Tree Genetics & Genomes

, 12:121 | Cite as

Identifying SNP markers tightly associated with six major genes in peach [Prunus persica (L.) Batsch] using a high-density SNP array with an objective of marker-assisted selection (MAS)

  • Patrick Lambert
  • Jose Antonio Campoy
  • Igor Pacheco
  • Jehan-Baptiste Mauroux
  • Cassia Da Silva Linge
  • Diego Micheletti
  • Daniele Bassi
  • Laura Rossini
  • Elisabeth Dirlewanger
  • Thierry Pascal
  • Michela Troggio
  • Maria Jose Aranzana
  • Andrea Patocchi
  • Pere Arús
Original Article
Part of the following topical collections:
  1. Complex Traits

Abstract

One of the applications of genomics is to identify genetic markers linked to loci responsible for variation in phenotypic traits, which could be used in breeding programs to select individuals with favorable alleles, particularly at the seedling stage. With this aim, in the framework of the European project FruitBreedomics, we selected five main peach fruit characters and a resistance trait, controlled by major genes with Mendelian inheritance: fruit flesh color Y, fruit skin pubescence G, fruit shape S, sub-acid fruit D, stone adhesion-flesh texture F-M, and resistance to green peach aphid Rm2. They were all previously mapped in Prunus. We then selected three F1 and three F2 progenies segregating for these characters and developed genetic maps of the linkage groups including the major genes, using the single nucleotide polymorphism (SNP) genome-wide scans obtained with the International Peach SNP Consortium (IPSC) 9K SNP array v1. We identified SNPs co-segregating with the characters in all cases. Their positions were in agreement with the known positions of the major genes. The number of SNPs linked to each of these, as well as the size of the physical regions encompassing them, varied depending on the maps. As a result, the number of useful SNPs for marker-assisted selection varied accordingly. As a whole, this study establishes a sound basis for further development of MAS on these characters. Additionally, we also discussed some limitations that were observed regarding the SNP array efficiency.

Keywords

Molecular breeding Fruit quality Genetic map Phenotyping Mendelian character 

Introduction

Peach [Prunus persica (L.) Batsch] is the second predominant temperate tree fruit species with 21.6 million tons of peaches and nectarines produced worldwide (FAOSTAT 2013, http://faostat3.fao.org/). It is one of the genetically best-characterized species in the Rosaceae family (Bassi and Monet 2008). As a result, the inheritance of numerous morphological characters behaving as major genes is well known (Lesley 1940; Bayley and French 1949; Yoshida 1970; Chaparro et al. 1994; Monet et al. 1996; Warburton et al. 1996; Dettori et al. 2001; Bliss et al. 2002; Pascal et al. 2002) and more than 25 of them have been mapped (Dirlewanger et al. 2004; Gillen and Bliss 2005: Lambert et Pascal 2011; Arús et al. 2012; Shen et al. 2013). Despite that, the selection of genetically superior seedlings remains laborious as traditional seedling selection is empirical and primarily based on phenotypic information, which impedes the breeding process when several characters have to be combined (Ru et al. 2015). Moreover, the narrow genetic background of the cultivated peach of American and European origins is a major drawback for the selection of innovative cultivars (Aranzana et al. 2010). Including other genetic pools in the breeding programs (i.e., that from other close related species or nonimproved accessions) could increase the available variability; however, this could also drag undesirable traits or horticultural defects that should be eliminated through several recurrent crosses (Bassi and Monet 2008). Therefore, there is a demand from breeders for cost-effective methods enabling reliable early selection of seedlings that carry desirable traits or allowing discarding those with poor potential. Methods based on molecular genetics, the identification of molecular markers linked to traits of interest, and screenings of seedlings at an early stage would allow selecting individuals several years before the characters can be evaluated in the field (Luby and Shaw 2001; Dirlewanger et al. 2004; Peace and Norelli 2009; Bliss 2010; Salazar et al. 2014). However, marker-assisted selection (MAS) has been slowly translated into routine practical application in plant breeding (Edge-Garza et al. 2010; Muranty et al. 2014; Ru et al. 2015) and only for a small number of major genes in peach (Lambert et al. 2009; Iezzoni et al. 2010; Arús et al. 2012; RosBREED: https://www.rosbreed.org/breeding) due to the low number of available efficient markers and the lack of high-throughput cost-effective methods.

In the last 10 years, the comparatively small genome size (225.7 Mbp) of peach, coupled with expanding available genomic resources, has led this species to be considered as a model within the Prunus fruit trees (Shulaev et al. 2008; Abbott et al. 2008; Pozzi and Vecchietti 2009) and, to some extent, within the Rosaceae family (Dirlewanger et al. 2004; Arús et al. 2006; Zhebentyayeva et al. 2008). In the meantime, the Genome Database for Rosaceae (GDR: https://www.rosaceae.org/species/prunus_persica) has gathered numerous molecular resources, among which the peach genome sequence v1.0 (The International Peach Genome Initiative 2013) and its improved version v2.0 (Verde et al. 2015; https://www.rosaceae.org/species/prunus_persica/genome_v2.0.a1). Additionally, the increasing number of genomic sequence datasets obtained from next-generation sequencing of additional peach accession genomes (Ahmad et al. 2011; Verde et al. 2012; Cao et al. 2014) has made possible the genome-scale identification of a large number of single nucleotide polymorphisms (SNPs) which are particularly suitable for high-throughput genome-wide genotyping. In this context, the release of a high-throughput peach SNP array by the International Peach SNP Consortium (IPSC), referred to as the IPSC 9K SNP array v1 (Verde et al. 2012) presented an opportunity to translate genome-based information into tools to facilitate breeding efforts. This array included a selection of 8144 SNPs distributed over the eight chromosomes most of which being polymorphic across large collections of peach accessions (Verde et al. 2012; Micheletti et al. 2015). It has allowed the implementation of ambitious collaborative projects (Iezzoni et al. 2010; Laurens et al. 2010), including the European project FruitBreedomics (Laurens et al. 2010), within which this study has been carried out. The project aimed at providing breeders with methods and SNP markers linked to major agronomic traits in order to implement high-throughput selection. With this objective and concurrently with a genome-wide association study (Micheletti et al. 2015), we conducted a mapping approach based on the IPSC 9K SNP array v1 and six segregating progenies, and targeted five major fruit characters controlled by genes with Mendelian inheritance (Monet et al. 1996): fruit flesh color Y, fruit skin pubescence G, fruit shape S, sub-acid fruit character D, stone adhesion-flesh texture F-M, and a major resistance trait, resistance to green peach aphid (Myzus persicae Sulzer) Rm2. All these traits have been previously mapped (Dirlewanger et al. 2004, 2006; Boudehri et al. 2009; Lambert and Pascal 2011; Arús et al. 2012) and for three of them (F-M, G, and Y), candidate genes have been identified (Peace et al. 2005; Ogundiwin et al. 2009; Adami et al. 2013; Falchi et al. 2013; Vendramin et al. 2014; Gu et al. 2016). The objective of this work was to construct high-density SNP-based genetic maps of the regions containing the major genes and to identify SNPs tightly associated with each of these genes that could be used, individually, or as haplotypes, for the further implementation of MAS.

Material and methods

Plant material

In this study, three F1 and three F2 peach progenies segregating for fruit quality or resistance traits were used for the construction of the genetic maps.

The first (Bb × Nl), with 95 seedlings, was an F1 progeny derived from ‘Belbinette®’, a white-fleshed peach, and ‘Nectalady’, a yellow-fleshed nectarine. This progeny segregates for Y and G. It was planted in the fields at the IRTA Experimental Station at Gimenells (Lleida, Spain).

The second (B × O), with 124 seedlings, was an F1 progeny (Eduardo et al. 2013) derived from the cross between ‘Bolero’ (syn. ‘BO78007001’, from the cross ‘Cresthaven’ × ‘Flamecrest’, University of Bologna breeding program), a freestone melting, yellow-fleshed peach, heterozygous for melting character, and OroA (syn. ‘Fla.84-12C’, from open pollination of ‘Diamante’, University of Florida/Chapingo breeding program) a clingstone nonmelting, yellow-fleshed peach. This progeny segregates for melting/nonmelting character and consequently for F-M. It is located on the ASTRA experimental orchards at Tebano (Faenza, northern Italy) as well as the following two progenies.

The third (M × R028), with 69 seedlings, was issued from an F1 cross between Max 10 (from the cross ‘Venus op’ × ‘Venus’, from an Italian private breeding program), a melting, acid, yellow fleshed nectarine and Rebus 028 (syn. ‘BO96003028’, from the cross ‘Big Top®’ × ‘Mayfire’, MasPES Italian Breeding program), a slow-softening, sub-acid, yellow-fleshed nectarine. This progeny segregates for D.

The fourth (W × By), with 92 seedlings, was an F2 progeny (Da Silva et al. 2015) derived from the cross between ‘NJ Weeping’ (PI91459), an ornamental peach probably from Japanese germplasm, with freestone, melting white-fleshed fuzzy fruits, and ‘Bounty’, a freestone, melting, yellow-fleshed peach from USDA West Virginia-Maryland breeding program. This progeny segregates for Y and F-M.

