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a Institute of Plant Breeding, Seed Science, and Population Genetics, Univ. of Hohenheim, 70593 Stuttgart, Germany
b Crop Science Dep., Univ. of Illinois, S-110 Turner Hall, 1102 South Goodwin Avenue, Urbana, IL 61801
* Corresponding author (melchinger{at}uni-hohenheim.de)
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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) and Type II (1 – ß) errors than observed with GDs based on SSRs and AFLPs. Consequently, morphological traits and heterosis are less suited for identification of EDVs in maize than molecular markers.
Abbreviations: AFLP, amplified fragment length polymorphism • BC, backcross • DUS, distinctness, uniformity, and stability • EDV, essentially derived variety • GD, genetic distance • GR, genetic ratio • IDV, independently derived variety • IV, initial variety • MD, morphological distance • MPH, midparent heterosis • PIC, polymorphic information content • PVP, plant variety protection • RFLP, restriction fragment length polymorphism • SSR, simple sequence repeat • UPOV, International Union for the Protection of New Varieties of Plants
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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Tools like doubled haploids, marker-assisted backcrossing, and genetic engineering allow to add a small number of genes to a protected variety and apply for PVP for this new variety. In addition, it is possible to select intentionally for lines that are similar to their parents. The efforts invested in breeding the original variety can thus be exploited by the breeder of the plagiarized variety without indemnification. The concept of EDVs was, therefore, implemented into the revised UPOV convention (UPOV, 1991) and several national PVP acts.
Regarding the EDV concept, a variety is deemed essentially derived from an IV if it is clearly distinguishable but conforms genetically to the IV. If the extent of conformity exceeds a certain threshold, the concept of EDVs indicates that the breeder of the EDV has to reach an agreement with the breeder of the IV. However, no consensus has currently been reached on the methods for determining the genetic conformity to distinguish between EDVs and independently derived varieties (IDVs). In addition, accepted or nonaccepted breeding procedures have not yet been defined.
Molecular markers, especially SSRs and AFLPs, have been recommended as appropriate tools for determining EDVs in various crops including maize (Dillmann et al., 1997; Roldan-Ruiz et al., 2000a; Borgo et al., 2002). By contrast, the use of morphological traits or heterosis is still under debate (International Association of Plant Breeders for the Protection of Plant Varieties, 1999). Until now, accurate morphological and agronomic descriptions of cultivars and varieties have been the basis of tests for distinctness, uniformity, and stability (DUS) within worldwide PVP systems and have assured farmers and breeders that they are using clearly identifiable varieties to high standards of purity and quality (Smith and Smith, 1989a). In addition, numerous studies showed significant correlations between MPH and the coefficient of parentage (f) (Melchinger, 1999; Smith et al., 1991). For these reasons, proponents of the use of morphological traits or heterosis for identifications of EDVs state that phenotypic information provides the basis for PVP and should also be used for identification of EDVs. Studies on the ability of morphological traits to estimate the genetic conformity between related ryegrass (Lolium perenne L.) varieties revealed that they had only a limited power to distinguish between IDVs and EDVs (Gilliland et al., 2000; Roldan-Ruiz et al., 2000b).
In maize, a triangular instead of a linear relationship was observed between MDs and GDs or the coancestry coefficient (f) (Dillmann and Guérin, 1998), which indicates that low GDs correspond necessarily with low MDs, whereas the reverse does not necessarily hold true because high GDs can correspond with both high and low MDs. In addition, genetic relationships among maize inbred lines based on morphology were essentially random compared with any relation derived from heterosis or pedigree data (Smith and Smith, 1989b). However, data on the usefulness of heterosis or morphological traits that reflect the degree of relatedness between maize inbred lines in terms of essential derivation is scanty.
The main goal of this study was to investigate the relationship of homozygous progeny lines in maize derived from F2, BC1, or BC2 populations to their parental inbreds based on heterosis and MDs in comparison with SSR- and AFLP-based GDs. In detail, our objectives were to (i) evaluate the power of heterosis and MDs to discriminate between progenies derived from F2, BC1, and BC2 populations, (ii) compare the findings to published data based on SSRs and AFLPs, and (iii) draw conclusions about the usefulness of the various distance measures for the identification of EDVs.
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MATERIALS AND METHODS |
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For each combination of lines within a triplet (P1 x P2, P1 x O, and P2 x O), seeds from the corresponding F1 hybrid were generated. In addition, if more than one progeny line (O1, O2, ...., Oj) was derived from a cross of the same two parental lines, each possible F1 hybrid (O1 x O2, ..., Oj–1 x Oj) was generated. In total, 114 intrapool F1 hybrids were tested in this study. Detailed information on all 38 triplets, the 58 maize inbreds, and the hybrids included in this study is available as supplemental data on the internet at http://crop.scijournals.org/.
