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CROP BREEDING & GENETICS

Relationships between Root-Knot Nematode Resistance and Plant Growth in Upland Cotton

Galling Index as a Criterion

^a Dep. of Plant and Environ. Sci., Box 30003, New Mexico State University, Las Cruces, NM 88003
^b Cotton Incorporated, Cary, NC 27513 USA

^* Corresponding author (jinzhang{at}nmsu.edu)

	ABSTRACT

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
The southern root-knot nematode (RKN) [Meloidogyne incognita (Kofoid and White) Chitwood] is one of the most destructive pests in the Cotton Belt of the USA. The lack of an economical evaluation method for RKN resistance has hindered the development of resistant cultivars. This investigation was conducted to develop an improved RKN evaluation technique. Twelve genotypes including seven susceptible (S) lines, one moderately resistant (MR) line, three highly resistant (R) lines derived from ‘Auburn 623 RNR,’ and one F₁ between DP 33B (S) and ‘Auburn 634 RNR’ (R) were evaluated in the greenhouse for plant growth, RKN egg reproduction, and root galling in Experiment 1. RKN egg reproduction was highly and positively correlated with galling index and both were highly and negatively correlated with plant growth characteristics including plant height, number of leaves, plant and root weight. Galling index was confirmed to be highly significantly and negatively correlated with plant height and fresh weight in Experiment 2 with 9 parents and their 36 F₁ hybrids. Galling index had highest genotypic F value and comparable coefficient of variance (CV) to the plant characteristics, while CV for egg counts was very high. Correlation between the two greenhouse tests in the 9 parental lines as measured by galling index was highly significant. Comparison between F₁ and their parents in egg reproduction and galling revealed that the RKN resistance is partially dominant. Using a common check and double inoculation in each pot, galling index is an easy, quick and reliable method for screening large numbers of cotton plants.

Abbreviations: ANOVA, analysis of variance • BG, Bollgard • CV, coefficient of variation • LSD, least significant difference • RKN, root knot nematode

	INTRODUCTION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
THE southern root-knot nematode Race 3 has become one of the major threats to US cotton production with an estimated annual yield loss of 2.2% (Blasingame and Patel, 2005). Yield loss in the western cotton-growing region is even higher (for example, 5% in Arizona and New Mexico). Management of RKN includes crop rotation, application of pesticides, and use of resistant cultivars. Among these options, development and use of resistant cultivars should be the most cost effective method of controlling RKN.

The history of breeding for RKN resistance in cotton can be traced back to the early 1900s, but it was not until the 1950s when the first cultivar that showed moderate RKN resistance, Auburn 56, was developed. However, a major breakthrough in RKN resistance breeding was the release of the highly resistant line, Auburn 623 RNR (Shepherd, 1974c). Its resistance was transferred by backcrossing into many commercial cotton backgrounds, resulting in the development of Auburn 634 RNR, other Auburn germplasm, and many M series of lines (e.g., M 240 and M 315) in the 1980s (Shepherd, 1982; Shepherd et al., 1996). The resistant plants permit penetration of second-stage juveniles (J2) into the roots and initiation of feeding sites, but most J2 do not ultimately develop into egg-bearing adults. RKN reproduction is reduced by more than 98% at the end of the normal reproductive cycle (Jenkins et al., 1995; Creech et al., 1995). Even though these lines had improved agronomic traits, the high level of RKN resistance has never been transferred to any commercial cotton cultivars (Robinson et al., 1999). Only a moderate level of RKN resistance was reported and confirmed in a few commercial cultivars, i.e., ST LA 887, PM 1560, and Acala Nem-X (Robinson et al., 1999; Ogallo et al., 1999).

