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A multiplexed microsatellite fingerprinting set for hazelnut cultivar identificationM. Akin1, A. Nyberg2, J. Postman2, S. Mehlenbacher1 and N.V. Bassil2

1 Oregon State University, Department of Horticulture, Corvallis, OR 97331, USA2 USDA-ARS, National Clonal Germplasm Repository, Corvallis, OR 97333, USA

Eur. J. Hortic. Sci. 81(6), 327–338 | ISSN 1611-4426 print, 1611-4434 online | http://dx.doi.org/10.17660/eJHS.2016/81.6.6 | © ISHS 2016

Original articleGerman Society for Horticultural Science

IntroductionThe genus Corylus (Betulaceae) includes 11 species that

are native to temperate regions of the northern hemisphere extending from Japan, Korea, China, the Russian Far East to the Caucasus and Turkey (Kasapligil, 1972). The European hazelnut, Corylus avellana L., is the most economically im-portant with a worldwide production of around 872,000 t of in-shell nuts and a cultivated area of about 604,000 ha (aver-age 2008–2012) (FAOstat, 2016).

Hazelnut is one of the most important nuts in world-wide production following cashew, walnut, almond, chestnut and pistachio (FAOstat, 2016). The major hazelnut produc-ing countries are Turkey (598,158 t), Italy (104,577 t), USA (32,399 t), Azerbaijan (30,035 t) and Georgia (25,020 t) (av-

SummaryThe objective of this study was to develop a robust

and cost-effective fingerprinting set for hazelnuts using microsatellite markers, also known as simple sequence repeat (SSR) markers. Twenty SSRs containing repeat motifs of three or more nucleotides distributed throughout the hazelnut genome were screened on eight cultivars to assess polymorphism, allele size range, and ease of scoring. Six SSRs were discarded after genotyping 96 hazelnut samples either due to large allele bin widths and/or alleles that do not match the motifs, which complicates allele scoring. Fourteen polymorphic, easy-to-score SSRs were selected and amplified in a single multiplex. The 14-SSR multiplexed set generated the same alleles that were obtained when amplifying each SSR individually in the eight test accessions. SSR primer concentrations were then optimized to generate a clear signal for each locus. This 14-SSR fingerprinting set was used to genotype 102 hazelnut accessions from different origins. The fingerprinting set distinguished unique accessions mainly according to parentage and in some cases based on geographic origin. They identified each of the cultivars released from the Oregon State University breeding program and confirmed the parentage of six cultivars. Tools for DNA fingerprinting of clonally propagated horticultural crops like hazelnut are in demand and this multiplexed set constitutes a reliable, less-time consuming and cost-effective procedure for identity and parentage confirmation in hazelnut.

KeywordsCorylus avellana L., genetic resources, identity, markers, simple sequence repeats, trueness-to-type

Significance of this studyWhat is already known on this subject? • Microsatellite markers are available in hazelnut and

can distinguish hazelnut cultivars.

What are the new findings? • We found that microsatellite markers with a minimum

of three core repeats have fewer artifacts than the more abundant dinucleotide-containing markers. After evaluating 20 SSRs in hazelnut, we developed a DNA test that contains 14 such SSRs and that can be amplified in a single PCR reaction. This DNA test distinguished all unique hazelnut cultivars tested with the exception of clonal duplicates in the field or in tissue culture.

What is the expected impact on horticulture?• This DNA test provides hazelnut growers, nurserymen,

propagators, breeders, curators of collections and other scientists with an economical and reliable tool to confirm identity and parentage, detect propagation errors and enforce intellectual property.

erage 2008–2012) (FAOstat, 2016). Ninety percent of the production is processed. Hazelnuts are diploid (2n = 2x = 22), monoecious, dichogamous and wind-pollinated trees or shrubs with high genetic variability among individuals in populations. Cross-pollination is enforced due to sporophyt-ic self-incompatibility, and use of pollinizers is required for good yield in a hazelnut orchard (Mehlenbacher, 2014). Cul-tivars are highly heterozygous, and clonally propagated by layering, cutting, grafting, or micropropagation. Assessment of trueness-to-type by phenotypic observation is very diffi-cult and mistakes during the several steps of nursery plant propagation are costly. Therefore, developing a reliable DNA fingerprinting set for identity verification of hazelnuts would provide a crucial tool for verifying cultivar integrity in propa-gation systems and in hazelnut collections, as well as protec-tion of breeders’ rights,

In Corvallis, Oregon, the US Department of Agriculture (USDA), Agricultural Research Service (ARS), National Clon-al Germplasm Repository (NCGR) maintains the largest col-lection of Corylus in the world, with more than 800 hazelnut accessions representing different Corylus species (Bassil et al., 2013). The Oregon State University hazelnut breeding program is the largest program in the world and continues to acquire germplasm from hazelnut-growing regions of the world and release cultivars and pollinizers that are resis-tant to eastern filbert blight (Anisograma anomala (Peck) E.

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Table 1. List of 102 hazelnut individuals used in this study. Local inventory number at the NCGR and OSU collections, species, pedigree and origin are indicated.

Cultivar name Local number Species Pedigree OriginTissue culture plants

Barcelona C. avellana Chance seedling SpainDorris C. avellana OSU 309.074 × Delta Oregon, USADundee C. hybrid C. colurna × C. avellana Oregon, USAFelix C. avellana OSU 384.095 × Delta Oregon, USAJefferson C. avellana OSU 252.146 × OSU 414.062 Oregon, USALewisb C. avellana OSU 17.028 × Willamette Oregon, USAWepster C. avellana Tonda Pacifica × OSU 440.005 Oregon, USAYork C. avellana OSU 479.027 × OSU 504.065 Oregon, USAZeta C. avellana OSU 342.019 × Zimmerman Oregon, USA

NCGR field collectionAla-Kieri 187.001 C. avellana Selection FinlandAlbania 55 625.001 C. avellana Selection AlbaniaAlli 999.001 C. avellana Kaiserin Eugenie × wild European hazelnut EstoniaAnglais 481.001 C. avellana Selection UncertainArtellet 256.003 C. avellana Selection SpainAurea 126.001 C. avellana Selection with yellow foliage England, UKB 3 273.001 C. avellana Selection MacedoniaBarcelloner Zellernuss 331.001 C. avellana Selection England, UKBarcelonaa 36.001 C. avellana Chance seedling SpainBarr’s Zellernuss 333.001 C. avellana Selection England, UKBergeri 262.001 C. avellana Selection ItalyBrixnut 26.001 C. avellana Barcelona × Du Chilly Oregon, USABurgundy Lace 955.07 C. avellana OSU 562.034 × OSU 562.062 Oregon, USAButler 116.001 C. avellana Barcelona × Daviana Oregon, USACasina 28.001 C. avellana Selection Asturias, SpainClarka 705.001 C. avellana Tombul Ghiaghli × Willamette Oregon, USAContorta 50.001 C. avellana Selection with contorted stems and leaves England, UK Cosford 41.001 C. avellana Selection England, UK Cutleaf 18.001 C. avellana Selection with deeply dissected leaves England, UK Daviana 42.001 C. avellana Selection England, UK Dorris 890.001 C. avellana OSU 309.074 × Delta Oregon, USADu Chilly 232.001 C. avellana Selection (syn. Kentish Cob) Kent, UKDundee 165.001 C. hybrid C. colurna × C. avellana Oregon, USAEnnisa 11.001 C. avellana Barcelona × Daviana Washington, USAJefferson 894.001 C. avellana OSU 252.146 × OSU 414.062 Oregon, USAGamma 776.001 C. avellana Casina × VR 6-28 Oregon, USAGasaway 54.001 C. avellana Selection Washington, USAGema 23.001 C. avellana Barcelona × Du Chilly United States. WAGeorgian 759.010 955.04 C. avellana Selection Republic of GeorgiaGrand Traversea 559.001 C. hybrid Faroka (C. colurna × C. avellana)

