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Genetic diversity and parentage of cacao (Theobroma cacao L.) populations from Ghana using single nucleotide polymorphism (SNP) markers

Published online by Cambridge University Press:  16 October 2024

Kwabena Asare Bediako*
Affiliation:
Cocoa Research Institute of Ghana, New Tafo-Akim, Ghana
Francis Kwame Padi
Affiliation:
Cocoa Research Institute of Ghana, New Tafo-Akim, Ghana
Ebenezer Obeng-Bio
Affiliation:
Cocoa Research Institute of Ghana, New Tafo-Akim, Ghana
Atta Ofori
Affiliation:
Cocoa Research Institute of Ghana, New Tafo-Akim, Ghana
*
Corresponding author: Kwabena Asare Bediako; Email: asbed63@gmail.com
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Abstract

Ortet selection remains an integral component of cacao breeding programme to develop improved clones and expand the gene pool of available germplasm. This study assessed the population structure of 168 cacao clones developed recently from selected ortets in on-station and on-farm progeny trials in Ghana using 45 SNP markers. Selection of ortets was primarily based on high bean yield, high yield efficiency, adaptability to marginal growing conditions, and low incidence of black pod and cocoa swollen shoot virus diseases. Additionally, 58 SNPs were employed to verify the parentage of 752 bi-clonal seedlings supplied to farmers for commercial plantations. Pairwise multilocus matching based on 45 SNPs showed that the 168 clones were all distinct. Overall, the clones had moderate genetic diversity (He = 0.349 ± 0.022) and shared ancestry with Marañón, Guiana, Contamana, Iquitos, Amelonado, Trinitario, Nanay and Purús based on Bayesian clustering, principal coordinates, and parentage analyses. Parentage analysis of bi-clonal seedlings assigned parent-offspring trios (>80% confidence level) to 65.2% of the farmers' varieties based on breeder's active clone collection. The results of the parentage analysis suggested the existence of mislabelled clones in the seed gardens, necessitating the need for correct clone identification or rogueing. Taken together, this study presents a new group of cacao genetic resources with potential to broaden the gene pool of cacao in cacao improvement programmes. Further, the study conveys evidence of the need for countries with established seed garden systems to constantly monitor the genetic purity of seedlings produced from the seed gardens.

Type
Research Article
Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press on behalf of National Institute of Agricultural Botany

Introduction

Cacao (Theobroma cacao L.) is cultivated in the humid tropics for its fruits (pods) from which the seeds (beans), following fermentation and drying are used to produce chocolate and other confectionery products. Cacao from the South American Amazon basin as its primary centre of diversity (Cheesman, Reference Cheesman1944; Schultes, Reference Schultes and Stone1984; Bartley, Reference Bartley2005) has been repeatedly introduced into various cacao growing countries across the globe (Schultes, Reference Schultes and Stone1984; Kennedy and Mooleedhar, Reference Kennedy and Mooleedhar1993; Lockwood and End, Reference Lockwood and End1993; Bartley, Reference Bartley2005). Presently, West Africa contributes over 70% to the global cacao production, with Cote d'Ivoire and Ghana being the major producing countries (ICCO, 2021).

Cultivation of cacao in Ghana commenced in the 19th century where the available cultivars were mainly of Amelonado origin and uniform in most economic traits (Posnette, Reference Posnette1943). In 1938, research into cacao formally began in Ghana through the establishment of the West Africa Cacao Research Institute following the destruction of cacao by the cocoa swollen shoot virus disease (CSSVD) and the difficulties associated with the crop's establishment resulting from primary forest cover loss (Posnette, Reference Posnette1941). To broaden the genetic base of the existing West African cacao germplasm composed mainly of Amelonado, different cacao introductions have occurred (Posnette, Reference Posnette1951; Glendinning, Reference Glendinning1957; Lockwood and Gyamfi, Reference Lockwood and Gyamfi1979; Abdul-Karimu et al., Reference Abdul-Karimu, Adomako and Adu-Ampomah2006). Some of these introductions were evaluated for agronomic performance and promising clones recommended as parents for production of hybrids for farmers (Posnette, Reference Posnette1951; Glendinning, Reference Glendinning1964, Reference Glendinning1966; Lockwood, Reference Lockwood1971; Adomako et al., Reference Adomako, Allen and Adu-Ampomah1999, Reference Adomako, Padi, Opoku, Assuah, Domfeh and Owusu-Ansah2007).

Based on the classification of cacao by Motamayor et al. (Reference Motamayor, Lachenaud, da Silva e Mota, Loor, Kuhn, Brown and Schnell2008), the available cacao germplasm (about 1000 clones) in Ghana was separated into eight genetic groups; namely, Nanay, Iquitos, Guiana, Amelonado, Trinitario, Purús, Contamana/Scavina and Marañón (Padi et al., Reference Padi, Ofori, Takrama, Djan, Opoku, Dadzie, Bhattacharjee, Motamayor and Zhang2015). The authors further observed that the base of the farmers' varieties in Ghana has been limited to few clones from only four genetic groups. Besides the narrow genetic base, the farmers' varieties were released many years ago (Thresh et al., Reference Thresh, Owusu, Boamah and Lockwood1988; Abdul-Karimu et al., Reference Abdul-Karimu, Adomako and Adu-Ampomah2006). The large-scale production of these varieties amidst changing climatic conditions (Sala et al., Reference Sala, Cilas, Gimeno, Wohl, Opoku, Găinuşă-Bogdan and Ribeyre2021) could partly explain the low average yields of 400 kg/ha observed in farms in Ghana (Aneani and Ofori-Frimpong, Reference Aneani and Ofori-Frimpong2013). Therefore, there is need to broaden the genetic base of the farmers' varieties by introducing superior clones of diverse genetic backgrounds in the seed gardens for production of improved varieties with better adaptation and yield. To this end, a recurrent selection programme involving superior clones in the available germplasm (largely from underrepresented genetic groups) was implemented, to identify new clones with good combining abilities for survival, vigour, precocity, yield, and disease resistance (Padi et al., Reference Padi, Ofori and Arthur2017b, Reference Padi, Domfeh, Arthur and Ofori2018). On the basis of the selection theory by Simmonds (Reference Simmonds1996), which suggests that the best clones are more frequently obtained in the best families as confirmed by Padi et al. (Reference Padi, Adu-Gyamfi, Akpertey, Arthur and Ofori2013a, Reference Padi, Takrama, Opoku, Dadzie and Assuah2013b), promising individual trees (ortets) were selected from families showing outstanding performance for a number of agronomic traits. Assessment of genetic diversity would be useful in revealing the genetic relationships among the current selections to guide their effective conservation, management, and utilization in the cacao breeding programme.

