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Construction of a linkage map of the Rennell Island Tall coconut type (Cocos nucifera L.) and QTL analysis for yield characters P. Lebrun, L. Baudouin, R. Bourdeix, J. Louis Konan, J.H.A. Barker, C. Aldam, A. Herrán, and E. Ritter

Abstract: AFLP and SSR DNA markers were used to construct a linkage map in the coconut (Cocos nucifera L.; 2n = 32) type Rennell Island Tall (RIT). A total of 227 markers were arranged into 16 linkage groups. The total genome length corresponded to 1971 cM for the RIT map, with 5–23 markers per linkage group. QTL analysis for yield characters in two consecutive sampling periods identified nine loci. Three and two QTLs were detected for number of bunches and one and three QTLs for number of nuts. The correlation of trait values between characters and evaluation periods is partially reflected in identical QTLs. The QTLs represent characters that are important in coconut breeding. The cosegregation of markers with these QTLs provides an opportunity for marker-assisted selection in coconut breeding programmes. Key words: coconut, QTL, AFLP, SSR, marker-assisted selection (MAS). Résumé : Des marqueurs AFLP et microsatellites ont été employés afin de produire une carte génétique du cocotier (Cocos nucifera L.; 2n = 32) de type « Rennel Island Tall » (RIT). Au total, 227 marqueurs ont été assemblés en 16 groupes de linkage. La longueur totale de la carte RIT totalisait 1971 cM et le nombre de marqueurs par groupe de linkage variait entre 5 et 23. Une analyse QTL de caractères contribuant au rendement, tel que mesuré lors de deux périodes d’échantillonnage, a permis d’identifier neuf locus. Trois et deux locus ont été identifiés pour le nombre de régimes tandis qu’un et trois locus ont été identifiés pour le nombre de noix. La corrélation entre les valeurs phénotypiques pour ces caractères et les périodes d’échantillonnage est partiellement reflétée par l’identification de QTL communs. Ces QTL représentent des caractères qui sont importants en amélioration génétique du cocotier. La co-ségrégation de marqueurs avec ces QTL rend possible la sélection assistée dans le cadre de programmes d’amélioration génétique du cocotier. Mots clés : cocotier, QTL, AFLP, microsatellite, sélection assistée par les marqueurs (MAS). [Traduit par la Rédaction]

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Introduction Coconut (Cocos nucifera L.) is, besides oil palm, the most important perennial oil plant of the tropics. Coconut oil is the major economic product of coconut processing and is particularly valuable, owing to its high lauric acid content (Jones 1991). In addition, coconut is of special importance for rural communities, since all parts of the coconut palm, from the root to the frond, are utilised for food and non-food purposes (Persley 1992). Consequently, this crop has been termed the “tree of life”.

Besides heavy competition for coconut oil in the world market, coconut production is also affected by different biotic and abiotic stress factors (De Taffin 1998). A great variety of pathogens, including fungi (Phytophthora), trypanosomes (heartrot), nematodes (red ring), DNA viruses (Vanuatu foliar decay), viroids (Cadang Cadang), and mycoplasma (lethal yellowing), cause heavy losses in coconut production. Depending on the growing region, the coconut also has to contend with abiotic constraints, such as drought, cold, and strong winds. In view of these problems, it is necessary to improve

Received March 26, 2001. Accepted June 29, 2001. Published on the NRC Research Press Web site at http://genome.nrc.ca on September 25, 2001. Corresponding Editor: K.J. Kasha. P. Lebrun and L. Baudouin. Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), TA 80/03, avenue Agropolis, 34398 Montpellier Cédex, France. R. Bourdeix and J.L. Konan. Centre National de la Recherche Agronomique (CNRA), Station Marc Delorme, 07 B.P. 13 Abidjan 07, Côte d’Ivoire. J.H.A. Barker and C. Aldam. Institute of Arable Crop Research (IACR), Long Ashton Research Station, Department of Agricultural Sciences, University of Bristol, Long Ashton, Bristol BS41 9AF, United Kingdom. A. Herrán and E. Ritter.1 Neiker, Apartado 46, 01080 Vitoria, Spain. 1

Corresponding author (e-mail: [email protected]).

