The genetic control of resistance to Ralstonia solanacearum in resistant tomato genotypes is determined by different genes

doi:10.21203/rs.3.rs-4680132/v1

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The genetic control of resistance to Ralstonia solanacearum in resistant tomato genotypes is determined by different genes

https://doi.org/10.21203/rs.3.rs-4680132/v1

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The tomato crop is one of the most studied fruit vegetables when it comes to genetics and breeding, with the aim of developing future cultivars that meet the needs of farmers and the consumer market. One of these needs is resistance to soil-borne diseases such as bacterial wilt caused by Ralstonia solanacearum, which causes major economic losses. One of the first steps in obtaining new cultivars is to determine the genetic control of their characteristics. Therefore, the aim of this study was to determine whether the Ralstonia solanacearum resistance loci of two resistant tomato genotypes are the same or not, based on an inheritance study. To this end, F₁, F₂, BC₁₁ and BC₂₁ generations were evaluated in one experiment, and 60 F_2:3 progenies were evaluated in a second experiment. In both experiments, the genitors Yoshimatsu and Hawaii 7996 were used as a control. A descriptive rating scale was used to evaluate all the treatments. The main result was that the genetic control of resistance to Ralstonia solanacearum in the two resistant tomato genotypes is determined by different genes. Two recessive genes were found in Yoshimatsu and one in Hawaii 7996.

Inheritance

Incidence

Bacteriosis

Solanaceous

Tomatoes are a fruit vegetable in great demand, being widely grown and consumed all over the world (Chaudhary et al. 2018). Its fruit is a healthy and functional food, as it is rich in nutrients, fiber, carbohydrates and vitamins (Petrucelli et al. 2022). For the food industry, the tomato is of great importance, as its fruit is versatile in its use and consumption, and can be eaten fresh or industrialized, such as sauces, extracts, preserves, among others, generating a wide variety of products (Heuvelink et al. 2018).

However, the tomato crop is very susceptible to attacks by phytopathogenic agents, which cause diseases that reduce the quantity and quality of fruit production. Among the diseases that affect tomatoes, bacterial wilt caused by Raltonia solanacearum species complex (RSSC) is considered one of the most destructive and infectious bacterial diseases (Abebe et al. 2020). It is a serious disease that can cause up to 91% loss in tomato production in tropical, subtropical and warm temperate regions (Hayward 1991; Cen et al. 2022).

The R. solanacearum species complex, is categorized into races, biovars and phylotypes, based on host diversity, the use of carbon sources and the analysis of the 16S-23S rRNA gene sequence of the strains, respectively (Cho et al. 2018, Hayward 1991). Based on genome sequencing, biochemical, cultural and physiological characteristics and DNA-DNA hybridization, the R. solanacearum complex is taxonomically classified into three independent species, R. solanacearum (phylotype II), R. pseudosolanacearum (phylotypes I and III) and R. syzygii (phylotype IV) (Safni et al. 2014). R. syzygii is divided into three subspecies: syzygii, indonesiensis and celebesensis (Prior et al. 2016).

Control of tomato bacterial wilt is considered a difficult and costly task for several reasons intrinsic to the Ralstonia solanacearum species complex, such as its wide host range, its long survival period in the soil and in crop residues, its high genetic variability and the difficulty of obtaining commercially acceptable resistant cultivars (Graham et al. 1979). However, obtaining cultivars resistant to bacterial wilt is considered the best approach to controlling this devastating disease (Lee et al. 2020).

There are no commercial cultivars on the market that are resistant to bacterial wilt. It is therefore necessary to obtain new cultivars to control this disease, as the introduction of resistance genes into a new cultivar is the most effective and sustainable control strategy, both in economic terms and in terms of ease of adoption by farmers (Batista et al. 2022). To this end, studying the genetic control of resistance to Ralstonia solanacearum in different genotypes is an essential step.

The genetic control of resistance to bacterial wilt is reported in the literature as monogenic (Grimault 1995), oligogenic (Sharma and Sharma 2015) and polygenic (Lima Neto et al. 2002). There are also reports of two recessive genes of greater effect with associated polygenes (Costa et al. 2019). These diverse responses obtained in the literature are the result of different experimental and statistical methodologies, isolates and species, sources of resistance and environments.

Thus, genetic control studies are needed with different sources of resistance, such as the Yoshimatsu and IPA-7 genotypes, in order to find out whether these sources of resistance have the same genetic control or not, so that breeding programs can be more efficient in the process of obtaining new cultivars. Therefore, the aim of this work was therefore to determine the genetic control of the resistance of the tomato genotypes Yoshimatsu and Hawaii 7996 to Ralstonia solanacearum and to determine whether the resistance loci that govern the trait in these materials are the same.

