ORIGINAL PAPER

Mapping quantitative trait loci associated with blush in peach[Prunus persica (L.) Batsch]

Terrence J. Frett & Gregory L. Reighard &

William R. Okie & Ksenija Gasic

Received: 17 January 2013 /Revised: 27 August 2013 /Accepted: 25 November 2013# Springer-Verlag Berlin Heidelberg 2014

Abstract Blush is an important trait for marketing peaches.The red skin pigmentation develops through the flavonoid andanthocyanin pathways, and both genetic and environmentalstimuli, and their interaction, control the regulation of thesepathways. The molecular basis of blush development in peachis yet to be understood. An F2 blush population (ZC

2) derivedfrom a cross between two peach cultivars with contrastingphenotypes for blush, “Zin Dai” (∼30 % red) and “CrimsonLady” (∼100 % red), was used for linkage map constructionand quantitative trait loci (QTLs) mapping. The segregatingpopulation was phenotyped for blush for 4 years using a visualrating scale and quantified using a colorimeter (L*, a*, and b*)1 year. The ZC2 population was genotyped with the IPSC 9 Kpeach single-nucleotide polymorphism (SNP) array v1, and ahigh-density ZC2 genetic linkage map was constructed. Themap covers genetic a distance of ∼452.51 cM with an averagemarker spacing of 2.38 cM/marker. Four QTLs were detected:one major QTL on LG3 (Blush.Pp.ZC-3.1) and three minorQTLs on LG 4 and 7 (Blush.Pp.ZC-4.1; Blush.Pp.ZC-4.2;Blush.Pp.ZC-7.1), indicating the presence of major and minorgenes involved in blush development. Candidate genes in-volved in skin and flesh coloration of peach (PprMYB10),cherry (PavMYB10), and apple (MdMYB1/MdMYBA/MdMYB10) are located within the interval of the major QTLon LG3, suggesting the same genetic control for color devel-opment in the Rosaceae family. Marker-assisted selection(MAS) for blush is discussed.

Keywords QTLs . Anthocyanin . Candidate gene

Introduction

Blush is an important fruit quality trait in marketing peaches.The red pigmentation is attractive to the consumer’s eye, andthe anthocyanin compounds associated with blush provideflavor and nutrients, which are essential components of thehuman diet (Parr and Bolwell 2000; Sun et al. 2002;Balasundram et al. 2006). Furthermore, anthocyanin com-pounds are known to combat the development of cancer,cardiovascular disease, and other health problems related toaging (Parr and Bolwell 2000; Sun et al. 2002; Schijlen et al.2004; Howad et al. 2005; Balasundram et al. 2006). Improv-ing blush offers the potential to improve the appearance,flavor, and nutrition of peaches and thus promote consump-tion. For these reasons, breeding efforts in the private andpublic sectors have been toward an extensive level of blushfirm ripe peaches for fresh market use (Scorza and Sherman1996; Okie et al. 2008).

The progression of blush development is linked to the stageof peach development. As a peach ripens, skin backgroundcolor changes from green to yellow or other hues. Then,during the final swell in peach development (stage III), differ-ent levels of red skin pigmentation emerge over this back-ground color (Delwiche and Baumgardner 1983, 1985; Byrneet al. 1991; Marini et al. 1991; Layne et al. 2001). The redovercolor develops in diverse intensities and patterns depend-ing on the genotype (mottled, striped, variegated, spotted,etc.). The phenotypic variation of blush is controlled by ge-netic (genotype dependent) and environmental factors (lightthroughout the canopy) (Layne et al. 2001), along with agenotype–environment interaction. Together, these three fac-tors regulate highly conserved flavonoid and anthocyaninbiochemical pathways (Schijlen et al. 2004).

Communicated by E. Dirlewanger

T. J. Frett :G. L. Reighard :K. Gasic (*)SAFES, Clemson University, Clemson, SC 29634, USAe-mail: kgasic@clemson.edu

W. R. OkieARS-USDA, S.E. Fruit and Tree Nut Research Lab,Byron, GA 31008, USA

Tree Genetics & GenomesDOI 10.1007/s11295-013-0692-y

Anthocyanins have been a focus of study in plants formany years, starting with Mendel’s study on flower color inpeas (Holton and Cornish 1995). Wu and Prior (2005) char-acterized the specific anthocyanins that develop in 25 differentfruits. Only two specific anthocyanins have been identifiedand associated with blush development in peach: cyanidin 3-O-glucoside and cyanidin 3-O-rutinoside (Hsia et al. 1965;Van Blaricom and Senn 1967; Chaparro et al. 1994; Tomás-Barberán et al. 2001; Byrne et al. 2004; Wu and Prior 2005;Cevallos-Casals et al. 2006; Vizzotto et al. 2006, 2007; Cantínet al. 2009). The concentrations of these two anthocyaninsvary depending on the type of peach and the particular tissue.Interestingly, the peach skin (exocarp) was found to containthree times more or greater levels of phenolic compounds(anthocyanins and flavonols) than the flesh (mesocarp)(Chang et al. 2000; Tomás-Barberán et al. 2001; Gil et al.2002; Gorinstein et al. 2002; Cevallos-Casals et al. 2006;Vizzotto et al. 2006, 2007). The skin is a highly concentratedsource of these compounds; however, it only represents ∼8 %of the total fresh fruit weight; therefore, the completedistribution of phenolic compounds in the skin and fleshfor each fruit is ∼30 % and 70 %, respectively (Cevallos-Casals et al. 2006).

Recently, there were several attempts to determine themolecular basis for red skin (i.e., anthocyanin accumulation)in peach through quantitative trait analysis. A quantitative traitlocus (QTL) responsible for red skin coloration (SRColor2)was discovered close to RFLP marker AC108 on linkagegroup (LG) 5 of the Prunus reference map (Quilot et al.2004). In the same general location on LG5, a QTL qP-Brn5.1m associated with leucoanthocyanidin dioxygenase(PpLDOX), an important structural gene in the anthocyaninpathway involved in peach flesh browning, was also reported(Ogundiwin et al. 2007, 2008, 2009). Recently, a QTL forblush on LG4 of a peach genetic linkage map, created using afilial 1 (F1) progeny from a cross between “Venus”דBigTop”(V×BT), was discovered (Cantín et al. 2010). Additionally,the qualitative inheritance of blush and existence of two singlegenes controlling development (Beckman and Sherman 2003)or suppression (Beckman et al. 2005) of red skin in peachbased on phenotype observations were also reported.

QTL studies for blush have also been performed in otherRosaceous species: apple (Malus domestica) (Takos et al.2006; Ban et al. 2007; Chagné et al. 2007; Espley et al.2007, 2009), cherry (Prunus avium L.) (Sooriyapathiranaet al. 2010), octoploid strawberry (Fragaria x ananassa)(Zorrilla-Fontanesi et al. 2011), raspberry (Rubus idaeus)(McCallum et al. 2010), and grape (Vitis vinifera)(Kobayashi et al. 2004; Walker et al. 2007; Kobayashi2009). The two-repeat R2R3 MYB transcription factor (TF)class has been associated with the activation and geneticregulation of the anthocyanin biosynthetic pathway through-out the Rosaceae (Allan et al. 2008; Lin-Wang et al. 2010). A

major gene MdMYB10/MdMYB1/MdMYBA associated withred skin (Takos et al. 2006; Ban et al. 2007) and red fleshcoloration in apple (Chagné et al. 2007; Espley et al. 2007,2009) was mapped. Lin-Wang et al. (2010) demonstrated thatthe three MYB activators of apple anthocyanin (MYB10/MYB1/MYBA) were expected alleles of each other. Throughcomparative genomic techniques, they determined that thislocus is highly likely to be homologous across the Rosaceaefamily. Overexpression of these genes in apple and strawberrycorrelated with elevated levels of anthocyanins in the fruit andflowers (Lin-Wang et al. 2010).

In sweet cherry (P. avium L.), the candidate gene,PavMYB10 (homologous to apple, MdMYB10, andArabidopsis, MYB75), was mapped and colocated within themajor QTL interval for red skin and flesh pigmentation (Lin-Wang et al. 2010; Sooriyapathirana et al. 2010). This sug-gested that PavMYB10 is likely a major TF gene responsiblefor the production of red skin and flesh in sweet cherry(Sooriyapathirana et al. 2010). The apple, cherry, and peachare all members of the Rosaceae family; therefore, it is likelythat the major geneMYB10/MYB1/MYBA has been conservedand can be associated with the production of anthocyanin inpeach skin and flesh. The peach MYB polypeptide chain,PprMYB10, was shown to be homologous with the RosaceaeMYB10, with only an 18-amino acid deletion in the C termi-nus, which does not hinder the ability of the TF to regulate theanthocyanin biosynthetic pathway (Lin-Wang et al. 2010).This demonstrated that the MYB10 (and possibly MYB1/MYBA) has been conserved in peach and has the potential toregulate the amount of anthocyanin production in peach skin(and potentially flesh). Despite this, the genes that code for theMYB10, MYB1, and MYBA remain to be mapped in peach.

