Bayesian QTL analyses using pedigreed families of an outcrossing species, with application to fruit firmness in apple

Abstract

Proof of concept of Bayesian integrated QTL analyses across pedigree-related families from breeding programs of an outbreeding species. Results include QTL confidence intervals, individuals' genotype probabilities and genomic breeding values. Bayesian QTL linkage mapping approaches offer the flexibility to study multiple full sib families with known pedigrees simultaneously. Such a joint analysis increases the probability of detecting these quantitative trait loci (QTL) and provide insight of the magnitude of QTL across different genetic backgrounds. Here, we present an improved Bayesian multi-QTL pedigree-based approach on an outcrossing species using progenies with different (complex) genetic relationships. Different modeling assumptions were studied in the QTL analyses, i.e., the a priori expected number of QTL varied and polygenic effects were considered. The inferences include number of QTL, additive QTL effect sizes and supporting credible intervals, posterior probabilities of QTL genotypes for all individuals in the dataset, and QTL-based as well as genome-wide breeding values. All these features have been implemented in the FlexQTL(™) software. We analyzed fruit firmness in a large apple dataset that comprised 1,347 individuals forming 27 full sib families and their known ancestral pedigrees, with genotypes for 87 SSR markers on 17 chromosomes. We report strong or positive evidence for 14 QTL for fruit firmness on eight chromosomes, validating our approach as several of these QTL were reported previously, though dispersed over a series of studies based on single mapping populations. Interpretation of linked QTL was possible via individuals' QTL genotypes. The correlation between the genomic breeding values and phenotypes was on average 90 %, but varied with the number of detected QTL in a family. The detailed posterior knowledge on QTL of potential parents is critical for the efficiency of marker-assisted breeding.

QTL mapping of pomological traits in peach and related species breeding germplasm

“…Through the application of FlexQTL TM , the eight traits considered in this study were analyzed individually and on a year to year basis through the implementation of the linear model described by Bink et al (2014). Such a linear model consists of an intercept, which is the phenotypic mean of the trait being analyzed, a design matrix and a vector of genetic group effects, a design matrix of a vector of regressions on the QTL covariates and a model residual error.…”

“…Such a linear model consists of an intercept, which is the phenotypic mean of the trait being analyzed, a design matrix and a vector of genetic group effects, a design matrix of a vector of regressions on the QTL covariates and a model residual error. This model was evaluated through Bayesian modeling following the Markov chain Monte Carlo (MCMC) algorithms described by Bink et al (2014). The number of QTL was considered a random variable, and the assignation of priors per vector and variances was done as described by Bink et al (2014).…”

“…PBA is facilitated through the dedicated software FlexQTL TM , which uses the IBD concept to track QTL and marker alleles and uses a Bayesian framework to map QTLs as well as estimate the genomic breeding values of germplasm generated from single and reciprocal test crosses to complex pedigree structures (van de Weg et al 2005;Bink et al 2008Bink et al , 2014. Results provide insights into each individual's genetic merit, including its capability to pass on additive genetic effects influencing a given trait.…”

Two QTL characterized for soft scald and soggy breakdown in apple (Malus × domestica) through pedigree-based analysis of a large population of interconnected families

“…PBA has been made a more attractive approach in apple through guidelines on the composition of the study germplasm (Peace et al 2014), high throughput genomewide genotyping capabilities through SNP arrays (Chagné et al 2012;Bianco et al 2014Bianco et al , 2016, the availability of sets of pedigreed full-sib families (Peace et al 2014), and standardized phenotyping procedures for some major traits (Evans et al 2011a). This approach has been increasingly utilized in a variety of Rosaceous fruit species, including strawberry (Whitaker 2011;Roach et al 2016;Mangandi et al 2017), peach (Fresnedo-Ramírez et al 2015Mora et al 2017), cherry (Rosyara et al 2013;Stegmeir et al 2014;Sandefur et al 2016), and apple (Schmitz et al 2013;Bink et al 2014;Guan et al 2015, Allard et al 2016Durand et al 2017).…”

“…The Bayesian statistics and PBA methodology used in FlexQTL™, as described in Bink et al (2002Bink et al ( , 2008Bink et al ( , 2012 built from approaches and procedures developed in Sillanpää and Arjas (1999). The implementation of FlexQTL™ in QTL analyses has been described in detail in Bink et al (2014) in a proof of concept paper. Each separate QTL analysis had Markov chain Monte Carlo simulation lengths of 2.5*10 5 , with every 250th sample stored for a total of 1000 samples for use in posterior QTL inferences.…”