The fifth (J × F), with 138 seedlings, was an F2 progeny from the cross between ‘Ferjalou Jalousia®’, a clingstone-melting, sub-acid fruit cultivar producing flat peaches, and ‘Fantasia’, a freestone, melting acid fruit cultivar producing round nectarines. This progeny segregates for four Mendelian characters analyzed in this study (F-M, D, G, and S). It is located on the experimental orchard of the INRA Unité Expérimentale Arboricole, Domaine des Jarres (Toulenne, France).

The last progeny (P × R), with 98 seedlings, was issued from an F2 cross between ‘Pamirskij 5’ (clone S6146), a green-leaf rootstock peach derived from seeds obtained from the Nikita Botanical Garden of Yalta (Crimea, Ukraine), and ‘Rubira®’, a red-leaf rootstock peach resistant to green peach aphid (M. persicae Sulzer). This progeny segregates for resistance to green peach aphid Rm2. It was planted in the INRA experimental orchard “Les Garrigues” (Montfavet, France). Crosses and parent description are listed in Table 1.
Table 1

Crosses and parent description

Cross

Type of cross

Parent

Parent phenotype

Genotype

Bb × Nl

F1

Belbinette®

White flesh

Y/y

   

Fuzzy skin (peach)

G/g

  

Nectalady

Yellow flesh

y/y

   

Glabrous skin (nectarine)

g/g

B × O

F1

Bolero

Freestone-melting

F/f1

  

OroA

Clingstone-nonmelting

f1/f1

M × R028

F1

Max_10

Acid

d/d

  

Rebus_028

Sub-acid

D/d

W × By

F2

NJ Weeping

Freestone-melting

F/f

   

White flesh

Y/Y

  

Bounty

Freestone-melting

F/f1

   

Yellow flesh

y/y

J × F

F2

Ferjalou Jalousia®

Sub-acid

D/D

   

Clingstone-melting

f/f

   

Fuzzy skin

G/g

   

Flat fruit

S/s

  

Fantasia

Acid

d/d

   

Freestone-melting

F/f

   

Glabrous skin (nectarine)

g/g

   

Round fruit

s/s

P × R

F2

Pamirskij 5

Susceptible to Myzus persicae

rm2/rm2

  

Rubira®

Resistant to Myzus persicae

Rm2//Rm2

Parent attributes are those segregating in their respective progenies

Trait description and candidate genes

Five major Mendelian fruit characters, Y, F-M, D, G, and S, and a major resistance trait, Rm2, were studied. Their characteristics and progenies in which they segregated are listed in Table 2. Y, D, S, and Rm2 segregate as bi-allelic dominant characters. For G, flat-fruit shape is caused by a dominant allele in obligated heterozygosity as the homozygous variant is responsible for fruit abortion (Dirlewanger et al. 2006). For F-M, four alleles have been described: F (Freestone-melting flesh), dominant over the other three alleles, f (clingstone-melting flesh), f1 (clingstone-non melting flesh), and f2 (clingstone-non softening flesh); f is dominant over f1 and f2, and f1 is dominant over f2. Intermediate phenotypes may also be observed in some heterozygous individuals that may make sensory classification of fruit type confusing (Bayley and French 1949).
Table 2

Trait information, progenies in which they segregate and maps constructed from SNP segregation

Trait

Trait variation

Dominant phenotype

Locus name

Linkage group

Segregating progeny

Genetic map constructed

Fruit flesh color

White/yellow

White

Y

G1

Bb × Nl, W × By

Bb, W × By

Resistance to green peach aphid

Resistant/susceptible

Resistant

Rm2

G1

P × R

P × R

Stone adhesion-flesh texture

Freestone/clingstone-melting/nonmelting

Freestone-melting

F-M

G4

J × Fb, B × Oc, W × Byc

J × F, B, W × By

Sub-acid fruit

Sub-acid/acid

Sub-acid

D

G5

J × F, M × R028

J × F, R028

Fruit skin pubescence

Fuzzy (peach)/glabrous skin (nectarine)

Fuzzy

G

G5

J × F, Bb × N

J × F, Bb

Fruit shape

Flat/round

Flata

S

G6

J × F

J × F

Y for yellow, Rm2 for resistance to Myzus persicae, F-M for freestone-melting flesh, D for French “doux,” meaning sweet, G for glabrous, S for saucer-shape

aSeedlings homozygous for S produce aborting fruits

bJ × F did not segregate for melting/nonmelting fruit texture

cStone adhesion was not evaluated in B × O and W × By

For three of the traits, candidate genes have been already reported. This is the case of Y, G, and F-M. PpCCD4, a carotenoid cleavage dioxygenase enzyme located on G1 was shown to correspond to the Y locus with three different loss-of-function mutations resulting in yellow flesh: one in a microsatellite, EPPISF025 (Vendramin et al. 2007), located in the 5′ UTR of PpCCD4, another corresponding to a SNP and the last one to the insertion of a transposable element (Adami et al. 2013; Falchi et al. 2013). A retro-transposon insertion in the MYB gene PpeMYB25 located on G5 has been associated to the recessive nectarine character (Vendramin et al. 2014). Freestone/clingstone and melting/nonmelting flesh characters are associated to copy-number variants of two tandemly duplicated endopolygalacturonase genes (endoPG) located at the bottom of G4 (Peace et al. 2005; Ogundiwin et al. 2009; Gu et al. 2016).

In order to identify the closest SNPs from the candidate genes, the sequences of the transcripts of PpCCD4 (Y), PpeMYB25 (G), PpendoPGF, and PpendoPGM (F-M) were retrieved from the GDR (http://www.rosacea.org) based on their previous names in peach v1.0 (ppa006109m, ppa023143m, ppa021953m, and ppa025787m, respectively). Their updated coordinates on peach v2.0 and names were identified by using BLAST on peach v2.0. Likewise, the updated coordinates of EPPISF025 were identified using the sequence of the primer pair used to amplify the fragment containing the SSR (Falchi et al. 2013).

Plant phenotyping and scoring

Plant phenotyping was carried out at maturity, on homogeneous samples of ten fruits picked 3 days after the first day of physiological ripening, defined as 2–3% eating-ripe fruits and no split pit. Fruit acidity was phenotyped by measuring the pH of a mixture of equal volumes of juices from the ten fruits representative of each seedling. Seedlings were then classified as sub-acid for pH equal and higher than 3.9, and as acid below this threshold, defined from previous studies (Dirlewanger et al. 2006; Boudehri et al. 2009). The other four fruit characters were distinguished visually or by sensory evaluation. For stone adhesion, freestone/clingstone variants were distinguished by cutting fruits in two halves, and observing stone adhesion to the flesh. Flesh texture (melting/nonmelting) was phenotyped by sensory evaluation. Flesh texture was not segregating in J × F. As a result, only stone adhesion was evaluated in this progeny. Various degrees of adhesion were observed in B × O and W × By, leading to confusing data. As a result, only flesh texture was evaluated in these progenies. Finally, P × R seedlings were classified as resistant or susceptible to green peach aphid as in Lambert and Pascal (2011).

DNA isolation and SNP genotyping

Samples of young leaves from the parents and the mapping progenies were collected in spring. Genomic DNA of the parents and of the seedlings was isolated using the Qiagen DNeasy 96 or Mini Plant Kit® (Quiagen, MD, USA), according to the protocol provided by the supplier. DNA quantification was performed for each sample using Quant-iT™ Picogreen® reagent (Invitrogen Ltd., Paisley, UK). Genomic DNAs were then diluted to a final concentration of 50 ng/μl. Each sample was genotyped at IASMA, San Michele All’adige Trento, Italy, using the IPSC peach 9K SNP array v1 (Verde et al. 2012). DNAs were assayed following the manufacturer’s recommendations. Bead chips were imaged, and raw genotyping data were collected using a HiScan detection platform (Illumina Inc., San Diego, CA, USA). SNP genotypes were then scored with the Genotyping Module of Genome Studio Data Analysis software (Illumina Inc. San Diego, CA, USA) using the default parameters. SNPs with GenTrain higher than 0.4, GeneCall 10% higher than 0.2 and showing at least two genotypic classes were classified as polymorphic. They were then classified as A, B, and C as follows:
  • A: SNPs with less than 5% of No Call (failed genotyping) and all possible genotypes defined according to the type of cross (AA, AB for F1 or AA, AB, BB for F2).

  • B: SNPs with a potential null allele or preferential annealing. Between 5 and 50% of individuals showed a normalized signal-intensity value R < 0.2, and the remaining individuals represented at least two of the three genotypic classes.

  • C: Probable presence of duplicated sequences/genes. These SNPs were characterized by the absence of one homozygous cluster in F2 progenies with an overrepresentation of heterozygous individuals, and a percentage of No Call <5%.

Then, segregations were tested for conformity to the expected ratio using the chi-squared goodness-of-fit test, and those SNPs showing a very strong distortion (p value = 0.001) were discarded. Filtered and formatted data were used to construct the genetic linkage maps.