Peach is one of the best characterized fruit tree species andserves as a model for genetic studies in Rosaceae and othertree species (Dirlewanger et al. 2004; Shulaev et al. 2008).The available Prunus reference map (Dirlewanger et al. 2004)along with release of peach genome sequence v1 (Sosinskiet al. 2009; Arus et al. 2012) and recently developed single-nucleotide polymorphism (SNP) genotyping resources(Ahmad et al. 2011; Verde et al. 2012) offers the opportunityto intensively study the development and inheritance of blushin peach at the molecular level. Traditional breeding has beensuccessful in developing current peach cultivars with in-creased levels of blush. However, blush is quantitative innature and thus presents practical challenges in selection(Bliss 2010). Furthermore, traditional peach breeding is atime-consuming process taking ∼15 years or more, until anew cultivar can be released. Moreover, consumer preferenceis known to change over time. Therefore, to overcome thelimitations of traditional breeding and enhance blush in futurepeach cultivars, discovery of molecular marker(s) linked toQTLs associated with the development of blush is a necessarystart to facilitate marker-assisted breeding (MAB) and enable

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a more efficient selection of this trait. Incorporation of MABas a tool to complement and accelerate traditional breedingtechniques could increase the efficiency of breeding newpeach cultivars with superior blush and other fruit qualitytraits. Ultimately, a more efficient cultivar development willhelp ensure that the peach industry has products to meetevolving consumer demands (Byrne 2005).

In this study, we are reporting development of an SNPlinkage map and mapping the QTLs associated with blush inpeach. In addition, development and validation of a cleavedamplified polymorphic sequence (CAPS) marker and its ap-plication to MAB for blush in peach is presented.

Materials and methods

Plant material used

An F2 population segregation for red skin pigmentation wasused to create a linkage map and perform QTL analysis ofblush. Parents with contrasting blush characteristics wereselected: “Zin Dai Jiu Bao” (“Zin Dai”), a low-acid, white-fleshed peach imported from China, (∼30 % blush) and“Crimson Lady”, a nonmelting, yellow-fleshed shippingpeach from California popular in the early season (∼100 %blush). From the “Zin Dai”דCrimson Lady” cross, an indi-vidual F1 tree (BY92p4019: ∼65% blush) was selfed to obtainan F2 population of 93 individuals (denoted as ZC2), segre-gating for blush (0–100 %). This population is located at theUSDA Fruit and Nut Research Laboratory in Byron, Georgia.The seedling progeny were planted on their own roots in asingle row at 0.9 m in-row spacing. Minimum horticulturalmaintenance was performed, and the trees were hedged annu-ally starting in their third year of growth.

Blush phenotyping

Phenotypic data were recorded over 4 years (2007, 2008,2010, and 2011) using a standardized phenotyping protocolas explained in Frett et al. (2012). Two evaluation methods forblush were used: visual qualitative coverage (0–5 scale) andquantitative intensity using a chroma meter (CR-400, KonicaMinolta, Tokyo, Japan).

Taking into account the entire tree, an average percent-age of the fruit with the highest blush was estimated toaccount for sunlight variance throughout the canopy andobtain an accurate representation of blush. The percentageof blush covering the fruit skin was approximated using ascale from 0 to 5, 0 indicating no blush and 5 indicatingfull red surface color.

In addition to visual qualitative coverage, blush was alsodocumented in 2011 using a standard KonicaMinolta ChromaMeter (CR-400, Konica Minolta Chroma Meter, Tokyo,

Japan; or other models). Fruits for quantitative intensity mea-surement were harvested after a few fruit on the tree becametree ripe (soft to the touch). The “light protection tube” (glassprotection plate CR-A33a, 22 mm in diameter) was placed onthe most intense area of blush on five peach samples pergenotype to quantitate blush: L* (intensity; −L*, dark; +L*,light), a* (−a*, green; +a*, red) and b* (−b* blue; +b*,yellow). For data analysis, the saturation and hue angle weredetermined by converting the Cartesian coordinates into polarcoordinates. Cartesian coordinates show a relative distancebetween two colors while polar coordinates determine theexact position. For this reason, the a* and b* values wereconverted from Cartesian (x, y) to polar coordinates (r=satu-ration, theta (θ)=hue angle) using a simple transformation ofcoordinate systems.

Statistical analysis

Descriptive statistics of all blush phenotypic data, both visualqualitative coverage (0–5 scale) and quantitative chroma me-ter readings (L*, a*, b*, r, and theta) were calculated usingSPSS® 19.0.0 (IBM®). The 0–5 blush scale ratings wereaveraged across years, and minimum and maximum valueswere identified. A combined approach was also used wherethe most abundant visual scoring throughout the 4 years ofdata was selected (i.e., 4-year scores 2, 2, 2, and 3; then, 2 wasselected for combined data). The descriptive statistics gener-ated included mean, standard deviation, skewness, and kurto-sis. Histograms were generated for each data set in order todetermine normality of data graphically. Pearson’s correlationcoefficients were calculated in SPSS for visual blush using a0–5 scale for 2007, 2008, 2010, 2011, and the 2011 L*, a*, b*,r, and theta data. Broad-sense heritability (H2) was approxi-

mated using the following formula: H2 ¼ σ2g= σ2

g þ σ2e=n

� �

σ2e ¼ genotic variance; σ2

e¼ environmental variance; n ¼

�

sample sizeÞ:

DNA isolation and genotyping

Twenty-five of the 93 ZC2 individuals were selected such thattheir mean blush rating followed a normal distribution for thistrait and included a range from 0 (0 % red) to 5 (100 % red)(Fig. 1). These selections were genotyped using an Interna-tional Peach SNP Consortium (IPSC) 9 K peach SNP arrayv1. (Verde et al. 2012). Isolation of genomic DNA and sub-sequent Infinium assay were performed as explained in Verdeet al. (2012). SNP genotypes were scored with the GenotypingModule of GenomeStudio Data Analysis software (IlluminaInc.). A GenTrain score of >0.4 and a GenCall 10 % of >0.2were applied to remove most SNPs that did not cluster(homozygous) or had ambiguous clustering.

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Genetic linkage map construction

A genetic linkage map was constructed using SNPs homozy-gous for alternate alleles in two parents as well as SNPshomozygous in one and heterozygous in the other parent. F2population type codes were applied (Van Ooijen 2006). Ge-netic linkage analyses and map construction were performedwith JoinMap 4.1 (Van Ooijen 2006). The deviations from aMendelian ratio were tested using the Chi-square-goodness-of-fit test (p<0.05). Linkage groups were established using aminimum 3.0 logarithm of odds (LOD) and maximum recom-bination frequency of 0.40. Marker distances were calculatedusing a Kosambi (1944) mapping function. Map figures weregenerated usingMapChart 2.2 software (Voorrips 2002). FinalLG assignment was performed after comparison between aZC2 linkage map and peach genome v1.0.

Linkage map comparisons to peach physical map

The ZC2 linkage map was compared to the peach physical mapto determine LG name and orientation. The set of SNPsmappedin the ZC2 linkage map were aligned with their position on thepeach genome using MapChart 2.2 (Voorrips 2002), and co-linearity among the linkage and physical maps was evaluated.

QTL analysis

Blush data were organized into 13 data sets for QTL analysis.All data sets consisted of 25 progeny excluding blush 2010,(e.g., 24) and all chroma meter data sets (e.g., 23). Visual datacollected for each accession in four seasons (2007, 2008,2010, and 2011) included yearly mean values as well as themaximum, minimum, average, and most consistent value overthe 4 years, resulting in eight data sets. Chroma meter datacollected in 2011 included L*, a*, b*, r, and theta and com-prised the other five data sets.

The ZC2 linkage map and phenotypic data sets were usedto characterize and map QTLs associated with blush in peach.Initially, all phenotypic data sets were tested for the normalityof distribution using the S-test [i.e., the standard error of mean(SEM)] calculated in Windows-QTL-Cartographer v2.5(Wang et al. 2007). Those data sets with S values lower than5.99 (p<0.05) and 9.21 (p<0.01) approximated a normaldistribution and were used for QTL analysis. Detection ofputative QTLs was performed separately for each data setusing composite interval mapping (CIM) (Jansen and Stam1994; Zeng 1994). Genome-wide QTL threshold values foreach data set were determined by a 1,000-permutation test(p<0.05). Through this analysis, every 1 cM of the genomewas scanned to approximate LOD curves. Multiple regression(MR) analysis was used to estimate the percentage of pheno-typic variation (R2) explained for each individual QTL and forall QTLs (R2t). The percentage of phenotypic variance (R2)explained by the QTL was taken as the QTL peak position asdetermined by WinQTL cartographer 2.5. QTLs with an R2>25 % were declared major QTLs. The QTLs with R2<25 %were termed minor QTLs. The LOD of the peaks were used toindicate the most likely position of QTL effects. QTL intervalswere reported in 1LOD (p<0.05) and 2LOD (p<0.01) confi-dence intervals. Figures of the resulting ZC2 linkage map andassociated QTL positions were developed usingMapChart 2.2(Voorrips 2002). QTLs were named as TTL1-YYYY whereTT=trait acronym; L=linkage group number; _1=numbers toidentify different QTLs for the same trait; YYYY=the year inwhich the trait was phenotyped, following the example fromFan et al. (2010).