× OSU 18.114 Michigan, USA

Gunslebener Zellernuss 382.001 C. avellana Selection GermanyGustav’s Zellernuss 206.001 C. avellana Selection GermanyHall’s Gianta 16.001 C. avellana Selection GermanyIannusa Racinante 368.001 C. avellana Selection Sicily, ItalyImperial de Trebizonde 81.001 C. avellana Selection TurkeyImperial de Trebizonde 484.001 C. avellana Selection TurkeyKadetten Zellernuss 323.001 C. avellana Selection GermanyLewis 633.001 C. avellana OSU 17.028 (Barcelona × Tombul Ghiaghli)

× WillametteOregon, USA

Montebelloa 17.001 C. avellana Selection ItalyMortarella 268.007 C. avellana Selection ItalyNegret 8.001 C. avellana Selection SpainNottinghama 297.001 C. avellana Selection England, UKNY 398 193.001 C. hybrid Rush × Red Lambert

(C. americana × C. avellana)New York, USA

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Cultivar name Local number Species Pedigree OriginNY 616 104.001 C. hybrid Rush × Barcelona

(C. americana × C. avellana) New York, USA

OSU 26.072 388.001 C. avellana Selection from seedlot B-122 from North Caucasus, Russia

Oregon, USA

OSU 54.039 88.001 C. avellana Selection, seeds collected in Turkey Oregon, USAOSU 495.045 427.001 C. avellana Selection, seeds from Russia Russian FederationOSU 556.011 707.001 C. avellana Selection, seeds from market in Istanbul Istanbul, TurkeyPalaz 265.002 C. avellana Selection TurkeyPayrone 458.001 C. avellana Selection Torino, ItalyPellicule Rouge 38.001 C. maxima Selection FrancePurple Aveline 832.001 C. maxima Selection FranceRatoli 344.001 C. avellana Selection SpainRote Zellernuss 13.001 C. avellana Selection NetherlandsSacajawea 859.001 C. avellana OSU 43.091 (self-pollination of

‘Montebello’?) × Sant PereOregon, USA

Sant Jaume 249.001 C. avellana Barcelona × Pinyolenc #2 SpainSimon 343.002 C. avellana Negret × Garrofi SpainTapparona di Mezzanego 750.001 C. avellana Selection Liguria, ItalyTombul Ghiaghli 55.001 C. avellana Selection TurkeyTonda Bianca 21.003 C. avellana Selection ItalyTonda di Giffoni 22.001 C. avellana Selection ItalyTonda Gentile delle Langhe 31.001 C. avellana Selection ItalyTonda Gentile delle Langhe 110.001 C. avellana Selection ItalyTonda Gentile delle Langhe 113.001 C. avellana Selection ItalyTonda Gentile delle Langhe 114.001 C. avellana Selection ItalyTonda Romana 5.001 C. avellana Selection ItalyWillamette 500.001 C. avellana Montebello × Compton Oregon, USAYamhill 738.001 C. avellana OSU 296.082 × VR 8-32 Oregon, USAYamhill 898.001 C. avellana OSU 296.082 × VR 8-32 Oregon, USAZeta 779.001 C. avellana OSU 342.019 × Zimmerman Oregon, USA

OSU field collectionDorrisb LB40.22 C. avellana OSU 309.074 × Delta Oregon, USADundeeb LB07.26.05 C. hybrid C. colurna × C. avellana Oregon, USAEpsilon LB11.35 C. avellana OSU 350.089 × Zimmerman Oregon, USAEta LB26.20 C. avellana OSU 581.039 × OSU 553.090 Oregon, USAFelix LB24.11 C. avellana OSU 384.095 × Delta Oregon, USAFusco Rubra 372.007 C. avellana Selection GermanyJeffersonb LB15.06 C. avellana OSU 252.146 × OSU 414.062 Oregon, USALewisb LB07.38 C. avellana OSU 17.028 (Barcelona × Tombul Ghiaghli)

× WillametteOregon, USA

McDonald LB22.07 C. avellana Tonda Pacifica × Santiam Oregon, USANewberg LB07.25a C. hybrid C. colurna × C. avellana Oregon, USAOSU 252.146 MP03.20 C. avellana OSU 41.083 × OSU 17.028 Oregon, USAOSU 408.040 LB07.34 C. avellana Selection Univ. of Minnesota,

USAOSU 414.062 MP03.07 C. avellana OSU 23.017 × VR11-27 Oregon, USAOSU 681.078 LB14.09 C. avellana Selection, seeds collected in Moscow,

RussiaMoscow, Russia

Pendula USDA Shop C. avellana Selection England, UKRed Dragon LB20.20 C. avellana OSU 487.055 × OSU 367.039 Oregon, USARed Majestic #1 LB15.02 C. avellana Selection GermanyRed Majestic #2 LB15.01 C. avellana Selection GermanyTheta LB27.11 C. avellana OSU 561.184 × Delta Oregon, USATonda Pacifica V04 C. avellana Tonda Gentile delle Langhe × OSU 23.024 Oregon, USAWepster LB23.04 C. avellana Tonda Pacifica × OSU 440.005 Oregon, USAYork LB22.04 C. avellana OSU 479.027 × OSU 504.065 Oregon, USAZetab LB11.40 C. avellana OSU 342.019 × Zimmerman Oregon, USA

a Test panel accessions.b Six hazelnut accessions not evaluated with the first 14-SSR fingerprinting set.

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Müller) with good annual production and desirable kernel qualities. A multiplexed DNA fingerprinting test that can be amplified in a single polymerase chain reaction (PCR) would provide a quick and economical method for identification and parentage confirmation of hazelnut accessions in the USDA collection and new cultivars from any breeding pro-gram, nursery, tissue culture lab or grower’s field.

Microsatellites or simple sequence repeats (SSRs) are tandemly repeated 1–6 bp sequence motifs that are random-ly distributed throughout the genome. SSRs are multi-allelic, co-dominant, highly polymorphic, relatively abundant in the genome, transferable to related species and genera, as well as reproducible between laboratories (Powell et al., 1996). These characteristics led to their extensive use in fingerprint-ing, paternity testing and identity certification. More than 700 polymorphic SSR markers were developed in C. avella-na (Bassil et al., 2005a, 2005b, 2013; Boccacci et al., 2005, 2015; Gürcan and Mehlenbacher, 2010a, 2010b; Gürcan et al., 2010a; Peterschmidt, 2013; Bhattarai, 2015). They have been used for linkage map construction (Bhattarai, 2015; Gürcan et al., 2010a; Mehlenbacher et al., 2006), quantita-tive trait locus (QTL) analysis (Beltramo et al., 2016), assess-ment of genetic relationships among cultivars (Bassil et al., 2013; Boccacci et al., 2006, 2008, 2013; Boccacci and Botta, 2010; Campa et al., 2011; Gökirmak et al., 2009; Gürcan et al., 2010b), and for identification and parentage confirmation (Bassil et al., 2009; Botta et al., 2005; Gökirmak et al., 2009; Sathuvalli and Mehlenbacher, 2012). Dinucleotide-contain-ing SSRs are the most abundant throughout the genome, but suffer from stuttering, split peaks and binning errors which lead to difficulties in unequivocal genotyping and genetic profile discrepancies among different laboratories (Baldoni et al., 2009; Testolin and Cipriani, 2010). Tri- and higher SSR repeats are also available in hazelnut and are easier to score and are preferred for automated fingerprinting.