Experimental Design
Field experiments were conducted in 2000 and 2001 at three locations in South Germany, with two replications per location. All sites (Bad Krozingen, Eckartsweier, and Scherzheim) are located in the Upper Rhine Valley, a major area of grain-maize production in Germany. All inbred lines and hybrids of a triplet were grown together in one block. Within each triplet block, F1 hybrids were grown side-by-side with their parental lines to guarantee heterosis estimates with high accuracy. All trials received standard cultural practices of fertilization as well as control of insects and weeds.
The experimental unit was a three-row plot with a row spacing of 0.75 m and a plot length of 4.0 m. Trials were overplanted and later thinned manually to 26 plants per row, with a final plant density of 8.7 plants m–2. Each row was harvested separately. To reduce neighbor effects between adjacent plots with different vigor (inbreds vs. hybrids), only data of the middle row of each plot were used for further analyses. The experiment was performed using a randomized complete block design. Parameter values were observed for 23 morphological traits according to the UPOV guidelines (UPOV, 1978), and for six additional agronomic traits (Table 1) by measuring a minimum of five individual plants of a particular plot or by visual observation of the whole plot.
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Statistical Analyses
Grain yield for each single row was adjusted to 84.5% dry matter content. Heterosis was determined as MPH = (F1 – MP)/MP, where F1 is the F1 hybrid performance, and MP = (P1 + P2)/2, the midparent value in which P1 and P2 are the performances of the inbred parents. Analyses of variance were performed for morphological traits of the inbreds using a mixed linear model considering genotypes as fixed effects, and environments as well as genotype x environment interactions as random effects. Genotypic variance among lines 
and the variance of genotype x environment interaction 
were defined and estimated according to Scheffé (1959). Similarly, genetic ratios (GR) analogous to broad-sense heritability were calculated as GRg = 
g2er/MSg, where e is the number of environments, r is the number of replications, and MSg is the mean square due to genotypes. Dhillon et al. (1990) may be consulted for further details. Likewise, ANOVAs were calculated for MPH values of each triplet to estimate the genotypic variance for midparent values among triplets 
and corresponding genetic ratio (GRt), using the same procedures.
For calculation of MDs, observations for each trait were standardized by dividing by the phenotypic standard deviation of the particular trait. Euclidean (MDEUC) and Mahalanobis (1936) (MDMAH) distances were calculated based on standardized observations for each pairwise comparison of inbred lines. Malécot's (1948) coancestry coefficient (f) was calculated between all pairwise line combinations. Polymorphic information content (PIC) values were estimated as suggested by Anderson et al. (1993). Genetic distances between lines based on SSR (GDSSR) or AFLP (GDAFLP) data were estimated using Rogers' distance (Rogers, 1972). The linear relationships between 1 – f, GDs, MDs, and heterosis estimates were evaluated with a lack-of-fit test (Snedecor and Cochran, 1980). Empirical and approximated frequency distributions of MD values were compared with a Kolmogorov-Smirnov test (Lehmann, 1986) to check for significant deviations. Furthermore, simple correlations (r) were calculated between 1 – f, GDs, MDs, and heterosis estimates. Homogeneity of variance components of data from flint and dent germplasm was evaluated with Levene's test (Levene, 1960). Variance components and correlations were not significantly different between flint and dent lines. Consequently, only results from pooled data were reported.
To evaluate potential EDV thresholds, the cumulative frequency distributions for GDs were approximated by ß distributions (Johnson et al., 1995), as described in detail in our companion study (Heckenberger et al., 2005). Frequency distributions for MDs and MPH for F2–, BC1–, or BC2–derived progeny lines were approximated by normal distributions with parameters chosen such that the mean and variance of the original distribution were conserved. On the basis of these distributions, we calculated Type I () and Type II (ß) errors for various EDV thresholds and various types of populations, as suggested by Heckenberger et al. (2005) for molecular marker data. Here, corresponds to the probability that a true IDV will be wrongly judged as EDV, whereas ß corresponds to the probability that a true EDV will not be recognized as such and judged as IDV. We first investigated the situation that a F2–derived progeny would be considered as IDV, and a BC1–derived progeny as EDV. Alternatively, we regarded a BC1–derived progeny as IDV, and a BC2–derived progeny as EDV.