Candidate gene prediction

The SNP markers flanking major and minor QTLs werelocated in the peach genome v1, to determine each QTL’sposition in the genome. The complete coding sequence of

Fig. 1 Visual blush observed over 4 years on 93 progeny and parents of ZC2 population. Asterisk marks individuals selected for genotyping andconsequently mapping

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P. persica R2R3MYBTF PprMYB10 (GenBank EU155160.1)and translated protein (GenBank: ABX79945.1) were obtain-ed and annotated against the peach genome v1.0 assembly(www.rosaceae.org) using blastn and tblastn (Altschul et al.1997). Likewise, cherry PavMYB10 (EU153581.1 andABX71493.1) and apple MdMYB10 (EU518249.2 andACQ45201.1)/MdMYB1 (DQ886414.1, DQ886415.1,DQ886416.1, ABK58136.1, ABK58137.1, and ABK58138.1)/MdMYBA (AB279598.1and BAF80582.1) genes and trans-lated protein sequences were annotated against the peachgenome v1.0 assembly using blastn and tblastn (Altschulet al. 1997: Takos et al. 2006; Ban et al. 2007; Chagné et al.2007; Espley et al. 2007; Espley et al. 2009; Lin-Wang et al.2010).

To further investigate the anthocyanin pathway in peach,Arabidopsis, cherry, and apple TF (bHLH and WD40) andmajor structural genes involved with the anthocyanin biosyn-thetic pathway were obtained from GenBank and used asquery nucleotide or protein sequences for homology searcheswithin the peach genome v1.

Development of CAPS marker

An SNP marker, SNP_IGA_341962 (A/G) (scaf-fold_3:12,836,182..12,836,182), heterozygous in F1 and inone grandparent, within the major blush QTL Blush.Pp.ZC-3.1 and 5.49 kbp upstream of PprMYB10was used to developa CAPS marker; CAPS_341962 with a Rsa1 recognition site.The conversion of the SNP into a CAPS marker was per-formed using CAPS designer software (http://solgenomics.net). Forward, 5′-CGTTTCTTGAAGCGTTACGG-3′, andreverse, 5′-GCAGCTCTCTTCAGCTAGGC-3′, primershave been designed in Primer3 software (Rozen andSkaletsky 2000) using a SNP_IGA_341962 flanking se-quence (http://www.rosaceae.org/species/prunus_persica/genome_v1.0).

PCR reaction was performed in the total volume of 25 μlwith final concentrations of 50 ng of DNA, 0.2 μM of bothprimers, 200 μM of each dNTP, and 0.5 U of Taq DNApolymerase in 10 mM, 1.5-mM MgCl2 and 50-mM KCl(New England Biolabs, Ipswich, MA). Amplification wasperformed in MBS Satellite Thermal Cyclers (Thermo FisherScientific, Waltham, MA) under the following conditions:3 min of initial denaturation at 94 °C, 30 s at 94 °C, 30 s at55ºC (Ta), and 30 s at 72 °C for 35 cycles, then a finalextension step of 5 min at 72 °C. The restriction digestion ofthe 25-μl PCR product was performed using a 1 U RsaIrestriction enzyme, in 50-μl total volume, and incubated at37ºC for 1 h. The restriction-digested PCR products wereresolved on 2 % agarose gels in 1X sodium boric acid (SB)buffer (Brody and Kern 2004) and visualized along a lowmolecular weight (LMW) ladder (New England Biolabs, Ips-wich, MA) with ethidum bromide under UV light.

Statistical analysis

Statistical analyses of the F2 progeny phenotypic data sets wereperformed using ANOVA in SPSS® 19.0 (IBM®). Significantdifferences were calculated at p<0.05, p<0.01, p<0.001 usingthe Tukey honestly significant difference (HSD) test. An asso-ciation test between blush and haplotypes and CAPS markergenotypes was performed by a t-test at p<0.05.

Results

Phenotypic evaluation of blush

In most years, the minimum and maximum values for visualblush ranged from 0 to 5 with the blush population grandparentsat extremes (Figs. 1 and 2, Table 1). Average blush coverageobserved across the progeny ranged from 1.56 to 1.88 with thehighest value observed in years 2007 and 2010. Five of thephenotypic data sets exhibited a bimodal distribution (I, J, K,L, and M) and two were not normally distributed (B and H).However, all data sets passed the required normal distribution test(S-test; Table 3) for the Win QTL software and subsequentlywere used for QTL analysis. Visual blush and L*, a*, b*, r, andΘ data showed significant correlations (p<0.01) through all yearsand all data comparisons (Table 2). Broad-sense heritability (H2)estimates were very high, >0.99, and highly significant in all datasets of visually scored blush (p<0.01) (Table 1). The broad-senseheritability for chroma data ranged from 0.63 to 0.97 (Table 1).

Linkage map construction

Out of 8,144 SNPs on the IPSC peach 9 K SNP array v1,5,059 (62.12 %) were polymorphic between “Zin Dai” and“Crimson Lady” (GenTrain score of ≥0.4). Of these, 1,370(27.08 %) were informative in the blush progeny and thusused to construct the ZC2 SNP genetic linkage map. A total of1,335 SNP markers (97 %) were successfully mapped to 190unique positions on 14 groups creating a ZC2 linkage map(Table 3). Four groups corresponded to LG3, 6, 7, and 8, and10 of them corresponded to LG1, 2, 4, and 5, representing alleight peach linkage groups (Fig. 3, Table 3). LG1 consisted ofthree groups, 1_1, 1_2, 1_3; LG2 of two, 2_1 and 2_2; LG4 ofthree 4_1, 4_2, and 4_3; and LG5 of two groups 5_1 and 5_2.The linkage groups that have more than one group of linkedmarkers were designated as G1, 2, 4, and 5 in further texts.Mapped SNP markers did not significantly deviate from Chi-square expectations. Approximately 86 % of the mappedSNPs shared a map position; therefore, 190 unique mappedpositions were represented with a single SNP marker for eachunique position (Fig. 3, Table 3). The ZC2 linkage mapspanned 452 cM with an average marker density of2.38 cM/marker (Fig. 3, Table 3). The number of unique

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map positions, mapped on each linkage group, ranged from 9 onG5 to 36 on LG3, with an average of 24 markers per LG/G(Table 3). The length of LGs was variable, with LG3 being the

largest, 108 cM, and G5 covering the shortest distance, 16.7 cM(Table 3). LG3 and G1 had the highest number of uniquepositions, 36 and 30, respectively, while the lowest number of

Fig. 2 Distribution of phenotypic data organized in 13 data sets for a subset of ZC2 population. aVisual blush 2007. bVisual blush 2008, cVisual blush2010, dVisual blush 2011. eAverage visual blush, fCombined visual blush, gMax blush, hMin blush, i L*, j r, k theta, l a*, m b*

Table 1 Descriptive statistics for all phenotypic data

Data set N Min Max Mean SD S-test Heritability (H2)

Blush2007 25 0.00 5.00 1.88 1.45 1.56 0.99**

Blush2008 25 0.00 4.00 1.56 1.26 0.75 0.99**

Blush2010 24 0.00 5.00 1.67 1.37 1.38 0.99**

Blush2011 25 0.00 4.00 1.88 1.13 0.47 0.99**

Average 25 0.00 4.00 1.88 1.30 0.11 0.99**

Combined 25 0.00 4.00 1.88 1.24 0.27 0.99**

Max 25 0.00 5.00 2.24 1.50 0.63 0.99**

Min 25 0.00 3.00 1.36 1.11 0.93 0.99**

L* 2011 23 33.39 70.91 51.50 14.24 1.81 0.93

r 2011 23 27.63 63.12 47.36 9.85 0.08 0.63

Θ 2011 23 25.70 88.45 54.61 24.15 2.30 0.97*

a* 2011 23 1.53 38.80 22.44 14.05 2.32 0.83

b* 2011 23 13.67 62.89 37.00 16.95 1.42 0.81

Critical values for the rejection of normality of data sets are 5.99 and 9.21 at the 5 % and 1 % levels, respectively, for the S-test statistics

N number of analyzed samples, SD standard deviation

*p<0.05

**p<0.01; i.e., highly significant

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unique positions were observed on G5 and G7 (9 and 14). Thelargest gaps, 16.5 cM and 13.7 cM were observed on LG3,between SNP_IGA_350488 and SNP_IGA_364100, and onG4 (LG4_2 ) , b e tween SNP_ IGA_511285 andSNP_IGA_540776, respectively (Fig. 3, Table 3).

