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

使用多位点模型对香蕉(Musa spp.)进行全基因组关联分析,揭示与形态、果实品质和产量相关的候选基因

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作者:Jaime Andrés Osorio-Guarin, Janet Higgins, Deisy Lisseth Toloza-Moreno, Federica Di Palma, Ayda Lilia Enriquez Valencia, Fernando Riveros Munévar, José J De Vega, Roxana Yockteng

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.

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