7. Length of anther 1.59 2.00 1.00 0.21 7.40 <0.0001 8. Length of the reproductive part 6.31 7.30 5.10 0.49 4.42 <0.0001 9. Number of fruits per shoot 4.84 13.00 1.00 2.32 34.44 <0.0001 10. Number of shoot per bulb 4.00 6.00 3.00 0.98 18.64 <0.0001 11. Length of shoot 60.03 96.50 38.60 18.68 7.03 <0.0001 12. Nodes per shoot 3.84 5.00 2.00 0.44 11.14 0.0240 13. Length of the internode 8.18 22.00 0 6.15 39.24 <0.0001 14. Number of branches per shoot 1.98 3.00 0.90 0.72 25.03 <0.0001 15. Length of the leaf 34.13 46.00 16.00 6.78 8.23 <0.0001 16. Width of the leaf 3.53 5.60 2.50 0.88 7.46 <0.0001 17. Length of the pseudopetiole 7.55 11.00 6.00 1.32 6.16 <0.0001 18. Floral scapus length 11.21 28.00 3.00 7.29 10.89 <0.0001 19. Floral scapus thickness 0.55 1.00 0.30 0.22 6.33 <0.0001 20. Length of the bract 11.29 24.50 8.00 3.88 16.60 <0.0001 21. Bract width 2.85 3.50 2.20 0.38 4.03 <0.0001 Table 1. Morphological characters and basic statistical data of nine varieties of *T. pavonia* (L.

For isozyme markers, two individuals of each *T. pavonia* variety were used. Leaf sections were taken from each individual eight to 12 weeks after budding initiated. All of the samples were

Approximately 50 mg of fresh leaf tissue from each sample was homogenized using a plastic chopstick in 50 μL extraction buffer Tris-HCl 0.1M, 2% EDTA-2Na, 50.4% glycerol, 3.2%

processed in the laboratory of Plant Molecular Biology at the FCAgr of the UAEM.

Tween-80, and 0.8% DTT, pH 7.5 (Arzate-Fernández et al., 2005a).

Deviation

1.92 4.00 1.00 1.23 22.72 <0.0001

1.05 2.50 0.30 0.54 20.46 <0.0001

CV (%) *P*

Character Mean Max Min Standar

**3. Methodology**

the stigma

f.) DC.

**3.2 Isozyme markers**

**3.1 Morphological markers**

individuals of each variety.

4. Type of internal tepal (oval formed, sharp pointed, lanceolated, rounded)

6. Distance from the base of the anther to

Young leaves were collected of two individuals of each variety (in the same development stage), and stored at -20 °C prior to DNA extraction. The genomic DNA was extracted of approximately 100 mg of leaf tissue of each variety of *T*. *pavonia*. The extraction procedure was the CTAB as reported by Zhou et al. (1999). The DNA samples were stored to -20 °C prior to analysis. The polymerase chain reaction (PCR) was made in a final volume of 10 µL with: 1 µL of DNA (10 ng), 1 µL of 10X PCR buffer with ammonium (15 mM), 0.5 µL of MgCl2 (15 mM), 1 µL of dNTPs (10 mM), 1 µL of the primer (20 mM) and 0.1 units of the enzyme Taq DNA polymerase.

### **3.3.1 ISSR markers**

For ISSR markers, five primers of the anchored microsatellites type were used (3'-ASSR) (Yamagishi et al*.*, 2002). In each primer, the anchor consisted of a triplicate of distinct sequence (Table 4). The amplification conditions for the primers 3'-ASSR02 and 3' -ASSR15 were those described by Arzate-Fernández et al*.* (2005b), and consisted of an initial cycle of 9 min at 94 °C, 1 min at 46 °C and 1 min at 72 °C and a final cycle of 9 min at 94 °C, 1 min at 46 °C and 10 min at 72 °C. For primers 3'-ASSR20, 3'-ASSR29 and 3'-ASSR35, the amplification cycles were those used by Yamagishi et al*.* (2002) and consisted of an initial cycle of 9 min at 94 °C, 1 min at 46 °C and 1 min at 72 °C and a final cycle of 10 min at 72 °C.

### **3.3.2 RAPD markers**

For RAPD markers, five 10 base primers (Yamagishi, 1995), five 15 base primers (Yamagishi et al., 2002), and five 20 base primers (Debener & Mattiesch, 1998) were used (Table 5). The amplification conditions for RAPD primers of 10 base were the reported by Yamagishi (1995). The program for 15 base primers used in this study was followed according to Yamagishi et al. (2002) with minor modifications (40 cycles of 94 °C for 1 min, 53 °C for 3

Marker Assisted Characterization in *Tigridia pavonia* (L.f) DC 229

The statistical analysis showed that the number of flowers per shoot and nodes per shoot were not significant. However, for the other 19 characters there were highly significant differences (p ≤ 0.0001) (Table 1). These results show the high phenotypic diversity among the varieties analyzed, and can be used for the selection of parental lines within a plant

The varieties formed two groups based on their morphological characteristics (Figure 2). Group I with average of GD = 0.42 consisted of the varieties Carolina, Trinidad, Mariana, Angeles, Sandra, Penelope and Dulce, while group II included the varieties Gloria and

The morphological characters (18 of 21 equal) showed the close genetic relationship between the varieties Trinidad and Mariana (GD = 0.28). In contrast, the least related varieties were Carolina and Samaria, as well as Penélope and Samaria (GD = 0.80), with 4 and 5 of 21

According to Vázquez-García et al. (2001), the varieties Gloria and Samaria can be easily distinguished by shoot length. In the present study, the results were similar and both varieties showed the highest values for length of shoot, length of internode, floral scapus

Fig. 2. Dendrogram of nine varieties of *T. pavonia* based on the genetic distance of Nei (1972), with the method UPGMA. The bar indicates the genetic distance among the varieties and

breeding program.

Samaria, with an average of GD= 0.32.

similar morphological characters, respectively.

length and length of the bract, as well as bract width.

the groups, calculated from morphological data.

min and 72 °C for 2 min). The PCR cycle conditions for 20 base primers were performed according to Debener & Mattiesch (1998).

The amplification of DNA fragments for ISSR and RAPD markers was made in a thermocycler (Mastercycler gradient, Eppendorf, Germany). The separation of the fragments was made in horizontal electrophoresis. A molecular marker of 100 to 3000 pb molecular weight was used. The running conditions for each sample were 100 V and 120 mA for 80 min, and the observation of the fragments was made in a transilluminator UVP.

### **3.4 Statistical analysis**

For morphological markers, the 21 morphological characters were evaluated through an analysis of variance and a completely randomized design with 14 replicates, with the statistical program SAS version 8.0. With the data generated of the morphological characters, a binary matrix was made following the criteria described by Vicente & Fulton (2003); that is, the value of 1 was assigned if the character was present and 0 if it was absent.

For isozyme markers, a record of banding patterns was constructed and each band was assigned to a binary matrix as absent, 0, or present, 1.

For ISSR and RAPD markers, each band generated by each primer was considered as an independent locus calculated manually; that is, the value of 1 was assigned for the presence of a band and 0 for its absence. The total number fragments (FT), polymorphic fragments (FP), percentage of polymorphism (%P) and the Nei' s genetic distance (GD) were calculated using the program POPGENE version 1.32 (Yeh & Boyle, 1999). Also, capacity of each primer to differentiate the nine varieties under study was evaluated through the resolution power (*Rp*), according to Prevost & Wilkinson (1999).

In RAPD markers, a simple correlation analysis was performed to investigate the correlation between the length primer and the polymorphism generated by each primer group.

In all cases (morphological, isozyme and DNA markers), to determine genetic relationships and variety grouping, a dendrogram was constructed with the data using POPGENE with the UPGMA method (modified from the NEIGHBOR procedure of PHYLIP, version 3.5) (Felsenstein, 1990) based on the Nei (1972) matrix genetic distances. UPGMA is one of the simplest and most commonly used hierarchical clustering algorithms. It receives as input a set of elements and a dissimilarity matrix which contains pairwise distances between all elements, and returns a hierarchy of clusters on this set.

### **4. Results and discussion**

### **4.1 Morphological markers**

The values of the mean, maximum, minimum, standard deviation (SD) and coefficient of variation (CV) were calculated for each one of the 21 morphological characters evaluated in the nine varieties (Table 1). According to the values of the CV, the characters number of flowers per shoot, type of internal tepal, distance from the base of the anther to the stigma, number of fruits per shoot, length of the internode and number of branches per shoot showed a slightly high variation level. In contrast, the characters that presented low variation levels among the varieties were the length of the staminal column, length of the reproductive part and bract width.

min and 72 °C for 2 min). The PCR cycle conditions for 20 base primers were performed

The amplification of DNA fragments for ISSR and RAPD markers was made in a thermocycler (Mastercycler gradient, Eppendorf, Germany). The separation of the fragments was made in horizontal electrophoresis. A molecular marker of 100 to 3000 pb molecular weight was used. The running conditions for each sample were 100 V and 120 mA for 80

For morphological markers, the 21 morphological characters were evaluated through an analysis of variance and a completely randomized design with 14 replicates, with the statistical program SAS version 8.0. With the data generated of the morphological characters, a binary matrix was made following the criteria described by Vicente & Fulton (2003); that is, the value of 1 was assigned if the character was present and 0 if it was absent. For isozyme markers, a record of banding patterns was constructed and each band was

For ISSR and RAPD markers, each band generated by each primer was considered as an independent locus calculated manually; that is, the value of 1 was assigned for the presence of a band and 0 for its absence. The total number fragments (FT), polymorphic fragments

using the program POPGENE version 1.32 (Yeh & Boyle, 1999). Also, capacity of each primer to differentiate the nine varieties under study was evaluated through the resolution

In RAPD markers, a simple correlation analysis was performed to investigate the correlation

In all cases (morphological, isozyme and DNA markers), to determine genetic relationships and variety grouping, a dendrogram was constructed with the data using POPGENE with the UPGMA method (modified from the NEIGHBOR procedure of PHYLIP, version 3.5) (Felsenstein, 1990) based on the Nei (1972) matrix genetic distances. UPGMA is one of the simplest and most commonly used hierarchical clustering algorithms. It receives as input a set of elements and a dissimilarity matrix which contains pairwise distances between all

The values of the mean, maximum, minimum, standard deviation (SD) and coefficient of variation (CV) were calculated for each one of the 21 morphological characters evaluated in the nine varieties (Table 1). According to the values of the CV, the characters number of flowers per shoot, type of internal tepal, distance from the base of the anther to the stigma, number of fruits per shoot, length of the internode and number of branches per shoot showed a slightly high variation level. In contrast, the characters that presented low variation levels among the varieties were the length of the staminal column, length of the

between the length primer and the polymorphism generated by each primer group.

s genetic distance (GD) were calculated

min, and the observation of the fragments was made in a transilluminator UVP.

according to Debener & Mattiesch (1998).

assigned to a binary matrix as absent, 0, or present, 1.

(FP), percentage of polymorphism (%P) and the Nei'

power (*Rp*), according to Prevost & Wilkinson (1999).

elements, and returns a hierarchy of clusters on this set.

**4. Results and discussion 4.1 Morphological markers**

reproductive part and bract width.

**3.4 Statistical analysis**

The statistical analysis showed that the number of flowers per shoot and nodes per shoot were not significant. However, for the other 19 characters there were highly significant differences (p ≤ 0.0001) (Table 1). These results show the high phenotypic diversity among the varieties analyzed, and can be used for the selection of parental lines within a plant breeding program.

The varieties formed two groups based on their morphological characteristics (Figure 2). Group I with average of GD = 0.42 consisted of the varieties Carolina, Trinidad, Mariana, Angeles, Sandra, Penelope and Dulce, while group II included the varieties Gloria and Samaria, with an average of GD= 0.32.

The morphological characters (18 of 21 equal) showed the close genetic relationship between the varieties Trinidad and Mariana (GD = 0.28). In contrast, the least related varieties were Carolina and Samaria, as well as Penélope and Samaria (GD = 0.80), with 4 and 5 of 21 similar morphological characters, respectively.

According to Vázquez-García et al. (2001), the varieties Gloria and Samaria can be easily distinguished by shoot length. In the present study, the results were similar and both varieties showed the highest values for length of shoot, length of internode, floral scapus length and length of the bract, as well as bract width.

Fig. 2. Dendrogram of nine varieties of *T. pavonia* based on the genetic distance of Nei (1972), with the method UPGMA. The bar indicates the genetic distance among the varieties and the groups, calculated from morphological data.

Marker Assisted Characterization in *Tigridia pavonia* (L.f) DC 231

POX produced two active bands (Figure 3F) arranged in a single pattern, and thus it was not

PGI produced four active bands (Figure 3G) and varieties with two, three or four bands arranged to produce three banding patterns were detected. Pattern 1 had four bands, and was observed in Angeles, Carolina, Dulce, Penelope, Samaria, Sandra, and Trinidad. Pattern 2 had three bands and was observed in Mariana. Pattern 3 had two bands and was observed

PHI produced three active bands (Figure 3H) and varieties with two or three active bands in three arrangement producing three banding patterns were detected. Pattern 1 had three bands and was observed in ANG, CAR, DUL, PEN, SAN, and TRI. Patterns 2 and 3 had two bands each. Varieties GLO and SAM exhibited pattern 2 and variety MAR pattern 3 (Table 2).