Comparison of ZC2 linkage map and peach physical map

Linkage positions of the 82 % of all SNP markers in the ZC2

linkage map were in agreement with their positions on thepseudomolecules/scaffolds of peach genome v 1.0. Eight re-gions in ZC2 map, involving five markers on LG1 (4/LG1_2

and 1/LG1_3), six on LG2 (LG2_1), eight on LG3, seven onLG4 (1/LG4_1, 4/LG4_2, and 2/LG4_3), two on LG6, and sixmarkers on LG8, appeared inverted relative to the physicalmap (Table 4).

LGs 5 and 7 exhibited high homology with the “dhLovell”physical map. The physical length of ZC2 linkage map wasestimated to cover 61.6 % of the pseudomolecules of peachgenome v 1.0. The largest coverage of 99.1 % was achievedbetween LG3 and pseudomolecule 1 and the lowest betweenLG5 and pseudomolecule 6 (17.1 %). In addition, the estimatedaverage coverage per marker on the pseudomolecules rangedfrom ∼1/400 kb on LG1 to 1.2/200 kb on LG4 (Table 4).

Table 2 Pearson’s correlation coefficients for visual blush % (0–5) 2007, 2008, 2010, and 2011 and L*, a*, b*, r and Θ in 2011 using 25 SNP chipindividuals

2008 % (25) 2010 % (24) 2011 % (25) 2011 L* (23) 2011 r (23) 2011 Θ (23) 2011 a* (23) 2011 b* (23)

2007 % (25) 0.77** 0.87** 0.73** −0.80** −0.83** −0.83** 0.69** −0.85**2008 % (25) 0.88** 0.90** −0.82** −0.73** −0.83** 0.75** −0.81**2010 % (24) 0.79** −0.84** −0.85** −0.86** 0.72** −0.87**2011 % (25) −0.79** −0.70** −0.79** 0.72** −0.76**L* (23) 0.90** 0.98** −0.91** 0.98**

r (23) 0.89** −0.72** 0.96**

Θ (23) −0.94** 0.98**

a* (23) −0.88**

*marks significance at p<0.05

**at p<0.001

Table 3 Description of ZC2

linkage map

aAverages were calculated con-sidering eight linkage groups

Bold entries are the total value foreach linkage group (LG/G)

Group Length(cM)

Mappedmarkers

Uniquely mappedpositions

SNP mapped tothe same position

Largestgap (cM)

Smallestgap (cM)

LG1_1 6.1 24 4 20 2.1 2

LG1_2 45.7 78 22 56 6.4 0.3

LG1_3 6.1 10 4 6 2.1 2

G1 57.9 112 30 82 6.4 0.3

LG2_1 47.4 259 22 237 6.4 0.9

LG2_2 4.1 14 3 11 2.1 2

G2 51.5 273 25 248 6.4 0.9

LG3 108.0 162 36 126 16.5 0.3

LG4_1 39.0 133 18 115 4.2 2

LG4_2 19.8 90 5 85 13.7 2

LG4_3 4.1 10 5 5 1.2 0.9

G4 62.9 233 28 205 13.7 0.9

LG5_1 8.2 27 5 22 2.1 2

LG5_2 8.5 6 4 2 4.3 2

G5 16.7 33 9 24 4.3 2

LG6 49.8 167 19 148 8.7 2

LG7 46.1 178 14 164 6.4 2

LG8 59.6 177 29 148 6 0.4

ZC2 map 452.5 1335 190 1145 16.5 0.3

Average a 56.6 167 24 143 — —

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QTL analysis

All blush data sets exhibited normal distribution and thus wereused for QTL mapping (Table 1). CIM QTL analysis depicteda total of four QTLs: Blush.Pp.ZC-3.1, Blush.Pp.ZC-4.1,Blush.Pp.ZC-4.2, and Blush.Pp.ZC-7.1 in 12 out of 13 datasets(Fig. 4, Table 5). One significant major QTL (p<0.001) was

identified on LG3, Blush.Pp.ZC-3.1, using all visual blush(VB) ZC2 data sets and all chroma quantified blush (QB) datasets, excluding QBr (Fig. 4, Table 5). Blush.Pp.ZC-3.1spanned 11–41 cM (LOD-2), peaked on average at∼29.89 cM, and explained on average 63.7 % of thephenotypic variance for blush (ranging from 9.1 to87.0 %).

Fig. 3 ZC2 linkage map (one SNP per loci), generated through JoinMap 4.1 (distances in cM)

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Three minor QTLs were located on LGs 4 and 7 indicatingthe presence of additional minor genes involved in blushdevelopment (Fig. 4, Table 5). Visual 2011 blush data setapproximated two minor QTLs on LG4: Blush.Pp.ZC-4.1spanned 0.2–6.1 cM (LOD2), peaked at 4.1 cM, and ex-plained 12.9 % phenotypic variance, while Blush.Pp.ZC-4.2spanned 10.5–16.3 cM (LOD2), peaked at 12.3 cM, andexplained ∼13.5 % phenotypic variance for blush. An addi-tional minor QTL, Blush.Pp.ZC-7.1, located on LG7 spanned∼35.6–44.7 cM (LOD2), peaked at 41.7 cM, and explained∼1.2 % phenotypic variance for blush (Fig. 4, Table 5).

Additive effects were also calculated to speculate the ori-gins of alleles associated with blush development (Table 5).Additive effects of the four QTLs, Blush.Pp.ZC-3.1,Blush.Pp.ZC-4.1, Blush.Pp.ZC-4.2, and Blush.Pp.ZC-7.1

varied from 0.17 to 4.48. The positive values suggested thatthe alleles associated with blush development originated fromthe parent with high blush “Crimson Lady”.

Since mapping was performed on the F2 population, onlytwo grandparental haplotypes were present in the F1, haplo-type “a” from low-blush grandparent “Zin Dai” and haplotype“b” from high-blush grandparent “Crimson Lady”. The threeprogeny haplotype combinations were defined as “aa”, “ab”,and “bb”, and the blushmeans were calculated using each dataset (Table 6). Those progeny that received the “b” haplotype(i.e., a/b and b/b) showed significantly (p<0.001) more blush,as measured by all 13 data sets over all four seasons, thanthose individuals that were homozygous a/a (Table 6). Addi-tionally, individuals that received both copies of haplotype “b”(b/b) showed significantly (p<0.05) more blush, as measured

Table 4 Comparison of ZC2

linkage to the peach physical map LG # ZC2 linkage map Physicalcoverage (%)

Marker density Averagecoverage(kb/cM)#SNPs

(inverted)Geneticdistance (cM)

Physicallength (Mb)

cM kb

G1 30 (5) 57.90 26.49 56.66 1.93 883.0 457.51

G2 25 (6) 51.47 18.21 68.17 2.06 728.4 353.59

LG3 36 (8) 108.04 21.70 99.07 3.00 602.8 200.93

G4 28 (7) 62.90 10.48 34.89 2.25 374.3 166.35

G5 9 16.72 3.11 17.06 1.86 345.6 185.78

LG6 19 (2) 49.80 21.61 75.51 2.62 1137.0 434.11

LG7 14 46.07 15.42 68.02 3.29 1101.0 334.78

LG8 29 (6) 59.61 16.58 76.60 2.06 571.7 277.54

Fig. 4 Location of QTL forvisual blush (VB) and quantifiedblush (QBL*, QBa*, QBb*, QBr,and QBΘ) mapped on peach ZC2

SNP linkage map using compos-ite interval mapping (CIM). Thick(1 LOD) and thin (2 LOD) barsmark significance areas of QTL(p<0.05; p<0.01). QTL werenamed following this formatTTL-YYYY-1. (“TT”=trait acro-nym; “L”=linkage group number;“1”=numbers to identify differentQTL for the same trait; “YYYY”=the year in which the trait wasphenotyped: LOD scores andphenotypic variability explainedby QTL (R2) depicted in Table 6)

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by visual blush in 2007 and 2011 and the average, maximum,and minimum for the group, than those individuals that onlyreceived one copy of the “b” haplotype (a/b) (Table 6).

Candidate gene prediction

The major QTL for blush, Blush.Pp.ZC-3.1 on LG3 of ZC2

SN P l i n k a g e m a p , r e s i d e s o n s c a f f o l d _ 3 :4,821,129..13891040 of the peach genome and collocateswith the P. persica R2R3 MYB TF and protein sequence(PprMYB10), cherry PavMYB10, and apple MdMYB10/MdMYB1/MdMYBA gene. Out of the 8,144 SNPs availableon the IPSC 9 K peach SNP array v1, 377 (4.6 %) residewithin the major QTL associated with blush,Blush.Pp.ZC-3.1,on peach scaffold 3. No SNPs from the IPSC 9 K peach SNParray v1 were anchored in the coding sequence of PprMYB10;however, snp_3_12840254 was located 1.417-kbp upstreamand SNP_IGA_342159 was located 36.383-kbp downstreamof PprMYB10.