Place and period of experiments

The two field studies were carried out in greenhouse conditions belonging to the Agronomy Department of the Federal Rural University of Pernambuco (DEPA/UFRPE). The location is at the following coordinates: 8°01'02“S and 34°56'41”O). The first experiment was developed for the study of P₁, P₂, F₁, F₂, BC₁₁ and BC₂₁) from November 2018 to December 2018, when the average temperature and relative humidity were 70.62% and 29.55°C, respectively. The second experiment was carried out to study the F_2:3 progenies from January 2019 to March 2019, with an average temperature and relative humidity of 30.11°C and 75.28%, respectively. To obtain climate data, a portable thermo-hygrometer was used inside the greenhouse.

Plant material and isolate

In hydroponic cultivation in the UFRPE greenhouse, crosses were made between bacterial wilt-resistant genitors (Yoshimatsu and Hawaii 7996). The following generations were acquired: P₁, P₂, F₁, F₂, BC₁₁, BC₂₁ and F_2:3. To carry out this stage, the techniques and procedures described by Costa (2017) were used. According to Costa et al. (2023), Yoshimatsu and Hawaii 7996 are reported as genotypes resistant to bacterial wilt. Yoshimatsu is considered a resistant cultivar in Brazil and Hawaii 7996 is called a cultivar with an international standard of resistance to this disease (Nick and Silva 2016).

All of the above treatments were tested for resistance to bacterial wilt caused by R. solanacearum. To this end, the CRMRs185 isolate was used, which was collected and characterized by the Phytobacteriology Laboratory at the Federal University of Rural Pernambuco. The isolate is characterized as biovar 1, sequevar II/50, and phylotype II. This isolate was obtained from tomato plants in the municipality of Petrolina, in the state of Pernambuco, Brazil.

A randomized block design with three replications was used to set up the two experiments. In the first, six treatments were evaluated using 99 plants from each parent and the F1 generation; 180 plants from each backcross (BC₁₁ and BC₂₁); and 402 plants from the F₂ generation. As a control, 99 plants of the susceptible cultivar IPA-7 were evaluated in order to find out about pathogenicity in susceptible plants. Next, 62 treatments were evaluated, consisting of 60 F_2:3 progenies along with the parents Yoshimatsu and Hawaii 7996. Each progeny was represented by 15 plants.

For sowing, 128-cell tomato seedling trays filled with Basaplant® pine bark substrate were used. According to the development and needs of the plants, fertigation with a nutrient solution was carried out in order to form high standard seedlings. After 21 days, the seedlings were transplanted into 500 mL plastic pots filled with a 3:1 soil:humus mixture.

Inoculation of Ralstonia solanacearum

The isolates mentioned above were obtained from preservation in water and were cultivated in TTC (triphenyltetrazolium tetrachloride) medium (Kelman 1954) for 48 hours at 28°C. A photocolorimeter (Analyser 500 M, Brazil) was used to adjust the bacterial suspension to A570 = 0.54 = 1x10⁸ CFU mL-1. At 30 days after sowing, the Jerusalem artichoke plants were inoculated by cutting the root followed by depositing the inoculum, using a scalpel to make a semicircular cut in the soil mixture near the neck of the plant, in which 15 mL of the bacterial suspension was deposited (Felix et al. 2012).

Assignment of phenotypes using a grading scale

At 20 days after inoculation, the disease was assessed using a descriptive scale with scores ranging from 1 to 5, adapted from Nielsen and Haynes (1960), where 1 = no symptoms; 2 = plants with up to 1/3 of the leaves wilted; 3 = plants with up to 2/3 of the leaves wilted; 4 = plants completely wilted; and 5 = dead plants. To classify resistant and susceptible plants, grade 2 was used as the truncation point (TP). Plants with scores 1 and 2 were considered resistant and those with scores 3, 4 and 5 susceptible.

Statistical analyses

Statistical analyses were carried out separately for each experiment. With the data from the first experiment, frequency distribution graphs of bacterial wilt scores were generated for each genitor and generation evaluated. The means and variances of the six generations were used to obtain estimates of environmental variance (V_E), genetic variance (V_G), additive variance (V_A), dominance variance (V_D), broad-sense heritability (h²_a) and narrow-sense heritability (h²_r) (Ramalho et al. 1993). The average additive [a] and non-additive [d] effects of the gene (s) controlling the wilt score character were estimated from the generation averages using the weighted least squares method (Mather and Jinks 1984). The GMD ([d] / [a]) was then obtained using this method.

In the second experiment, analyses of variance were carried out in randomized blocks with information within plots, to estimate the genetic and phenotypic parameters, and then the Skoot Knoot grouping test was applied at 5% probability. In both experiments, score 2 was established as the screening point (PT), considering the score above which the greatest number of susceptible plants were found and below which the greatest number of resistant plants were found.

With the observed frequency of resistant and susceptible plants in the F_2:3 progenies obtained in the grouping test, hypothesis tests were carried out considering expected frequencies for one, two and three genes involved in resistance to Ralstonia solanacearum. To test these hypotheses, the non-parametric chi-square test (χ_c²) at 5% probability was used, as carried out by Costa et al. (2018) and Costa et al. (2019).

