Genome-wide association analyses using multilocus models on bananas (Musa spp.) reveal candidate genes related to morphology, fruit quality, and yield

Abstract

Abstract Bananas (Musa spp.) are an essential fruit worldwide and rank as the fourth most significant food crop for addressing malnutrition due to their rich nutrients and starch content. The potential of their genetic diversity remains untapped due to limited molecular breeding tools. Our study examined a phenotypically diverse group of 124 accessions from the Colombian Musaceae Collection conserved in AGROSAVIA. We assessed 12 traits categorized into morphology, fruit quality, and yield, alongside sequence data. Our sequencing efforts provided valuable insights, with an average depth of about 7× per accession, resulting in 187,133 single-nucleotide polymorphisms (SNPs) against Musa acuminata (A genome) and 220,451 against Musa balbisiana (B genome). Population structure analysis grouped samples into four and five clusters based on the reference genome. By using different association models, we identified marker–trait associations (MTAs). The mixed linear model revealed four MTAs, while the Bayesian-information and linkage-disequilibrium iteratively nested keyway and fixed and random model for circulating probability unification models identified 82 and 70 MTAs, respectively. We identified 38 and 40 candidate genes in linkage proximity to significant MTAs for the A genome and B genome, respectively. Our findings provide insights into the genetic underpinnings of morphology, fruit quality, and yield. Once validated, the SNP markers and candidate genes can potentially drive advancements in genomic-guided breeding strategies to enhance banana crop improvement.