The objective of this study was to develop a robust and cost-effective multiplexed fingerprinting set consisting of high core repeat SSRs (≥3 nucleotides), and to test them in a di-verse set of field-grown C. avellana accessions and some inter-specific hybrids from the USDA-ARS and OSU collections. We also used this set to confirm identity of in vitro cultures of nine commercially important cultivars or pollinizers by comparing their fingerprints to those obtained from field-grown trees.

Materials and methods

Plant materials and DNA extractionDNA was extracted from actively growing leaves of 93

field-planted (70 from the USDA-ARS and 23 from the OSU collection) and nine tissue culture (TC) grown hazelnut plants (Table 1) in spring 2015. Up to 50 mg of leaf tissue from each sample were frozen in liquid nitrogen and ho-mogenized with an MM 301 Mixer Mill (Retsch Internation-al, Haan, Germany). DNA was extracted according to the modified Puregene protocol (Qiagen Inc., Valencia, CA, USA) (Gilmore et al., 2011).

Microsatellite marker evaluationFourteen SSR primer pairs were first evaluated (Table 2)

in a test panel of eight diverse hazelnut accessions (Table 1) for polymorphism and ease of scoring indicated by lack of PCR artifacts (stuttering or split peaks). Each of these SSRs was amplified individually using the Type-it® Microsatellite PCR Kit (Qiagen, Inc., Valencia, CA, USA). Each reaction con-sisted of a 15 µL volume of 1× Type-It Multiplex PCR Master

Mix containing D2, D3 or D4 fluorescent dye labeled primers (WellRED Beckman Coulter, Inc., CA, USA) and 10.5 ng gen- omic DNA. The cycling protocol began with an initial dena-turation at 95°C for 5 min, followed by ten cycles of 30 sec at 95°C; 90 sec at 62°C, decreasing 1°C each cycle; and 30 sec at 72°C. PCR continued for 29 cycles of 30 sec at 95°C, 90 sec at 52°C, and 30 sec at 72°C. The protocol was terminated with a final elongation step at 60°C for 30 min. PCR success was confirmed by agarose gel electrophoresis and PCR products were separated by capillary electrophoresis using the Beck-man CEQ 8000 (Beckman Coulter, Inc.). Alleles were scored and visualized with the fragment analysis module of the CEQ 8000 software (Beckman Coulter, Inc.). Alleles were scored by fitting peaks into bins less than 1 nucleotide wide.

Each SSR was evaluated for presence of well separated alleles that form narrow peaks (bin widths ≤ 1) that match the motif and for amplification of a single locus as indicated by the presence of a maximum of two products (Supplemen-tary Information – Table S1). Preliminary analysis of these 14 SSRs (Table 2; Supplementary Information – Table S1) in 96 hazelnut accessions (Table 1) identified 6 SSRs that generated alleles with wide bins and/or whose consecutive alleles differed from expectation based on the repeat motif. These six SSRs were replaced with six other SSRs (Table 2) and the set was tested again in simplex and multiplex PCR as described above to confirm lack of primer interaction.

Fourteen polymorphic, easy to score SSRs were selected to meet the following criteria: no PCR artifacts (low to no stuttering, low to no split peaks); single locus (amplifying up to two products); and with alleles that form narrow peaks (bin widths < 1.4) and that differ according to SSR motif (Ta-ble 2). They were amplified in a single multiplex using the above PCR conditions. SSR primer concentrations were opti-mized in the eight hazelnut accession test panel to generate a clear signal for each locus and the optimal concentrations are shown in Table 2. The 14 SSRs were then amplified in mul-tiplex in the remaining 94 DNA samples using the optimized primer concentrations. Product separation, allele sizing and visualization were as described above.

Data analysisPowerMarker (Version 3.0) (Liu and Muse, 2004) was

used to calculate diversity parameters of the 14 SSRs including the number of alleles (A), observed heterozygosity (Ho), gene diversity or expected heterozygosity (He), and polymorphism information content (PIC). Ho is the frequency of heterozygous genotypes per locus and is calculated by dividing the number of heterozygous genotypes by the total number of genotypes at each locus; He is the probability that a randomly chosen in-dividual is heterozygous at a given locus; PIC is a measure of marker informativeness and useful for probability estimation of polymorphism between genotypes (Botstein et al., 1980). An estimate of the frequency of null alleles (r) based on het-erozygote deficiencies, was calculated as r=(He–Ho) / (1+He) with Excel® (Microsoft®) (Brookfield, 1996).

Cluster analysis of the data was performed using R (ver-sion 3.1.2; R Core Team, 2014), after installing the package ‘Poppr’ version 1.1.2 (Kamvar et al., 2014). The following packages and their libraries were also imported for use: Ape v3.1-4 (Paradis et al., 2004), Adegenet v1.4-2 (Jombart, 2008), and Pegas v 0.6 (Paradis, 2010). Trees were con-structed with the ‘aboot’ function. Parameters were Nei’s distance (Nei, 1972, 1978), Unweighted Pair Group Method with Arithmetic Mean (UPGMA), a sample of 5,000 bootstrap replicates, and a cutoff value of 75%.

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Parentage verificationCervus 3.0.6 (Marshall et al., 1998; Kalinowski et al., 2007,

2010) was used for parentage confirmation in six cultivars whose eight parents (Table 3) were also genotyped in this study. This program uses a likelihood-based approach to as-sign parentage combined with simulation of parentage anal-ysis to determine the confidence (95% = strict; or 80% = re-laxed) of parentage assignments. The genotypes of candidate parents are compared against the offspring’s genotype and are excluded as parents if a mismatch occurs at one or more loci. The natural logarithm of the overall likelihood ratio is termed the LOD score and indicates the ratio between the likelihood of parentage for an individual, relative to a ran-domly selected individual from the population. Another mea-sure, Delta, is a derivative of the LOD score, and can be also used as a criterion for assignment of parentage. Cervus sim-ulation parameters included: number of offspring, 10,000; number of candidates, 8; average candidate parent pairs per offspring, 28; rate of typing error, 0.01; relaxed confidence level, 80%; and strict confidence level, 95%. We conducted parent pair analysis with unknown parent sexes to confirm correct parent assignment when using this 14-SSR set.

Results and discussion

SSR screeningTwenty SSRs with repeat motifs ≥ 3 nucleotides that

were previously reported to be polymorphic and easy to score (Bhattarai, 2015; Peterschmidt, 2013; Sathuvalli and

Mehlenbacher, 2013) were evaluated in a diverse panel of eight accessions (Table 1) for ease of scoring determined by lack of artifacts (stuttering, split peaks) on the Beckman CEQ capillary electrophoresis platform. They were also evaluated for lack of primer interaction when amplified in multiplex PCR. Comparison of alleles generated when each of the 20 SSRs was amplified individually in the test panel as opposed to in multiplex PCR generated the same alleles, indicating no primer interaction.