Genome 44: 962–970 (2001)

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DOI: 10.1139/gen-44-6-962

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coconut varieties by applying, as in many other crops, DNAmarker technology, to assist in and accelerate breeding programmes. Different types of DNA markers have already been applied in several biodiversity studies of coconut germplasm (Rohde et al. 1995; Ashburner et al. 1997; Duran et al. 1997; Lebrun et al. 1998, 1999; Perera et al. 1998). Furthermore, primers for microsatellites or simple-sequence repeats (SSRs) have been developed for coconut (Perera et al. 1999; Rivera et al. 1999; Teulat et al. 2000) and were used in our mapping experiment. The primer sequences for 11 additional SSR primer pairs are presented in this work. In previous studies, the availability of F1 mapping populations from controlled crosses allowed linkage maps of the East African Tall (EAT) and Laguna Tall (LAGT) coconut types to be constructed, based on inverse sequence tagged repeat (ISTR) markers (Rohde et al. 1999). This work was extended using different DNA marker types (including amplified fragment length polymorphisms (AFLPs), ISTRs, random amplified polymorphic DNA (RAPD), and interSSRs (ISSRs)), and several quantitative trait loci (QTLs) for early germination were detected (Herrán et al. 2000). In addition, QTLs for other traits, including leaf production and girth height, were identified for the same mapping population (Ritter et al. 2000). In this paper, we present the first linkage map of 16 linkage groups for a coconut type from the Solomon Islands, Rennell Island Tall (RIT). RIT is used in various breeding programmes across the world and is widely used as a male parent for commercial hybrids in the Pacific. In addition, the first QTL analyses for some yield characters are presented.

Materials and methods Plant material A set of coconut half-sib progenies from crosses between 12 Cameroon Red Dwarf (CRD) genotypes (genitor numbers PO4383–PO4394) and a common RIT pollen donor (P02664) was used as the mapping population. Half-sib families were composed of five or six genotypes each. Like most Dwarf coconuts, CRD is highly self-pollinating, and it was reasonable to consider it as a pure line. Moreover, as the distinctive light-orange colour of both its fruit and the petiole of its leaves is recessive, it is commonly used by coconut breeders to ensure trueness to type. As a result, the 67 genotypes descending from these crosses were considered as a single cross and used for linkage mapping and QTL analyses. Crosses to establish this population were performed in 1979; the resulting F1 seedlings were planted in the field in 1981, as part of progeny trial PBGC25, with the progeny number PB 1819. The trial is located in field M51 at the Marc Delorme Research Station (Centre National de la Recherche Agronomique, Ivory Coast) and has a balanced lattice design, with 16 treatments, five repetitions, and 14 palms per elementary plot. Genomic DNA was extracted from the youngest fully open leaf tissues, as described by Lebrun et al. (1998).

Molecular methods AFLP fragments were produced with 66 primer combinations, using different adapters as indicated in Table 1. AFLP analysis with EcoRI–MseI adapters was performed according to Vos et al. (1995). Amplification products were separated in denaturing polyacrylamide gels (6 or 8%). For the 24 primer combinations used with MseI–PstI adapters, AFLP analysis was performed as described in Teulat et al. (2000), using the magnetic-bead method for fragment selection, followed by a single selective PCR amplifi-

963 cation (Zabeau and Vos 1993). Amplification products were separated in denaturing polyacrylamide gels (4.5%). AFLP fragments were detected by autoradiography or using a LI-COR 4200-S1 DNA sequencer. In the latter case, primers were labelled with the fluorescent infrared dye IRD800 (LI-COR, Lincoln, Nebr., U.S.A.) and fragment analysis was recorded by a laser system as described by the manufacturer (LI-COR 1997). For radioactive detection, dried gels were exposed to Kodak Biomax MR-1 film for 18 h or to Fuji RX film for 3 days (Teulat et al. 2000). The SSR primer pairs developed by Rivera et al. (1999) (SSR primer pairs Nos. 1–13; Table 2A) were used to screen the mapping population as described in Teulat et al. (2000), except that 2µL aliquots of amplification products were separated in 6% denaturing polyacrylamide gels using 96-well combs. The forward primer was radio-labelled with [γ-33P]ATP. After drying, gels were exposed to KODAK XLS film for 72 h. The other primer pairs in Table 2A were obtained by Lebrun according to Kijas et al. (1994). Their sequences are given in Table 2B. PCR reactions and the detection of amplification products were performed as described in Teulat et al. (2000) and above, but always using an annealing temperature of 51°C. Heterologous probes from rice, maize, or oil palm were used for restriction fragment length polymorphism (RFLP) analysis. Genomic DNA was digested with either EcoRI, SstI, or BglII, as specified in Table 2C. The radioactive detection method using 32P is described in Lebrun et al. (1999).