In Ghana and other cacao growing countries in West Africa such as Côte d'Ivoire, Nigeria and Cameroon, cacao planting materials are supplied to farmers as seed pods from established seed gardens planted with recommended parental clones. At present, there are about 26 cacao seed garden stations in Ghana being managed by the Seed Production Division (SPD) of the Ghana Cocoa Board. Each seed garden station is generally planted with between four and six recommended parental clones which are manually pollinated to produce seedling varieties of good agronomic performance for farmers. Padi et al. (Reference Padi, Ofori, Takrama, Djan, Opoku, Dadzie, Bhattacharjee, Motamayor and Zhang2015) observed that 2 to 100% of trees in clonal plots sampled across six cacao seed gardens in Ghana were mislabelled. More importantly, studies on cocoa (Padi et al., Reference Padi, Ofori, Takrama, Djan, Opoku, Dadzie, Bhattacharjee, Motamayor and Zhang2015) and coffee (Akpertey et al., Reference Akpertey, Padi, Meinhardt and Zhang2020) revealed that progenies derived from mislabelled or pollen contaminated clones had reduced vigour and number of pods per tree relative to those with correct parentage. For this reason, it is essential to frequently monitor the genetic purity of seedling varieties produced in the seed gardens and implement measures, where necessary, to maintain the genetic integrity of varieties distributed to farmers.

Single nucleotide polymorphism (SNP) markers have become the marker of choice for genetic studies in T. cacao due to their cost-effectiveness, high abundance in the genome and amenability to high-throughput automation (Gupta et al., Reference Gupta, Roy and Prasad2001; Mammadov et al., Reference Mammadov, Aggarwal, Buyyarapu and Kumpatla2012). In recent times, the effectiveness of SNP fingerprinting in improving the efficiency of variety development and recommendations in cacao breeding programmes has been undoubtedly proven in cacao accessions in Honduras and Nicaragua (Ji et al., Reference Ji, Zhang, Motilal, Boccara, Lachenaud and Meinhardt2012), Indonesia (Lukman et al., Reference Lukman, Susilo, Dinarti, Bailey, Mischke and Meinhardt2014), Ghana (Padi et al., Reference Padi, Ofori, Takrama, Djan, Opoku, Dadzie, Bhattacharjee, Motamayor and Zhang2015), Puerto Rico (Cosme et al., Reference Cosme, Cuevas, Zhang, Oleksyk and Irish2016), Colombia (Osorio-Guarín et al., Reference Osorio-Guarín, Berdugo-Cely, Coronado, Zapata, Quintero, Gallego-Sánchez and Yockteng2017), Costa Rica (Mata-Quirós et al., Reference Mata-Quirós, Arciniegas-Leal, Phillips-Mora, Meinhardt, Motilal, Mischke and Zhang2018), Uganda (Gopaulchan et al., Reference Gopaulchan, Motilal, Bekele, Clause, Ariko, Ejang and Umaharan2019), Dominica (Gopaulchan et al., Reference Gopaulchan, Motilal, Kalloo, Mahabir, Marissa, Joseph and Umaharan2020), tropical Americas (Gutiérrez et al., Reference Gutiérrez, Martinez, Zhang, Livingstone, Turnbull and Motamayor2021), and north Peru (Bustamante et al., Reference Bustamante, Motilal, Calderon, Mahabir and Oliva2022). These authors used varying number of informative SNP markers ranging from 44 to 219 in achieving different objectives, including identification of mislabelled/duplicated accessions, genetic diversity, ancestry, population structure and parentage analyses, and construction of core collections in cacao.

The objectives of this study were to (1) determine the population structure and parentage of locally bred cacao accessions in Ghana and (2) verify the parentage of seedling varieties produced in seed gardens for commercial plantations.

Materials and methods

Cacao sample analysis and SNP genotyping

Two populations, consisting of 168 ramets (pop1) and 752 bi-clonal seedlings (pop2) were sampled and genotyped in the current study. The ramets were developed from ortets selected from progeny trials established on-station and on-farm by the Cocoa Research Institute of Ghana (CRIG) from 2010 to 2021. Ortets were selected from families generated from parents with good combining abilities and showing outstanding performance for a number of agronomic traits including yield, growth, precocity and adaptability to marginal production conditions (Padi et al., Reference Padi, Takrama, Opoku, Dadzie and Assuah2013b, Reference Padi, Ofori and Akpertey2017a; Ofori et al., Reference Ofori, Padi, Akpertey, Asare Bediako, Arthur, Adu-Gyamfi, Nyadanu, Obeng-Bio and Anokye2023). Generally, ortets selection was based on visual inspection for number of pod-harvest scars, and absence of disease symptoms, including stem canker (caused by Phytophthora spp.), and cocoa swollen shoot virus and black pod diseases. The bi-clonal seedlings were generated through manual pollination by the Seed Production Division (SPD) of the Ghana Cocoa Board to supply planting material of recommended varieties for commercial plantations. Additionally, 41 international clones (from the CRIG germplasm) belonging to the 10 genetic groups described by Motamayor et al. (Reference Motamayor, Lachenaud, da Silva e Mota, Loor, Kuhn, Brown and Schnell2008) and Trinitario group were included as references for genetic structure and parentage analyses of local clones (Table 1). Sources of reference accessions and references for the genetic clusters are presented in Table S1.

Table 1. Reference cacao clones of 11 genetic groups used in genetic structure and parentage analyses for assignment of ancestry

Young leaves of tagged trees/seedlings were collected into labelled brown paper envelopes. Total genomic DNA was extracted from the leaf samples using CTAB protocol (Doyle and Doyle, Reference Doyle and Doyle1990). Concentration of DNA was determined with a NanoDrop spectrophotometer (Thermo Scientific, Wilmington, DE, USA). Genotyping was done at 45 and 60 SNP loci for the ramets and bi-clonal seedlings, respectively. The SNP markers were selected from 1560 candidate SNPs developed from cDNA sequences from a wide range of cocoa tissues (Argout et al., Reference Argout, Fouet, Wincker, Gramacho, Legavre, Sabau, Risterucci, Da Silva, Cascardo, Allegre, Kuhn, Verica, Courtois, Loor, Babin, Sounigo, Ducamp, Guiltinan, Ruiz, Alemanno, Machado, Phillips, Schnell, Gilmour, Rosenquist, Butler, Maximova and Lanaud2008). Selection of markers was based on their distribution across the ten chromosomes of cacao and levels of polymorphism in the previous experiments (Ji et al., Reference Ji, Zhang, Motilal, Boccara, Lachenaud and Meinhardt2012; Padi et al., Reference Padi, Ofori, Takrama, Djan, Opoku, Dadzie, Bhattacharjee, Motamayor and Zhang2015; Mata-Quirós et al., Reference Mata-Quirós, Arciniegas-Leal, Phillips-Mora, Meinhardt, Motilal, Mischke and Zhang2018). The discovery, design, and map positions of these SNP markers on the T. cacao consensus linkage map are given in Allegre et al. (Reference Allegre, Argout, Boccara, Fouet, Roguet, Bérard, Thévenin, Chauveau, Rivallan, Clement, Courtois, Gramacho, Boland-Augé, Tahi, Umaharan, Brunel and Lanaud2012). The list of the SNPs and their flanking sequences are presented in Table S2. Leaf samples (as desiccated leaf discs) from which DNA was extracted for SNP assay were obtained from each cacao accession in 96-well plates that were supplied by KBiosciences, UK. The subsequent SNP fingerprinting was performed at KBiosciences using the competitive allele-specific PCR KASPar chemistry (KBiosciences, Hoddesdon, Hertfordshire, UK).