Amplification of the first 14 SSR multiplex set (Table 2) in 96 hazelnut accessions (Table 1) allowed us to assess SSRs for the presence of well-separated alleles that form narrow peaks (bin widths ≤ 1) and size increments that match ex-pectation based on the motif. Six SSRs did not match this cri-terion (BR249, BR359, BR427, BR446, LG631 and LG 639) (Table 2; Supplemental Information – Table S1). Some of the alleles generated by LG639 had wide bins and consecutive alleles that did not differ by the tetranucleotide motif size (Supplemental Information – Table S1). For example, the 225 allele ranged from a minimum of 225.8 to 228.44 with a bin width of 2.64 bps (Supplemental Information – Table S1). At BR249 only two of the six alleles (302 and 296) differed by the expected 6 bp motif size; the 304 allele had a wide bin exceeding 2 bp; and the distance between the unique alleles varied and was less than 6 bp (Supplemental Information – Table S1). At BR427, the 315, 317 and 319 alleles differed by two bps instead of the expected motif size of three and the bin width for the 319 allele was 1.65 (Supplemental Informa-tion – Table S1). Six of the eight alleles amplified by BR359

Table 2. Twenty SSRs tested for fingerprinting in hazelnuts. The motif, size range, number of alleles, linkage group (LG) and primer concentrations (in mM) for the optimized multiplex set in addition to the references describing them.

Name Motif Size range (bp)

Number of alleles (A) LG Primer concentration

(mM) References

SSRs removed from the studyLG639 (ATGT)6 224-236 10 6 - Sathuvalli and

Mehlenbacher (2013)BR249 (AACAGA)5 287-305 7 10S - Peterschmidt (2013)BR427 (CCA)5 314-317 5 5S - Peterschmidt (2013)BR359 (TCT)5 387-402 13 4S, 4R - Peterschmidt (2013)LG631 (TCT)6 355-439 4 6 - Sathuvalli and

Mehlenbacher (2013)BR446 (CAA)5 155-164 4 11S, 11R - Peterschmidt (2013)

14 SSR MultiplexBR270 (CTG)6 90-102 5 1S 0.75 Peterschmidt (2013)BR322 (ACT)7 102-114 5 8S 0.375 Peterschmidt (2013)BR414 (AAT)6 116-164 10 9S, 9R 0.25 Peterschmidt (2013)GB949a (TGG)7 154-166 4 10S 3 Bhattarai (2015)GB950a (TGG)7 162-178 6 7S 1 Bhattarai (2015)BR438a (TCA)8 187-211 4 11S 0.25 Peterschmidt (2013)CAC-C008 (AAG)11(AAG)3 200-253 21 4 4 Bassil et al. (2013)BR259 (TCA)10 226-250 9 5S 2 Peterschmidt (2013)BR464 (ATC)7 274-292 5 3S 2 Peterschmidt (2013)GB875a (GGA)9 330-355 8 5S 3 Bhattarai (2015)GB673 (TCACCA)5 355-379 7 5S 2 Bhattarai (2015)LG688 (TTC)5 360-372 4 6b 1 Sathuvalli and

Mehlenbacher (2013)GB395a (CTC)6 377-408 7 2S, 2R 3 Bhattarai (2015)BR343a (TGC)6 393-407 3 1S,1R 1 Peterschmidt (2013)

a Six SSRs used to replace the six discarded SSRs.

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Supplementary information – Table S1. Allele IDs and corresponding size ranges of six SSRs discarded and 14 SSRs used in the multiplex. Wide bin widths (> 1.4) are underlined; allele IDs that do not change according to the motif length are in bold.

SSRs Allele ID Minimum Maximum Bin

width

Basepairs between alleles

Removed from the study

LG639

219 219.57 219.9 0.33 222 222.03 224.16 2.13 2.1225 225.8 228.44 2.64 1.6228 229.72 230.2 0.48 1.3231 231.98 232.24 0.26 1.8234 233.84 236.24 2.4 1.6237 237.44 237.89 0.45 1.2

BR249

284 284.77 284.89 0.12 287 287.16 287.26 0.1 2.3292 292.01 292.01 0 4.8296 296.02 296.02 0 4302 302.29 303.6 1.31 6.3304 304.11 306.13 2.02 0.5

BR427

305 305.53 306.54 1.01 312 312.12 312.84 0.72 5.58315 315.38 315.6 0.22 2.54317 316.67 317.07 0.4 1.07319 317.91 319.56 1.65 0.84

BR359

383 383.51 383.51 0 387 386.09 388.24 2.15 2.6389 390.02 390.02 0 1.8393 393.01 395.1 2.09 3397 396.93 397.97 1.04 1.8399 399.05 399.05 0 1.1401 400.98 401.88 0.9 1.9403 402.96 403.16 0.2 1.1

LG631432 432.31 433.81 1.5 435 435.07 439.84 4.77 1.3441 441.79 442.99 1.2 2

BR446

154 154.01 154.58 0.57 157 157.31 157.76 0.45 2.7160 160.5 160.77 0.27 2.7163 163.22 163.83 0.61 2.4166 166.43 166.43 0 2.6

14-SSR Multiplex

BR270

90 90.05 90.11 0.06 93 92.93 93.14 0.21 2.896 96.06 96.13 0.07 2.999 99.04 99.18 0.14 2.9

102 102.03 102.15 0.12 2.8

BR322

102 101.91 102.5 0.59 105 104.88 105.25 0.37 2.4108 107.98 108.36 0.38 2.7111 111.22 111.33 0.11 2.9114 114.47 114.49 0.02 3.1

BR414

116 115.93 115.96 0.03 122 121.96 122.31 0.35 6125 125.05 125.45 0.4 2.7134 134.55 134.8 0.25 9.1137 137.63 137.77 0.14 2.8140 140.76 140.94 0.18 3146 147.05 147.2 0.15 6.1164 163.94 163.94 0 16.7

GB949

154 154.24 154.5 0.26 157 157.63 157.71 0.08 3.1160 160.56 160.85 0.29 2.8163 163.79 163.96 0.17 2.9166 166.93 167.2 0.27 3

GB950

162 162.18 162.45 0.27 165 165.22 165.58 0.36 2.8168 168.41 168.72 0.31 2.8171 171.56 171.85 0.29 2.8178 178.17 178.17 0 6.3

BR438

187 187.36 187.44 0.08 197 197.28 197.7 0.42 9.8199 199.23 199.75 0.52 1.5201 201.42 201.72 0.3 1.7203 203.72 204.57 0.85 2211 211.6 211.66 0.06 7

CAC C008

200 200.78 201.24 0.46 203 203.67 203.67 0 2.4209 209.37 209.76 0.39 5.7212 212.21 212.32 0.11 2.5218 217.93 218.38 0.45 5.6221 220.88 221.06 0.18 2.5241 241.37 241.86 0.49 20.3244 244.44 244.54 0.1 2.6253 253.17 253.17 0 8.6

BR259

226 226.01 226.27 0.26 229 229.06 229.21 0.15 2.8232 232.28 232.28 0 3.1235 234.96 235.29 0.33 2.7238 237.86 238.11 0.25 2.6241 240.96 241.18 0.22 2.8244 244.01 244.23 0.22 2.8247 247.02 247.18 0.16 2.8250 249.95 250.11 0.16 2.8

BR464

274 274.27 274.49 0.22 280 280.02 280.56 0.54 5.5283 283.22 283.22 0 2.7286 285.97 286.38 0.41 2.8292 291.93 292.34 0.41 5.6

GB875

330 330.89 330.9 0.01 334 334.23 334.24 0.01 3.3336 336.73 337.09 0.36 2.5340 340.07 340.18 0.11 3343 342.99 343.14 0.15 2.8346 345.85 346.09 0.24 2.7349 348.8 349.02 0.22 2.7352 352.62 352.62 0 3.6355 354.62 355.69 1.07 2

GB673

355 355.36 355.79 0.43 367 367.11 367.61 0.5 11.3370 370.34 370.54 0.2 2.7373 373.2 373.6 0.4 2.7376 376.32 376.32 0 2.7379 379.15 379.52 0.37 2.8

LG688

360 360.47 360.73 0.26 363 363.27 363.63 0.36 2.5366 367.18 367.61 0.43 3.6369 369.39 370.21 0.82 1.8372 372.89 373.07 0.18 2.7

GB395

377 377.11 377.42 0.31 380 380.25 380.66 0.41 2.8383 383.15 383.52 0.37 2.5386 386.39 386.78 0.39 2.9389 389.38 389.83 0.45 2.6395 395.34 396.66 1.32 5.5398 398.88 398.88 0 2.2404 404.32 404.32 0 5.4408 408.7 408.7 0 4.4

BR343

393 392.55 392.97 0.42 396 395.57 395.96 0.39 2.6399 398.72 398.89 0.17 2.8402 401.38 402.23 0.85 2.5407 407.7 407.73 0.03 5.5

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Tabl

e 3.

