Identification and characterization of resistance quantitative trait loci against bacterial wilt caused by the Ralstonia solanacearum species complex in potato

DOI: https://doi.org/10.21203/rs.3.rs-1591184/v1

Abstract

Bacterial wilt (BW) caused by the Ralstonia solanacearum species complex (RSSC) represents one of the most serious diseases affecting potato cultivation. The development of BW-resistant cultivars represents the most efficient strategy to control this disease. The resistance-related quantitative trail loci (QTLs) in plants against different RSSC strains have not been studied extensively. Therefore, we performed QTL analysis for evaluating BW resistance using a diploid population derived from Solanum phureja, Solanum chacoense, and Solanum tuberosum. Plants cultivated in vitro were inoculated with different strains (phylotype I/biovar 3, phylotype I/biovar 4, and phylotype IV/biovar 2A) and incubated at 24°C or 28°C under controlled conditions. Interval mapping was performed for the disease indexes using the resistant parent-derived map consisting of 1,476 single-nucleotide polymorphism (SNP) markers and the susceptible parent-derived map consisting of 2,663 SNP markers. We identified five major and five minor resistance QTLs on potato chromosomes 1, 3, 5, 6, 7, 10, and 11. The major QTLs qBWR-3 and qBWR-7 conferred stable resistance against Ralstonia pseudosolanacearum (phylotype I) and Ralstonia syzygii (phylotype IV), while qBWR-6b was a strain-specific major resistance QTL against phylotype I/biovar 3 and was more effective at a relatively lower temperature. Therefore, we suggest that broad-spectrum QTLs and strain-specific QTLs can be combined to develop the most effective BW-resistant cultivars for particular areas.

Introduction

Solanum tuberosum L. (potato) is cultivated worldwide and is the most important Solanaceae crop (Liu et al. 2016); over 462 million metric tons were produced in 2019 (Food and Agriculture Organization of the United Nations 2021). However, its cultivation is frequently limited by pests and diseases, including bacterial wilt (BW), which represents one of the most serious and widespread bacterial diseases in the tropics, subtropics, and warm temperate regions worldwide (Hayward 1985).

BW is caused by the Ralstonia solanacearum species complex (RSSC), which mainly enters plants via roots and then colonizes the xylem vessels and spreads through the vascular system of plants. RSSC infection causes typical wilting symptoms, leading to rapid death of the host plant. RSSC has been reported to infect over 250 plant species including many cash crops and major food crops, such as banana, potato, tomato, and eggplant (Peeters et al. 2013). Recently, it has been ranked second in the list of the most scientifically/economically important bacterial pathogens (Mansfield et al. 2012).

RSSC is classified into five races based on host range or six biovars based on their ability to produce acid using various disaccharides and sugar alcohols (Buddenhagen and Kelman 1964; Denny 2006). Based on molecular analysis, RSSC is classified into four monophyletic groups called phylotypes (Gillings and Fahy 1994). A probable geographical origin represents an attribute of each phylotype; phylotypes I, II, III, and IV have been considered to originate from Asia, the Americas, Africa, and Indonesia and Australia, respectively (Fegan and Prior 2005; Wicker et al. 2012). Recently, RSSC has been suggested to comprise three species: R. solanacearum including phylotype II, Ralstonia pseudosolanacearum including phylotypes I and III, and Ralstonia syzygii including the former R. solanacearum phylotype Ⅳ and the closely related pathogen R. syzygii (Safni et al. 2014). Although genomic, proteomic, and functional phenotypic analyses support this classification (Prior et al. 2016), the ecological and evolutionary relationships of these species remain unknown.

Strategies to control BW, such as crop rotation, elimination of weeds that represent alternative hosts, and biological control, are insufficient and the disease continues to cause major profit loss (Huet 2014). In addition, chemical-based control using chloropicrin has an adverse impact on the environment and its use is undesirable. The development of BW-resistant cultivars is cost-effective and environmentally friendly; however, only a few factors that confer BW resistance have been identified (Laferriere et al. 1999). BW resistance has been found in cultivated diploid species and closely related wild species (Thurston and Lozaro 1968; Sequeira and Rowe 1969; French and De Lindo 1982; Laferriere et al. 1999; Fock et al. 2000, 2001; Kim-Lee et al. 2005; Carputo et al. 2009; Chen et al. 2013). The cultivated diploid species Solanum phureja is often used as a source of BW resistance factors (Sequeira and Rowe 1969; Watanabe et al. 1992; French et al. 1998). The S. phureja-derived breeding clone Saikai 35 has a high level of BW resistance (Mori et al. 2012), from which a BW-resistant cultivar Nagasaki Kogane has been derived (Sakamoto et al. 2017).

BW resistance is controlled by multiple genes (Elphinstone 1994; Rowe and Sequeira 1970; Sequeira 1979). Two major quantitative trait loci (QTLs) bwr-12 and bwr-6 and several minor QTLs have been identified in the tomato cultivar Solanum lycopersicum Hawaii 7996. bwr-12 confers partial resistance to the phylotype I strain and bwr-6 confers partial resistance to both phylotype I and II strains or broad-spectrum resistance (Thoquet et al. 1996a, 1996b; Wang et al. 2000, 2013; Carmeille et al. 2006). In potatoes, BW resistance against race 1/biovar 3 strains has been found in somatic hybrids of S. tuberosum + Solanum chacoense, and the resistance QTLs have been identified in chromosomes 2 and 9 (Chen et al. 2013). However, resistance QTLs against different strains have not been studied extensively.

We previously identified resistance QTLs against the phylotype Ⅰ/biovar 4 strain on chromosomes 1, 3, 7, 10, and 11 using a diploid mapping population consisting of S. tuberosum, S. chacoense, and S. phureja (Habe et al. 2019). In this study, we assayed the same diploid population using different strains (phylotypes I and IV or biovars 3, 4, and 2A) at different incubation temperatures (24°C and 28°C) after inoculation and performed QTL analysis.