Statistical analyses of marker data and f values were performed as described by Heckenberger et al. (2005) using the PLABSIM software package (Frisch et al., 2000). The ANOVAs for field experiments were calculated with the PLABSTAT software (Utz, 2001). All other statistical calculations were performed with the R software package (Ihaka and Gentleman, 1996).
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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pooled across flint and dent inbred lines were significant (P < 0.01) for all traits (Table 1). In addition, significant (P < 0.01) genotype x environment interactions were observed for most traits due to cool and wet weather conditions in 2000 and hot and dry weather conditions in 2001 (data not shown). In most cases, ge2 was considerably smaller than 
g2.
Significant (P < 0.01) estimates of t2 among triplets for MPH were observed for most traits (Table 2). However, considerable differences were found between traits depending on the relative amount of MPH with highest values for grain yield (GYD), grain yield of hand harvested ears (GYE), number of kernels per ear (NKE), and plant length (PLG). The GR for MPH of heterotic traits ranged from 0.66 to 0.97 and were slightly smaller than for line per se performance.
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Relationships among Distance Measures, Heterosis, and Coancestry
Correlations (r) between 1 – f and GDs based on SSRs (GDSSR) and AFLPs (GDAFLP) were highly significant (P < 0.01) and exceeded 0.85 in both flint and dent lines, with a single exception (Table 3). By comparison, r values between GDs and MDs were moderate (0.40 
r 0.68). Likewise, r values between MDEUC and MDMAH were only of moderate sizes. Correlations were consistently higher for flint lines than for dent lines. Coancestry was moderately correlated with MDEUC, but poorly correlated with MDMAH; both relationships showed a triangular form (Fig. 1).
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= 0.05 for F2–derived lines (Table 4). Assuming = 0.05 for BC1–derived lines, corresponding values of 1 – ß for BC2–derived lines were considerably higher for MDEUC and MDMAH. The power 1 – ß for thresholds determined by = ß to classify BC1– or BC2–derived progenies as EDVs increased considerably compared with the values of = 0.05. This increase in 1 – ß was associated with higher values of .
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= 0.05 between F2–derived lines (Table 4). Choosing = 0.05 for BC1–derived lines, the values of ß increased for BC2–derived lines. For = ß, the power to classify BC1– or BC2–derived progenies as EDVs increased substantially; however, this was again associated with higher values of . In general, values of and ß were of similar magnitude for MDs and MPH. |
DISCUSSION |
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Data Quality and Relatedness between Different Measures for Genetic Conformity
Despite the contrasting climatic conditions during the vegetation seasons in 2000 and 2001, high GR values were observed for morphological traits and MPH, the former being considerably higher than those reported by Rebourg et al. (2001). In addition, UPGMA cluster analysis based on MDEUC showed a clear grouping of flint and dent lines, which further corroborates the high quality of morphological data (available as supplemental data to the online version of this paper; see http://crop.scijournals.org/). However, the dendrogram based on MDMAH deviated considerably from the expectations based on pedigree data or GDs, and only moderate correlations between MDEUC and MDMAH were observed. This can be explained by the different statistical properties of MDEUC and MDMAH, because MDMAH adjusts for the correlations of traits.
The graphs between MDs and GDs (Fig. 1) confirmed the triangular relationship between morphological and GDs reported in previous studies (Dillmann et al., 1997; Rebourg et al., 2001). This indicates that low GDs correspond necessarily with low MDs, whereas the reverse does not necessarily hold true because high GDs can correspond with both high and low MDs (van Eeuwijk and Baril, 2001). In addition, the triangular shape has several biological explanations (Nuel et al., 2001) and is also expected if only molecular markers tightly linked with the genes controlling the phenotypic trait(s) were used (Burstin and Charcosset, 1997).
In the present investigation, flint and dent lines showed similar estimates of 
g2 and correlations among the various criteria, and the same applied to flint and dent triplets. This is in harmony with a previous study of Bar-Hen et al. (1995), who examined 974 maize inbred lines with morphological traits and RFLPs. Correlations of 1 – f, GDSSR, or GDAFLP, with MPH were higher than reported by Ajmone Marsan et al. (1998) for AFLPs but similar to correlations of MPH with 1 – f and GDs based on RFLPs in intrapool crosses (Boppenmaier et al., 1993; Smith et al., 1990). In addition, our study confirms the findings of Smith and Smith (1989b) that correlations of molecular markers or 1 – f are considerably higher with MPH than with MDEUC or MDMAH.