14-

SSR

finge

rpri

nts o

f six

haz

elnu

t cul

tivar

s and

thei

r eig

ht p

aren

ts. B

lank

cel

ls in

dica

te in

abili

ty to

dis

tingu

ish

betw

een

null

and

hom

ozyg

ous a

llele

s at

that

locu

s. Th

e ac

cess

ion

in b

old

font

is th

e pr

ogen

y of

the

two

pare

nts i

n ea

ch g

roup

.

Acce

ssion

sBR

270

BR27

0BR

322

BR32

2BR

414

BR41

4GB

949

GB94

9GB

950

GB95

0CA

C-C0

08CA

C-C0

08GB

875

GB87

5Ba

rcelon

a93

105

108

122

125

154

160

165

171

200

218

346

346

Du C

hilly

9399

105

122

134

154

160

165

168

200

218

349

349

Brixn

ut93

10

5

122

125

154

154

165

171

200

218

346

349

Gem

93

105

108

122

125

154

160

165

171

200

218

346

349

Barce

lona

93

105

108

122

125

154

160

165

171

200

218

346

Da

viana

9399

105

108

125

160

162

168

200

218

346

349

Enni

s93

10

510

812

212

516

0

162

171

200

218

346

349

Butle

r93

10

510

812

512

515

416

016

216

521

821

834

634

6To

mbul

Ghiag

hli99

10

510

812

212

516

016

316

5

200

209

346

349

Willa

mette

9399

108

122

125

154

160

165

168

218

221

346

349

Clar

k99

10

510

812

212

516

016

016

5

200

218

346

346

OSU

252.1

4693

9910

510

812

212

515

416

016

516

820

921

834

634

9OS

U 41

4.062

9310

512

212

515

416

516

820

924

134

6

Jeffe

rson

93

105

12

212

215

4

168

168

209

209

346

Ac

cess

ions

GB67

3FGB

673F

BR43

8BR

438

BR25

9aBR

259a

BR46

4BR

464

LG68

8LG

688

GB39

5aGB

395a

BR34

3BR

343

Barce

lona

355

379

197

199

226

244

280

286

363

369

380

383

396

Du

Chil

ly35

519

920

122

623

828

028

636

636

938

0nu

ll39

640

2Br

ixnut

355

19

920

122

624

428

028

636

336

638

3nu

ll39

640

2Ge

m35

537

919

719

922

622

628

028

036

936

938

3nu

ll39

640

2Ba

rcelon

a35

537

919

719

922

624

428

028

636

336

938

038

339

6

Davia

na35

537

319

923

5nu

ll28

636

938

040

2

Enni

s35

535

519

719

924

4nu

ll28

028

636

336

938

0

396

402

Butle

r37

337

919

9

226

235

286

36

9

380

39

640

2To

mbul

Ghiag

hli35

5

199

201

250

235

280

286

369

37

738

339

6

Willa

mette

355

373

197

199

235

244

280

369

383

386

393

396

Clar

k35

537

319

919

923

525

028

028

636

9

383

383

396

OS

U 25

2.146

355

373

197

199

235

250

280

286

369

38

038

939

640

2OS

U 41

4.062

355

199

244

280

369

377

383

396

402

Jeffe

rson

355

373

199

23

524

428

0

369

37

738

039

640

2

334 E u r o p e a n J o u r n a l o f H o r t i c u l t u r a l S c i e n c e

Akin et al. | A multiplexed microsatellite fingerprinting set for hazelnut cultivar identification

were two base pairs apart and allele widths of 387 and 393 > 2.0 bps (Supplemental Information – Table S1). At LG631, the 432 and 441 alleles were easy to score but alleles that ranged from 435.07 to 439.84 were continuous and could not be clearly scored. BR446 amplified more than two alleles in many accessions and was difficult to score consistently because of split peaks. These six SSRs were subsequently re-placed with the following six SSRs: BR343, BR438, GB395, GB875, GB949, and GB950 (Table 2). After again confirming

that primer interaction did not occur between any of the SSRs in this new set of 14 SSRs, primer concentrations were optimized to yield a clear signal (Figure 1) and it was used to genotype all of the hazelnut accessions included in this study.

Microsatellite marker characteristicsEach of the 11 linkage groups (Bhattarai, 2015; Gürcan

et al., 2010a; Mehlenbacher et al., 2006) was represented by one SSR in these 14 SSRs except for LG1 with two SSRs and

Table 4. Diversity parameters of 14 single-locus hazelnut SSRs used in multiplex. Allele number (A), observed heterozygosity (Ho), expected heterozygosity (He) or gene diversity, polymorphism information content (PIC ), and frequency of null alleles in the 87 hazelnuts evaluated (r_ALL) and as calculated in Cervus in the 14 cultivars and parents subjected to parentage analysis with this software (r_Cervus). SSRs with the highest estimates of null allele frequency calculated with Cervus are in bold.

Marker Allele number(A)

Heterozygosity(Ho)

Gene diversity(He)

PIC r_ALL r_Cervus

BR270 5 0.48 0.57 0.48 0.057 0.233BR322 5 0.55 0.61 0.56 0.037 -0.148BR414 7 0.63 0.59 0.53 -0.025 -0.196GB949 5 0.44 0.57 0.51 0.083 0.025GB950 5 0.63 0.68 0.64 0.030 -0.087BR438 6 0.48 0.45 0.41 -0.021 -0.152CAC-C008 9 0.70 0.80 0.77 0.056 -0.114BR259 9 0.72 0.84 0.82 0.065 0.043BR464 5 0.55 0.54 0.46 -0.006 -0.077GB875 8 0.67 0.68 0.63 0.006 -0.109GB673 6 0.75 0.67 0.63 -0.048 -0.078LG688 5 0.61 0.61 0.57 0.000 0.044GB395 9 0.64 0.79 0.76 0.084 0.166BR343 5 0.66 0.59 0.52 -0.044 -0.189Mean 6.36 0.61 0.64 0.59

9

FIGURE 1. Electropherograms of 14-SSR set in ‘Gem’ and ‘Dundee’ based on capillary electrophoresis with the Beckman CEQ 8000. The name of each SSR is listed above the alleles whose sizes are given in base pairs. Blue, green and black peaks indicate the SSR primers were labeled with D4, D3 and D2, respectively.

Figure 1. Electropherograms of 14-SSR set in ‘Gem’ and ‘Dundee’ based on capillary electrophoresis with the Beckman CEQ 8000. The name of each SSR is listed above the alleles whose sizes are given in base pairs. Blue, green and black peaks indicate the SSR primers were labeled with D4, D3 and D2, respectively.

