ABSTRACT
Cowpea aphidborn mosaic virus disease (CABMV) is one of the reasons for rejection of cowpea seed by seed inspectors in Burkina Faso. With regard to this, this study was undertaken to analyze the genetic components underlying the resistance of cowpea lines to the cowpea aphidborne mosaic virus (CABMV) and to determine the mechanism of transmission of the resistance from parents to offspring. Therefore, crosses were made in 5x5 full diallel design. Data analysis was done following Griffing and Hayman method on disease severity and the area under disease progress curve (AUDPC) for five cowpea varieties during the 2015 offseason at Kamboinse research station. The analysis of variance associated with the general and specific combining abilities (GCA and SCA) and reciprocal effect (RCE) showed that the genetic variability was explained by additive effect. The F1 population showed that there was partial dominance and the narrow sense heritability for severity and AUDPC was high (60%). To improve cowpea for resistance to CABMV, rigorous choice of parents should be made before crosses and there was no maternal effect.
Key words: Cowpea, full diallel, severity, resistance, Cowpea aphidborn mosaic virus disease (CABMV), Burkina Faso.
Cowpea (Vigna unguiculata, L. Walp) is a leguminous crop, selfpollinated, grown in all agroecological zones of Burkina Faso and has numerous advantages at both agronomical and economical levels. Its grains constitute an important source of protein and income for producers and consumers. Cowpea is also an important fodder. However, one of the main problems in the genetic improvement of the crop to address is the choice of the parents for hybridization. This choice of parents for hybridization depends, beyond beyond resistance to diverse constraints, heavily on market and consumers’ criteria. Tignegre (2010) and Batieno (2014) have reported that the market criteria were mainly based on seed size (large) and color (white). Also, the effectiveness of a method of selection depends largely on the number of genes involved in the control of the trait (Zagre et al., 1999).
Within the main constraints for cowpea production, the cowpea aphidborne mosaic virus (CABMV) is one of the principal reasons for rejection of cowpea seeds by the seed inspectors and also by producers in Burkina Faso. Cultural practices have been used to control the disease but are weak in seed production system. Therefore, there is a need to develop resistant varieties in order to reduce losses due to CABMV.
Thus, the objective of this study was to analyze the genetic nature of resistance of cowpea lines to CABMV in order to formulate hypotheses on the possible ways of using them to improve cowpea for resistance to the disease. For this, a full diallel analysis was used following Hayman (1954) and Griffing (1956) approaches. This method has been already used in cowpea to study the genetics underlying Striga resistance (Tignegre, 2010). The Griffing’s method is based on the determination of the general and the specific combining abilities. The general combining ability for (GCA) is the average of gametic effects of an individual. It provides information on combining abilities at global and individual level (Griffing, 1956). In other words, it is a measure of the value of the average gametes of a parent (Demarly 1977). It is the ability of both parents to transmit positive or negative characters to their descendants (Allard, 1999). Specific combining ability (SCA) is a deviation from the additivity of general combining. Contrary to GCA, SCA is not linked to a parent, but a cross. Statistically, while GCA appears as a primary effect, SCA is an interaction (Demarly, 1977). GCA varies depending on the additive gene action. It is therefore passed from one generation to another. SCA measures the deviation from the performance of F_{1} as compared to the average of the parents.
The method of Hayman (1954) is used to estimate different genetic components for the trait and the various parameters: the additive, dominance, reciprocal effects, heterosis and heritability. It comprises four types of analysis that complement the level of interpretation: the analysis of variance of diallel tables testing the significance of the various terms that are not unlike the specific combining ability, the validity test for the model, the statistical analysis of the genetic components of the total variation and the analysis of relationships between statistical terms.
Genetic resources
Genetic resources used in this study comprised five released cowpea varieties from Burkina Faso and 20 F_{1 }hybrids from 5x5 full diallel crosses. Lines used in these crosses were chosen based on their reaction visàvis to CABMV. The five lines involved in the crosses are: KVx396452D (resistant), KVx640 (resistant), KVx611 (moderately susceptible), KVx303096G (susceptible) and Gorom local (susceptible) all from the longterm storage germplasm of the cowpea breeding program at Kamboinsé Research Station in Burkina Faso.
Methods