The minor QTLs for blush were located on scaf-fold_4:2337191..3966620 (Blush.Pp.ZC-4.1), scaf-fold_4:4306550..5226293 (Blush.Pp.ZC-4.2), and scaf-fold_7:12111894..16021970 (Blush.Pp.ZC-7.1) of the peachgenome. Comparison of peach genome sequence from minorQTL regions to the Arabidopsis genome sequence revealeduridine diphosphate (UDP)-glycosyltransferase (GI:75311632)within Blush.Pp.ZC-4.1 and 4-coumarate coenzyme A (CoA)ligase (GI:15217838: GI:9280225: GI:30695037:GI:15232507) and flavonoid 3′-hydroxylase (GI:8132327)within Blush.Pp.ZC-7.1. Each of these potential candidategenes when compared with the peach genome showed higherhomology elsewhere on other scaffolds of the peach genome.

Marker validation and MAB for blush in peach

One SNP marker, SNP_IGA_341962, linked upstream toPprMYB10, was converted into a codominant CAPS marker,CAPS_341962. It successfully amplified a 104-bp PCR

Table 5 Summary of the QTL detected for blush using visual blush and chroma-quantified blush data sets by composite interval mapping

QTL Dataset LG QTL peak position incM & (closest marker)

LOD atQTL peak

R2 (%) LOD2-left LOD1-left LOD1-right LOD2-right Add.

Blush.Pp.ZC-3.1 Θ 2011 3 15.3 (SNP_IGA_315904) 5.87* 18.45 11.9 12.2 17.3 18.3 8.69

a* 2011 3 16.3 (SNP_IGA_315904) 7.2*** 16.78 11 11.3 18.3 18.3 −11.18b* 2011 3 21 (snp_3_7344624) 6.49** 87.04 21 21 23.1 23.1 20.78

Blush2008 3 21 (snp_3_7344624) 4.94* 9.10 14.4 19.2 22.8 24.1 0.32

Θ 2011 3 22 (snp_3_7344624) 9.19*** 63.65 21 21 22.4 22.7 22.28

a* 2011 3 27.1 (SNP_IGA_317767) 12.93*** 61.20 25.6 25.9 31.1 31.1 −14.56Average 3 27.1 (SNP_IGA_317767) 7.22*** 75.43 25.1 25.6 30.8 31.5 −0.81L* 2011 3 27.1 (SNP_IGA_317767) 7.81*** 60.84 26.1 26.9 31.1 31.1 13.23

Θ 2011 3 31.5 (SNP_IGA_326457) 14.2*** 83.89 25.9 27.1 36 37.1 28.91

b* 2011 3 31.5 (SNP_IGA_326457) 9.88*** 83.25 25.7 26.5 36.7 37.3 22.186

a* 2011 3 34.5 (SNP_IGA_329177) 12.24*** 39.35 33.5 33.5 34.9 35.2 −14.12Blush2007 3 35.6 (SNP_IGA_341490) 6.06** 69.61 25.1 30.4 37.2 39.5 −1.60Blush2008 3 35.6 (SNP_IGA_341490) 7.53*** 65.32 31.5 33.9 37 37.6 −1.97Blush2010 3 35.6 (SNP_IGA_341490) 4.13* 60.64 32 27 37.3 40.8 −1.35Blush2011 3 35.6 (SNP_IGA_341490) 10.97*** 87.98 30.8 33.9 37 37.6 −1.43Combined 3 35.6 (SNP_IGA_341490) 6.13*** 68.01 30.1 30.1 37 37.6 −1.52Average 3 35.6 (SNP_IGA_341490) 6.28*** 72.89 31.5 31.5 37 37.6 −1.40Max 3 35.6 (SNP_IGA_341490) 6*** 71.64 25.1 31.1 37.5 40.5 −1.67Min 3 35.6 (SNP_IGA_341490) 8.09*** 97.26 31.2 33.8 37 37.6 −1.42Θ 2011 3 38.6 (SNP_IGA_343773) 9.91*** 81.81 37.8 38.2 40.7 41 26.27

Blush.Pp.ZC-4.1 Blush2011 4 4.1 (SNP_IGA_384731) 7.61*** 12.85 0.2 0.7 5.6 6.1 0.40

Blush.Pp.ZC-4.2 Blush2011 4 12.3 (SNP_IGA_386970) 4.92* 13.52 10.5 11.6 15.3 16.3 0.17

Blush.Pp.ZC-7.1 Min 7 41.7 (SNP_IGA_776348) 5.3** 1.24 35.6 39.9 44.7 44.7 0.20

QTL were named following this format TTTL-YYYY-1 (“TTT”=trait acronym, “L”=linkage group number, “YYY”=the year in which the trait wasphenotyped, “1”=numbers to identify different QTL for the same trait), Add. additive effectsboldface=major QTL significant at p<0.05 or lower.italics=minor QTLs significant at p<0.05 or lower

*1 LOD, ** 2 LOD, *** 3 LOD values significant at p<0.05, p<0.01, p<0.001—based on 1,000 permutation tests

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fragment in all materials analyzed (data not shown). Restric-tion digestion, using RsaI, yielded from two to four fragmentsallowing detection of all three genotypes, “A/A”, “G/G”, and“A/G” (Fig. 5). Blush progeny analysis using CAPS_341962revealed 1:2:1 segregation that followed phenotypic observa-tions. Statistically significant differences were observedamong three genotypes (Fig. 6, Table 7). Out of 93 progenyanalyzed, 24 individuals showed genotype “AA”, 47 “AG”,and 22 “GG” (Fig. 6, Table 7). The highest average blush of2.37 over 4 years (scale 0–5; 2007, 2008, 2010, and 2011) wasobserved in 24 individuals with “AA” genotype, followed bythe intermediate levels of blush, 1.74, in 47 individuals withheterozygous genotype “AG”, and low levels of blush, 0.38,in 22 individuals with a “GG” genotype (Table 7).

Discussion

Phenotypic data

Highly significant broad-sense heritability (H2) for all visuallyscored blush data sets showed that blush accumulation for agenotype did not vary much between years. Therefore, suggest-ing that blush development in the ZC2 population was primarilycontrolled by the genotype, and the environment did not play asignificant role. High broad-sense heritability, ∼0.96 and 0.95for red skin color, was also reported in cherry (Sooriyapathiranaet al. 2010). The minimum horticultural maintenance applied to

this population could be a major reason for the low environ-mental variation observed. Trees were planted in a single roworiented north/south and were not pruned to a standard trainingsystem. Hedging was applied each year starting in year 3,resulting in limited fruiting wood and foliation in the outer partof the canopy. The inner part of the tree canopy was relativelybarren (nearly no foliation and no fruit). The fruits were locatedtoward the outer part of the canopy with the best sunlightexposure, therefore allowing ample sun exposure to the fruit.Fruit sampling should also be taken into account since specialattention was applied to ensure uniform and homogeneoussample collection from each evaluated tree.

ZC2 genetic map

Reports on the development of SNP marker resources andSNP genetic linkage maps for peach have recently been in-creasing (Ahmad et al. 2011; Arazana et al. 2012; Martinez-Garcia et al. 2012; Verde et al. 2012; Eduardo et al. 2012;Yang et al. 2012). Estimated SNP frequency of 1/100 bp innoncoding/intronic and 1/225 bp in coding/exonic genomeregions have been reported (Sargent et al. 2009; Illa et al.2011). The IPSC peach 9 K SNP v1 array contains 8,144 high-quality SNPs covering all eight peach chromosomes with anaverage spacing of 26.7 kb between SNPs and 31.5 kb be-tween only polymorphic SNPs, which were all detected inexonic regions of the peach genome (Verde et al. 2012). Theaverage ratio of genetic to physical distance in peach is about

Fig. 5 F2 individuals screened with CAPS_341962_ marker. PCR prod-uct, 104 bp, digested with RsaIGT*AC on 2 % agarose. Asteriskmarksindividuals used for genotyping and mapping. 1 average blush score over

4 years (2007, 2008, 2010, and 2011); 2 SNP genotype, AA (37 and67 bp), GG (15, 37 and 52 bp), and AG (15, 37, 52 and 67 bp)

Table 6 The mean visual and chroma meter blush values for ZC2 progeny in each haplotype class for the QTL region on linkage group 3

QTL Haplotypecombination

Visual blush 2007–2011 Chroma meter 2011

2007 2008 2010 2011 Average Comb. Max Min L* r Θ a* b*

Blush.Pp.ZC-3.1 aa (7) 0.28a 0.00a 0.14a 0.42a 0.28a 0.42a 0.57a 0.00a 69.30a 57.73a 85.91a 4.10a 57.57a

ab (13) 2.15b 1.92b 2.08b 2.23b 2.23b 2.23b 2.53b 1.61b 45.64b 44.14b 43.98b 9.49b 30.40b

bb (5) 3.40c 2.80b 2.80b 3.00c 3.20c 3.00b 3.80c 2.60c 39.43b 39.92b 34.14b 32.58b 22.69b

Different letters indicate significant differences between means within the year of observation at p<0.05 according to t-test

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440 kb/cM (Dirlewanger et al. 2004; Verde et al. 2012), whichgives an average of 13.3 polymorphic SNPs per cM for thearray (Verde et al. 2012).

