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GENETIC VARIABILITY OF INTRODUCED AND LOCAL
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SPANISH PEACH CULTIVARS DETERMINED BY SSR
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MARKERS
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MARIEM BOUHADIDA1, 2, MARÍA ÁNGELES MORENO1, MARÍA JOSÉ
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GONZALO1, JOSÉ MANUEL ALONSO3 and YOLANDA GOGORCENA1
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50080 Zaragoza, Spain. 2 Current address: Field Crops Laboratory, INRAT, Rue Hedi
Dpto. Pomología, Estación Experimental de Aula Dei, CSIC, Apartado 13034, E-
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Karray, 2080 Ariana, Tunisia. 3Unidad de Fruticultura, Centro de Investigación y
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Tecnología Agroalimentaria de Aragón. Avda. Montañana 930, 50059 Zaragoza,
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Spain.
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Corresponding author:
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Yolanda Gogorcena
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Tel: +34976716133
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Fax: +34976716145
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e-mail: [email protected]
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Proofs should be sent to:
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Yolanda Gogorcena
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Departamento de Pomología, Estación Experimental de Aula Dei, CSIC, Apartado
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13034, E-50080 Zaragoza, Spain
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ABSTRACT
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A set of 94 peach cultivars including Spanish native peach and foreign commercial
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cultivars were analyzed using 15 SSR markers, selected for their high level of
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polymorphism. The number of alleles obtained varied from two to eleven with an
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average of 6.73 giving 185 different genotypes. All the cultivars showed a unique
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genetic profile, each one using different genotypic combination of all loci. BPPCT001
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was the most informative locus showing also the highest discrimination power. Only
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six loci allowed the unambiguous separation of all the Spanish native cultivars
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studied, and the genotypic combination of only eight loci permitted the total
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differentiation of the 94 peach cultivars analyzed. The six selected loci (BPPCT001,
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BPPCT006, BPPCT008, PS9f8, UDP98-022, and UDP98-412) seem to be very useful
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for future Spanish peach identification works, and they will help to establish a
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molecular data base for native peach cultivars. UPGMA analysis was performed from
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the genetic distance matrix, and allowed the arrangement of all genotypes according
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to their genetic diversity. The genetic diversity among cultivars, observed in this
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work, led to their separation according to their regional origin, their morphological
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characteristics, and especially according to their fruit traits. Analysis of molecular
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variance was performed for seven populations from different regions of Spain and
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USA to examine the distribution of genetic variation of the studied accessions,
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showing that the major variation occurred within populations in each geographic site.
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The results reveal the existence of two diversity regions in Spain for peach
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germplasm.
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Key words: Spanish native peach, Genetic diversity, SSR markers
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INTRODUCTION
Today, plant diversity is under threat as never before. In agriculture, the
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widespread adoption of a few improved varieties has narrowed the genetic base of the
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most important food crops and it has contributed to the disappearance of hundreds of
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landraces (Gepts 1995). Peach is one of the most economically important cultivated
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species of the Prunus genus subjected to intense breeding activity. Every year, several
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new peach varieties are created based on the market demand. So, more than thousand
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new varieties were released around the world between 1991 and 2001 (Llácer et al.
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2009a). However, the diversity of this crop has been drastically reduced by the use of
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improved varieties with a common genetic base from parents belonging to the same
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gene pool (Aranzana et al. 2003a). The United States peach cultivars are considered to
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be especially limited for diversity (Scorza et al. 1985). Besides, these cultivars are
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grown widely in many foreign countries. In Spain, the genetic diversity within
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peaches is also decreasing rapidly, because of the replacement of traditional varieties
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by introduced ones, mostly from North America (Badenes et al. 1998; Llácer et al.
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2009b). This replacement is being stimulated by the exigency of the European market
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for melting flesh cultivars that exhibit similar characteristics throughout the marketing
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season. In Spain, the peach industry is based on non-melting flesh peaches, primarily
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derived from native populations adapted to specific growing areas and genetically
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diverse. Thus, they are an excellent source of traits for breeding. Characteristics such
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as medium and high chilling requirements, late flowering, extended harvest season
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from July to November, and very high flesh quality can be found in these populations
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(Badenes et al. 1998). Managing peach biodiversity on farms and conserving it in
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collections of genetic resources are complementary approaches. Together they address
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the need for the continued future availability and use of peach biodiversity to increase
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productivity, both by breeding improved varieties and by better control of farm
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ecosystems (Gepts 1995). A detailed characterization of the peach germplasm from
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Spain is necessary to save these important genetic resources and to obtain an efficient
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core collection. Conservation of the genetic diversity provides species with the ability
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to adapt to changing stresses, such as pests and diseases or drought.
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The homogeneity of the peach germplasm is not only relevant in the decrease of
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genetic resources but also in the cultivar identification. Genetic markers reveal
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patterns and levels of genetic diversity that reflect the evolutionary relationships of
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individual accessions and can thus assist in identifying groups of accessions that are
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related by common ancestry (Gepts 1995). The number of loci assessed should be as
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high as possible and preferably should be distributed at random in the genome to
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ensure adequate genome coverage (Aranzana et al. 2003a; 2003b). Different type of
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molecular markers, from isoenzymes (Gašíc et al. 2000; Messeguer et al. 1987) to
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DNA markers like RAPDs, AFLPs, and RFLPs (Gogorcena and Parfitt 1994; Hurtado
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et al. 2001; Quarta et al. 2001) or SSR (Bouhadida et al. 2009; Decroocq et al. 2004)
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have been used to characterize genetic diversity in Prunus germplasm collections.
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Microsatellite markers, or simple sequence repeats (SSRs), which are codominant,
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and highly polymorphic markers easily detected with PCR procedure, appear as the
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best available choice of markers for peach genetic diversity assessment (Aranzana et
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al. 2003a; Bouhadida et al. 2007; Cheng and Huang 2009; Dirlewanger et al. 2002; Li
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et al. 2008; Testolin et al. 2000; Wünsch et al. 2006). However, the results depend on
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the fragment separation method used since the polyacrylamide or agarose gels have
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different resolution power.
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Local germplasm survey and collection were carried out in 1965 in all over the
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Spanish territory to start up the first germplasm collection of peach varieties in Spain
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(Cambra 1979). These peach materials have been morphologically characterized; one
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of the principal aims of this study their molecular characterization to be efficiently
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conserved in the Spanish National Peach Collection and to be used as a source of
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traits for present and future breeding programs.
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In this work, 15 SSRs were used from published sequences for the screening of 94
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peach accessions composed for a representative sample of traditional and
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autochthonous peach cultivars from different Spanish growing areas, and some
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commercial varieties included as references, in order to: (1) examine SSR
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polymorphism among cultivars; (2) estimate the genetic diversity among native and
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foreign cultivated peaches; and (3) analyze the distribution of genetic variation among
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native and foreign commercial varieties according to their geographic distribution.