Twenty (20) F_{1} hybrids and their parents were planted in pots and arranged in randomized complete blocks design (RCBD) with three replications. Each replication comprised 25 entries of one pot per entry containing individual plant. Plants were sprayed to avoid contamination from aphids. The experiment was conducted under screen house at Kamboinsé Research Station (latitude 12°28N, longitude 1°32W and altitude 296m) in Burkina Faso in July 2015. To protect plants, insecticide spray was done using a mixture of PACHA (lambdacyhalothrin 15 g/l + acetameprid 10 g/l) and TITAN (25 EC Acétamiprid 25 g/l) two weeks after planting at doses of 2 ml per liter of water per product.
Each plant received 45 kg of P_{2}O_{5} per hectare from NPK fertilizer (1423146S1B formula). One week after planting, all plants were inoculated using extract of leaves from CABMV serotype D grinded based on weight/volume proportion (p/v) =1/10. The inoculum used was from infected seedlings of Gorom local, a CABMV serotype D susceptible cowpea variety in Burkina Faso. Prior to infestation, the inoculum was homogenized in sodium phosphate buffer (0.01 M, pH 7.4). The extract was filtered through gauze and placed in melting ice. Before inoculation, the leaves of cowpea plants older than a week from the three replications were dusted with the mixture of carborundum 600 mesh, an abrasive product and inoculum using a cotton swab pestle dipped in the extract, the upper leaf surface was rubbed gently (Neya, 2011). The symptoms of CABMV were recorded between the 6^{th} and 21^{st} day after inoculation.
Data collection
Observations were made on:
1. The severity assessment using rating scale 6 classes (0 to 5) which is a strength criterion in CABMV.
2. AUDPC: The area under disease progression curve proposed by Shaner and Finnay (1977) using the following equation AUDPC = (X_{i}+1 + X_{i}) / 2][t_{i}+1 – t_{i}] where n: total number of cases; X_{i}: the first observation of disease in days; X_{i} + 1: the second observation of disease in days; t_{i}: time in days from the first observation of disease and t_{i} + 1: time in days for the second observation of the disease. It is a study of a disease development rate of a given crop. This parameter selects the best lines in terms of their ability to slow down the progression of the disease.
Data analyses
Hayman (1954) and Griffing (1956) methods were used for analysis of variance (ANOVA) from DIAL Win 98 software revised 22 September 2002.
The method of Griffing (1956) is based on two models: the fixed pattern and random model. The fixed model is applied to a limited number of lines set for selfpollinated crops and inbred lines of crosspollinated species.
As for the random model, information may extend to the entire population, provided individuals are the representation of a random mating population in equilibrium. There are four methods for each model according to the use of the parents and crossing type.
a. Reciprocal crosses and parents.
b. A twoway crossing and parents.
c. Reciprocal crosses without parents.
d. A twoway crossing without parents.
In this experiment, the fixed model and method a were used. The statistical model is:
Υij = μ + λi + λj + Sij + eij
where: μ = population mean; λ (λj) = general combining ability (GCA) of the parent i (j); Sij = specific combining ability of crossing by i j; eij = effect of the environment on the individual ij.
Hayman (1954) used the following symbols for a given character to express the statistics in his model where, VP: variance of a parent; Vr: a variance r parent and his descendants; Wr: r covariance between a parent and his descendants; W'r: covariance between the value of each descendant of r parent and other descendants of that parent; Yr: r value of a parent.
The interpretation by the model of Hayman requires a certain number of conditions: homozygous parents, identical reciprocal crosses, no multiallelism, diploid parents, absence of epistasis, no maternal effect, independent distribution of the relevant genes of the parents.
The authors can estimate the various genetic components of the change and test their significance from their own variance and the following statistical terms: E: component due to the environment; D: component due to additive effects; H_{1}: component due to nonadditive effects; H_{2}: component due to unweighted additive effects in terms of a possible asymmetry in the distribution of allele’s dominance representative loci; F: covariance between the additive effects and nonadditives.
Knowledge of these components allows the following calculations:
DH_{1}, in which sign expresses the kind of dominance.
½ (D + H_{1}H_{2}F) 1/2 (D + H_{1}F) 1 / 4H_{2} + E: Heritability in the narrow sense
The conformity of the model with these restrictions can be rarely achieved in practice. Most of them however, can be checked during the statistical analysis, when the results are consistent with the additivedominance model Mather and Jinks (1982), although only the interpretation of parental values and F_{1} hybrids cannot fully control the factors of noncompliance with the model. Furthermore, the influence of reciprocal effect is erased by working out the average mutual boxes.
Analysis of variance for GCA and SCA and reciprocal using Griffing’s method for severity
The results of the variance related to the general combining ability effects (GCA), the specific combining ability (SCA) and the reciprocal effects (RCE) are shown in Table 1.