Materials And Methods

Plant materials

Saikai 35 is a breeding clone highly resistant to BW (Mori et al. 2012). From Saikai 35, a resistant haploid clone (10-03-30) was obtained via parthenogenesis by crossing the pollen of a haploid inducer S. phureja 460 (= IvP 35). This resistant parent (RP) was crossed as the female parent with a susceptible diploid clone F1-1 (SP) as the male parent, which generated 94 F1 plants grown in vitro using Murashige and Skoog (MS) medium (Murashige and Skoog 1962). The F1 population (Habe et al. 2019) was previously characterized for BW resistance to the strain MAFF327001 (phylotype I/ biovar 4).

Inoculation and disease resistance analysis

The in vitro inoculation test (Habe 2018) was performed to evaluate resistance in the F1 plants. The in vitro screening medium, containing 30 mL vermiculite and 20 mL MS liquid medium in a glass tube (40 mm × 130 mm), was sterilized via autoclaving. The plants cultivated in vitro were cut at nodes below the third or fourth leaf from the apex. The cut stems were transplanted into an in vitro screening medium and incubated in a growth chamber for two weeks to promote rooting. The light-dark cycle was 16 h light at 3000–4000 lux and 8 h dark. The incubation temperature was 18°C.

The RSSC strains MAFF327001 (phylotype I/biovar 4), MAFF327095 (phylotype IV/biovar 2A), and MAFF327142 (phylotype I/ biovar 3) isolated from potato (Horita et al. 2010) were used in this study for the inoculation test (Table 1). The strains were cultured at 30 ºC in 2,3,5-triphenyltetrazolium chloride solid medium (Kelman 1954). White fluid-containing colonies were transferred to casamino acid-peptone-glucose medium (Hendrick and Sequeira 1984). The inoculum cell concentration was determined by measuring the optical density at 600 nm and adjusted to 108 colony-forming units/mL in sterile water. The bacterial suspension (1 mL) was poured into each screening medium. Nine or ten plantlets per genotype were used as one replicate, and three replicates were tested for BW resistance. After inoculation, one set was incubated at 24°C and the other set was incubated at 28°C.

Table 1

QTLs detected by CIM analysis for the resistance to the R. solanacearum species complex in the F1 population

BW strain

Temperature

QTL1)

Detected map

Chr

Position (cM)

Position of maximum LOD (cM)

Maximum LOD score

Explained variance (%)

MAFF327142

(Phylotype I/

biovar 3)

24 C°

qBWR-6b

R map

6

10.8–23.7

21.7

14.17

40.5

qBWR-10b

S map

10

53.2–56.6

55.6

4.32

14.5

28 C°

qBWR-6b

R map

6

13.8–23.7

21.7

5.51

17.6

qBWR-6a

S map

6

0.0

0.0

3.93

13.6

MAFF327001

(Phylotype I/

biovar 4)

24 C°

qBWR-7

R map

7

12.2–27.2

25.3

6.86

20.5

28 C°

qBWR-1b

S map

1

79.0–79.1

79.1

3.83

11.4

qBWR-3

S map

3

13.8–17.0

15.0

4.30

13.0

qBWR-5

S map

5

54.7–55.7

54.7

3.76

11.2

qBWR-7

R map

7

15.2–27.2

25.3

6.64

21.9

qBWR-10a

S map

10

6.6–10.9

8.8

4.93

15.1

MAFF327095

(Phylotype IV/

biovar 2A)

28 C°

qBWR-1a

S map

1

74.6–75.7

74.7

4.91

15.1

qBWR-7

R map

7

25.2–26.3

25.3

4.39

15.3

qBWR-11

S map

11

32.6–33.6

32.6

3.94

12.4
1) Detected by a permutation test (1,000 permutations) at a 0.01 level

The resistance level is represented as the disease index (DI) measured 20 d after inoculation using a 0–4 scale based on the extent of stem wilting: 0 (no symptoms), 1 (up to 25% stem wilting), 2 (26–50%), 3 (51–75%), and 4 (76–100%) (Habe 2018).

QTL analysis

A genetic map (Habe et al. 2019) was previously constructed using single-nucleotide polymorphism (SNP) markers. Since both diploid parents were highly heterozygous, the segregating population was considered a two-way pseudo testcross population (Grattapaglia and Sederoff 1994) and the parental maps were constructed. For RP, 1,476 heterozygous SNP loci were mapped, while for SP, 2,663 heterozygous SNP loci were mapped on 12 chromosomes (Supplemental Table 1). QTL Cartographer version 2.5 (Wang et al. 2005) was used to perform composite interval mapping (CIM; Zeng 1994), which was specifically designed to reduce background noise that can affect QTL detection; CIM was performed on a backcross design by regarding the F1 population as a backcross population. Parameters of the analysis were set for model 6 with a window size of 2 cM and 0.05 probabilities for “into” and “out”. A LOD threshold for QTL detection was obtained via permutation tests using 1,000 repetitions to control for a genome-wide error rate of 1%. Since the distributions of DIs from the resistance tests using MAFF327001 at 28°C and MAFF327095 at 24°C were slightly distorted from normal distributions, an additional QTL analysis was performed on all data using an R/qtl package (Broman et al. 2003) of R software (R Core Team 2017) which performs nonparametric QTL mapping. The function “scanone” with model=“np” and step = 1 cM was used for nonparametric interval mapping, which is an extension of the Kruskal–Wallis test (Kruskal and Wallis 1952; Kruglyak and Lander 1995). A 5% LOD score threshold was determined using a permutation test (1,000 permutations). The interval estimate of genetic factor location was calculated using the “lodint” function, which computes the interval position corresponding to 1.0-LOD support intervals; the “expandtomarkers” argument determines the nearest flanking markers of the interval’s higher limits. QTL analyses were performed separately for each of the two parental linkage maps. Linkage maps and QTL positions were drawn using MapChart 2.30 (Voorrips 2002).

Statistical analysis

All statistical analyses, excluding QTL analysis, were performed using Rcmdr package (Fox 2005) and EZR package (Kanda 2013) of R version 3.3.3. (R Core Team 2017). Phenotypic correlations between variables were estimated using the Spearman’s rank coefficient for each trial. The Mann–Whitney U test was performed to analyze the mean DIs of the F1 population on the allele differences of the markers at the nearest locus of each QTL.