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MATERIALS AND METHODS
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Plant material
A set of 94 peach [Prunus persica (L.) Batsch] cultivars including 62 Spanish
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native cultivars and 32 foreign commercial cultivars, 28 of them from USA (Table 1),
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were studied.
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The cultivars were divided based on the fruit type in 82 peach, seven nectarines and
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five flat peaches. The 84% of them are non-melting fruit cultivars, being the main
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peach type cultivated in Spain. Fifty cultivars were obtained from the National Peach
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Germplasm Collection of the “Centro de Investigación y Tecnología Agroalimentaria
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de Aragón” (CITA) and the rest from the “Estación Experimental de Aula Dei”
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(CSIC), both of them located at Zaragoza (northern Spain).
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DNA extraction and microsatellite amplification
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Table 1
Total genomic DNA was extracted using the modified CTAB procedure described
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by Cheng et al. (1997). The DNA was quantified using a spectrophotometer (Gene
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Quant, Amersham Pharmacia Biotech), and diluted to 5 ng/μl to carry out PCR
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amplification reactions.
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The 94 peach genotypes were analyzed using 15 SSRs primer pairs previously
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developed in peach by different research groups (Table 2). These 15 SSRs were
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selected according to their high polymorphism and their clear and repeatable
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amplification patterns. The loci were randomly distributed in six of the eight linkage
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groups of the peach genome. Amplification reactions were carried out according to
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the protocol cited by Bouhadida et al. (2007). The PCR amplifications were
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performed on a Gene Amp 2700 thermocycler (Applied Biosystems) using the
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following temperature cycles: one cycle of 3 min at 95ºC, 35 cycles of 1 min at 94ºC,
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45 s at the corresponding annealing temperature (Table 2), and 1 min at 72ºC. The last
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Table 2
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cycle was followed by a final incubation for 7 min at 72ºC and the PCR products were
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stored at 4ºC before electrophoresis analysis. At least two independent SSR reactions
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were performed for each DNA sample until two data points were available for each
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SSR per cultivar combination. The DNA amplification products were loaded on
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denaturing 5% polyacrylamide gels. The gels were silver-stained according to the
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protocol described by Bassam et al. (1983). Fragment sizes were estimated with the
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30-330 bp AFLP ladder (Invitrogen, Carlsbad, CA) DNA sizing markers and they
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were analyzed by the Quantity One program (Bio Rad, Hercules, CA).
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Data analysis
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To evaluate the information obtained with the 15 SSRs studied, we calculated the
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following parameters: the number of alleles (A), the effective number of alleles (Ae)
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per locus (Ae= 1/Σpi2, where pi is the frequency of the ith allele), the observed
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heterozygosity (Ho) (Ho = number of heterozygous individuals/number of individuals
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scored), the expected heterozygosity (He) (He = 1- Σpi2), and the Wright’s fixation
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index (F= 1-Ho/He) (Wright 1965). The polymorphism information content (PIC) for
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each marker was also determined (
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where pi is the frequency of the ith allele, and n is the number of alleles (Botstein et al.
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1980). The ability of a marker to discriminate between two random cultivars was
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estimated for each locus with the ‘power of discrimination’ (PD = 1-1/Σgi2, where gi
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is the frequency of the ith genotype) (Kloosterman et al. 1993).
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Samples, in which only a single allele per locus was detected, were considered
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homozygous genotypes instead of heterozygous with a null allele (that did not
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amplify) for the purpose of computing genetic diversity parameters.
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A dendrogram was constructed from a 0/0.5/1 (absence/allele in
heterozygosity/allele in homozygosity) matrix using the unweighted pair group
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method average (UPGMA) clustering. The genetic distance between cultivars was
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calculated according to the coefficient of Rogers (1972), and analyzed with the
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SIMGEND procedure of NTSYSpc V.2.1 program (Rohlf 2000). Searches for the
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most parsimonious trees were executed with PAUP* version 4.0 (Swofford, 2002).
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Parsimony analysis was carried out through an heuristic search with CLOSEST
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addition of samples, tree bisection reconnection branch swapping algorithm, and the
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MULPARS option on Bootstrap support (Felsenstein, 1985) was estimated through
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10,000 replicates imposing the same conditions as for the heuristic search.
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Geographic distribution of genetic variability
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To study the distribution of the genetic variation, the nectarine and flat fruit type
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cultivars were excluded because its low number and their geographic distribution
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make the group not representative. The analysis of molecular variance (AMOVA) was
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performed in the remainder 82 peach fruit type cultivars using the program
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ARLEQUIN Ver 3.1 (Excoffier et al. 2005) based on the number of different alleles
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and 10,000 permutations. The peach cultivars were separated a priori according to
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their origin into three groups (G1, G2, and G3) and divided in a total of seven
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populations (P1 to P7). The G1 group consisted in five populations with Spanish
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cultivars from the Ebro Valley (north-east Spain): P1 (with genotypes from Huesca
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province), P2 (Lérida), P3 (Teruel), P4 (Zaragoza), and P5 (four cultivars from the
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north of Spain). In the G2 group were included all the cultivars from Murcia and
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‘Infanta Isabel’ from Valencia, south-east of Spain (P6). The localization of both
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groups throughout the Spanish geography was represented in a map in Figure 1.
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Finally, the G3 group consisted in one population including the North American
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cultivars from USA (P7). The three foreign peach cultivars ‘Cristalino’ ‘Golden
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Figure 1
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Queen’, and ‘Nuevo 2803’ from Argentine, New Zealand, and France, respectively,
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were added to the closest population based on the genetic distances found.
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F statistics relative to each component (i.e., FCT among groups, FSC among
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populations within groups, FST within populations) were computed (Excoffier et al.
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1992). Pairwise FST values obtained by AMOVA calculations were used to construct a
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UPGMA dendrogram using NTSYS pc 2.10 software (Rohlf 2000).
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RESULTS
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Genetic diversity of SSRs markers and cultivars identification
Ninety four peach cultivars were analyzed with 15 polymorphic SSRs. All loci
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evaluated in this study were multiallelic. The number of alleles detected for each
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locus ranged from 2 (PceGA34, pchgms1, pchgms2) to 11 (UDP98-412) (Table 3).
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Size differences detected between alleles at the same locus, oscillated from 2 to 68 bp
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and differences between consecutives alleles varied from 2 to 32 bp, being 2 bp in
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47% of the cases. The alleles obtained in different loci and their respective
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frequencies are shown in Table 3. The most frequent alleles of this study were
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detected for the loci pchgms1 (194 bp) and pchgms2 (157 bp), with frequencies
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higher than 90%. Seven alleles (6.93% of the total) showed frequencies between 0.40
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and 0.90. The frequencies of 16 alleles (15.84%) were comprised between 0.20 and
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0.40. Furthermore, 45 alleles (44.55%) exhibited low frequencies (less than 5%)
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including 14 unique allele with frequencies of 0.5% (Table 3). These rare alleles were
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detected at 13 of the 15 loci analyzed and 33 of them, counting 10 unique alleles,
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were observed at the non-melting peach cultivars.