PGM produced four active bands (Figure 3I) and varieties with three or four bands arranged in two banding patterns were observed. Pattern 1 had four bands and was observed only in Gloria. Pattern 2 had three bands and was observed in Angeles, Carolina, Dulce, Mariana,

As can be seen in Table 2, the nine isozymes produced sufficient polymorphic bands to distinguish most of the *T. pavonia* varieties evaluated. Of all the isozymes tested, MDH produced the highest number (4) of IBP and, therefore, the highest percentage of polymorphism (18.75%). Based on the observed IBP, this isozyme allowed to differentiate a larger number of varieties. In contrast, the isozymes PGD and POX produced only one IBP,

Twenty-nine bands derived from seven isozymes were only considered: five for AAT, four for ACP, two for CAT, six for MDH, four for PGI, three for PHI, and four for PGM (Figure 3). A dendrogram (Figure 4) was generated from the genetic relationship among these bands, clustering the varieties in two main groups. Group 1 comprises seven varieties: Angeles, Sandra, Carolina, Dulce, Mariana, Penelope, and Trinidad, with an average GD of

Genetic analysis yielded an average genetic distance GD of 0.194 among the nine *T. pavonia* varieties (Table 3). As observed in Table 3, the GD between Angeles and Sandra varieties and between Carolina and Dulce was 0.0, revealing genetic similarity and, in spite of the number of isozymes tested, it was not possible to distinguish one variety from the other. In contrast, Vázquez-García et al. (2001) characterized these four varieties morphologically, differentiating them by flower color: white (Angeles), red (Sandra), pink (Carolina), and yellow (Dulce). The varieties with the highest GD value (0.421) were Gloria-Mariana, Gloria-

and therefore neither isozyme was useful for differentiating the varieties used.

0.074. Group II only includes the Gloria and Samaria varieties, with a GD of 0.374.

**4.2.6 Peroxidase**

in Gloria (Table 2).

possible to differentiate varieties (Table 2).

**4.2.7 Phosphoglucose isomerase**

**4.2.8 Phosphohexose isomerase**

**4.2.9 Phosphoglucomutase**

Penelope, and Mariana-Samaria.

Penelope, Samaria, Sandra, and Trinidad (Table 2).

### **4.2 Isozyme markers**

The nine *T. pavonia* varieties evaluated were wild and free-pollinating. Therefore, they were considered to be heterozygotic; this agrees with the diverse isozyme banding patterns (IBPs) observed. Of the 18 isozymes tested, 12 could be stained, but only nine had sufficient resolution and clarity to be recorded and studied. Some bands were omitted because of their poor resolution. The isozymes ACP, MDH, PGI, PHI and PGM had better resolution when examined with the H-AC system, pH 5.7, and the isozymes AAT and PGD in the same system, but at pH 6.5. In contrast, the isozymes CAT and POX were better in the T-C/T-H system. Of the selected isozymes, nine zimograms in which 32 bands arranged in 20 IBP were identified: two for AAT, two for ACP, two for CAT, four for MDH, one for PGD, one for POX, three for PGI, three for PHI, and two for PGM (Figure 3).

In this study most of the varieties could be identified by the IBP obtained in each isozyme, as we describe in the following sections.

### **4.2.1 Aspartate amino transferase**

AAT showed five active bands (Figure 3A) and varieties with four bands arranged in two banding patterns were detected. Pattern 1 was observed in the Angeles, Carolina, Dulce, Mariana, Penelope, and Sandra varieties, while the Gloria, Samaria, and Trinidad varieties exhibited pattern 2 (Table 2).

### **4.2.2 Acid phosphatase**

ACP revealed four active bands (Figure 3B) and varieties with one or four bands arranged in two banding patterns were detected. The Angeles, Carolina, Dulce, Gloria, Mariana, Penelope, Sandra, and Trinidad varieties exhibited pattern 1 with four bands. Pattern 2 had a single band and was seen only in the Samaria variety (Table 2).

### **4.2.3 Catalase**

CAT produced two active bands (Figure 3C) and varieties with one or two bands arranged in two banding patterns were detected. Pattern 1 with two bands was observed in Carolina, Dulce, Mariana, Penelope, and Samaria. Pattern 2 was observed in Angeles, Gloria, Sandra, and Trinidad (Table 2).

### **4.2.4 Malate dehydrogenase**

MDH showed six active bands (Figure 3D) and varieties with three or four bands in four different arrangements were detected to produce four banding patterns. Patterns 1, 2, and 3 were composed of four bands. Pattern 1 was observed in Angeles, Carolina, Dulce, Mariana, Sandra, and Trinidad, while Penelope and Gloria exhibited patterns 2 and 3. Pattern 4 had three active bands and was observed in Samaria (Table 2).

### **4.2.5 Phosphoglucose dehydrogenase**

PGD produced two active bands (Figure 3E) arranged in a single pattern, so that it was not possible to differentiate any of the varieties (Table 2).

### **4.2.6 Peroxidase**

230 Plant Breeding

The nine *T. pavonia* varieties evaluated were wild and free-pollinating. Therefore, they were considered to be heterozygotic; this agrees with the diverse isozyme banding patterns (IBPs) observed. Of the 18 isozymes tested, 12 could be stained, but only nine had sufficient resolution and clarity to be recorded and studied. Some bands were omitted because of their poor resolution. The isozymes ACP, MDH, PGI, PHI and PGM had better resolution when examined with the H-AC system, pH 5.7, and the isozymes AAT and PGD in the same system, but at pH 6.5. In contrast, the isozymes CAT and POX were better in the T-C/T-H system. Of the selected isozymes, nine zimograms in which 32 bands arranged in 20 IBP were identified: two for AAT, two for ACP, two for CAT, four for MDH, one for PGD, one

In this study most of the varieties could be identified by the IBP obtained in each isozyme,

AAT showed five active bands (Figure 3A) and varieties with four bands arranged in two banding patterns were detected. Pattern 1 was observed in the Angeles, Carolina, Dulce, Mariana, Penelope, and Sandra varieties, while the Gloria, Samaria, and Trinidad varieties

ACP revealed four active bands (Figure 3B) and varieties with one or four bands arranged in two banding patterns were detected. The Angeles, Carolina, Dulce, Gloria, Mariana, Penelope, Sandra, and Trinidad varieties exhibited pattern 1 with four bands. Pattern 2 had

CAT produced two active bands (Figure 3C) and varieties with one or two bands arranged in two banding patterns were detected. Pattern 1 with two bands was observed in Carolina, Dulce, Mariana, Penelope, and Samaria. Pattern 2 was observed in Angeles, Gloria, Sandra,

MDH showed six active bands (Figure 3D) and varieties with three or four bands in four different arrangements were detected to produce four banding patterns. Patterns 1, 2, and 3 were composed of four bands. Pattern 1 was observed in Angeles, Carolina, Dulce, Mariana, Sandra, and Trinidad, while Penelope and Gloria exhibited patterns 2 and 3. Pattern 4 had

PGD produced two active bands (Figure 3E) arranged in a single pattern, so that it was not

for POX, three for PGI, three for PHI, and two for PGM (Figure 3).

a single band and was seen only in the Samaria variety (Table 2).

three active bands and was observed in Samaria (Table 2).

possible to differentiate any of the varieties (Table 2).

**4.2.5 Phosphoglucose dehydrogenase**

as we describe in the following sections.

**4.2.1 Aspartate amino transferase**

exhibited pattern 2 (Table 2).

**4.2.2 Acid phosphatase**

**4.2.3 Catalase**

and Trinidad (Table 2).

**4.2.4 Malate dehydrogenase**

**4.2 Isozyme markers**

POX produced two active bands (Figure 3F) arranged in a single pattern, and thus it was not possible to differentiate varieties (Table 2).

### **4.2.7 Phosphoglucose isomerase**

PGI produced four active bands (Figure 3G) and varieties with two, three or four bands arranged to produce three banding patterns were detected. Pattern 1 had four bands, and was observed in Angeles, Carolina, Dulce, Penelope, Samaria, Sandra, and Trinidad. Pattern 2 had three bands and was observed in Mariana. Pattern 3 had two bands and was observed in Gloria (Table 2).

### **4.2.8 Phosphohexose isomerase**

PHI produced three active bands (Figure 3H) and varieties with two or three active bands in three arrangement producing three banding patterns were detected. Pattern 1 had three bands and was observed in ANG, CAR, DUL, PEN, SAN, and TRI. Patterns 2 and 3 had two bands each. Varieties GLO and SAM exhibited pattern 2 and variety MAR pattern 3 (Table 2).

### **4.2.9 Phosphoglucomutase**

PGM produced four active bands (Figure 3I) and varieties with three or four bands arranged in two banding patterns were observed. Pattern 1 had four bands and was observed only in Gloria. Pattern 2 had three bands and was observed in Angeles, Carolina, Dulce, Mariana, Penelope, Samaria, Sandra, and Trinidad (Table 2).

As can be seen in Table 2, the nine isozymes produced sufficient polymorphic bands to distinguish most of the *T. pavonia* varieties evaluated. Of all the isozymes tested, MDH produced the highest number (4) of IBP and, therefore, the highest percentage of polymorphism (18.75%). Based on the observed IBP, this isozyme allowed to differentiate a larger number of varieties. In contrast, the isozymes PGD and POX produced only one IBP, and therefore neither isozyme was useful for differentiating the varieties used.

Twenty-nine bands derived from seven isozymes were only considered: five for AAT, four for ACP, two for CAT, six for MDH, four for PGI, three for PHI, and four for PGM (Figure 3). A dendrogram (Figure 4) was generated from the genetic relationship among these bands, clustering the varieties in two main groups. Group 1 comprises seven varieties: Angeles, Sandra, Carolina, Dulce, Mariana, Penelope, and Trinidad, with an average GD of 0.074. Group II only includes the Gloria and Samaria varieties, with a GD of 0.374.

Genetic analysis yielded an average genetic distance GD of 0.194 among the nine *T. pavonia* varieties (Table 3). As observed in Table 3, the GD between Angeles and Sandra varieties and between Carolina and Dulce was 0.0, revealing genetic similarity and, in spite of the number of isozymes tested, it was not possible to distinguish one variety from the other. In contrast, Vázquez-García et al. (2001) characterized these four varieties morphologically, differentiating them by flower color: white (Angeles), red (Sandra), pink (Carolina), and yellow (Dulce). The varieties with the highest GD value (0.421) were Gloria-Mariana, Gloria-Penelope, and Mariana-Samaria.

 Isozyme characterization of nine *T. pavonia* (L.f.) DC. varieties using nine isozyme systems. The number indicates the isozyme banding pattern (IBP) of each variety. AAT, aspartate amino transferase; ACP, acid phosphatase; CAT, catalase; MDH, malate dehydrogenase; PGD, phosphoglucose dehydrogenase; PGI, phosphoglucose isomerase; PGM, phosphoglucomutase; PHI, phoshohexose isomerase; POX, peroxidase. 1, 2 varieties with the same number can not be distinguished with the evaluated isozymes. § It was not

Fig. 4. Dendrogram of nine varieties of *Tigridia pavonia* based on Nei (1972) genetic distance, UPGMA method. The bar indicates the genetic distance among the varieties and the groups

AAT ACP CAT MDH PGD POX PGI PHI PGM

Variety Isozyme and pattern

possible determinate the IBP.

obtained with isozyme markers.

Fig. 3. Schematic representation of isozyme banding patterns (IBP) detected in nine *T*. *pavonia* (L.f.) DC. varieties, produced by A) AAT; B) ACP; C) CAT; D) MDH; E) PGD; F) POX; G) PGI; H) PHI; I) PGM. (m=monomer, d=dimer, t=trimer. "o" represents origin of electrophoresis.

Fig. 3. Schematic representation of isozyme banding patterns (IBP) detected in nine *T*. *pavonia* (L.f.) DC. varieties, produced by A) AAT; B) ACP; C) CAT; D) MDH; E) PGD; F) POX; G) PGI; H) PHI; I) PGM. (m=monomer, d=dimer, t=trimer. "o" represents origin of

electrophoresis.

Table 2. Isozyme characterization of nine *T. pavonia* (L.f.) DC. varieties using nine isozyme systems. The number indicates the isozyme banding pattern (IBP) of each variety. AAT, aspartate amino transferase; ACP, acid phosphatase; CAT, catalase; MDH, malate dehydrogenase; PGD, phosphoglucose dehydrogenase; PGI, phosphoglucose isomerase; PGM, phosphoglucomutase; PHI, phoshohexose isomerase; POX, peroxidase. 1, 2 varieties with the same number can not be distinguished with the evaluated isozymes. § It was not possible determinate the IBP.

Fig. 4. Dendrogram of nine varieties of *Tigridia pavonia* based on Nei (1972) genetic distance, UPGMA method. The bar indicates the genetic distance among the varieties and the groups obtained with isozyme markers.