Results

Evaluation of BW resistance

The 94 plants in the F1 population were evaluated under six treatments: three strains (phylotype I/biovar 4, phylotype IV/biovar 2A, and phylotype I/biovar 3) at two incubation temperatures (24°C or 28°C). The DIs of RP 10-03-30 varied from 0.00–0.73, while those of SP F1-1 ranged from 2.00–3.47, indicating a clear difference between the parents in all treatments (Fig. 1). The DIs of F1 plants varied consistently between susceptible and resistant plants in all treatments, with the mean DIs ranging from 1.21–2.88 (Fig. 1), and were all positively correlated between treatments (r = 0.25–0.61, P < 0.05)(Supplemental Table 2). Incubation at 28°C was associated with relatively higher DIs for all strains, and phenotypes with higher and lower DIs than those of SP and RP, respectively (transgressive segregation) were observed in all treatments. Particularly, the DIs against the strain MAFF327142 (phylotype I/biovar 4) changed drastically between temperatures: the distribution was skewed toward relatively lower DIs at 24°C, whereas its was skewed toward relatively higher DIs at 28°C. Thus, the resistance in the F1 population against MAFF327142 varied greatly depending on the incubation temperature.

QTL detection

Since the F1 population exhibited both normal and skewed distributions at different treatments, CIM and nonparametric interval mapping were performed for the DIs of the F1 population using the RP map consisting of 1,476 SNP markers and the SP map consisting of 2,663 SNP markers. The LOD thresholds were determined using permutation tests with 1000 repetitions for the 1% significance level in CIM and 5% significance level in nonparametric interval mapping analysis. The CIM analysis identified ten QTLs on seven chromosomes (qBWR-1a, qBWR-1b, qBWR-3, qBWR-5, qBWR-6a, qBWR-6b, qBWR-7, qBWR-10a, qBWR-10b, and qBWR-11) (Table 1). Nonparametric interval mapping analysis revealed four QTLs on three chromosomes (qBWR-3, qBWR-6a, qBWR-6b, and qBWR-7): three of them were detected in the same treatments via the two analyses, whereas qBWR-3 was detected against MAFF327001 (phylotype I/biovar 4) at 28°C via CIM analysis and against MAFF327095 (phylotype IV/biovar 2A) at 28°C via nonparametric interval mapping analysis (Table 2). The locations of these QTLs are schematically shown in Fig. 2.

Table 2

Genetic factors detected by a nonparametric QTL mapping method for the resistance to the R. solanacearum species complex in the F1 population

BW strain

Temperature

QTL1)

Detected map

Chr

Position (cM)2)

Position of maximum LOD (cM)

Maximum LOD score

MAFF327142

(Phylotype I/

biovar 3)

24 C°

qBWR-6b

R map

6

10.8–33.6

28.0

8.66

28 C°

qBWR-6b

R map

6

10.8–42.0

21.7

3.42

qBWR-6a

S map

6

0.0–26.4

2.0

2.59

MAFF327001

(Phylotype I/biovar 4)

24 C°

qBWR-7

R map

7

12.2–31.1

27.8

4.82

28 C°

qBWR-7

R map

7

12.2–65.5

28.9

3.17

MAFF327095

(Phylotype IV/biovar 2A)

28 C°

qBWR-3

S map

3

5.4–36.4

18.8

2.91
1)Detected by a permutation test (1,000 permutations) at a 0.05 level
2)Positions were indicated by the 1.0-LOD interval

Function of the detected QTLs

The mean DIs for two genotypes (AA or AB since the population was treated as a pseudo testcross population) in the nearest SNP locus to the QTL were compared (Table 3). All QTLs showed significant resistance effects, although to varying degrees, on at least one strain. qBWR-6b, located at 21.7 cM in chromosome 6, considerably contributed to the resistance to MAFF327142 (phylotype I/biovar 3) alone at both 24°C and 28°C (explaining 40.5% and 17.6% of the variances, respectively). qBWR-6a and qBWR-10b contributed to the resistance against this strain at 28°C and 24°C, respectively. qBWR-3 located at 15.0 cM in chromosome 3 considerably contributed to resistance against MAFF327142 at 24°C, while qBWR-7, located at 25.3 cM in chromosome 7, contributed to resistance against this strain at 28°C. Furthermore, qBWR-3 and qBWR-7 conferred resistance against MAFF327001 (phylotype I/biovar 4) and MAFF327095 (phylotype IV/biovar 2A) at both temperatures. The other five QTLs qBWR-1a, qBWR-1b, qBWR-5, qBWR-10a, and qBWR-11 conferred resistance to a minor extent and were more effective at 28°C than at 24°C (Table 3).

Table 3

Mean DIs in BW resistant vs susceptible genotypes

QTL

SNP1)

MAFF327142

(Phylotype I/biovar 3)

  

MAFF327001

(Phylotype I/biovar 4)

  

MAFF327095

(Phylotype IV/biovar 2A)

24 C°

28 C°

  

24 C°

28 C°

  

24 C°

28 C°

qBWR-1a

c2_4943

1.25 vs 1.47

2.67 vs 3.07*

  

1.29 vs 1.40

1.53 vs 1.71

  

1.40 vs 1.46

1.69 vs 2.29**

qBWR-1b

c2_37816

1.19 vs 1.46

2.64 vs 3.05*

  

1.30 vs 1.41

1.51vs 1.71

  

1.41 vs 1.45

1.68 vs 2.31**

qBWR-3

c2_50637

1.10 vs 1.75**

2.76 vs 3.05

  

1.15 vs 1.64**

1.45 vs 1.88**

  

1.23 vs 1.74**

1.80 vs 2.32**

qBWR-5

c2_10291

1.15 vs 1.47

2.83 vs 2.91

  

1.26 vs 1.44

1.36 vs 1.82**

  

1.39 vs 1.49

1.90 vs 2.12

qBWR-6a

c2_55554

0.98 vs 1.63*

2.48 vs 3.15***

  

1.29 vs 1.39

1.45 vs 1.74*

  

1.26 vs 1.55

1.89 vs 2.08

qBWR-6b

c1_12696

0.73 vs 2.19***

2.53 vs 3.31***

  