The analysis of variance was highly significant for the SCA and nonsignificant for GCA and RCE. SCA effects occur very significantly in expression of severity. The calculated mean value of the GCA/SCA variance ratio is low (1.29).
Analysis of variance for severity by Hayman model
The results of different terms of Hayman variance analysis is presented in Table 2. With regards to the degree of significance of the dominance effects (SCA), the results obtained are consistent with those found using Griffing’s method. The results shown in Table 2 are presented based on the different terms described by Hayman. These terms are:
1. The term b_{1} is the mean deviation of the first generation F_{1} hybrids relative to the average parent which is highly significant for the severity. This result shows that the dominant genes are exerted in a unidirectional manner.
2. The term b_{2 }which is the average deviation of the F_{1} as compared to the average values â€‹â€‹of each parent is not significant for the severity. This result indicates that there is no asymmetry in the distribution of alleles at loci showing dominance.
3. The term b_{3 }deviation due to the dominance of own F_{1} represents the specific combining ability. This term is highly significant for the severity.
4. The term that tests the differences between reciprocal crosses is not significant for the severity.
Analysis of variance and GCA, SCA and RCE effects by Griffing’s method of AUDPC
The results of the variance related to the effect of the general combining ability (GCA), specific combining ability (SCA) and the reciprocity effects (RCE) are shown in Table 3.
The analysis of variance is significant for SCA and not significant for the GCA and RCE. The calculated mean value of the variance ratio GCA / SCA is low (1.24).
Analysis of variance for AUDPC in F_{1} generation by Hayman’s model
The results of the different terms are presented in Table 4. The results obtained by the method of Hayman concerning the degree of significance of the dominance effects (SCA) and additive (GCA) are not consistent with those found by Griffing. These results provide the following clarifications:
1. The term b_{1} which is the mean deviation of F_{1} as compared to the average parent, is highly significant for AUDPC. This result shows that the dominant genes are exerted in a unidirectional manner.
2. The term b_{2 }which is the average deviation of the F_{1} as
compared to the average values â€‹â€‹of each parent is also highly significant for AUDPC.
3. The term b_{3} deviation due to the dominance of own F_{1} represents the specific combining ability. This term is significant for AUDPC.
4. The term that tests the differences between reciprocal crosses is not significant for AUDPC.
Validity of the assumptions corresponding to the additivedominance model
The results of the homogeneity of the expression WrVr test are presented in Table 5. The test is not significant for the severity and for the AUDPC, so the model is respected and thus allows further analysis.
Moreover, Vr/Wr regression on the slope of the line for the severity (0.88) and for the AUDPC (1.04) is not significantly different from 1.
Analysis of genetic components
The estimates of the different genetic components of the characters studied for the F_{1} are presented in Table 6. These values were used to calculate the narrow sense heritability by Mather and Jinks (1982). The term DH_{1} reflects the type of dominance. When this expression is negative, there is super dominance. In that case, the variance of additive effects (D) is smaller than the variance of nonadditive effects (H_{1}). When it is positive, there's partial dominance and this is the case for the severity and AUDPC with respective value of 1.56 and 85.33. When D is equal to H_{1}, there is a total dominance.
The expression H_{1}H_{2 }= 0.089 for severity is low as compared to the H_{1} and H_{2} estimates of dominance effects. Although, the asymmetry in the distribution of genes is significant (b_{2} refers to the analysis of variance), this effect does not play a major role in nonadditive effects. The same result was obtained with the area under the disease progression curve (AUDPC); H_{1}H_{2}: 7.63, which is low as compared to the H_{1} and H_{2} estimates of dominance effects.
Table 7 shows the average values of heritability in the narrow sense obtained by Griffing and Hayman. There is a high heritability strict sense according to Griffing (68.64%) and Hayman (63.35%) for the severity parameter. By cons, it is very high according to Hayman (85.21%) and high according to Griffing (66.99%) for the AUDPC.
Graphical analysis for severity and AUDPC
The graphical representation of Wr (covariance between a parent r and its progeny) by the Vr (variance of a parent r and its progeny) are given in Figures 1 and 2 for the severity and the AUDPC respectively. Three curves are shown on the graph:
1. A regression line;
2. A dish that cuts the regression line in two points, M and M*
3. A tangent to the parabola is almost confused with the regression line