Distinctness versus Conformity
To confirm an essential derivation in the sense of the UPOV convention (UPOV, 1991), three separate criteria must be fulfilled. An EDV must (i) be distinct from the IV, (ii) be predominantly derived from the IV, and (iii) conform to it in the expression of its essential characteristics. Distinctness can be determined based on morphological traits by established procedures for DUS testing. Establishing a predominant derivation will either require a directly documented evidence, for example, by breeding books, or could be determined with molecular evidence similar to forensic approaches in the human sector (Gill et al., 1995). However, the question whether conformity in the expression of essential characteristics should be assessed by phenotypic rather than molecular data is still unsolved. While differences in the expression of one single trait are sufficient to prove distinctness between two varieties, assessment of conformity should be based on a large number of morphological traits and still could not give a definite answer due to the triangular relationship mentioned above.
Proponents of phenotypic data state that the term "conform in the expression of its essential characteristics that result from the genotype" (UPOV, 1991) implies the use of phenotypic and agronomic data rather than molecular data (Troyer and Rocheford, 2002). In contrast, opponents state that even highly heritable phenotypic traits can only offer an indirect measure of the relatedness between two cultivars (Roldan-Ruiz et al., 2000b). Molecular data provide a direct estimate of the true relatedness between two genotypes because they are unbiased by environmental effects and reflect the percentage of the genome in common between the IV and a putative EDV. On the basis of our results, GDs based on molecular markers have clear advantages for identification of EDVs.
Power of Morphological Distances and Heterosis for Identification of EDVs
For MDEUC as well as for MDMAH, extensive overlaps of the frequency distributions of F2–, BC1–, and BC2–derived progenies were found in spite of the significant correlations with 1 – f. Type I () and Type II (ß) errors observed for MDs were thus considerably higher than observed for GDs based on molecular markers (Table 4). Consequently, MDs provide only a rough estimate of the true relatedness between two lines and can only poorly discriminate F2–, BC1–, and BC2–derived progenies. These results confirm data from ryegrass (Gilliland et al., 2000) and maize (Smith and Smith, 1989b), showing that morphological conformity could give an initial indication of the relatedness between two cultivars, particularly for highly conforming pairs of inbreds. Nevertheless, a small MD between two varieties cannot be taken as a definitive proof that they are in fact closely related because of the triangular relationship between 1 – f and MDs.
In contrast to the triangular relationship between GDs and MDs, a linear relationship of MPH with GDs or 1 – f was observed, as expected by quantitative genetic theory (Melchinger, 1999). However, in spite of the higher correlation between MPH and 1 – f or GDs, MPH was not markedly superior to MDs regarding the power to discriminate between F2–, BC1– or BC2–derived progeny. This is attributable to the larger experimental error and genotype x environment interactions of MPH in comparison with line per se performance (data not shown), as reflected by the comparison of GRt vs. GRg.
For nearly all of the examined scenarios, GDs based on SSRs or AFLPs were superior to MDs or MPH for any trait or combination of traits in their power 1 – ß to discriminate among F2–, BC1–, and BC2–derived progenies for given values of . However, different from MDs and MPH, the use of SSR or AFLP markers would require thresholds specific for a given germplasm pool. This is necessary because flint and dent lines differ significantly in their mean GD between unrelated lines due to the different levels of polymorphism within each germplasm pool (Heckenberger et al., 2005). The lower T values for AFLPs compared with SSRs are due to their lower degree of polymorphism, but this has no influence on the ability to discriminate different types of progeny.
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CONCLUSIONS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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In conclusion, we strongly recommend the use of molecular markers for the identification of suspected EDVs by fingerprinting with at least 100 SSR markers or 20 AFLP PCs. If doubts still remain whether a variety is IDV or EDV, the corresponding genotypes should be fingerprinted with an additional set of SSRs or AFLPs. Use of MPH for the identification of EDVs is problematic because the rationale for using MPH is merely its linear relationship with 1 – f, and the biological mechanisms underlying heterosis are not yet fully understood.
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ACKNOWLEDGMENTS |
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Received for publication February 23, 2004.
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REFERENCES |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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and genetic ratios (GRg) observed for 58 flint and dent maize lines in four or six environments in South Germany.
, and genetic ratio of midparent heterosis (GRt) among triplets observed for different morphological and agronomic traits of 114 flint and dent hybrids and their parental lines tested in four or six environments in South Germany as well as correlations (r) of MPH with coancestry (1 – f), genetic distance based on 100 simple sequence repeats (GDSSR) or 20 amplified fragment length polymorphism primer combinations (GDAFLP), and Euclidean (MDEUC) or Mahalanobis (MDMAH) morphological distances.
