Insights Into the Genetic Basis of Blueberry Fruit-Related Traits Using Diploid and Polyploid Models in a GWAS Context

Abstract

Polyploidization is an ancient and recurrent process in plant evolution, impacting the diversification of natural populations and plant breeding strategies. Polyploidization occurs in many important crops; however, its effects on inheritance of many agronomic traits are still poorly understood compared with diploid species. Higher levels of allelic dosage or more complex interactions between alleles could affect the phenotype expression. Hence, the present study aimed to dissect the genetic basis of fruit-related traits in autotetraploid blueberries and identify candidate genes affecting phenotypic variation. We performed a genome-wide association study (GWAS) assuming diploid and tetraploid inheritance, encompassing distinct models of gene action (additive, general, different orders of allelic interaction, and the corresponding diploidized models). A total of 1,575 southern highbush blueberry individuals from a breeding population of 117 full-sib families were genotyped using sequence capture and next-generation sequencing, and evaluated for eight fruit-related traits. For the diploid allele calling, 77,496 SNPs were detected; while 80,591 SNPs were obtained in tetraploid, with a high degree of overlap (95%) between them. A linear mixed model that accounted for population and family structure was used for the GWAS analyses. By modeling tetraploid genotypes, we detected 15 SNPs significantly associated with five fruit-related traits. Alternatively, seven significant SNPs were detected for only two traits using diploid genotypes, with two SNPs overlapping with the tetraploid scenario. Our results showed that the importance of tetraploid models varied by trait and that the use of diploid models has hindered the detection of SNP-trait associations and, consequently, the genetic architecture of some commercially important traits in autotetraploid species. Furthermore, 14 SNPs co-localized with candidate genes, five of which lead to non-synonymous amino acid changes. The potential functional significance of these SNPs is discussed.

Genomic prediction of autotetraploids; influence of relationship matrices, allele dosage, and continuous genotyping calls in the phenotype prediction

“…After filtering a total of 85,973 SNP were used in the GS analysis. Further information regarding population composition and genotyping approach were described in Ferrão et al (2018). The genotypes for the diploid calling were coded as 0 ( AA ), 1 ( AB ), or 2 ( BB ).…”

Association Mapping Considering Allele Dosage: An Example of Forage Traits in an Interspecific Segmental Allotetraploid Urochloa spp. Panel

“…Most of the genetic studies in polyploid species simplify the data to use diploid models inducing errors as under‐ or overestimating the real genetic control of important traits (Dufresne et al, 2014), as observed in the autotetraploid blueberry (Ferrão et al, 2018) and in the allotetraploid clover (Inostroza et al, 2018). However, Urochloa spp.…”

“…However, little is known about the consequences of using these models on the GWAS results compared with the use of adequate allele dosage, especially considering Urochloa spp. Ferrão et al (2018) performing GWAS analysis in autotetraploid blueberries ( Vaccinium corymbosum L.) verified that the importance of tetraploid models varies with traits and the use of diploid models has hindered the detection of single nucleotide polymorphism (SNP)–trait associations in this autotetraploid species. In turn, Inostroza et al (2018) only detected significant SNP–trait association in the allotetraploid clover ( Trifolium repens L.) when GWAS analyses were performed with tetraploid genetic models, showing the importance of considering the correct allele dosage.…”

High-Resolution Linkage Map and QTL Analyses for Machine Harvest Traits in Autotetraploid Blueberry

“…Firmness is a genetically controlled trait that has long been among the focus of blueberry breeding programs (Edwards et al, 1974; Cappai et al, 2018; Cellon et al, 2018; Ferrão et al, 2018). It is also a desirable trait across the whole market chain: for growers, less fruit is discarded due to physical damage; for retailers, firmer berries have a longer shelf life; and for consumers, firm texture positively correlates to liking (Mehra et al, 2013; Olmstead and Finn, 2014; Yu et al, 2014; Gilbert et al, 2015).…”