Nonsignificant GCA was observed for both parameters (severity and AUDPC). This implies that nonadditive gene action is operating for these parameters. This result differed from what was observed by Orawu (2007). This author found significant GCA effects in CABMV, suggesting that additive gene action is involved in the resistance of cowpea to the disease. Nevertheless, the ratio of Griffing (1956) between GCA/SCA showed that additive genes were also operating for the resistance of cowpea to CABMV disease. For this author, when the ratio is greater than 1 (one), additive effects are more important than nonadditive effects. This is also in agreement with the findings of Singh and Chaudhary (1977). Additive gene action seems to be important in cowpea. Tignegre (2010) also found additive gene action for more than seven parameters under a Striga infestation study.
SCA effects were highly significant for the two parameters studied (severity and AUDPC). This implies that nonadditive gene effects involving either dominance or epistasis and in some instances both, were observed for these parameters. However, where nonadditive gene effects including epistasis were operative, prediction of the breeding outcome would be difficult as nonadditive gene effects are not heritable for pure line cultivars (Tignegre, 2010). Dominance effects (that is, partial dominance, complete dominance or over dominance) cannot be transferred to the progenies and might slow down the progress in selection. However, such gene action would have been useful in hybrid production. Nonetheless, the selfpollinating nature of cultivated cowpea renders difficult the production of hybrid cowpea. However, with some perennial cowpea wild relatives, the occurrence of high rates of cross pollinations (unpublished data) are new fields for hybrid production in cowpea.
There were no maternal and reciprocal effects, suggesting that there were no genetic implications in using a parent as male or female when crossing cowpea for these characters. Therefore, seeds of F_{1} and reciprocal crosses can be bulked and used in studying these parameters. These results are in agreement with those of Tignegre (2010). This also implies that no genes originating from the cytoplasm are involved in the inheritance of the characters studied.
Narrow sense heritability measures the breeding value that is passed on to the progenies. Regardless of the method used, high narrow sense heritability was observed in this study. By Griffing’s method, the narrow sense heritability was 68.64% for severity and 66.99% for AUDPC. By Hayman’s method, the narrow sense heritability was 63.35% for severity and 85.21% for AUDPC. These rates measure the breeding progress that can be expected during selection using the type of protocol employed here.
For all parameters, based on the graphical analysis, with a regression of unit slope b Wr>0.50, a regression coefficient of approximately 50.00% or more indicated that the additive model was adequate to describe the data (Jinks and Hayman, 1953; Christie and Shattuck, 1992; Dalbholkar, 1992; Sharma, 1995). Considering Figures 1 and 2, two extremes to be taking into account are, M and M* corresponding to the intercepts between the regression line and the parabola. Theoretically, M and M* correspond to the genotypes of the parents that have respectively the parent with dominant genes and parent with recessive genes. All individuals close to M have dominant genes, those close to M* have the recessive genes and intermediate genotypes to the two points have a mixture of dominant and recessive genes. Thus, in both figures, parents 5 and 4 have dominant genes; parents 2 and 3 have both dominant and recessive genes, and parent 1 has the recessive genes for severity and AUDPC parameters. Parents 5 and 4 correspond to resistant genotypes and parent 1 is the susceptible genotype. Parents 2 and 3 are intermediate varieties. The parent 5 is very close to M and parent 1 close to M*. This means that opportunities for transgression are relatively low. The slope of the severity on the regression line is equal to 0.88 and that of the AUDPC is 1.04. These values are not significantly different from 1, showing that there is nonallelic relationship and particularly complementary gene actions between parental combinations. Only additive gene action and partially dominant action exists in the parental combinations. These results are similar to those found in 2012 by Zagre on soybeans.
From this study, it was inferred that from the pot screening, regardless of the method used, nonadditive genes were predominant in the inheritance of CABMV resistance with regard to the parameters severity and AUDPC. Only nonallelic interactions (epistasis and failure of some assumption) were present with both parameters (severity and AUDPC).
Narrow sense heritability according to the methods of Griffing and Hayman for severity and area under the disease progress curve is high. This suggests that these resistance parameters are strongly passing from parents to offspring. Hayman's method is more restrictive, the heritability was retain from this model. High values of heritability indicate that additive is the major gene action phenomenon in this study.
The authors have not declared any conflict of interests.
REFERENCES
Allard RW (1999). Principal of plant breeding. John Wiley and Sons. USA. 254.