The ZC2 genetic linkage map spanned a total length of∼452 cM with an average density of 2.4 cM/marker (rangingfrom 1.86 to 3.29 cM or 1/166.35 to 1/457.51 kb). This is inagreement with the latest published size for the Prunus refer-ence map, 519 cM and 0.92 cM/marker (Dirlewanger et al.2004). In addition, similar map coverage (452 cM vs 422 cMvs 421), number of mapped SNP markers (1335 vs 1037 vs1161), shared map positions (190 vs 298 vs 256), and averagemarker density (2.4 cM vs 1.48 cM vs 1.42) were obtained inrecently published high-density “Pop-DF” ("Dr. Davis" x "F8,1-42") and “OC” ("O'Henry" x "Clayton") peach SNP maps(Martinez-Garcia et al. 2012; Yang et al. 2012).

The accuracy of the high resolution ZC2 genetic map wascompared with the peach genome assembly v1 (GDR, www.rosaceae.org). Several inversions of SNP marker order(<10 cM) were observed in LG1, LG2, LG3, LG4, and LG8(Table 4). Two hundred and forty mapped SNP markersexhibited a different orientation when compared with peachgenome v1.0, which is higher than 56 and 77 mapped SNPmarkers (Martinez-Garcia et al. 2012; Yang et al. 2012).However, the ZC2 genetic map was developed using only 25individuals (compared with 69 and 63 in Pop-DF and OCpopulations, respectively) and contained 108 and 66 sharedSNP map positions (recombination events) less and 174 and298 more SNP markers than the Pop-DG and OC maps,respectively. Amajor chromosomal rearrangement, a reciprocaltranslocation between G6 and G8, has been previously docu-mented in peach intra- and interspecific crosses (Jauregui et al.2001; Yamamoto et al. 2001; Lambert and Pascal 2011). ZC2

linkage map showed an inverted region larger than 15 cM onthe upper part of LG2_1 (Table 2) suggesting possible translo-cation of chromosome fragments. The inversion on LG2 haspreviously been reported in a peach SNP map developed in ourlab using the same SNP array (Yang et al. 2012). However, bothmaps have been developed with a relatively small number ofindividuals (25 and 63), so genotyping of more progeny fromboth populations would be necessary to support the hypothesisof the chromosome fragment translocation.

Blush QTLs

Both major and minor QTLs for blush development in peachwere detected in our study. Blush.Pp.ZC-3.1 on LG3 withmajor effects and Blush.Pp.ZC-4.1 and Blush.Pp.ZC-4.2 onLG4 and Blush.Pp.ZC-7.1 on LG7 with minor effects indicatethe polygenic nature of blush inheritance that supports previ-ous reports suggesting blush in peach being a quantitative trait(Cantín et al. 2010; Quilot et al. 2004; Ogundiwin et al. 2007,2008, 2009).

QTL for blush on LG4 has been already detected using F1progeny from a cross between “Venus”דBigTop” (V×BT)(Cantín et al. 2010). This QTL could potentially be the sameas Blush.Pp.ZC-4.1 and/or Blush.Pp.ZC-4.2 detected in ourstudy and be associated with the same candidate structuralgene/s involved in the anthocyanin pathway. QTLs for blushin peach, reported on LG5 (Quilot et al. 2004; Ogundiwinet al. 2007, 2008, 2009), were not supported in our findings,probably due to different parental backgrounds and the limi-tations of the biparental mapping approach, which constrictsdiscovery only to alleles present in parental genotypes.

Candidate genes for blush and implications for MAB in peach

The flavonoid and anthocyanin pathways are conserved inplants (Schijlen et al. 2004; Lin-Wang et al. 2010; McCallumet al. 2010; Sooriyapathirana et al. 2010; Zorrilla-Fontanesiet al. 2011). The major TF R2R3 MYB10/MYB1/MYBA hasbeen associated with the activation of the anthocyanin

Fig. 6 Association of“SNP_IGA_341962” and visualblush data (average of 4 years;2007, 2008, 2010, and 2011)for 93 progeny and parentsof ZC2 population

Table 7 Mean visual blush of three CAPS_341962 genotype classesobserved in F2 progeny

Genotype No. of individuals Blush average

AA 24 2.37 a

AG 47 1.74 b

GG 22 0.38 c

Different letters indicate significant differences between means detectedby Tukey–Kramer HSD at p>0.05

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biosynthesis pathway in the Rosaceae leading to the develop-ment of red skin and flesh pigmentation (Lin-Wang et al.2010). Through comparative genomics, Lin-Wang et al.(2010) demonstrated that this orthologous major TF geneR2R3 MYB10/MYB1/MYBA is conserved throughout theRosaceae family and that MYB10/MYB1/MYBA are expectedalleles of each other. This TF gene was first located in apple(Takos et al. 2006; Ban et al. 2007; Chagné et al. 2007; Espleyet al. 2007, 2009; Lin-Wang et al. 2010) and then in sweetcherry (Sooriyapathirana et al. 2010). Candidate genePavMYB10 was shown to be homologous to theanthocyanin-associated genes in apple (MdMYB10) andArabidopsis (MYB75) and to colocate within a QTL for redskin and flesh in cherry (Lin-Wang et al. 2010;Sooriyapathirana et al. 2010).

Peach PprMYB10, apple MdMYB10, MdMYB1, andMdMYBA and cherry PavMYB10 genes and translated proteinsequences all colocate to the same location within the majorQTL for blush on LG3. Therefore, it is possible that MYB1,MYBA and MYB10 are alleles or tightly linked genes associ-ated with blush and potentially red flesh in peach as well asthey are thought to be in apple and cherry (Takos et al. 2006;Ban et al. 2007; Chagné et al. 2007; Espley et al. 2007, 2009;Lin-Wang et al. 2010).

Another red flesh anthocyanin-related apple phenotypeassociated with enhanced expression ofMYB110a a paralogueofMYB10, has been recently reported (Chagné et al. 2013). Itslocation suggests that a whole genome duplication eventoccurred during evolution within the Maloidae family. Thehypothesis of a similar paralogue ofMYB10 existing in peachmight not be as likely since each peach chromosome has beenshown to have major orthology to more than two apple chro-mosomes, thereby supporting whole genome duplication ofapple after divergence from peach and other Rosaceae genera(Jung et al. 2012). Future research to discover specific R2R3MYB TF allelic variations that control other anthocyanin-related peach phenotypes is necessary.

The potential candidate genes revealed by minor QTLs forblush located on LG4 and 7, UDP-glycosyltransferase, 4-coumarate CoA ligase, and flavonoid 3′-hydroxylase showedhigher blast hits elsewhere within the peach genome. There-fore, a more diverse background or powerful analysis ap-proach, e.g., pedigree-based QTL analysis (van de Weg et al.2004) and/or genome-wide association study (Zhu et al.2008), is necessary to further determine whether these and/or other candidate genes are important in the anthocyaninpathway in the peach genome and to what extent.

The development of a CAPS marker tightly linked to thePprMYB10, itscodominant nature, and ease of use enablesmarker-assisted selection for individuals with desirable levelsof blush. Nucleotide “A”, inherited from the grandparent withsignificantly higher blush (“Crimson Lady”, ∼100%), ensuresat least 40 % blush coverage in the progeny. CAPS_341962 is

a quick, simple, informative, and cheap marker that can beutilized in marker-assisted parental selection (MAPS) andmarker-assisted seedling selection (MASS) for blush in peach.

Conclusions

The primary goal of this study was to investigate the geneticcontrol and enable MAB for blush in peach. Traditionalbreeding has been successful in developing peach cultivarswith increased levels of blush. However, being quantitative innature, blush presents practical challenges in selection, mak-ing traditional breeding time consuming and labor intensive.A candidate gene involved in skin and flesh coloration ofpeach (PprMYB10) was located within the major QTL forblush detected in this study, Blush.Pp.ZC-3.1, which showscontrasting haplotypes for blush. A CAPS marker(CAPS_341962 ) , b a s e d on a c a nd i d a t e SNP(SNP_IGA_341962) linked upstream of PprMYB10, is ableto distinguish between individuals with high (“A/A”), medi-um (“A/G”), and low (“G/G”) levels of blush. This marker canbe used for high-throughput MAPS/MASS for blush in peach.The molecular tools developed in this study will facilitatebreeding efficiency in the development of future peach culti-vars with desirable levels of blush by complementing tradi-tional breeding methods. Informed parental and seedling se-lection will reduce the expenditure of valuable resources suchas time, money, and space and provide new peach cultivars toever evolving consumer and industry demands.

Acknowledgments This work was supported by NIFA/USDA underproject number SC-1700382 and technical contribution No. 6099 of theClemson University Experiment Station. This work was partially fundedby USDA’s National Institute of Food and Agriculture—Specialty CropResearch Initiative project, “RosBREED: Enabling marker-assistedbreeding in Rosaceae” (2009-51181-05808).

Data Archiving Statement ZC2 linkage map and QTL positions areavailable on Genome Database for Rosaceae (www.rosaceae.org).

