Almond [Prunus dulcis (Miller) D.A. Webb, syn. Prunus amygdalus Batsch] occupies a very peculiar place among fruit trees (Miller et al., 1989). Because of almond’s tolerance to cold, drought and salinity, it is considered an important tree crop and is cultivated in different climatic regions of Iran. Breeding practices in Prunus face unique challenges resulting from the narrow genetic background of commercial cultivars (Scorza et al., 1985). Morphological traits such as seed and kernel size, kernel yield, and blooming time are usually used for cultivar identification in almond (De iorgio and Polignano, 1999). However, morphological traits are limited because of their environmental fluctuations.
In recent years, molecular markers have been used to study genetic diversity and cultivar identification of peach and almond (Shiran et al., 2007; Sorkheh et al., 2007; Amirbakhtiar et al., 2006; Kadkhodaei et al., 2006; Sanchez-Pérez et al., 2006; Xie et al., 2006; Testolin et al., 2000, 2004; Aranzana et al., 2003). Methods based on knowledge provided by advances in molecular genetics, notably molecular markers, promise faster and more efficient approaches to cultivar improvement. In fact important tools such as molecular markers, maps, DNA sequences, and quantitative trait loci (QTLs) have been developed and made available to researchers, and applications at the breeding program level have already started (Dirlewanger et al., 2004). Recently, DNA microarray-based genome composition analysis has also been used in comparative genomic studies of trees (Martinez-Gomez et al., 2007). The objectives of the present study are to investigate the genetic diversity of major Iranian almond landraces/cultivars, to identify their relationship to important foreign cultivars, and to introduce informative markers for important nut traits using microsatellite markers.
Materials and Methods
Plant materials: Fifty-one Prunus dulcis landraces/cultivars from different provinces of Iran along with three and two registered cultivars from Spain and USA, respectively, were used in this study (Table 1). The trees with similar ages were sown in a randomized complete block design, with four replications, at the experimental field of the Agricultural Biotechnology Research Institute of Iran (ABRII), Isfahan.
Phenotypic analysis: Fourteen independent morphological traits including leaf shape, leaf length (cm), leaf width (cm), petiole length (cm), flowering duration (day), tree altitude (cm), frostbite kernel yield (g), kernel length (cm), kernel width (cm), kernel thickness (cm), nut weight (g), kernel nut weight (g) and kernel percentage were recorded, based on food and agriculture organization (FAO).
Microsatellite analysis: Total genomic DNA was extracted according to the method described by Doyle and Doyle (1987), with minor modifications. Thirty-five simple sequence repeat (SSR) markers, isolated from peach and almond were used in this study (Testolin et al., 2004; Dirlewanger et al., 2002). Amplification reaction products were separated on a 6% (w/v) denaturing polyacrylamide gel using a Sequi-Gen GT Sequencing Cell 30 cm gel apparatus (BioRad Laboratories Inc., Hercules, CA, USA). The amplified fragments were detected by the silver staining method as described by Bassam et al. (1991). The gels were visually scored by two independent observations.
Data analysis: Each polymorphic fragment was scored as either present (1) or absent (0) across all genotypes. The data were used to calculate the similarity matrix among cultivars employing simple matching coefficients. The similarity matrix was then used to construct dendrograms using the unweighted pair group method with arithmetic averages (UPGMA). This was achieved by employing the sequential, agglomerative, hierarchical, and nested clustering (SAHN) using the numerical taxonomy and multivariate analysis system (NTSYS-PC), version 2.00 (Rohlf, 1998). Observed heterozygosity (Ho) and expected heterozygosity (He) were calculated using the POPGENE version 1.32 (Yeh et al., 1997). The degree of polymorphism was quantified using the polymorphic information content (PIC). Probability of identity (PI) was estimated according to Paetkau et al. (1995). Analysis of molecular variance (AMOVA) was performed using the Arlequin version 2.00 (Schneider et al., 2000) to determine genetic variation (Nei, 1972). Average value of the Shannon index was also measured (Shannon and Weaver, 1949). Informative markers were determined by stepwise regression using the SPSS software version 10.0 for windows (SPSS Inc., Chicago, IL).
Morphological trait analysis: Mean, maximum, minimum and the percentage of coefficient of variation (CV%) of 14 morphological characters are shown in Table 2. A large diversity in the characters was observed, indicating a high level of variation in the studied plant materials.