The GraphPad Prism 9 (2023) computer application was used to obtain the frequency distribution graphs. The other analyses were carried out using the Genes computer application (Cruz 2013).

Figure 1 shows the frequency distributions of bacterial wilt caused by Ralstonia solanacearum in the parents, in the F₁, F₂, BC₁₁, BC₂₁ generations and in the control. As observed in the study conducted by Costa et al. (2018), the Yoshimatsu and Hawaii 7996 genotypes showed the same behavior, with a 100% frequency of plants resistant to bacterial wilt. High resistance to bacterial wilt in the Yoshimatsu genotype was also reported by Costa et al. (2023). Therefore, the Yoshimatsu and Hawaii 7996 genotypes can be considered as resistance standards for this study. In view of the results found, grades 1 and 2 were established as resistant plants and 3, 4 and 5 as susceptible. The F1 generation showed 80% of resistant plants with a score of 1 at 20 days after inoculation. In the F₂ generation, there was an approximation of a continuous distribution, with plants in all ranges and levels of resistance, demonstrating transgressive segregation and the influence of more than one gene, as well as indicating that possibly the genetic control of resistance to R. solanacearum in the Yoshimatsu cultivar is governed by different loci to the Hawaii 7996 cultivar, thus justifying the occurrence of susceptible individuals from the crossing of two resistant parents. In this generation, 44% of plants were found to be resistant with scores of 1 and 2, compared to 56% of plants with scores of 3 and 4. In view of the above, it is clear that as the disease progresses, more precisely at 20 days, a drop in resistance can be observed, which is possibly due to epistatic effects between the genes that govern the resistance character in the parents.

The genetic control of resistance to R. solanacearum in the Yoshimatsu and Hawaii 7996 genotypes is probably oligogenic or polygenic and corroborates the results observed by Costa et al. (2019) in their study of the same trait, with the exception of epistasis, which was not observed by the authors, who nevertheless evaluated contrasting genotypes for the resistance trait, these being Yoshimatsu (resistant) and IPA-7 (susceptible).

With regard to the RC₁₁ generation (Yoshimatsu x F₁), it showed a wilting pattern in the plants tending towards resistance, and it can be seen that 93% of the total number of plants had resistant plants and only 6% had plants with scores of 4 and 5. For the other backcross RC₁₂ (Hawaii 7996 x F₁) there was also a wilting pattern tending towards resistance, as a total of 88% of resistant plants were found for only 9 dead plants. This re-establishment of resistance to bacterial wilt was also observed by Costa et al. (2018) and Costa et al. (2019) in plants obtained from backcrossing using the Yoshimatsu genitor.

The IPA-7 control had 100% of the plants with bacterial wilt symptoms. This cultivar obtained 81 plants with a score of 5, i.e. dead plants, 17 plants with a score of 4 and 1 with a score of 3. The use of this cultivar as a susceptibility standard confirms the pathogenicity of the isolates used, reinforcing the veracity of the results. High susceptibility of IPA-7 was also reported in the work conducted by Mendes et al. (2018).

Table 1 shows the mean and variance components obtained from the scores of bacterial wilt caused by Ralstonia solanacearum in the genitors, in the F₁, F₂, BC₁₁, BC₂₁ generations. It can be seen that the mean values of the parents were the same (1.00), and that the mean of the F₁ generation (1.33) is close to the mean of the resistant parents, indicating that the resistance pattern is greatly influenced by dominant alleles because in the F₁ generation the dominant alleles overlap with the recessive ones. The presence of dominant alleles linked to resistance to bacterial wilt has been reported in the literature by Grimault et al. (1995) and Oliveira et al. (1999). It is worth noting that these two studies used the Hawaii 7996 cultivar as the source of resistance in the inheritance study.

Table 1

Means and variances in plants from P₁, P₂ and the F₁, F₂, BC₁₁ and BC₂₁ generations; mean and variance components for resistance to bacterial wilt caused by *R. solanacearum.*
Average Components		Grades
P₁		1.00
P₂		1.00
F₁		1.33
F₂		2.59
BC₁₁		1.26
BC₂₁		1.52
m		1.2215
[a]		-0,0522
[d]		0.5548
ADD		-10.6245
χ_c²		0.1126^ns
Variance Components		Variance
V_P1		0.0000
V_P2		0.0000
V_F1		0.6173
V_F2		1.4292
V_RC11		0.7374
V_RC21		1.1828
V_E		0.2058
V_G		1.2234
V_A		0.9381
V_D		0.2853
h²_a		85.60
h²_r		65.63

m = estimated average of the parents; [a] = additive gene effect; [d] = non-additive gene effect; ADD = mean degree of dominance; χ_c² = Chi-square for the test of the dominant additive model; V_E = Enviromental variance; V_G = Genetic variance; V_A = variance due to additive effects; V_D = variance due to non-additive effects; h²_a = heritability in the broad sense (%) e h²_r = heritability in the narrow sense (%).