Batieno TBJ (2014). Breeding for Drought Tolerance in Cowpea [Vigna unguiculata (L.) Walp.] using Marker Assisted Backcrossing. Doctor of philosophy, University of Ghana, Legon, West Africa Centre for Crop Improvement, P 153.


Christie BR, Shattuck VI (1992). The diallel cross: Design, analysis, and use for plant breeders. Wiley, New York, USA. pp. 936.


Dalbholkar AR (1992). The diallel mating design: Graphical and numerical approach. New Delhi, India. Concept Publishing Company. P 431.


Demarly Y (1977). Génétique et amélioration des plantes. Masson. Paris, New York,Barcelone, Milan. p 287.


Griffing B (1956). Concept of general and specific combining ability in relation to diallel crossing system. Austr. J. Biol. Sci. 9:463493.
Crossref


Hayman BI (1954). The theory and analysis of diallel crosses. Genet. 1:789809.


Jinks JL, Hayman BI (1953). The analysis of diallel crosses. Maize Genet. Coop Newslett. 27:4854.


Mather K, Jinks C (1982). Biometrical genetics. London: Chapman and Hall. P 396.
Crossref


Neya J (2011). Sérologie, pathologie, épidémiologie et contrôle de la mosaïque Cowpea Aphid Borne Mosaic Virus (CABMV) du niébé (Vigna unguiculata (L.) Walp.) Transmise par des pucerons (Aphid crassivora, A. gossypii) au Burkina Faso. Thèse de Doctorat, Université de Ouagadougou. P 153.


Orawu M (2007). Occurrence of cowpea aphidborne mosaic virus and prospects of improving resistance in local cowpea landraces in Uganda. PhD Thesis, University of KwaZuluNatal, P 137.


Shaner G, Finney R (1977). The effect of nitrogen fertilization on the expression of slowmildewing in Knox wheat. Phytopathol. 36:13071311.
Crossref


Sharma JR (1995). Hayman's model of diallel analysis: Models for intensive studies2. In: Statistical and biometrical techniques in plant breeding. J. R. Sharma, (ed). Lucknow. New age international (P) limited, Publishers pp. 179203.


Singh RK, Chaudhary BD (1977). Biometrical Methods in Quantitative Genetic Analysis. Kalyani Pub. New Dehli.P 288.


Tignegre JB (2010). Genetic study of cowpea (Vigna unguiculata L. Walp) resistance to Striga gesnerioides (willd.) Vatke in Burkina Faso. Doctor of philosophy, University of KwaZuluNatal. P 176.


Zagre B (2012). Analyse diallèle du rendement graines par hectare et du poids de 1000 graines chez le soja (Glycine MAX (L.) MERRILL. J. Rech. Univ. Lomé (Togo), série A, 14(2):5159.


Zagre B, Balma D, Cattan P (1999). Analyse diallèle du poids de mille graines chez le sésame. Cahiers Agric. 8:11822.