1.32 vs 1.38

1.59 vs 1.68

  

1.46 vs 1.39

2.01 vs 1.99

qBWR-7

c2_4555

1.11 vs 1.57

2.56 vs 3.16**

  

0.98 vs 1.73***

1.31 vs 1.90***

  

1.23 vs 1.65**

1.74 vs 2.29**

qBWR-10a

c2_32779

1.27 vs 1.45

2.72 vs 3.05

  

1.24 vs 1.46

1.45 vs 1.80*

  

1.38 vs 1.49

2.00 vs 2.03

qBWR-10b

c2_22699

0.90 vs 1.70***

2.75 vs 2.96

  

1.32 vs 1.40

1.51 vs 1.71

  

1.41 vs 1.45

1.76 vs 2.24*

qBWR-11

c1_7668

1.29 vs 1.54

2.77 vs 3.22*

  

1.27 vs 1.61

1.53 vs 1.93*

  

1.32 vs 1.77*

1.88 vs 2.47**
Significance levels between resistant and susceptible genotypes were tested by Mann-Whitney U-test; *0.05, **0.01, ***0.001
1)SNP identity was given without the prefixed identity “solcap_snp_”

Discussion

Polygenic segregation of BW resistance in the hybrid population

BW resistance is controlled by multiple genes in potato plants (Elphinstone 1994; Rowe and Sequeira 1970; Sequeira 1979) and is greatly influenced by environmental conditions such as temperature and soil moisture (Tung et al. 1990a, b). Different strains show resistance to different extents (French and De Lindo 1982; Katayama and Kimura 1984; Tung et al. 1990a; Suga et al. 2013). Thus, the resistance was evaluated against three strains using an in vitro assay method (Habe 2018) under controlled environmental conditions at 24°C and 28°C. The RP and SP plants showed stable resistance and susceptibility against all the strains used, including phylotype I/biovar 3, phylotype I/biovar 4, and phylotype IV/biovar 2A. The resistance levels in the hybrid population varied consistently, confirming that the resistance was polygenically controlled, and the resistance was positively correlated among all six treatments, indicating that the pathogenicity was similar between phylotypes I and IV in potato plants. This was in agreement with previous findings that indicate no difference in virulence between phylotypes I and IV and between phylotypes II and III in potato cultivars (Habe et al. 2016; Sharma et al. 2021). Although Suga et al. (2013) reported that phylotype IV is more virulent than phylotype I, the classification of phylotypes may not correlate with the degree of virulence as suggested for tomato, eggplant, and pepper plants (Lebeau et al. 2011).

Segregation of multiple resistance QTLs in the hybrid population

CIM and non-parametric QTL mapping were performed to evaluate BW resistance using a hybrid population, which identified five major QTLs (qBWR-3, qBWR-6a, qBWR-6b, qBWR-7, and qBWR-10b) and five minor QTLs (qBWR-1a, qBWR-1b, qBWR-5, qBWR-10a, and qBWR-11). Only QTLs conferring heterozygous resistance in either one of the parents could be segregated and mapped in the population. Thus, the ten QTLs were likely the minimal ones that could be detected using this population. The combined segregation resulted in transgressive segregation, where hybrid plants with higher levels of resistance than that in RP and those with lower levels of susceptibility than that in SP were obtained. The resistance-related QTL alleles were derived from both parents.

Resistance specificity to strains and temperatures

We found strain-specific and temperature-dependent QTLs (qBWR-6a, qBWR-6b, and qBWR-10b) and strain-non-specific and broad-spectrum resistance QTLs (qBWR-3 and qBWR-7). qBWR-6a, qBWR-6b, and qBWR-10b considerably contributed to the resistance to MAFF327142 (phylotype I/biovar 3), in which the latter two were more effective at 24°C. The distributions of the DIs in the F1 population were skewed toward relatively lower DIs at 24°C and toward higher DIs at 28°C, which was likely due to the effect of qBWR-6b (Fig. 1ab). qBWR-6b was considered to be derived from RP 10-03-30, a haploid clone of Saikai 35 (Habe et al. 2019), which was originally derived from S. phureja (Mori et al. 2012). S. phureja is a well-known source of BW-resistant factors, and the resistance is strain-specific and sensitive to high temperatures (Sequeira and Rowe 1969; Sequeira 1979; Ciampi and Sequeira 1980; French and De Lindo 1982). The strain-specific resistance of S. phureja appeared to be simply inherited in few cases (Elphinstone 1994). Therefore, we suggest that qBWR-6b was derived from S. phureja and functions as a simply-inherited, major QTL at low temperatures. qBWR-3 and qBWR-7 showed stable resistance to all strains at low and high temperatures, irrespective of different phylotypes and biovars. These QTLs may be effective under diverse environmental conditions and highly desired in breeding BW-resistant cultivars.

Reliability of the BW resistance QTLs

Chen et al. (2013) identified S. chacoense-derived BW resistance QTLs against the race 1/biovar 3 strain on chromosomes 2 and 9. The SP used in our study was F1-1, an interspecific hybrid between S. chacoense and S. phureja (Hosaka and Hanneman 1998). However, we did not identify any QTLs on chromosomes 2 and 9, indicating that the source of resistance factors for all the QTLs detected in our study was S. phureja. In our previous study using the same F1 population and the same inoculum (MAFF327001, phylotype I/ biovar 4) at 28°C, five QTLs were identified on chromosomes 1, 3, 7, 10, and 11 (Habe et al. 2019). When their locations were compared, the previously identified QTLs qBWR-1, qBWR-2, qBWR-3, qBWR-4, and qBWR-5 correspond to the QTLs identified in the present study: qBWR-1b, qBWR-3, qBWR-7, qBWR-10a, and qBWR-11, respectively. The QTL qBWR-5 on chromosome 5 which showed a minor contribution to resistance was newly found, and qBWR-11 was not significant in this study (Table 1). Repeated resistance assays may increase or decrease certain genetic variances, affecting significance levels of the QTLs. Here, difficulty in the BW resistance evaluation was featured again, and importance of the major-effect QTLs is emphasized.