Data analyses

Descriptive statistics for measuring informativeness of the SNP markers, including observed heterozygosity, expected heterozygosity, polymorphic information content (PIC) and the probability of identity among siblings (PID-sib) were estimated using CERVUS v3.0.7 (Kalinowski et al., Reference Kalinowski, Taper and Marshall2007). The PID-sib is defined as the probability that two sibling individuals drawn at random from a population have the same multilocus genotype (Waits et al., Reference Waits, Luikart and Taberlet2001). In addition, major allele frequency was computed for the SNP markers using PowerMarker v3.25 (Liu and Muse, Reference Liu and Muse2005). For the identification of duplicates, pairwise multilocus matching was performed among individual samples in CERVUS v3.0.7 using the Identify Analysis module. Clones with different names that were fully matched at all SNP loci were declared duplicates.

Population structure of the 168 cacao clones was determined using the Bayesian model-based clustering algorithm of STRUCTURE v2.3.4 (Pritchard et al., Reference Pritchard, Stephens and Donnelly2000). SNP fingerprints at the 45 loci of 22 pure reference accessions, each composed by two clones representing the 10 genetic groups identified by Motamayor et al. (Reference Motamayor, Lachenaud, da Silva e Mota, Loor, Kuhn, Brown and Schnell2008) and Trinitario, were included in the analysis to trace the possible ancestry in the local clones. An admixture model with alpha inferred, independent allele frequency with 200,000 burn-ins and 500,000 Markov Chain Monte Carlo (MCMC) repetitions was used. The number of clusters (K) was set from 4 to 10 and ten independent runs were performed for each value of K. The optimum K value was determined using the ad hoc ΔK method described by Evanno et al. (Reference Evanno, Regnaut and Goudet2005) as implemented in the STRUCTURE HARVESTER software (Earl and von Holdt, Reference Earl and von Holdt2012).

Further clustering of the 168 local cacao clones in relation to the 22 pure reference accessions as used for the STRUCTURE was performed using principal coordinates analysis (PCoA) in GenAlEx v6.5 (Peakall and Smouse, Reference Peakall and Smouse2006, Reference Peakall and Smouse2012). Pairwise Euclidean distances (GD) were calculated on the 45 SNP data and the GD was used to perform the PCoA using a covariance matrix with data standardization option.

Parentage analysis was conducted to assess the parentage contribution from the reference clones to the local clones and identify parent-offspring trios for the bi-clonal seedlings (with unknown maternity and paternity). A likelihood-based method implemented in CERVUS v3.0.7 (Marshall et al., Reference Marshall, Slate, Kruuk and Pemberton1998; Kalinowski et al., Reference Kalinowski, Taper and Marshall2007) was used for computation. The list of candidate parents for the clones included 33 pure reference accessions each composed by three clones belonging to the 10 genetic groups (Motamayor et al., Reference Motamayor, Lachenaud, da Silva e Mota, Loor, Kuhn, Brown and Schnell2008) and Trinitario. For the bi-clonal seedlings, the list of candidate parents comprised all genotypes found in trees of the core clone selection which had been used as progenitors in seed gardens or breeding programme in Ghana. In CERVUS, an error rate of 0.01 was used as the proportion of mistyped loci. In the parentage analysis, simulations were run for 20,000 cycles with the assumption that 90% of the candidate parents were sampled (80% was assumed for the local clones), and a total of 95% of loci were typed. Critical likelihood values (LOD scores) of 95% (strict) and 80% (relaxed) confidence in assignments were obtained using simulations.

Results

Genetic diversity statistics

Two (TcSNP 1075 and TcSNP 1096) of the 60 SNP markers used to genotype the bi-clonal seedlings were found to be monomorphic and were eliminated from further analysis. The PIC, major allele frequency, observed heterozygosity and expected heterozygosity of the SNP markers employed in the analysis of the local clones, reference clones and bi-clonal seedlings are presented in Tables S3–S5. The clones and bi-clonal seedlings showed mean PIC of 0.277 ± 0.016 and 0.256 ± 0.017, respectively. Mean major allele frequency of the clones was 0.737 ± 0.021, whereas the bi-clonal seedlings had 0.783 ± 0.022. Average observed heterozygosity values of 0.378 ± 0.026 and 0.348 ± 0.025 were obtained respectively for clones and bi-clonal seedlings. Mean expected heterozygosity was 0.349 ± 0.022 for the clones and 0.323 ± 0.022 for the bi-clonal seedlings. The local clones had higher mean observed heterozygosity (0.378 ± 0.026) than the reference population (0.187 ± 0.018), indicating that the ramets were derived from hybrid families (ortets). The probability of identity among siblings (PID-sib) based on the 45 and 58 SNP loci were 4.43 × 10−8 and 1.15 × 10−9, respectively, indicating that there is almost a null probability of finding two individuals with the same genotype in the populations. Additionally, a high total exclusion probability of 99.999 × 10−2 was obtained for the 45 and 58 SNP markers used for parentage analysis of clones and seedling varieties, respectively. This indicates that the set of markers are sufficient for assignment of parentage in cacao. The 168 local selections were all distinct clones without duplication.

Inference of ancestral background of local clones

The Bayesian clustering analysis produced five clusters (K = 5), the optimal value determined by the ad hoc ΔK statistic (Evanno et al., Reference Evanno, Regnaut and Goudet2005) (Fig. S1). These clusters are associated with clones of the 10 genetic groups (Motamayor et al., Reference Motamayor, Lachenaud, da Silva e Mota, Loor, Kuhn, Brown and Schnell2008) and Trinitario used as controls in this study. At the threshold of Q = 0.80 (Fig. 1, Table S6), cluster 1 (red) comprised reference accessions from Guiana and Marañón with 35 (20.8%) local selections. Cluster 2 (green) was composed of reference samples from Iquitos with 18 (10.7%) local clones. Cluster 3 (blue) grouped reference accessions from Nacional, Criollo and Curaray genetic backgrounds with no local sample. Cluster 4 (yellow) consisted of reference accessions from Contamana and Purús with 48 (28.6%) local clones. The fifth cluster (pink) included reference samples from Amelonado, Trinitario and Nanay genetic backgrounds, and 21 (12.5%) local accessions. At Q < 0.80, 16 (9.5%), 11 (6.5%), 5 (3.0%) and 14 (8.3%) samples of admixed parentage were found in clusters 1, 2, 4 and 5, respectively. In general, ancestral contributions to the local clones were in the decreasing order; Contamana-Purús > Guiana-Marañón > Amelonado-Trinitario-Nanay > Iquitos (Fig. 1, Table S6).

Figure 1. Q-plot showing clustering of 168 local and 22 reference T. cacao accessions based on analysis of genotypic data at 45 SNP loci using STRUCTURE (K = 5). Each genotype is represented by a vertical bar. The coloured subsections within each vertical bar indicate membership coefficient (Q) of the genotype to different subpopulations. Identified subpopulations following Motamayor et al. (2008) are Guiana-Marañón (red): GU 216/A, GU 230/A, PA 150, PA 70; Iquitos (green): IMC 33, IMC 6; Nacional-Criollo-Curaray (blue): Gloria 1, Gloria 12, PR145, PR71, LCT EEN 389, LCT EEN 434; Contamana-Purús (yellow): Ucayali 66, Ucayali 69, LCT EEN 411, LCT EEN 414; Amelonado-Trinitario-Nanay (pink): ES 03 Belize, PR76, ICS 40, RIM 189, POUND 1/B, POUND 2/A. At Q < 0.80, admixed samples in subpopulations 1, 2, 4, and 5 were 16, 11, 5, and 14, respectively.