Data analysis and linkage mapping Polymorphic DNA fragments were scored for presence or absence in parents and F1 progenies. Only fragments that were present in the RIT parent and absent in all CRD parents were considered; thus, the mapping population could be evaluated as a backcross. Linkage analysis between marker fragments, estimation of recombination frequencies, determination of linear orders between linked loci, including multipoint linkage analysis, and the expectation–maximization (EM) algorithm for handling missing data (Lander et al. 1987; Little and Rubin 1987) were performed as described by Ritter et al. (1990) and Ritter and Salamini (1996). The MAPRF program (Ritter and Salamini 1996) was applied for the computational methods.

QTL analysis The mapping population was examined for two yield characters—number of bunches and number of nuts—in two consecutive evaluation periods. As vegetative propagation is not effective in coconut, each genotype was represented by only one tree. Following standard research protocols (Santos et al. 1995), these characters were observed six times per year. These observed values were averaged on a yearly basis over two consecutive periods: juvenile (July 1985 – June 1989) and mature (July 1989 – June 1996). Finally, these observed averages were corrected for environmental bias, using the average of elementary plots and of repetitions from the design mentioned above as covariables, according to Baudouin et al. (1987). To map QTLs, the least square interval mapping methods developed for backcross progeny, as described by Knapp et al. (1990) and Knapp and Bridges (1990), were used and applied to consecutive intervals of the linkage map. SAS software (SAS Institute Inc. 1989), in particular the procedure PROC NLIN, was used for computational analysis. In addition, QTL analyses were performed at single-marker loci, following the procedure of Soller et al. (1976). Progeny genotypes were divided into two subgroups, based on the presence or absence of a fragment. The trait means of these two marker classes were tested for significant differences with a twosample t test, implemented in SAS. © 2001 NRC Canada



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Table 1. Polymorphisms specific for the Rennell Island Tall (RIT) coconut type obtained with the AFLP primer combinations Primer combination No.a

Primer combination

No. of segregating bands specific for the RIT parentb

31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84

Eaac/Mcag Eaac/Mcta Eaac/Mctc Eaac/Mctg Eaac/Mctt Eaag/Mcta Eaag/Mctc Eaca/Mcag Eaca/Mcat Eaca/Mcta Eagc/Mcaa Eagc/Mcag Eagc/Mcat Eagc/Mctc Eagg/Mcaa Eagg/Mcac Eagg/Mcag Eagg/Mcta Eagg/Mctc Eagg/Mctg Eagg/Mctt Egaa/Mtac Egaa/Mtag Egaa/Mtca Egaa/Mtcc Egaa/Mtcg Egaa/Mtct Egaa/Mtga Egaa/Mtgc Egaa/Mtgg Egaa/Mtta Egaa/Mttc Egac/Mtgg Egac/Mtgt Egac/Mtta Egac/Mttc Egac/Mttg Egac/Mttt Paa/Maca Pac/Maca Pca/Maca Pcc/Maca Paa/Macc Pca/Macc Pcc/Macc Paca/Mgaa Pacc/Mgaa Pacg/Mgaa Pact/Mgaa Paa/Mgaa Pca/Mgaa Paa/Mttg Pac/Mttg Pca/Mttg

9 1 7 3 8 3 3 3 2 2 1 1 3 1 1 4 1 1 2 3 2 3 6 9 5 2 3 2 4 2 3 2 4 4 5 2 3 1 5 3 4 3 3 3 3 3 3 2 2 4 4 2 1 3

Table 1 (concluded). Primer combination No.a 85 86 87 88 89 90 91 92 93 94 95 96

Primer combination Pcc/Mttg Egag/Mtgt Egag/Mttt Egag/Mtta Egag/Mttg Paa/Mctt Paa/Mctc Pca/Mctc Paa/Mcta Pca/Mcta Paa/Mccg Paa/Mggc

No. of segregating bands specific for the RIT parentb 2 2 2 2 2 4 5 1 3 2 4 3

Note: The total number of polymorphic bands was 201, the total number of primer combinations was 66, and the total number of distorted fragments was 13. a See also Fig. 1.