Universal resistance QTLs

BW resistance QTLs have been identified in chromosomes 3, 4, 6, 8, 10, 11, and 12 in tomato plants (Thoquet et al. 1996a, 1996b; Mangin et al. 1999; Carmeille et al. 2006; Wang et al. 2000, 2013) and in chromosomes 1, 2, 3, 4, 5, 6, 7, 8, and 9 in eggplants (Mimura et al. 2012; Lebeau et al. 2013; Salgon et al. 2017, 2018). Comparison of the physical location in each chromosome indicates that the strain-specific resistance QTL qBWR-6b is likely to be colocalized with tomato QTL (Bwr-6) and eggplant QTL (ERPR6) on chromosome 6 (Fig. 3b). However, both Bwr-6 and ERPR6 confer resistance against phylotypes І and ІІ (Carmeille et al. 2006; Wang et al. 2013; Salgon et al. 2018; Shin et al. 2020), whereas the resistance of qBWR-6b is limited to phylotype I/biovar 3. The mapping position of Bwr-6 slightly varies depending on different inoculums and field conditions (Wang et al. 2013), which was similarly observed for ERPR6 (Salgon et al. 2018). These findings indicate that strain-specific single-locus resistance genes are clustered on the same chromosome (Meyers et al. 1998; Andolfo et al. 2013), which superficially made Bwr-6 and ERPR6 broad-spectrum resistance genes (Salgon et al. 2018). For Bwr-6 in tomato, 18 candidate genes have been proposed (Kim et al. 2018; Shin et al. 2020; Abebe et al. 2020).

A tomato-derived QTL (Bwr-3) and two eggplant-derived QTLs (ERPR3a and ERPR3b) have been reported on chromosome 3 (Thoquet et al. 1996b; Carmeille et al. 2006; Wang et al. 2013; Salgon et al. 2018). Bwr-3 and ERPR3b are colocalized and may include the same locus (Salgon et al. 2018), while the potato-derived QTL qBWR-3 is likely colocalized with ERPR3a (Fig. 3a). Like qBWR-3, ERPR3a is a strain-non-specific, broad-spectrum QTL (Salgon et al. 2018). The nearest SNP locus to qBWR-3 (solcap_snp_c2_50637) is located in the receptor-like kinase gene (PGSC0003DMG400016685). This gene may represent one of candidate genes for BW resistance because a leucine-rich repeat receptor-like kinase gene (ERECTA) is involved in BW resistance in Arabidopsis thaliana (Godiard et al. 2003).

The broad-spectrum resistance QTL qBWR-7 was detected in a span between 12.2 and 27.2 cM or between 10.9 and 39.2 Mb near the centromere, where recombination is less likely to occur, and comprised 23 SNP loci at the peak position (25.3 cM) (Table 1). The long arm of chromosome 7 in potato plants harbors a resistance gene hotspot containing Rpi1 and Rpi2 against Phytophthora infestans and Gro1-4 against Globodera rostochiensis (Ballvora et al. 1995; Kuhl et al. 2001; Paal et al. 2004; Ruggieri et al. 2014; Yan et al. 2017); however, qBWR-7 is considered to be excluded in this hot spot. Since the effect of resistance of qBWR-7 is slightly higher than that of qBWR-3, additional fine mapping is desired to determine the accurate location and to develop molecular markers.

Conclusion

RSSC strains have spread worldwide and show a wide host range (Hayward 1985; Peeters et al. 2013). Potatoes are infected by all four phylotypes of this species complex. Therefore, BW-resistant varieties are sought after that show resistance to these four phylotypes. The phylotype-specific resistance has been reported in S. phureja (Suga et al. 2013), which emphasizes the need for phylotype-specific breeding (Horita et al. 2014). However, in tomato and eggplant, both phylotype-specific and non-specific, broad-spectrum resistance QTLs have been identified. We identified five major and five minor resistance QTLs, which included both strain-specific and broad-spectrum resistance QTLs. The major QTLs qBWR-3 and qBWR-7 showed stable resistance against R. pseudosolanacearum (phylotype I) and R. syzygii (phylotype IV), which are major phylotypes in Asia (Fegan and Prior 2005; Wicker et al. 2012). qBWR-6b is a strain-specific major resistance QTL against phylotype I/biovar 3 and can be effectively used in relatively cool area because the resistance conferred was more effective at a relatively lower temperature. Therefore, we suggest that broad-spectrum QTLs and strain-specific QTLs can be combined to develop the most efficient BW-resistant cultivars in particular areas.

Declarations

Acknowledgements

The authors thank Dr. Kazuyoshi Hosaka, Obihiro University of Agriculture and Veterinary Science, for improving the manuscript. We would like to thank Editage (www.editage.com) for English language editing.

Author Contributions

All authors contributed to the study design. Material preparation, data collection and analysis were performed by Ippei Habe. The first draft of the manuscript was written by Ippei Habe and all authors commented on previous versions of the manuscript. All authors approved the final manuscript.

Funding

This work was supported by Nagasaki prefectural government.

Availability of data and materials

All data generated or analyzed during this study are included in this published article.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing Interests

The authors declare no competing interests.