Parentage analysis shows that 22 known parental clones were responsible for the maternity or paternity of 152 local clones (90% of 168 accessions) at the confidence level above 80%. When the confidence level was raised to 95%, the number of identified parent-offspring relationships was reduced to 113 with contributions from 21 parental clones (Table S7). Among the 152 identified parent-offspring relationships, 43 (28.3%) were associated with Contamana parents, 40 (26.3%) with Marañón, 26 (17.1%) with Guiana, 15 (9.9%) with Amelonado, 15 (9.9%) with Iquitos, 8 (5.3%) with Trinitario, 3 (2.0%) with Nanay and 2 (1.3%) with Purús (Fig. 2, Table S7). The assigned parent-offspring relationships largely agree with the results of the genetic structure (Fig. 1), reaffirming the ancestral contributions of Guiana, Marañón, Contamana, Purús, Amelonado, Trinitario, Nanay and Iquitos genetic groups to the parentage of the local clones. However, with the disintegration of the joint genetic clusters by the likelihood-based parentage analysis, the contributions of the eight genetic groups were in the decreasing order; Contamana > Marañón > Guiana > Amelonado and Iquitos > Trinitario > Nanay > Purús (Fig. 2).

Figure 2. Partitioned ancestry based on assigned parentage of 152 cacao accessions from Ghana with LOD scores above 80% probability. Critical LOD (the natural logarithm of the likelihood) ratios for assignment of maternity/paternity are 4.17 at >95% confidence and 0.33 at >80% confidence.

Genetic relationship between the local selections and the reference clones

The principal coordinates analysis (PCoA) showed the genetic relationships between the local selections and reference clones (Fig. 3). The first and second axes explained 25.7 and 9.8% of the total variation, respectively. Consistent with the results of the Bayesian clustering and parentage analyses, the studied clones had close relationship with the eight genetic groups out of the 10 used as reference. None of the local clones had genetic background of Nacional, Criollo and Curaray. A substantial number of the newly developed clones were distributed among the reference groups, particularly Marañón, Guiana, Iquitos, Trinitario, Nanay and Amelonado, suggesting their background as hybrids of these groups (Fig. 3). This observation was supported by the high proportions of admixed samples in Guiana-Marañón, Iquitos, and Amelonado-Trinitario-Nanay genetic clusters relative to Contamana-Purús genetic cluster (Fig. 1).

Figure 3. PCoA plot of 168 cacao clones in Ghana and 22 reference accessions using 45 SNP genetic data.

Parentage analysis to verify genetic purity of farmers' varieties

Parent-offspring relationships in the 752 seedlings of farmers' varieties were explored using CERVUS software. At >80% confidence level, parentage assignment identified parent-offspring trios for 48.7 to 80.3% of the seedlings sampled from six sources (Table 2). In general, 65.2% of the seedlings raised for commercial plantations had assigned parentage.

Table 2. Likelihood assignment of parentage of 752 T. cacao plants sampled from six different sources based on 58 SNP markers with LOD scores above 80% probability

Critical LOD (the natural logarithm of the likelihood) ratios for assignment of parentage are 12.45 at >95% confidence and 2.25 at >80% confidence.

Discussion

The present study analysed the population structure of recently developed cacao clones identified through rigorous testing at CRIG. In addition, the parentage of bi-clonal seedling varieties supplied to farmers for commercial plantations was verified to ascertain whether the seedlings were correctly produced. Overall, the SNP markers were informative and polymorphic, justifying their use in studying the genetic diversity, population structure and parentage of the populations under study. Further, the local clones were of diverse genetic origin, comprising eight ancestral genetic groups in contrast to four and five genetic groups associated with cacao populations in Puerto Rico (Cosme et al., Reference Cosme, Cuevas, Zhang, Oleksyk and Irish2016) and Indonesia (Dinarti et al., Reference Dinarti, Susilo, Meinhardt, Ji, Motilal, Mischke and Zhang2015), respectively. Furthermore, the study identified correct parentage for 65.2% of the bi-clonal seedlings produced in the seed gardens for commercial plantations, providing critical information for proper seed garden management. This study is among the few studies (Efombagn et al., Reference Efombagn, Sounigo, Eskes, Motamayor, Manzanares-Dauleux, Schnell and Nyassé2009; Padi et al., Reference Padi, Ofori, Takrama, Djan, Opoku, Dadzie, Bhattacharjee, Motamayor and Zhang2015) that assessed the genetic purity of seedlings or clones from the cacao seed gardens.

Information content of SNP markers

The PIC, which is highly correlated with the expected heterozygosity (He) measures the informativeness of a genetic marker. In the present study, average PIC values of 0.277 and 0.256 were observed for the clones and bi-clonal seedlings, respectively. According to Botstein et al. (Reference Botstein, White, Skolnick and Davis1980), markers with PIC values < 0.25, from 0.25 to 0.5, and > 0.5 are classified as slightly informative, informative, and highly informative, respectively. However, for bi-allelic markers (such as SNPs) with maximum PIC value of 0.5, slightly informative (PIC < 0.25) and informative (0.5 > PIC > 0.25) classes of markers are applicable. Therefore, the results indicate that the SNP markers employed in this study were informative and polymorphic. The efficiency of the 45 and 58 SNPs was further revealed by the respective PID-sib values of 4.43 × 10−8 and 1.15 × 10−9, which indicate a high probability (99.999 × 10−2) of identifying an individual tree in the studied populations. The PID-sib values observed for the SNP markers are consistent with estimates reported for 44 SNPs (PID-sib = 1.0 × 10−6; Mata-Quirós et al., Reference Mata-Quirós, Arciniegas-Leal, Phillips-Mora, Meinhardt, Motilal, Mischke and Zhang2018), 53 SNPs (PID-sib = 1.0 × 10−9; Takrama et al., Reference Takrama, Ji, Meainhardt, Mischke, Opoku, Padi and Zhang2014), and 64 SNPs (PID-sib = 2.44 × 10−10; Padi et al., Reference Padi, Ofori, Takrama, Djan, Opoku, Dadzie, Bhattacharjee, Motamayor and Zhang2015) used in cacao diversity studies. Furthermore, the efficiency of the two sets of SNPs used in this study corroborates the findings of Ji et al. (Reference Ji, Zhang, Motilal, Boccara, Lachenaud and Meinhardt2012) who observed that a minimum set of 26 SNPs could identify an individual cacao tree with 99.999% confidence.