References

Ahmad R, Parfitt DE, Fass J, Ogundiwin E, Dhingra A, Gradziel TM, LinDW, Joshi NA, Martinez-Garcia PJ, Crisosto CH (2011) Wholegenome sequencing of peach (Prunus persica L.) for SNP identifi-cation and selection. BMC Genomics 12:1471–2164

Allan AC, Hellens RP, Laing WA (2008) MYB transcription factors thatcolour our fruit. Trends Plant Sci 13:99–102

Altschul SF, Madden TL, Schäffer AA, Jinghui Z, Zheng Z, Webb M,Lipman DJ (1997) Gapped BLAST and PSI-BLAST: a new gener-ation of protein database search programs. Nucleic Acids Res 25:3389–3402

Arazana MJ, Illa E, Howard W, Arus P (2012) A first insight into peach[Prunus persica (L.) Batsch] SNP variability. Tree Genet Genomes8:1359–1369

Tree Genetics & Genomes

Arus P, Verde I, Sosinksi B, Zhebentyayeva T, Abbott A (2012) Thepeach genome. Tree Genet Genomes 8:531–547

Balasundram N, Sundram K, Samman S (2006) Phenolic compounds inplants and agri-industrial by-products: antioxidant activity, occur-rence, and potential uses. Food Chem 99:191–203

Ban Y, Honda C, Hatsuyama Y, Igarashi M, Bessho H, Moriguchi T(2007) Isolation and functional analysis of a MYB transcriptionfactor gene that is a key regulator for the development of redcoloration in apple skin. Plant Cell Physiol 48:958–970

Beckman TG, Sherman WB (2003) Probable qualitative inheritance offull red skin color in peach. HortSci 38:1184–1185

Beckman TG, Alcazar JR, ShermanWB,Werner DJ (2005) Evidence forqualitative suppression of red skin color in peach. HortSci 40:523–524

Bliss FA (2010) Marker-assisted breeding in horticultural crops. ActaHort 859:339–350

Brody JR and Kern SE (2004) Sodium boric acid: a Tris-free, coolerconductive medium for DNA electrophoresis. Biotechniques 36:214-216

Byrne DH (2005) Trends in stone fruit cultivar development. HortTechnol 15:494–500

Byrne DH, Nikolic AN, Burns EE (1991) Variability in sugars, acids,firmness, and color characteristics of 12 peach genotypes. J AmerSoc Hort Sci 116:1004–1006

Byrne DH, Vizzotto M, Cisneros-Zevallos L, Ramming D, Okie WR(2004) Antioxidant content of peach and plum genotypes. HortSci39:798

Cantín CM, Moreno MA, Gogorcena Y (2009) Evaluation of the antiox-idant capacity, phenolic compounds, and vitamin C content ofdifferent peach and nectarine [Prunus persica (L.) Batsch] breedingprogenies. J Agric Food Chem 57:4586–4592

Cantín CM, Crisosto CH, Ogundiwin EA, Gradziel T, Torrents J, MorenoMA, Gogorcena Y (2010) Chilling injury susceptibility in an intra-specific peach [Prunus persica (L.) Bastch] progeny. PostharvestBiol Technol 58:79–87

Cevallos-Casals BA, Byrne D, Okie WR, Cisneros-Zevallos L (2006)Selecting new peach and plum genotypes rich in phenolic com-pounds and enhanced functional properties. Food Chem 96:273–280

Chang S, Tan C, Frankel EN, Barrett DM (2000) Low density lipoproteinantioxidant activity of phenolic compounds and polyphenol oxidaseactivity in selected clingstone peach cultivars. J Agric Food Chem48:147–151

Chagné D, Carlisle CM, Blond C, Volz RK,Whitworth CJ, Oraguzie NC,Crowhurst RN, Allan AC, Espley RV, Hellens RP, Gardiner SE(2007) Mapping a candidate gene (MdMYB10) for red flesh andfoliage colour in apple. BMC Genomics 8:212

Chagné D, Lin-Wang K, Espley RV, Volz RK, How NM, Rouse S,Brendolise C, Carlisle CM, Kumar S, Silva ND, Micheletti D,McGhie T, Crowhurst RN, Storey RD, Velasco R, Hellens RP,Gardiner SE, Allan AC (2013) An ancient duplication of appleMYB transcription factors is responsible for novel red fruit-fleshphenotypes. Plant Physiol 161:225–239

Chaparro JX, Werner DJ, Omalley D, Sederoff RR (1994) Targetedmapping and linkage analysis of morphological isozyme, andRAPD markers in peach. Theor Appl Genet 87:805–815

Delwiche MJ, Baumgardner RA (1983) Ground color measurements ofpeach. J Amer Soc Hort Sci 108:1012–1016

DelwicheMJ, Baumgardner RA (1985) Ground color as a peach maturityindex. J Amer Soc Hort Sci 110:53–57

Dirlewanger E, Graziano E, Joobeur T, Garriga-Caldere F, Cosson P,Howad W, Arus P (2004) Comparative mapping and marker-assisted selection in Rosaceae fruit crops. PNAS 101:9891–9896

Eduardo I, Chietera G, Pirona R, Pacheco I, Troggio M, Banchi E, BassiD, Rossini L, Vecchietti A, Pozzi C (2012) Genetic dissection ofaroma volatile compounds from the essential oil of peach fruit: QTL

analysis and identification of candidate genes using dense SNPmaps. Tree Genet Genomes. doi:10.1007/s11295-012-0546-z

Espley RV, Hellens RP, Putterill J, Stevenson DE, Kutty-Amma S,Allan AC (2007) Red colouration in apple fruit is due to theactivity of the MYB transcription factor, MdMYB10. Plant J 49:414–427

Espley RV, Brendolise C, Chagné D, Kutty-Amma S, Green S, Volz R,Putterill J, Schouten HJ, Gardiner SE, Hellens RP, Allan AC (2009)Multiple repeats of a promoter segment causes transcription factorautoregulation in red apples. Plant Cell 21:168–183

Fan S, Bielenberg DG, Zhebentyayeva TN, Reighard GL, Okie WR,Holland D, Abbott AG (2010) Mapping quantitative trait loci asso-ciated with chilling requirement, heat requirement and bloom date inpeach (Prunus persica). New Phytol 185:917–930

Frett TJ, Gasic K, Clark JR, Byrne D, Gradziel T, Crisosto C (2012)Standardized phenotyping for fruit quality in peach [Prunus persica(L.) Batsch]. J Amer Pomological Soc 66(4):214–219

Gil MI, Tomás-Barberán FA, Hess-Pierce B, Kader AA (2002)Antioxidant capacities, phenolic compounds, carotenoids, and vita-min C contents of nectarine, peach, and plum cultivars fromCalifornia. J Agric Food Chem 50:4976–4982

Gorinstein S, Martin-Belloso O, Lojek A, ČížM, Soliva-Fortuny R, ParkY-S, Caspi A, Libman I, Trakhtenberg S (2002) Comparative con-tent of some phytochemicals in Spanish apples, peaches and pears. JSci Food Agric 82:1166–1170

Holton TA, Cornish EC (1995) Genetics and biochemistry of anthocyaninbiosynthesis. Plant Cell 7:1071–1083

Howad W, Yamamoto T, Dirlewanger E, Testolin R, Cosson P, CiprianiG,Monforte AJ, Georgi L, Abbott AG, Arus P (2005)Mappingwitha few plants: using selective mapping for microsatellite saturation ofthe Prunus reference map. Genet 171:1305–1309

Hsia CL, Luh BS, Chichester CO (1965) Anthocyanin in freestonepeaches. J Food Sci 30:5

Illa E, Eduardo I, Audergon J, Barale F, Dirlewanger E, Li X, Moing A,Lambert P, Le Dantec L, Gao Z, Poessel J-L, Pozzi C, Rossini L,Vecchietti A, Arus P, HowadW (2011) Saturating the Prunus (stonefruits) genome with candidate genes for fruit quality. Mol Breed 28:667–682

Jansen RC, Stam P (1994) High resolution of quantitative traits intomultiple loci via interval mapping. Genet 136:1447–1455

Jauregui B, de Vicente MC, Messeguer R, Felipe A, Bonnet A, SalessesG, Arus P (2001) A reciprocal translocation between ‘Garfi’ almondand ‘Nemared’ peach. Theor Appl Genet 102:1169–1176

Jung S, Cestaro A, Troggio M, Main D, Zheng P, Cho I, Folta KM,Sosinski B, Abbott A, Celton J-M, Arus P, Shulaev V, Verde I,Morgante M, Rokhsar DS, Velasco R, Sargent DJ (2012) Wholegenome comparisons ofFragaria,PrunusandMalus reveal differentmodes of evolution between Rosaceous subfamilies. BMCGenomics 13:129

Kobayashi S, Goto-Yamamoto N, Hirochika H (2004) Retrotransposon-induced mutations in grape skin color. Sci 304:982

Kobayashi S (2009) Regulation of anthocyanin biosynthesis in grapes. JJapanese Soc Hort Sci 78:387–393

