Location: Sustainable Perennial Crops
2013 Annual Report
Phenotyping will be carried out in the International Cocoa Genebank, Trinidad. Within plot (intra-clone) mislabeling will be identified using 40-50 SNPs. Phenotypic traits related to yield components and diseases resistance, including number of pods, pod index, bean number, bean size, bean weight, butter fat content, field resistance to witches’ broom disease (Moniliophthora perniciosa) and black pod (Phytophthora) will be evaluated. Previously recorded data on morphological variations, (Bekele et al., 2006); will be combined with new observations. In case duplicated trees in different environment (e.g. in the UWI campus) and Marper Farm) are available, phenotypic data will be recorded from different environments. Based on the multi-year field observations, resistance to witches’ broom disease will be further evaluated using the agar-drop inoculation method (Surujdeo-Maharaj et al., 2003).
Genotyping will be done with the Illumina Golden Gate’s Bead Array platform and a total of 3000-4000 SNP markers will be genotyped. Part of these SNP have been developed through an agreement (SCA: 1275-21000-264-04S; CIRAD). These SNP markers were developed based on forty-five cDNA libraries constructed from a wide range of cacao organs and tissues, including flowers, cherels, pod cortex, shoot, root, germinated seeds and embryos from diverse genotypes (Lanaud et al., 2009). The first panel of 1536 SNPs has been tested. In addition, two to three hundreds candidate gene SNPs for disease resistance will be developed based on the expression studies of ARS Project (Project number: 1275-21220-225-00D). More SNPs will be available from the ARS cacao genome project in Miami, FL.
Population structure patterns will be investigated using the Bayesian clustering method implemented in the STRUCTURE program (Pritchard et al. 2000). Both single-marker models and hyplotype-based tests will be applied for all SNP–trait combinations. Normality of traits and variance homogeneity will be tested using the UNIVARIATE and GLM Procedure of SAS, respectively (SAS Institute Inc., 1998). Marker data will be compared with trait values by three methods: a one-way ANOVA using SAS, a non-parametric Kruskal–Wallis test and a likelihood of the odds (LOD) score test both performed by MapQTL 4 (Van Ooijen and Maliepaard, 1996). Patterns of linkage disequilibrium (LD) among SNPs that are significantly associated with the same trait will be assessed using the maximum-likelihood approach implanted in GENETICS (WARNES and LEISCH 2006; http://cran.r-project.org).