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A total of 101 alleles were identified at the 15 SSR loci with an average of 6.73
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alleles per locus (Table 4). Among the observed alleles in this study, 92 were found in
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the non-melting peaches and 41 (45%) were specific for this group. The nectarine and
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the melting peach groups showed 59 and 44 alleles, respectively, with only one
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specific allele for each one. On the other hand, 36 alleles were shared by the three
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groups, 15 were common to the non-melting and melting peach groups, and seven
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were found in both nectarine and melting peach groups.
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Values of the observed heterozygosity were lower than the corresponding expected
heterozygosity for all loci (Table 4). The expected heterozygosity ranged from 3% in
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Table 3
Table 4
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pchgms2 to 85% in BPPCT001, with an average value of 57%. The observed
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heterozygosity varied between 1% (pchgms2) and 43% (BPPCT006), with an average
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value of 23%. Another of the parameters calculated, the Wright’s fixation index (F),
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compares He with Ho, estimating the degree of allelic fixation, and ranged from 0.30
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in BPPCT006 to 0.76 in CPPCT029, with an average value of 0.58.
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The PIC values are equal or slightly lower than the expected heterozygosity and
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are correlated with the corresponding Ae (effective number of alleles) values. The
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most informative locus of this study was BPPCT001, with a PIC value of 0.84 and a
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Ae of 6.67, while the less informative one was pchgms2 with a PIC and Ae values of
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0.03 and 1.03, respectively (Table 4).
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Table 4 also shows the discrimination power (PD) for each SSR locus with a mean
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value of 0.66. The highest PD was observed in BPPCT001 (0.93), whereas pchgms2
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showed the lowest one (0.04). All loci distinguished up 185 different genotypes.
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The selection of the five most polymorphic loci which revealed the highest number
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of different genotypes: BPPCT001 (22); BPPCT008 (21); PS9f8 (24); UDP98-412
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(18); and UDP98-022 (17), allowed us to distinguished unambiguously all the 62
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Spanish native peach cultivars, with the exception of ‘Paraguayo Villamayor’ and
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‘Paraguayo San Mateo’. To identify separately these two cultivars, an additional
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BPPCT006 marker was selected, which revealed distinct alleles between them. Thus,
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an identification key was established to distinguish among the 62 Spanish peach
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cultivars (Figure 2). The procedure consists at joining together the cultivars presenting
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the same genotype for one locus. Cultivars which showed different genotypes were
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separated.
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Figure 2
The six selected loci also allowed the identification of 92 genotypes from the 94
studied. Whereas, the cultivars ‘Halford’ and ‘Gaume’, as well as ‘Valentín’ and
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‘Garau’, showed the same genetic profile each pair with the six SSRs. The loci
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CPPCT022 and CPPCT029 were also selected to separate between the first and the
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second pair of cultivars, respectively. Consequently, only eight from the 15 SSRs
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initially used, allowed the total identification of all (94) peach cultivars included in
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the study.
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Genetic diversity among peach cultivars based on SSR variation
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To elucidate genetic diversity among the peach cultivars studied, a dendrogram
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was produced using UPGMA cluster analysis and the Rogers distance over the 15
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SSR loci (Figure 3).
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The cultivars were clustered in two different groups at a genetic distance of 0.48.
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The first one constituted a main group which was subdivided into different subgroups.
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On the contrary, the second group of the dendrogram was composed only for five
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cultivars, representing four flat white melting peaches and the white non-melting
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peach cultivar ‘Binaced’.
At the similarity coefficient value of 0.38, the first main group, generated from the
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UPGMA cluster analysis, showed four subgroups. The first one was composed
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principally by clingstone non-melting peaches, and it was also divided into different
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clusters. The second and third subgroups were composed for three clingstone non-
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melting peach cultivars each one, while all the nectarines and melting peaches (except
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Spanish flat melting peach cultivars) were included in the fourth subgroup. The
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nectarine cultivars were clustered together while four melting peach cultivars and
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some non-melting peaches (‘Sudanell 3’, ‘Montamar’, ‘Babyi Gold 7’, ‘Babyi Gold
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6’, and ‘Babyi Gold 8’) were included in the other cluster of this subgroup 4.
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Considering genetic distance values, non-melting peaches were the most diverse with
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an average distance between cultivars of 0.40, compared with 0.25 for nectarines and
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Figure 3
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0.32 for melting peaches. The non-melting peaches were also the most separated from
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the others, with average distances of 0.43 and 0.40 from the melting peaches and
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nectarines, respectively. A lower average distance was detected between melting
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peaches and nectarines with a value of 0.35. Some cultivars of this study, such as
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‘Jerónimo Ortiz’ and ‘Maruja Perfección’; ‘Selma’ and ‘Calabacero Rancho’;
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‘Amarillo de Calanda’ and ‘Tardío del Pilar’, were closely related with distance
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coefficient values of 0.020, 0.025, and 0.025, respectively. The highest distance
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between cultivars was found between ‘Paraguayo Villamayor’ and ‘Campiel Montes
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de Cierzo’ with a genetic distance of 0.58.
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The first subgroup of the first main group appeared as the most diversified one,
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showing the genetic variability among the peach cultivars. It is relevant to notice that
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inside of this subgroup were included most of the local Spanish peach cultivars. The
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peach cultivars from the Murcia region (south-east Spain) but ‘Brasileño’ (Figure 3)
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were clustered together. Also, in this cluster, peach cultivars from other Spanish
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regions (Valencia, Lérida, and Bilbao) and some foreign ones were included.
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Additionally, Spanish native peach cultivars, mostly from the Ebro Valley area
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(Navarra, Zaragoza, Huesca, Teruel, Lérida) in the north-east of Spain, were clustered
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in the subgroup 1. Some associations were validated using the bootstrap analysis as it
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is showed in Fig. 3. The connection among three of the flat white melting peaches in
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group 2 showed high bootstrap support (90%), as well as other associations between
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peach cultivars as in the case of ‘Amarillo de Calanda’ and ‘Tardío del Pilar’ or
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‘Brasileño’ and ‘Del Gorro’ with a support of 92%, or ‘Pepita’ and ‘Babyi Gold 5’
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with 83%.
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Distribution of genetic variability
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AMOVA calculations were performed only with the remaining peach cultivars
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resulted after the exclusion of nectarine and flat fruit type cultivars. The 82 cultivars
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were grouped by their geographical origin into seven populations. The results of the
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AMOVA analysis (Table 5) showed that the 88.70% of the allelic diversity was
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attributed to individuals within populations while only a small but significant
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proportion was associated to differences among groups (5.41%) and among
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populations within groups (5.88%). F values at different levels were highly significant
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(FCT= 0.054, FSC= 0.062, FST= 0.113) with P< 0.001.