Gene diversity in the cacao populations

The cacao populations had a moderate level of gene diversity (He = 0.323–0.349), which is comparable to cacao collections in Ghana (He = 0.343; Takrama et al., Reference Takrama, Ji, Meainhardt, Mischke, Opoku, Padi and Zhang2014), Honduras and Nicaragua (He = 0.367; Ji et al., Reference Ji, Zhang, Motilal, Boccara, Lachenaud and Meinhardt2012), Colombia (He = 0.314; Osorio-Guarín et al., Reference Osorio-Guarín, Berdugo-Cely, Coronado, Zapata, Quintero, Gallego-Sánchez and Yockteng2017), Uganda (He = 0.332; Gopaulchan et al., Reference Gopaulchan, Motilal, Bekele, Clause, Ariko, Ejang and Umaharan2019), Dominica (He = 0.320; Gopaulchan et al., Reference Gopaulchan, Motilal, Kalloo, Mahabir, Marissa, Joseph and Umaharan2020) and north Peru (He = 0.336; Bustamante et al., Reference Bustamante, Motilal, Calderon, Mahabir and Oliva2022). The moderate genetic diversity could be explained by the large contribution of few genetic groups (limited in genetic diversity) to the cacao populations under study as well as those in the above-mentioned countries. The clones and bi-clonal seedlings were largely of three out of the 10 genetic groups identified by Motamayor et al. (Reference Motamayor, Lachenaud, da Silva e Mota, Loor, Kuhn, Brown and Schnell2008). Similarly, the cacao populations in Dominica, Uganda, Honduras and Nicaragua, and north Peru had significant contributions from two, three, two, and three genetic groups, respectively.

The absence of duplicates in the clonal population as revealed by pairwise multilocus matching is an indication that the ramets may have been developed from highly heterozygous bi-parental families. This observation suggests that the 168 studied clones were unique and could provide enormous genetic variation for selection of clones with improved characteristics such as bean yield, bean quality, yield efficiency, precocity, and tolerance/resistance to biotic and abiotic stresses.

Population diversity and ancestry of local clones

The delta K estimated by the Evanno's method (Evanno et al., Reference Evanno, Regnaut and Goudet2005) revealed that the cacao population used in this study could be classified into five genetic clusters. The results indicate the existence of intra-population diversity within the clonal population worthy of exploring for cacao improvement.

The present study could not identify distinct clusters for the 10 genetic groups (Motamayor et al., Reference Motamayor, Lachenaud, da Silva e Mota, Loor, Kuhn, Brown and Schnell2008) but classified clones of the 10 genetic groups into five clusters. This could be due to sharing of alleles by clones developed from ortets of different genetic backgrounds, resulting in joint genetic groups. Similar results were reported for cacao accessions in Colombia (Osorio-Guarín et al., Reference Osorio-Guarín, Berdugo-Cely, Coronado, Zapata, Quintero, Gallego-Sánchez and Yockteng2017) and Côte d'Ivoire (Guiraud et al., Reference Guiraud, Tahi, Fouet, Trebissou, Pokou, Rivallan, Argout, Koffi, Koné, Zoro and Lanaud2018).

Analysis of genetic structure, PCoA and parentage assignment revealed that the recently developed clones were associated with eight of the 10 genetic groups identified by Motamayor et al. (Reference Motamayor, Lachenaud, da Silva e Mota, Loor, Kuhn, Brown and Schnell2008), indicating a significant proportion of genetic variation available in the clones. However, the parentage analysis of clones further highlighted that the local clones were largely of Contamana, Marañón and Guiana genetic groups. This observation was largely influenced by the genetic composition of the newly developed clones which constituted the clonal population in this study. The background of the local clones was largely of Scavina relating to Contamana genetic group, Parinari from Marañón genetic group, and GU clones from Guiana genetic group. The absence of clones of Curaray, Nacional and Criollo genetic groups in this study agrees with classification of cacao germplasm in Ghana in previous studies (Takrama et al., Reference Takrama, Ji, Meainhardt, Mischke, Opoku, Padi and Zhang2014; Padi et al., Reference Padi, Ofori, Takrama, Djan, Opoku, Dadzie, Bhattacharjee, Motamayor and Zhang2015). The results indicate that all eight genetic groups identified in the available germplasm in Ghana (Padi et al., Reference Padi, Ofori, Takrama, Djan, Opoku, Dadzie, Bhattacharjee, Motamayor and Zhang2015) have been exploited, indicating effective recurrent selection programme. The large proportion of the local clones belonging to the Contamana, Marañón and Guiana genetic groups could be explained by the strong preference for high yielding clones with large pods, large bean size, resistance to diseases and pests, precocity, establishment ease and adaptability to marginal growing conditions (Lachenaud et al., Reference Lachenaud, Oliver and Letourmy2000, Reference Lachenaud, Paulin, Ducamp and Thevenin2007; Bekele et al., Reference Bekele, Iwaro, Butler and Bidaisee2008; Paulin et al., Reference Paulin, Ducamp and Lachenaud2008; Padi et al., Reference Padi, Adu-Gyamfi, Akpertey, Arthur and Ofori2013a, Reference Padi, Ofori and Arthur2017b; Ofori et al., Reference Ofori, Padi, Assuah and Anim-Kwapong2014, Reference Ofori, Padi, Acheampong and Lowor2015, Reference Ofori, Padi and Amoako-Attah2020, Reference Ofori, Padi, Ameyaw, Dadzie, Opoku-Agyeman, Domfeh and Ansah2022). Furthermore, the Amelonado, Nanay and Iquitos background of the current farmers' varieties (Padi et al., Reference Padi, Ofori, Takrama, Djan, Opoku, Dadzie, Bhattacharjee, Motamayor and Zhang2015) could explain the large selection of new clones belonging to the Contamana, Marañón and Guiana genetic groups. Further studies would be initiated to evaluate the new clones for agronomic performance to enable selection of superior clones for the seed gardens and for population improvement.

Parentage analysis to verify genetic purity of farmers' varieties

Parentage analysis was conducted to assess if bi-clonal seedlings distributed to farmers were produced correctly. Seedlings were produced through manual pollination from seed garden plots of the SPD for commercial production. The analysis revealed that 65.2% of the seedlings were assigned parent-offspring relationship, suggesting that most of the seedlings supplied to farmers for commercial plantations had their parents from the breeder's active collection or recommended seed garden clones. The 34.8% of seedlings which emerged from parents outside of the breeder's active collection could be attributed to mislabelling in seed garden clonal plots or pollen contamination from trees not belonging to the breeder's active collection. A study by Padi et al. (Reference Padi, Ofori, Takrama, Djan, Opoku, Dadzie, Bhattacharjee, Motamayor and Zhang2015) observed clone mislabelling within seed garden clones and among clones of the breeder's active collection in Ghana, which resulted in unexpected parentage in cacao. Besides cacao, mislabelling of parental clones and pollen contamination have been highlighted as probable causes of unexpected parentage in loblolly pine (Grattapaglia et al., Reference Grattapaglia, do Amaral Diener and dos Santos2014), Larix gmelinii (Sun et al., Reference Sun, Yu, Dong, Zhao, Wang, Zhang and Zhang2017) and coffee (Akpertey et al., Reference Akpertey, Padi, Meinhardt and Zhang2020). The mislabelling or pollen contamination, however, occurred significantly in seed garden plots meant to produce seedlings for commercial production. As erroneous labelling and pollen contamination could result in yield reduction and large variations in agronomic traits within plots of tree crop varieties (Padi et al., Reference Padi, Ofori, Takrama, Djan, Opoku, Dadzie, Bhattacharjee, Motamayor and Zhang2015; Akpertey et al., Reference Akpertey, Padi, Meinhardt and Zhang2020), it is essential to investigate clone mislabelling in all active seed gardens and rogue off-type trees in order to maintain trees with proven performance in the seed gardens to produce quality seedlings for farmers.

