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Genome-Wide Association Analysis of Fruit Shape-Related Traits in Areca catechu .

Hao DingGuangzhen ZhouLong ZhaoXinyu LiYicheng WangChengcai XiaZhiqiang XiaYinglang Wan
Published in: International journal of molecular sciences (2023)
The areca palm ( Areca catechu L.) is one of the most economically important palm trees in tropical areas. To inform areca breeding programs, it is critical to characterize the genetic bases of the mechanisms that regulate areca fruit shape and to identify candidate genes related to fruit-shape traits. However, few previous studies have mined candidate genes associated with areca fruit shape. Here, the fruits produced by 137 areca germplasms were divided into three categories (spherical, oval, and columnar) based on the fruit shape index. A total of 45,094 high-quality single-nucleotide polymorphisms (SNPs) were identified across the 137 areca cultivars. Phylogenetic analysis clustered the areca cultivars into four subgroups. A genome-wide association study that used a mixed linear model identified the 200 loci that were the most significantly associated with fruit-shape traits in the germplasms. In addition, 86 candidate genes associated with areca fruit-shape traits were further mined. Among the proteins encoded by these candidate genes were UDP-glucosyltransferase 85A2, the ABA-responsive element binding factor GBF4, E3 ubiquitin-protein ligase SIAH1, and LRR receptor-like serine/threonine-protein kinase ERECTA. Quantitative real-time polymerase chain reaction (qRT-PCR) analysis showed that the gene that encoded UDP-glycosyltransferase, UGT85A2 , was significantly upregulated in columnar fruits as compared to spherical and oval fruits. The identification of molecular markers that are closely related to fruit-shape traits not only provides genetic data for areca breeding, but it also provides new insights into the shape formation mechanisms of drupes.
Keyphrases
  • genome wide
  • protein kinase
  • dna methylation
  • genome wide association
  • genome wide association study
  • high resolution
  • deep learning
  • cancer therapy
  • dna binding
  • big data
  • protein protein
  • case control
  • neural network