Genetic variability in progenies of Eucalyptus dunnii Maiden for resistance to Puccinia psidii

Variabilidade genética em progênies de Eucalyptus dunnii Maiden para resistência à Puccinia psidii

ARTICLE

Genetic variability in progenies of Eucalyptus dunnii Maiden for resistance to Puccinia psidii

Variabilidade genética em progênies de Eucalyptus dunnii Maiden para resistência à Puccinia psidii

Cleber da Silva PintoI, ^*; Rodolfo Manoel Lemes da Costa^I; Cristiano Bueno de Moraes^II; Cristiane de Pieri^I; Evandro Vagner Tambarussi^III; Edson Luiz Furtado^I; Edson Seizo Mori^I

^IUniversidade Estadual Paulista Júlio de Mesquita Filho(UNESP) - Botucatu, Av. Dr. José Barbosa de Barros, 1780, Lageado, 18.610-307, Botucatu, SP, Brazil

^IIUniversidade Federal de Tocantins (UFT), Rua Padejós, L7 Chácara 69/72, Zona Rural CP 66, 77.402-970, Gurupi, TO, Brazil

^IIIEscola Superior de Agricultura “Luiz de Queiroz”, Universidade de São Paulo, Av. Pádua Dias, 11, CP 9, 13.418-900, Piracicaba, SP, Brazil

ABSTRACT

This study investigated the genetic variability in progenies of Eucalyptus dunnii Maiden for resistance against rust (Puccinia psidii). Field experiments were installed in two regions with differentsoil-climatic conditions. Open-pollinated progenies were established in arandomized complete block design. Sixty and 48 progenies were evaluated underfield conditions at two sites, respectively, with six replications and eight trees per plot. In another experiment in a controlled environment, 53 progenies were evaluated in randomized blocks with six replications and nine plants perplot. The following traits were evaluated: plant height, severity of pestattack and the most susceptible stage to the leaf disease. The genetic variability for rust resistance in the E. dunnii population under studywas high, with a genetic coefficient of variation of 36.07%; 7% of thee valuated progenies were rust-resistant. It indicates a high potential for selection and breeding of the species.

Key words: Eucalyptus, genetic parameters, progeny testing, forest breeding

RESUMO

Avaliou-se a variabilidade genética em progênies de Eucalyptus dunnii Maiden para resistência à ferrugem (Puccinia psidii). Experimentos de campo foram instalados em duas regiões edafoclimáticas.Progênies de polinização aberta foram estabelecidas em um delineamento emblocos casualizados. Em condições de campo foram avaliadas 60 e 48 progênies emdois locais, com seis repetições e oito plantas por parcela. Instalou-se tambémum experimento em ambiente controlado, com 53 progênies, em blocoscasualizados, com seis repetições e nove plantas por parcela. Foram avaliadas altura da planta e a severidade de ataque que determinam a fase mais suscetível à doença foliar. A população de E. dunnii estudada apresentou alta variabilidade genética para resistência à ferrugem, com coeficiente de variação genética de 36, 07% e 70% das progênies avaliadas foram imunes a ferrugem. Isto indica alto potencial para seleção e melhoramento da espécie.

Palavras-chave: Eucalyptus, parâmetros genético, teste de progênies, melhoramentogenético florestal

INTRODUCTION

Brazilis one of the world's largest producers of Eucalyptus wood. The share ofthe forest sector in the national economy, which has a participation ofapproximately 4.5% of GDP, clearly shows the importance of this genus for thecountry is grown on an area of 6.5 million hectares and generates about 4.73million jobs (ABRAF 2012).

With the expansion of eucalyptus cultivation to warmer and more humid regions and withthe impact of climate changes, conditions have become favorable for theoccurrence of diseases (Telechea et al. 2003, Glen et al. 2007). Consequently, the planting of susceptible species and the uninterrupted use of the samecultivation areas increase the chances of pest attacks.