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The dendrogram (Figure 4) based on population pairwise genetic distances (FST)
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between regions showed the distribution of genetic diversity for the peach accessions,
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and two main groups (A and B) were differentiated. Group A included all the
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populations from the Ebro Valley (Huesca, Zaragoza, Lérida and the cultivars from
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the North of Spain), USA and Teruel. However, group B included only one
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population (P6), with cultivars from the South-East of Spain (Murcia and Valencia).
Table 5
Figure 4
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DISCUSSION
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Genetic diversity of SSRs markers and cultivars identification
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In this study, we obtained an average of 6.73 of alleles per locus. This value was
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higher than the averages observed by others authors [(2.3) Bouhadida et al. (2007);
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(3.1) Cheng and Huang 2009; (4.2) Dirlewanger et al. 2002; (5.0) Li et al. 2008; (4.5)
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Testolin et al. 2000], probably due to the use of a more diverse number of cultivars
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and a set of microsatellites with higher polymorphism level. The level of
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polymorphism and the range of amplified band sizes were similar to those reported by
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Aranzana et al. (2003a) for peach, using 11 common SSR markers to that used in this
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study. The results are also consistent with Testolin et al. (2000) using UDP markers in
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other peach cultivars.
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Thirty-three from the 45 rare alleles (frequencies less than 5%) found in this study
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were observed for the non-melting peaches, 10 of them being unique alleles. This
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result could be due to the large number of non-melting cultivars analyzed in this work
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and provide additional information about the genetic diversity existing among
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cultivars of this group. Likewise, the non-melting peach cultivars presented 41
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specific alleles out of the 92 detected for this group confirming its high variability
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with respect to nectarine (one specific allele) and melting peach (one specific allele)
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groups. Although the high proportion of non-melting cultivars analyzed in this study
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could distort the results, these are in agreement with the results reported in other
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works. Aranzana et al. (2003a) analyzed peach cultivars, using 16 SSRs, and also
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observed that the non-melting peach group, was the most diverse one with 76 alleles,
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and showing the highest number (18) of specific alleles with respect to melting peach
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(8) and nectarine (16) groups.
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In the present study, observed heterozygosity averaged over the 15 SSR loci and 64
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peach fruit type cultivars was 0.23, lower than the 0.35 mean value reported by
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Aranzana et al. (2003a) for a set of 212 peach cultivars analyzed with 16 SSRs
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whereas the expected heterozygosity was slightly higher than the 0.50 obtained by the
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same authors (Aranzana et al. 2003a). The presence of null alleles that affected the
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heterozygosity level could be the cause of the differences. The lower value obtained
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in our analysis for the Ho was probably due to the assumption of homozygosity
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instead of null alleles, implying an overestimation of the allele frequency and an
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underestimation of heterozygosity. The high allele number observed in this study
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(mean value=6.73) and the expected heterozygosity reflect the ability of SSR markers
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to provide unique molecular profiles for individual plant genotypes. Our results
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indicate that PIC and Ae are very useful parameters for the evaluation of adequate
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SSR markers to distinguish unambiguously related peach cultivars. In fact, it is
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important to select the most informative SSR loci to reduce the number of loci
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necessary to characterize a peach collection. Moreover, the mean value of the PD
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obtained in this study (0.66), agrees well with the mean value (0.64) obtained by
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Aranzana et al. (2003a), which justify the use of SSR markers to identify the level of
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variation in peach.
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The fixation index average (F=0.58) indicated very great genetic differentiation
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(Hartl and Clark 1997) among the peach accessions studied. At the same time, this
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average showed an excess of homozygotes (Murray 1996), probably due to these two
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factors: the presence of null alleles which are leading to a false observation of excess
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homozygotes or the inbreeding in the population. Peach is, in fact, a self-fertile and
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naturally self-pollinates. It is considered tolerant of inbreeding, and open pollination
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usually results in less than 5% outcrossing (Fogle 1977), which can explain this
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deviation from the Hardy-Weinberg equilibrium.
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On the other hand, the high level of genetic differentiation detected among the
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peach accessions could be attributed either to the different geographical region
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adaptation of accessions, to the peach mating system or to human impact. Maghuly et
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al. (2005) also reported similar observations for apricot. Several cultivars included in
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this study were analyzed by Wünsch et al. (2006) with 10 SSR markers. They
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observed various synonyms among them. In fact, they mentioned that the followed
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group of cultivars: ‘Paraguayo Villamayor’ and ‘Paraguayo San Mateo’; ‘Sudanell 2’
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and ‘San Lorenzo’; ‘Pomar 1’ and ‘Calanda’; ‘Rojo del Rito (5233)’, ‘Escolapio’ and
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‘Borracho de Jarque’; finally, ‘San Jaime’, ‘Calabacero Candelo’, ‘Calabacero
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Rincón’, ‘Calabacero Soto’, ‘Calabacero Deleite’, ‘Calabacero Rancho’, and ‘Maruja
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Perfección’ showed the same SSR profile patterns for each group. It is relevant to
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notice that only six SSRs of the present study permit to distinguish unambiguously
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among these accessions. This can be explained by the higher level of polymorphism
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of the SSRs selected and the use of polyacrylamide gels as separation method in our
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work, which shows a better resolution and permit to detect more alleles in the
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collection.
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The identification key elaborated for the 62 Spanish native peach cultivars based
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on the selected six SSRs seems to be very useful to establish a molecular data base for
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Spanish peach cultivars to be included in the National Germplasm Collection.
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Moreover, the most polymorphic microsatellites selected for the elaboration of this
372
identification key can be used for future Spanish peach identification works. Similar
373
identification keys have been obtained for other woody species using microsatellite
374
markers (Krichen et al. 2006; Zehdi et al. 2004).
17
375
Genetic diversity among peach cultivars based on SSR variation
376
The dendrogram generated from the UPGMA cluster analysis (Figure 3) produced
377
significant groups, related to the morphological characteristics and the geographical
378
origin of the genotypes. The dendrogram showed two main groups. The first one
379
corresponded to the most important group, which is divided in four subgroups
380
subdivided in turn in clusters. The Spanish yellow flesh, clingstone, and non-melting
381
peach cultivars were localized mainly in the first subgroup. They were clustered by
382
their geographic origin showing the existence of two important diversity regions for
383
peach in Spain due to the selection carried out in function of the edaphoclimatic needs
384
of each region (Martínez-Mora et al. 2008). Thus, cultivars growing in the Murcia
385
region (south-east of Spain) were grouped under the same cluster inside the subgroup
386
1 just like other Spanish native peach cultivars, mostly growing in the Ebro Valley,
387
that were in separated clusters of the same subgroup. The cultivars from USA were
388
distributed in different clusters mixed with the Spanish germplasm and it could be due
389
to the use of ancient non-melting Spanish cultivars in American breeding programs as
390
it was mentioned by Okie (1998).
