Background and AimsThe production of triploid banana and plantain (Musa spp.) cultivars with improved characteristics (e.g. greater disease resistance or higher yield), while still preserving the main features of current popular cultivars (e.g. taste and cooking quality), remains a major challenge for Musa breeders. In this regard, breeders require a sound knowledge of the lineage of the current sterile triploid cultivars, to select diploid parents that are able to transmit desirable traits, together with a breeding strategy ensuring final triploidization and sterility. Highly polymorphic single sequence repeats (SSRs) are valuable markers for investigating phylogenetic relationships.MethodsHere, the allelic distribution of each of 22 SSR loci across 561 Musa accessions is analysed.Key Results and ConclusionsWe determine the closest diploid progenitors of the triploid ‘Cavendish’ and ‘Gros Michel’ subgroups, valuable information for breeding programmes. Nevertheless, in establishing the likely monoclonal origin of the main edible triploid banana subgroups (i.e. ‘Cavendish’, ‘Plantain’ and ‘Mutika-Lujugira’), we postulated that the huge phenotypic diversity observed within these subgroups did not result from gamete recombination, but rather from epigenetic regulations. This emphasizes the need to investigate the regulatory mechanisms of genome expression on a unique model in the plant kingdom. We also propose experimental standards to compare additional and independent genotyping data for reference.

Genomic selection empirically appeared valuable for reciprocal recurrent selection in oil palm as it could account for family effects and Mendelian sampling terms, despite small populations and low marker density. Genomic selection (GS) can increase the genetic gain in plants. In perennial crops, this is expected mainly through shortened breeding cycles and increased selection intensity, which requires sufficient GS accuracy in selection candidates, despite often small training populations. Our objective was to obtain the first empirical estimate of GS accuracy in oil palm (Elaeis guineensis), the major world oil crop. We used two parental populations involved in conventional reciprocal recurrent selection (Deli and Group B) with 131 individuals each, genotyped with 265 SSR. We estimated within-population GS accuracies when predicting breeding values of non-progeny-tested individuals for eight yield traits. We used three methods to sample training sets and five statistical methods to estimate genomic breeding values. The results showed that GS could account for family effects and Mendelian sampling terms in Group B but only for family effects in Deli. Presumably, this difference between populations originated from their contrasting breeding history. The GS accuracy ranged from -0.41 to 0.94 and was positively correlated with the relationship between training and test sets. Training sets optimized with the so-called CDmean criterion gave the highest accuracies, ranging from 0.49 (pulp to fruit ratio in Group B) to 0.94 (fruit weight in Group B). The statistical methods did not affect the accuracy. Finally, Group B could be preselected for progeny tests by applying GS to key yield traits, therefore increasing the selection intensity. Our results should be valuable for breeding programs with small populations, long breeding cycles, or reduced effective size.

Multi-parental populations are promising tools for identifying quantitative disease resistance loci. Stem rot caused by Ganoderma boninense is a major threat to palm oil production, with yield losses of up to 80% prompting premature replantation of palms. There is evidence of genetic resistance sources, but the genetic architecture of Ganoderma resistance has not yet been investigated. This study aimed to identify Ganoderma resistance loci using an oil palm multi-parental population derived from nine major founders of ongoing breeding programs. A total of 1200 palm trees of the multi-parental population was planted in plots naturally infected by Ganoderma, and their health status was assessed biannually over 25 yr. The data were treated as survival data, and modeled using the Cox regression model, including a spatial effect to take the spatial component in the spread of Ganoderma into account. Based on the genotypes of 757 palm trees out of the 1200 planted, and on pedigree information, resistance loci were identified using a random effect with identity-by-descent kinship matrices as covariance matrices in the Cox model. Four Ganoderma resistance loci were identified, two controlling the occurrence of the first Ganoderma symptoms, and two the death of palm trees, while favorable haplotypes were identified among a major gene pool for ongoing breeding programs. This study implemented an efficient and flexible QTL mapping approach, and generated unique valuable information for the selection of oil palm varieties resistant to Ganoderma disease.