The proportion of RKN resistance that is due to total genetic or additive genetic variation, i.e., broad-sense heritability or narrow-sense heritability, has not been reliably estimated due to high experimental errors in RKN resistance evaluation. The lack of a reliable and efficient RKN resistance evaluation method has been one of the major limiting factors in analyzing the genetics of RKN resistance, and breeding this trait in cotton. Because of this, few consistent conclusions have ever been drawn, even though the inheritance of RKN resistance for Auburn 623 RNR and its derived resistant lines has been investigated since the 1970s using traditional Mendelian and quantitative genetics. Both RKN egg counting and galling index have been extensively used by cotton geneticists, agronomists, and nematologists (Shepherd, 1974a, 1974b, 1974c; McPherson, 1993; McPherson et al., 1995, 2004; Colyer et al., 2000; Robinson et al., 1999, 2004; Ogallo et al., 1999; Bezawada et al., 2003; Zhou, 1999; Zhou and Starr, 2003; Zhang et al., 2004; Ynturi et al., 2004). In comparison with counting root eggs or egg masses per plant, galling index would be preferred in breeding because it can be more easily assayed on large numbers of plants as needed in breeding programs. In addition, galling index is a direct measurement of cotton plant response to RKN infection. Zhou and Starr (2003) reported that the initial RKN population density is significantly correlated with galling index and seedcotton yield reduction in susceptible and resistant cultivars. However, the relationship between RKN reproduction and RKN damage to cotton in terms of galling and cotton growth characteristics has not been extensively investigated. The objectives of the present study were to develop a reliable, easy, and fast RKN screening technique, and demonstrate the validity of the technique by evaluating the Auburn resistant source germplasm, Acala Nem-X, and commercial, susceptible cultivars for RKN resistance.

	MATERIALS AND METHODS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Experiment 1: Parent Screening
A population of M. incognita Race 3 was isolated in Las Cruces, New Mexico and maintained on and collected from susceptible tomato plants (Lycospersicon esculentum cv. Rutgers) grown in the greenhouse. Twelve cotton genotypes were grown in a completely randomized design with five replications (one plant per replicate) in the greenhouse located at the Fabian Garcia Science Center, Las Cruces, NM. These 12 genotypes were six susceptible commercial cultivars, DP 33B, ST 474, SG 125, SG 747, DP 428 BG, and Acala Maxxa with no known RKN resistant source in the pedigrees; two moderately resistant cultivars, Acala Nem-X (Ogallo et al., 1999) and PM 1560 BG (http://www.agctr.lsu.edu/NR/rdonlyres/E1A22B05-1110-4A08-9004-91F2468C58DA/2837/pub2135Cottonvarieties2.pdf); three highly resistant lines, Auburn 634 RNR, M 240, and M 315 (Shepherd et al., 1996); and one F₁ (DP 33B x Auburn 634 RNR). Fuzzy seeds were planted in 10-cm plastic pots containing sterile sand on 15 Oct. 2002. To monitor and ensure a consistent RKN infection, ‘Acala 1517–99’ was used as a check and included in each pot (one plant per pot). When planting, two 2.5-cm deep holes were made in each pot and labeled to indicate the genotypes. The holes were covered with the sandy loam soil immediately after planting. Each pot was then inoculated with 5.0 mL of inoculum containing 5000 eggs (2500 eggs per plant). After emergence, seedlings were thinned to one plant per genotype and one plant of check cultivar per pot. Seeds that did not germinate or seedlings that wilted were replaced by replanting on 30 Oct. 2002 and all pots were reinoculated on the following day with 2.5 mL of inoculum containing 2500 juveniles to ensure consistent RKN infection. Pots were placed on heat pads with the temperature initially set at 29.4°C. Temperatures were reduced to 24°C after germination. Plants were hand watered daily.

Plant height and leaf length were recorded before RKN screening on 2 Dec. 2002. Root systems of the two plants from each pot were washed under running water and carefully separated. After fresh whole plant weight and root weight were weighed, roots were evaluated for gall index on a scale of 0 to 4 according to Shepherd (1979), Robinson et al. (1999), and Zhou and Starr (2003) with a minor modification, where, 0 = no galls; 1 = light galling (10–25% of roots with galls); 2 = moderate galling (26–50% roots with galls); 3 = heavy galling (51–75% roots with galls); and 4 = very heavy galling (>75% roots with galls).