391
All the nectarine and melting peach cultivars but four flat melting peaches were
392
clustered together in the fourth subgroup. Aranzana et al. (2003a) also observed a
393
narrow genetic base among melting peaches and nectarines with respect to non-
394
melting peach cultivars. However, some non-melting peach cultivars (‘Ortiz’,
395
‘Sudanell 3’, ‘Montamar’, ‘Babyi Gold 7’, ‘Babyi Gold 6’, and ‘Babyi Gold 8’) were
396
also clustered in the fourth subgroup probably due to the existence of a common
397
genetic base within the cultivars of this subgroup. Aranzana et al. (2003a) also
398
observed one non-melting peach cultivar (‘Babyi Gold 7’) clustered with the melting
399
peach group, which can agree with our findings. Analysis of population structure
18
400
performed in 225 peaches and nectarines showed also a division of the cultivars based
401
on the fruit type and according with the results obtained in our work (Abbassi 2007).
402
High average genetic distances detected first, within non-melting cultivars, and
403
second, between non-melting and melting (0.43) as well as between non-melting and
404
nectarine (0.40) groups, confirm the higher diversity of the peach cultivars used in this
405
study.
406
The second main group of the dendrogram was composed of only five cultivars
407
representing four flat melting peaches and the white non-melting peach cultivar
408
‘Binaced’. Aranzana et al. (2003a) and Wünsch et al. (2006) also showed the genetic
409
separation of the Spanish flat shape peach type group called ‘Paraguayos’ from the
410
other peach cultivars. The bootstrap analysis was not especially informative since few
411
connections could be validated by this method. However, it was possible to confirm
412
some of the associations found with the UPGMA method. So, the close relationship
413
between cultivars with almost the same genetic profile such as ‘Halford’ and
414
‘Gaume’, ‘Valentín’ and ‘Garau’, or ‘Amarillo de Calanda’ and ‘Tardío del Pilar’ was
415
verified. These results were in agreement with the existence of a common genetic
416
base within the group 1 cultivars.
417
Distribution of genetic variability
418
The distribution of the genetic variation in the peach fruit type cultivars was
419
performed by AMOVA analysis. The biggest differences occurred within populations
420
confirming the high variability found in the studied peach cultivars (Table 5). The
421
dendrogram based on population pairwise genetic distances (FST) between regions
422
showed the distribution of genetic variability for the peach accessions, and
423
differentiates two main groups according to their adaptation to different
424
environmental conditions (Figure 4). Group A included all the populations from the
19
425
Ebro Valley area (Huesca, Zaragoza, Lérida and the cultivars from the north of
426
Spain), USA and Teruel. Group B included only one population (P6) with cultivars
427
from the south-east of Spain (Murcia and Valencia).
428
Surprisingly, the Ebro Valley cultivars with a continental Mediterranean influence,
429
clustered together with the cultivars from USA suggesting a more common gene pool.
430
These results agree with the fact that some Spanish cultivars could be used in the
431
American breeding programs as it was mentioned above. The group B containing
432
cultivars from the south-east of Spain with Mediterranean maritime climate pointed
433
out the existence of two diversity regions in Spain for peaches (Martínez-Mora et al.
434
2008). The diversity found in both regions might be due to the adaptation to specific
435
edaphoclimatic conditions and the socioeconomic factor associated. In fact, peach
436
industry in the north is mainly based on medium to late harvested cultivars with
437
medium to high chilling requirements. In contrast, cultivars growing in the warmer
438
areas of the south-east exhibit in general lower chilling requirements and early
439
maturity. It is worthy to mention that Teruel appeared in the dendrogram connecting
440
Ebro Valley and south-east populations in agreement with the geographic location for
441
this province.
442
443
In conclusion, non-melting peach populations from Spain can be an excellent
444
source of traits for breeding due to the genetic diversity found. As it was mentioned
445
above, the distribution of the genetic variation point out the existence of two
446
diversification regions in Spain that could be attributed to the specific adaptation to
447
the different regional environments and the peach industry requirements.
448
The molecular identification of the genetic diversity among native and foreign
449
cultivated peaches is required to preserve this plant material. The conservation will
20
450
provide an excellent source of traits available for future breeding goals and for the
451
creation of new varieties, although further studies have to be done in order to establish
452
the structure of the Spanish populations as well as the pedigree of the cultivars
453
included in the peach National Germplasm Collection.
21
454
ACKNOWLEDGMENTS
455
This study was supported by the Spanish MICINN (Ministry of Science and
456
Innovation) projects AGL2005-05533 and AGL-2008-00283, cofunded by FEDER,
457
INIA (Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, project
458
RF2007-00026-C02-00) and the Regional Government of Aragon (A44). M.
459
Bouhadida was supported by a fellowship from the AECI (Agencia Española de
460
Cooperación Internacional) of the Spanish Ministry of Foreign Affairs, and M.J.
461
Gonzalo was the beneficiary of an I3P-PC2006 contract from the CSIC-FSE. We
462
thank L.A. Inda for technical assistance with the bootstrap analysis.
22
463
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464
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582
Table 1. Names of the studied cultivars and their collections; origin and geographic
583
area; main fruit characteristics, and group classification.