Conclusions

The present study assessed the genetic diversity and population structure of locally bred cacao clones to enhance effective utilization, management, and conservation of these clones. The study revealed that the local clones were distinct and had ancestral contributions from Marañón, Guiana, Contamana, Iquitos, Amelonado, Trinitario, Nanay and Purús, representing a wide range of trait diversity for cacao genetic improvement. Given that the current farmers' varieties in Ghana are composed largely of Amelonado, Nanay and Iquitos background, the new clones with different genetic backgrounds could be used to develop improved seedling varieties for farmers. However, the clones should be evaluated for their agronomic performance before being utilized in the breeding programme.

A significant proportion (34.8%) of the seedling varieties supplied to farmers for commercial plantations had incorrect parentage (possibly due to clone mislabelling and pollen contamination), which could result in underperformance and low adoption of recommended varieties. It is therefore imperative to investigate the existence of mislabelled clones or sources of pollen contamination in all active seed gardens for the appropriate measures to be applied.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S1479262124000510.

Acknowledgements

The authors appreciate the support and assistance of the field and technical staff of the Plant Breeding Division of the Cocoa Research Institute of Ghana (CRIG). We are also grateful to the anonymous reviewers and editors for their valuable suggestions on the paper. This work is published with the kind permission of the Executive Director of CRIG as manuscript number CRIG/02/2024/061/002.

Authors’ contributions

Kwabena Asare Bediako: Investigation, methodology, formal analysis, writing – original draft. Francis Kwame Padi: Conceptualization, funding acquisition, project management, methodology, data curation, supervision, writing – review and editing. Ebenezer Obeng-Bio: Formal analysis, writing – review and editing. Atta Ofori: Methodology, supervision, writing – review and editing.

Funding statement

This work was supported by the Ghana Cocoa Board.

Competing interests

None.