References

  1. Andolfo G, Sanseverino W, Rombauts S, Van de Peer Y, Bradeen JM, Carputo D, Frusciante L, Ercolano MR (2013) Overview of tomato (Solanum lycopersicum) candidate pathogen recognition genes reveals important Solanum R locus dynamics. New Phytol 197:223–237
  2. Abebe AM, Choi J, Kim Y, Oh CS, Yeam I, Nou IS (2020) Development of diagnostic molecular markers for marker-assisted breeding against bacterial wilt in tomato. Breed Sci 70:462–473
  3. Ballvora A, Hesselbach J, Niewöhner J, Leiste D, Salamini F, Gebhardt C (1995) Marker enrichment and high-resolution map of the segment of potato chromosome VII harbouring the nematode resistance gene Gro1. Mol Gen Genet 249:82–90
  4. Broman KW, Wu H, Sen S, Churchill GA (2003) R/qtl: QTL mapping in experimental crosses. Bioinformatics 19:889–890
  5. Buddenhagen I, Kelman A (1964) Biological and physiological aspects of bacterial wilt caused by Pseudomonas solanacearum. Annu Rev Phytopathol 2:203–230
  6. Carmeille A, Caranta C, Dintinger J, Prior P, Luisetti J, Besse P (2006) Identification of QTLs for Ralstonia solanacarum race 3-phylotype II resistance in tomato. Theor Appl Genet 113:110–121
  7. Carputo D, Aversano R, Barone A, Di Matteo A, Iorizzo M, Sigillo L, Zoina A, Frusciante L (2009) Resistance to Ralstonia solanacearum of sexual hybrids between Solanum commersonii and S. tuberosum. Am J Pot Res 86:196–202
  8. Chen L, Guo X, Xie C, He L, Cai X, Tian L, Song B, Liu J (2013) Nuclear and cytoplasmic genome components of Solanum tuberosum + S. chacoense somatic hybrids and three SSR alleles related to bacterial wilt resistance. Theor Appl Genet 126:1861–1872
  9. Ciampi L, Sequeira L (1980) Influence of temperature on virulence of race 3 strains of Pseudomonas solanacearum. Am Potato J 57:307–317
  10. Denny TP (2006) Plant pathogenic Ralstonia species. In: Gnanamanickam SS (ed) Plant-associated bacteria. Springer, Dordrecht, pp 573–644
  11. Elphinstone JG (1994) Inheritance of resistance to bacterial diseases. In: Bradshaw JE, Mackay GR (eds) Potato genetics. CAB international, Wallingford, pp 429–446
  12. Fegan M, Prior P (2005) How complex is the Ralstonia solanacearum species complex. In: Allen C, Prior P, Hayward AC (eds) Bacterial wilt disease and the Ralstonia solanacearum species complex. APS Press, St. Paul, pp 449–461
  13. Fock I, Collonnier C, Purwito A, Luisetti J, Souvannavong V, Vedel F, Servaes A, Ambroise A, Kodja H, Ducreux G, Sihachakr D (2000) Resistance to bacterial wilt in somatic hybrids between Solanum tuberosum and Solanum phureja. Plant Sci 160:165–176
  14. Fock I, Collonnier C, Luisetti J, Purwito A, Souvannavong V, Vedel F, Servaes A, Ambroise A, Kodja H, Ducreux G, Sihachakr D (2001) Use of Solanum stenotomum for introduction of resistance to bacterial wilt in somatic hybrids of potato. Plant Physiol Biochem 39:899–908
  15. Food and Agriculture Organization of the United Nations (2021) Food and agriculture data. https://www.fao.org/faostat/en/#home
  16. Fox J (2005) The R Commander: A basic statistics graphical user interface to R. J Stat Softw 14:1–42
  17. French ER, De Lindo L (1982) Resistance to Pseudomonas solanacearum in potato: specificity and temperature sensitivity. Phytopathology 72:1408–1412
  18. French ER, Anguiz R, Aley P (1998) The usefulness of potato resistance to Ralstonia solanacearum, for the integrated control of bacterial wilt. In: Prior P, Allen C, Elphinstone J (eds) Bacterial wilt disease: molecular and ecological aspects. Springer Verlag, Berlin, pp 381–385
  19. Gillings MR, Fahy P (1994) Genomic fingerprinting: towards a unified view of the Pseudomonas solanacearum species complex. In: Hayward AC, Hartman GL (eds) Bacterial wilt: the Disease and Its Causative Agent, Pseudomonas solanacearum. CAB INTERNATIONAL, Wallingford, pp 95–112
  20. Godiard L, Sauviac L, Torii KU, Grenon O, Mangin B, Grimsley NH, Marco Y (2003) ERECTA, an LRR receptor-like kinase protein controlling development pleiotropically affects resistance to bacterial wilt. Plant J 36:353–365
  21. Grattapaglia D, Sederoff R (1994) Genetic linkage maps of Eucalyptus grandis and Eucalyptus urophylla using a pseudo-testcross: mapping strategy and RAPD markers. Genetics 137:1121–1137
  22. Habe I (2016) Pathogenic characteristics by temperature of Ralstonia solanacearum phylotypes I and â…£ using in vitro screening assay for resistance to bacterial wilt in potato. Kyushu Plant Protec Res 62:20–26
  23. Habe I (2018) An in vitro assay method for resistance to bacterial wilt (Ralstonia solanacearum) in potato. Am J Potato Res 95:311–316
  24. Habe I, Miyatake H, Nunome T, Yamasaki M, Hayashi T (2019) QTL analysis of resistance to bacterial wilt caused by Ralstonia solanacearum in potato. Breed Sci 69:592–600
  25. Hayward AC (1985) Bacterial wilt caused by Pseudomonas solanacearum in Asia and Australia: an overview. In: Persley GJ (ed) Bacterial wilt disease in Asia and the South Pacific: proceedings of an international workshop held at PCARRD, ACIAR Proceedings No. 13. Canberra, pp 15–24
  26. Hendrick CA, Sequeira L (1984) Lipopolysaccharide-defective mutants of the wilt pathogen Pseudomonas solanacearum. Appl Environ Microbiol 48:94–101
  27. Horita M, Suga Y, Ooshiro A, Tsuchiya K (2010) Analysis of genetic and biological characters of Japanese potato strains of Ralstonia solanacearum. J Gen Plant Pathol 76:196–207