Cultivar
Alcañiz 1
Collectiona
EEAD
Originb
Teruel, SP
Alcañiz 2
EEAD
Teruel, SP
Amarillo de Calanda
EEAD
Amarillo Tardío
Andora
Geographic
areac
Group /
population
NE
Fruit type
Peach
Flash color
Yellow
Flesh type
Non-melting
NE
Peach
Yellow
Non-melting
G1/P3
Huesca, SP
NE
Peach
Yellow
Non-melting
G1/P1
EEAD
Zaragoza, SP
NE
Peach
Yellow
Non-melting
G1/P4
EEAD
USA
-
Peach
Yellow
Non-melting
G3/P7
G3/P7
G1/P3
Andross
CITA
USA
-
Peach
Yellow
Non-melting
Armking
CITA
USA
-
Nectarine
Yellow
Melting
-
Baby Gold 5
EEAD
USA
-
Peach
Yellow
Non-melting
G3/P7
Baby Gold 6
EEAD
USA
-
Peach
Yellow
Non-melting
G3/P7
Baby Gold 7
EEAD
USA
-
Peach
Yellow
Non-melting
G3/P7
Baby Gold 8
EEAD
USA
-
Peach
Yellow
Non-melting
G3/P7
Ballejo
CITA
Zaragoza, SP
NE
Peach
White
Non-melting
G1/P4
Benasque
EEAD
Huesca, SP
NE
Peach
Yellow
Non-melting
G1/P1
Binaced
CITA
Huesca, SP
NE
Peach
White
Non-melting
G1/P1
Blanco Tardío
CITA
Zaragoza, SP
NE
Peach
White
Melting
G1/P4
Bonet 2
EEAD
Lérida, SP
NE
Peach
Yellow
Non-melting
G1/P2
Bonet 3
EEAD
Lérida, SP
NE
Peach
Yellow
Non-melting
G1/P2
Bonet 4
EEAD
Lérida, SP
NE
Peach
Yellow
Non-melting
G1/P2
Bonet 5
EEAD
Lérida, SP
NE
Peach
Yellow
Non-melting
G1/P2
Borracho de Jarque
CITA
Zaragoza, SP
NE
Peach
Yellow
Non-melting
G1/P4
Brasileño
EEAD
Murcia, SP
SE
Peach
Yellow
Non-melting
G2/P6
Calabacero Candelo
CITA
Murcia, SP
SE
Peach
Yellow
Non-melting
G2/P6
Calabacero Deleite
CITA
Murcia, SP
SE
Peach
Yellow
Non-melting
G2/P6
Calabacero Rancho
CITA
Murcia, SP
SE
Peach
Yellow
Non-melting
G2/P6
Calabacero Rincón
CITA
Murcia, SP
SE
Peach
Yellow
Non-melting
G2/P6
Calabacero Soto
CITA
Murcia, SP
SE
Peach
Yellow
Non-melting
G2/P6
Calanda
CITA
Teruel, SP
NE
Peach
Yellow
Non-melting
G1/P3
Campiel Montes de Cierzo
CITA
Navarra, SP
N
Peach
Yellow
Non-melting
G1/P5
Campiel Rojo
EEAD
Huesca, SP
NE
Peach
Yellow
Non-melting
G1/P1
Carolyn
EEAD
USA
-
Peach
Yellow
Non-melting
G3/P7
Carson
EEAD
USA
-
Peach
Yellow
Non-melting
G3/P7
Corona
EEAD
USA
-
Peach
Yellow
Non-melting
G3/P7
Cristalino
CITA
ARG
-
Peach
White
Non-melting
G3/P7
Del Gorro
EEAD
Zaragoza, SP
NE
Peach
Yellow
Non-melting
G1/P4
Duraznillo
CITA
Zaragoza, SP
NE
Peach
Yellow
Non-melting
G1/P4
Escolapio
CITA
Zaragoza, SP
NE
Peach
Yellow
Non-melting
G1/P4
Everts
EEAD
USA
-
Peach
Yellow
Non-melting
G3/P7
Early Diamond
EEAD
USA
-
Nectarine
Yellow
Melting
-
Fantasia
EEAD
USA
-
Nectarine
Yellow
Melting
-
Flamekist
EEAD
USA
-
Nectarine
Yellow
Melting
Flavortop
EEAD
USA
-
Nectarine
Yellow
Melting
-
Fraga
EEAD
Huesca, SP
NE
Peach
White
Non-melting
G1/P1
Gallur
CITA
Zaragoza, SP
NE
Peach
Yellow
Non-melting
G1/P4
Garau
CITA
USA
-
Peach
Yellow
Non-melting
G3/P7
G3/P7
Gaume
CITA
USA
-
Peach
Yellow
Non-melting
Goiri
EEAD
Bilbao, SP
N
Peach
Yellow
Non-melting
G1/P5
Golden Queen
EEAD
NZL
-
Peach
Yellow
Non-melting
G1/P4
Halford
EEAD
USA
-
Peach
Yellow
Non-melting
G3/P7
584
28
585
Table 1 (Continued)
Collectiona
EEAD
Originb
Valencia, SP
Jerónimo
CITA
Murcia, SP
Jerónimo de Alfaro
EEAD
Jerónimo Ortiz
Cultivar
Infanta Isabel
Geographic
Areac
Group /
population
SE
Fruit type
Peach
Flash color
Yellow
Flesh type
Non-melting
SE
Peach
Yellow
Non-melting
G2/P6
Murcia, SP
SE
Peach
Yellow
Non-melting
G2/P6
CITA
Murcia, SP
SE
Peach
Yellow
Non-melting
G2/P6
Jerónimo Torres
CITA
Murcia, SP
SE
Peach
Yellow
Non-melting
G2/P6
Jesca
CITA
Teruel, SP
NE
Peach
Yellow
Non-melting
G1/P3
Jungerman
EEAD
USA
-
Peach
Yellow
Non-melting
G3/P7
Klamt
EEAD
USA
-
Peach
Yellow
Non-melting
G3/P7
Loadel
EEAD
USA
-
Peach
Yellow
Non-melting
G3/P7
Maluenda
EEAD
Zaragoza, SP
NE
Peach
Yellow
Non-melting
G1/P4
Manolito
CITA
Lérida, SP
NE
Peach
Yellow
Non-melting
G1/P2
Maruja Perfección
CITA
Murcia, SP
SE
Peach
Yellow
Non-melting
G2/P6
May Grand
CITA
USA
-
Nectarine
Yellow
Melting
-
Miraflores Serapio
CITA
Zaragoza, SP
NE
Peach
Yellow
Non-melting
G1/P4
Montamar
CITA
Zaragoza, SP
NE
Peach
Yellow
Non-melting
G1/P4
Nuevo 2803
EEAD
FRA
-
Peach
Yellow
Non-melting
G2/P6
Ortiz
CITA
Zaragoza, SP
Peach
White
Melting
G1/P4
Paloro A
EEAD
USA
NE
-
Peach
Yellow
Non-melting
G3/P7
Paloro B
EEAD
USA
-
Peach
Yellow
Non-melting
G3/P7
Paraguayo Amarillo
CITA
Zaragoza, SP
NE
Flat
Yellow
Melting
-
Paraguayo Caspe
CITA
Zaragoza, SP
NE
Flat
White
Melting
-
G2/P6
Paraguayo San Mateo
CITA
Zaragoza, SP
NE
Flat
White
Melting
Paraguayo Sweet Cap
CITA
FRA
-
Flat
White
Melting
-
Paraguayo Villamayor
CITA
Zaragoza, SP
NE
Flat
White
Melting
-
Pepita
CITA
Huesca, SP
NE
Peach
Yellow
Non-melting
G1/P1
Pigat
CITA
Huesca, SP
NE
Peach
Yellow
Non-melting
G1/P1
Pigat Susagna
CITA
Huesca, SP
NE
Peach
White
Non-melting
G1/P1
Pomar 1
CITA
Lérida, SP
NE
Peach
White
Non-melting
G1/P2
Redhaven
CITA
USA
-
Peach
Yellow
Melting
G3/P7
Rojo Amarillo de Septiembre
CITA
Zaragoza, SP
NE
Peach
Yellow
Non-melting
G1/P4
Rojo del Rito
CITA
Lérida, SP
NE
Peach
Yellow
Non-melting
G1/P2
Rojo del Rito 5233
CITA
Lérida, SP
NE
Peach
Yellow
Non-melting
G1/P2
San Jaime
CITA
Lérida, SP
NE
Peach
Yellow
Non-melting
G1/P2
San Lorenzo
CITA
Huesca, SP
NE
Peach
Yellow
Non-melting
G1/P1
Selma
EEAD
USA
-
Peach
Yellow
Non-melting
G3/P7
September Red
CITA
USA
-
Nectarine
Yellow
Melting
-
Starn
EEAD
USA
-
Peach
Yellow
Non-melting
G3/P7
Sudanell 1
CITA
Lérida, SP
NE
Peach
Yellow
Non-melting
G1/P2
Sudanell 2
CITA
Lérida, SP
NE
Peach
Yellow
Non-melting
G1/P2
Sudanell 3
CITA
Lérida, SP
NE
Peach
Yellow
Non-melting
G1/P2
Sudanell Blanco
EEAD
Zaragoza, SP
NE
Peach
White
Non-melting
G1/P4
Tambarria
CITA
Navarra, SP
N
Peach
White
Non-melting
G1/P5
Tardío del Pilar
EEAD
Teruel, SP
NE
Peach
Yellow
Non-melting
G1/P3
Valentín
CITA
Navarra, SP
N
Peach
White
Non-melting
G1/P5
Zaragozano Amarillo
EEAD
Zaragoza, SP
NE
Peach
Yellow
Non-melting
G1/P4
Zaragozano Rojo
EEAD
Zaragoza, SP
NE
Peach
Yellow
Non-melting
G1/P4
a
EEAD: Estación Experimental de Aula Dei (CSIC); CITA: Centro de Investigación y Tecnología Agroalimentaria de Aragón (DGA).