Eggs were recovered from excised roots by agitated extraction in a 10% bleach solution (1.5% sodium hypochlorite, NaOCl). The extracted solution was poured through a sieve with a pore size of 73.7 µm nested over a sieve with a pore size of 25.4 µm in which the eggs were collected. Eggs were rinsed gently with running water and transferred into a vial with 10 mL of water (Shepherd, 1979; Klump and Thomas, 1987). Roots were bagged, dried, and weighed after egg extraction. The number of total eggs plant^–1, eggs g^–1 dry root, eggs g^–1 fresh root, and eggs g^–1 total fresh plant weight were determined for each plant and its corresponding check. Data for experimental and check plants were separately subjected to analysis of variance (ANOVA) using AgroBase 21 (Agronomix Software Inc., Winnipeg, MB, Canada).

Experiment 2: Parent and Hybrid Screening
Thirty-six F₁ crosses representing a diallel mating were made in the summer 2002, excluding reciprocals among DP 33B, ST 474, SG125, SG 747, PM 1560 BG, Acala Nem-X, Auburn 634 RNR, M 240, and M 315. Forty-five genotypes including the F₁'s and their parents were planted in the greenhouse on 30 Oct. 2002 in a randomized complete block design with three replications (one plant per replication).

Seeds were planted in 10-cm plastic pots that were filled with sterilized sandy loam soil. The soil was watered before 2 seeds per genotype were planted. A susceptible check, Acala 1517–99, was again planted as the control in each pot, as described previously. On 7 Nov. 2002, a hole near a plant in each pot was made and inoculated by pipetting 1 mL of 2500 nematode eggs mL^–1 per hole and then the holes were covered with the sandy loam soil. Seedlings were thinned to one plant per genotype and one plant of check cultivar per pot after emergence. The plants were watered daily by hand in the greenhouse with the air temperatures ranging from 20 to 34°C. To optimize the temperature for the nematode reproduction, the pots in each of the three replications were placed on a heating pad with a temperature setting at 26.7°C (about optimal temperature for RKN growth) for the duration of the test. The differences in inoculation approaches between the two tests reflected the convenience and flexibilities of the procedures.

On 17 Dec. 2002 (40 d after inoculation), plant height was measured from the soil line to the top of the plants. Immediately, the plants were harvested by gently rinsing off the soil from the roots in a sink with running water. The fresh plant weight was measured and roots were rated for galls (root-knots) induced by the root-knot nematodes following a scale of 0 to 4 as described previously.

Data were subjected to ANOVA and covariate analysis using AgroBase 21 (Agronomix Software Inc., Winnipeg, MB, Canada). Estimates for genotypic means were used for analysis of correlation between traits. The genotypic means for egg counting and galling index reported by Robinson et al. (1999) and Colyer et al. (2000) were also used for correlation analysis in each test.

	RESULTS AND DISCUSSION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Screening Techniques
For between-pot variation control, we implemented two modifications in the greenhouse screening for RKN resistance by growing a susceptible plant from the common check (Acala 1517–99) and double inoculation in every pot. ANOVA for Experiment 1 (Table 1) showed that the cultivars tested varied significantly (p < 0.01) in resistance to RKN infection, whereas a separate ANOVA based on only the control plants indicated that there were no significant differences among pots. Furthermore, use of the control plant data as a covariate in the analysis of experimental plants did not improve the precision of the experiment (data not shown). The ANOVA also detected significant genotypic differences (p < 0.01) for plant height, leaf size, total number of leaves, total fresh weight, dry root weight, and fresh root weight. During the test, we observed that the resistant genotypes were larger and taller than the susceptible ones and the check plants, Acala 1517–99. The inoculum level and RKN infection were consistent across all pots based on the check plants in each pot. Coefficients of variation (CV) for plant height, leaf size, and leaf number ranged from 13.5 to 19.7%, while plant fresh weight, fresh root weight, and dry root weight had CV of 25.5 to 32.2%. Galling index also had a similar CV (24.1%), but the highest genotypic F value (19.65).