  28. Horita M, Tsuchiya K, Suga Y, Yano K, Waki T, Kurose D, Furuya N (2014) Current classification of Ralstonia solanacearum and genetic diversity of the strains in Japan. J Gen Plant Pathol 80:455–465
  29. Hosaka K, Hanneman RE (1998) Genetic of self-compatibility in a self-incompatible wild diploid potato species Solanum chacoense. 1. Detection of an S locus inhibitor (Sli) gene. Euphytica 99:191–197
  30. Huet G (2014) Breeding for resistances to Ralstonia solanacearum. Front Plant Sci 5:715
  31. Kanda Y (2013) Investigation of the freely available easy-to-use software ‘EZR’ for medical statistics. Bone Marrow Transplant 48:452–458
  32. Katayama K, Kimura S (1984) Prevalence and temperature requirements of biovar II and â…£ strains of Pseudomonas solanacearum from potatoes. Ann Phytopath Soc Japan 50:476–482
  33. Kelman A (1954) The relationship of pathogenicity of Pseudomonas solanacearum to colony appearance in a tetrazolium medium. Phytopathology 44:693–695
  34. Kim B, Hwang IS, Lee HJ, Lee JM, Seo E, Choi D, Oh CS (2018) Identification of a molecular marker tightly linked to bacterial wilt resistance in tomato by genome-wide SNP analysis. Theor Appl Genet 131:1017–1030
  35. Kim-Lee H, Moon JS, Hong YJ, Kim MS, Cho HM (2005) Bacterial wilt resistance in the progenies of the fusion hybrids between haploid of potato and Solanum commersonii. Am J Potato Res 82:129–137
  36. Kruglyak L, Lander ES (1995) A nonparametric approach for mapping quantitative trait loci. Genetics 139:1421–1428
  37. Kruskal WH, Wallis WA (1952) Use of ranks in one-criterion variance analysis. J Am Stat Assoc 47(260):583–621
  38. Kuhl J, Hanneman REJr, Havey M (2001) Characterization and mapping of Rpi1, a late-blight resistance locus from diploid (1EBN) Mexican Solanum pinnatisectum. Mol Genet Genomics 265:977–985
  39. Laferriere LT, Helgeson JP, Allen C (1999) Fertile Solanum tuberosum + S. commersonii somatic hybrids as sources of resistance to bacterial wilt caused by Ralstonia solanacearum. Theor Appl Genet 98:1272–1278
  40. Lebeau A, Daunay MC, Frary A, Palloix A, Wang JF, Dintinger J, Chiroleu F, Wicker E, Prior P (2011) Bacterial wilt resistance in tomato, pepper, and eggplant: genetic resources respond to diverse strains in the Ralstonia solanacearum species complex. Phytopathology 101:154–165
  41. Lebeau A, Gouy M, Dauuay MC, Wicker E, Chiroleu F, Prior P, Frary A, Dintinger J (2013) Genetic mapping of a major dominant gene for resistance to Ralstonia solanacearum in eggplant. Theor Appl Genet 126:143–158
  42. Liu T, Yu Y, Cai X, Tu W, Xie C, Liu J (2016) Introgression of bacterial wilt resistance from Solanum melongena to S. tuberosum through asymmetric protoplast fusion. Plant Cell Tissue Organ Cult 125:433–443
  43. Mangin B, Thoquet P, Olivier J, Grimsley NH (1999) Temporal and multiple quantitative trait loci analyses of resistance to bacterial wilt in tomato permit the resolution of linked loci. Genetics 151:1165–1172
  44. Mansfield J, Genin S, Magori S, Citovsky V, Sriariyanum M, Ronald P, Dow M, Verdier V, Beer SV, Machado M, Toth I, Salmond G, Foster GD (2012) Top 10 plant pathogenic bacteria in molecular plant pathology. Mol Plant Pathol 13:614–629
  45. Meyers BC, Chin DB, Shen KA, Sivaramakrishnan S, Lavelle DO, Zhang Z, Michelmore R (1998) The major resistance gene cluster in lettuce is highly duplicated and spans several megabases. Plant Cell 10:1817–1832
  46. Mimura Y, Inoue T, Minamiyama Y, Kubo N (2012) An SSR-based genetic map of pepper (Capsicum annuum L.) serves as an anchor for the alignment of major pepper maps. Breed Sci 62:93–98
  47. Mori K, Mukojima N, Nakao T, Tamiya S, Sakamoto Y, Sohbaru N, Hayashi K, Watanuki H, Nara K, Yamazaki K, Ishii T, Hosaka K (2012) Germplasm release: Saikai 35, a male and female fertile breeding line carrying Solanum phureja-derived cytoplasm and potato cyst nematode resistance (H1) and Potato virus Y resistance (Rychc) genes. Am J Potato Res 89:63–72
  48. Murashige T, Skoog F (1962) A revised medium for rapid growth and bio assays with tobacco tissue cultures. Physiol Plant 15:473–497
  49. Paal J, Henselewski H, Muth J, Meksem K, Menéndez CM, Salamini F, Ballvora A, Gebhardt C (2004) Molecular cloning of the potato Gro1–4 gene conferring resistance to pathotype Ro1 of the root cyst nematode Globodera rostochiensis, based on a candidate gene approach. Plant J 38:285–297
  50. Peeters N, Guidot A, Vailleau F, Valls M (2013) Ralstonia solanacearum, a widespread bacterial wilt plant pathogen in the post-genomic era. Mol Plant Pathol 14:651–662
  51. Prior P, Ailloud F, Dalsing BL, Remenant B, Sanchez B, Allen C (2016) Genomic and proteomic evidence supporting the division of the plant pathogen Ralstonia solanacearum into three species. BMC Genomics 17:90
  52. R Core Team (2017) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria
  53. Rowe PR, Sequeira L (1970) Inheritance of resistance to Pseudomonas solanacearum in Solanum phureja. Phytopathology 60:1499–1501
  54. Ruggieri V, Nunziata A, Barone A (2014) Positive selection in the leucine-rich repeat domain of Gro1 genes in Solanum species. J Genet 93:755–765
  55. Safni I, Cleenwerck I, De Vos P, Fegan M, Sly L, Kappler U (2014) Polyphasic taxonomic revision of the Ralstonia solanacearum species complex: proposal to emend the descriptions of Ralstonia solanacearum and Ralstonia syzygii and reclassify current R. syzygii strains as Ralstonia syzygii subsp. syzygii subsp. nov., R. solanacearum phylotype IV strains as Ralstonia syzygii subsp. indonesiensis subsp. nov., banana blood disease bacterium strains as Ralstonia syzygii subsp. celebesensis subsp. nov. and R. solanacearum phylotype I and III strains as Ralstonia pseudosolanacearum sp. nov. Int J Syst Evol Microbiol 64:3087–3103