Results Generation of polymorphic DNA markers The number of AFLP fragments present in the RIT parent ranged from 42 to 115 (with an average of 81), depending on the primer combination. The number of CRD-parent fragments varied in a similar range, depending on the primer combination, with an average of 77 fragments. On average, 74 fragments were found in common between the RIT and CRD parents. On average, eight fragments were polymorphic between maternal trees, but four of them were also present in the pollen donor; however, these fragments did not segregate in the progeny. On average, polymorphic AFLP primer combinations generated three segregating fragments (ranging from one to nine in the set of primer combinations) that were only present in the paternal tree (Table 1). Several primer combinations did not provide any polymorphic fragments. The obtained polymorphisms did not differ significantly for primer combinations with EcoRI–MseI or MseI–PstI adaptors. The 66 polymorphic AFLP primer combinations generated a total of 201 segregating fragments for use in linkage mapping. In addition, six heterologous RFLP probes (from rice, maize, and oil palm) and the 24 SSR primer pairs used in this study (Table 2) each amplified a single locus. Therefore, a total of 231 segregating polymorphic DNA markers were available for map construction. Only 13 fragments showed moderate but significant deviations from the expected segregation ratio of 1:1 (absence vs. presence). These distortions occurred randomly and were not associated with particular primer combinations. They also did not belong to extended chromosomal regions. Construction of linkage maps Initially, a logarithmic odds (LOD) score threshold value of 4.0 for the recombination frequency between at least one pair of fragments was used to establish linkage subgroups. Fragments composing each linkage group were ordered by minimizing the sum of LOD scores of recombination fre© 2001 NRC Canada



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Table 2. Characteristics of the markers used for linkage mapping and their map locations. (A) Characteristics of the SSR markers. SSR No.

Name

Repeat motif

Size of amplification products

Map location

1 2 3 4 5 6 7 8a 9 10 11 12a 13 14 15 16 17 18 19 20 21 22 23 24

CNZ03 CNZ05 CNZ09 CNZ12 CNZ23 CNZ24 CNZ26 CNZ29 CNZ33 CNZ40 CNZ42 CN11E10 CNIC6 CnCirA4 CnCirB3 CnCirB11 CnCirB12 CnCirC5 CnCirC9 CnCirC11 CnCirD1 CnCirD8 CnCirE1 CnCirF3

(GA)7 (CT)17(GT)7 (CT)13(CA)6 (CT)19(CA)8 (CT)15 (GA)18 (CT)19(GT)19 (GT)17(GA)19 (GT)22(GA)14 (GT)11 (CT)20 (CT)16 (GT)22(GA)14 (GT)11TT(GT)5 (TTA)3TA (CA)8 (GT)8(GA)17 (CT)13(CA)7 (CA)20(GA)15 (TG)10(GA)27 (CA)18(CGCA)8 (GT)9 (TC)12(GT)9 (AC)30 (CA)11 (CT)15(CA)17

92 and 94 156 and 168 121, 127, and 216 and 228 146, 162, and 251, 255, and 223, 231, and 131, 141, and 152 and 168 143, 153, and 163, 165, and 129, 139, and 177 and 181 293 292 225 168 133 214 221 204 247 228 381

5 5 1 Unmapped 10 10 10 2 2 10 10 2 2 12 3 10 8 4 4 15 4 8 4 4

Forward primer (5′→3′) ATATAGATGTTGTTGGTTACTGGA CATCTTGCTTTTCACCATCC TCTGCATCCCTTCTTTATTA GCTCTTCAGTCTTTCTCAA ACCAACAAAGCCAGAGC CAGAAAGGAGAAAGGAAAT TGTTATTTTGTTATTTCAGG GGGAGGGGAGCGAGACTATG GCTCTTGATGTGGCTGCT CTTGTTATGTCGTTTGTTG TGCCCTACTCCCTCAT

Reverse primer (5′→3′) ACCAGCCTTTTCCTTCG AATACTGTGCGGTTTTGCTT TTGTCTTTCTTTATTCTATTGG CTGTATGCCAATTTTTCTA GCAGCCACTACCTAAAAAG CTACGATAGAGGAATGAGC TCACCATCTTCTCAGTTTC AATTCAGGCCAACACCAGACC AGGCGTGTTGAGATTGTGA CTGAGACCCTGTTGATGT TACCACATAACAGAAACAAGATAA