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LG5 with three SSRs (Table 2). On LG1, BR 270 mapped at po-sition 62.2 cM, while BR343 was at 137.6 cM, and thus were distant from each other (Peterschmidt, 2013). The S-locus controls pollen-stigma incompatibility and is placed on LG5 where three of our SSRs were located: GB875 (0 cM), BR259 (64.9 cM), and GB673 (88.2 cM) (Bhattarai, 2015; Mehlen-bacher, 2014). LG688 is located on LG6, where the ‘Gasaway’ eastern filbert blight resistance was mapped (Sathuvalli and Mehlenbacher, 2013). This fingerprinting set contains two markers that are linked to two important traits in hazelnut: incompatibility (BR259) and eastern filbert blight resistance (LG688). These two SSRs will be evaluated in the future for marker assisted selection for these traits (Bhattarai, 2015).

The number of alleles per locus ranged from five in BR270, BR322, GB949, GB950, BR464 and LG688 to nine at BR259, CAC-C008 and GB395, with an average of 6.36 (Table 4). The PIC values ranged from 0.41 to 0.81 with an average of 0.59. The most polymorphic loci were BR259, CAC-C008 and GB395 with PIC values of 0.82, 0.77 and 0.76, respective-ly. The least polymorphic locus was BR438 with a PIC value of 0.41. The observed heterozygosity (Ho) for individual loci ranged from 0.44 to 0.75 and averaged 0.61, while expected heterozygosity (He) ranged from 0.45 to 0.84 and averaged 0.64 (Table 4). The number of alleles reported for CAC-C008

by Bassil et al. (2013) was higher than that observed in the current study (21 versus 9 alleles). The larger number of al-leles is not surprising given that Bassil et al. (2013) examined 11 hazelnut species while the current study consisted most-ly of C. avellana genotypes and four hybrid accessions. The estimated frequency of null alleles as an excess of heterozy-gotes was low (< 10%) and ranged from -0.048 at GB673 to 0.084 at GB395 (Table 4). Lack of amplification indicating the possibility of homozygotes for a null allele was not observed at any of the SSR loci selected, as expected since these SSRs were preselected based on universal amplification, polymor-phism and ease of scoring in previous studies. The genetic diversity parameters for the remaining 13 SSRs were com-parable to previous reports (Bhattarai, 2015; Peterschmidt, 2013; Sathuvalli and Mehlenbacher, 2013).

Cluster analysisUPGMA cluster analysis based on Nei’s genetic distance

identified 81 unique genotypes among the 93 field-grown accessions and the nine TC-grown cultivars (Figure 2). ‘Con-torta’ was excluded from the UPGMA cluster analysis because it amplified three alleles at GB950. Strong bootstrap support (>99%, not shown) was observed for all sets of cultivars with identical genetic profiles such (e.g., TC versus field-grown

10

FIGURE 2. UPGMA cluster analysis of 102 hazelnut individuals using the 14-SSR multiplex.

Figure 2. UPGMA cluster analysis of 102 hazelnut individuals using the 14-SSR multiplex.

336 E u r o p e a n J o u r n a l o f H o r t i c u l t u r a l S c i e n c e

Akin et al. | A multiplexed microsatellite fingerprinting set for hazelnut cultivar identification

trees) irrespective of source location (USDA or OSU collec-tions). Three sets of trees with the same name but obtained by the NCGR from different sources had the same profile and included four trees of ‘Tonda Gentile delle Langhe’ and two trees each of ‘Yamhill’ and ‘Imperiale de Trebizonde’ (Figure 2). Genetic profiles of ‘Dorris’, ‘Dundee’, ‘Lewis’, ‘Jefferson’ and ‘Zeta’ from the OSU collection were identical to those from the NCGR collection (Figure 2). Fingerprints of each of the nine tissue-culture grown plants (Table 1) were identical to those of field-grown trees of the same cultivar (Figure 2). Therefore, these TC plants appear true-to-type and this fingerprinting set is useful for detection of micropropagation error.

Two trees of ‘Red Majestic’ had different alleles at nine (BR414, GB949, GB950, CAC-C008, GB673, BR259, BR464, LG688 and GB395) of the fourteen SSRs, indicating the pres-ence of multiple genotypes for this cultivar in the market. Genotypes of the French cultivars ‘Purple Aveline’ and ‘Pel-licule Rouge’ were identical, as previously found by Gökir-mak et al. (2009) based on 21 SSRs. Both of these cultivars have purple pellicles. However, ‘Purple Aveline’ has dark red leaves while the leaves of ‘Pellicule Rouge’ are green with a trace of red pigment. Differences in pellicle and leaf color are attributed to mutation (Gökirmak et al., 2009).

In the UPGMA dendrogram (Figure 2), the cultivars and selections mostly grouped according to pedigree and based on geographical origin into five groups (Spanish-Italian, Turkish, English, German and Diverse) as previously ob-served by Gökirmak et al. (2009) and Gürcan et al. (2010a). The Spanish-Italian Group contained most of the OSU releas-es that grouped with one of their parents. In the TGDL sub-group, ‘Tonda Pacifica’ clustered with its parent TGDL and its offspring ‘Wepster’ and ‘McDonald’. A ‘Casina’-‘Montebello’ subgroup contained other Italian and Spanish cultivars in addition to OSU releases that have either one or both of these cultivars in their background including ‘Dorris’, ‘Felix’, ‘Gam-ma’, ‘York’, ‘Sacajawea’ and ‘Zeta’. ‘Clark’ and ‘Lewis’ grouped with ‘Tombul Ghiaghli’, which is a parent and grandparent, respectively, and close to the other parent ‘Willamette’ in the ‘Willamette’ subgroup while the ‘Barcelona’ subgroup con-tained important grower selections from the Pacific North-west of the US that are offspring of this important Spanish cultivar and include ‘Brixnut’, ‘Ennis’ and ‘Gem’. The polliniz-er ‘Epsilon’ clustered close to its grandparent ‘Tonda Roma-na’. ‘Yamhill’ and ‘Eta’ grouped together as they are descend-ed from VR 8-32 while ‘Jefferson’ clustered with its pollen parent ‘OSU 414.062’.

The Turkish Group contained the Turkish cultivar ‘Palaz’ and OSU 54.039, a selection from a Turkish seedlot. The En-glish Group contained the English cultivars ‘Du Chilly’, ‘Cos-ford’, ‘Daviana’ and its offspring ‘Butler’ in addition to two Italian cultivars, ‘Tapparona di Mezzanego’ and ‘Tonda Bianca’. The pollinizer ‘Theta’ grouped with its grandparent ‘Gasaway’, one of the major sources of eastern filbert blight resistance in most cultivars released from the OSU breeding program to date. The German Group included many German cultivars such as the ‘Zellernuss’ series and the two genotypes of ‘Red Majestic’. The ornamental ‘Burgundy Lace’ released by OSU and that combines the cutleaf trait with red colored leaves and eastern filbert blight resistance grouped at high bootstrap support (89%) with its grandparent ‘Cutleaf’ that originat-ed in England and is the source of the cutleaf trait. A Diverse Group contained a mix of cultivars from different geographi-cal origins in addition to the two C. colurna × C. avellana hy-brids, ‘Newberg’ and ‘Grand Traverse’, as well as one of the two C. americana × C. avellana hybrids, ‘NY398’. The red-leaved

ornamental hazelnut cultivar ‘Red Dragon’ with the contorted habit was also found in this diverse group.