The mean non-additive gene effect [d] was higher than the mean additive gene effect [a], indicating that the deviation from the mean is mainly due to heterozygous loci. The average degree of dominance (ADD) found was greater than 1, which is characteristic of an overdominant allelic interaction in the direction of resistance, reinforcing the strong influence of non-additive effects on the deviation from the mean. Costa et al. (2019) found an average degree of dominance below 1 (0.4337), which represents partial dominance in the direction of susceptibility. It is worth noting that this work involved crossing contrasting genitors in terms of resistance. These mean component results are consistent since the dominant additive model is efficient for explaining the genetic controlo of resistance to Ralstonia solanacearum in the tomato genotypes Yoshimatsu and Hawaii 7996, since its validity is proven by the fact that there are no significant differences using the chi-square test (χ_c²) at 5% probability. According to Ramalho et al. (2012) the absence of epistasis facilitates the selection process in plant breeding programs.

Yoshimatsu and Hawaii 7996 genitors showed zero variances, due to the full resistance reaction, in which no plants showed symptoms. In the segregating generations, variance values were higher than those of the parents, even though the crosses were between similar individuals for the resistance character, which can be explained by the recombination of genes characteristic of the generations and by the distribution of plants in all grades of the evaluation scale. Null variance for the resistant genotype (Yoshimatsu) was also found in the studie conducted by Costa et al. (2019).

Genotypic variance was significantly higher than the environmental variance, indicating that the variations observed are due to a greater extent to genetic effects, a condition which according to Oliveira (1999) favors the selection of genotypes, since the environment has less influence on phenotypic expression. The additive genetic variance (0.9381) contributed more to the genetic variance than the non-additive variance (0.2853). Heritability in the broad sense was 85.60% and in the narrow sense 65.63%. According to Borém et al. (2021), the higher the heritability, the greater the proportion of genetic variance in the phenotypic response, which is very good for the process of selecting and fixing genotypes, especially if the greater contribution is due to additive genetic variance, which culminates in greater restricted heritability.

Table 2 shows the analysis of variance, genetic and phenotypic parameters of the 60 F_2:3 tomato progenies, obtained from the scores for bacterial wilt caused by Ralstonia solanacearum. Using the F-test at 1% probability, it was possible to identify significant differences between the F_2:3 progenies. The significance of this test indicates the existence of variability among the progenies, a very favorable factor for the development of plant breeding programs. Next, it will be possible to identify the contribution of the genetic parameters obtained from the analysis of variance with information on the plot, as was done by Costa et al. (2018) in segregating tomato progenies. The experimental coefficient of variation was 4.61%, according to Ferreira's criteria (2018), values below 10 indicate optimum experimental precision, so this result demonstrates the reliability of the results found.

Table 2

Summary of the analyses of variance, genetic and phenotypic parameters of 60 F_2:3 tomato progenies and their respective parents in relation to scores for bacterial wilt caused by *Ralstonia solanacearum*
Source of variation	Grades / Parameters
Blocks	0.2700
Progenies	40.737728**
Between progenies	0.1231
Within progenies	0.2039
Average	3.3966
V_F total	2.8959
V_F between progenies	0.2038
V_G within progenies	2.7076
V_G between de progenies	0.4512
V_E environmental	0.0161
h² progeny average (%)	99.70
h² within progenies (%)	61.21
h² individual block (%)	100
h² individual experiment (%)	100
CV_e% experimental (CV1)	4.61
CV_ee% experimental between (CV2)	3.74
CV_ge% genetic between (CV3)	48.44
CV_gd% genetic within (CV4)	19.77
e between progenies	12.95
e within progenies	5.28

**: Significant at 1% probability by the F test. e between families: CVge/CVee. e within families: CVgd/CVee.

Phenotypic variance is the result of the sum of genetic factors, environmental factors and their interaction, the analysis of variance shows that the variability in the F_2:3 progenies is mainly due to genetic factors (2.7076). The total phenotypic variance was 2.8959 and the genetic variance between the progenies was 0.4512. There was less contribution from environmental variance (0.0161).

The phenotypic variance within progenies was 0.3744 and, as between progenies, a greater genetic contribution to phenotypic expression can be seen when observing the genetic variance within progenies. There is a greater contribution from the genetic part between progenies than within progenies, a fact that was also observed by Costa et al. (2018). Genetic variance is the most important portion of phenotypic variance for the success of the selection process in breeding programs, so knowledge of genetic parameters in bacterial wilt resistance experiments is fundamental (Borém et al. 2021).

The average heritability between progenies was higher (99.70%), which was to be expected due to the greater contribution of genetic variance between progenies. Heritability within progenies, on the other hand, was lower (61.21%). According to Vencovsky (1987) and Borém et al. (2021), the estimate of the heritability coefficient tells us how reliably the phenotypic value represents the genotypic value, i.e. how accurate it is. However, considering the high heritabilities found, it is clear that there is a high probability of efficiency in the selection of plants resistant to Ralstonia solanacearum, as well as the prediction of high genetic gains. The total experimental coefficient of variation (CV1) and the experimental coefficient of variation between progenies (CV2) showed values of 4.61% and 3.64, respectively, which are low and, according to Ferreira's criteria (2018), indicate excellent experimental precision. CV3 was 48.44% and CV4 was 19.77%.