b
SP: Spain; USA: United States of America; FRA: France; ARG: Argentine; NZL: New Zealand
c
N: north; NE: north-east; SE: south-east
29
586
587
Table 2. Characteristics of the 15 SSR markers studied
Locus
Ta (ºC)
LG
Origin
BPPCT001
60
2
P. persica
Dirlewanger et al. (2002)
BPPCT006
58
7
P. persica
Dirlewanger et al. (2002)
BPPCT008
59
6
P. persica
Dirlewanger et al. (2002)
CPPCT005
58
4
P. persica
Aranzana et al. (2002)
CPPCT006
60
8
P. persica
Aranzana et al. (2002)
CPPCT022
58
7
P. persica
Aranzana et al. (2002)
CPPCT029
58
1
P. persica
Aranzana et al. (2002)
PceGA34
58
2
P. cerasus
Downey and Iezzoni (2000)
pchgms1
57
2
P. persica
Sosinski et al. (2000)
pchgms2
58
4
P. persica
Sosinski et al. (2000)
pchgms3
58
1
P. persica
Sosinski et al. (2000)
PS9f8
50
1
P. cerasus
Joobeur et al. (2000)
UDP98-022
64
1
P. persica
Testolin et al. (2000)
UDP98-407
60
6
P. persica
Testolin et al. (2000)
UDP98-412
57
6
P. persica
Testolin et al. (2000)
Ta: annealing temperature used
References
LG: Linkage group location of the 15 SSR markers. The position was based on the Prunus reference map (TxE)
cited by Aranzana et al. (2003b)
30
588
589
Table 3. Allele size (AS) in base pairs and allele frequency (AF) observed for the 94 peach cultivars analyzed with 15 SSR markers
Letter code
A
B
C
D
E
F
G
H
I
J
K
BPPCT001
AS
AF
134
0.059
148
0.011
154
0.149
156
0.117
158
0.176
160
0.122
162
0.202
164
0.011
166
0.154
BPPCT006
AS
AF
119
0.601
121
0.053
127
0.043
129
0.027
131
0.154
133
0.005
135
0.053
137
0.043
141
0.021
BPPCT008
AS
AF
103
0.106
135
0.080
137
0.250
139
0.074
149
0.005
155
0.053
157
0.287
159
0.096
161
0.037
CPPCT005
AS
AF
153
0.867
155
0.005
157
0.032
161
0.005
176
0.005
178
0.064
180
0.021
CPPCT006
AS
AF
182
0.005
184
0.144
194
0.761
196
0.011
198
0.005
CPPCT022
AS
AF
232
0.027
252
0.053
254
0.011
282
0.043
284
0.011
288
0.138
294
0.011
296
0.394
298
0.229
300
0.064
PS9f8
AF
0.011
0.021
0.181
0.048
0.032
0.059
0.261
0.271
0.027
0.005
UDP98-022
AS
AF
127
0.346
133
0.011
135
0.096
137
0.223
139
0.150
141
0.138
143
0.011
UDP98-407
AS
AF
184
0.261
186
0.011
206
0.059
208
0.410
210
0.213
218
0.021
236
0.016
UDP98-412
AS
AF
102
0.005
116
0.005
118
0.016
124
0.016
126
0.117
128
0.059
130
0.293
132
0.388
134
0.069
136
0.011
138
0.011
CPPCT029
AS
AF
178
0.005
184
0.005
192
0.484
194
0.154
196
0.293
198
0.021
PceGA34
AS
AF
144
0.362
148
0.617
pchgms1
AS
AF
194
0.947
196
0.053
Table 3 (continued)
Letter code
A
B
C
D
E
F
G
H
I
J
K
pchgms2
AS
AF
157
0.984
165
0.005
pchgms3
AS
AF
173
0.005
175
0.043
181
0.633
204
0.069
206
0.229
AS
152
154
156
160
162
164
166
168
170
172
31
590
Table 4. Parameters of variability calculated for the 15 SSR markers in 94 peach
591
cultivars
592
Locus
A
Ae
Ho
He
F
PIC
# Genotypes
PD
BPPCT001
9
6.67
0.41
0.85
0.51
0.84
22
0.93
BPPCT006
9
2.53
0.43
0.60
0.30
0.59
15
0.79
BPPCT008
9
5.51
0.27
0.82
0.68
0.81
21
0.87
CPPCT005
7
1.32
0.14
0.24
0.43
0.24
11
0.31
CPPCT006
5
1.67
0.15
0.40
0.63
0.40
5
0.50
CPPCT022
10
4.23
0.19
0.76
0.75
0.75
16
0.81
CPPCT029
6
2.91
0.16
0.66
0.76
0.63
9
0.74
PceGA34
2
1.95
0.19
0.49
0.61
0.44
3
0.62
pchgms1
2
1.11
0.06
0.10
0.37
0.10
3
0.16
pchgms2
2
1.03
0.01
0.03
0.66
0.03
2
0.04
pchgms3
5
2.18
0.27
0.54
0.51
0.51
8
0.70
PS9f8
10
5.49
0.31
0.82
0.62
0.80
24
0.89
UDP98-022
7
4.54
0.35
0.78
0.55
0.77
17
0.89
UDP98-407
7
3.51
0.30
0.71
0.58
0.69
11
0.81
UDP98-412
11
3.86
0.21
0.74
0.71
0.72
18
0.81
Mean
6.73
3.23
0.23
0.57
0.58
0.55
12.33
0.66
All loci
101
48.51
185
1
A: Number of alleles; Ae: Effective number of alleles; Ho: Observed heterozygosity; He Expected heterozygosity; F:
Wright’s fixation index; PIC: Polymorphism information content; PD: Discrimination power
593
32
594
Table 5: Analysis of molecular variance partitioning genetic variability within and
595
among eight populations and three groups after amplification of 82 peach cultivars
596
using 15 SSRs.