Map construction

For B × O and W × By progenies, we used the SNP datasets from Eduardo et al. (2013) and Da Silva Linge et al. (2015) to construct the linkage groups including the major-gene regions. For the other four progenies (M × R028, Bb × Nl, J × F, and P × R), only those SNPs with 2% or less of missing data were considered for mapping. In addition, six and 14 SSRs were included in the Bb × Nl and J × F datasets, respectively, among which EPPISF025. For all the progenies, phenotypic markers were coded as dominant markers according to the coding system of the software used for mapping.

For Bb × Nl, linkage analyses were performed with Mapmaker/exp 3.0 (Lincoln et al. 1992). Parental maps were analyzed separately using a pseudo testcross model (Grattapaglia and Sederoff 1994). Recombination fraction value was set at 0.4, and groups were established with a minimal LOD score of 4.0. Separate maps were developed for each of the parents. The Kosambi mapping function (Kosambi 1944) was used for calculating genetic distances as well as for the other maps below. For the other progenies (B × O, M × R028, W × By, J × F, and P × R), linkage analyses were performed with JoinMap 4.1 (Van Ooijen 2006). Genotypic data derived from the F1 crosses were coded as out-breeder full-sib family (CP) populations (Van Ooijen 2006), and each parental map was constructed using “Create maternal and paternal progeny nodes” option. At first, quality of markers was checked and those with high probabilities of genotyping errors were discarded. In order to make map construction easier, the function “Assign identical loci to their groups” was used. As a result, a maximum of two SNP per map position was represented with the exception of the regions containing major genes as well as the two flanking loci at either side, for which all co-segregating SNPs were included. Linkage groups were then constructed using maximum likelihood mapping algorithm (Jansen et al. 2001) and three rounds per sample. Group nodes were defined by a LOD value of 10.0. For the F2 crosses, methodology was similar as above except that genotypic data were coded as F2 progeny-type according to the JoinMap coding system. Information on the physical positions of the SNPs on the pseudomolecules/scaffolds of peach genome sequence v2.0 was used to check their correct positioning on the linkage groups (GDR: https://www.rosaceae.org/species/prunus_persica/genome_v2.0.a1). Peach genome sequence v2.0 will be hereunder referred to as peach v2.0. Map figures were drawn using MapChart software (Voorips 2002).

Results

SNP polymorphism

We used the IPSC 9K SNP array v1 to genotype six mapping populations. In total, 2012 SNPs out of 8144 failed (24.7%) and 877 were monomorphic (10.8%) in all the progenies. As a consequence, 5255 SNPs (64.5%) were useful for map construction. In addition, 224 SNPs among the latter (2.75% of the total) were monomorphic or failed in one or several of the progenies. For the six progenies, the overall rate of polymorphic SNPs in the peach v2.0 pseudomolecules/scaffolds ranged from 60.3% in Pp02 to 67.22% in Ppo6 with an average of 64.53% (Table 3). Average SNP distributions in the scaffolds ranged from 14.8 SNP/Mbp in Pp01 to 35.5 SNP/Mbp in Pp04 with an overall average of 23.3 SNP/Mbp (Table 3). Based on the genetic distances of the T × E reference map for Prunus in GDR, SNP distributions were comprised between 7.4 SNP/cM in G5 and 17.7 SNP/cM in G2 (Table 3).
Table 3

Distribution of the SNPs included in the ISPC peach 9K SNP array v.1 according to their updated positions in the peach v2.0 pseudomolecules/scaffolds, their polymorphism in the progenies of the study, and the reference map for Prunus (T × E)

Peach v2.0 scaffolds

Scaffold size (bp)

T × E linkage-group length (cM)a

Total SNPs in the array

SNPs failed in all the progenies

SNPs monomorphic in all the progenies

Total SNPs polymorphic in the study

% polymorphic SNPs vs total (8144) SNPs

Avg no. of polymorphic SNP/Mbp

Avg no. of polymorphic SNP/cM

Pp01

47,851,208

87

1120

201

211

708

63.21

14.8

8.1

Pp02

30,405,870

50.3

1474

437

148

889

60.31

29.2

17.7

Pp03

27,368,013

48.4

874

190

98

586

67.05

21.4

12.1

Pp04

25,843,236

62.5

1462

391

102

969

66.28

37.5

15.5

Pp05

18,496,696

49.1

546

134

49

363

66.48

19.6

7.4

Pp06

30,767,194

83.7

961

222

93

646

67.22

21

7.7

Pp07

22,388,614

70.6

791

189

71

531

67.13

23.7

7.5

Pp08

22,573,980

55.9

915

248

104

563

61.53

24.9

10.1

Scaf_285

 

1

0

1

0

0

0

0

Total

225,694,811

507.5

8144

2012

877

5255

64.53

23.3

10.4

aLengths of the groups of the reference map for Prunus (T × E) are those reported in GDR: http://www.rosacea.org/peach/genome. Linkage group numbers correspond to pseudomolecules/scaffold numbers

Genetic maps of the linkage groups including major genes

We used the marker datasets to construct genetic linkage maps of the four linkage groups (G1, G4, G5, and G6) including the six traits of interest (major genes) segregating in their respective progenies (Table 2). Ten genetic linkage maps were constructed for a total of 11 regions including major genes (Fig. 1): one map for each of the linkage groups and the parents of the F1 progenies heterozygous at the segregating trait loci (Bb, B, Ro28) and one map for each of the linkage groups of the F2 crosses (W × By, J × F, and P × R). The number of polymorphic SNPs varied depending on the linkage group and the progeny, ranging from 198 (Bb) to 306 (P × R) for G1, 170 (W × By) to 467 (B) for G4, and 11 (Bb) to 173 (J × F) for G5 (Table 4). As a result, polymorphism rate (percentage of polymorphic SNPs when compared with the total number of SNPs assayed per scaffold) varied from 28 to 43% for G1, 17.5 to 48.2% for G4, and 3 to 47.7% for G5. The map of G6 (J × F) included 158 SNPs which accounted for a polymorphism rate of 24.4% (Table 3). Most of the SNPs shared map positions in the linkage groups due to the absence of recombination between some of the SNPs. For G1, an average of 2.6 to 6 SNPs co-segregated at each map position in W × By and B, respectively (Table 4), and the average distance between map positions ranged from 1 cM (W × By) to 2.1 cM (P × R). For G4, the number of SNPs per map position was higher (2.6 to 9.5 in W × By and B, respectively) but for a smaller difference between the average distances between map positions (1 cM in W × By to 1.5 cM in J × F). In G5, the average number of SNPs per map position ranged from 2.2 SNPs in Bb to 5.2 in R028 and the average distance between map positions varied from a low of 1.4 cM in J × F to a high of 2.9 cM in R028. For all the linkage groups, linkage positions of the SNPs were in agreement with their physical positions as defined from the peach v2.0 pseudomolecules.
Fig. 1

Linkage maps of the regions including the major genes. All the markers co-segregating with the major genes as well as those mapped at the two flanking map positions at either side of the major-gene positions are included in their respective linkage groups. For the other map positions, when several markers co-segregate, only those at both ends in terms of physical distance are placed. SSRs are in italics. Major genes are in bold and in italics

Table 4

Description of the linkage groups containing the major genes

Genetic map

Linkage group

Polymorphic SNPs

%b

No. of map positions (SNP)a

Avg no. of SNPs/map positiona

Other markers

Total markers

No. of map positions (total)a

Map length (cM)

Average distance between map positionsa (cM)

Bb

G1

198

28

33

6

7

205

35

59.5

1.7

 

G5

11

3

5

2.2

5

16

5

9.6

1.9

P × R

G1

306

43

71

4.3

306

71

145.9

2.1

W × By

G1

253

35.7

98

2.6

253

98

102.4

1.0

 

G4

170

17.5

65

2.6

170

65

61.9

1.0

J × F

G4

327

33.7

42

7.8

15

342

57

86.9

1.5

 

G5

173

47.7

47

3.7

19

192

58

71.1

1.4

 

G6

158

24.4

52

3

15

173

62

88.4

1.4

B

G4

467

48.2

49

9.5

467

49

59.0

1.2

R028

G5

109

30

21

5.2

109

21

61.2

2.9

aMap position: single position on a genetic map where one or several co-segregating markers map

b% of polymorphic SNPs as compared to the total no. of SNPs of the 9K SNP peach array v1 that correspond to the linkage groups in column 2