  56. Sakamoto Y, Mori K, Matsuo Y, Mukojima N, Watanabe W, Sobaru N, Tamiya S, Nakao T, Hayashi K, Watanuki H, Nara K, Yamazaki K, Chaya M (2017) Breeding of a new potato variety ‘Nagasaki Kogane’ with high eating quality, high carotenoid content, and resistance to diseases and pests. Breed Sci 67:320–326
  57. Salgon S, Jourda C, Sauvage C, Daunay M-C, Reynaud B, Wicker E, Dintinger J (2017) Eggplant resistance to the Ralstonia solanacearum species complex involves both broad-spectrum and strain-specifc quantitative trait loci. Front Plant Sci 8:828
  58. Salgon S, Raynal M, Lebon S, Baptiste JM, Daunay MC, Dintinger J, Jourda C (2018) Genotyping by sequencing highlights a polygenic resistance to Ralstonia pseudosolanacearum in eggplant (Solanum melongena L.). Int J Mol Sci 19:357
  59. Sequeira L (1979) Development of resistance to bacterial wilt derived from Solanum phureja. Developments in control of potato bacterial diseases. CIP, Lima, Peru, pp 55–62
  60. Sequeira L, Rowe PR (1969) Selection and utilization of Solanum phureja clones with high resistance to different strains of Pseudmonas solanacearum. Am Potato J 46:451–462
  61. Sharma SK, Bolser D, de Boer J, Sønderkær M, Amoros W, Carboni MF, D’Ambrosio JM, de la Cruz G, Genova AD, Douches DS, Eguiluz M, Guo X, Guzman F, Hackett CA, Hamilton JP, Li G, Li Y, Lozano R, Maass A, Marshall D, Martinez D, McLean K, Mejía N, Milne L, Munive S, Nagy I, Ponce O, Ramirez M, Simon R, Thomson SJ, Torres Y, Waugh R, Zhang Z, Huang S, Visser RGF, Bachem CWB, Sagredo B, Feingold SE, Orjeda G, Veilleux RE, Bonierbale M, Jacobs JME, Milbourne D, Martin DMA, Bryan GJ (2013) Construction of reference chromosome-scale pseudomolecules for potato: integrating the potato genome with genetic and physical maps. G3. Genes Genomics Genetics 3:2031–2047
  62. Sharma K, Kreuse J, Abdurahan A, Parker M, Nduwayezu A, Rukundo P (2021) Molecular diversity and pathogenicity of Ralstonia solanacearum species complex associated with bacterial wilt of potato in Rwanda. Plant Dis 105:770–779
  63. Shin IS, Hsu JC, Huang SM, Chen JR, Wang JF, Hanson P, Schafleitner R (2020) Construction of a single nucleotide polymorphism marker based QTL map and validation of resistance loci to bacterial wilt caused by Ralstonia solanacearum species complex in tomato. Euphytica 216:54
  64. Suga Y, Horita M, Umekita M, Furuya N, Tsuchiya K (2013) Pathogenic characters of Japanese potato strains of Ralstonia solanacearum. J Gen Plant Pathol 79:110–114
  65. Thoquet P, Olivier J, Sperisen C, Rogowsky P, Laterrot H, Grimsley N (1996a) Quantitative trait loci determining resistance to bacterial wilt in tomato cultivar Hawaii7996. Mol Plant Microbe Interact 9:826–836
  66. Thoquet P, Olivier J, Sperisen C, Rogowsky P, Prior P, Anais G, Mangin B, Bazin B, Nazer R, Grimsley N (1996b) Polygenic resistance of tomato plants to bacterial wilt in the French West Indies. Mol Plant Microbe Interact 9:837–842
  67. Thurston HD, Lozaro TJC (1968) Resistance to bacterial wilt of potatoes in Colombian clones of Solanum phureja. Am Potato J 45:51–55
  68. Tung PX, Rasco ET, Vander Zaag P, Schmiediche P (1990a) Resistance to Pseudomonas solanacearum in the potato: I. Effects of sources of resistance and adaptation. Euphytica 45:203–210
  69. Tung PX, Rasco ET, Vander Zaag P, Schmiediche P (1990b) Resistance to Pseudomonas solanacearum in the potato: II. Aspects of host-pathogen-environment interaction. Euphytica 45:211–215
  70. Voorrips RE (2002) Mapchart: software for the graphical presentation of linkage maps and QTLs. J Hered 93:77–78
  71. Wang S, Basten CJ, Graffney P, Zeng ZB (2005) Windows QTL Cartographer 2.5 user manual. Bioinformatics Research Center, North Carolina State University, Raleigh
  72. Wang JF, Olivier J, Thoquet P, Mangin B, Sauviac L, Grimsley NH (2000) Resistance of tomato line Hawaii 7996 to Ralstonia solanacearum Pss4 in Taiwan is controlled mainly by a major strain-specific locus. Mol Plant Microbe Interact 13:6–13
  73. Wang JF, Ho FI, Hong Truong HT, Huang SM, Balatero CH, Dittapongpitch V, Hidayati N (2013) Identification of major QTLs associated with stable resistance of tomato cultivar ‘Hawaii 7996’ to Ralstonia solanacearum. Euphytica 190:241–252
  74. Watanabe K, El-Nashaar HM, Iwanaga M (1992) Transmission of bacterial wilt resistance by first division restitution (FDR) 2n pollen via 4x×2x crosses in potatoes. Euphytica 60:21–26
  75. Wei Q, Wang J, Wang W, Hu T, Hu H, Bao C (2020) A high-quality chromosome-level genome assembly reveals genetics for important traits in eggplant. Hortic Res 7:153
  76. Wicker E, Lefeuvre P, de Cambiaire JC, Lemaire C, Poussier S, Prior P (2012) Contrasting recombination patterns and demographic histories of the plant pathogen Ralstonia solanacearum inferred from MLSA. Int Soc Microb Ecol J 6:961–974
  77. Yang L, Wang D, Xu Y, Zhao H, Wang L, Cao X, Chen Y, Chen Q (2017) A new resistance gene against potato late blight originating from Solanum pinnatisectum located on potato chromosome 7. Front Plant Sci 8:1729
  78. Zeng ZB (1994) Precision mapping of quantitative trait loci. Genetics 136:1457–1468
  79. Zhang Z, Schwartz S, Wagner L, Miller W (2000) A greedy algorithm for aligning DNA sequences. J Comput Biol 7:203–214