Marker Assisted Characterization in *Tigridia pavonia* (L.f) DC 235

Prevost & Wilkinson (1999) described the resolution power (*Rp*) as a useful tool for evaluating the capacity of a primer in the distinction of various genotypes. In our results, the highest values of *Rp* were for the primers ASSR02 and ASSR35 (Table 4), with which the nine varieties were distinguished from each other. Escandón et al*.* (2005a) obtained similar results with just two ASSR primers and generated specific profiles for 18 of 21 collections of *Jacaranda mimosifolia*. The efficiency of the ASSR primers for discriminating genotypes in the inter-varietal level has also been reported in *Solanum tuberosum* (Prevost & Wilkinson, 1999), *Jacaranda mimosifolia* (Pérez de la Torre et al*.*, 2003), *Nierembergia linaeriefolia* (Escandón et al*.*,

The dendrogram generated with the ISSR data (Figure 5) formed two groups of varieties: group I included Carolina, Ángeles, Trinidad, Sandra, Dulce, Mariana and Penélope with an average GD = 0.19 whereas the group II included Gloria and Samaria with a GD = 0.39. The highest genetic association (GD = 0.07) was found between the varieties Carolina and

Fig. 5. Dendrogram of nine varieties of *T. pavonia* based on the genetic distance of Nei (1972), with the method UPGMA. The bar indicates the genetic distance among the varieties and

In the present study, PCR amplification with 10, 15 and 20 length base RAPD primers led to reproducible fragment patterns for all varieties of *T*. *pavonia* evaluated. The majority of those RAPD fragments ranged from 250 to 2800 bp (Figure 6). For 10 base primers, the average of

the groups, calculated from ISSR data.

**4.3.2 RAPD markers**

2005b) and *Ficus carica* (Guasmi et al*.*, 2006), among others.

Ángeles, while the least related were Gloria and Dulce (GD = 0.91).

Table 3. Estimation of genetic distance (GD), according to the formula of Nei (1972), for the nine varieties of *T. pavonia*.

### **4.3 DNA markers**

### **4.3.1 ISSR markers**

The total number of fragments reproducible with the five ASSR primers was 40, with an interval of 350 to 1900 pb in the size of the amplified fragments. Of the 40 fragments, 35 were polymorphic, with an average of seven per primer. The percentage of polymorphic fragments varied from 66.6 to 100%, with an average of 87.5% (Table 4). These results are similar with those reported by Yamagishi et al*.* (2002) and Arzate-Fernández et al*.* (2005b), who used these ASSR primers and proved their efficiency for detecting high polymorphism percentage in different species of the genus *Lilium.*

One aspect that favors the effectiveness of the ASSR primers as well as the type of the motive replicate in its sequence, is the sequence of its anchor. The CT motive sequences produce higher polymorphism with respect to the AT replicates (Pradeep et al*.*, 2002; Hu et al*.*, 2003), which despite being the most abundant in the plant genomes, have the disadvantage that the amplification of DNA fragments is low; this may be due to the semicomplementarity of the primer in the alignment stage of the PCR (Fang & Roose, 1997). In this study, the level of distinction among the variables depended on the sequence of the anchor of the primer. Thus, it was possible to obtain 100% polymorphism among the varieties of *T. pavonia* with primers ASSR02 and ASSR35 (Table 4).

Table 4. Characteristics of the ISSR fragments amplified in nine varieties of *T. pavonia* (L.f.) DC.: total amplified fragments (AF), polymorphic fragments (PF), percentage of polymorphism (%P), resolving power (*Rp*) and size of the amplified fragments (FS) for each ASSR primer.

Variety ANG CAR DUL GLO MAR PEN SAM SAN

ANG

CAR 0.031

DUL 0.031 0.000

nine varieties of *T. pavonia*.

**4.3 DNA markers 4.3.1 ISSR markers**

ASSR primer.

GLO 0.287 0.330 0.330

MAR 0.098 0.064 0.064 0.421

percentage in different species of the genus *Lilium.*

varieties of *T. pavonia* with primers ASSR02 and ASSR35 (Table 4).

PEN 0.098 0.064 0.064 0.421 0.133

SAM 0.374 0.330 0.330 0.374 0.421 0.246

SAN 0.000 0.031 0.031 0.287 0.098 0.098 0.374

TRI 0.064 0.098 0.098 0.207 0.169 0.169 0.287 0.064 Table 3. Estimation of genetic distance (GD), according to the formula of Nei (1972), for the

The total number of fragments reproducible with the five ASSR primers was 40, with an interval of 350 to 1900 pb in the size of the amplified fragments. Of the 40 fragments, 35 were polymorphic, with an average of seven per primer. The percentage of polymorphic fragments varied from 66.6 to 100%, with an average of 87.5% (Table 4). These results are similar with those reported by Yamagishi et al*.* (2002) and Arzate-Fernández et al*.* (2005b), who used these ASSR primers and proved their efficiency for detecting high polymorphism

One aspect that favors the effectiveness of the ASSR primers as well as the type of the motive replicate in its sequence, is the sequence of its anchor. The CT motive sequences produce higher polymorphism with respect to the AT replicates (Pradeep et al*.*, 2002; Hu et al*.*, 2003), which despite being the most abundant in the plant genomes, have the disadvantage that the amplification of DNA fragments is low; this may be due to the semicomplementarity of the primer in the alignment stage of the PCR (Fang & Roose, 1997). In this study, the level of distinction among the variables depended on the sequence of the anchor of the primer. Thus, it was possible to obtain 100% polymorphism among the

Primer Sequence (5'-3') AF PF %P *Rp* FS (pb) 3´-ASSR02 CTCTCTCTCTCTCT ATC 9 9 100 3.12 500-1300 3´-ASSR15 CTCTCTCTCTCTCT ATG 8 6 85.7 2.2 350-1200 3´-ASSR20 CTCTCTCTCTCTCT GCA 7 6 85.7 2.2 600-1800 3´-ASSR29 CTCTCTCTCTCTCT GTA 6 4 66.6 1.8 550-1400 3´-ASSR35 CTCTCTCTCTCTCT TGA 10 10 100 5.54 350-1900 Total or mean 40 35 87.5 1.97 450 Table 4. Characteristics of the ISSR fragments amplified in nine varieties of *T. pavonia* (L.f.)

polymorphism (%P), resolving power (*Rp*) and size of the amplified fragments (FS) for each

DC.: total amplified fragments (AF), polymorphic fragments (PF), percentage of

Prevost & Wilkinson (1999) described the resolution power (*Rp*) as a useful tool for evaluating the capacity of a primer in the distinction of various genotypes. In our results, the highest values of *Rp* were for the primers ASSR02 and ASSR35 (Table 4), with which the nine varieties were distinguished from each other. Escandón et al*.* (2005a) obtained similar results with just two ASSR primers and generated specific profiles for 18 of 21 collections of *Jacaranda mimosifolia*. The efficiency of the ASSR primers for discriminating genotypes in the inter-varietal level has also been reported in *Solanum tuberosum* (Prevost & Wilkinson, 1999), *Jacaranda mimosifolia* (Pérez de la Torre et al*.*, 2003), *Nierembergia linaeriefolia* (Escandón et al*.*, 2005b) and *Ficus carica* (Guasmi et al*.*, 2006), among others.

The dendrogram generated with the ISSR data (Figure 5) formed two groups of varieties: group I included Carolina, Ángeles, Trinidad, Sandra, Dulce, Mariana and Penélope with an average GD = 0.19 whereas the group II included Gloria and Samaria with a GD = 0.39. The highest genetic association (GD = 0.07) was found between the varieties Carolina and Ángeles, while the least related were Gloria and Dulce (GD = 0.91).

Fig. 5. Dendrogram of nine varieties of *T. pavonia* based on the genetic distance of Nei (1972), with the method UPGMA. The bar indicates the genetic distance among the varieties and the groups, calculated from ISSR data.

### **4.3.2 RAPD markers**

In the present study, PCR amplification with 10, 15 and 20 length base RAPD primers led to reproducible fragment patterns for all varieties of *T*. *pavonia* evaluated. The majority of those RAPD fragments ranged from 250 to 2800 bp (Figure 6). For 10 base primers, the average of

Marker Assisted Characterization in *Tigridia pavonia* (L.f) DC 237

**(a)**

**(b)**

**(c)**

Fig. 6. RAPD profiles of nine varieties of *T*. *pavonia* generated by the 10 base primer Y38 (a),

15 base primer P647 (b) and 20 base primer P497 (c).

total and the polymorphic fragments generated per primer were 8.8 and 8.2, respectively, whereas for 15 base primers, those values were 11 and 10.4, respectively, and for 20 base primers, 9.4 and 9, respectively (Table 5).

Generally, in RAPD analysis 10 base primers are preferred, nevertheless, because of the high annealing temperature applied in PCR reaction than their original, some 10 base primers could not hybridize with template DNA, generating only a few minor bands or none (Yamagishi et al., 2002), while the advantage of long primers is the smaller number of fragments containing repetitive DNA, thereby increasing the specificity and reproducibility of DNA fragments (Debener & Mattiesch, 1998). In the present study, the positive correlation (r = 0.99; p ≤ 0.05) between primer length and the percentage of polymorphism generated per each primer was observed, indicating that the efficiency of primers to generate polymorphic fragments it increased by primer length. Thus, 15 or 20 base primers generated more DNA fragments (55), and a greater number of polymorphic fragments (52), in comparison with those obtained by the 10 base primers (44, and 41, respectively) (Table 5). The high efficiency of long primers to generate a large number of RAPD markers has been also reported in other species as *Lilium* spp. (Yamagishi et al., 2002), *Vitis vinifera* (Solouki et al., 2007) and *Matricaria chamomilla* (Solouki et al., 2008).

Table 5. Percentage of GC (%GC), total amplified fragments (AF), polymorphic fragments (PF), percentage of polymorphism (%P) and resolving power (*Rp*) for each RAPD primer used. \*10 base (Yamagishi, 1995). \*\*15 base (Yamagishi et al., 2002). \*\*\*20 base (Debener & Mattiesch 1998).

total and the polymorphic fragments generated per primer were 8.8 and 8.2, respectively, whereas for 15 base primers, those values were 11 and 10.4, respectively, and for 20 base

Generally, in RAPD analysis 10 base primers are preferred, nevertheless, because of the high annealing temperature applied in PCR reaction than their original, some 10 base primers could not hybridize with template DNA, generating only a few minor bands or none (Yamagishi et al., 2002), while the advantage of long primers is the smaller number of fragments containing repetitive DNA, thereby increasing the specificity and reproducibility of DNA fragments (Debener & Mattiesch, 1998). In the present study, the positive correlation (r = 0.99; p ≤ 0.05) between primer length and the percentage of polymorphism generated per each primer was observed, indicating that the efficiency of primers to generate polymorphic fragments it increased by primer length. Thus, 15 or 20 base primers generated more DNA fragments (55), and a greater number of polymorphic fragments (52), in comparison with those obtained by the 10 base primers (44, and 41, respectively) (Table 5). The high efficiency of long primers to generate a large number of RAPD markers has been also reported in other species as *Lilium* spp. (Yamagishi et al., 2002), *Vitis vinifera*

Primer %GC AF PF %P *Rp*  Y24\* 70 8 6 75 1.6 Y29\* 70 10 10 100 5.1 Y37\* 70 3 2 66.6 0.9 Y38\* 70 15 15 100 7.5 Y41\* 80 8 8 100 3.3 Average 72 8.8 8.2 93.1 3.6 P619\*\* 66 13 13 100 5.8 P625\*\* 66 8 6 75 2.6 P628\*\* 60 4 3 75 1.3 P635\*\* 73 17 17 100 8.9 P647\*\* 60 13 13 100 6.4 Average 65 11 10.4 94.5 5 P495\*\*\* 60 11 10 90.9 3.9 P496\*\*\* 60 6 5 83.3 2.6 P497\*\*\* 60 8 8 100 3.8 P498\*\*\* 60 12 12 100 4.9 P500\*\*\* 60 10 10 100 3.8 Average 60 9.4 9 95.7 3.8 Table 5. Percentage of GC (%GC), total amplified fragments (AF), polymorphic fragments (PF), percentage of polymorphism (%P) and resolving power (*Rp*) for each RAPD primer used. \*10 base (Yamagishi, 1995). \*\*15 base (Yamagishi et al., 2002). \*\*\*20 base (Debener &

(Solouki et al., 2007) and *Matricaria chamomilla* (Solouki et al., 2008).

primers, 9.4 and 9, respectively (Table 5).

Mattiesch 1998).

Fig. 6. RAPD profiles of nine varieties of *T*. *pavonia* generated by the 10 base primer Y38 (a), 15 base primer P647 (b) and 20 base primer P497 (c).

Marker Assisted Characterization in *Tigridia pavonia* (L.f) DC 239

Fig. 7. Dendogram generated using UPGMA analysis, showing relationships between nine varieties of *T*. *pavonia*, based on RAPD data of 10 (a), 15 (b), 20 (c) and the pooled (10, 15 and 20) base of length primer (d). The bar indicates the genetic distance among the varieties and

the groups.

Although it is no clear exactly why the long primers produced more polymorphic bands, it has been reported that the GC content may be a factor that determine the efficiency of a primer (Solouki et al., 2007), since GC content is associated with annealing temperature and related to generation of more DNA fragments. Thus, it has been observed that with long primers with a lower GC content, the efficiency for amplifying polymorphic bands is higher, in comparison with short primers with a higher GC content (Ye et al., 1996; Solouki et al., 2007). According to this, it is possible that the GC content has favored the major efficiency of the 15 (65 % GC) and 20 (60 % GC) base primers used in the present study, because more DNA fragments were amplified and also a greater percentage of polymorphism, in comparison with those amplified with 10 base primers with 72 % GC content (Table 5). Our results are closely similar with those reported by Solouki et al., (2008) where it were obtained more DNA fragments and 100 % of polymorphism, using a long primer with low GC content.

The high efficiency of long primers in the genetic differentiation of *T*. *pavonia* varieties was also confirmed with the measurement of resolving power. The highest values of *Rp* belonged to the 15 and 20 base primers (5 and 3.8, respectively) (Table 5), indicating a better distinction of the varieties. So, these results also confirm the utility of the *Rp* as measure of capacity of a primer to discriminate among closely related individuals as was pointed out by Prevost &Wilkinson (1999) and Escandón et al. (2007).