Mapping of major genes

Fruit flesh color Y

Fruit flesh color segregated in two of the progenies, Bb × Nl and W × By (Fig. 1). With respect to Bb × Nl, Y mapped at 30.7 cM in G1 of Bb and co-segregated with three SNPs and EPPISF025, the SSR included in PpCCD4. The updated coordinates of PpCCD4 transcript (Prupe.1G255500) and EPPISF025, on peach v2.0, were Pp01 26,613,248–26,616,233 bp and Pp01 26,614,050–26,614,215 bp, respectively. The four markers above spanned an interval of 6,326,438 bp in peach v2.0 (Pp01 20,287,777–26,614,215) with nearly half of the distance (3,309,037 bp) between the SNP at the downstream end of the region (SNP_IGA_78954) and EPPISF025. The closest markers at the two flanking map positions (SNP_IGA_67270 and UDP96-005) framed an interval of 6,806,703 bp and 2 cM corresponding to 3.4 Mbp/cM (Table 5). This highlights a low recombination rate in the Y region of Bb as well as a high homozygosity as the interval of similar length (6.92 Mbp) between EPPISF025 and SNP_IGA_103422, the closest SNP downstream Y, spanned a much larger genetic distance of 9.7 cM (0.71 Mbp/cM). Regarding W × By, Y mapped at 50.5 cM in G1 and co-segregated with a single SNP (SNP_IGA_86918, Pp01 26,616,924 bp) that mapped 691 bp outside the 3′ UTR of PpCCD4. In this way, it marks out the 3′ boundary of the gene. This SNP could not be mapped in Bb while two of the SNPs co-segregating with Y in Bb (SNP_IGA_67620 and SNP_IGA_69306) mapped at 12.2 and 11.1 cM, respectively, upstream of Y position in the map of WxBy (Fig. 1). The upper flanking SNP, SNP_IGA_84580 (Pp01 25,541,717) was 1,071,831 bp upstream of the 5′ end of PpCCD4. No marker downstream of Y was common to both maps.
Table 5

Characteristics of the regions including the major genes in the linkage maps

Locus name

Genetic map

No. of markers at the map positiona

Peach v2.0 scaffold

Upper-boundary marker at the major-gene map positiona,b (bp)

Lower-boundary marker at the major-gene map positiona,b (bp)

Closest marker at the upper flanking map positiona,b (bp)

Closest marker at the lower flanking map positiona,b (bp)

Flanking interval length (bp)

Genetic distance (cM)

Physical. coverage (Mbp/cM)

Y

Bb

4

Pp01

SNP_IGA_67620 (20,287,777)

EPPISF025 (26,614,215)

SNP_IGA_67270 (20,223,483)

UDP96–005 (27,040,186)

6,806,703

2

3.40

 

W × By

1

Pp01

SNP_IGA_86918 (26,616,924)

SNP_IGA_86918 (26,616,924)

SNP_IGA_84580 (25,541,717)

SNP_IGA_86968 (26,640,558)

1,098,841

3.1

0.35

Rm2

P × R

6

Pp01

SNP_IGA_128189 (45,753,343)

SNP_IGA_127181 (46,012,310)

SNP_IGA_131130 (45,083,225)

SNP_IGA_126,668 (46,225,560)

1,142,335

4

0.29

F-M

B

56

Pp04

snp_4_23038297 (19,435,125)

SNP_IGA_513312 (22,613,908)

SNP_IGA_449118 (17,994,567)

SNP_IGA_529568 (24,293,092)

6,298,525

2.4

2.62

 

J × F

42

Pp04

SNP_IGA_451930 (18,593,828)

SNP_IGA_482587 (20,176,048)

SNP_IGA_449118 (17,994,567)

SNP_IGA_484030 (20,243,860)

2,249,293

2.1

1.07

 

W × By

9

Pp04

SNP_IGA_448998 (17,984,794)

SNP_IGA_469044 (19,206,580)

SNP_IGA_445689 (17,409,876)

SNP_IGA_480804 (20,068,418)

2,658,542

1.1

2.42

D

J × F

7

Pp05

SNP_IGA_545261 (821,356)

SNP_IGA_546467 (1,075,596)

SNP_IGA_544961 (698,215)

SNP_IGA_546765 (1,141,536)

443,321

1.1

0.40

 

R028

33

Pp05

SNP_IGA_543179 (246,971)

SNP_IGA_548597 (1,518,366)

N/A (246,971)

SNP_IGA_551853 (2,180,900)

1,933,929

4.6

0.42

G

Bb

2

Pp05

SNP_IGA_60239716(575,343)

SNP_IGA_60243216,584,717

SNP_IGA_600517 (14,889,273)

CPSCT022 (16,621,096)

1,731,826

5.3

0.33

 

J × F

1

Pp05

SNP_IGA_602432 (16,584,717)

SNP_IGA_602432 (16,584,717)

SNP_IGA_601135 (15,445,817)

SNP_IGA_602605 (16,636,368)

1,190,551

3.8

0.31

S

J × F

33

Pp06

SNP_IGA_691296 (27,066,639)

SNP_IGA_696162 (28,432,347)

MA040a (26,722,384)

SNP_IGA_699045 (29,318,074)

2,595,690

1

2.60

N/A no upper map position flanking D in R028

aMap position: single position on a genetic map where one or several co-segregating markers map

bPositions are those in the peach genome v2.0 scaffolds. SSR markers are in italics

Fruit skin pubescence G

Peach/nectarine character segregated in two of the progenies, J × F and Bb × Nl. G mapped at 61.7 and 7.8 cM in G5 of J × F and Bb, respectively (Fig. 1). One common SNP (SNP_IGA_602432, Pp05: 16,584,717) co-segregated with G in both maps and an additional one (SNP_IGA_602397, Pp05 16,575,343) in the map of Bb only. The closest SNPs at the map positions upstream to G mapped at a physical position of 15,445,817 bp (SNP_IGA_601135, 1.1 Mbp from G) and 14,889,273 bp (SNP_IGA_600517, 1.7 Mbp from G) in J × F and Bb, respectively (Table 5), allowing the identification of a candidate region comprised between 15,445,817 bp (SNP_IGA_601135) and 16,584,717 bp (SNP_IGA_602432). As the updated coordinates of the transcript of the MYB gene responsible for the trait (Prupe.5G196100) were Pp05 15,892,316–15,894,063, the position of G in both maps was therefore in agreement with that expected.

Stone adhesion and flesh texture F-M

F-M segregated in three of the mapping progenies: B × O, J × F, and W × By (Fig. 1). For B × O, F-M mapped in B only. Fifty-six SNPs co-segregated with F-M at 54.1 cM in G4 in a 3.1-Mbp interval comprised between 19,435,125 and 22,613,908 bp (Table 5); the flanking map-positions framed a region of 2.4 cM (0.8 and 1.6 cM apart of F-M locus, respectively) and 6,298,525 bp corresponding to 2.62 Mbp/cM (Table 5).

Regarding the J × F map, 42 SNPs co-segregated with F-M at 77.4 cM in G4, spanning an interval of 1.6 Mbp (18,593,828 to 20,176,048 bp). The interval between the SNPs closest from F-M at the flanking map positions was 2,249,293 bp in total for a genetic distance of 2.1 cM (Table 5). The upper flanking map position included two SNPs (SNP_IGA_449112, homozygous in both parents, and SNP_IGA_449118). The closest (SNP_IGA_449118) was 598,961 bp upstream to the upper boundary of F-M; this SNP mapped also at the flanking map position upstream to F-M in B. The marker position downstream to F-M locus consisted in eight SNPs and two SSRs. The closest SNP (SNP_IGA_484030) was separated from F-M by an interval of 67,812 bp). The last 16 SNPs co-segregating with the F-M locus (SNP_IGA_481642 to SNP_IGA_494363) were homozygous in ‘Fantasia’, suggesting a likely position upstream to SNP_IGA_481642, for F-M.

In W × By, nine SNPs co-segregated with F-M at 53.7 cM in an interval of 1,221,786 between 17,994,794 and 19,206,580 bp (Table 5). The flanking map positions framed an interval of 2,654,582 bp (1.1 cM) between SNP_IGA_445689 and SNP_IGA_480804. One SNP (SNP_IGA_449112) co-segregated with F-M in W × By and was mapped at the flanking map position upstream to F-M in J × F. In addition, this SNP was homozygous in ‘Fantasia’ where it was expected heterozygous if highly associated with the trait (Table 6). This allowed identifying the upper boundary of the F-M locus in W × By. In addition, SNP_IGA_480804 at the map position downstream to F-M in W × By allowed identifying the lower boundaries of the F-M locus in J × F and B. The two transcripts corresponding to the endoPG candidate genes were identified as Prupe.4G261900 (coordinates Pp04 19,046,344–19,049,605) and Prupe.4G262200 (coordinates Pp04 19,081,325–19,083,984). When comparing the three maps (B, J × F, and W × By), the consensus position of F-M was in an interval of 2,073,851 bp between SNP_IGA_449118 and SNP_IGA_480804 (Pp04 17,994,567–20,068,418), in agreement with the positions of the endoPG transcripts.
Table 6

Informative SNPs co-segregating with the six Mendelian traits in their respective genetic maps, with their characteristics and the alleles in coupling with the corresponding recessive phenotypes

Trait locus

Cross

Genetic map

SNPa,b

Scaffold

Position in peach v2.0 (bp)

Map position (cM)

SNP variants (as in GDR)

Parental alleles (♀/♂)

Allele in coupling with the recessive phenotype

Y

Bb × Nl

Bb

SNP_IGA_67270

Pp01

20,223,483

29.6

T/C

TC/TT

T

   

SNP_IGA_67620

Pp01

20,287,777

30.7

T/C

TC/TT

T

   

SNP_IGA_69306

Pp01

20,665,616

30.7

T/C

TC/TT

T

   

SNP_IGA_78954

Pp01

23,305,178

30.7

T/G

TG/TT

T

   