Kosambi D (1944) The estimation of map distances from recombinationvalues. Ann Eugen 12:172–175

Lambert P, Pascal T (2011) Mapping Rm2 gene conferring resistance tothe green peach aphid (Myzus persicaeSulzer) in the peach cultivar“Rubira®”. Tree Genet Genomes 7:1057–1068

Layne DR, Jiang ZW, Rushing JW (2001) Tree fruit reflective filmimproves red skin coloration and advances maturity in peach. HortTechnol 11:234–242

Lin-Wang K, Bolitho K, Grafton K, Kortstee A, Karunairetnam S,McGhie TK, Espley RV, Hellens RP, Allan AC (2010) An R2R3MYB transcription factor associated with regulation of the anthocy-anin biosynthetic pathway in Rosaceae. BMC Plant Biol 10:50. doi:10.1186/1471-2229-10-50

Tree Genetics & Genomes

Marini RP, Sowers D, Marini MC (1991) Peach fruit-quality is affectedby shade during final swell of fruit-growth. J Amer Soc Hort Sci116:383–389

Martinez-Garcia P, Parfitt D, Ogundiwin E, Fass J, Chan H, Ahmad R,Lurie S, Dandekar A, Gradziel T, Crisosto C (2012) High densitySNP mapping and QTL analysis for fruit quality characteristics inpeach (Prunus persica L.). Tree Genet Genomes 9:1–18. doi:10.1007/s11295-012-0522-7

McCallum S, Woodhead M, Hackett C, Kassim A, Paterson A, Graham J(2010) Genetic and environmental effects influencing fruit colourand QTL analysis in raspberry. Theor Appl Genet 121:611–627

Ogundiwin EA, Peace CP, Gradziel TM, Dandekar AM, Bliss FA,Crisosto CH (2007) Molecular genetic dissection of chilling injuryin peach fruit. Acta Hort 738:633–638

Ogundiwin EA, Peace CP, Nicolet CM, Rashbrook VK, Gradziel TM,Bliss FA, Parfitt D, Crisosto CH (2008) Leucoanthocyanidindioxygenase gene (PpLDOX): a potential functional marker for coldstorage browning in peach. Tree Genet Genomes 4:543–554

Ogundiwin EA, Peace CP, Gradziel TM, Parfit DE, Bliss FA, CrisostoCH (2009) A fruit quality gene map of Prunus. BMC Genomics 10:587

Okie WR, Bacon T, Bassi D (2008) Fresh market cultivar development.In: Layne DR, Bassi D (eds) The peach, botany, production anduses. CABI, Cambridge, pp 139–174

Parr AJ, Bolwell GP (2000) Phenols in the plant and inman. The potentialfor possible nutritional enhancement of the diet by modifying thephenols content or profile. J Sci Food Agric 80:985–1012

Quilot B,WuBH, Kervella J, GenardM, FoulongneM,MoreauK (2004)QTL analysis of quality traits in an advanced backcross betweenPrunus persica cultivars and the wild relative species P. davidiana.Theor Appl Genet 109:884–897

Rozen S, Skaletsky H (2000) Primer3 on theWWW for general users andfor biologist programmers. In: Krawetz S, Misener S (eds)Bioinformatics Methods and Protocols: Methods in MolecularBiology. Humana Press, Totowa, NJ, USA, pp 365–386

Sargent DJ, Marchese A, Simpson DW, HowadW, Fernandez-FernandezF, Monfort A, Arus P, Evans KM, Tobutt KR (2009) Developmentof “universal” gene-specific markers from Malus spp. cDNA se-quences, their mapping and use in synteny studies within Rosaceae.Tree Genet Genomes 5:133–145

Schijlen EGWM, Ric de Vos CHR, van Tunen AJ, Bovy AG (2004)Modification of flavonoid biosynthesis in crop plants. Phytochem65:2631–2648

Scorza R, Sherman WB (1996) Peaches. In: Janick J, Moore JN (eds)Fruit Breeding. Wiley, New York, pp 325–440

Shulaev V, Korban SS, Sosinski B, Abbott AG, Aldwinckle HS, FoltaKM, Iezzoni A, Main D, Arus P, Dandekar AM, Lewers K, BrownSK, Davis TM, Gardiner SE, Potter D, Veilleux RE (2008) Multiplemodels for Rosaceae genomics. Amer Soc Plant Biologists 147:985–1003

Sosinski B, Shulaev V, Dhingra A, Kalyanaraman A, Bumgarner R,Rokhsar D, Verde I, Velasco R, Abbott AG (2009) Rosaceaousgenome sequencing: perspectives and progress. In: Folta KM,Gardiner SE (eds) Genetics and genomics of Rosaceae. Springer,New York, pp 601–615

Sooriyapathirana SS, Khan A, Sebolt AM, Wang D, Bushakra JM, Lin-WangK, Allan AC, Gardiner SE, Chagné D, Iezzoni AF (2010) QTLanalysis and candidate genemapping for skin and flesh color in sweetcherry fruit (Prunus avium L.). Tree Genet Genomes 6:821–832

Sun J, Chu Y-F, Wu X, Liu RH (2002) Antioxidant and antiproliferativeactivities of common fruits. J Agric Food Chem 50:7449–7454

Takos AM, Jaffe FW, Jacob SR, Bogs J, Robinson SP, Walker AR (2006)Light-induced expression of a MYB gene regulates anthocyaninbiosynthesis in red apples. Plant Physiol 142:1216–1232

Tomás-Barberán FA, Gil MI, Cremin P, Waterhouse AL, Hess-Pierce B,Kader AA (2001) HPLC-DAD-ESIMS analysis of phenolic com-pounds in nectarines, peaches, and plums. J Agric Food Chem 49:4748–4760

Van Blaricom LO, Senn TL (1967) Anthocyanin pigments in freestonepeaches grown in the southeast. Proc Amer Soc Hort Sci 90:541

van de Weg WE, Voorips RE, Finkers HJ, Kodde LP, Jansen J, Bink M(2004) Pedigree genotyping: a new pedigree based approach of QTLidentification and allele mining. Acta Hort 663:45–50

Van Ooijen JW (2006) JoinMap® 4.0, software for the calculation ofgenetic linkage maps in experimental populations. Kyazma BV,Wageningen, Netherlands

Verde I, Bassil N, Scalabrin S, Gilmore B, Lawley CT, Gasic K,Micheletti D, Rosyara UR, Cattonaro F, Vendramin E, Main D,Aramini V, Blas AL, Mockler TC, Bryant DW, Wilhelm L,Troggio M, Sosinski B, Aranzana MJ, Arus P, Iezzoni A,Morgante M, Peace C (2012) Development and evaluation of a9 K SNP array for peach by internationally coordinated SNP detec-tion and validation in breeding germplasm. PLoS ONE 7:1–13

Vizzotto M, Cisneros-Zevallos L, Byrne DH, Ramming DW, Okie WR(2006) Total phenolic, carotenoid, and anthocyanin content andantioxidant activity of peach and plum genotypes. Acta Hort 713:453–456

Vizzotto M, Cisneros-Zevallos L, Byrne DH, Ramming DW, Okie WR(2007) Large variation found in the phytochemical and antioxidantactivity of peach and plum germplasm. J Amer Soc Hort Sci 132:334–340

Voorrips RE (2002)MAPCHART: software for the graphical presentationof linkage maps and QTLs. J Hered 93:77–78

Walker AR, Lee E, Bogs J, McDavid DAJ, Thomas MR, Robinson SP(2007) White grapes arose through the mutation of two similar andadjacent regulatory genes. Plant J 49:772–785

Wang S, Basten CJ, Zeng ZB (2007) Windows QTL cartographer 25.Department of Statistics, North Carolina State University, Raleigh

WuXL, Prior RL (2005) Systematic identification and characterization ofanthocyanins byHPLC-ESI-MS/MS in common foods in the UnitedStates: fruits and berries. J Agric Food Chem 53:2589–2599

Yamamoto T, Shimada T, Imai T, Yaegaki T, Haji T, Matsuta N,Yamaguchi M, Hyashi T (2001) Characterization of morphologicaltraits based on a genetic linkagemap in peach. Breeding Sci 51:271–278

Yang N, Reighard GL, Ritchie D, Okie WR, Gasic K (2012) Mappingquantitative trait loci associated with resistance to bacterial spot(Xanthomonas arboricola pv. pruni) in peach. Tree GenetGenomes. doi 10.1007/s11295-012-0580-x

Zeng ZB (1994) Precision mapping of quantitative trait loci. Genet 136:1457–1468

Zorrilla-Fontanesi Y, Cabeza A, Domınguez P, Medina JJ, Valpuesta V,Denoyes-Rothan S-SJF, Amaya I (2011) Quantitative trait loci andunderlying candidate genes controlling agronomical and fruit qual-ity traits in octoploid strawberry (Fragaria x ananassa). Theor ApplGenet 123:755–778

Zhu C, Gore M, Buckler ES, Yu J (2008) Status and prospects ofassociation mapping in plants. The Plant Genome 1:5–20

Tree Genetics & Genomes