Source of
variation
df
Sum of
squares
Variance
Percentage of
components
variation
Among groups
2
37.94
0.19
Among populations
within groups
4
27.39
Within populations
157
Total
163
F
P
5.41
0.054
< 0.001
0.21
5.88
0.062
< 0.001
496.29
3.16
88.7
0.113
< 0.001
561.62
3.56
597
33
598
Figure legends
599
Figure 1. Geographic localization of the six Spanish populations defined a priori for
600
the distribution of the genetic variation study (P1: genotypes from Huesca, P2: Lérida,
601
P3: Teruel, P4: Zaragoza, P5: cultivars from the north of Spain, P6: Murcia and
602
Valencia, south-east of Spain). The Ebro Valley area was highlighted.
603
Figure 2. Identification key for the 62 Spanish native peach cultivars based on six
604
microsatellite markers: BPPCT001, BPPCT008, PS9f8, UDP98-412, UDP98-022, and
605
BPPCT006
606
Figure 3. .UPGMA dendrogram of 94 peach cultivars based on their variation at 15
607
SSR loci according to the coefficient of Rogers. Bootstrap percentages, when greater
608
than 50%, are shown above the branches.
609
Figure 4. UPGMA dendrogram of 82 peach cultivars based on population pairwise
610
genetic distance among regions (FST) derived from AMOVA analysis after
611
amplification with 15 SSR loci. Geographic areas are based on populations names
612
defined a priori (see Material and Methods): Huesca (P1), Lérida (P2), Teruel (P3),
613
Zaragoza (P4), North (P5), Murcia (P6), and USA (P7).
34
614
Figure 1
615
P5
P5
P1
P2
P4
Ebro Valley
P3
Madrid
P6
P6
35
616
617
Figure 2
bb
PS9f8
cc
Infanta Isabel
Duraznillo
cc
gi
cc
BPPCT008
dh
PS9f8
gg
UDP98-412
ii
UDP98-022
ff
BPPCT006
Paraguayo San Mateo
ii
Paraguayo Villamayor
di
Paraguayo Caspe
gg
cd
bb
Montamar
gh
Paraguayo Amarillo
PS9f8
gg
Pigat Susagna
hh
Gallur
BPPCT008
cf
Blanco Tardio
bb
cg
BPPCT008
cc
Calabacero Soto
cd
Calabacero Candelo
ce
Calabacero Rincón
cg
Calabacero Deleite
ci
Calabacero Rancho
PS9f8
dg
San Lorenzo
ci
Manolito
aa
cc
Fraga
ee
Campiel Montes de Cierzo
PS9f8
af
dd
Campiel Rojo
BPPCT008
ff
Zaragozano Amarillo
ah
gg
Calanda
PS9f8
gg
UDP98-412
ef
aa
Brasileño
af
Del Gorro
UDP98-022
dg
Jerónimo de Alfaro
di
Ballejo
bb
Goiri
bc
BPPCT001
ee
BPPCT008
cc
Jerónimo Ortiz
PS9f8
hh
UDP98-412
hh
aa
Maruja Perfección
ad
San Jaime
UDP98-022
di
Miraflores Serapio
gg
Sudanell 1
ag
eg
ei
BPPCT008
BPPCT008
bb
Ortiz
PS9f8
ce
gh
Jerónimo
hh
Jerónimo Torres
UDP98-412
ch
Sudanell 3
aa
Alcañiz 2
ci
Bonet 3
ff
Benasque
fg
Amarillo Tardío
cc
Pepita
dh
gg
BPPCT008
gg
Tambarria
PS9f8
ah
UDP98-412
ee
aa
Maluenda
cc
Pomar 1
UDP98-022
dd
hh
gg
gi
BPPCT008
Escolapio
PS9f8
ff
Bonet 4
hh
Borracho de Jarque
UDP98-412
ac
Bonet 2
ah
Jesca
ai
Rojo Amarillo de Septiembre
hh
Zaragozano Rojo
aa
ii
618
36
BPPCT008
PS9f8
cc
UDP98-412
gg
UDP98-022
ad
Alcañiz 1
cd
Tardío del Pilar
dd
Amarillo Calanda
ah
Rojo del Rito 5233
ai
Pigat
bc
Valentín
ci
Sudanell Blanco
di
Sudanell 2
ff
Bonet 5
gg
Binaced
gh
Rojo del Rito
619
Figure 3
56
58
92
63
51
Subgroup
1
64
Group 1
92
Subgroup 2
83
Subgroup 3
55
Subgroup 4
Group 2
90
0.48
0.36
0.24
0.12
Goiri
Paloro A
Andross
San Jaime
Jerónimo Ortiz
Maruja Perfección
Carson
Jerónimo Torres
Nuevo 2803
Calabacero Soto
Infanta Isabel
Jerónimo
Jerónimo de Alfaro
Calabacero Candelo
Calabacero Deleite
Calabacero Rincón
Selma
Calabacero Rancho
Everts
Carolyn
Klamt
Loadel
Halford
Gaume
Duraznillo
Paloro B
Sudanell Blanco
Sudanell 2
Jesca
Bonet 2
Bonet 3
Sudanell 1
Bonet 5
Corona
Miraflores Serapio
Manolito
Amarillo de Calanda
Tardío del Pilar
Alcañiz 1
Alcañiz 2
Jungerman
Zaragozano Rojo
Rojo Amarillo de Septiembre
Pigat
San Lorenzo
Andora
Rojo del Rito 5233
Valentín
Garau
Rojo del Rito
Borracho de Jarque
Bonet 4
Escolapio
Starn
Tambarria
Fraga
Campiel Rojo
Campiel Montes de Cierzo
Zaragozano Amarillo
Golden Queen
Gallur
Pigat Susagna
Benasque
Maluenda
Pomar 1
Calanda
Brasileño
Del Gorro
Ballejo
Pepita
Babygold 5
Amarillo Tardío
Fantasia
May Grand
Flavortop
Early Diamond
Armking
September Red
Flamekist
Ortiz
Redhaven
Paraguayo Sweet Cap
Sudanell 3
Cristalino
Montamar
Babygold 7
BlancoTardío
Babygold 6
Babygold 8
Binaced
Paraguayo Amarillo
Paraguayo Caspe
Paraguayo Villamayor
Paraguayo San Mateo
0.00
0.384
620
Rogers Coefficient
37
621
Figure 4
HUESCA (P1)
ZARAGOZA (P4)
LÉRIDA (P2)
NORTH (P5)
A
USA (P7)
TERUEL (P3)
B
MURCIA (P6)
0.83
622
0.87
0.92
Similarity Coefficient
623
38
0.96
1.00