The dendrograms based on UPGMA analysis of the 10, 15, 20 and the pooled (10, 15 and 20) RAPD data showed the genetic differentiation of the nine varieties of *T*. *pavonia* (Figure 7). In the dendrogram generated with decamers, the GD among the varieties ranged from 0.20 to 0.69, with an average of 0.24. For the 15 base dendrogram, the GD ranged from 0.13 to 0.78, with an average of 0.32, while the dendrogram of the 20 base showed a range of GD of 0.11 to 0.67, with an average of 0.28, and finally the dendrogram with pooled data showed a range of GD of 0.20 to 0.68, with an average of 0.24.

All four dendrograms clearly grouped the varieties in two major clusters. In the dendrograms of 10 and 15 bases, and in the pooled, the cluster I consisted of the varieties Carolina, Dulce, Trinidad, Penelope, Angeles, Mariana, and Sandra, whereas the cluster II grouped the varieties Gloria and Samaria. The close relationship observed in these dendrograms, among the varieties collected in Tenancingo and Temascaltepec municipalities, might be the result of having some common morphological characters such as: number of shoots by bulb, number of nodes by shoot, length of leaf, and number flowers by shoot. The separation of Gloria and Samaria collected in Temoaya, could be due to the highest values for length of shoot, length of internode, and length of floral escape, besides that the flowering of these varieties is delayed in comparison with the rest of them, as it was reported in our previous study (Piña-Escutia et al., 2010).

On the other hand, the dendrogram developed with 20 base primers also grouped the cluster I similar to the dendrograms generated with other primers sets, except for the variety Sandra, which was grouped with the varieties Gloria and Samaria in the cluster II. Thus, this dendrogram showed a best differentiation of the varieties evaluated, confirming the utility of long primers in generation high polymorphism and genetic discrimination of plant species, which was also reported by Solouki et al. (2007), and Solouki et al. (2008).

Although it is no clear exactly why the long primers produced more polymorphic bands, it has been reported that the GC content may be a factor that determine the efficiency of a primer (Solouki et al., 2007), since GC content is associated with annealing temperature and related to generation of more DNA fragments. Thus, it has been observed that with long primers with a lower GC content, the efficiency for amplifying polymorphic bands is higher, in comparison with short primers with a higher GC content (Ye et al., 1996; Solouki et al., 2007). According to this, it is possible that the GC content has favored the major efficiency of the 15 (65 % GC) and 20 (60 % GC) base primers used in the present study, because more DNA fragments were amplified and also a greater percentage of polymorphism, in comparison with those amplified with 10 base primers with 72 % GC content (Table 5). Our results are closely similar with those reported by Solouki et al., (2008) where it were obtained more DNA fragments and 100 % of polymorphism, using a long primer with low

The high efficiency of long primers in the genetic differentiation of *T*. *pavonia* varieties was also confirmed with the measurement of resolving power. The highest values of *Rp* belonged to the 15 and 20 base primers (5 and 3.8, respectively) (Table 5), indicating a better distinction of the varieties. So, these results also confirm the utility of the *Rp* as measure of capacity of a primer to discriminate among closely related individuals as was pointed out by

The dendrograms based on UPGMA analysis of the 10, 15, 20 and the pooled (10, 15 and 20) RAPD data showed the genetic differentiation of the nine varieties of *T*. *pavonia* (Figure 7). In the dendrogram generated with decamers, the GD among the varieties ranged from 0.20 to 0.69, with an average of 0.24. For the 15 base dendrogram, the GD ranged from 0.13 to 0.78, with an average of 0.32, while the dendrogram of the 20 base showed a range of GD of 0.11 to 0.67, with an average of 0.28, and finally the dendrogram with pooled data showed a

All four dendrograms clearly grouped the varieties in two major clusters. In the dendrograms of 10 and 15 bases, and in the pooled, the cluster I consisted of the varieties Carolina, Dulce, Trinidad, Penelope, Angeles, Mariana, and Sandra, whereas the cluster II grouped the varieties Gloria and Samaria. The close relationship observed in these dendrograms, among the varieties collected in Tenancingo and Temascaltepec municipalities, might be the result of having some common morphological characters such as: number of shoots by bulb, number of nodes by shoot, length of leaf, and number flowers by shoot. The separation of Gloria and Samaria collected in Temoaya, could be due to the highest values for length of shoot, length of internode, and length of floral escape, besides that the flowering of these varieties is delayed in comparison with the rest of them, as it was

On the other hand, the dendrogram developed with 20 base primers also grouped the cluster I similar to the dendrograms generated with other primers sets, except for the variety Sandra, which was grouped with the varieties Gloria and Samaria in the cluster II. Thus, this dendrogram showed a best differentiation of the varieties evaluated, confirming the utility of long primers in generation high polymorphism and genetic discrimination of plant

species, which was also reported by Solouki et al. (2007), and Solouki et al. (2008).

Prevost &Wilkinson (1999) and Escandón et al. (2007).

range of GD of 0.20 to 0.68, with an average of 0.24.

reported in our previous study (Piña-Escutia et al., 2010).

GC content.

Fig. 7. Dendogram generated using UPGMA analysis, showing relationships between nine varieties of *T*. *pavonia*, based on RAPD data of 10 (a), 15 (b), 20 (c) and the pooled (10, 15 and 20) base of length primer (d). The bar indicates the genetic distance among the varieties and the groups.

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The assessment of genetic variability of Mexican native species is fundamental for the conservation, and plant variety protection. In this review we have conducting the morphological analysis in combination with the molecular assays to distinguish *T*. *pavonia* varieties. The analyses of the morphological and DNA markers (ISSR and RAPD) seem to be more efficient than the isozymes, because whereas the former showed polymorphism among the nine varieties evaluated and permit the distinction among them, the biochemical characterization revealed that the varieties Angeles and Sandra as well as Carolina and Dulce were the same, indicating the low discrimination power of isozymes which can be due to inadequate genome coverage. So, our results indicate that the marker assisted characterization can be applied to complement existing conventional breeding programmes and, despite its application in genetic improvement of horticultural crops is limited, their use as balance between molecular and non-molecular methods can offers opportunities of improved phenotypic selection in the future.

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We are grateful to RED TIGRIDIA (SINAREFI, México) for covering the publishing payment.

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markers system in accessing genetic variation of rice bean (*Vigna umbellate*) landraces. *Electronic Journal of Biotechnology* Vol.11, No.3, (July 2008), pp. 1-10. ISSN 0717-3458 Available from

a punto de la técnica de microsatélites anclados para la caracterización de individuos selectos de jacaranda. En: Mascarini, L., F. Vilella., and E. WRIGHT, (eds). *Floricultura en la Argentina*. Investigación y Tecnología de Producción. 3-12. Piña-Escutia, J.L.; Vences-Contreras, C.; Gutiérrez-Martínez, M.G.; Vázquez-García, L.M. &

Arzate-Fernández, A.M. (2010). Morphological and molecular characterization of nine botanical varieties of *Tigridia pavonia* (L.f.) DC. *Agrociencia* Vol.44, No.2, (Febrero-Marzo 2010), pp. 147-158. ISSN 1405-3195 Available from

polymorphism and its application in plant breeding. *Euphytica* Vol.128, No.1,

ISSR fingerprint of potato cultivars. *Theoretical and Applied Genetics* Vol.98, No.1

(2007). Polymorphism of some native sistan grapes assesed by long and short primers for RAPD markers. *Pakistan Journal of Biological Sciences* Vol. 10, No.12, (August 2007), pp. 1996-2001. ISSN 1028-8880 Available from

diversity in chamomile (*Matricaria chamomilla*) based on morphological traits and molecular markers. *Scientia Horticulturae* Vol.117, No. 3, (July 2008), pp. 281–287.

procedures for starch gel electrophoresis of enzymes from maize (*Zea mays* L.) Tech. Bull. 286. North Carolina State University. Raleigh, North Carolina. 217. Tanksley, S.D. & Rick, C.M. (1980). Isozyme gene linkage map of the tomato: applications in

genetics and breeding. *Theoretical and Applied Genetics* Vol.58, no.2 (March 1980), pp.

**Part 4**

**Breeding For Pest and Disease Resistance**

## **Part 4**

### **Breeding For Pest and Disease Resistance**

244 Plant Breeding

Young, N.D. (1999). A cautiously optimistic vision for marker assisted breeding. *Molecular*

Zhou, Z.; Miwa, M. & Hogetsu, T. (1999). Analysis of genetic structure of a *Suillus grevillei*

population in a Laris kaemferi stand by polymorphism of inter-simple sequence repeat (ISSR). *New Phytologist* Vol.144, No.1, (October 1999), pp. 55-63. ISSN 1469- 8137 Available from http://onlinelibrary.wiley.com/doi/10.1046/j.1469-

*Breeding* Vol.5, No.6, (December 1999), pp. 505-510. ISSN 1572-9788

8137.1999.00504.x/pdf

**11**

*1,3Portugal 2Spain*

**Olive –** *Colletotrichum acutatum***:**

Henrique Guedes-Pinto1 and Paula Martins-Lopes1

*University of Trás-os-Montes and Alto Douro (IBB/CGB-UTAD),*

<sup>3</sup>*National Station of Plant Breeding, Department of Oliviculture,*

Sónia Gomes1, Pilar Prieto2, Teresa Carvalho3,

**An Example of Fruit-Fungal Interaction**

<sup>1</sup>*Institute of Biotechnology and Bioengineering, Centre of Genomics and Biotechnology -*

Plants are continuously exposed to an extensive array of environmental biotic and abiotic stresses. Among the first ones, viruses, bacteria, fungi, nematodes and insects are the causal agents of the most serious plant diseases. In some cases the interactions between host and pathogen result in the loss of agricultural yield that is often linked to product quality decrease (Bhadauria et al., 2010; Bray et al., 2000; Montesano et al., 2003; Zipfel, 2008). The best and most effective approach for increasing crop yield is to enhance the production efficiency and to reduce agricultural yield losses due to various plant diseases and several other stress factors. However, plants are under strong evolutionary pressure to maintain surveillance against pathogens. Part of this success is because plants have evolved a variety of sophisticated responses that recognise compounds produced and/or are released by the pathogens (elicitors) and employ these, to trigger defence signalling, normally designated by innate immunity (Montesano et al., 2003; Parker, 2009; Zipfel, 2008). Moreover, to grow in their natural environment, some crop genotypes naturally defend themselves against pathogen infection through the development of a series of morphological, physiological and molecular changes, which are all controlled by functional genomic networks. For instance, the interaction between fungal cell wall and plant surface is the beginning of compatible interaction establishment. Plant cuticle is the region where fungal infection structures differentiated, and the plant/fruit invasion is initiated. The molecular recognition of fungal cell wall may cause stress reactions and activate host's defence mechanisms. Pathogen stresses are one of the most significant damaging factors that limit the development and consequently, decrease the yield and quality of many crops. Understanding the pathogen infection mechanisms is crucial in an integrated analysis in order to target specialized functions as signalling, defence responses, and cell death, among others. Nowadays, the use of model plants may help to target candidate genes in other crop species, decreasing, therefore, the amount of work required in unknown genomes. This chapter is a review of the state-of-the-art concerning plant-pathogen interaction focused on: (i) plant defence

**1. Introduction**

<sup>2</sup>*Department of Mejora Genética Vegetal, Instituto de Agricultura Sostenible (CSIC),*

### **Olive –** *Colletotrichum acutatum***: An Example of Fruit-Fungal Interaction**

Sónia Gomes1, Pilar Prieto2, Teresa Carvalho3,

Henrique Guedes-Pinto1 and Paula Martins-Lopes1

<sup>1</sup>*Institute of Biotechnology and Bioengineering, Centre of Genomics and Biotechnology - University of Trás-os-Montes and Alto Douro (IBB/CGB-UTAD),*  <sup>2</sup>*Department of Mejora Genética Vegetal, Instituto de Agricultura Sostenible (CSIC),*  <sup>3</sup>*National Station of Plant Breeding, Department of Oliviculture, 1,3Portugal 2Spain*

### **1. Introduction**

Plants are continuously exposed to an extensive array of environmental biotic and abiotic stresses. Among the first ones, viruses, bacteria, fungi, nematodes and insects are the causal agents of the most serious plant diseases. In some cases the interactions between host and pathogen result in the loss of agricultural yield that is often linked to product quality decrease (Bhadauria et al., 2010; Bray et al., 2000; Montesano et al., 2003; Zipfel, 2008). The best and most effective approach for increasing crop yield is to enhance the production efficiency and to reduce agricultural yield losses due to various plant diseases and several other stress factors. However, plants are under strong evolutionary pressure to maintain surveillance against pathogens. Part of this success is because plants have evolved a variety of sophisticated responses that recognise compounds produced and/or are released by the pathogens (elicitors) and employ these, to trigger defence signalling, normally designated by innate immunity (Montesano et al., 2003; Parker, 2009; Zipfel, 2008). Moreover, to grow in their natural environment, some crop genotypes naturally defend themselves against pathogen infection through the development of a series of morphological, physiological and molecular changes, which are all controlled by functional genomic networks. For instance, the interaction between fungal cell wall and plant surface is the beginning of compatible interaction establishment. Plant cuticle is the region where fungal infection structures differentiated, and the plant/fruit invasion is initiated. The molecular recognition of fungal cell wall may cause stress reactions and activate host's defence mechanisms. Pathogen stresses are one of the most significant damaging factors that limit the development and consequently, decrease the yield and quality of many crops. Understanding the pathogen infection mechanisms is crucial in an integrated analysis in order to target specialized functions as signalling, defence responses, and cell death, among others. Nowadays, the use of model plants may help to target candidate genes in other crop species, decreasing, therefore, the amount of work required in unknown genomes. This chapter is a review of the state-of-the-art concerning plant-pathogen interaction focused on: (i) plant defence