References

Abdul-Karimu, A, Adomako, B and Adu-Ampomah, Y (2006) Cocoa introduction into Ghana. Ghana Journal of Agricultural Science 39, 227238.Google Scholar
Adomako, B, Allen, RC and Adu-Ampomah, Y (1999) Combining abilities for yield and vegetative traits of Upper Amazon cocoa selections in Ghana. Plantations, Recherche, Developpement 6, 183192.Google Scholar
Adomako, B, Padi, FK, Opoku, SY, Assuah, MK, Domfeh, O and Owusu-Ansah, F (2007) International Clone Trial and Local Clone Selection Trial. Annual Report 2007/08. Cocoa Research Institute of Ghana, pp. 4349.Google Scholar
Akpertey, A, Padi, FK, Meinhardt, L and Zhang, D (2020) Effectiveness of single nucleotide polymorphism markers in genotyping germplasm collections of Coffea canephora using KASP assay. Frontiers in Plant Science 11, 612593.CrossRefGoogle ScholarPubMed
Allegre, M, Argout, X, Boccara, M, Fouet, O, Roguet, Y, Bérard, A, Thévenin, JM, Chauveau, A, Rivallan, R, Clement, D, Courtois, B, Gramacho, K, Boland-Augé, A, Tahi, M, Umaharan, P, Brunel, D and Lanaud, C (2012) Discovery and mapping of a new expressed sequence tag-single nucleotide polymorphism and simple sequence repeat panel for large-scale genetic studies and breeding of Theobroma cacao L. DNA Research 19, 2335.CrossRefGoogle ScholarPubMed
Aneani, F and Ofori-Frimpong, K (2013) An analysis of yield gap and some factors of cacao (Theobroma cacao L.) yields in Ghana. Sustainable Agriculture Research 2, 117127.Google Scholar
Argout, X, Fouet, O, Wincker, P, Gramacho, K, Legavre, T, Sabau, X, Risterucci, AM, Da Silva, C, Cascardo, J, Allegre, M, Kuhn, D, Verica, J, Courtois, B, Loor, G, Babin, R, Sounigo, O, Ducamp, M, Guiltinan, MJ, Ruiz, M, Alemanno, L, Machado, R, Phillips, W, Schnell, R, Gilmour, M, Rosenquist, E, Butler, D, Maximova, S and Lanaud, C (2008) Towards the understanding of the cocoa transcriptome: production and analysis of an exhaustive datasets of ESTs of Theobroma cacao L. generated from various tissues and under various conditions. BMC Genomics 9, 512.CrossRefGoogle Scholar
Bartley, BGD (2005) The Genetic Diversity of Cacao and Its Utilization. Wallingford, UK: CABI.CrossRefGoogle Scholar
Bekele, FL, Iwaro, AD, Butler, DR and Bidaisee, GG (2008) Upper Amazon Forastero cacao (Theobroma cacao L.) 2: an overview of Parinari clones from a breeder's perspective. Tropical Agriculture (Trinidad) 85, 1633.Google Scholar
Botstein, D, White, RL, Skolnick, M and Davis, RW (1980) Construction of a genetic linkage map in man using restriction fragment length polymorphisms. American Journal of Human Genetics 32, 314331.Google ScholarPubMed
Bustamante, DE, Motilal, LA, Calderon, MS, Mahabir, A and Oliva, M (2022) Genetic diversity and population structure of fine aroma cacao (Theobroma cacao L.) from north Peru revealed by single nucleotide polymorphism (SNP) markers. Frontiers in Ecology Evolution 10, 895056.CrossRefGoogle Scholar
Cheesman, E (1944) Notes on the nomenclature, classification and possible relationships of cocoa populations. Tropical Agriculture 21, 144159.Google Scholar
Cosme, S, Cuevas, HE, Zhang, D, Oleksyk, TK and Irish, BM (2016) Genetic diversity of naturalized cacao (Theobroma cacao L.) in Puerto Rico. Tree Genetics & Genomes 12, 88.CrossRefGoogle Scholar
Dinarti, D, Susilo, AW, Meinhardt, LW, Ji, K, Motilal, LA, Mischke, S and Zhang, D (2015) Genetic diversity and parentage in farmer selections of cacao from Southern Sulawesi, Indonesia revealed by microsatellite markers. Breeding Science 65, 438446.CrossRefGoogle ScholarPubMed
Doyle, J and Doyle, J (1990) Isolation of plant DNA from fresh tissue. Focus 12, 1315.Google Scholar
Earl, DA and von Holdt, B (2012) STRUCTURE HARVESTER: a website program for visualizing STRUCTURE output and implementing the Evanno method. Conservation Genetics Resources 4, 359361.CrossRefGoogle Scholar
Efombagn, MIB, Sounigo, O, Eskes, AB, Motamayor, JC, Manzanares-Dauleux, MJ, Schnell, R and Nyassé, S (2009) Parentage analysis and outcrossing patterns in cacao (Theobroma cacao L.) farms in Cameroon. Heredity 103, 4653.CrossRefGoogle ScholarPubMed
Evanno, G, Regnaut, S and Goudet, J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Molecular Ecology 14, 26112620.CrossRefGoogle ScholarPubMed
Glendinning, DR (1957) The performance of the introductions and hybrids in W.A.C.R.I. trials. In: Report Cocoa Conference 1957, Cocoa, Chocolate and Confectionery Alliance, London, pp. 4144.Google Scholar
Glendinning, DR (1964) A study of clonal cocoa variety. Horticulture Research 4, 8997.Google Scholar
Glendinning, DR (1966) Further developments in the breeding programme at the Cocoa Research Institute, Tafo. Ghana Journal of Science 6, 5262.Google Scholar
Gopaulchan, D, Motilal, LA, Bekele, FL, Clause, S, Ariko, JO, Ejang, HP and Umaharan, P (2019) Morphological and genetic diversity of cacao (Theobroma cacao L.) in Uganda. Physiology and Molecular Biology of Plants 25, 361375.CrossRefGoogle ScholarPubMed
Gopaulchan, D, Motilal, LA, Kalloo, RK, Mahabir, A, Marissa, M, Joseph, F and Umaharan, P (2020) Genetic diversity and ancestry of cacao (Theobroma cacao L.) in Dominica revealed by single nucleotide polymorphism markers. Genome 63, 583595.CrossRefGoogle ScholarPubMed
Grattapaglia, D, do Amaral Diener, PS and dos Santos, GA (2014) Performance of microsatellites for parentage assignment following mass controlled pollination in a clonal seed orchard of loblolly pine (Pinus taeda L.). Tree Genetics & Genomes 10, 16311643.CrossRefGoogle Scholar
Guiraud, BSHB, Tahi, MG, Fouet, O, Trebissou, CI, Pokou, D, Rivallan, R, Argout, X, Koffi, KK, Koné, B, Zoro, BIA and Lanaud, C (2018) Assessment of genetic diversity and structure in cocoa trees (Theobroma cacao L.) in Côte d'Ivoire with reference to their susceptibility to Cocoa swollen shoot virus disease (CSSVD). Tree Genetics & Genomes 14, 52.CrossRefGoogle Scholar
Gupta, P, Roy, J and Prasad, M (2001) Single nucleotide polymorphisms: a new paradigm for molecular marker technology and DNA polymorphism detection with emphasis on their use in plants. Current Science 80, 524535.Google Scholar
Gutiérrez, OA, Martinez, K, Zhang, D, Livingstone, DS, Turnbull, CJ and Motamayor, JC (2021) Selecting SNP markers reflecting population origin for cacao (Theobroma cacao L.) germplasm identification. Beverage Plant Research 1, 15.CrossRefGoogle Scholar
International Cocoa Organization (ICCO) (2021) Quarterly Bulletin of Cocoa Statistics. London, UK: International Cocoa Organization, Vol. XLVII, No. 4, Cocoa year 2020/21.Google Scholar
Ji, K, Zhang, D, Motilal, LA, Boccara, M, Lachenaud, P and Meinhardt, LW (2012) Genetic diversity and parentage in farmer varieties of cacao (Theobroma cacao L.) from Honduras and Nicaragua as revealed by single nucleotide polymorphism (SNP) markers. Genetic Resources and Crop Evolution 60, 441453.CrossRefGoogle Scholar
Kalinowski, ST, Taper, ML and Marshall, TC (2007) Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Molecular Ecology 16, 10991106.CrossRefGoogle ScholarPubMed
Kennedy, AJ and Mooleedhar, V (1993) Conservation of cocoa in field genebanks–the International Cocoa Genebank, Trinidad. In International workshop on conservation, characterisation and utilization of cocoa genetic resources in the 21st century, Port of Spain, Trinidad, 1992. Cocoa Research Unit, The University of the West Indies, pp. 2123.Google Scholar
Lachenaud, P, Oliver, G and Letourmy, P (2000) Agronomic assessment of wild cacao trees (Theobroma cacao L.) from the Camopi and Tanpok basins (French Guiana). Plant Genetic Resources Newsletter 124, 16.Google Scholar
Lachenaud, P, Paulin, D, Ducamp, M and Thevenin, M (2007) Twenty years of agronomic evaluation of wild cacao trees (Theobroma cacao L.) from French Guiana. Scientia Horticulturae 113, 313321.CrossRefGoogle Scholar
Liu, K and Muse, SV (2005) Power marker: integrated analysis environment for genetic marker data. Bioinformatics (Oxford, England) 21, 21282129.CrossRefGoogle Scholar
Lockwood, G (1971) Early results from a trial of Upper Amazon cocoa clones in Ghana. Experimental Agriculture 7, 321327.CrossRefGoogle Scholar
Lockwood, G and End, MJ (1993) History, technique and future needs for cacao collection. In International workshop on conservation, characterisation and utilization of cocoa genetic resources in the 21st century, Port-of-Spain, Trinidad, 1992. Cocoa Research Unit, The University of the West Indies, pp. 114.Google Scholar
Lockwood, G and Gyamfi, MMO (1979) The CRIG cocoa germplasm collection with notes on codes used in the breeding programme at Tafo and elsewhere. Technical Bulletin, No. 10. Cocoa Research Institute of Ghana, Tafo.Google Scholar
Lukman, Zhang D, Susilo, AW, Dinarti, D, Bailey, B, Mischke, S and Meinhardt, LW (2014) Genetic identity, ancestry and parentage in farmer selections of cacao from Aceh, Indonesia revealed by single nucleotide polymorphism (SNP) markers. Tropical Plant Biology 7, 133144.CrossRefGoogle Scholar
Mammadov, J, Aggarwal, R, Buyyarapu, R and Kumpatla, S (2012) SNP markers and their impact on plant breeding. International Journal of Plant Genomics 2012, 728398.CrossRefGoogle ScholarPubMed
Marshall, TC, Slate, J, Kruuk, LEB and Pemberton, JM (1998) Statistical confidence for likelihood-based paternity inference in natural populations. Molecular Ecology 7, 639655.CrossRefGoogle ScholarPubMed
Mata-Quirós, A, Arciniegas-Leal, A, Phillips-Mora, W, Meinhardt, LW, Motilal, L, Mischke, S and Zhang, D (2018) Assessing hidden parentage and genetic integrity of the “United Fruit Clones” of cacao (Theobroma cacao) from Costa Rica using SNP markers. Breeding Science 68, 545553.CrossRefGoogle ScholarPubMed
Motamayor, JC, Lachenaud, P, da Silva e Mota, JW, Loor, R, Kuhn, DN, Brown, SJ and Schnell, RJ (2008) Geographic and genetic population differentiation of the Amazonian chocolate tree (Theobroma cacao L). PLoS ONE 3, e3311.CrossRefGoogle ScholarPubMed
Ofori, A, Padi, FK, Assuah, MK and Anim-Kwapong, GJ (2014) Broadening the gene pool of cocoa (Theobroma cacao L.) progenies with Guiana Clones: establishment and precocity traits. Journal of Crop Improvement 28, 715728.CrossRefGoogle Scholar
Ofori, A, Padi, FK, Acheampong, K and Lowor, S (2015) Genetic variation and relationship of traits related to drought tolerance in cocoa (Theobroma cacao L.) under shade and no-shade conditions in Ghana. Euphytica 201, 411421.CrossRefGoogle Scholar
Ofori, A, Padi, FK and Amoako-Attah, I (2020) Field evaluation of cacao progenies derived from Guiana clones for yield and black pod disease resistance. Crop Science 60, 249261.CrossRefGoogle Scholar
Ofori, A, Padi, FK, Ameyaw, GA, Dadzie, AM, Opoku-Agyeman, M, Domfeh, O and Ansah, FO (2022) Field evaluation of the impact of cocoa swollen shoot virus disease infection on yield traits of different cocoa (Theobroma cacao L.) clones in Ghana. PLoS ONE 17, e0262461.CrossRefGoogle ScholarPubMed
Ofori, A, Padi, FK, Akpertey, A, Asare Bediako, K, Arthur, A, Adu-Gyamfi, PKK, Nyadanu, D, Obeng-Bio, E and Anokye, E (2023) Genotype × environment interaction for establishment and precocity traits among elite cocoa (Theobroma cacao L.) hybrids in Ghana. Euphytica 219, 64.CrossRefGoogle Scholar
Osorio-Guarín, JA, Berdugo-Cely, J, Coronado, RA, Zapata, YP, Quintero, C, Gallego-Sánchez, G and Yockteng, R (2017) Colombia a source of cacao genetic diversity as revealed by the population structure analysis of germplasm bank of Theobroma cacao L. Frontiers in Plant Science 8, 1994.CrossRefGoogle ScholarPubMed
Padi, FK, Adu-Gyamfi, P, Akpertey, A, Arthur, A and Ofori, A (2013 a) Differential response of cocoa (Theobroma cacao) families to field establishment stress. Plant Breeding 132, 229236.CrossRefGoogle Scholar
Padi, FK, Takrama, J, Opoku, SY, Dadzie, AM and Assuah, MK (2013 b) Early-stage performance of cocoa clones relative to their progenitor ortets: implications for large-scale clone selection. Journal of Crop Improvement 27, 319341.CrossRefGoogle Scholar
Padi, FK, Ofori, A, Takrama, J, Djan, E, Opoku, SY, Dadzie, AM, Bhattacharjee, R, Motamayor, JC and Zhang, D (2015) The impact of SNP fingerprinting and parentage analysis on the effectiveness of variety recommendations in cacao. Tree Genetics & Genomes 11, 44.CrossRefGoogle Scholar
Padi, FK, Ofori, A and Akpertey, A (2017a) Genetic base-broadening of cacao for precocity and cropping efficiency. Plant Genetic Resources 15, 548557.CrossRefGoogle Scholar
Padi, FK, Ofori, A and Arthur, A (2017 b) Genetic variation and combining ability for vigor and yield in a recurrent selection programme for cacao. Journal of Agricultural Science 155, 444464.CrossRefGoogle Scholar
Padi, FK, Domfeh, OK, Arthur, A and Ofori, A (2018) Potential of recurrent selection for developing improved cocoa varieties in Ghana. In International Symposium on Cocoa Research (ISCR), Lima, Peru, 13–17 November 2017. International Cocoa Organization (ICCO).Google Scholar
Paulin, D, Ducamp, M and Lachenaud, P (2008) New sources of resistance to Phytophthora megakarya identified in wild cacao tree populations of French Guiana. Crop Protection 27, 11431147.CrossRefGoogle Scholar
Peakall, R and Smouse, PE (2006) GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes 6, 288295.CrossRefGoogle Scholar
Peakall, R and Smouse, PE (2012) Genalex 6.5: genetic analysis in Excel. Population genetic software for teaching and research – an update. Bioinformatics (Oxford, England) 28, 25372539.Google ScholarPubMed
Posnette, AF (1941) Swollen-shoot virus disease of cacao. Tropical Agriculture (Trinidad) 18, 8790.Google Scholar
Posnette, AF (1943) Cocoa selection on the gold coast. Tropical Agriculture (Trinidad) 20, 149155.Google Scholar
Posnette, AF (1951) Virus research at the West African cacao research Institute, Tafo, Gold Coast. Tropical Agriculture (Trinidad) 28, 133142.Google Scholar
Pritchard, JK, Stephens, M and Donnelly, P (2000) Inference of population structure using multilocus genotype data. Genetics 155, 945959.CrossRefGoogle ScholarPubMed
Sala, PD, Cilas, C, Gimeno, TE, Wohl, S, Opoku, SY, Găinuşă-Bogdan, A and Ribeyre, F (2021) Assessment of atmospheric and soil water stress impact on a tropical crop: the case of Theobroma cacao under Harmattan conditions in eastern Ghana. Agricultural and Forest Meteorology 311, 108670.CrossRefGoogle Scholar
Schultes, RE (1984) Amazonian cultigens and their northward and westward migrations in pre-Columbian times. In Stone, D (ed.), Pre-Columbian Plant Migration, Papers of the Peabody Museum of Archaeology and Ethnology, Vol 76. Cambridge, Mass. Harvard University Press, pp. 6983.Google Scholar
Simmonds, NW (1996) Family selection in plant breeding. Euphytica 90, 201208.CrossRefGoogle Scholar
Sun, W, Yu, D, Dong, M, Zhao, J, Wang, X, Zhang, H and Zhang, J (2017) Evaluation of efficiency of controlled pollination based parentage analysis in a Larix gmelinii var. principis-rupprechtii Mayr. Seed orchard. PLoS ONE 12, e0176483.CrossRefGoogle Scholar
Takrama, J, Ji, K, Meainhardt, L, Mischke, S, Opoku, SY, Padi, FK and Zhang, D (2014) Verification of genetic diversity of introduced cacao germplasm in Ghana using single nucleotide polymorphism (SNP) markers. African Journal of Biotechnology 13, 21272136.Google Scholar
Thresh, JM, Owusu, GK, Boamah, A and Lockwood, G (1988) Ghanaian cocoa varieties and swollen shoot virus. Crop Protection 7, 219231.CrossRefGoogle Scholar
Waits, LP, Luikart, G and Taberlet, P (2001) Estimating the probability of identity among genotypes in natural populations: cautions and guidelines. Molecular Ecology 10, 249256.CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Reference cacao clones of 11 genetic groups used in genetic structure and parentage analyses for assignment of ancestry