Parentage analysisUsing the maximum likelihood approach implemented in

Cervus, correct parent pairs were identified for five (‘Brix-nut’, ‘Butler’, ‘Clark’, ‘Jefferson’ and ‘Ennis’) of the six cultivars tested at 95% confidence level. While ‘Barcelona’ and ‘Du Chilly’ were also found to have the highest likelihood as par-ents of ‘Gem’, the confidence level was lower than 80%, most likely due to null alleles at GB395 and possibly at BR270 (Ta-ble 3). A single mismatch was found between the ‘Du Chilly’ parent and ‘Brixnut’ and ‘Gem’ and between ‘Daviana’ and its offspring ‘Ennis’. The number of mismatches indicates the number of loci where the offspring and the candidate par-ent have no shared alleles. Visual comparison of genotypes between parents and the six offspring cultivars (Table 3) confirmed Mendelian inheritance and the presence of a null allele leading to a mismatch between ‘Daviana’ and ‘Ennis’ at BR259 and between ‘Du Chilly’ and its two offspring ‘Brixnut’ and ‘Gem’ at GB395. When calculated across all the tested ac-cessions in this study, null allele frequencies at BR259 and GB395 were 0.065 and 0.084, respectively. However, when calculated by Cervus only in the six cultivars and eight can-didate parents, null allele frequency for BR259 was lower at 0.043 and that of GB395 was higher at 0.166 than that found across the 84 unique accessions (Table 4). In these 14 culti-vars, null allele frequencies were highest at BR270 (0.233) and GB395 (0.166) indicating dependence of null allele oc-currence on the accessions used, as expected since it is esti-mated based on excess of heterozygotes in these accessions. According to Dakin and Avise (2004), computer simulations indicated that microsatellite null alleles at frequencies typi-cally reported in 233 articles (almost always < 0.4 and usual-ly < 0.2) are unlikely to affect genetic parentage assessments. They are indirect estimates and indicate the possible pres-ence of null alleles. They must be confirmed by sequencing and genetic parentage analysis in family groups. The pres-ence of null alleles indicates that at least one of the primers was developed in a variable region, not surprising given the high polymorphism of hazelnut. The development of alterna-tive primers in a more conserved region flanking the locus is possible and can prevent null alleles. However, since none of the SSRs resulted in alleles that were homozygotes for null alleles indicated by lack of amplification, and the overall al-lele frequency estimator was <0.2, we recommend including all of them in the DNA test.

During allele frequency analysis, Cervus calculated the combined non-exclusion probabilities across all loci. The average probability of not excluding a single randomly-cho-sen unrelated individual from parentage at one or more loci was low (3.4E-4) for the parent pair analyses at these 14 loci. Furthermore, the probability of identity (PI) defined as the probability of two independent samples having the identical genotype, using all 14 microsatellites, was as low as 1.0E-8. The probability of identity when related individuals are in-cluded in the samples (PISibs) was also low at 2.3E-4. These measures indicate a high level of informativeness of this 14 SSR set to identify hazelnut accessions and determine their parentage even if closely related.

ConclusionThis fingerprinting DNA test of 14 multiplexed SSRs from

all 11 hazelnut linkage groups developed in this study is a re-liable and cost-effective method for confirming identity and

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parentage in hazelnut. This test will be useful for breeders, germplasm collection curators, propagators and growers for verification of trueness-to-type, and to facilitate comparison of accessions from different germplasm collections and iden-tify possible duplications and discrepancies. Use of this set in genetic diversity assessment can assist in choosing diverse parents in making new crosses in heterozygous hazelnut where inbreeding depression is of concern and necessitates selection of unrelated parents.

AcknowledgmentsWe thank Gehendra Bhattarai for providing hazelnut

SSR information, and Jason Zurn for technical assistance and training in data analysis using R. We acknowledge funding from a Higher Education Scholarship from the government of Turkey and from the USDA-ARS CRIS number 2072-21000-044-00D for this research project.

ReferencesBaldoni, L., Cultrera, N., Mariotti, R., Ricciolini, C., Arcioni, S., Vendramin, G., Buonamici, A., Porceddu, A., Sarri, V., Ojeda, M., et al. (2009). A consensus list of microsatellite markers for olive genotyping. Mol. Breed. 24, 213–231. https://doi.org/10.1007/s11032-009-9285-8.

Bassil, N.V., Botta, R., and Mehlenbacher, S.A. (2005a). Microsatellite markers in hazelnut: isolation, characterization and cross-species amplification. J. Am. Soc. Hortic. Sci. 130, 543–549.

Bassil, N.V., Botta, R., and Mehlenbacher, S.A. (2005b). Additional microsatellite markers of the European hazelnut. Acta Hortic. 686, 105–110. https://doi.org/10.17660/ActaHortic.2005.686.13.

Bassil, N.V., Hummer, K., Botu, M., and Sezer, A. (2009). SSR fingerprinting panel verifies identities of clones in backup hazelnut collection of USDA genebank. Acta Hortic. 845, 95–102. https://doi.org/10.17660/actahortic.2009.845.9

Bassil, N.V., Boccacci, P., Botta, R., Postman, J., and Mehlenbacher, S.A. (2013). Nuclear and chloroplast microsatellite markers to assess genetic diversity and evolution in hazelnut species, hybrids and cultivars. Genet. Resources Crop Evol. 60, 543–568. https://doi.org/10.1007/s10722-012-9857-z.

Beltramo, C., Valentini, N., Portis, E., Torello Marinoni, D., Boccacci, P., Sandoval Prando, M.A., and Botta, R. (2016). Genetic mapping and QTL analysis in European hazelnut (Corylus avellana L.). Mol. Breed. 36, 1–17. https://doi.org/10.1007/s11032-016-0450-6.

Bhattarai, G. (2015). Microsatellite marker development, characterization and mapping in European hazelnut (Corylus avellana L.), and investigation of novel sources of eastern filbert blight resistance in Corylus. Dissertation, Oregon State University, Corvallis, USA.

Boccacci, P., Akkak, A., Bassil, N.V., Mehlenbacher, S.A., and Botta, R. (2005). Characterization and evaluation of microsatellite loci in European hazelnut (Corylus avellana L.) and their transferability to other Corylus species. Molec. Ecol. Notes 5, 934–937. https://doi.org/10.1111/j.1471-8286.2005.01121.x.

Boccacci, P., Botta, R., and Akkak, A. (2006). DNA typing and genetic relations among European hazelnut (Corylus avellana L.) cultivars using microsatellite markers. Genome 49, 598–611. https://doi.org/10.1139/G06-017.

Boccacci, P., Rovira, M., and Botta, R. (2008). Genetic diversity of hazelnut (Corylus avellana L.) germplasm in northeastern Spain. HortScience 43, 667–672.

Boccacci, P., Aramini, M., Valentini, N., Bacchetta, L., Rovira, M., Drogoudi, P., Silva, A.P., Solar, A., Calizzano, F., Erdoğan, V. et al. (2013). Molecular and morphological diversity of on-farm hazelnut

(Corylus avellana L.) landraces from southern Europe and their role in the origin and diffusion of cultivated germplasm. Tree Genetics & Genomes 9, 1465–1480. https://doi.org/10.1007/s11295-013-0651-7.

Boccacci, P., Beltramo, C., Sandoval Prando, M.A., Lembo, A., Sartor, C., Mehlenbacher, S.A., Botta, R., and Torello Marinoni, D. (2015). In silico mining, characterization and cross-species transferability of EST-SSR markers for European hazelnut (Corylus avellana L.). Mol. Breed. 35, 1–14. https://doi.org/10.1007/s11032-015-0195-7.

Boccacci, P., and Botta, R. (2010). Microsatellite variability and genetic structure in hazelnut (Corylus avellana L.) cultivars from different growing regions. Scientia Hortic. 124, 128–133. https://doi.org/10.1016/j.scienta.2009.12.015.