Olive – Colletotrichum acutatum: An Example of Fruit-Fungal Interaction 249

2005; Zhang et al., 2006). For instance, cDNA from strawberry differently expressed upon challenge with the pathogen *Colletotrichum acutatum* has recently been isolated, and showed similarity to (*At* WRKY75) defence genes in *Arabidopsis thaliana* (Casado-Díaz et al., 2006; Encinas-Villarejo et al., 2009). With the development of high-throughput sequencing technologies, the number of genomes sequenced has been increasing fast. The O*ryza sativa*  L., *Triticum aestivum* L., *Zea mays* L., *Vitis vinifera* L., *Glycine max* L., and *Fragaria vesca* L. genome sequencing have been extremely successful in the discovery of new genes. Similarly to plants, the knowledge of the pathogens genome is very important to monitor global changes that occur during plant-fungal interactions. Several fungal genomes have been now sequenced, being some of them extremely important in terms of yield lost in key crops such as *Botrytis cinerea* (grape grey mould, and other host species), *Fusarium graminearum* (cereal head blight), *Fusarium verticillioides* (corn seed rot), *Magnaporthe oryzae* (rice blast), *Mycosphaerella fijiensis* (banana black leaf streak), *Septoria tritici* (wheat leaf blotch), *Puccinia graminis* (cereal rust), *Phytophthora ramorum* (sudden oak death) and *Phytophthora sojae*

Disease resistance in plant-pathogen interactions requires sensitive and specific recognition mechanisms for pathogen-derived signals in plants. Plants lack mobile defender cells (like animal antibodies) and a somatically adaptive immune system (Jones & Dangl, 2006; Palma et al., 2009). However, they are equipped, at least, by two levels of defence: a *pre-invasive*, which is expressed at the cell wall and apoplastic spaces level aiming to prevent pathogens penetration, and a *post-invasive*, which mediates resistance relatively to pathogen that have successfully penetrated plant cells, and often results in a localized cell death at the infection

The physical barriers are the first level of a general plant defence against pathogens invasion, and include waxy cuticular skin layers, the plants' cell wall and actin cytoskeleton that play a key role in penetration resistance (Dangl & Jones, 2001; Kobayashi & Kobayashi, 2007). The plants' cell wall is one of the sites where the changes, due to the defence response, can be observed. These can include cell-wall thickening and lignification, papilla formation, phenolic compounds accumulation, phytoalexins and other secondary metabolites, as well transcriptional activation of pathogenesis-related proteins (Anand et al., 2009; Bhadauria et al., 2010; Montesano et al., 2003; Salazar et al., 2007; Shan & Goodwin, 2005; Zipfel, 2008). The papilla structures were observed on blueberry fruits inoculated with *Colletotrichum acutatum,* and it was formed beneath subcuticular hyphae and represented one of the host defence responses (Wharton & Schilder, 2008). If passive defences, such as the cell wall, is overcome by the pathogen, active defence responses are triggered a long lasting systemic response (systemic acquired resistance, SAR) which confers to the plant

resistance against a broad spectrum of pathogens (Thordal-Christensen, 2003).

Primary or basal immune defence response is induced by perception of molecules called pathogen-associated molecular patterns (PAMPs or MAMPs) (Dangl & Jones, 2001; Jeong et al., 2009). The pathogen-associated molecular patterns (PAMPs) are recognised by the plant innate immune systems through receptor proteins called pattern recognition receptors

(soybean stem/root rot) (Bhadauria et al., 2009).

**2.1 Pre and post-invasive levels in plant-pathogen interaction**

**2. Plant defence responses**

site.

responses (e.g., levels of host defence, pathogen molecules), (ii) plant defence signalling (e.g., molecular recognition, gene expression), and (iii) *Olea europaea* L. and *Colletotrichum acutatum* strategies in susceptible and resistant olive cultivars.

### **1.1 Compatible and Incompatible Interactions**

The resistance in plants has been defined as an incompatible interaction between plant and pathogen. In general, a incompatible interaction involves the plant recognition processes that prevent or retard the pathogen growth, and spread it through plant cells. On the other hand, a compatible interaction is when plant disease occurs, due to an inadequate defence response of the host against the pathogen in terms of timing and intensity (Casado Díaz et al., 2006; Mysore & Ryu, 2004). In many plant species one of the most typical symptoms of defence response is the rapid plant cell death at the infection site, the hypersensitive response (HR), which limits pathogen from spreading to other cells (Dangl et al., 1996; Glazebrook, 2005; Oh et al., 2006). Van Der Plank (1966) reported two categories of disease resistance in plants: vertical and horizontal resistance. Vertical resistance (monogenic or oligogenic) protects hosts against only one pathogen race. This complete resistance is conferred by a few genes, or even it can be based on a single gene pair, i.e., host *R*-gene activation by pathogen avirulence gene (*avr*). The horizontal resistance (polygenic) or incomplete resistance is conditioned by many genes with minor effect. In the review work Mysore & Ryu (2004) proposed that non-host resistance against bacteria, fungi, and oomycetes can be also classified into: (i) type I, which does not result in visible cell death and (ii) type II, in which a hypersensitive response occurs, resulting in cell death at the infection site. The host resistance has been studied intensively in different pathosystem, while non-host resistance remains poorly understood (Oh et al., 2006). However, many aspects related to the gene expression patterns in some host-pathogen interaction have not yet been cleared.

### **1.2 Functional genomic**

Functional genomics in plant-pathogen interaction involves studies that reveal the complex networks of host stresses perception and signal transduction, leading to the multiple defensive responses to pathogens (Langridge et al., 2006; Sreenivasulu et al., 2007; Vij & Tyagi, 2007). Functional genomics involves the development of global experimental approaches in order to analyse gene function, in contrast to structural genomics, where the entire nucleotide sequence of an organism's genome is determined (Hieter & Boguski, 1997). The purpose of functional genomics is to understand the genes function, how cells work, how cells form organisms, what goes wrong in disease and how components work together to comprise functioning cells and organisms (Lockhart & Winzeler, 2000). Advances on functional analysis considering genome, proteome and metabolome of an organism, together with the potential of bioinformatics and microscopic tools, enable scientists to assess global gene and, protein expression, and metabolite profiles of some damaged tissues, allowing a better understanding of the plant response mechanisms. The knowledge of complete genomic sequence of different crops is, sometimes the only way to gain access to the entire set of genes. The genome sequencing of the first higher plant, thale cress (*Arabidopsis thaliana*), provides nowadays an excellent model species to study host plant stress responses and to identify target genes for biotechnology applications (Bevan & Walsh, 2005; Zhang et al., 2006). For instance, cDNA from strawberry differently expressed upon challenge with the pathogen *Colletotrichum acutatum* has recently been isolated, and showed similarity to (*At* WRKY75) defence genes in *Arabidopsis thaliana* (Casado-Díaz et al., 2006; Encinas-Villarejo et al., 2009). With the development of high-throughput sequencing technologies, the number of genomes sequenced has been increasing fast. The O*ryza sativa*  L., *Triticum aestivum* L., *Zea mays* L., *Vitis vinifera* L., *Glycine max* L., and *Fragaria vesca* L. genome sequencing have been extremely successful in the discovery of new genes. Similarly to plants, the knowledge of the pathogens genome is very important to monitor global changes that occur during plant-fungal interactions. Several fungal genomes have been now sequenced, being some of them extremely important in terms of yield lost in key crops such as *Botrytis cinerea* (grape grey mould, and other host species), *Fusarium graminearum* (cereal head blight), *Fusarium verticillioides* (corn seed rot), *Magnaporthe oryzae* (rice blast), *Mycosphaerella fijiensis* (banana black leaf streak), *Septoria tritici* (wheat leaf blotch), *Puccinia graminis* (cereal rust), *Phytophthora ramorum* (sudden oak death) and *Phytophthora sojae* (soybean stem/root rot) (Bhadauria et al., 2009).

### **2. Plant defence responses**

248 Plant Breeding

responses (e.g., levels of host defence, pathogen molecules), (ii) plant defence signalling (e.g., molecular recognition, gene expression), and (iii) *Olea europaea* L. and *Colletotrichum*

The resistance in plants has been defined as an incompatible interaction between plant and pathogen. In general, a incompatible interaction involves the plant recognition processes that prevent or retard the pathogen growth, and spread it through plant cells. On the other hand, a compatible interaction is when plant disease occurs, due to an inadequate defence response of the host against the pathogen in terms of timing and intensity (Casado Díaz et al., 2006; Mysore & Ryu, 2004). In many plant species one of the most typical symptoms of defence response is the rapid plant cell death at the infection site, the hypersensitive response (HR), which limits pathogen from spreading to other cells (Dangl et al., 1996; Glazebrook, 2005; Oh et al., 2006). Van Der Plank (1966) reported two categories of disease resistance in plants: vertical and horizontal resistance. Vertical resistance (monogenic or oligogenic) protects hosts against only one pathogen race. This complete resistance is conferred by a few genes, or even it can be based on a single gene pair, i.e., host *R*-gene activation by pathogen avirulence gene (*avr*). The horizontal resistance (polygenic) or incomplete resistance is conditioned by many genes with minor effect. In the review work Mysore & Ryu (2004) proposed that non-host resistance against bacteria, fungi, and oomycetes can be also classified into: (i) type I, which does not result in visible cell death and (ii) type II, in which a hypersensitive response occurs, resulting in cell death at the infection site. The host resistance has been studied intensively in different pathosystem, while non-host resistance remains poorly understood (Oh et al., 2006). However, many aspects related to the gene expression patterns in some host-pathogen interaction have not

Functional genomics in plant-pathogen interaction involves studies that reveal the complex networks of host stresses perception and signal transduction, leading to the multiple defensive responses to pathogens (Langridge et al., 2006; Sreenivasulu et al., 2007; Vij & Tyagi, 2007). Functional genomics involves the development of global experimental approaches in order to analyse gene function, in contrast to structural genomics, where the entire nucleotide sequence of an organism's genome is determined (Hieter & Boguski, 1997). The purpose of functional genomics is to understand the genes function, how cells work, how cells form organisms, what goes wrong in disease and how components work together to comprise functioning cells and organisms (Lockhart & Winzeler, 2000). Advances on functional analysis considering genome, proteome and metabolome of an organism, together with the potential of bioinformatics and microscopic tools, enable scientists to assess global gene and, protein expression, and metabolite profiles of some damaged tissues, allowing a better understanding of the plant response mechanisms. The knowledge of complete genomic sequence of different crops is, sometimes the only way to gain access to the entire set of genes. The genome sequencing of the first higher plant, thale cress (*Arabidopsis thaliana*), provides nowadays an excellent model species to study host plant stress responses and to identify target genes for biotechnology applications (Bevan & Walsh,

*acutatum* strategies in susceptible and resistant olive cultivars.

**1.1 Compatible and Incompatible Interactions**

yet been cleared.

**1.2 Functional genomic**

### **2.1 Pre and post-invasive levels in plant-pathogen interaction**

Disease resistance in plant-pathogen interactions requires sensitive and specific recognition mechanisms for pathogen-derived signals in plants. Plants lack mobile defender cells (like animal antibodies) and a somatically adaptive immune system (Jones & Dangl, 2006; Palma et al., 2009). However, they are equipped, at least, by two levels of defence: a *pre-invasive*, which is expressed at the cell wall and apoplastic spaces level aiming to prevent pathogens penetration, and a *post-invasive*, which mediates resistance relatively to pathogen that have successfully penetrated plant cells, and often results in a localized cell death at the infection site.

The physical barriers are the first level of a general plant defence against pathogens invasion, and include waxy cuticular skin layers, the plants' cell wall and actin cytoskeleton that play a key role in penetration resistance (Dangl & Jones, 2001; Kobayashi & Kobayashi, 2007). The plants' cell wall is one of the sites where the changes, due to the defence response, can be observed. These can include cell-wall thickening and lignification, papilla formation, phenolic compounds accumulation, phytoalexins and other secondary metabolites, as well transcriptional activation of pathogenesis-related proteins (Anand et al., 2009; Bhadauria et al., 2010; Montesano et al., 2003; Salazar et al., 2007; Shan & Goodwin, 2005; Zipfel, 2008). The papilla structures were observed on blueberry fruits inoculated with *Colletotrichum acutatum,* and it was formed beneath subcuticular hyphae and represented one of the host defence responses (Wharton & Schilder, 2008). If passive defences, such as the cell wall, is overcome by the pathogen, active defence responses are triggered a long lasting systemic response (systemic acquired resistance, SAR) which confers to the plant resistance against a broad spectrum of pathogens (Thordal-Christensen, 2003).