The e between progenies (CV3/CV2) represents the ratio between the genetic coefficient of variation between progenies divided by the experimental coefficient of variation between progenies. O e within progenies (CV4/CV2) represents the ratio between the genetic coefficient of variation within progenies divided by the experimental coefficient of variation between progenies. According to Cruz et al. (2014), both parameters indicate the feasibility of practicing selection that allows for good genetic gains. The two indices showed values of 12.95 and 5.28, respectively, and these ratios, which are well above 1.0, reinforce what was discussed earlier, in terms of the genetic contribution being significantly higher than the environmental influence, as well as indicating high genetic variability, especially between progenies, showing that there is sufficient variability to allow for improvement and selection between and within progenies in relation to bacterial wilt caused by Ralstonia solanacearum.

Table 3 shows the Scott-Knott grouping test of 60 F_2:3 tomato progenies and their respective parents, Hawaii 7996 and Yoshimatsu, based on the scores for bacterial wilt caused by Ralstonia solanacearum. It was possible to classify the F_2:3 progenies and genitors into two groups, separating them into phenotypic classes of resistance and susceptibility. The first was formed by the Yoshimatsu and Hawaii 7996 genotypes, which showed greater resistance, but did not differ significantly from the following 19 progenies: 2, 5, 7, 8, 11, 12, 13, 17, 20, 21, 23, 33, 40, 45, 47, 50, 52, 55, 57. The second group, susceptible, was made up of 41 progenies that showed no significant differences between each other. They are as follows: 1, 3, 4, 6, 9, 10, 14, 15, 16, 18, 19, 22, 24, 25, 26, 27, 28, 29, 30, 31, 32, 34, 35, 36, 37, 38, 39, 41, 42, 43, 44, 46, 48, 49, 51, 53, 54, 56, 58, 59, 60.

Table 3

Scott-Knott grouping of 60 F_2:3 tomato progenies and their respective parents, Hawaii 7996 and Yoshimatsu, based on the scores for bacterial wilt caused by *Ralstonia solanacearum*
Progenies	Grades	Progenies	Grades
Hawaii 7996	1.00 a	Progeny F_2:3 # 30	4.60 b
Yoshimatsu	1.00 a	Progeny F_2:3 # 31	4.46 b
Progeny F_2:3 # 1	4.46 b	Progeny F_2:3 # 32	4.46 b
Progeny F_2:3 # 2	1.00 a	Progeny F_2:3 # 33	1.00 a
Progeny F_2:3 # 3	4.53 b	Progeny F_2:3 # 34	4.53 b
Progeny F_2:3 # 4	4.40 b	Progeny F_2:3 # 35	4.53 b
Progeny F_2:3 # 5	1.00 a	Progeny F_2:3 # 36	4.33 b
Progeny F_2:3 # 6	4.60 b	Progeny F_2:3 # 37	4.53 b
Progeny F_2:3 # 7	1.00 a	Progeny F_2:3 # 38	4.40 b
Progeny F_2:3 # 8	1.00 a	Progeny F_2:3 # 39	4.33 b
Progeny F_2:3 # 9	4.53 b	Progeny F_2:3 # 40	1.00 a
Progeny F_2:3 # 10	4.46 b	Progeny F_2:3 # 41	4.80 b
Progeny F_2:3 # 11	1.00 a	Progeny F_2:3 # 42	4.46 b
Progeny F_2:3 # 12	1.00 a	Progeny F_2:3 # 43	1.00 a
Progeny F_2:3 # 13	1.00 a	Progeny F_2:3 # 44	4.60 b
Progeny F_2:3 # 14	4.40 b	Progeny F_2:3 # 45	1.00 a
Progeny F_2:3 # 15	4.33 b	Progeny F_2:3 # 46	4.40 b
Progeny F_2:3 # 16	4.66 b	Progeny F_2:3 # 47	1.00 a
Progeny F_2:3 # 17	1.00 b	Progeny F_2:3 # 48	4.53 b
Progeny F_2:3 # 18	4.60 b	Progeny F_2:3 # 49	4.53 b
Progeny F_2:3 # 19	4.53 b	Progeny F_2:3 # 50	1.00 a
Progeny F_2:3 # 20	1.00 a	Progeny F_2:3 # 51	4.40 b
Progeny F_2:3 # 21	1.00 a	Progeny F_2:3 # 52	1.00 a
Progeny F_2:3 # 22	4.40 b	Progeny F_2:3 # 53	4.60 b
Progeny F_2:3 # 23	1.00 a	Progeny F_2:3 # 54	4.60 b
Progeny F_2:3 # 24	4.40 b	Progeny F_2:3 # 55	1.00 a
Progeny F_2:3 # 25	4.43 b	Progeny F_2:3 # 56	4.46 b
Progeny F_2:3 # 26	4.66 b	Progeny F_2:3 # 57	1.00 a
Progeny F_2:3 # 27	4.60 b	Progeny F_2:3 # 58	4.46 b
Progeny F_2:3 # 28	4.46 b	Progeny F_2:3 # 59	4.66 b
Progeny F_2:3 # 29	4.73 b	Progeny F_2:3 # 60	4.46 b

Averages followed by the same letter in the column do not differ significantly by the Scott-Knott grouping test at 5% probability.