SNP_IGA_103422

Pp01

33,531,389

40.4

T/C

TC/TT

T

 

W × By

W × By

SNP_IGA_84580

Pp01

25,541,717

47.8

A/G

AA/GG

G

   

SNP_IGA_86918

Pp01

26,616,924

50.4

T/C

TT/CC

C

   

SNP_IGA_86968

Pp01

26,640,558

50.9

T/G

GG/TT

T

Rm2

P × R

P × R

SNP_IGA_131130

Pp01

45,083,225

140.9

A/G

AA/GG

A

   

SNP_IGA_128189

Pp01

45,753,343

144.3

T/C

TT/CC

T

   

SNP_IGA_128148

Pp01

45,764,232

144.3

A/C

CC/AA

C

   

SNP_IGA_127836

Pp01

45,821,173

144.3

A/G

GG/AA

G

   

SNP_IGA_127673

Pp01

45,841,357

144.3

T/G

TT/GG

T

   

SNP_IGA_127323

Pp01

45,900,381

144.3

A/G

AA/GG

A

   

SNP_IGA_127181

Pp01

46,012,310

144.3

A/G

AA/GG

A

   

SNP_IGA_126,668

Pp01

46,225,560

144.9

T/C

CC/TT

C

F-M

B × O

B

SNP_IGA_449118

Pp04

17,994,567

53.3

T/C

TC/CC

C

   

snp_4_23038297

Pp04

19,435,125

54.1

A/G

AG/GG

G

   

SNP_IGA_477941

Pp04

19,894,211

54.1

T/C

TC/CC

C

   

SNP_IGA_477945

Pp04

19,895,212

54.1

A/G

AG/GG

G

   

SNP_IGA_477951

Pp04

19,895,639

54.1

A/C

AC/AA

A

   

SNP_IGA_478039

Pp04

19,905,780

54.1

A/C

AC/AA

A

   

SNP_IGA_499780

Pp04

21,720,307

55.7

A/G

AG/GG

G

 

W × By

W × By

SNP_IGA_449112

Pp04

17,993,741

53.7

T/C

CC/TT

T

   

SNP_IGA_450711

Pp04

18,253,499

53.7

A/G

AA/GG

G

   

SNP_IGA_467302

Pp04

19,028,425

53.7

T/C

TT/T-

-

   

Pp31Cl

Pp04

19,047,191

53.7

A/G

AA/A-

-

   

SNP_IGA_467844

Pp04

19,100,410

53.7

AG

GG/AA

A

   

SNP_IGA_468829

Pp04

19,180,126

53.7

T/C

CC/TT

T

   

SNP_IGA_469044

Pp04

19,206,580

53.7

T/C

CC/TT

T

   

SNP_IGA_480804

Pp04

20,068,418

54.2

A/G

AA/GG

G

 

J × F

J × F

SNP_IGA_449112

Pp04

17,993,741

76.3

T/C

CC/TT

C

   

SNP_IGA_449118

Pp04

17,994,567

76.3

T/C

CC/TC

C

   

SNP_IGA_451930

Pp04

18,593,828

77.4

T/C

CC/TC

C

   

SNP_IGA_451947

Pp04

18,595,300

77.4

T/C

CC/TC

C

   

SNP_IGA_451959

Pp04

18,595,581

77.4

T/C

CC/TC

C

   

SNP_IGA_453202

Pp04

18,696,436

77.4

A/G

AA/AG

A

   

SNP_IGA_453669

Pp04

18,730,554

77.4

T/G

TT/TG

T

   

SNP_IGA_453774

Pp04

18,735,941

77.4

T/C

TT/TC

T

   

SNP_IGA_454257

Pp04

18,750,563

77.4

T/C

CC/TC

C

   

SNP_IGA_454568

Pp04

18,760,831

77.4

A/G

GG/AG

G

   

SNP_IGA_455216

Pp04

18,802,018

77.4

A/G

GG/AG

G

   

SNP_IGA_455222

Pp04

18,802,250

77.4

A/G

AA/AG

A

   

SNP_IGA_465473

Pp04

18,845,078

77.4

T/C

CC/TC

C

   

SNP_IGA_465802

Pp04

18,882,347

77.4

T/G

GG/TG

G

   

SNP_IGA_465820

Pp04

18,882,673

77.4

A/C

AA/AG

A

   

SNP_IGA_466532

Pp04

18,929,411

77.4

T/C

CC/TC

C

   

SNP_IGA_467230

Pp04

19,023,768

77.4

A/C

CC/AC

C

   

SNP_IGA_467302

Pp04

19,028,425

77.4

T/C

CC/TC

C

   

SNP_IGA_467618

Pp04

19,086,802

77.4

T/C

TT/TC

T

   

SNP_IGA_467844

Pp04

19,100,410

77.4

A/G

GG/AG

G

   

SNP_IGA_468829

Pp04

19,180,126

77.4

T/C

CC/TC

C

   

SNP_IGA_469044

Pp04

19,206,580

77.4

T/C

CC/TC

C

   

SNP_IGA_470760

Pp04

19,282,744

77.4

A/G

AA/AG

A

   

SNP_IGA_470811

Pp04

19,285,852

77.4

A/C

CC/AC

C

   

SNP_IGA_471458

Pp04

19,359,315

77.4

T/C

TT/TC

T

   

SNP_IGA_472376

Pp04

19,400,609

77.4

A/G

AA/AG

A

   

SNP_IGA_474444

Pp04

19,533,514

77.4

A/C

AA/AC

A

   

SNP_IGA_475922

Pp04

19,704,554

77.4

T/C

CC/TC

C

   

SNP_IGA_475950

Pp04

19,709,352

77.4

A/G

GG/AG

G

   

SNP_IGA_476568

Pp04

19,785,395

77.4

T/G

TT/TG

T

   

SNP_IGA_476569

Pp04

19,786,201

77.4

A/C

AA/AC

A

   

SNP_IGA_477336

Pp04

19,833,919

77.4

A/G

AA/AG

A

   

SNP_IGA_477690

Pp04

19,872,124

77.4

A/C

AA/AC

A

   

SNP_IGA_477777

Pp04

19,879,849

77.4

A/C

AA/AC

A

   

SNP_IGA_477896

Pp04

19,889,802

77.4

A/G

GG/AG

G

   

SNP_IGA_479502

Pp04

19,998,863

77.4

T/C

TT/TC

T

   

SNP_IGA_480804

Pp04

20,068,418

77.4

A/G

AA/AG

A

D

J × F

J × F

SNP_IGA_544961

Pp05

698,215

0

A/G

AA/GG

G

   

SNP_IGA_545261

Pp05

821,356

0.7

A/G

AA/GG

G

   

SNP_IGA_545448

Pp05

850,261

0.7

A/G

AA/GG

G

   

SNP_IGA_545655

Pp05

882,334

0.7

T/C

CC/TT

T

   

SNP_IGA_546094

Pp05

987,686

0.7

T/G

GG/TT

T

   

SNP_IGA_546316

Pp05

1,049,936

0.7

A/G

GG/AA

A

   

SNP_IGA_546467

Pp05

1,075,596

0.7

A/G

GG/AA

A

   

SNP_IGA_546765

Pp05

1,141,536

1.1

A/G

AA/GG

G

 

M × R028

R028

SNP_IGA_544961

Pp05

698,215

0

A/G

GG/AG

G

   

SNP_IGA_545261

Pp05

821,356

0

A/G

GG/AG

G

   

SNP_IGA_545448

Pp05

850,261

0

A/G

GG/AG

G

   

SNP_IGA_545655

Pp05

882,334

0

T/C

TT/TC

T

   

SNP_IGA_546094

Pp05

987,686

0

T/G

TT/TG

T

   

SNP_IGA_546316

Pp05

1,049,936

0

A/G

AA/AG

A

   

SNP_IGA_546467

Pp05

1,075,596

0

A/G

AA/AG

A

   

SNP_IGA_546765

Pp05

1,141,536

0

A/G

GG/AG

G

G

J × F

J × F

SNP_IGA_601135

Pp05

15,445,817

59.1

T/C

TC/TT

T

   

SNP_IGA_602432

Pp05

16,584,717

61.7

T/G

TG/TT

T

   

SNP_IGA_602605

Pp05

16,636,368

62.9

T/C

TC/TT

T

 

Bb × Nl

Bb

SNP_IGA_600517

Pp05

14,889,273

4.3

A/C

AC/AA

A

   

SNP_IGA_602397

Pp05

16,575,343

7.8

A/G

AG/GG

G

   

SNP_IGA_602432

Pp05

16,584,717

7.8

T/G

TG/TT

T

   

SNP_IGA_602605

Pp05

16,636,368

9.6

T/C

TC/TT

T

S

J × F

J × F

SNP_IGA_689067

Pp06

26,569,269

80.5

A/G

AA/AG

G

   

SNP_IGA_691341

Pp06

27,089,604

81.2

A/G

AG/GG

G

   

SNP_IGA_691727

Pp06

27,237,960

81.2

T/C

TC/CC

C

   

SNP_IGA_691838

Pp06

27,308,224

81.2

T/G

TG/TT

T

   