Origin cDNA cDNA cDNA cDNA cDNA cDNA

Map location 15 7 11 5 5 6

139 164 259 237 145 155 167 143

(B) Sequences of SSR primer pairs.b SSR No. 14 15 16 17 18 19 20 21 22 23 24

Name CnCirA4 CnCirB3 CnCirB11 CnCirB12 CnCirC5 CnCirC9 CnCirC11 CnCirD1 CnCirD8 CnCirE1 CnCirF3

(C) Characteristics of RFLP probes. Probe name Eg5/E Eg22/S Eg39/B c1677/E Eg6/S CSU94/S a b

Restriction enzyme EcoRI SstI BglII EcoRI SstI SstI

Elaeis Elaeis Elaeis rice Elaeis maize

guineensis guineensis guineensis guineensis

Primer pairs corresponding to SSR numbers 8 and 12 amplify the same locus. Primer sequences for SSRs 1–13 were published in Teulat et al. (2000).

quencies for alternative orders. Finally, subgroups were connected based on the smallest recombination frequencies between the lateral markers of each linkage group but using a minimum LOD score value of 2.0. In this way, a linkage

map of 16 linkage groups was established for the RIT parent of the mapping population (Fig. 1). The characteristics of this map are summarised in Table 3. Linkage groups of the RIT map contained 5–23 markers each and were between © 2001 NRC Canada



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Fig. 1. Linkage map of Rennell Island Tall coconut genotype PO2664 and location of the QTLs for number of bunches and number of nuts in two evaluation periods (Qxx, in boxes). SSR and RFLP markers are underlined. AFLP markers are indicated with their primer combination number (see Table 1) and corresponding base pair numbers (migration values). Distances are given in centi-morgans (Kosambi units; Kosambi 1944). See also Tables 2, 3, and 4 for details of markers, linkage groups, and QTLs.

52.1 and 191.7 cM in length (Table 3). The total map length was 1971 cM. In total, 227 of the 231 markers could be mapped to the 16 linkage groups. The residual four markers showed identical recombination frequencies with different distant markers of the same linkage group. Therefore, it was not possible to establish a correct order unambigously and they were discarded. All SSR markers, with the exception of CNZ12, were mapped. Their map locations and other characteristics are given in Tables 2A and 2C. The number of SSR markers per linkage group varied between one and six. However, 4 of the 16 linkage groups do not contain any SSR markers. QTL analyses On average, progeny genotypes produced 9.37 bunches/year (BN1) in the first evaluation period and 13.55 bunches/year (BN2) in the second (Table 4). The corresponding values for number of nuts were 82.2 (NN1) and 121.5 (NN2) nuts/year. The trait number of nuts also exhibited a higher degree of variation within the population, as shown by the range of minimum and maximum values and the coefficients of variation in Table 4. All characters showed highly significant positive correlations except for number of bunches in the first evaluation period and number of nuts in the second. The highest correlations were found for numbers of bunches and numbers of nuts in identical sampling periods. When scanning all marker intervals in the obtained linkage map, three and two QTLs with error probabilities smaller than 5% were detected for number of bunches in the first and second evaluation periods, respectively (Table 4; Fig. 1). All were located on different linkage groups and explained between 7.1 and 21.1% of the total phenotypic variance. They had relatively small effects (i.e., QTL–allele differences), around 0.1 bunches/year, but error probabilities for the null hypothesis of no QTLs ranged between 3.8 and 0.1% (Table 4). In total, three QTLs were detected for number of nuts in the two evaluation periods and were located on three different linkage groups. They explained between 11.8 and 21.3% of the total variation and showed average effects of between 4.7 and 14 nuts per genotype. One QTL for number of nuts mapped to a similar position in both sampling periods (Q3a and Q4a; 5.1 cM apart). The correlation of the trait values is reflected in the similar positions of two QTLs for number of nuts and number of bunches in linkage groups II and X.

Discussion Genetic design As for many trees, coconut breeding is a costly and lengthy process; testing a single progeny requires observing at least 0.5 ha (approximately 70 palms) for at least 10 years after planting (Santos et al. 1995). Under these conditions, any method that can increase the efficiency of breeding is welcome. However, molecular methods have only recently

Table 3. Characteristics of the Rennell Island Tall coconut type linkage map. Linkage group No.