One of the major diseases of Eucalyptus today is rust. The economic problemsresulting from rust are related to planting in the field (Ferreira 1983), wherefungicide treatments are practically unfeasible. The vegetative growth of Eucalyptusgrandis trees infected with this pathogenic fungus can be reduced by 28% to35%, compared to unaffected plants, resulting in direct losses in productivityand economic gains.

Nowadays, several forms of rust control are being applied, for example: fungicidetreatment, tree harvest for regrowth in disease-unfavorable seasons andcultivation of resistant plants. For a number of reasons, the use of resistantvarieties is the most indicated measure: it is cheap, practical and has lessenvironmental impacts for requiring less fungicide application (Carvalho et al.1998.).

Resistant plants can be selected in the field in progeny and clonal tests (Zobel andTalbert 1984, Alfenas et al. 2004, Teixeira et al. 2009), in areas wherethe disease is severe, endemic or even by infection through artificialinoculation in a controlled environment (Xavier et al. 2001).

A series of studies on rust have been conducted for the genus Eucalyptus (Dianeseet al. 1984, Freeman et al. 2008, Zauza et al. 2010, Miranda et al. 2013, Silvaet al. 2013) in view of the great commercial importance for the country.However, there are few reports in the literature about the disease in thespecies Eucalyptus dunnii Maiden, although the occurrence of the diseasein the field has been observed. Therefore, this study evaluated the geneticvariability in E. dunnii progenies for rust resistance caused by Puccinia psidii.

MATERIAL AND METHODS

Twotrials of E. dunnii open-pollinated progenies were set up in the field(Itapetininga and Itatinga , SP, see Table 1), in July 2009. Thetrials were arranged in a randomized block design with 60 and 48 progenies, both with eight plants per plot with six replications, in a 3 x 2 m spacing Thetrial into the controlled environment (inoculation chamber) was carried out inthe Department of Crop Science in the Sector of Plant Protection and PlantBreeding of São Paulo State University (UNESP), in Botucatu, SP, Brazil, by therandomized blocks with 53 progenies, with nine plants per plot and sixreplications, totalizing 2, 544 plants. The total used progenies in thecontrolled environment trial, 48 were set up at Itapetininga, and all of 53were at Itatinga.

Inoculation was performed with an uredospore solution of P. psidii from plants of aspontaneously infected rose apple (Syzygium jambos) tree, in acontrolled environment. The spores were scraped from the leaves with a stylusand suspended in distilled water plus Tween 20% to reach a concentration of 9 x104 spores mL^-1. The suspension was sprayed on all plantswith an air compressor (Chiaperini® 2, 3pcm, ModelE48C) to ensure an even distribution of the spore suspension. Thetest temperature was maintained at 22 ºC, the average relative humidity was 80%and the photoperiod 12 hours, for 15 days, until evaluations.

The following characteristics were evaluated in progeny field trials: tree height(H) and severity of fungal attack, to correlate the attack intensity with thedevelopment of the progenies. Evaluations were performed every three months forseverity, with four assessments, and every six months for height, with twoevaluations. Data on the severity of rust attack were collected in the field, based on grade criteria from 0 to 4, where: 0 - resistant plant; 1 - sporadicsporulation; 2 - generalized sporulation, but no apparent damage to the plant;3 - generalized sporulation on leaves and branches, causing major damage and 4- advanced disease, with loss of apical dominance. To determine resistancelevels in E. dunnii progenies we used a grade scale adapted by Aparecidoet al. (2003), and the data were previously transformed to .

The genetic parameters for each individual test were estimated using the program SELEGEN (Resende 2007) model 93, by the statistical model: y = Xr + Za + Wp + e, where y is the data vector, r the vector of effects ofreplications (assumed as fixed) added to the overall mean, a is thevector of individual additive genetic effects (assumed as random), p isthe vector of plot effects (random) and e is the error or residue vector(random). Capital letters represent the incidence matrices for these effects. X, Z and W are known incidence matrices formed by the values zero andone, which associate the unknown r, a and p to the datavector y, respectively. By the mixed model methodology r can beestimated by the generalized least square procedure and predict a and p by the BLUP procedure. The REML procedure (method of maximum likelihood) wasperformed based on Expectation-Maximization (EM) algorithms, where theresolutions of the matrices provide estimates of adjusted effects of thecalculated vectors. The following genetic parameters were estimated:

a) Additive genetic variance ()

b) Environmental variance between plots ()

c) Residual variance (environmental +non-additive) ()

where C²² and C³³ are the inverse of C.