SNP_IGA_695629

Pp06

28,356,561

81.2

A/G

AG/GG

G

   

SNP_IGA_695665

Pp06

28,364,553

81.2

A/G

AG/GG

G

   

SNP_IGA_695678

Pp06

28,365,695

81.2

A/G

AG/AA

A

   

SNP_IGA_695715

Pp06

28,369,835

81.2

A/G

AG/GG

G

   

SNP_IGA_695780

Pp06

28,377,171

81.2

A/G

AG/GG

G

   

SNP_IGA_695791

Pp06

28,379,072

81.2

T/C

TC/CC

C

   

SNP_IGA_695928

Pp06

28,397,661

81.2

T/G

TG/TT

T

   

SNP_IGA_695974

Pp06

28,414,438

81.2

T/C

TC/TT

T

   

SNP_IGA_695991

Pp06

28,416,018

81.2

A/G

AG/GG

G

   

SNP_IGA_696071

Pp06

28,426,294

81.2

A/C

AC/AA

A

   

SNP_IGA_696113

Pp06

28,429,136

81.2

A/G

AG/AA

A

   

SNP_IGA_696128

Pp06

28,430,004

81.2

A/G

AG/GG

G

S

J × F

J × F

SNP_IGA_696152

Pp06

28,431,786

81.2

A/G

AG/AA

A

   

SNP_IGA_696162

Pp06

28,432,347

81.2

A/G

AG/AA

A

   

SNP_IGA_699045

Pp06

29,318,074

81.8

T/C

TT/TC

C

aSNPs in italics are those co-segregating with the major genes. The others are the closest SNPs outside of the major gene loci. For F-M, SNP_IGA_449112 has been added in J × F, in order to facilitate the comparison with W × By

bFor F-M and D, only SNPs in the consensus regions are listed. For S, only SNPS both heterozygous in the flat parent (‘Fantasia’) and homozygous in the other parent (‘Jalousia’®) are listed

No SNP was shared by the three maps at the F-M map position. Four SNPs (SNP_IGA_467302, SNP_IGA_467844, SNP_IGA_468829, and SNP_IGA_469044) were shared by J × F and W × By maps (Fig. 1). The alleles in coupling with the recessive phenotype in each of them were opposite (Table 6), but two different characters involved in F-M (stone adherence and flesh texture, respectively) were observed in each of the progenies. The ratio between physical and genetic distances was similar in B and W × By (2.10 and 2.62 Mbp/cM, respectively) and lower in J × F (1.07 Mbp/cM), suggesting a higher recombination rate in the second progeny.

Sub-acid fruit D

Two progenies segregated for the sub-acid fruit trait: J × F and M × R028. In J × F, one SSR (CPPCT040) previously mapped in this progeny, and six SNPs, co-segregated with D at 0.7 cM in G5, spanning a physical distance of 254,240 bp. The two flanking map positions included 14 markers (13 SNPs and one SSR) and 7 SNPs, respectively (Fig. 1). They encompassed a 1.1 cM region corresponding to 443,321 bp between the closest SNPs to D and 1,044,636 bp in total (0.95 Mbp/cM). Two SSRs and 26 SNPs in total were included in these three map positions (Table 5).

In M × R028, D mapped at the upper end of G5 in R028. Thirty-three SNPs co-segregated with the trait, among which six co-segregated also with D in J × F. The distance between outmost SNPs was 1,271,395 and 1,933,929 bp in total to the flanking map position downstream D, for a genetic distance of 4.6 cM (0.42 Mbp/cM). When including the two map positions flanking D in J × F, 24 SNPs were common to both maps. This suggests a likely position of D locus in the interval of 443,321 bp between SNP_IGA_544961 and SNP_IGA_546765 (Pp05 698,215–1,141,536).

Fruit shape S

Fruit shape segregated only in J × F. S locus mapped in G6 at 81.2 cM (Fig. 1). Thirty SNPs and three SSRs co-segregated with S, spanning a physical distance of 1,366,308 bp. Seventeen among these SNPs were heterozygous in ‘Ferjalou Jalousia®’ and are therefore better candidate markers for the flat phenotype (Table 6). The map positions upstream and downstream S included two SSRs and two SNPs, respectively, which delimited an interval of 2,595,690 bp for 1 cM (Fig. 1). The closest SNPs flanking the S locus were SNP_IGA_6889177 and SNP_IGA_699045 at 26,569,269 and 29,318,074 bp, respectively (Table 5). They delimited an interval of 2,748,805 bp for 1.3 cM (Fig. 1) corresponding to 2.11 Mbp/cM (Table 5). This highlights the low recombination rate in the S region, despite the quite large population size (138).

Resistance to M. persicae Rm2

Rm2 segregated only in P × R. It mapped at 144.3 cM in G1 together with six SNPs spanning a total distance of 276,967 bp (Fig. 1, Table 5). The closest SNPs at the flanking map positions framed a 4-cM region corresponding to 1,142,335 bp (0.29 Mbp/cM). Rm2 was mapped before in a region of 2.88 Mbp comprised between two SSRs, UDP-022 and UDAp-467 (Pp01 43,622,315 to 46,502,361). The current interval including Rm2 is therefore reduced from 2.88 to 1.14 Mbp.

SNPs for MAS

A total of 76 SNPs co-segregating with Y (four SNPS), Rm2 (six SNPs), F-M (41 SNPs), D (six SNPs), G (two SNPs), and S (17 SNPs) were selected as potentially associated with their respective phenotypes and useful for MAS. They are listed in Table 6 as well as two SNPs flanking each major-gene map position. Only a small number among these SNPs were polymorphic in more than one progeny, at locus D (six SNPs shared by J × F and R028), G (one SNP shared by J × F and Bb), and F-M (four SNPs shared by J × F and W × By). For F-M, however, the alleles in coupling with the recessive phenotype of each of the two characters involved in F-M (freestone/clingstone and melting/nonmelting) were opposite in J × F and W × By.

Discussion

IPSC 9K SNP array v1 performance

High-density SNP genotyping arrays are powerful tools for studying genomic patterns of diversity and marker–trait associations in mapping experiments (Muranty et al. 2014). The IPSC 9K SNP array v1 (Verde et al. 2012) consisted of 8144 working SNPs, among which 84.3% were polymorphic across 709 accessions of peach and 5% failed. In our study, a total of 5255 SNPs (64.5%) were polymorphic at least in one segregating progeny, while 2012 (24.7%) failed in all the progenies. This percentage of polymorphic SNPs is intermediate between the ones reported by Verde et al. (2012) for SNPs with MAF >0.1 (71.4%) and SNPs with MAF >0.2 (55.5%). These results are also consistent with those reported by Micheletti et al. (2015) in which 66% of the SNPs were polymorphic and 25% failed in a panel of 1580 peach accessions used for association studies, reflecting similar genetic background in the material genotyped in both studies, even if the failed SNPs could have been different. This underlines the fact that only 2/3 of the SNPs distributed in the 9K array v1 were finally useful, suggesting a limited overall efficiency for high-throughput studies in commercial gene pool and particularly when a small number of accessions is involved or when their genetic backgrounds are too close. On the other hand, numerous rearrangements have been made in peach.v2.0 compared to peach v1.0 (The International Peach Genome Initiative 2013) in some of the pseudomolecules/scaffolds (GDR: (http://www.rosaceae.org/species/prunus_persica/genome_v2.0.a1). Taking it all together, distribution of useful SNPs is consequently not as uniform as expected among the pseudomolecules regarding physical as well as genetic distances. Furthermore, the least covered scaffold had a SNP density 2.4-fold lower than that of the most covered scaffold. As a consequence, some regions or pseudomolecules were disadvantaged in terms of marker coverage. This is notably the case for Pp01, the longest pseudomolecule, in which SNP coverage is among the lowest on the basis of both physical and genetic distances. On the other hand, SNPs in Pp04 are overrepresented. These points could be detrimental, particularly for the development of genetic maps derived from F1 progenies as markers have to be heterozygous at least in one of the parents, which reduces accordingly the number of useful SNPs. Although the IPSC 9K SNP array v1 is a powerful tool for studies in association genetics and genetic mapping, the choice of the SNPs placed on the current array could thus be optimized in a further version in order to maximize the genotyping efficiency.