Based on the grouping test, there were two phenotypic classes in the 60 F2:3 progenies, resistance and susceptibility. This way of separating the phenotypic classes was used by Carvalho Filho et al. (2011). Considering that the loci involved in resistance are different between the genotypes according to the results discussed, Table 4 presents the hypotheses for the genetic control of resistance. The chi-square test for testing hypotheses about the genetic control of resistance is widely used, and its application can be seen in the works by Carvalho Filho et al. (2011) and Batista et al. (2017).

Table 4

Chi square tests (χ_c²) (p = 0.05) for genetic control hypotheses of resistance to *R. solanacearum* in Yoshimatsu and Hawaii 7996 tomato cultivars and 60 F_2:3 progenies
Fenotypes	FO	FE	Genotypes
One gene
Resistant	19	30*	AA; aa
Susceptible	41	30*	Aa
Two gene
Resistant	19	26*	AABB; aabb; Aabb; AAbb; AABb
Susceptible	41	34*	AaBB; aaBb; aaBB; AaBb; AaBB
Three gene
Resistant	19	18 ^ns	AABBDD; aabbdd; Aabbdd; Aabbdd; AAbbDd; AAbbDD; AABbdd; AABbDd; AABbDd; AABBdd; AABBDd;
Susceptible	41	42 ^ns	AaBBDD; aabbDd; aabbDD; aaBbdd; aaBbDd; aaBbDD; aaBBdd; aaBBDd; aaBBDD; AabbDd; AabbDD; AaBbdd; AaBbDd; AaBbDD; AaBBdd; AaBBDd; AaBBDD

Expected and observed frequency for 1, 2 and 3 genes with partial dominance and/or recessive dominance. *= Significant at 5% probability. ns = Not significant at 5% probability. χ_c² at 5% probability: 3.84.

The first hypothesis tested was that of one gene, in which resistance would be promoted in recessive homozygosity arising from the genetic inheritance of the Yoshimatsu genotype, or dominant homozygosity due to the contribution of the Hawaii 7996 genotype, in which a 2:2 phenotypic segregation would be expected. There were significant differences at 5% probability by the chi-squared test, indicating that resistance is governed by more than one gene.

The second hypothesis tested was the existence of two genes, in which, similar to the previous hypothesis, resistance would be caused by the expression of the locus in recessive homozygosity due to the genetic inheritance of the Yoshimatsu genotype and/or dominant homozygosity due to the contribution of the Hawaii 7996 genotype, in which case the expected phenotypic ratio would be 13:17. In this case, there were also significant differences at 5% probability by the chi-squared test, showing that resistance must be governed by more than two genes.

Next, the three-gene hypothesis was tested, considering that resistance would be governed by the expression of two genes in recessive homozygosity arising from the genetic inheritance of the Yoshimatsu genotype and/or dominant homozygosity due to the contribution of the Hawaii 7996 genotype, in which the expected phenotypic segregation would be 9:21. For this hypothesis, there were no significant differences at 5% probability using the chi-square test. Given the results of the χ_c² test, it can be inferred that resistance to R. solanacearum in the progenies evaluated is oligogenic, resulting from the action of three genes, two of which are contributed by the Yoshimatsu genotype and conditioned by recessive alleles, and one characterizing the contribution of the Hawaii 7996 genotype, conditioned by dominant alleles with a partial dominance effect.

The results found in this study corroborate those observed by Costa et al. (2019) who, when evaluating the resistance of the Yoshimatsu cultivar to R. solanacearum, found that two genes with a greater effect in recessive homozygosis were responsible for the trait. However, Grimault et al. (1995) in inheritance studies with the Hawaii 7996 genotype in relation to resistance to bacterial wilt also indicate dominant monogenic genetic control, although they did not observe a partial effect of dominance.

The results found in this study corroborate some of the authors cited in this article, but they make a significant contribution, since they provide detailed information that each genotype has a different genetic control of resistance. Thus, breeding programs can be more efficient when using methods to select plants resistant to bacterial wilt in tomatoes, since the genetic control of each cultivar shows the need for different planning, depending on the species inoculated and the source of resistance used as a gene donor.

The main result was that the genetic control of resistance to Ralstonia solanacearum in the two resistant tomato genotypes is determined by different genes. Two recessive genes were found in Yoshimatsu and one in Hawaii 7996.

