Genetic architecture and candidate loci associated with growth and yield- related traits in sweet fig banana (Musa acuminata cv Sotoumon, AA)
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Background The yield of sweet fig banana is low due to the crop's poor agronomic performance and susceptibility to environmental stresses. Identifying the genomic regions underlying yield-related traits can increase the efficiency of selection processes for improved cultivars development. However, the genetic determinism of growth and yield-related traits in the sweet fig banana are still not well understood. Results In this study, we investigated the genetic architecture regulating growth and yield-related traits through a genome-wide association study (GWAS) on a panel of 238 sweet fig banana accessions (spanning the Guinean and Sudano-Guinean geographical regions of Benin) using 1,473 high-quality SNPs and five GWAS models including GLM, MLM, BLINK, FarmCPU, and MLMM. Our findings revealed that there were significant variations in all phenotypic traits among accessions. The GWAS revealed 71 significant marker-trait associations across 59 loci distributed in the eleven chromosomes, with 29 of them pertaining to yield-related traits. The five models detected seven marker-trait associations. In addition, seven pleiotropic loci were identified for plant height and yield-related traits (especially the number of hands). The loci M1 (18271887, position 5248569, chromosome 1) and M36 (20341671, position 27420981, chromosome 1) exert an antagonistic pleiotropic effect on the plant height and number of fingers of the bunch. These results showed that a complex genetic architecture governed yield-related traits, resulting from the cumulative minor effects of multiple SNPs. Conclusions A synergistic selection of pleiotropic and non-pleiotropic SNPs underlying plant height and yield-related traits can target relevant gene combinations for developing high-yielding sweet fig banana and other Musa cultivars. The GWAS data set generated in this study has the potential to drive advancements in genomic-guided breeding strategies to enhance banana yield improvement.
