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

Abstract

27Estimation of allele dosage in autopolyploids is challenging and current methods 28 often result in the misclassification of genotypes. Here we propose and compare the use of 29 next generation sequencing read depth as continuous parameterization for autotetraploid 30 genomic prediction of breeding values, using blueberry (Vaccinium corybosum spp.) as a 31 model. Additionally, we investigated the influence of different sources of information to 32 build relationship matrices in phenotype prediction; no relationship, pedigree, and genomic 33 information, considering either diploid or tetraploid parameterizations. A real breeding 34 population composed of 1,847 individuals was phenotyped for eight yield and fruit quality 35 traits over two years. Analyses were based on extensive pedigree (since 1908) and high-36 density marker data (86K markers). Our results show that marker-based matrices can yield 37 significantly better prediction than pedigree for most of the traits, based on model fitting and 38 expected genetic gain. Continuous genotypic based models performed as well as the current 39 best models and presented a significantly better goodness-of-fit for all traits analyzed. This 40 approach also reduces the computational time required for marker calling and avoids 41 problems associated with misclassification of genotypic classes when assigning dosage in 42 polyploid species. Accuracies are encouraging for application of genomic selection (GS) for 43 blueberry breeding. Conservatively, GS could reduce the time for cultivar release by three 44 years. GS could increase the genetic gain per cycle by 86% on average when compared to 45 phenotypic selection, and 32% when compared with pedigree-based selection.46 47 48 Polyploidy events are not an exception in plants, as about 70% of Angiosperms and 53 95% of Pteridophytes underwent at least one polyploidization event (Soltis and Soltis 1999). 54 Polyploids are normally grouped into two categories, autopolyploids and allopolyploids, but 55 intermediate forms are also possible, such as segmental allopolyploids (Spoelhof et al. 2017). 56 Thresholds for polyploid classification have been controversial, but following the general 57 taxonomic definition, autopolyploids arise from within-species whole genome duplication, 58 and allopolyploids arise from whole genome duplication prior to or after an inter-specific 59 hybridization event (Soltis et al. 2007). 60 Because speciation via ploidy increase can generate new phenotypic variability, this 61 phenomenon is considered a powerful evolutionary source (Hieter and Griffiths 1999; Soltis 62 et al. 2016). Despite the important role of polyploidization in plant evolution, its effects on 63 inheritance of many agronomic traits and population genetics are still poorly understood 64 when compared with diploid species (Dufresne et al. 2014). This especially holds true for 65 autopolyploids. The complex nature of autopolyploid genetics is due to the presence of 66 genotypes with higher allele dosage than diploids, larger number ...

Making the most of all data: Combining non‐genotyped and genotyped potato individuals with HBLUP

“…Traits of great interest, such as tuber yield and quality, are polygenic and complex, and using MAS for individual genetic effects for these traits would not be practical for potato breeding programs (Slater et al., 2014a). While significant genetic gains have been achieved for complex traits in diploid crops from high throughput genotyping methods and advanced genetic and statistical analysis (Crossa et al., 2010; Daetwyler, Bansal, Bariana, Hayden, & Hayes, 2014; Heffner, Jannink, & Sorrells, 2011), genomic data application in autopolyploids is still developing (Bourke, Voorrips, Visser, & Maliepaard, 2018; de Bem Oliveira et al., 2019). Autopolyploid inheritance is complex due to the presence of genotypes with higher allele dosage, a higher number of genotypic classes, poor knowledge of meiotic behaviour and multivalent formation (de Bem Oliveira et al., 2019; Sharma et al., 2018; Slater et al., 2014b).…”

Sequencing depth and genotype quality: Accuracy and breeding operation considerations for genomic selection applications in autopolyploid crops

“…Oliveira et al (2019) showed that the relative advantage of including dosage information to PA is dependent on trait architecture. Our results confirm this and show that for simple traits diploidized data, especially when the genotypic data are directly called as diploid during variant calling e.g.…”

“…Additionally, we calculated the estimated rate of genetic gains from genomic selection per additive model with or without dosage for each trait according to Oliveira et al (2019) as: assuming L=5 for sweetpotato following the accelerated breeding scheme currently implemented ( Mwanga et al 2017 ), and L= 8 for potato.…”

Sequencing depth and genotype quality: accuracy and breeding operation considerations for genomic selection applications in autopolyploid crops

“…Additionally, we calculated the estimated rate of genetic gains from genomic selection per additive model with or without dosage for each trait according to Oliveira et al (2019) as:…”