Primary or basal immune defence response is induced by perception of molecules called pathogen-associated molecular patterns (PAMPs or MAMPs) (Dangl & Jones, 2001; Jeong et al., 2009). The pathogen-associated molecular patterns (PAMPs) are recognised by the plant innate immune systems through receptor proteins called pattern recognition receptors

Olive – Colletotrichum acutatum: An Example of Fruit-Fungal Interaction 251

Various signalling molecules mediate the expression of pathogenesis-related proteins, which can interfere with the plant resistant to a pathogen attack. The defence protein products include peroxidase, polyphenol oxidase, which catalyzes the formation of lignin and phenylalanine ammonia-lyase, involved in phytoalexin and phenolics biosynthesis (Salazar et al., 2007). Some pathogenesis-related proteins such as chitinase, and β-1,3 glucanase have potential antifungal activity which degrade the fungal cell wall and cause fungal cells lyses. Co-induction of chitinases, peroxidases, Ɣ-thionins and β-1,3-glucanases gene expression, during pathogen infection, has been described in several plants, including wheat, strawberry, potato, soybean, maize, tobacco, tomato, bean, and pea, among others (Bettini et al., 1998; Casado-Díaz et al., 2006; Cheong et al., 2000; Lambais & Mehdy, 1998; Li et al., 2001; Liu et al., 2010; Petruzzelli et al., 1999; Vogelsang & Barz, 1993). Defence responses can also be mediated by endogenous signalling molecules such as salicylic acid, jasmonic acid, and ethylene (Encinas-Villarejo et al., 2009; Mysore & Ryu, 2004). Plant hormones have been reported to have a role in induce plant defence responses, operating in two major defence pathways in plants, depending on salicylic acid or jasmonic acid and ethylene, and conferring resistance to different pathogens (de Vos et al., 2005; Dempsey et al., 1999; Jones & Dangl, 2006; Métraux, 2001). Salicylic acid confers resistance to host plants, especially against biotrophs and hemibiotrophs pathogens, whereas jasmonic acid and ethylene signalling contributes to resistance against necrotrophs pathogens (Ausubel, 2005; Chisholm et al., 2006; Glazebrook, 2005). An incompatible interaction has been reported (Lee et al., 2009), where salicylic acid protects unripe fruit of pepper against *Colletotrichum gloeosporioides* infection through the inhibition of appressorium development. Genes encoding ethylene and jasmonic acid biosyntheses and indole-3-acetic acid regulation were found to be highly induced in citrus

flowers during *Colletotrichum acutatum* infection (Lahey et al., 2004; Li et al., 2003).

*Bactrocera oleae*, and *Prays oleae* (Sergeeva & Spooner-Hart, 2009; Tsitsipis et al., 2009).

Olive anthracnose was reported for the first time in Portugal in 1899 by Almeida (1899) which classified the *Gloesporium olivarum* as the causal agent of olive disease. In 1957, Von

Fungi are the causal agents of most serious disease and are one of the pathogens that are able to breach the intact surfaces of hosts, rapidly establishing infections that can result in significant agricultural yield loss (Bhadauria et al., 2010). *Colletotrichum* species comprises a diverse range of important plant pathogenic fungi that cause pre- and postharvest crop losses worldwide. *Colletotrichum acutatum* and *Colletotrichum gloeosporioides* have been reported as causal agents of olive anthracnose, which is a major disease of cultivated olive orchards. The *Olea europaea* L. was domesticated in the Mediterranean region where it has a huge eco-social role. However, due to its importance as a crop it has spread to other Mediterranean climates worldwide (Gutiérrez & Ponti, 2009). Like other crops, olive is susceptible to a large number of diseases some of which are causing considerable damage to the olive orchards worldwide. Without the support of pest-control chemicals, such as fungicides or herbicides, crops are increasingly exposed to a range of biotic attacks. As for *Olea europaea* L. one of the main problems, concerning long-term cultivation, is the fungal contamination such as *Colletotrichum acutatum*, *Colletotrichum gloeosporioides, Fusicladium oleagineum, Phytophthora megasperma, Rhizoctonia, Verticillium dahliae, Pseudomonas syringae* pv. *savastanoi*, and the pests such as

**2.3** *Colletotrichum spp.* **as pathogenic fungi of** *Olea europaea L.*

**2.2 Plant defence signaling molecules**

(PRRs), and include cold shock protein, flagellin, lipopolysaccharides of Gram-negative bacteria, lipids, elongation factor (EF-Tu), enzyme superoxide dismutase, peptidoglycan, and chitin of fungi (Bent & Mackey, 2007; Chisholm et al., 2006; Jeong et al., 2009; McDowell & Simon, 2008; Raqi et al., 2009; Zipfel, 2008). Perception of PAMPs occurs through PRRs located on the cell surface which could activate a chain of intracellular defensive signalling pathways, including the activation of a mitogen-activated protein kinase (MAPK) signalling cascade. When PAMPs are recognised by PRRs the PAMP-triggered immunity (PTI) system can halt microbial growth. In general, the PRRs are constituted by an extracellular leucinerich repeat (LRR) domain, and an intracellular kinase domain.

The second molecular level of plants defence (*post-invasive*) occurs after the effectors pathogen invasion. The effectors secreted by pathogens into host cells are recognised by intracellular nucleotide-binding (NB)-LRR receptors which induce effector-triggered immunity (ETI). Successful pathogens have evolved effector molecules that target virulence effector proteins (Avr) that can overcome host defensive pathways. In a dynamic coevolution between plants and pathogens, some plants have evolved disease resistance proteins (R) to recognise these effectors directly or indirectly, and activate an effective immune response like activation of localised cell death at the pathogen infection sites, called the hypersensitive response (HR) (Kim et al., 2008; Lindeberg & Collmer, 2009; Zipfel, 2008). The gene-for-gene resistance model, proposed by Flor (1971), requires that Avr-protein recognise the corresponding R-protein, which is accompanied by localised cell death. This effect triggers a cascade of signal transduction events that include rapid ion fluxes, extracellular oxidative burst, changes of phosphorylation status, induction of salicylic acid, and localised transcription reprogramming at the infection site (Dangl & Jones, 2001; Dangl & McDowell, 2006; Kim et al., 2008; Palma et al., 2009). Although they have been documented in others pathosystem in the olive fruits infected by *Colletotrichum acutatum* no reports considering these events have been made. New perspectives on plant defence signal transduction mechanisms have been given by the discovery of novel intracellular perception of pathogen effector proteins. The events of pathogen effectors recognition are mediated by plant NB-LRR proteins and allows resistance defence response to pathogens (Dodds & Rathjen, 2010). The plant NB-LRR proteins are able to recognise pathogen effectors through diverse pathways: (i) direct recognition, (ii) guard and decoy models, or by (iii) bait-andswitch model, and translate these interactions into a defence response (Collier & Moffett, 2009; Dangl & Jones, 2001; Dodds & Rathjen, 2010; Rafiqi et al., 2009; Van der Hoorn & Kamour, 2008). All models illustrated the diversity of perception mechanisms employed by plants to detect the broad variety of pathogen effectors, and activating plant defence responses to infection. In pathogen and plant direct recognition, the effectors triggers immune signalling by physical binding to the NB-LRR receptor. The LRR domain is considered the major determinant of perception and recognition specificity (Rafiqi et al., 2009). The guard and decoy models report a modification on an accessory protein which is then recognised by NB-LRR receptor. In bait-and-switch model the effector interacts with an accessory protein associated with NB-LRR, and then a recognition mechanism occurs between the effector and NB-LRR protein in order to trigger signalling. However, none of these models are completely understood. Thus we face the need to expand our knowledge on how plant immune receptors are activated by effector recognition and how the resistance signal is triggered.

### **2.2 Plant defence signaling molecules**

250 Plant Breeding

(PRRs), and include cold shock protein, flagellin, lipopolysaccharides of Gram-negative bacteria, lipids, elongation factor (EF-Tu), enzyme superoxide dismutase, peptidoglycan, and chitin of fungi (Bent & Mackey, 2007; Chisholm et al., 2006; Jeong et al., 2009; McDowell & Simon, 2008; Raqi et al., 2009; Zipfel, 2008). Perception of PAMPs occurs through PRRs located on the cell surface which could activate a chain of intracellular defensive signalling pathways, including the activation of a mitogen-activated protein kinase (MAPK) signalling cascade. When PAMPs are recognised by PRRs the PAMP-triggered immunity (PTI) system can halt microbial growth. In general, the PRRs are constituted by an extracellular leucine-

The second molecular level of plants defence (*post-invasive*) occurs after the effectors pathogen invasion. The effectors secreted by pathogens into host cells are recognised by intracellular nucleotide-binding (NB)-LRR receptors which induce effector-triggered immunity (ETI). Successful pathogens have evolved effector molecules that target virulence effector proteins (Avr) that can overcome host defensive pathways. In a dynamic coevolution between plants and pathogens, some plants have evolved disease resistance proteins (R) to recognise these effectors directly or indirectly, and activate an effective immune response like activation of localised cell death at the pathogen infection sites, called the hypersensitive response (HR) (Kim et al., 2008; Lindeberg & Collmer, 2009; Zipfel, 2008). The gene-for-gene resistance model, proposed by Flor (1971), requires that Avr-protein recognise the corresponding R-protein, which is accompanied by localised cell death. This effect triggers a cascade of signal transduction events that include rapid ion fluxes, extracellular oxidative burst, changes of phosphorylation status, induction of salicylic acid, and localised transcription reprogramming at the infection site (Dangl & Jones, 2001; Dangl & McDowell, 2006; Kim et al., 2008; Palma et al., 2009). Although they have been documented in others pathosystem in the olive fruits infected by *Colletotrichum acutatum* no reports considering these events have been made. New perspectives on plant defence signal transduction mechanisms have been given by the discovery of novel intracellular perception of pathogen effector proteins. The events of pathogen effectors recognition are mediated by plant NB-LRR proteins and allows resistance defence response to pathogens (Dodds & Rathjen, 2010). The plant NB-LRR proteins are able to recognise pathogen effectors through diverse pathways: (i) direct recognition, (ii) guard and decoy models, or by (iii) bait-andswitch model, and translate these interactions into a defence response (Collier & Moffett, 2009; Dangl & Jones, 2001; Dodds & Rathjen, 2010; Rafiqi et al., 2009; Van der Hoorn & Kamour, 2008). All models illustrated the diversity of perception mechanisms employed by plants to detect the broad variety of pathogen effectors, and activating plant defence responses to infection. In pathogen and plant direct recognition, the effectors triggers immune signalling by physical binding to the NB-LRR receptor. The LRR domain is considered the major determinant of perception and recognition specificity (Rafiqi et al., 2009). The guard and decoy models report a modification on an accessory protein which is then recognised by NB-LRR receptor. In bait-and-switch model the effector interacts with an accessory protein associated with NB-LRR, and then a recognition mechanism occurs between the effector and NB-LRR protein in order to trigger signalling. However, none of these models are completely understood. Thus we face the need to expand our knowledge on how plant immune receptors are activated by effector recognition and how the resistance

rich repeat (LRR) domain, and an intracellular kinase domain.

signal is triggered.

Various signalling molecules mediate the expression of pathogenesis-related proteins, which can interfere with the plant resistant to a pathogen attack. The defence protein products include peroxidase, polyphenol oxidase, which catalyzes the formation of lignin and phenylalanine ammonia-lyase, involved in phytoalexin and phenolics biosynthesis (Salazar et al., 2007). Some pathogenesis-related proteins such as chitinase, and β-1,3 glucanase have potential antifungal activity which degrade the fungal cell wall and cause fungal cells lyses. Co-induction of chitinases, peroxidases, Ɣ-thionins and β-1,3-glucanases gene expression, during pathogen infection, has been described in several plants, including wheat, strawberry, potato, soybean, maize, tobacco, tomato, bean, and pea, among others (Bettini et al., 1998; Casado-Díaz et al., 2006; Cheong et al., 2000; Lambais & Mehdy, 1998; Li et al., 2001; Liu et al., 2010; Petruzzelli et al., 1999; Vogelsang & Barz, 1993). Defence responses can also be mediated by endogenous signalling molecules such as salicylic acid, jasmonic acid, and ethylene (Encinas-Villarejo et al., 2009; Mysore & Ryu, 2004). Plant hormones have been reported to have a role in induce plant defence responses, operating in two major defence pathways in plants, depending on salicylic acid or jasmonic acid and ethylene, and conferring resistance to different pathogens (de Vos et al., 2005; Dempsey et al., 1999; Jones & Dangl, 2006; Métraux, 2001). Salicylic acid confers resistance to host plants, especially against biotrophs and hemibiotrophs pathogens, whereas jasmonic acid and ethylene signalling contributes to resistance against necrotrophs pathogens (Ausubel, 2005; Chisholm et al., 2006; Glazebrook, 2005). An incompatible interaction has been reported (Lee et al., 2009), where salicylic acid protects unripe fruit of pepper against *Colletotrichum gloeosporioides* infection through the inhibition of appressorium development. Genes encoding ethylene and jasmonic acid biosyntheses and indole-3-acetic acid regulation were found to be highly induced in citrus flowers during *Colletotrichum acutatum* infection (Lahey et al., 2004; Li et al., 2003).