Botstein, D., White, R.L., Skolnick, M., and Davis, R.W. (1980). Construction of a genetic linkage map in man using restriction fragment length polymorphisms. American Journal of Human Genetics 32, 314–331.

Botta, R., Akkak, A., and Boccacci, P. (2005). DNA-typing of hazelnut: a universal methodology for describing cultivars and evaluating genetic relatedness. Acta Hortic. 686, 117–124. https://doi.org/10.17660/ActaHortic.2005.686.15.

Brookfield, J.F.Y. (1996). A simple new method for estimating null allele frequency from heterozygote deficiency. Mol. Ecol. 5, 453–455. https://doi.org/10.1111/j.1365-294X.1996.tb00336.x.

Campa, A., Trabanco, N., Pérez-Vega, E., Rovira, M., and Ferreira, J.J. (2011). Genetic relationship between cultivated and wild hazelnuts (Corylus avellana L.) collected in northern Spain. Plant Breeding 130, 360–366. https://doi.org/10.1111/j.1439-0523.2010.01835.x.

Dakin, E.E., and Avise, J.C. (2004). Microsatellite null alleles in parentage analysis. Heredity 93, 504–509. https://doi.org/10.1038/sj.hdy.6800545.

FAOstat (2016). Agriculture data. http://faostat3.fao.org/home/index.html (accessed May 25, 2016).

Gilmore, B.S., Bassil, N.V., and Hummer, K.E. (2011). DNA extraction protocols from dormant buds of twelve woody plant genera. J. Amer. Pom. Soc. 65, 201–207.

Gökirmak, T., Mehlenbacher, S.A., and Bassil, N.V. (2009). Characterization of European hazelnut (Corylus avellana) cultivars using SSR markers Genet. Resour. Crop Ev. 56, 147–172.

Gürcan, K., and Mehlenbacher, S.A. (2010a). Development of microsatellite marker loci for European hazelnut (Corylus avellana L.) from ISSR fragments Mol. Breed. 26, 551–559. https://doi.org/10.1007/s11032-010-9464-7.

Gürcan, K., and Mehlenbacher, S.A. (2010b). Transferability of microsatellite markers in the Betulaceae. J. Amer. Soc. Hortic. Sci. 135, 159–173.

Gürcan, K., Mehlenbacher, S.A., Botta, R., and Boccacci, P. (2010a). Development, characterization, segregation, and mapping of microsatellite markers for European hazelnut (Corylus avellana L.) from enriched genomic libraries and usefulness in genetic diversity studies. Tree Genetics and Genomes 6, 513–531. https://doi.org/10.1007/s11295-010-0269-y.

Gürcan, K., Mehlenbacher, S.A., and Erdogan, V. (2010b). Genetic diversity in hazelnut cultivars from Black Sea countries assessed using SSR markers. Plant Breeding 129, 422–434. https://doi.org/10.1111/j.1439-0523.2009.01753.x.

Jombart, T. (2008). adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics 24, 1403–1405. https://doi.org/10.1093/bioinformatics/btn129.

Kalinowski, S.T., Taper, M.L., and Marshall, T.C. (2007). Revising how the computer program Cervus accommodates genotyping error

338 E u r o p e a n J o u r n a l o f H o r t i c u l t u r a l S c i e n c e

Akin et al. | A multiplexed microsatellite fingerprinting set for hazelnut cultivar identification

increases success in paternity assignment. Mol. Ecol. 16, 1099–1106. https://doi.org/10.1111/j.1365-294X.2007.03089.x.

Kalinowski, S.T., Taper, M.L., and Marshall, T.C. (2010). Corrigendum. Mol. Ecol. 19, 1512–1512. https://doi.org/10.1111/j.1365-294X.2010.04544.x.

Kamvar, Z.N., Tabima, J.F., and Grünwald, N.J. (2014). Poppr: an R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction. PeerJ 2, e281. https://doi.org/10.7717/peerj.281.

Kasapligil, B. (1972). A bibliography on Corylus (Betulaceae) with annotations. Ann. Rep. North Nut Grow. Assoc. 63, 107–162.

Liu, K., and Muse, S. (2004). PowerMarker: new genetic data analysis software. Version 3.0. http://www.powermarker.net.

Marshall, T.C., Slate, J., Kruuk, L.E.B., and Pemberton, J.M. (1998). Statistical confidence for likelihood-based paternity inference in natural populations. Mol. Ecol. 7, 639–655. https://doi.org/10.1046/j.1365-294x.1998.00374.x.

Mehlenbacher, S.A. (2014). Geographic distribution of incompatibility alleles in cultivars and selections of European hazelnut. J. Amer. Soc. Hortic. Sci. 139, 191–212.

Mehlenbacher, S.A., Brown, R.N., Nouhra, E.R., Gökirmak, T., Bassil, N.V., and Kubisiak, T.L. (2006). A genetic linkage map for hazelnut (Corylus avellana L.) based on RAPD and SSR markers. Genome 49, 122–133.

Nei, M. (1972). Genetic distance between populations. The American Naturalist 106, 283–292. https://doi.org/10.1086/282771.

Nei, M. (1978). Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics 89, 583–590.

Paradis, E. (2010). pegas: an R package for population genetics with an integrated–modular approach. Bioinformatics 26, 419–420. https://doi.org/10.1093/bioinformatics/btp696.

Paradis, E., Claude, J., and Strimmer, K. (2004). APE: Analyses of phylogenetics and evolution in R language. Bioinformatics 20, 289–290. https://doi.org/10.1093/bioinformatics/btg412.

Peterschmidt, B. (2013). DNA markers and characterization of novel sources of eastern filbert blight resistance in European hazelnut (Corylus avellana L.). Dissertation, Oregon State University, Corvallis, USA.

Powell, W., Machray, G.C., and Provan, J. (1996). Polymorphism revealed by simple sequence repeats. Trends in Plant Science 1, 215–222. https://doi.org/10.1016/S1360-1385(96)86898-0.

R Core Team (2014). R: A language and environment for statistical computing (Vienna, Austria: R Foundation for Statistical Computing), http://www.R-project.org/.

Sathuvalli, V.R., and Mehlenbacher, S.A. (2012). Characterization of American hazelnut (Corylus americana) accessions and Corylus americana × Corylus avellana hybrids using microsatellite markers. Genetic Resources and Crop Evolution 59, 1055–1075. https://doi.org/10.1007/s10722-011-9743-0.

Sathuvalli, V.R., and Mehlenbacher, S.A. (2013). De novo sequencing of hazelnut bacterial artificial chromosomes (BACs) using multiplex Illumina sequencing and targeted marker development for eastern filbert blight resistance. Tree Genetics & Genomes 9, 1109–1118. https://doi.org/10.1007/s11295-013-0626-8.

Testolin, R., and Cipriani, G. (2010). Molecular markers for germplasm identification and characterization. Acta Hortic. 859, 59–72. https://doi.org/10.17660/ActaHortic.2010.859.5.

Received: Sep. 20, 2016Accepted: Nov. 21, 2016

Addresses of authors: Meleksen Akin1, April Nyberg2, Joseph Postman2, Shawn Mehlenbacher1 and Nahla V. Bassil2,*1 Oregon State University, Department of Horticulture, ALS 4017, Corvallis, OR 97331, USA2 USDA-ARS, National Clonal Germplasm Repository, 33447 Peoria Rd, Corvallis, OR 97333, USA* Corresponding author; E-mail: nahla.bassil@ars.usda.gov

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