C: matrix of the coefficients of the mixed model equations

tr: trace operator matrix.

r(x): rank of matrix X.

N, q, s: number of data, plants and plots, respectively.

d) Individual phenotypic variance ()

e) Individual narrow-sense heritability, i.e., the additive effects:

f) Heritability of progeny means:

g) Additive heritability within plot:

h) Coefficient of individual additive geneticvariation:

i) Coefficient of genotypic variation amongprogenies:

j) Coefficient of experimental variation:

k) Coefficient of relative variation:

l) The combined analysis (mathematical model 4)and genetic and phenotypic correlations (mathematical models 105 and 102) wereestimated using SELEGEN software.

RESULTS AND DISCUSSION

The coefficient of experimental variation for rust resistance was 19.2%, 15.7% and18.9%, in the three trials, respectively (Table 2). These values indicate good experimental accuracyfor field trials and controlled environments in species of the genus Eucalyptus (Garcia 1989).

The values of the estimates for individual narrow-sense heritability were moderate ( = 0.48 and 0.37) and high for mean progenyheritability ( = 0.84 and 0.64) into the inoculation chamberand in Itapetininga trial, indicating low influence of the environment on therust resistence (Resende 2007). The values were similar to those reported byMori et al. (2004) for rust resistance in E. grandis progenies underfield conditions.

In the region of Itatinga, heritability was generally low, indicating the influence ofenvironmental factors on trait expression. In the case of rust resistance, thiscan be influenced by the low availability of inoculum in the environment.

In general, estimates of the coefficient of individual genetic variation (CV_gi)were higher than the variation among progenies (CV_gp) forrust resistance. Lowest values of CV_gi (2.1%) and CV_gp (1.0%) were observed for rust severity in the Itatinga field trial, and highestvalues of CV_gi (36.1%) and CV_gp (18.0%) were found in the progeny trial in the inoculation chamber. The high CV_gi values show possibilities for selection in breeding programs. Miranda etal. (2013) found very similar CV_gi values (11.7% - 36.7%) for Eucapyptus grandis by nine different locations.

The relative coefficients of variation (CV_r) were low, medium andhigh, in the experiments in Itatinga, Itapetininga, and the controlledenvironment, respectively (Table 2). According to Vencovsky and Barriga (1992), the higher the CV_r value, the greater is the genetic controlof traits and the lower is the influence by environmental factors, favoringselection.

The experimental coefficient of variation (CV_exp) for H (Table 3), evaluated after six and 12 months, was high in both field trialts. Thehighest CV_exp values were found in Itapetining (19% after 6 monthsand 21.7% after 12 months). In Itatinga, CV_exp was adequate(15.2% after 6 months and 14.3% after 12 months), which is close to values foundin the literature (Santos et al. 2004, Souza et al. 2011).

The heritability at the individual plant level, in the narrow sense () was low for H in Itapetininga (0.10 ± 0.04after 6 months and 0.07 ± 0.03 after 12 months) and high in Itatinga trial(0.60 ± 0.09 after six months and 0.58 ± 0.09 after 12 months). This mayindicate that about 90% of the variation in Itapetininga and 40% in Itatingamay be induced by the environment. The values found in Itatinga, at the two ages for H, werehigher than values found in the literature (Rocha et al. 2007, Rosado et al. 2009), in their studies with E. urophylla. For meanprogeny heritability (), the highest values found for Itatinga show that theenvironment had little influence on the phenotypic expression of H.