The F values (data not shown) for 45 genotypes in Experiment 2 were significant (P < 0.01) for plant height, fresh plant weight, and galling index, confirming that significant genotypic differences did exist among the genotypes tested. When the susceptible check plants were analyzed separately, the F-values for among-pot differences were not significant for any measured parameters (data not shown). Furthermore, when the check plot data were used as covariates for analysis of the experimental plants, there was no improvement in the precision of the analysis. These results demonstrated that check plants performed similarly whether they were grown with the susceptible genotypes or resistant genotypes. The CVs for galling index, plant height, and fresh plant weight were similar to these in Experiment 1.

The two experiments indicated that galling index is a reliable measurement in terms of experimental error control. Even though galling index is subjective in nature, its easy and quick use and low CV makes it a method of choice for RKN resistance screening in cotton used by others or in combination with egg or egg mass counting (McPherson et al., 1995, 2004; Robinson et al., 1999; Colyer et al., 2000; Bezawada et al., 2003). Shepherd (1979) was the first to report a significant correlation between egg count and galling index in Upland cotton. Robinson et al. (1999) and Colyer et al. (2000) also used both galling index and RKN counts to measure resistance in various cotton cultivars, but did not report the correlation between the two measurements. Robinson et al. (1999) tested 59 cultivars (divided into six groups, together with a resistant control and a susceptible control) released in the US since 1950 in growth chambers. We estimated the correlation between galling index and RKN production (multiplication factor) based on the genotypic means for the two traits reported by Robinson et al. (1999). This correlation was significant in most of the cultivar groups: Pima (n = 6, r = 0.842, P < 0.05), California Acala (n = 8, r = 0.850, P < 0.01), New Mexico Acala (n = 7, r = 0.921, P < 0.01), High Plain type (n = 15, r = 0.797, P < 0.01), Delta type (n = 27, r = 0.706, P < 0.01), and Coker (n = 8, r = 0.669, P > 0.05). In the same experiment, seven cultivars were also separately tested using two different RKN sources. Our calculation showed that galling index was highly correlated with RKN reproduction (r = 0.948, P < 0.01) when one RKN source was used, while the association was positive (r = 0.669) and significant at P < 0.10 when another RKN source was used. In the case of Colyer et al. (2000), seven cultivars were evaluated in the field in 1997 and 1998, and six cultivars were tested twice in a growth-room. The genotypic means for galling index were highly correlated (r = 0.842–0.901, P < 0.05) with those for RKN reproduction (J2 juvenile density 500 cm^–3 soil in the field or eggs plant^–1 in the growth-room) except for one growth-room test (r = 0.789, P > 0.05). Our results and the previous reports demonstrate that gall abundance indicates RKN reproduction and susceptibility in the cotton genotypes tested; however, it should be noted that RKN infection in some host plant species does not produce obvious root galling.

Since the check plants had consistent RKN infection, genotypic means with no adjustment were used for the correlation analysis (Table 2). In Experiment 1, plant growth characteristics were positively correlated, especially between plant height and weight. Galling index was significantly correlated (P < 0.01) with total egg counts, eggs g^–1 dry root weight, eggs g^–1 fresh root weight, and eggs g^–1 total fresh plant weight. The plant growth characteristics were consistently and negatively correlated with nematode reproduction and gall index ratings. Galling index was significantly correlated (P < 0.01) with all of the plant growth characteristics except for leaf size. The results in Experiment 2 confirmed that plant height was significantly correlated (r = 0.73; P < 0.01) with the fresh plant weight, i.e., the taller the plants, the higher the plant weight. Also, both traits were negatively correlated (r = –0.65, r = –0.39, P < 0.01) with the galling index. Therefore, the high level of RKN infection indicated by galling suppressed cotton plant growth. The more severe the RKN infection, the shorter and the smaller the plants were. Thus, under the greenhouse conditions, plant height and fresh plant weight in comparison with the susceptible genotypes could be used in combination with the galling index as the criterion for measuring RKN resistance in cotton.