Acknowledgements To the Federal Rural University of Pernambuco for the support in the stages of inoculation and to the National Council for Scientific and Technological Development for the doctoral scholarship.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Competing Interests

The authors have no relevant financial or non-financial interests to disclose.

Author Contributions

All the authors contributed to the conception and design of the study. Material preparation, data collection and analysis were carried out by Djayran Sobral Costa, Ester da Silva Costa and Kleyton Danilo da Silva Costa. Professors Elineide Barbosa de Souza, Rejane Rodrigues da Costa e Carvalho, Adriano Márcio Freire e Silva and José Luiz Sandes de Carvalho Filho were responsible for providing guidance on genetic improvement and phytobacteriology, as well as contributing to the writing of the article. The first draft of the manuscript was written by Djayran Sobral Costa and all the authors commented on the previous versions of the manuscript. All the authors have read and approved the final manuscript.

Data Availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Ethics statement

The tomato genotypes evaluated in this experiment were acquired from the INPA, IPA and UFRPE experimental stations and have been authorized for use and study. Each generation obtained and each genotype was identified by a number of different progenies. All the tomato genotypes belong to the same family, Solanum lycopersicum L.. It should be noted that the authors confirm that all the methods were carried out in accordance with the relevant guidelines and regulations for research with generations. And that the experimental protocols were approved by the University's Research Center, since this work is the result of a doctoral thesis approved by the CNPQ. And finally, the genotypes used in the study are in accordance with local or national guidelines, without the need for additional confirmation.