### **2.3** *Colletotrichum spp.* **as pathogenic fungi of** *Olea europaea L.*

Fungi are the causal agents of most serious disease and are one of the pathogens that are able to breach the intact surfaces of hosts, rapidly establishing infections that can result in significant agricultural yield loss (Bhadauria et al., 2010). *Colletotrichum* species comprises a diverse range of important plant pathogenic fungi that cause pre- and postharvest crop losses worldwide. *Colletotrichum acutatum* and *Colletotrichum gloeosporioides* have been reported as causal agents of olive anthracnose, which is a major disease of cultivated olive orchards. The *Olea europaea* L. was domesticated in the Mediterranean region where it has a huge eco-social role. However, due to its importance as a crop it has spread to other Mediterranean climates worldwide (Gutiérrez & Ponti, 2009). Like other crops, olive is susceptible to a large number of diseases some of which are causing considerable damage to the olive orchards worldwide. Without the support of pest-control chemicals, such as fungicides or herbicides, crops are increasingly exposed to a range of biotic attacks. As for *Olea europaea* L. one of the main problems, concerning long-term cultivation, is the fungal contamination such as *Colletotrichum acutatum*, *Colletotrichum gloeosporioides, Fusicladium oleagineum, Phytophthora megasperma, Rhizoctonia, Verticillium dahliae, Pseudomonas syringae* pv. *savastanoi*, and the pests such as *Bactrocera oleae*, and *Prays oleae* (Sergeeva & Spooner-Hart, 2009; Tsitsipis et al., 2009).

Olive anthracnose was reported for the first time in Portugal in 1899 by Almeida (1899) which classified the *Gloesporium olivarum* as the causal agent of olive disease. In 1957, Von

Olive – Colletotrichum acutatum: An Example of Fruit-Fungal Interaction 253

Fig. 1. Olive fruits infected by *Colletotrichum acutatum*. (**a**) Olive fruits without pathogen infection; (**b**) olive fruits with *Colletotrichum acutatum* infection, and (**c**) 192 hours after

olive oil, there was also an increase in exportations of about 19%. Nationally, the prevalent olive cultivar is 'Galega' that gives to olive oil a good specificity when compared with olive oils from others cultivars. This characteristic is unique in the world and for that reason it is a national imperative to preserve 'this heritage' at all cost. However, this cultivar has a disease resistant problem, related to its high susceptibility to olive anthracnose caused by the *Colletotrichum acutatum*, known in Portugal as 'gafa' disease. This disease is very aggressive and is one of the main constraints affecting both the Portuguese olive oil production and unique characteristics. The *Colletotrichum* species are known to produce enzymes that degrade carbohydrates and thus dissolve plant cell walls (e.g., polygalacturonases, pectin lyases and proteases) and hydrolyze fruit cuticles (Wharton & Diéguez-Uribeondo, 2004). In a response, several plants have evolved inhibitor proteins (PGIPs) that specifically recognise and inhibit fungal polygalacturonases (Mehli et al., 2004). Recently, a new report concerning the reduction of *Colletotrichum acutatum* infection by a polygalacturonase inhibitor protein

The penetration of the plant tissue is always a crucial event for plant-pathogen interaction and the success of colonization depends on the ability of the pathogen to retrieve the nutrients from the host. In some host-pathogen interactions, such as olive fruits and pepper, the fruit index maturation may compromise the success of colonization (Lee et al., 2009; Moral et al., 2008). The resistance of immature fruits to colonization by *Colletotrichum* species can be related with the sugar content which is a non-suitable substrate to fulfil the nutritional and energy requirements of the pathogen (Wharton & Diéguez-Uribeondo, 2004). Additionally, there are a large number of secondary metabolites such as alkaloids, tannins, phenols and resins, which create a hostile and toxic environment for pathogens growth due to their anti-microbial activity (Dixon, 2001). Preformed fungi toxic compounds in unripe avocado fruit were reported to inhibit the *Colletotrichum gloeosporioides* growth

inoculation olive fruit is completely destroyed by pathogen infection.

extracted from apple, has been provided (Gregori et al., 2008).

Arx reported that *Colletotrichum gloeosporioides* was the species responsible for olive anthracnose. Latter, Simmonds introduced *Colletotrichum acutatum* in 1965 as one of the pathogen responsible for olive anthracnose. Research focused in host–pathogen interactions developed in Greece, Italy, and Spain has provided new insights into olive disease identification, and *Colletotrichum gloeosporioides* (originally: *Gloeosporium olivarum*) was reported as the primary cause of olive anthracnose (Mateo-Sagasta, 1968; Zachos & Makris, 1963). It has also been very difficult to discriminate between *Colletotrichum acutatum* and *Colletotrichum gloeosporioides* by traditional taxonomical methods. Morphologically, *Colletotrichum acutatum* and *Colletotrichum gloeosporioides* are very similar because of their host range overlapping and the wide variability found among their pathotypes. Considerable progress has been made in *Colletotrichum* species identication. In Portugal, Talhinhas et al. (2005) using molecular approaches, and Carvalho et al. (2003) with Potato dextrose agar enzyme linked immunosorbent assay (PDA-ELISA) reported that *Colletotrichum acutatum* is the predominate species in olive orchards, and consequently responsible for olive anthracnose. Nowadays, *Colletotrichum acutatum* is the dominant species in both olive growing regions: Alentejo in Portugal, and Andalusia in Spain (Moral et al., 2009; Talhinhas et al., 2005, 2009). Recently, molecular tools such as random amplification of polymorphic DNA (RAPD), species-specific primers for *Colletotrichum acutatum* isolates using internal transcribed spacer (ITS) region of rDNA sequences, and other regions of the genome have been effectively used to clearly discriminate *Colletotrichum acutatum* from *Colletotrichum gloeosporioides* and to identify genetically distinct subgroups of *Colletotrichum acutatum* (Peres et al., 2005; Talhinhas et al., 2005, 2011). Other characters, such as growth rates and sensitivity to benomyl fungicide, have been helpful to differentiate between *Colletotrichum acutatum* and *Colletotrichum gloeosporioides* (Peres et al., 2005).

Besides olive crop, *Colletotrichum acutatum* is a major constraint in global food production as it causes many of the world's most devastating diseases in cereals, grasses, legumes, vegetables, perennial crops and a number of fruit trees (Bailey et al., 1992; Peres et al., 2005; Wharton & Diéguez-Uribeondo, 2004). This species can infect all plant surfaces, but favours the young leaves, small branches and fruits of herbaceous species growing in a humid microclimate (Peres et al., 2005; Wharton & Diéguez-Uribeondo, 2004). In different regions of Portugal the *Colletotrichum acutatum* severely affects olive orchards leading to a decrease in olive oil production and quality, which compromises the protected denomination of origin (PDO) of Portuguese olive oils (Fig. 1). The *Colletotrichum acutatum* can affect up to 100% of the fruit on a olive tree during humid (or rain) autumns where susceptible olive cultivars are grown (Casado-Díaz et al., 2006; Freeman et al., 2002; Garrido et al., 2008; Peres et al., 2005; Talhinhas et al., 2011; Trapero & Blanco, 2008). Moreover, a poor quality and low stability olive oil is obtained from olives harvested in areas affected by anthracnose, presenting alterations in oil color (red), high acidity and other typical organoleptic characteristics (Carvalho et al., 2006; Moral et al., 2008; Talhinhas et al., 2009, 2011) (Fig.1).

In Portugal the olive oil production employs more than 400 000 people and the average yield is about 42 000 ton/year. The area occupied by olive trees is more than 340 thousand of hectares. In the last ten years, an expansion of olive tree planting area by Portuguese farmers was observed. This was as a result of an increasing of 2.5% in the demand of olives in the world. During the same period of time, in Portugal, the consume of olive oil was recuperated from 3.3 Kg to 7.0 Kg per capita. Beyond the improvement of national production/consume of

Arx reported that *Colletotrichum gloeosporioides* was the species responsible for olive anthracnose. Latter, Simmonds introduced *Colletotrichum acutatum* in 1965 as one of the pathogen responsible for olive anthracnose. Research focused in host–pathogen interactions developed in Greece, Italy, and Spain has provided new insights into olive disease identification, and *Colletotrichum gloeosporioides* (originally: *Gloeosporium olivarum*) was reported as the primary cause of olive anthracnose (Mateo-Sagasta, 1968; Zachos & Makris, 1963). It has also been very difficult to discriminate between *Colletotrichum acutatum* and *Colletotrichum gloeosporioides* by traditional taxonomical methods. Morphologically, *Colletotrichum acutatum* and *Colletotrichum gloeosporioides* are very similar because of their host range overlapping and the wide variability found among their pathotypes. Considerable progress has been made in *Colletotrichum* species identication. In Portugal, Talhinhas et al. (2005) using molecular approaches, and Carvalho et al. (2003) with Potato dextrose agar enzyme linked immunosorbent assay (PDA-ELISA) reported that *Colletotrichum acutatum* is the predominate species in olive orchards, and consequently responsible for olive anthracnose. Nowadays, *Colletotrichum acutatum* is the dominant species in both olive growing regions: Alentejo in Portugal, and Andalusia in Spain (Moral et al., 2009; Talhinhas et al., 2005, 2009). Recently, molecular tools such as random amplification of polymorphic DNA (RAPD), species-specific primers for *Colletotrichum acutatum* isolates using internal transcribed spacer (ITS) region of rDNA sequences, and other regions of the genome have been effectively used to clearly discriminate *Colletotrichum acutatum* from *Colletotrichum gloeosporioides* and to identify genetically distinct subgroups of *Colletotrichum acutatum* (Peres et al., 2005; Talhinhas et al., 2005, 2011). Other characters, such as growth rates and sensitivity to benomyl fungicide, have been helpful to differentiate between *Colletotrichum*

Besides olive crop, *Colletotrichum acutatum* is a major constraint in global food production as it causes many of the world's most devastating diseases in cereals, grasses, legumes, vegetables, perennial crops and a number of fruit trees (Bailey et al., 1992; Peres et al., 2005; Wharton & Diéguez-Uribeondo, 2004). This species can infect all plant surfaces, but favours the young leaves, small branches and fruits of herbaceous species growing in a humid microclimate (Peres et al., 2005; Wharton & Diéguez-Uribeondo, 2004). In different regions of Portugal the *Colletotrichum acutatum* severely affects olive orchards leading to a decrease in olive oil production and quality, which compromises the protected denomination of origin (PDO) of Portuguese olive oils (Fig. 1). The *Colletotrichum acutatum* can affect up to 100% of the fruit on a olive tree during humid (or rain) autumns where susceptible olive cultivars are grown (Casado-Díaz et al., 2006; Freeman et al., 2002; Garrido et al., 2008; Peres et al., 2005; Talhinhas et al., 2011; Trapero & Blanco, 2008). Moreover, a poor quality and low stability olive oil is obtained from olives harvested in areas affected by anthracnose, presenting alterations in oil color (red), high acidity and other typical organoleptic characteristics (Carvalho et al., 2006; Moral et al., 2008; Talhinhas et al., 2009, 2011) (Fig.1). In Portugal the olive oil production employs more than 400 000 people and the average yield is about 42 000 ton/year. The area occupied by olive trees is more than 340 thousand of hectares. In the last ten years, an expansion of olive tree planting area by Portuguese farmers was observed. This was as a result of an increasing of 2.5% in the demand of olives in the world. During the same period of time, in Portugal, the consume of olive oil was recuperated from 3.3 Kg to 7.0 Kg per capita. Beyond the improvement of national production/consume of

*acutatum* and *Colletotrichum gloeosporioides* (Peres et al., 2005).

Fig. 1. Olive fruits infected by *Colletotrichum acutatum*. (**a**) Olive fruits without pathogen infection; (**b**) olive fruits with *Colletotrichum acutatum* infection, and (**c**) 192 hours after inoculation olive fruit is completely destroyed by pathogen infection.

olive oil, there was also an increase in exportations of about 19%. Nationally, the prevalent olive cultivar is 'Galega' that gives to olive oil a good specificity when compared with olive oils from others cultivars. This characteristic is unique in the world and for that reason it is a national imperative to preserve 'this heritage' at all cost. However, this cultivar has a disease resistant problem, related to its high susceptibility to olive anthracnose caused by the *Colletotrichum acutatum*, known in Portugal as 'gafa' disease. This disease is very aggressive and is one of the main constraints affecting both the Portuguese olive oil production and unique characteristics. The *Colletotrichum* species are known to produce enzymes that degrade carbohydrates and thus dissolve plant cell walls (e.g., polygalacturonases, pectin lyases and proteases) and hydrolyze fruit cuticles (Wharton & Diéguez-Uribeondo, 2004). In a response, several plants have evolved inhibitor proteins (PGIPs) that specifically recognise and inhibit fungal polygalacturonases (Mehli et al., 2004). Recently, a new report concerning the reduction of *Colletotrichum acutatum* infection by a polygalacturonase inhibitor protein extracted from apple, has been provided (Gregori et al., 2008).