On the basis of the plant growth, galling, and RKN reproduction in the two greenhouse tests, these cultivars can be grouped into three groups: susceptible genotypes, including SG 125, DP 33B, PM 1560 BG, ST 474, SG 747, DP 428B, and Acala Maxxa; moderately resistant genotypes, including Acala Nem-X and F₁ between DP 33B and Auburn 634 RNR; and highly resistant genotypes, including Auburn 634 RNR, M 315, and M 240.

As expected, the F₁'s between the five S parents had galling indices of 3.33 to 4.00 (Table 4), exhibiting no resistance. The galling index in the F₁'s between these five S parents and the moderately resistant Acala Nem-X ranged from 2.17 to 3.33, below or similar to the resistant parent, Acala Nem-X in the same experiment (3.33). The results suggest that the moderately resistant Acala Nem-X contains a dominant or partially dominant mode of resistance.

The lower experimental error for galling index also allowed the detection of significant variances due to general combining ability (GCA) and specific combining ability (SCA) for RKN resistance (data not shown). From the ratio of the mean square values (GCA/SCA = 35.9), GCA was more important, indicating that additive genetic effect played a more important role in controlling the RKN resistance in this set of parents and their hybrids.

	CONCLUSIONS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
To reduce experimental error control, we grew a susceptible plant from the common check (Acala 1517–99) and used double inoculations in every pot. The check plants were used as a measure for experimental error control in that if a check plant did not exhibit a high level of susceptibility, the plant to be evaluated in the same pot should be excluded in data analysis or the data should be adjusted based on the infection from the check plants using various methods such as covariate analysis. Therefore, check plants were used to monitor the success of inoculation and RKN infection level in each pot. Furthermore, to avoid escapes, we also re-inoculated the pots 2 wk after planting. Thus, susceptible check plants and double inoculations ensured consistent RKN infection and minimized random experimental errors. In the present study, all the check plants sustained a consistently high galling index, indicating no need for data adjustment. In fact, the use of the check plant data as a covariate did not improve the precision of either experiment. The results from the improved RKN screening technique reliably grouped the genotypes tested into three groups: susceptible group, including SG 125, DP 33B, PM 1560 BG, ST 474, DP 428B, and Acala Maxxa; moderately resistant group, including Acala Nem-X and F₁ between 33B and Auburn 634 RNR; and highly resistant group, including Auburn 634 RNR, M 315, and M 240.

Using the modified screening technique, we demonstrated that galling index was highly significantly and negatively correlated with plant growth characteristics and positively correlated with egg reproduction. Therefore, galling index could be used as a quick and easy screening method to evaluate large cotton breeding populations without the need to count eggs or destroy plants when Auburn 623 RNR resistant source is used. By comparing plant height, weight, root structure, and galling index to a susceptible control grown in the same pot, RKN resistance could be readily determined. These three traits could be used to develop a selection index for reliably selecting RKN resistant cotton progeny.

	ACKNOWLEDGMENTS

 
We thank Drs. J. N. Jenkins and Jack McCarty, Jr. of USDA-ARS, MS for providing the seeds of Auburn 634 RNR, M 240, and M 315. We also thank Mrs. D. Stanley of Monsanto for assistance in making necessary hybrids screening. The research was in part funded by the United States Department of Agriculture through the Southwest Consortium on Plant Genetics and Water Resources and the New Mexico Agricultural Experiment Station. We also thank the two anonymous reviewers for their constructive suggestions for earlier versions of the manuscripts.

Received for publication September 24, 2005.

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TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 

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