Figure 1

Figure 1. Q-plot showing clustering of 168 local and 22 reference T. cacao accessions based on analysis of genotypic data at 45 SNP loci using STRUCTURE (K = 5). Each genotype is represented by a vertical bar. The coloured subsections within each vertical bar indicate membership coefficient (Q) of the genotype to different subpopulations. Identified subpopulations following Motamayor et al. (2008) are Guiana-Marañón (red): GU 216/A, GU 230/A, PA 150, PA 70; Iquitos (green): IMC 33, IMC 6; Nacional-Criollo-Curaray (blue): Gloria 1, Gloria 12, PR145, PR71, LCT EEN 389, LCT EEN 434; Contamana-Purús (yellow): Ucayali 66, Ucayali 69, LCT EEN 411, LCT EEN 414; Amelonado-Trinitario-Nanay (pink): ES 03 Belize, PR76, ICS 40, RIM 189, POUND 1/B, POUND 2/A. At Q < 0.80, admixed samples in subpopulations 1, 2, 4, and 5 were 16, 11, 5, and 14, respectively.

Figure 2

Figure 2. Partitioned ancestry based on assigned parentage of 152 cacao accessions from Ghana with LOD scores above 80% probability. Critical LOD (the natural logarithm of the likelihood) ratios for assignment of maternity/paternity are 4.17 at >95% confidence and 0.33 at >80% confidence.

Figure 3

Figure 3. PCoA plot of 168 cacao clones in Ghana and 22 reference accessions using 45 SNP genetic data.

Figure 4

Table 2. Likelihood assignment of parentage of 752 T. cacao plants sampled from six different sources based on 58 SNP markers with LOD scores above 80% probability

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