Inheritance and Quantitative Trait Loci Mapping of Aromatic Compounds from Clementine (Citrus × clementina Hort. ex Tan.) and Sweet Orange (C. × sinensis (L.) Osb.) Fruit Essential Oils

Genes (Basel). 2023 Sep 14;14(9):1800. doi: 10.3390/genes14091800.

Abstract

Despite their importance in food processing, perfumery and cosmetics, the inheritance of sweet orange aromatic compounds, as well as their yield in the fruit peel, has been little analyzed. In the present study, the segregation of aromatic compounds was studied in an F1 population of 77 hybrids resulting from crosses between clementine and blood sweet orange. Fruit-peel essential oils (PEOs) extracted by hydrodistillation were analyzed by gas chromatography coupled with flame ionization detection. Genotyping by sequencing was performed on the parents and the hybrids. The resulting "clementine × sweet blood orange" genetic map consists of 710 SNP markers distributed in nine linkage groups (LGs), representing the nine citrus chromosomes, and spanning 1054 centimorgans. Twenty quantitative trait loci (QTLs) were identified, explaining between 20.5 and 55.0% of the variance of the major aromatic compounds and PEO yield. The QTLs for monoterpenes and aliphatic aldehydes predominantly colocalized on LGs 5 and 8, as did the two QTLs for PEO yield. The sesquiterpene QTLs were located on LGs 1, 3, 6 and 8. The detection of major QTLs associated with the synthesis of aliphatic aldehydes, known for their strong aromatic properties, open the way for marker-assisted selection.

Keywords: blood sweet orange; essential oil yield; genetic linkage map; genotyping by sequencing; quantitative trait loci; single-nucleotide polymorphism markers.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aldehydes
  • Chromosome Mapping
  • Citrus sinensis* / genetics
  • Citrus* / genetics
  • Fruit / chemistry
  • Fruit / genetics
  • Oils, Volatile*
  • Quantitative Trait Loci

Substances

  • Oils, Volatile
  • Aldehydes

Grants and funding

This research was funded by the Association Nationale de la Recherche et de la Technologie (ANRT), grant number 2019/0084 for Vincent Ferrer’s Ph.D.