AFLP, RAPD, RFLP, ISSR, and SSR, have been used to determine relationships between a limited number of sand pear cultivars (Cao et al., 2007; Kimura et al., 2002; Shen et al., 2006; Teng et al., 2001, 2002; Zhang et al., 2007) but a genetic analysis of the extant gene pool made up from the large number of traditional landraces in China has not previously been attempted. The present study provides most of the information now available on the extent of genetic diversity within sand pear landraces, information that is required for germplasm repository management in China. As was also found by Kimura et al. (2002), SSRs are particularly useful for assessing levels of genetic variation in cultivated sand pears. All except two of the primer pairs tested allowed reliable scoring of alleles across 233 landraces. The 14 primer pairs used all appear to be hypervariable and generated a total of 184 different alleles, which made it possible to discriminate unequivocally all the sand pear genotypes studied. The average estimates of genetic diversity for each locus (A = 13.1, Ho = 0.671, PD = 0.91) found in this study were slightly different from those (A = 14.8, Ho = 0.63, PD = 0.91) derived by Kimura et al. (2002) in their work on Pyrus species. The higher than expected heterozygosity (Ho) observed by us in sand pear landraces indicates that they are genetically more diverse than the 60 pear accessions from six Pyrus species studied by Kimura et al. (2002). However, the slightly lower value of A could be the result of different sets of SSR primer pairs being used in the two studies and/or to unique alleles not present in P. pyrifolia.

The extent and distribution of genetic diversity within a plant species depends on its evolution and breeding systems, ecological and geographical factors, and human activities. Although sand pears were generally believed to lack morphological variation (Yamamoto et al., 2002a, 2002b), the high SSR diversity observed in all populations appears to be related to the evolutionary history of the species. First, sand pears were and still are widely distributed throughout south–central China, including at least 13 provinces. Such a large number of sand pear landraces accumulated during the long history of selection and cultivation should have generated tremendous genetic variation in adaptation to different environments. This high genetic diversity would be maintained despite the intense but narrowly focused selection under the complex ecogeographic factors such as latitude, altitude, temperature, and rainfall. Second, the self-incompatibility mating system of P. pyrifolia could effectively prevent genetic homogenization within each population as evidenced by the highly discriminatory power of the SSR procedure (Table 3). The rich genetic diversity in sand pears provides an opportunity to broaden the genetic base of modern pear cultivars. Although the Guangxi, Guizhou, Sichuan, and Yunnan populations were slightly more diverse genetically than the other populations, when all estimates of genetic diversity were considered, the difference was not significant except for the Jiangxi population being the least diverse (Table 2). The provincial populations with the highest mean number (8.500) of alleles per locus were those in Guizhou and Guangxi. The regional population with the most alleles per locus (11.428) was from southwestern China; this regional population also showed the highest values for Ae and I (Table 2), suggesting that the Guizhou population should perhaps be a priority for conservation.

It is likely that the genetic diversity of the sand pear gene pool may have been underestimated because that the landraces used in this analysis were only some representatives from different parts of the geographic distribution (Table 1). For example, the 11 landraces in Jiangxi were collected from only three districts with six of them collected from Wuyuan and four and one from Shangrao and Jiujiang, respectively; 87.5% of the landraces (28 of 32 accessions) in Guizhou were derived from a single county, Weining, an area with a long history of pear cultivation (Fig. 1). Therefore, we can reasonably conclude that there are extensive sand pear resources yet to be collected and assessed. Further work should be focused on those districts that have not so far been studied considering the significant genetic differentiation among and between regions. A total of 20 unique alleles was found in 23 landraces belonging to eight different populations. These local alleles could be associated with certain adaptive characteristics, which would be of interest to plant breeders for cultivar improvement and should be given priority for conservation.

At the regional level, southwestern China contains the most diverse sand pear germplasm with slightly lower genetic diversity in central China (Table 2). Our results provide further support for the hypothesis that P. pyryfolia originated from southwest China, including Guizhou, Sichuan, and Yunnan Provinces (Rubtsov, 1944). It is interesting to note that the sand pear populations in eastern China (Fujian, Jiangxi, and Zhejiang) are more diverse than those in central China (Hubei and Hunan). This might be the result of ancient gene flow through cultivar exchanges by local pear growers in different regions of China. Historically, pear production in eastern China was closely associated with Japan and Korea, where sand pears are also distributed, and probably provided additional opportunities for genetic exchanges with foreign cultivars developed in Japan. RAPD analysis of Pyrus species and cultivars revealed close genetic relationships between cultivars from Fujian, Zhejiang, and Japan, indicating ancient gene flow among those regions (Teng et al., 2002).