Abebe AM, Choi J, Kim Y, Oh CS, Yeam I, Nou IS, Lee JM (2020) Development of diagnostic molecular markers for marker-assisted breeding against bacterial wilt in tomato. Breeding science, 70(4), 462-473. https://doi.org/10.1270/jsbbs.20027
Batista RO, Furtado LL, Carneiro JE, Carneiro PCS, Nicoli A, Sousa LBD, Evaristo AB (2022) Inheritance of resistance to Fusarium wilt in the carioca grain type common bean. Crop Breeding and Applied Biotechnology. http://dx.doi.org/10.1590/1984-70332022v22n4a37
Batista RO, Silva LC, Moura LM, Souza MH, Carneiro PCS, Carvalho Filho JLS, Carneiro JES (2017) Inheritance of resistance to fusarium wilt in common bean. Euphytica 2013:133. https://doi.org/10.1007/s10681-017-1925-1
Borém A, Miranda GV, Fritsche-Neto R (2021) Melhoramento de plantas. 8ª edição. 384
Carvalho Filho JLS, Gomes LAA, Maluf WR, Oliveira RR, Costa DS, Ferreira S, Monteiro AB, Costa RR (2011) Resistance to Meloidogyne incognita race 1 in the lettuce cultivars Grand Rapids and Salinas-88. Euphytica 182:199–208. https://doi.org/10.1007/s10681-011-0429-7
Cen Y, Ying H, Shunshi H, Lifu Z, Jian Z (2022) "Early Detection of Bacterial Wilt in Tomato with Portable Hyperspectral Spectrometer" Remote Sensing 14, no. 12: 2882. https://doi.org/10.3390/rs14122882
Chaudhary P, Sharma A, Singh B, Nagpal AK (2018) Bioactivities of phytochemicals present in tomato. Journal of food science and technology, 55, 2833-2849. https://doi.org/10.1007/s13197-018-3221-z
Cho HES, Song YK, Lee S, Lee SW, Lee A, Jo BM, Lee JG, Kim Hwang, I Hwang (2018) Analysis of genetic and pathogenic diversity of Ralstonia solanacearum causing potato bacterial wilt in Korea. Plant Pathol. J. 34: 23–34. https://doi.org/10.5423%2FPPJ.FT.09.2017.0203
Costa ES, Costa KDS, Carvalho Filho JLSC, Silva MO (2023) Reação de resistência do tomateiro à Ralstonia solanacearum em condições de casa de vegetação. Brazilian Journal of Development, 9: 19413–19428. https://doi.org/10.34117/bjdv9n6-048
Costa KDS (2017) Controle genético da resistência do tomate ‘Yoshimatsu’ à Ralstonia pseudosolanacearum e Ralstonia solanacearum. Tese de Doutorado, Universidade Federal Rural do Pernambuco, Recife, Pernambuco. 164p
Costa KDS, Santos AMM, Santos PRS, Nascimento MR, Silva AMF, Albuquerque GMR, Batista RO, Pereira JWL, Carvalho Filho JLS (2018) Inheritance of resistance to Ralstonia pseudosolanacearum in tomato. Euphytica. https://doi.org/10.1007/s10681-018-2217-0
Costa KDS, Santos PR, Santos AMM, Silva AMF, Chagas JTB, Carvalho Filho JLSC, Pereira JWL, Silva MO, Silva JR, Menezes D (2019) Genetic control of tomato resistance to Ralstonia solanacearum. Euphytica, 215: 136. https://doi.org/10.1007/s10681-019-2458-6
Cruz CD (2013) GENES - a software package for analysis in experimental statistics and quantitative genetics. Acta Scientiarum. 35: 271-276. https://doi.org/10.4025/actasciagron.v35i3.21251
Cruz CD, Carneiro PC, Regazzi AJ (2014) Modelos Biométricos Aplicados ao Melhoramento Genético - Vol 2 - 3ª Edição. 668
Felix KC, Souza EB, Michereff SJ, Mariano RLR (2012) Survival of R. solanacearum in infected tissues of Capsicum annuum and in soils of the state of Pernambuco, Brazil. Phytoparasitica 40:53–62
Ferreira PV (2018) Estatística experimental aplicada às ciências agrárias. 588
Graham J, Jones DA, Lloyd AB (1979) Survival of Pseudomonas solanacearum race 3 in plant debris and in latently infected potato tubers. Phytopathology, 69(10), 1100–1103. https://10.1094/Phyto-69-1100
Grimault V, Prior P, Anais G (1995) A monogenic dominant resistance of tomato to bacterial wilt in Hawaii 7996 is associated with plant colonization by Pseudomonas solanacearum. J Phytopathol 143: 349–352. https://doi.org/10. 1111/j.1439-0434.1995.tb00274.x
Hayward AC (1991) Biology and epidemiology of bacterial wilt caused by Pseudomonas Solanacearum. Annu. Rev. Phytopathol. 29: 65–87. https://doi.org/10.1146/annurev.py.29.090191.000433
Heuvelink E, Li T, Dorais, M (2018) Crop growth and yield. Tomatoes, 2, 89-136. https://doi.org/10.1079/9781780641935.0089
Kelman A (1954) The relationship of pathogenicity in Pseudomonas solanacearum to colony appearance on a tetrazolium medium. Phytopathology 44:693–695
Lee I, Kim Y, S Kim, J W, Park, DH (2020) Genetic and pathogenic characterization of bacterial wilt pathogen, Ralstonia pseudosolanacearum (Ralstonia solanacearum Phylotype I), on roses in Korea. The Plant Pathology Journal, 36(5), 440. https://10.5423/PPJ.OA.06.2020.0095
Lima Neto AF, Silveira MA, Souza RM, Nogueira SR, Andre´ CMG (2002) Inheritance of bacterial wilt resistance in tomato plants cropped in naturally infested soils of the state of Tocantins. Crop Breed Appl Biotechnol 2:25–32
Mather K, Jinks JL (1982) Biometrical genetics, 3rd edn. University Press, Cambridge
Mendes AQ, Menezes D, Carvalho IDE, Freire Silva AMF, Oliveira AA, Francisco FF (2018) Estimativa da Capacidade Geral e Específica de Combinação em Tomate para Produção de Híbridos Resistentes à Murcha Bacteriana. Jornal de Agricultura Experimental Internacional. 24:1–11. https://doi.org/10.9734/JEAI/2018/42322
Nick C, Silva DJH (2016) Melhoramento de tomate. Melhoramento de hortaliças. Viçosa: UFV, 396–431
Nielsen LW, Haynes FL (1960) Resistance in Solanum tuberosum to Pseudomonas solanacearum. Am Potato J 37:260–267
Oliveira WF, Giordano LB, Lopes CA (1999) Herança da resistência em tomateiro à murcha-bacteriana. Fitopatologia Brasileira. 24:49–53
Petrucelli A, Alves M R, Gianotti F (2022) Estudo de viabilidade de uma agroindústria de tomates e polpas na cidade de taquaritinga-SP. Revista Interface Tecnológica, 19(2), 797-809. https://doi.org/10.31510/infa.v19i2.1541
Prior, P., Ailloud, F., Dalsing, B. L., Remenant, B., Sanchez, B., and Allen, C. (2016). Genomic and proteomic evidence supporting the division of the plant pathogen Ralstonia solanacearum into three species. BMC Genomics 17:90. https://doi.org/10.1186/s12864-016-2413-z.
Ramalho APR, Abreu AFB, Santos JB, Nunes JAR (2012) Aplicações de genética quantitativa no melhoramento de plantas autógamas. Editora UFLA, Lavras
Ramalho MAP, SANTOS JB and ZIMMERMANN (1993) Genética quantitativa de plantas autógamas: aplicações ao melhoramento do feijoeiro. Goiânia: UFG, 271
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. https://doi.org/10.1099/ijs.0.066712-66710
Sharma KC, Sharma LK (2015) Genetic studies of bacterial wilt resistance in tomato crosses under mid-hill conditions of Himachal Pradesh. J Hill Agric 6:136–137. https://doi.org/ 10.5958/2230-7338.2015.00026.9
Vencovsky R (1987) Heranca quantitativa. In: Paterniani E (ed) Melhoramento e produção de milho no Brasil. Fundação Cargill, Piracicaba,1204–1214

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The genetic control of resistance to Ralstonia solanacearum in resistant tomato genotypes is determined by different genes

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