Name

Length (cM)

No. of markers

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Total

I II III IV V VI VII VIII IX X XI XII XIII XIV XV XVI

106.0 146.6 98.1 177.4 112.5 59.6 170.4 151.3 52.1 167.6 191.7 147.1 93.3 79.1 162.4 55.8 1970.9

16 23 19 18 9 7 13 16 16 20 17 21 9 8 10 5 227

been introduced into coconut breeding. This is partly due to the rarity of suitable experimental designs; isolated hand pollination techniques have been used for a long period and, in addition, the multiplication rate (number of progenies that can be obtained from a single mother palm in a year) is low. To overcome this difficulty, progeny trials have been designed using half-sib families that originate from the same Tall coconut pollen donor and several Dwarf mother palms of the same cultivar. Such progeny trials have been planted since 1977 at the Marc Delorme Research Station and some other coconut-breeding stations. Most Dwarf cultivars can be treated as pure lines; their rate of self-pollination is high and it is easy to eliminate off-types using petiole colour as a marker. Despite limited sample size and the consequent limited precision of QTL detection, the material used in this study had the merit of being observed over many years, thus offering the opportunity of identifying QTLs for yield traits. The present study confirmed the genetic uniformity of the CRD and the suitability of such progeny trials for genetic mapping and QTL identification in coconut. In future studies, QTL detection could be enhanced by compounding results obtained with several similar half-sib families involving the same male parent. In each of these families, the set of female parents would comprise several palms from the same Dwarf cultivar (the Dwarf cultivar being different for each family). Besides this increase in precision, using different Dwarf cultivars would allow the influence of the detected QTLs to be tested in a varying genetic context. Generation of segregating polymorphic DNA markers A large number of amplification products was obtained using AFLPs, but only a relatively low percentage (3.4%) of © 2001 NRC Canada


(A) Trait characteristics. Trait

Mean

Minimum

BN1 9.37 9.03 BN2 13.55 13.27 NN1 82.17 77.77 NN2 121.53 104.09 (B) Correlation coefficients.a BN1 BN2 BN1 — 0.36 (0.72) BN2 — NN1 NN2 (C) Results of the QTL analyses. Trait QTL Effect BN1 Q1a 0.10 Q1b 0.12 Q1c 0.13 BN2 Q2a 0.11 Q2b 0.09 NN1 Q3a 14.0 NN2 Q4a 6.6 Q4b 4.7 Q4c 5.7

Maximum

Coefficient of variation

9.74 13.76 86.01 140.01

1.84 0.78 2.18 5.59

NN1 0.81 (>0.01) 0.51 (>0.01) —

NN2 0.23 (8.37) 0.73 (>0.01) 0.37 (0.45) —

Interval 64/120–56/154 91/435–66/225 52/490–54/120 69/540–55/198 79/374–37/600 38/260–91/670 91/670–90/300 74/275–69/261 76/240–79/374

Chromosome No.b III IX XII II X II II VII X

Interval length (cM) 10.0 3.1 14.3 10.6 4.8 6.5 3.2 11.3 3.2

Positionc 20.0 0 14.3 10.2 0 1.4 0 14.1 1.7

Probabilityd (%) 1.3 3.8 2.8 0.1 1.9 3.2 0.1 2.8 1.2

R2e (%) 7.1 10.5 8.9 21.1 15.4 11.8 21.3 10.8 16.6

Note: BN1, number of bunches 1985–1988; BN2, number of bunches 1989–1996; NN1, number of nuts 1985–1988; NN2, number of nuts 1989–1996. a Values in parentheses are significance (%). b Location of interval on linkage group (Table 3). c Position of QTL with respect to the upper flanking marker of the interval (Fig. 1). d Probability for the null hypothesis of no QTL. e Portion of the total variance explained by the QTL.


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Table 4. Trait characteristics and their correlations and the results of the QTL analyses.