The coefficients of individual genetic variation (CV_gi %) werehigher than those of genetic variation of progenies (CV_gp %)in both experiments and at both ages. In the tests, CV_gi %varied from 9.8% for Itapetininga / SP, after 12 months, to 26.7% forItatinga / SP after 6 months. The same trend was found for CV_gp %. The results show the genetic variability for the trait ALT, under theexperimental conditions of the study site.

The coefficients of relative variation (CV_r) were high inItatinga, with an approximate value of 0.87, at both ages. In Itapetininghowever, the values were close to 0.27, similar to the values found foropen-pollinated progenies of E. urophylla (CV_r =0.21)after 17 years for plant height, in Selvíria, MS (Souza et al. 2011). Accordingto Vencovsky and Barriga (1992), these values are considered low. The low CV_r values indicate that the genetic control of the trait is low and highlyinfluenced by the environment. According to Vencovsky (1978), the CV_r estimates close to 1 are recommendable.

The genetic and phenotypic correlations are presented in Table 4. The correlationswere highest for the character height (H), between different ages in the sameenvironment. The high values show that the performance of the genotypes doesnot vary with increasing age. This behavior is important in the case of earlyselection.

Forrust, the highest correlation was found between Itapetininga and inoculationchamber, where a genetic correlation (r_g) of 0.50 wasobserved. However, the same was not true for the phenotypic correlation (r_f), where a value of 0.04 was calculated. When progeny performance, tree height, and rust susceptibility were correlated, the values were very low, indicating that thepoor performance of the plant material had no influence on rust attack. Thismay have occurred because of the low rust-susceptibility of the species, or tothe low availability of inoculum in the area of the field trials. In general, the correlations found in this study were low, hampering indirect selection forthe studied traits.

The estimates of genetic parameters in the combined analysis for rust in all threeenvironments in pairwise analysis (controlled environment / Itapetininga, controlled environment / Itatinga and Itapetininga / Itatinga) andfor the trait plant height in Itapetininga / Itatinga are shown in Table 5.

The combined analysis showed mean and low values for heritability. The values were highest in the analysis betweentests of inoculation chamber and Itapetininga. The lowest values on the otherhand were observed in the combinedanalysis of the two field tests for rust resistance.

The genotypes x environments (GE) interactions were high in the rust analysis inthree environments, between the test controlled environment / Itapetiningaand at both ages for plant height. This shows the presence of a complex GEinteraction. In this case, the decision on selection is more difficult, sincethe selection of genotypes adapted to specific environments is required.Miranda et al. (2013) observed strong genetic control associated with rustresistance between provenances of E. grandis. For resistance in interspecific Eucalyptus hybrids to P. psidii, Alves et al. (2012) observedthat quantitative additive and epistatic trait loci explain between 29.8 and44.8% of the phenotypic variation, respectively. This is evidence of a morecomplex inheritance pattern of the trait. The genotypic correlation between theprogeny performance in various environments (r ˆ _gloc = 0.21) wasconsidered low. Still, this interaction could be exploited in a positive way inbreeding programs since it allows directing a particular genotype towards aspecific region, maximizing the phenotypic trait expression in thisenvironment. However, if the genotype is directed towards another region, itsphenotypic value might be reduced.

In summary, this study shows the great potential of the studied populations of E.dunnii for selection and breeding, with a view to rust resistance, since70% of the progenies obtained grade zero (resistant plants) and the geneticvariability for rust resistance in the studied population was good (CV_gi = 36.07%). The genetic correlation between the test in the controlle denvironment and field test in Itapetininga was also good (r_g = 0.50); this shows that the controlled environment is a good alternative forearly selection of plant material for rust resistance to obtain progress in the E. dunnii breeding program for rust. It is noteworthy that the geneticcorrelation between the controlled environment and Itatinga (CI/R2) is zero, which prevents a selection under controlled conditions for response toselection in Itatinga. Even the field data showed no genotypic correlationbetween Itatinga and Itapetininga.

Received 4 June 2013

Accepted 12 May 2014

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Publication Dates

• Publication in this collection
  25 Nov 2014
• Date of issue
  Oct 2014

History

• Accepted
  12 May 2014
• Received
  04 June 2013