Analysis of molecular variance showed that most genetic diversity of landraces was within populations with smaller, although still significant, amounts of genetic variation between regions and populations. The estimate of Wright's FST (0.129) was also higher for sand pears than for wild populations of plant species with similar life histories (FST = 0.084, Hamrick et al., 1992). This fact reflects the outstanding characteristic of landraces; they are the result of selection through climatic and edaphic adaptation and human activities (Harlan, 1975a, 1975b). Indeed, local crop races are the consequences of long periods of interaction between the environment and genetic systems (Brush, 1995). During the long history of cultivation, farmers have made direct selection for desirable genotypes under the specific agricultural regimes resulting in accumulated genetic differentiation among populations.

The UPGMA dendrograms show that the 10 populations formed region-specific clusters (Fig. 2). Three populations in east China grouped into a distinct subcluster, suggesting profound genetic divergence from other populations, which might be the result of the P. pyrifolia distribution. In addition, landraces in this region maybe have an ancient gene introgression with genotypes from Japan and/or Korea, which further increased differentiation with landraces of inland China. Similar region-specific clusters were also evident in the PCA plots, except that the Jiangxi population cannot be grouped with the Fujian and Zhejiang populations (Fig. 3). Furthermore, the Fujian population was, surprisingly, more similar to the Guizhou and Yunnan populations than to its two bordering populations in Jiangxi and Guangdong as shown by the genetic distance matrix (Table 5) and PCA plots (Fig. 3). One possible explanation is that the landraces collected from those populations were from the same latitude and similar climate conditions may force landraces into similar ecotypes. Populations from Hubei and Hunan, Guangdong and Guangxi, and Guizhou, Yunnan, and Sichuan generated similar clusters in the UPGMA dendrograms and PCA plots, which reflected their geographic relationships. The three distinct clusters of the 233 landraces suggest that east China, south China, and southwest China have different germplasm pools and should each be conserved.

In summary, the present study has demonstrated that SSR markers provide an effective tool for assessing genetic diversity and relationships within sand pear germplasm. Further work should focus on combining molecular data and pomological traits for delineating a core collection of sand pear and developing effective conservation strategies and breeding programs.

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Contributor Notes

This research was supported by the CAS project KSCX2-YW-N-061 and NSFC grant 30070082.

To whom reprint requests should be addressed; e-mail huanghw@mail.scbg.ac.cn.

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    Sixty-six geographic origins of 233 sand pear landraces evaluated in this study. 1) Yiwu; 2) Lishui; 3) Yunhe; 4) Leqing; 5) Shouning; 6) Fuan; 7) Pingnan; 8) Pucheng; 9) Jianyang; 10) Jianou; 11) Shunchang; 12) Jinjiang; 13) Jiujiang; 14) Wuyuan; 15); Shangrao; 16) Lianping; 17) Huiyang; 18) Gaoyao; 19) Fengkai; 20) Wuzhou; 21) Guanyang; 22) Gongcheng; 23) Longsheng; 24) Guilin; 25) Lipu; 26) Beiliu; 27) Liucheng; 28) Hengxian; 29) Wuming; 30) Leye; 31) Baise; 32) Tianyang; 33) Debao; 34) Jingxi; 35) Linwu; 36) Yizhang; 37) Longhui; 38) Jingxian; 39) Anjiang; 40) Baojing; 41) Wuhan; 42) Suizhou; 43) Yuanan; 44) Badong; 45) Jianshi; 46) Xuanen; 47) Xianfeng; 48) Lichuan; 49) Meitan; 50) Zunyi; 51) Xingyi; 52) Weining; 53) Tongliang; 54) Cangxi; 55) Jianyan; 56) Jinchuan; 57) Luding; 58) Hanyuan; 59) Huili; 60) Lijing; 61) Dali; 62) Fuyuan; 63) Midu; 64) Kunming; 65) Chuxiong; 66) Chenggong.

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    Unweighted pair group with arithmetic average dendrograms of 10 populations of sand pear based on Nei et al.'s (1983) genetic distance (DA).

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    Plot of first and second principal components of principal components analysis on 10 populations of sand pear, together accounting for 42.01% of the total variation.

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