The penetration of the plant tissue is always a crucial event for plant-pathogen interaction and the success of colonization depends on the ability of the pathogen to retrieve the nutrients from the host. In some host-pathogen interactions, such as olive fruits and pepper, the fruit index maturation may compromise the success of colonization (Lee et al., 2009; Moral et al., 2008). The resistance of immature fruits to colonization by *Colletotrichum* species can be related with the sugar content which is a non-suitable substrate to fulfil the nutritional and energy requirements of the pathogen (Wharton & Diéguez-Uribeondo, 2004). Additionally, there are a large number of secondary metabolites such as alkaloids, tannins, phenols and resins, which create a hostile and toxic environment for pathogens growth due to their anti-microbial activity (Dixon, 2001). Preformed fungi toxic compounds in unripe avocado fruit were reported to inhibit the *Colletotrichum gloeosporioides* growth

Olive – Colletotrichum acutatum: An Example of Fruit-Fungal Interaction 255

still not understood, and therefore needs to be explored. The *Colletotrichum* species life cycle comprises a teleomorph (sexual) and an anamorph (asexual) stages. However, in many plant-fungal systems asexual phase has still not been found, even on economically important crops like olive tree. The *Colletotrichum* species life cycle is summarized in Fig. 2. In general, the sexual stage accounts for the fungus genetic variability while the asexual is responsible for fungal spore formation and appressorium development. The *Colletotrichum* spores are essential for the fungus dispersal (Peres et al., 2005; Wharton & Diéguez-Uribeondo, 2004). Specific structures or developmental stages, such as acervuli formation, spore germination and appressorium formation are distinguished during the

To establish a compatible interaction with a host, the fungal pathogen does not only need to overcome host physical barriers, but also they have to establish a feeding relationship with the host. The early events in *Colletotrichum* spp. infection process are very similar among the different hosts. Frequently, the host-pathogen interaction includes (i) spore adhesion to the host surface, (ii) spore germination, (iii) appressorium development and (iv) fungal growth through the colonization of the hosts' tissues (Fig. 3). Spores are embedded in a matrix of moist hydrophilic mucilaginous material including glycoproteins, lipids and polysaccharides. These compounds are essential not only for spore adhesion, but also for their protection against desiccation, physical damage, and host defence responses. After spore germinate a short germ tube is generated which finally differentiate into an appressorium with a penetration

The appressorium with penetration pore are a penetration structure that is formed after germ tube germination, and allows many pathogens to enter into the host cells. Pathogens may force their way through plant surfaces by different means; some take advantage of natural doors, such as stomata or lenticels; some others enter through wounds or directly through cuticle (Bailey et al., 1992; Gomes et al., 2009; Jong & Ackerveken, 2009). In order to infect plants, fungal pathogens have developed a wide variety of infection strategies: (i) *Necrotrophs*, pathogen kill the host and feed from the cell contents; (ii) *Biotrophs*, require a living host to complete their life cycle; and (iii) *Hemibiotrophs*, act as both biotrophs and necrotrophs at different stages of infection. Most of the *Colletotrichum* species are hemibiotrophs with different spans of their biotrophic phase, and may also undergo a period of quiescence in order to overcome resistance mechanisms (Gomes et al., 2009; Peres et al., 2005). Two types of interaction between *Colletotrichum* species and their hosts have been reported: intercellular hemibiotrophy and subcuticular intramural necrotrophy

In intercellular hemibiotrophic infections, a symptomless biotrophic phase is followed by a destructive necrotrophic one, during which symptoms become apparent. Examples of pathogens employing this infection strategy are *Colletotrichum graminicola* Politis & Wheeler, 1973). *Colletotrichum gloeosporioides* (Ogle et al., 1990), and *Colletotrichum lindemuthianum* (Mercer et al., 1975; O'Connell et al., 1985). In the subcuticular intramural infection strategy, rather than penetrating the epidermal cell wall, the fungus grows under the cuticle and within the periclinal and anticlinal walls of epidermal cells (Arroyo et al., 2007; O'Connell et

(Gomes et al., 2009; O'Connell et al., 2000; Perfect et al., 1999) (Fig. 4).

*Colletotrichum* species life cycle.

pore (Fig. 3).

**2.4** *Colletotrichum acutatum* **and olive fruits interaction**

(Prusky et al., 2000). Phytoalexins have also been identified in *Capsicum annum* L. anthracnose, caused by *Colletotrichum capsici* and *Glomerella cingulata*. There are few reports about phytoalexins production after *Colletotrichum* species infection. The most recently, an evidence of phytoalexins production was observed on unripe blueberry fruits inoculated with *Colletotrichum acutatum* (Wharton & Diéguez-Uribeondo, 2004).

Fig. 2. The *Colletotrichum acutatum* life cycle on *Olea europaea* L. fruits. All *Colletotrichum* spp. produce acervuli with abundant spores that are rain-splashed and serve as an inoculum source for futures infections. Spore germinates to form appressoria, and quiescent infections can be established on fruits, small branches and/or leaves. Long biotrophic phase on unripe fruits are observed during spring, and summer. Necrotrophic phase appears primarily on ripe fruits and then on leaves and branches (adapted from Peres et al., 2005; Trapero & Blanco, 2008).

### **2.3.1** *Colletotrichum acutatum* **life cycle on olive fruits**

The early events of basic pathogenicity and susceptible interactions between olive cultivars and *Colletotrichum acutatum* as well as lifestyle of the *Colletotrichum* species are

(Prusky et al., 2000). Phytoalexins have also been identified in *Capsicum annum* L. anthracnose, caused by *Colletotrichum capsici* and *Glomerella cingulata*. There are few reports about phytoalexins production after *Colletotrichum* species infection. The most recently, an evidence of phytoalexins production was observed on unripe blueberry fruits inoculated

*Summer*

Conidia rain splash dispersal

Acervulus

Infected fruits may remain on the olive tree and/or in the

?

*Autumn*

Infected ripe olive fruits

Fig. 2. The *Colletotrichum acutatum* life cycle on *Olea europaea* L. fruits. All *Colletotrichum* spp. produce acervuli with abundant spores that are rain-splashed and serve as an inoculum source for futures infections. Spore germinates to form appressoria, and quiescent infections can be established on fruits, small branches and/or leaves. Long biotrophic phase on unripe fruits are observed during spring, and summer. Necrotrophic phase appears primarily on ripe fruits and then on leaves and branches (adapted from Peres et al., 2005; Trapero &

?

*Winter*

Soil

soil

The early events of basic pathogenicity and susceptible interactions between olive cultivars and *Colletotrichum acutatum* as well as lifestyle of the *Colletotrichum* species are

**2.3.1** *Colletotrichum acutatum* **life cycle on olive fruits**

Conidia

Blanco, 2008).

Quiescent infection on small branches, unripe fruits and leaves

*Spring*

with *Colletotrichum acutatum* (Wharton & Diéguez-Uribeondo, 2004).

still not understood, and therefore needs to be explored. The *Colletotrichum* species life cycle comprises a teleomorph (sexual) and an anamorph (asexual) stages. However, in many plant-fungal systems asexual phase has still not been found, even on economically important crops like olive tree. The *Colletotrichum* species life cycle is summarized in Fig. 2. In general, the sexual stage accounts for the fungus genetic variability while the asexual is responsible for fungal spore formation and appressorium development. The *Colletotrichum* spores are essential for the fungus dispersal (Peres et al., 2005; Wharton & Diéguez-Uribeondo, 2004). Specific structures or developmental stages, such as acervuli formation, spore germination and appressorium formation are distinguished during the *Colletotrichum* species life cycle.

### **2.4** *Colletotrichum acutatum* **and olive fruits interaction**

To establish a compatible interaction with a host, the fungal pathogen does not only need to overcome host physical barriers, but also they have to establish a feeding relationship with the host. The early events in *Colletotrichum* spp. infection process are very similar among the different hosts. Frequently, the host-pathogen interaction includes (i) spore adhesion to the host surface, (ii) spore germination, (iii) appressorium development and (iv) fungal growth through the colonization of the hosts' tissues (Fig. 3). Spores are embedded in a matrix of moist hydrophilic mucilaginous material including glycoproteins, lipids and polysaccharides. These compounds are essential not only for spore adhesion, but also for their protection against desiccation, physical damage, and host defence responses. After spore germinate a short germ tube is generated which finally differentiate into an appressorium with a penetration pore (Fig. 3).

The appressorium with penetration pore are a penetration structure that is formed after germ tube germination, and allows many pathogens to enter into the host cells. Pathogens may force their way through plant surfaces by different means; some take advantage of natural doors, such as stomata or lenticels; some others enter through wounds or directly through cuticle (Bailey et al., 1992; Gomes et al., 2009; Jong & Ackerveken, 2009). In order to infect plants, fungal pathogens have developed a wide variety of infection strategies: (i) *Necrotrophs*, pathogen kill the host and feed from the cell contents; (ii) *Biotrophs*, require a living host to complete their life cycle; and (iii) *Hemibiotrophs*, act as both biotrophs and necrotrophs at different stages of infection. Most of the *Colletotrichum* species are hemibiotrophs with different spans of their biotrophic phase, and may also undergo a period of quiescence in order to overcome resistance mechanisms (Gomes et al., 2009; Peres et al., 2005). Two types of interaction between *Colletotrichum* species and their hosts have been reported: intercellular hemibiotrophy and subcuticular intramural necrotrophy (Gomes et al., 2009; O'Connell et al., 2000; Perfect et al., 1999) (Fig. 4).

In intercellular hemibiotrophic infections, a symptomless biotrophic phase is followed by a destructive necrotrophic one, during which symptoms become apparent. Examples of pathogens employing this infection strategy are *Colletotrichum graminicola* Politis & Wheeler, 1973). *Colletotrichum gloeosporioides* (Ogle et al., 1990), and *Colletotrichum lindemuthianum* (Mercer et al., 1975; O'Connell et al., 1985). In the subcuticular intramural infection strategy, rather than penetrating the epidermal cell wall, the fungus grows under the cuticle and within the periclinal and anticlinal walls of epidermal cells (Arroyo et al., 2007; O'Connell et

Olive – Colletotrichum acutatum: An Example of Fruit-Fungal Interaction 257

Fig. 4. Intracellular hemibiotrophic-like infection structures in infected olive fruit. Penetration of epidermal cells and fungal development inside the host were observed. (**a**) The host membrane (arrow) encloses a globose infection vesicle without damaging the host plasma membrane. (**b**) and (**c**) Subcuticular infection vesicles were observed in susceptible 'Galega' (**b**) and resistant 'Picual' (**c**) olive fruit. During the early events of infection, hyphae grow inside the host cell wall of 'Galega' without penetrating the lumen. (**c**) Development of hyphae with internodes are marked with arrows. Scale bar represents 10 µm in all panels. HM - host membrane; GIV - globose infection vesicle; I - internodes; SCH - subcuticular hypha.

Functional genomics studies in species like *Olea europaea* L., where no sequence data are available, has a major constraint, which limits the screening of potentially transcript-derived fragments (TDFs) and their function. The identification and the role of genes involved in olive polygenic resistance is complex and remain unknown. Current knowledge about *Colletotrichum acutatum*-olive interaction, in susceptible and resistant cultivars and its functional genomic impact on plant resistance is not yet sufficient to provide solid explanations. Data for model plants may direct strategies that are transferable to crop systems, even when there is a lack of sequencing information related to the crop under study, once they may provide guidelines to which direction studies may be conducted. Furthermore, *Colletotrichum acutatum*-strawberry (pathosystem model for *Colletotrichum acutatum* - plant interaction) interactions are still poorly understood making the task even

**3. Conclusion**

al., 2000; Wharton & Diéguez-Uribeondo, 2004). *Colletotrichum phomoides* (Bailey et al., 1992), *Colletotrichum capsici* (Pring et al., 1995) and *Colletotrichum circinans* (Bailey et al., 1992) behave in this manner*.* On olive fruits, a combination of both strategies has been reported, and results in intra- and intercellular colonization of fruits (Gomes et al., 2009) (Fig. 4). In this pathosystem *Colletotrichum acutatum* used hemibiotrophy and subcuticular colonization strategies to colonize 'Galega' that is *Colletotrichum acutatum* susceptible olive cultivar and 'Picual' that is *Colletotrichum acutatum* resistant olive cultivar.

Fig. 3. *Colletotrichum acutatum* infection structures in olive fruits. (**a**) Massive adhesion of fusiform spore on the susceptible cultivar (Galega) was observed at 48 hours after inoculation (hai). (**b**) Germinated and ungerminated spore on the fruit surface 48 hai; a penetration pore has differentiated under a mature appressorium and internal light spot (*ILS*) was observed at 72 hai. (**c**) Conidia (with a septum at the equatorial zone (arrow)) developed a germ tube at the end of which a pigmented fluorescing appressorium differentiated within 72 hai. (**d**) The development of one or more secondary conidia simultaneously was observed at 48 hai. Scale bar represents 20 µm in panel (**a**) 10 µm in panels (**b**) and (**d**) and 5 µm in panel (**c**) CL - host cuticle; MS - mesocarp; C - conidium; A appressorium; ILS - internal light spot; PP - penetration pore; GT - germ tubes; SP - septum; NC - new conidial formation.

**C**

Fig. 4. Intracellular hemibiotrophic-like infection structures in infected olive fruit. Penetration of epidermal cells and fungal development inside the host were observed. (**a**) The host membrane (arrow) encloses a globose infection vesicle without damaging the host plasma membrane. (**b**) and (**c**) Subcuticular infection vesicles were observed in susceptible 'Galega' (**b**) and resistant 'Picual' (**c**) olive fruit. During the early events of infection, hyphae grow inside the host cell wall of 'Galega' without penetrating the lumen. (**c**) Development of hyphae with internodes are marked with arrows. Scale bar represents 10 µm in all panels. HM - host membrane; GIV - globose infection vesicle; I - internodes; SCH - subcuticular hypha.

### **3. Conclusion**

256 Plant Breeding

al., 2000; Wharton & Diéguez-Uribeondo, 2004). *Colletotrichum phomoides* (Bailey et al., 1992), *Colletotrichum capsici* (Pring et al., 1995) and *Colletotrichum circinans* (Bailey et al., 1992) behave in this manner*.* On olive fruits, a combination of both strategies has been reported, and results in intra- and intercellular colonization of fruits (Gomes et al., 2009) (Fig. 4). In this pathosystem *Colletotrichum acutatum* used hemibiotrophy and subcuticular colonization strategies to colonize 'Galega' that is *Colletotrichum acutatum* susceptible olive cultivar and

**<sup>b</sup> <sup>C</sup> <sup>A</sup>**

**ILS**