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RIT-specific fragments segregated in the mapping population. Even if 50% of the fragments that were polymorphic between CRD parents were considered, the maximum level of segregating fragments would have been only 5.8%. This low polymorphism is in accordance with that observed in previous studies using Laguna Tall and Malayan Yellow Dwarf (MYD) parents and much lower than that observed in many other crops, as discussed by Herrán et al. (2000). In this study, the total number of AFLP fragments was similar for the parental Dwarf and Tall genotypes of the mapping population. Although CRD was collected in Cameroon, this cultivar belongs to a small group of Dwarf coconuts that have in common the traits low growth, short internodes, an early bearing habit, and a strong tendency toward self-pollination. This latter characteristic is confirmed by the virtually uniform genetic structure of the mother palms. Only a small number of AFLP bands were polymorphic and these did not segregate in the progeny. RIT belongs to the main group of Tall coconut cultivars, which ranges from Southeast Asia toward the South Pacific and is the source of the Dwarf coconuts (Lebrun et al. 1999). While Tall coconuts are predominantly outcrossing, RIT originates from a small island in the South Pacific and the effective population size is thought to be limited. In consequence, it is not surprising that 93% of the generated DNA fragments were monomorphic between the two parents, indicating that they share a large number of identical loci and show a high degree of homozygosity. Arrangement of DNA markers into coconut linkage maps The analysis of segregating DNA markers established 16 independent linkage groups for the RIT coconut genotype (i.e., lateral markers were not statistically linked to any other lateral marker of any other linkage group). These 16 linkage groups may correspond to the 16 chromosomes of the haploid coconut genome (2x = 32). The inclusion of numerous SSR markers in the linkage map is of particular interest. This codominant marker type is of great value, owing to its easy transferability to different genetic backgrounds and easy application through PCR technology (Risterucci et al. 2000). This is the first study in which SSR markers have been integrated into a coconut linkage map. Since the SSR markers amplified only single loci and can be mapped—if heterozygous—to identical locations in other coconut mapping populations, it should be possible to assign homologous chromosomes in different maps and align them. In this way, the information in different maps could be combined and the number of markers available per coconut chromosome could be increased. Currently, SSR markers are located on only 12 of the 16 chromosomes and, therefore, additional SSR markers are required to achieve this goal. It would also be convenient to compare map locations of comigrating AFLP fragments in different studies, to analyse possible transferability of this marker type between different genetic backgrounds. The total map length for coconut was found to be relatively large but of similar magnitude to that found in previous studies (Herrán et al. 2000). In addition, the low percentage of distorted markers was confirmed in this study.

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Since aberrant segregation ratios might be related to the introgression of wild species, apparently “normal” coconut genotypes were used for the cross that constituted our mapping population, as discussed by Herrán et al. (2000). The amount of nuclear DNA is also very large in coconut, compared with other monocot species (Röser et al. 1997), and could explain the relatively large size of the coconut map. QTL analysis As mentioned above, QTL analysis was performed by single marker t tests and interval regression involving four marker classes. The QTLs listed in Table 4 are only those detected by interval mapping that were also highly significant in t tests. Several additional significant trait mean differences were discarded, since this approach is less sensitive, particularly with a small sample size, and does not allow estimation of the recombination frequency between the marker and the QTL (Lander and Botstein 1989). QTL analyses measure the overall differences of paternal quantitative trait alleles interacting with maternal quantitative trait alleles. Considering the composition of the half-sib population, different maternal quantitative trait alleles might be involved. Considering the structure of the mapping population, the reduced progeny size, and the small degree of variation present in certain traits, the detected loci may represent main QTLs for general use in coconut breeding in this specific genetic background, as previously discussed by Herrán et al. (2000). However, the transferability of these QTLs has to be verified in other progenies from different genetic backgrounds. The QTLs detected in this study point to the genomic locations of genes for important yield characters. Molecular markers closely linked to this trait will provide the opportunity to select promising genotypes at early seedling stages through marker-assisted selection (MAS). For crosses involving the same pollen donor (PO2664), the flanking markers indicated for the QTL intervals in Table 4 could be used for this purpose. In coconut, QTLs are now available for the traits early germination (Herrán et al. 2000), girth height, and leaf production (Ritter et al. 2000) and for the yield characters in our study. However, for further exploitation of MAS in coconut breeding, it will be necessary to establish additional mapping populations segregating for important traits such as early flowering, tolerance to biotic and abiotic stress, copra yield and quality, and other characters of interest. Furthermore, these analyses should be performed in several different crosses, to establish QTLs in different genetic backgrounds. This will facilitate comparative QTL analyses in terms of the location of QTLs and the effects of quantitative trait alleles and their possible interaction.

Acknowledgements The Bureau for the Development of Research on Tropical Perennial Oil Crops (BUROTROP) and the International Coconut Genetic Resources Network (COGENT) played important roles in the origin of this paper. This research was supported, in part, by European Community Directorate General XII (EC DG XII) under contract ERBIC18-CT97-0207 of the International Cooperation with Developing Countries (INCO-DC) programme. The Institute of © 2001 NRC Canada



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Arable Crop Research receives grant-aided support from the Biotechnology and Biological Sciences Research Council of the United Kingdom.

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