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Article|20 Jan 2022|OPEN
Multiple haplotype-based analyses provide genetic and evolutionary insights into tomato fruit weight and composition
Jiantao Zhao1,2 , Christopher Sauvage1,3 , Frédérique Bitton1 , Mathilde Causse,1 ,
1INRA, UR1052, Centre de Recherche PACA, Génétique et Amélioration des Fruits et Légumes, Domaine Saint Maurice, 67 Allée des Chênes CS 60094 – 84140, Montfavet Cedex, France
2Boyce Thompson Institute for Plant Research, Cornell University, 533 Tower Road, Ithaca, NY 14853-1801, USA
3Syngenta SAS France, 1228 Chemin de l’Hobit, Saint Sauveur 31790, France
*Corresponding author. E-mail: mathilde.causse@inrae.fr

Horticulture Research 9,
Article number: uhab009 (2022)
doi: https://doi.org/10.1093/hr/uhab009
Views: 21

Received: 17 Jun 2021
Revised: 12 Oct 2021
Accepted: 15 Oct 2021
Published online: 20 Jan 2022

Abstract

Improving fruit quality traits such as metabolic composition remains a challenge for tomato breeders. To better understand the genetic architecture of these traits and decipher the demographic history of the loci controlling tomato quality traits, we applied an innovative approach using multiple haplotype-based analyses, aiming to test the potentials of haplotype based study in association and genomic prediction studies. We performed and compared haplotype vs SNP-based associations (hapQTL) with multi-locus mixed model (MLMM), focusing on tomato fruit weight and metabolite contents (i.e. sugars, organic acids and amino acids). Using a panel of 163 tomato accessions genotyped with 5995 SNPs, we detected a total of 784 haplotype blocks, with an average size of haplotype blocks ~58 kb. A total of 108 significant associations for 26 traits were detected thanks to Haplotype/SNP-based Bayes models. Haplotype-based Bayes model (97 associations) outperformed SNP-based Bayes model (50 associations) and MLMM (53 associations) in identifying marker-trait associations as well as in genomic prediction (especially for those traits with moderate to low heritability). To decipher the demographic history, we identified 24 positive selective sweeps using the integrated haplotype score (iHS). Most of the significant associations for tomato quality traits were located within selective sweeps (54.63% and 71.7% in hapQTL and MLMM models, respectively). Promising candidate genes were identified controlling tomato fruit weight and metabolite contents. We thus demonstrated the benefits of using haplotypes for evolutionary and genetic studies, providing novel insights into tomato quality improvement and breeding history.