Genetic linkage groups

In the present work, we constructed ten SNP-based genetic maps derived from various F1 and F2 progenies and focused on six regions of the four linkage groups known to include the major genes of interest (Dirlewanger et al. 2004; Peace et al. 2005: Lambert et Pascal 2011; Arús et al. 2012). Previous maps were already available for B, W × By, J × F, P × R, and Bb. The first two maps were based on the IPSC 9K SNP array (Eduardo et al. 2013; Da Silva Linge et al. 2015) but were constructed with other objectives. The three others were mainly based on SSRs (Dirlewanger et al. 2006; Lambert et Pascal 2011; Eduardo et al. 2015). Compared to the latter, as expected, map coverage was improved in the selected linkage groups by using the IPSC 9K SNP array v1. In the previous maps, G1 was indeed composed of 5 and 18 map positions in Bb and P × R, respectively; G4 of 25 map positions in J × F; G5 of 4 and 41 map positions in Bb and J × F, respectively; and G6 of 26 map positions as opposed to 33, 71, 42, 3, 47, and 52 map positions, respectively, in the current SNP-based maps. However, difference in the number of map positions appear low between both types of maps when compared to the large number of polymorphic SNPs available on the IPSC 9K SNP array v1 for each of these linkage groups. Similar results were obtained by Eduardo et al. (2013), Yang et al. (2013), and Frett et al. (2014) with different crosses. One of the likely reasons is that the IPSC 9K SNP array is based on a multi-purpose oligonucleotide pool (Verde et al. 2012). As a consequence, both screening and genotyping steps are associated, contrary to the previous maps for which only polymorphic markers were kept for mapping. Another reason is a significant clustering of SNPs co-segregating at the same map positions in all the linkage groups. Indeed, the average number of SNPs per map position ranged from 2.2 to 9.5 SNPs but with large differences between linkage groups and crosses as one single SNP up to 56 co-segregating SNPs (F-M locus in B) were observed. Similar results were obtained by Martínez-García et al. (2013) using another set of 1536 SNPs in a F1 map in which 71% of the SNPs shared the same positions with an average of 3.5 SNP per map position. The main reason of the clustering is the high level of linkage-disequilibrium (LD) resulting from the low number of meiosis between the parents and each of the derived progenies, and additionally, the limited number of individuals in each of the progenies providing limited opportunities for recombination. Another possible reason is the LD conservation observed in peach cultivars from European and North American origin, due to the limited germplasm pools used for developing cultivars (Aranzana et al. 2010; Li et al. 2013). This high LD could explain the nonrandom distribution of heterozygosity in the cultivars used to develop the F1 maps as well as the one of polymorphism in the parents of the F2 crosses. However, high level of LD is considered a favorable parameter for the efficiency of MAS (Muranty et al. 2014). As expected, all the linkage groups align to the respective pseudomolecules of peach v2.0 (http://www.rosaceae.org/species/prunus_persica/genome_v2.0.a1) and marker order is in general agreement with their genomic positions. This confirms the increased accuracy of peach v2.0 (Verde et al. 2015) as compared to peach v1.0 (The International Peach Genome Initiative 2013).

Association of the SNPs and the major-gene traits: implications for MAS

During the past 10 years, several studies were carried out in peach to develop markers useful for MAS (Dirlewanger et al. 2006; Lambert et al. 2009; Picañol et al. 2013; Martínez-García et al. 2013; Eduardo et al. 2014). At the same time, molecular resources adapted to US germplasm have been made available to breeders (https://www.rosbreed.org/breeding/dna-tests) in the framework of RosBREED (Iezzoni et al. 2010). With similar objectives, we developed an approach based on the IPSC 9K SNP array v1 and several unrelated progenies to map six Mendelian traits (major genes) among the most important for peach breeding. The array had already been used in several mapping studies on peach, but with different objectives (Eduardo et al. 2013; Yang et al. 2013; Frett et al. 2014; Pacheco et al. 2014; Da Silva Linge et al. 2015; Donoso et al. 2015). The positions of the traits on the chromosomes were known (Dettori et al. 2001; Bliss et al. 2002; Dirlewanger et al. 2006; Lambert and Pascal 2011; Arús et al. 2012) and for Y, G, and F-M, candidate genes have been identified, which enabled clear identification of the closest SNPs among those co-segregating with the traits. Besides this, a genome-wide association study based on a panel of 1580 peach accessions (Micheletti et al. 2015) and the IPSC 9K SNP array has identified a set of SNPs tightly associated with five of these Mendelian traits allowing direct comparison with our results. As a result, we identified a total of 18 SNPs co-segregating with the traits and shared between the two studies: four among five in B for F-M; five among six in both J × F and R028 for D; one among one and two among two in J × F and Bb for G, respectively; and finally, seven among 17 in J × F for S. In addition, 24 SNPs were shared at flanking map positions. These SNPs are listed in Table 7. In our study, SNPs co-segregating with the traits were found for all progenies and located in the expected regions. For those for which genes and sequences were available (Y, G, and F-M), the identification of the relevant SNPs was all the more obvious as the genomic positions of both genes and SNPs were known (https://www.rosaceae.org/species/prunus_persica). For Y, two SNPs frame the locus, among which the closest map only 691 bp downstream the 3′ UTR of PpCCD4. For G, two SNPs map, respectively, 446 kbp upstream and 690 kbp downstream from Prupe.5G196100, the MYB transcription factor responsible for the pubescent/glabrous phenotype. For F-M, two common SNPs frame both endoPG transcripts in two of the maps (J × F and W × By), delimiting an interval of only 72 kbp encompassing both transcripts. When more than one progeny could be used for mapping, as in Y, F-M, D, and G, some co-segregating SNPs (F-M and G) or all of them (D) were shared between progenies, except for Y where none of the co-segregating markers were in common. Regarding Y, three independent mutations in PpCCD4 are responsible for the yellow flesh-color in peach (Falchi et al. 2013). The lack of common SNPs co-segregating with Y in Bb and W × B may indicate that the causative allele for the yellow flesh in ‘Belbinette’ is different from that in ‘Bounty’. This also demonstrates that, in general, the variants of the SNPs that are not shared are not directly involved in a specific phenotype although they are close to the genes in terms of genetic distances. This is also the case for the SNPs close to the genes that were identified by association analysis by Micheletti et al. (2015) but were monomorphic in this study. Indeed, although most of the SNPs in the array were designed in coding regions (Verde et al. 2012), we should not expect that they occur in the causal gene/factor, but close in terms of genetic distances, and therefore, they may be polymorphic only in some of the germplasm. Regarding F-M for instance, four SNPs were shared between two maps (W × By and J × F) but the alleles in coupling with the recessive phenotype in each of the maps were opposite. However, two different characters involved in F-M were observed in each of the progenies (stone adherence and flesh texture, respectively). This suggests that either each of the alleles is associated to one of the characters involved in F-M or that these four SNPs are not associated with the phenotype. As a result, these SNPs are unsuitable for a widespread use and would need preliminary tests on the parents for other crosses. On the other hand, four among the five SNPs identified in the third map (B) were shared with Micheletti et al. (2015); they correspond to the best association values in the GWA study (P value = 4.83E−11 to 9.82E−10) although they are 800 kbp downstream the two endoPG transcripts and not shared with the other two maps. According to Peace and Norelli (2009), due to the two copies of the gene, different effects such as additivity, dominance, pleiotropy, or epistasis of the locus could influence the phenotype. In the same way, Martínez-García et al. (2013) observed similar inconsistencies using a different set of SNPs for mapping F-M and Y genes and suggested that multiple modifier genes (or duplicate loci) could be associated with the F-M and Y phenotypes. More recently, Gu et al. (2016) proposed a model with two functional divergent endoPG genes, one responsible for stone adhesion (PpendoPGF) and the other for melting flesh phenotypes (PpendoPGM). This could explain the different results we obtained for F-M with the three progenies. Regarding the other traits mapped in several progenies, no shared SNP was observed for Y and the closest common SNP identified by GWAS (SNP_IGA_91050, P value = 1.47E−07) is 2.1 cM downstream locus Y in G1 of W × By. SNPs shared between progenies were only observed for D and G. For D, all the six SNPs co-segregating with the trait were shared between the two maps involved. Moreover, four of these ones (P values = 3.57E−24 to 4.37E−21) are among the best eight matches in Micheletti et al. (2015), with only two SNPs (SNP_IGA_544640 and 544,657) having a better association (P values = 1.54E−25 and 6.06E−25, respectively). In our study, they were co-segregating with D in R028 but map upstream to D in J × F. For G only one SNP (SNP_IGA_602432) was shared by the two maps involved. It is also one of the most significant (P value = 4.37E−12) in Micheletti et al. (2015) for this character, and only three SNPs had a better association by GWAS (P values = 2.53E−19 to 4.92E−14). The other two traits (S and Rm2) were each mapped in a single progeny. For S, nine SNPs were shared with Micheletti et al. (2015). Four SNPs have higher P values by GWAS than the two most significant ones from our study, SNP_IGA_691341 and SNP_IGA_691727 (P value = 9.983E−8) but were monomorphic in J × F and anyway are upstream of the S locus according to its known position (Dirlewanger et al. 2006). Regarding Rm2, no comparison was possible as this trait was not included in the GWAS, but two SNPs (SNP_IGA_131130 and 126,668) frame the Rm2 locus which contains six co-segregating SNPs that could be further tested in larger progenies in order to identify the closest to Rm2.
Table 7

SNPs shared between this study and the genome-wide association study by Micheletti et al. (2015)

Trait locus

Cross

Genetic map

SNPa

Scaffold

Position in peach v2.0 (bp)

Map position (cM)

SNP variants (as in GDR)

P valueb (GWAS)

F-M

B × O

B

SNP_IGA_477941

Pp04

19,894,211

54.1

T/C

5.09E−11

   

SNP_IGA_477945

Pp04

19,895,212

54.1

A/G

5.09E−11

   

SNP_IGA_477951

Pp04

19,895,639

54.1

A/C

9.82E−10

   