SSR marker analysis: The results of this study showed cross amplification ability of microsatellite markers among the studied almond genotypes. Out of 35 SSR markers, Out of 35 SSR markers, 25 were polymorphic and produced 215 alleles. The number of alleles per locus ranged from 2 to 16, with an average of 8.76 (Table 3). Average value of the Shannon index was 1.79, which varied from 0.35 in UDP96-008 to 2.6 in CPPCT3. Mean He across microsatellite loci ranged from 0.92 in CPPCT3 to 0.17 in UDP96-008. The highest level of observed heterozygosity was found in XAM18 and CPPCT22 and the lowest in UDP96-008. According to PI, the most informative loci were UDP98-412 and CPPCT3 with values of 0.041 and 0.042, respectively. PIC for these two loci was greater (0.7) than others. The least informative locus was XAM04 with PI of 0.98 and PIC of 0.159, followed by XAM18 with PI and PIC values of 0.494 and 0.0018, respectively. The average of PI and PIC values for all loci were 0.258 and 0.475, respectively (Table 3). Rare polymorphic alleles (i.e. those with a frequency of £ 0.005) and their weights were determined for the purpose of rapid cultivar identification (Table 4). Regression analyses revealed that there was a positive correlation between the CPPCT03 locus and kernel yield (b = 0.424), kernel percentage (b = 0.49), grain weight (b = 0.35), leaf length (b = 0.32) and tree altitude (b = 0.327) (Table 5).
Based on sampling sites, average He was 0.697 and the largest heterozygosity was observed for cultivars from Hamadan (0.731). The results of AMOVA indicated that approximately 4.5% of genetic variance belonged to between collected sites (Table 6). Based on SSR data, the studied almond genotypes were classified into five main groups (Fig. 1). The first cluster included some landraces and cultivars from the Shiraz, Isfahan, Hamadan and Arak provinces. The second cluster included two sub-clusters: the first sub-cluster contained 4 landraces from the Shiraz province and the second sub-cluster contained registered cultivars from Spain, USA and Azerbaijan. Two landraces from Shiraz and Arak provinces were gathered into cluster III. One registered cultivar from USA (HO) and one registered cultivar from Azerbaijan (Harir) were located in two distinct clusters (IV and V).
The results of this study support those of Sosinski et al. (2000), regarding the cross amplification ability of microsatellite markers across the Prunus species. High level of heterozygosity for all loci (0.697) can be attributed to cross pollination and the self-incompatibility nature of almond. The high values of polymorphic loci (71%), average number of alleles per locus (8.76), He (0.775), average polymorphism information content (0.475) and PI (0.258) observed in this study indicate that SSR markers are able to identify genetic variation among the studied almond genotypes. According to PI and PIC values, CPPCT3, UDP98-412, UDP96-409, XAM05, XAM08, XAM09, XAM15 and XAM19 are the best loci for further studies of almond genetic diversity. The percentage of polymorphic SSR loci (71%) in this study was much higher than that estimated for RFLPs (21.9%), suggesting that SSRs can act as better systems for almond cultivar identification (Eldredge et al., 1992).
During this research, alleles were identified that correlated with yield-related traits. The allele belonging to the XAM09 locus had a positive correlation with blooming duration (0.418) (Table 5). In addition, CPPCT17 was found to be an informative marker for nut weight, average kernel thickness and leaf width (Table 5).
In this investigation, cluster analyses showed that most Iranian landraces are well separated from the Spanish and American (USA) cultivars, indicating that they may be native to Iran. However, Shiraz almond landraces are assigned to the same group as the Spanish and American cultivars. A possible explanation is that they might carry a common genetic background. According to the results of this study, SSR data failed to separate genotypes based on their sampling sites. Germplasm migration or insufficient SSR markers can explain this incomplete separation. The results show that Iranian registered cultivars including Yalda, Shokofe and Sahand are similar to the foreign cultivars.
Informative markers are most applicable for breeding purposes. These markers have previously been used in the identification of peach and nectarine varieties (Manubens et al., 1999). A combination of molecular and morphological data is the best choice to find informative markers. In summary, results of the present study reveal that microsatellite markers can be successfully used to assay genetic diversity among Iranian almond landraces/cultivars and to identify informative markers for breeding of important traits.
We would like to thank the Agricultural Biotechnology Research Institute of Iran (ABRII) for funding this study.