SNP_IGA_478039

Pp04

19,905,780

54.1

A/C

4.83E−11

D

J × F

J × F

SNP_IGA_543786

Pp05

467,068

0

A/G

1.17E−07

   

SNP_IGA_543942

Pp05

481,015

0

A/G

7.10E−08

   

SNP_IGA_544495

Pp05

610,569

0

T/G

5.06E−20

   

SNP_IGA_544640

Pp05

629,642

0

A/G

1.54E−25

   

SNP_IGA_544,657

Pp05

635,222

0

A/G

6.06E−25

   

SNP_IGA_544961

Pp05

698,215

0

A/G

7.24E−24

   

SNP_IGA_545261

Pp05

821,356

0.7

A/G

3.58E−24

   

SNP_IGA_545448

Pp05

850,261

0.7

A/G

1.77E−14

   

SNP_IGA_546094

Pp05

987,686

0.7

T/G

4.37E−21

   

SNP_IGA_546316

Pp05

1,049,936

0.7

A/G

6.54E−16

   

SNP_IGA_546467

Pp05

1,075,596

0.7

A/G

2.524E−22

   

SNP_IGA_546765

Pp05

1,141,536

1.1

A/G

3.90E−18

   

SNP_IGA_546791

Pp05

1,147,069

1.1

T/C

1.10E−17

   

SNP_IGA_546835

Pp05

1,155,451

1.1

A/C

2.05E−18

   

SNP_IGA_546987

Pp05

1,166,290

1.1

A/G

2.31E−19

   

SNP_IGA_547211

Pp05

1,190,201

1.1

A/G

5.65E−18

 

M × R028

R028

SNP_IGA_543786

Pp05

467,068

0

A/G

1.17E−07

   

SNP_IGA_543942

Pp05

481,015

0

A/G

7.10E−08

   

SNP_IGA_544495

Pp05

610,569

0

T/G

5.06E−20

   

SNP_IGA_544640

Pp05

629,642

0

A/G

1.54E−25

   

SNP_IGA_544,657

Pp05

635,222

0

A/G

6.06E−25

   

SNP_IGA_544961

Pp05

698,215

0

A/G

7.24E−24

   

SNP_IGA_545261

Pp05

821,356

0

A/G

3.57E−24

   

SNP_IGA_545448

Pp05

850,261

0

A/G

1.77E−14

   

SNP_IGA_546094

Pp05

987,686

0

T/G

4.371E−21

   

SNP_IGA_546316

Pp05

1,049,936

0

A/G

6.54E−16

   

SNP_IGA_546467

Pp05

1,075,596

0

A/G

2.52E−22

   

SNP_IGA_546765

Pp05

1,141,536

0

A/G

3.90E−18

   

SNP_IGA_546791

Pp05

1,147,069

0

T/C

1.10E−17

   

SNP_IGA_546835

Pp05

1,155,451

0

A/C

2.05E−18

   

SNP_IGA_546987

Pp05

1,166,290

0

A/G

2.31E−19

   

SNP_IGA_547211

Pp05

1,190,201

0

A/G

5.65E−18

   

SNP_IGA_547473

Pp05

1,216,762

0

A/G

4.33E−17

   

SNP_IGA_547510

Pp05

1,219,833

0

A/C

2.21E−17

   

SNP_IGA_548037

Pp05

1,376,475

0

T/C

1.74E−16

   

SNP_IGA_548512

Pp05

1,503,387

0

T/C

1.26E−23

   

SNP_IGA_548597

Pp05

1,518,366

0

A/G

1.04E−18

   

SNP_IGA_551853

Pp05

2,180,900

4.6

A/C

4.25E−08

G

J × F

J × F

SNP_IGA_600517

Pp05

14,889,273

55.8

A/C

6.98E−11

   

SNP_IGA_602432

Pp05

16,584,717

61.7

T/G

4.37E−12

   

SNP_IGA_602605

Pp05

16,636,368

62.9

T/C

1.81E−10

   

SNP_IGA_602661

Pp05

16,655,703

62.9

A/G

1.74E−10

 

Bb × Nl

Bb

SNP_IGA_600509

Pp05

14,888,402

4.3

A/G

1.78E−08

   

SNP_IGA_600517

Pp05

14,889,273

4.3

A/C

6.98E−11

   

SNP_IGA_602397

Pp05

16,575,343

7.8

A/G

6.51E−11

   

SNP_IGA_602432

Pp05

16,584,717

7.8

T/G

4.37E−12

   

SNP_IGA_602605

Pp05

16,636,368

9.6

T/C

1.81E−10

   

SNP_IGA_602661

Pp05

16,655,703

9.6

A/G

1.74E−10

S

J × F

J × F

SNP_IGA_683904

Pp06

25,033,223

76.5

T/C

1.61E−13

   

SNP_IGA_684085

Pp06

25,090,090

76.8

T/C

1.61E−13

   

SNP_IGA_685825

Pp06

25,500,953

77.9

T/G

6.44E−11

   

SNP_IGA_691341

Pp06

27,089,604

81.2

A/G

9.983E−8

   

SNP_IGA_691727

Pp06

27,237,960

81.2

T/C

9.983E−8

   

SNP_IGA_695665

Pp06

28,364,553

81.2

A/G

5.278E−7

   

SNP_IGA_695678

Pp06

28,365,695

81.2

A/G

1.071E−6

   

SNP_IGA_695715

Pp06

28,369,835

81.2

A/G

5.278E−7

   

SNP_IGA_695780

Pp06

28,377,171

81.2

A/G

5.278E−7

   

SNP_IGA_695791

Pp06

28,379,072

81.2

T/C

1.071E−6

aSNPs in italic are those which co-segregated with the major genes when one single progeny is involved or which are in the consensus region when two progenies are involved. The others mapped at neighboring loci

bP values calculated by Micheletti et al. (2015) based on a panel of 1.546 peach accessions. For S, values correspond to the best association observed among 15 repeats

Conclusion

Using a mapping approach, we identified SNPs tightly associated with the six Mendelian characters (major genes) studied. For those characters for which candidate genes were available, SNPs were always in the physical regions encompassing the genes. For the others, they allowed higher resolution of the regions including the genetic factor responsible for the character, and therefore provide SNPs that could be a starting point to identify candidate targets. Moreover, we showed that a number of these SNPs were highly associated by GWA with the traits, in particular with F-M, D, G, and S, therefore confirming their close link with the phenotypes under study and their usefulness for MAS. However, we also showed that, for certain characters, their polymorphism and therefore their power to discriminate between phenotypic variants were dependent on the parent combination used for the cross. As a result, SNP sets would need to be validated on each parent combination before widespread application of MAS. Another approach, that needs further development, would be to identify the different haplotypes for various sets of SNPs in the major-gene regions in order to select the most predictive ones for each given cross, based on the parent patterns, and use these haplotypes as diagnostic markers.

As a whole, this study establishes a sound basis for further development of MAS on major-gene traits. It is complementary to the previously published GWAS (Micheletti et al. 2015) confirming shared SNPs but also demonstrating that a number of highly significant SNPs by GWA may be unsuitable when used in the bi-parental crosses of many breeding programs. This could help develop haplotype-based methods for MAS that could be practical alternatives, as long as markers strictly linked with the phenotype (diagnostic markers) are not available.

Notes

Acknowledgements

This work has been funded under the EU seventh Framework program by the FruitBreedomics project (FP7-KBBE-2010-265582): Integrated Approach for increasing breeding efficiency in fruit tree crop. The views expressed in this work are the sole responsibility of the authors and do not necessary reflect the views of the European Commission. We acknowledge Stefano Foschi and Martina Lama (CRPV, Cesena, Italy) for their help with field work.

Data archiving statement

Genetic linkage maps of the regions including major genes as well as the list of the SNPs highly associated with the major genes will be submitted to the Genome Database for Rosaceae (www.rosaceae.org).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Patrick Lambert
    • 1
  • Jose Antonio Campoy
    • 2
  • Igor Pacheco
    • 3
    • 4
  • Jehan-Baptiste Mauroux
    • 1
  • Cassia Da Silva Linge
    • 3
  • Diego Micheletti
    • 5
    • 6
  • Daniele Bassi
    • 3
  • Laura Rossini
    • 3
    • 7
  • Elisabeth Dirlewanger
    • 2
  • Thierry Pascal
    • 1
  • Michela Troggio
    • 6
  • Maria Jose Aranzana
    • 5
  • Andrea Patocchi
    • 8
  • Pere Arús
    • 5
  1. 1.GAFL, INRAMontfavetFrance
  2. 2.UMR 1332 B.P. INRA, Univ. BordeauxVillenave d’OrnonFrance
  3. 3.Università degli Studi di Milano, DiSAAMilanItaly
  4. 4.INTA, Universidad de ChileSantiagoChile
  5. 5.IRTA, Centre de Recerca en Agrigenòmica CSIC-IRTA-UAB-UBBarcelonaSpain
  6. 6.Research and Innovation Centre, Fondazione Edmund Mach (FEM)San Michele all’AdigeItaly
  7. 7.Parco Tecnologico PadanoLodiItaly
  8. 8.Research Station AgroscopeWädenswilSwitzerland

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